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Repository: Shenyi-Z/ToCa
Branch: main
Commit: e84096ffd85a
Files: 713
Total size: 6.6 MB
Directory structure:
gitextract_nz69m5ai/
├── COCO_caption_prompts_30k.txt
├── DiT-ToCa/
│ ├── cache_functions/
│ │ ├── __init__.py
│ │ ├── attention.py
│ │ ├── cache_cutfresh.py
│ │ ├── cache_init.py
│ │ ├── cal_type.py
│ │ ├── force_init.py
│ │ ├── force_scheduler.py
│ │ ├── fresh_ratio_scheduler.py
│ │ ├── global_force_fresh.py
│ │ ├── score_evaluate.py
│ │ ├── scores.py
│ │ ├── token_merge.py
│ │ └── update_cache.py
│ ├── diffusion/
│ │ ├── __init__.py
│ │ ├── diffusion_utils.py
│ │ ├── gaussian_diffusion.py
│ │ ├── respace.py
│ │ └── timestep_sampler.py
│ ├── download.py
│ ├── environment-dit.yml
│ ├── models.py
│ ├── sample.py
│ ├── sample_ddp.py
│ └── train.py
├── DrawBench200.txt
├── LICENSE
├── Open-Sora/
│ ├── Dockerfile
│ ├── LICENSE
│ ├── README.md
│ ├── assets/
│ │ └── texts/
│ │ ├── VBench/
│ │ │ ├── all_category.txt
│ │ │ ├── all_dimension.txt
│ │ │ ├── all_i2v.txt
│ │ │ ├── prompts_per_category/
│ │ │ │ ├── animal.txt
│ │ │ │ ├── architecture.txt
│ │ │ │ ├── food.txt
│ │ │ │ ├── human.txt
│ │ │ │ ├── lifestyle.txt
│ │ │ │ ├── plant.txt
│ │ │ │ ├── scenery.txt
│ │ │ │ └── vehicles.txt
│ │ │ └── prompts_per_dimension/
│ │ │ ├── appearance_style.txt
│ │ │ ├── color.txt
│ │ │ ├── human_action.txt
│ │ │ ├── multiple_objects.txt
│ │ │ ├── object_class.txt
│ │ │ ├── overall_consistency.txt
│ │ │ ├── scene.txt
│ │ │ ├── spatial_relationship.txt
│ │ │ ├── subject_consistency.txt
│ │ │ ├── temporal_flickering.txt
│ │ │ └── temporal_style.txt
│ │ ├── imagenet_id.txt
│ │ ├── imagenet_labels.txt
│ │ ├── rand_types.txt
│ │ ├── t2i_samples.txt
│ │ ├── t2i_sigma.txt
│ │ ├── t2v_car.txt
│ │ ├── t2v_latte.txt
│ │ ├── t2v_pllava.txt
│ │ ├── t2v_ref.txt
│ │ ├── t2v_samples.txt
│ │ ├── t2v_short.txt
│ │ ├── t2v_sora.txt
│ │ ├── ucf101_id.txt
│ │ └── ucf101_labels.txt
│ ├── build/
│ │ └── lib/
│ │ ├── opensora/
│ │ │ ├── acceleration/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── checkpoint.py
│ │ │ │ ├── communications.py
│ │ │ │ ├── parallel_states.py
│ │ │ │ ├── plugin.py
│ │ │ │ └── shardformer/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── modeling/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── t5.py
│ │ │ │ └── policy/
│ │ │ │ ├── __init__.py
│ │ │ │ └── t5_encoder.py
│ │ │ ├── datasets/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── aspect.py
│ │ │ │ ├── bucket.py
│ │ │ │ ├── dataloader.py
│ │ │ │ ├── datasets.py
│ │ │ │ ├── read_video.py
│ │ │ │ ├── sampler.py
│ │ │ │ ├── utils.py
│ │ │ │ └── video_transforms.py
│ │ │ └── models/
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── dit/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dit.py
│ │ │ ├── latte/
│ │ │ │ ├── __init__.py
│ │ │ │ └── latte.py
│ │ │ ├── layers/
│ │ │ │ ├── __init__.py
│ │ │ │ └── blocks.py
│ │ │ ├── pixart/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── pixart.py
│ │ │ │ └── pixart_sigma.py
│ │ │ ├── stdit/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── stdit.py
│ │ │ │ ├── stdit2.py
│ │ │ │ ├── stdit3 copy.py
│ │ │ │ └── stdit3.py
│ │ │ └── text_encoder/
│ │ │ ├── __init__.py
│ │ │ ├── classes.py
│ │ │ ├── clip.py
│ │ │ └── t5.py
│ │ ├── tools/
│ │ │ ├── caption/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── acceleration/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── llava/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── policies/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── llama.py
│ │ │ │ │ └── mistral.py
│ │ │ │ ├── camera_motion/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── camera_motion.py
│ │ │ │ │ ├── detect.py
│ │ │ │ │ ├── utils.py
│ │ │ │ │ └── visualizer.py
│ │ │ │ ├── camera_motion_detect.py
│ │ │ │ ├── caption_gpt4.py
│ │ │ │ ├── caption_llama3.py
│ │ │ │ ├── caption_llava.py
│ │ │ │ └── utils.py
│ │ │ ├── datasets/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── analyze.py
│ │ │ │ ├── convert.py
│ │ │ │ ├── datautil.py
│ │ │ │ ├── filter_panda10m.py
│ │ │ │ ├── split.py
│ │ │ │ ├── transform.py
│ │ │ │ └── utils.py
│ │ │ ├── frame_interpolation/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── interpolation.py
│ │ │ │ ├── networks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── amt_g.py
│ │ │ │ │ └── blocks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── feat_enc.py
│ │ │ │ │ ├── ifrnet.py
│ │ │ │ │ ├── multi_flow.py
│ │ │ │ │ └── raft.py
│ │ │ │ └── utils/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── dist_utils.py
│ │ │ │ ├── flow_utils.py
│ │ │ │ └── utils.py
│ │ │ ├── scene_cut/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── convert_id_to_path.py
│ │ │ │ ├── cut.py
│ │ │ │ └── scene_detect.py
│ │ │ └── scoring/
│ │ │ ├── aesthetic/
│ │ │ │ ├── __init__.py
│ │ │ │ └── inference.py
│ │ │ └── matching/
│ │ │ ├── __init__.py
│ │ │ └── inference.py
│ │ ├── vbench/
│ │ │ ├── __init__.py
│ │ │ ├── aesthetic_quality.py
│ │ │ ├── appearance_style.py
│ │ │ ├── background_consistency.py
│ │ │ ├── cli/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── evaluate.py
│ │ │ │ ├── static_filter.py
│ │ │ │ └── vbench.py
│ │ │ ├── color.py
│ │ │ ├── dynamic_degree.py
│ │ │ ├── human_action.py
│ │ │ ├── imaging_quality.py
│ │ │ ├── motion_smoothness.py
│ │ │ ├── multiple_objects.py
│ │ │ ├── object_class.py
│ │ │ ├── overall_consistency.py
│ │ │ ├── scene.py
│ │ │ ├── spatial_relationship.py
│ │ │ ├── subject_consistency.py
│ │ │ ├── temporal_flickering.py
│ │ │ ├── temporal_style.py
│ │ │ ├── third_pary/
│ │ │ │ ├── 0.txt
│ │ │ │ ├── RAFT/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── core/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── corr.py
│ │ │ │ │ ├── datasets.py
│ │ │ │ │ ├── extractor.py
│ │ │ │ │ ├── raft.py
│ │ │ │ │ ├── update.py
│ │ │ │ │ └── utils_core/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── augmentor.py
│ │ │ │ │ ├── flow_viz.py
│ │ │ │ │ ├── frame_utils.py
│ │ │ │ │ └── utils.py
│ │ │ │ ├── ViCLIP/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── simple_tokenizer.py
│ │ │ │ │ ├── viclip.py
│ │ │ │ │ ├── viclip_text.py
│ │ │ │ │ └── viclip_vision.py
│ │ │ │ ├── __init__.py
│ │ │ │ ├── amt/
│ │ │ │ │ ├── benchmarks/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── adobe240.py
│ │ │ │ │ │ ├── gopro.py
│ │ │ │ │ │ ├── snu_film.py
│ │ │ │ │ │ ├── speed_parameters.py
│ │ │ │ │ │ ├── ucf101.py
│ │ │ │ │ │ ├── vimeo90k.py
│ │ │ │ │ │ ├── vimeo90k_tta.py
│ │ │ │ │ │ └── xiph.py
│ │ │ │ │ ├── datasets/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── adobe_datasets.py
│ │ │ │ │ │ ├── gopro_datasets.py
│ │ │ │ │ │ └── vimeo_datasets.py
│ │ │ │ │ ├── flow_generation/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── gen_flow.py
│ │ │ │ │ │ └── liteflownet/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── run.py
│ │ │ │ │ ├── losses/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── loss.py
│ │ │ │ │ ├── metrics/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── psnr_ssim.py
│ │ │ │ │ └── networks/
│ │ │ │ │ ├── AMT-G.py
│ │ │ │ │ ├── AMT-L.py
│ │ │ │ │ ├── AMT-S.py
│ │ │ │ │ └── blocks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── feat_enc.py
│ │ │ │ │ ├── ifrnet.py
│ │ │ │ │ ├── multi_flow.py
│ │ │ │ │ └── raft.py
│ │ │ │ ├── grit_model.py
│ │ │ │ ├── grit_src/
│ │ │ │ │ └── centernet2/
│ │ │ │ │ └── centernet/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── config.py
│ │ │ │ │ └── modeling/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── backbone/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── bifpn.py
│ │ │ │ │ │ ├── bifpn_fcos.py
│ │ │ │ │ │ ├── dla.py
│ │ │ │ │ │ ├── dlafpn.py
│ │ │ │ │ │ ├── fpn_p5.py
│ │ │ │ │ │ └── res2net.py
│ │ │ │ │ ├── debug.py
│ │ │ │ │ ├── dense_heads/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── centernet.py
│ │ │ │ │ │ ├── centernet_head.py
│ │ │ │ │ │ └── utils.py
│ │ │ │ │ ├── layers/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── deform_conv.py
│ │ │ │ │ │ ├── heatmap_focal_loss.py
│ │ │ │ │ │ ├── iou_loss.py
│ │ │ │ │ │ └── ml_nms.py
│ │ │ │ │ ├── meta_arch/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── centernet_detector.py
│ │ │ │ │ └── roi_heads/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── custom_fast_rcnn.py
│ │ │ │ │ ├── custom_roi_heads.py
│ │ │ │ │ └── fed_loss.py
│ │ │ │ ├── tag2Text/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── med.py
│ │ │ │ │ ├── swin_transformer.py
│ │ │ │ │ ├── tag2text.py
│ │ │ │ │ ├── tag_class.py
│ │ │ │ │ └── vit.py
│ │ │ │ └── umt/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── datasets/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── build.py
│ │ │ │ │ ├── kinetics.py
│ │ │ │ │ ├── kinetics_sparse.py
│ │ │ │ │ ├── mae.py
│ │ │ │ │ ├── masking_generator.py
│ │ │ │ │ ├── mixup.py
│ │ │ │ │ ├── rand_augment.py
│ │ │ │ │ ├── random_erasing.py
│ │ │ │ │ ├── ssv2.py
│ │ │ │ │ ├── transforms.py
│ │ │ │ │ ├── video_transforms.py
│ │ │ │ │ └── volume_transforms.py
│ │ │ │ ├── functional.py
│ │ │ │ └── models/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── clip.py
│ │ │ │ ├── modeling_finetune.py
│ │ │ │ ├── modeling_pretrain.py
│ │ │ │ └── modeling_pretrain_umt.py
│ │ │ └── utils.py
│ │ └── vbench2_beta_i2v/
│ │ ├── __init__.py
│ │ ├── camera_motion.py
│ │ ├── crop_to_diff_ratio.py
│ │ ├── i2v_background.py
│ │ ├── i2v_subject.py
│ │ └── utils.py
│ ├── configs/
│ │ ├── dit/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256.py
│ │ │ │ ├── 1x256x256-class.py
│ │ │ │ └── 1x256x256.py
│ │ │ └── train/
│ │ │ ├── 16x256x256.py
│ │ │ └── 1x256x256.py
│ │ ├── latte/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256-class.py
│ │ │ │ └── 16x256x256.py
│ │ │ └── train/
│ │ │ └── 16x256x256.py
│ │ ├── opensora/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256.py
│ │ │ │ ├── 16x512x512-rflow.py
│ │ │ │ ├── 16x512x512.py
│ │ │ │ └── 64x512x512.py
│ │ │ └── train/
│ │ │ ├── 16x256x256-mask.py
│ │ │ ├── 16x256x256-spee-rflow.py
│ │ │ ├── 16x256x256-spee.py
│ │ │ ├── 16x256x256.py
│ │ │ ├── 16x512x512.py
│ │ │ ├── 360x512x512.py
│ │ │ ├── 64x512x512-sp.py
│ │ │ └── 64x512x512.py
│ │ ├── opensora-v1-1/
│ │ │ ├── inference/
│ │ │ │ ├── sample-ref.py
│ │ │ │ └── sample.py
│ │ │ └── train/
│ │ │ ├── benchmark.py
│ │ │ ├── image.py
│ │ │ ├── image_rflow.py
│ │ │ ├── stage1.py
│ │ │ ├── stage2.py
│ │ │ ├── stage3.py
│ │ │ └── video.py
│ │ └── opensora-v1-2/
│ │ └── inference/
│ │ └── sample.py
│ ├── docs/
│ │ ├── acceleration.md
│ │ ├── commands.md
│ │ ├── config.md
│ │ ├── data_processing.md
│ │ ├── datasets.md
│ │ ├── installation.md
│ │ ├── report_01.md
│ │ ├── report_02.md
│ │ ├── report_03.md
│ │ ├── structure.md
│ │ ├── vae.md
│ │ └── zh_CN/
│ │ ├── README.md
│ │ ├── READMEv1.1.md
│ │ ├── acceleration.md
│ │ ├── commands.md
│ │ ├── datasets.md
│ │ ├── report_v1.md
│ │ ├── report_v2.md
│ │ ├── report_v3.md
│ │ ├── structure.md
│ │ └── vae.md
│ ├── environment-opensora.yml
│ ├── eval/
│ │ ├── README.md
│ │ ├── human_eval/
│ │ │ ├── generate.sh
│ │ │ └── launch.sh
│ │ ├── loss/
│ │ │ ├── eval_loss.py
│ │ │ ├── launch.sh
│ │ │ └── tabulate_rl_loss.py
│ │ ├── sample.sh
│ │ ├── vae/
│ │ │ ├── cal_flolpips.py
│ │ │ ├── cal_lpips.py
│ │ │ ├── cal_psnr.py
│ │ │ ├── cal_ssim.py
│ │ │ ├── eval_common_metric.py
│ │ │ ├── flolpips/
│ │ │ │ ├── correlation/
│ │ │ │ │ └── correlation.py
│ │ │ │ ├── flolpips.py
│ │ │ │ ├── pretrained_networks.py
│ │ │ │ ├── pwcnet.py
│ │ │ │ └── utils.py
│ │ │ └── script/
│ │ │ └── eval.sh
│ │ ├── vbench/
│ │ │ ├── VBench_full_info.json
│ │ │ ├── calc_vbench.py
│ │ │ ├── launch.sh
│ │ │ ├── launch_calc.sh
│ │ │ └── tabulate_vbench_scores.py
│ │ └── vbench_i2v/
│ │ ├── calc_vbench_i2v.py
│ │ ├── json_to_txt.py
│ │ ├── launch.sh
│ │ └── launch_calc.sh
│ ├── gradio/
│ │ ├── README.md
│ │ ├── app.py
│ │ └── requirements.txt
│ ├── notebooks/
│ │ ├── inference.ipynb
│ │ └── launch.ipynb
│ ├── opensora/
│ │ ├── __init__.py
│ │ ├── acceleration/
│ │ │ ├── __init__.py
│ │ │ ├── checkpoint.py
│ │ │ ├── communications.py
│ │ │ ├── parallel_states.py
│ │ │ ├── plugin.py
│ │ │ └── shardformer/
│ │ │ ├── __init__.py
│ │ │ ├── modeling/
│ │ │ │ ├── __init__.py
│ │ │ │ └── t5.py
│ │ │ └── policy/
│ │ │ ├── __init__.py
│ │ │ └── t5_encoder.py
│ │ ├── datasets/
│ │ │ ├── __init__.py
│ │ │ ├── aspect.py
│ │ │ ├── bucket.py
│ │ │ ├── dataloader.py
│ │ │ ├── datasets.py
│ │ │ ├── read_video.py
│ │ │ ├── sampler.py
│ │ │ ├── utils.py
│ │ │ └── video_transforms.py
│ │ ├── models/
│ │ │ ├── __init__.py
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── dit/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dit.py
│ │ │ ├── latte/
│ │ │ │ ├── __init__.py
│ │ │ │ └── latte.py
│ │ │ ├── layers/
│ │ │ │ ├── __init__.py
│ │ │ │ └── blocks.py
│ │ │ ├── pixart/
│ │ │ │ └── pixart.py
│ │ │ ├── stdit/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── stdit.py
│ │ │ │ ├── stdit2.py
│ │ │ │ └── stdit3.py
│ │ │ ├── text_encoder/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── classes.py
│ │ │ │ ├── clip.py
│ │ │ │ └── t5.py
│ │ │ └── vae/
│ │ │ ├── __init__.py
│ │ │ ├── discriminator.py
│ │ │ ├── losses.py
│ │ │ ├── lpips.py
│ │ │ ├── utils.py
│ │ │ ├── vae.py
│ │ │ ├── vae_temporal.py
│ │ │ └── video_sdxl/
│ │ │ └── blocks.py
│ │ ├── registry.py
│ │ ├── schedulers/
│ │ │ ├── __init__.py
│ │ │ ├── dpms/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dpm_solver.py
│ │ │ ├── iddpm/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── diffusion_utils.py
│ │ │ │ ├── gaussian_diffusion.py
│ │ │ │ ├── respace.py
│ │ │ │ ├── speed.py
│ │ │ │ └── timestep_sampler.py
│ │ │ └── rf/
│ │ │ ├── __init__.py
│ │ │ └── rectified_flow.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── ckpt_utils.py
│ │ ├── config_utils.py
│ │ ├── inference_utils.py
│ │ ├── lr_scheduler.py
│ │ ├── misc.py
│ │ └── train_utils.py
│ ├── opensora.egg-info/
│ │ ├── PKG-INFO
│ │ ├── SOURCES.txt
│ │ ├── dependency_links.txt
│ │ ├── requires.txt
│ │ └── top_level.txt
│ ├── pyproject.toml
│ ├── requirements/
│ │ ├── requirements-cu121.txt
│ │ ├── requirements-data.txt
│ │ ├── requirements-eval.txt
│ │ ├── requirements-pllava.txt
│ │ ├── requirements-vae.txt
│ │ └── requirements.txt
│ ├── scripts/
│ │ ├── inference.py
│ │ ├── inference_vae.py
│ │ └── misc/
│ │ ├── extract_feat.py
│ │ └── launch_extract_feat.sh
│ ├── setup.py
│ ├── tests/
│ │ ├── test_attn.py
│ │ └── test_lr_scheduler.py
│ └── tools/
│ ├── __init__.py
│ ├── caption/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── acceleration/
│ │ │ ├── __init__.py
│ │ │ └── llava/
│ │ │ ├── __init__.py
│ │ │ └── policies/
│ │ │ ├── __init__.py
│ │ │ ├── llama.py
│ │ │ └── mistral.py
│ │ ├── camera_motion/
│ │ │ ├── __init__.py
│ │ │ ├── camera_motion.py
│ │ │ ├── detect.py
│ │ │ ├── requirements.txt
│ │ │ ├── utils.py
│ │ │ └── visualizer.py
│ │ ├── camera_motion_detect.py
│ │ ├── caption_gpt4.py
│ │ ├── caption_llama3.py
│ │ ├── caption_llava.py
│ │ ├── pllava_dir/
│ │ │ └── caption_pllava.py
│ │ └── utils.py
│ ├── datasets/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── analyze.py
│ │ ├── convert.py
│ │ ├── datautil.py
│ │ ├── filter_panda10m.py
│ │ ├── split.py
│ │ ├── transform.py
│ │ └── utils.py
│ ├── frame_interpolation/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── interpolation.py
│ │ ├── networks/
│ │ │ ├── __init__.py
│ │ │ ├── amt_g.py
│ │ │ └── blocks/
│ │ │ ├── __init__.py
│ │ │ ├── feat_enc.py
│ │ │ ├── ifrnet.py
│ │ │ ├── multi_flow.py
│ │ │ └── raft.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── dist_utils.py
│ │ ├── flow_utils.py
│ │ └── utils.py
│ ├── scene_cut/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── convert_id_to_path.py
│ │ ├── cut.py
│ │ └── scene_detect.py
│ └── scoring/
│ ├── README.md
│ ├── __init__.py
│ ├── aesthetic/
│ │ ├── __init__.py
│ │ └── inference.py
│ ├── matching/
│ │ ├── __init__.py
│ │ └── inference.py
│ ├── ocr/
│ │ ├── __init__.py
│ │ ├── dbnetpp.py
│ │ └── inference.py
│ └── optical_flow/
│ ├── __init__.py
│ ├── inference.py
│ └── unimatch/
│ ├── __init__.py
│ ├── attention.py
│ ├── backbone.py
│ ├── geometry.py
│ ├── matching.py
│ ├── position.py
│ ├── reg_refine.py
│ ├── transformer.py
│ ├── trident_conv.py
│ ├── unimatch.py
│ └── utils.py
├── PixArt-alpha-ToCa/
│ ├── Dockerfile
│ ├── README(PixArt-alpha).md
│ ├── app/
│ │ ├── app.py
│ │ ├── app_512.py
│ │ ├── app_controlnet.py
│ │ ├── app_lcm.py
│ │ ├── style.css
│ │ └── style_controlnet.css
│ ├── asset/
│ │ ├── docs/
│ │ │ ├── pixart-dreambooth.md
│ │ │ ├── pixart.md
│ │ │ ├── pixart_comfyui.md
│ │ │ ├── pixart_controlnet.md
│ │ │ ├── pixart_inpaint.md
│ │ │ ├── pixart_lcm.md
│ │ │ └── sasolver.md
│ │ ├── examples.py
│ │ └── samples.txt
│ ├── configs/
│ │ ├── PixArt_xl2_internal.py
│ │ ├── PixArt_xl2_sam.py
│ │ ├── pixart_app_config/
│ │ │ ├── PixArt_xl2_img1024_controlHed.py
│ │ │ ├── PixArt_xl2_img1024_dreambooth.py
│ │ │ └── PixArt_xl2_img512_controlHed.py
│ │ └── pixart_config/
│ │ ├── PixArt_xl2_img1024_internal.py
│ │ ├── PixArt_xl2_img1024_internalms.py
│ │ ├── PixArt_xl2_img1024_lcm.py
│ │ ├── PixArt_xl2_img256_SAM.py
│ │ ├── PixArt_xl2_img256_internal.py
│ │ ├── PixArt_xl2_img512_internal.py
│ │ └── PixArt_xl2_img512_internalms.py
│ ├── diffusion/
│ │ ├── __init__.py
│ │ ├── data/
│ │ │ ├── __init__.py
│ │ │ ├── builder.py
│ │ │ ├── datasets/
│ │ │ │ ├── Dreambooth.py
│ │ │ │ ├── InternalData.py
│ │ │ │ ├── InternalData_ms.py
│ │ │ │ ├── SA.py
│ │ │ │ ├── __init__.py
│ │ │ │ ├── pixart_control.py
│ │ │ │ └── utils.py
│ │ │ └── transforms.py
│ │ ├── dpm_solver.py
│ │ ├── iddpm.py
│ │ ├── lcm_scheduler.py
│ │ ├── model/
│ │ │ ├── __init__.py
│ │ │ ├── builder.py
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── diffusion_utils.py
│ │ │ ├── dpm_solver.py
│ │ │ ├── edm_sample.py
│ │ │ ├── gaussian_diffusion.py
│ │ │ ├── hed.py
│ │ │ ├── llava/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── llava_mpt.py
│ │ │ │ └── mpt/
│ │ │ │ ├── attention.py
│ │ │ │ ├── blocks.py
│ │ │ │ ├── configuration_mpt.py
│ │ │ │ ├── modeling_mpt.py
│ │ │ │ ├── norm.py
│ │ │ │ └── param_init_fns.py
│ │ │ ├── nets/
│ │ │ │ ├── PixArt.py
│ │ │ │ ├── PixArtMS.py
│ │ │ │ ├── PixArt_blocks.py
│ │ │ │ ├── __init__.py
│ │ │ │ └── pixart_controlnet.py
│ │ │ ├── respace.py
│ │ │ ├── sa_solver.py
│ │ │ ├── t5.py
│ │ │ ├── timestep_sampler.py
│ │ │ └── utils.py
│ │ ├── sa_sampler.py
│ │ ├── sa_solver_diffusers.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── checkpoint.py
│ │ ├── data_sampler.py
│ │ ├── dist_utils.py
│ │ ├── logger.py
│ │ ├── lr_scheduler.py
│ │ ├── misc.py
│ │ └── optimizer.py
│ ├── docker-compose.yml
│ ├── docker-entrypoint.sh
│ ├── docker-readme.md
│ ├── environment-pixart.yml
│ ├── environment.yml
│ ├── notebooks/
│ │ ├── PixArt_xl2_img512_internal_for_pokemon_sample_training.py
│ │ ├── convert-checkpoint-to-diffusers.ipynb
│ │ ├── infer.ipynb
│ │ └── train.ipynb
│ ├── requirements.txt
│ ├── scripts/
│ │ ├── infer_pixart_8_bits.py
│ │ ├── inference.py
│ │ ├── inference_ddp.py
│ │ ├── inference_lcm.py
│ │ ├── interface.py
│ │ ├── interface_controlnet.py
│ │ ├── pipeline_pixart_inpaint.py
│ │ └── pipeline_pixart_reference.py
│ ├── timing_analysis.py
│ ├── timing_info.json
│ ├── tools/
│ │ ├── VLM_caption_lightning.py
│ │ ├── convert_pixart_alpha_to_diffusers.py
│ │ ├── download.py
│ │ └── extract_features.py
│ ├── train.sh
│ ├── train_latents.py
│ └── train_scripts/
│ ├── train.py
│ ├── train_controlnet.py
│ ├── train_diffusers.py
│ ├── train_dreambooth.py
│ ├── train_pixart_lcm.py
│ ├── train_pixart_lcm_lora.py
│ └── train_pixart_lora_hf.py
├── PixArt-alpha-ToCa-tools/
│ └── clip_score.py
├── README.md
└── flux-ToCa/
├── .gitignore
├── LICENSE
├── README.md
├── demo_gr.py
├── demo_st.py
├── demo_st_fill.py
├── docs/
│ ├── fill.md
│ ├── image-variation.md
│ ├── structural-conditioning.md
│ └── text-to-image.md
├── model_cards/
│ ├── FLUX.1-dev.md
│ └── FLUX.1-schnell.md
├── model_licenses/
│ ├── LICENSE-FLUX1-dev
│ └── LICENSE-FLUX1-schnell
├── pyproject.toml
├── setup.py
└── src/
├── flux/
│ ├── __init__.py
│ ├── __main__.py
│ ├── _version.py
│ ├── api.py
│ ├── cli.py
│ ├── cli_control.py
│ ├── cli_fill.py
│ ├── cli_redux.py
│ ├── ideas/
│ │ ├── __init__.py
│ │ └── cache_denoise.py
│ ├── math.py
│ ├── model.py
│ ├── modules/
│ │ ├── autoencoder.py
│ │ ├── cache_functions/
│ │ │ ├── __init__.py
│ │ │ ├── attention.py
│ │ │ ├── cache_cutfresh.py
│ │ │ ├── cache_init.py
│ │ │ ├── cal_type.py
│ │ │ ├── force_init.py
│ │ │ ├── force_scheduler.py
│ │ │ ├── fresh_ratio_scheduler.py
│ │ │ ├── global_force_fresh.py
│ │ │ ├── score_evaluate.py
│ │ │ ├── scores.py
│ │ │ ├── support_set_selection.py
│ │ │ ├── token_merge.py
│ │ │ └── update_cache.py
│ │ ├── conditioner.py
│ │ ├── image_embedders.py
│ │ ├── layers.py
│ │ └── lora.py
│ ├── sampling.py
│ └── util.py
├── geneval_flux.py
└── sample.py
================================================
FILE CONTENTS
================================================
================================================
FILE: COCO_caption_prompts_30k.txt
================================================
A man about to return a serve with his tennis racket
A horse drawn carriage in a historic city.
Two gray fire hydrants sitting next to each other at a park.
A goat with horns is standing in a grassy field.
Several buses parked under a carport in a parking lot.
A bowl of soup with bread and a cup of coffee.
Three polar bears walk across a snowy field.
A glass mosaic vase filled with colorful flowers.
A bunch of apples in large trays on top of wooden crates.
A girl does a skateboard trick in the air.
A dog rests in the grass next to a fire hydrant.
A giraffe standing in the shade of a near by tree.
a plate of chilies with carrots and peas
A motorcycle parked in front of a red brick wall.
A tour bus stopped near a mountain while people gather nearby
A young girl and her dad play with kites in a park.
a man who appears to be herding sheep is closing two big fence doors
A man with glasses holding a glass of wine.
Group of skiers and different colored outfits on Ace Eastlynn.
A fortune note on a tea bag next to a bagel.
a man walks along the beach with a surfboard
The view of a clean toilet surrounded by marble tile.
a couple of people that are skateboarding down the road
A couple of cars are riding down the street from a window view.
A pet crate and a lot of tools and wires.
a man holding a kite and a dog in a field.
Four women with snowboards and gear are posing for a photograph near some snowy mounds.
The boy and his dog are posing for the camera.
The streets and the double decker bus are lit up in the night.
A small vase has a good luck plant in it.
a man riding on the back of a bike on dirt ground.
A group of people standing on the street.
The girl is riding her skateboard while using her cell phone.
A person doing a trick on a skateboard in the road
A lone zebra is walking in tall green grass.
A fuzzy image of some people on skate boards.
A man throws a frisbee to another man with two children.
a number of people in a body of water with a small boat
A complete train set, with tracks, buildings, and three piece train.
A couple of buses parked in front of a building.
A girl wearing a wet suit surfing in the ocean.
A picture of something and it appears like sustenance.
A man on a skateboard on a concrete lip.
A person walking next to a horse at a horse show.
A man with a beard looks pensive and wears a tie.
A blue vase filled with colorful flowers sitting on the ground.
A street name on a sign built into a curb.
Two zebras are behind a fence on green grass.
Young person on the street skateboarding wearing a helmet.
A toilet with a red seat in a small bathroom with red tiles.
Woman lying in an unmowed field with a frisbee.
Cars and a bus driving down a busy road.
A blurry image of some car lights on a dark night.
A smiling young man stands beneath an Obama street sign.
this is a train riding under a bridge
A group of giraffes eating bark off trees.
A horse is looking in the living room window of a farmhouse.
A man holding a frisbee on a beach next to another man.
a mixture of black and white sheep in a dried out field
A chocolate caked covered in strawberries sitting next to a knife.
Two people standing next to each other on a snow covered slope.
A young boy is flying a kite in the park.
Baseball pitcher in the process of pitching in a baseball game.
Two men are in the water on a boat.
A fighting plane turning sideways in a cloudy sky.
Several red roosters together in a small area.
A few small boats sail down a waterway.
A dog and a cat are looking at the snowy front yard through a glass door
A small child sitting on a shelf with teddy bears.
One giraffe standing behind a dead tree branch.
A bright green kite with a scary monster face flying high
A man holding a tennis racket and staring at the camera with pride.
This is a thing that is straightforward and plain.
A large open field with small bushes and trees, and a giraffe standing in the middle of the field.
Two women who are sitting at a table together.
A small dog eating out of a bowl on the floor.
a cow that is standing up eating a pan
Two people smile as they ride on an elephant.
some city workers work on a car crash
A giraffe walking past a tree on a dirt landscape.
A tow truck vehicle on a street in a city area.
Professional baseball player winding up to pitch the ball.
A dog is wearing a baseball hat over it's eyes.
A bearded man standing in front of bookcases
A horse drawn carriage traveling away fro ma very large cathedral.
a man is standing inside of a food truck
There is a stop sign with two road signs on top of it.
A girl looking a a beautiful view of the Rockies.
A very big high ceiling room with a yellow fan.
A man in an office chair looking at a laptop next to a glass of wine.
a brown desk a keyboard a computer and a monitor and speakers
A woman talking on her cell phone while walking.
An abandoned train with lots of graffiti painted on it.
a person bending down cutting another persons hair
A plane at an airport with a truck driving past
there are many men sitting at a small table
A girl looking inside a living cartoon refrigerator.
Two sheep are in a dirt outdoor enclosure.
People look on as a ball heads towards a batter.
Several glazed donuts are lined up on a tray.
A guy standing on a snowboard in the snow.
There is now image here to provide a caption for.
A man practicing baseball on a field.
A bedroom that has a large computer desk in it.
A close up of a pizza with spinach on it.
a living room with a couch a tv and a table
A man checks his cell phone as he walks to his car in the parking lot.
Several people on skis in the snow outside of a lodge.
A small pink beanie hat next to a cell phone.
A mother handing her son a piece of cake on a paper plate.
a man in a tuxedo sits at a table and uses a laptop
A young man holding a Nintendo Wii game controller.
A wrap of some sort on a plate with potatoes
A motor boat next to a beach and others in the background
A fruit bowl sitting on a table with bananas and apples.
Three people running around in grass playing Frisbee.
A person sits down to their meal of a sandwich on a croissant with a side of french fries.
A man is holding up an old cellphone
a couple of animals standing in a field
a cup on a table next to a tv
A large brick building with a tall tower containing a clock near the top
A figurine of a little boy riding a snow board in yellow pants.
A memorial set on a fence by the ocean with flowers and teddy bears.
A group of white sheep eating from blue bowls
A couple of kids laying in a bed with an umbrella.
A small table set with pastries and tea
A rainbow lorikeet parrot eats sun flower seeds.
A white plate topped with a sandwich and a salad.
A woman getting ready to hit a tennis ball.
A tennis player jumps into the air and swings his racket.
A mustached man is standing in front of a larger mustache.
Street signs showing the intersection of Eight Mile and Shadyside
A white desk has a computer, keyboard, globe and green phone.
A man with bandaged hands lying in bed.
A baseball player is trying to hit the ball.
a woman gets ready to pet a big horse
A herd of black cows grazing in a field.
A very pretty girl looking at her cell phone.
A man rides a bicycle across a wet intersection.
a man with a bat walks as other look on
Two zebras are running through some high grass.
A baseball stadium full of fans while two teams play ball.
there is two pictures of a female tennis player
There are flowers that are in a vase filled with rocks.
Fruit and vegetables are hanging in a metal basket.
A boat that is sitting in the water.
A living room with a couch, TV, and fireplace.
some people walking up a snowy hill with skis
A woman is eating spam off of a plate with a camera next to her.
A person that is playing in a tennis game.
A red truck in street next to wall and buildings.
A light with multiple bulbs is on a tall post.
Grey toned elephant head closeup with grass and hill background.
A man in striped shirt sitting on a fire hydrant.
A person on a skateboard and bike at a skate park.
a close up of a red tie and a white and blue shirt
A kid about to ride his skateboard down a pool.
LIVING ROOM WITH COUCH, TABLE, END TABLE, LAMP, PHONE, AND MIRROR
A happy boy is waiting outside with his suitcase.
Two men stand together using their cell phones.
A group of men cutting into a celebratory cake
A man eating a donut wrapped in tissue paper.
A bedroom with a bed with blue cover and blue curtains, and a pair of shoes on the wooden floor.
A penguin is standing and pecking at a teddy bear left in the snow.
Two brown bears sitting on top of a black and white checkered bed.
Two lambs with black heads look out from a gate.
This person is holding a cell phone while standing on the sidewalk.
There are a group of people snow boarding on the hill
A jet on a runway near other jets.
A baseball player is getting ready to go to bat.
Man on a black motorcycle wearing a helmet.
Horse standing in dead grass area near fenced field.
someone is skiing through the trees by themself.
The zebras are grazing in the field together.
The cut sandwich has meat, lettuce and tomato.
A small dog sitting on a stuffed animal teddy bear
A person holding a slice of pizza in their hands.
A man wearing a hat eating a hotdog at a sporting event.
A painting of a man sitting next to a woman near the ocean.
People are standing in front of a small store
a train on tracks at the front of the train depot
Elephants moving along on a very open field of some sort.
A cat sits curiously perched in an empty cup
Large collection of scissors attached with price tags.
An older man and two kids sitting on a bench.
Two motorcycle riders are riding a motorcycle bike.
People watching motor cross bike riders racing on a field
Two small children stand together scrubbing an elephant.
a close up of a shirtless man wearing a neck tie
The view of a distant mountain taken from an airplane window.
A train on tracks in a city with high rises.
PEOPLE BOARDING A BUS PARKED ON A STREET.
A woman holds a decorative umbrella and walks with a man.
A couple of cows standing on top of a grass covered field.
A crossed eyed man holding a remote in his mouth.
A single young giraffe stands and looks forward.
two giraffes standing next to several huge rocks
A person is flying a kite on the beach.
Two giraffes are standing next to a tall fence.
there is a person holding up a nokia lumia phone
A boy sitting at a table while he puts something in his mouth.
A man sitting in front of a laptop computer in an office.
A woman is on the side of a mountain in ski gear.
A view of a bed from across the room, it has a TV tray on it.
View of traffic signal against a dark sky that looks like rain.
A boy being affectionate with a baby on a bed.
A man with a top hat on and a carrot in his mouth.
There is a stove and a sink in a narrow kitchen.
A hand picking up a bunch of bananas from a display.
A cow and a person on a horse in the dirt.
Many doughnuts on a display in a store.
umbrellas, trees and a hut line a sandy beach
A man eating a hot dog on a tray
Some stacked with much sublime sustenance ready to eat.
Seven people smile as they pose with tennis rackets.
A school bus is parked by a street sign.
A train coming out of an enclosure under a snowy mountain.
A woman holding a surfboard walking into the ocean toward a dog.
Three people on snowboards riding down a snowy slope.
A black dog on a leash holding a frisbee in his mouth.
A woman water boarding in a lake near land.
A red stop light on a street at night.
A kitchen with wood cabinets and white countertops.
A bathroom decorated in pink ceramic tile and wallpaper..
A platter on a table that has pizza on it.
A snowboarding is doing tricks on a ramp.
A desk with a computer, a keyboard, a mouse, a bobble head, speakers and a lava lamp on it.
A man in a crowd balancing a skateboard on top of his head
A bathroom with a paper dispenser, toilet roll and garbage bin.
A seagull majestically flying through the air over the ocean.
A bed topped with a colorful blanket and lots of papers.
A person looking into a convex mirror on the front of a school bus.
wild animals graze in fields in front of a lake and snow-covered mountains
The side dish of the meal consists of a macaroni salad.
A plated meal on a table with flowers.
THERE ARE TWO ZEBRAS THAT ARE STANDING BY EACH OTHER
a cross walk sign in a busy city as light up the walk symbol
A small cooked pizza on a dining table.
a close up of a bunch of bananas and a container of garlic
a couple of people sit on a horse pulled cart
A wooden park bench sitting in front of a window.
Two white vases on a shelf next to a window.
Wearing shorts, a man holds up a snowboard while standing in the snow.
Two people playing tennis in a neighborhood park.
An outdoor area that has a glass top table with a plate on it and a blue vase with flowers in it.
An empty bathroom with toilet and pictures on the wall.
Two yellow bowls of food containing broccoli and potatoes.
Group of people paddling boats on water in front of a city.
A child holds an object while someone else cuts it
A man approaching a water ski jump holding on to a wire.
a toilet with a shower near by with tiled walls
A skateboarder performs a trick while being photographed.
A white fire hydrant near the address 700 Jones Street.
A bed with red sheets on it and messy blanket and a lap top.
A yellow school bus traveling a dark road.
A boy wearing a helmet and using a skateboard on the sidewalk.
A woman holding a knife over an unconscious woman.
A close-up of a man brushing his teeth.
a man sits next to a child as he uses a computer
a kitchen view of cabinets a stove microwave adn refridgerator
A dog and a railroad official and one person in train yard.
A motorcycle is parked inside of a building.
Two elephants that are walking in the dirt.
A baseball player throws a pitch while others watch from the dugout.
A group of people walking around an area together.
people on a small boat in a body of water
a train station and a train removing much smoke
There is a elephant in the grass, there are also trees in the background.
A small dog sitting on top of a couch cushion.
A security officer using a segway as a footrest
The mostly eaten pizza slice is next to olive pieces.
A baseball player starting his run for first base.
A man standing on top of a tennis court holding a racquet.
A post clock is positioned on the sidewalk with flags in the background.
Cars drive down a multi-lane road and pass businesses.
Inside of a living room with a sofa and several tables.
Two small suitcase is sitting in front of a white sheet.
a living room with couches and a table
Elephant with a brown eye hyper focused in the camera.
A man in a white shirt has his hands on another man's shirt collar.
A picture of five african american's sitting on a bench and chair.
A counter holds tomatoes, bananas, pineapples and other fruits.
A girl and a woman watching a candle being lit up on top of a cake.
Pair of giraffes walking on grassy area in enclosure.
A red fire hydrant next to some stones.
a yellow and red apple and some bananas
A green and yellow rain on tracks with building in background.
A large elephant is standing in a fenced in enclosure.
A boy on a boogie board in the snow.
Photos of sports memorabilia including shirts, caps, and baseball bats.
A young child mutton busting at a rodeo event
The bald man leaning against the tree holds his face in place with one gloved hand.
A young man with a neck tie untied around his neck
Sheep are running across a green field of grass.
a simple, normal toilet with the lid closed
A cat look through a window at a dog.
Busy city street with red signs on the traffic lights.
several cows one lying and one standing in a dirt field
A plastic container sitting on top of a table.
An old fashioned television and a newer electronic gadget sitting on top.
A white pickup truck sitting in front of two wooden scaffolding.
A child biting into a piece of pizza
The people are over by the cows in the water
A couple of cows standing on a lush green field.
A view along the transept of an older style church.
The bed in the room has been made with a large purple blanket.
A table that has people sitting around it with food in front of them.
a group of small dogs are staring out of the window
Two people sitting on a park bench near trees.
A table has a bowl, candle, and Christmas decorations on it.
A Skyteam Delta airline passenger jet taking off from an airport.
a black white yellow blue green and red kite and a person
A STREET SIGN POINTING IN WITH A TREE AND BUILDING IN THE BACKGROUND
Two different slices of pizza with tissue paper under it on a paper plate.
People riding a small boat under a very large bridge.
A group of people injured and covered in blood.
Three fire hydrants that are green stands near a parking sign at night.
A striped giraffe is grazing in the grass.
three chickens some water a fence and trees
Four men play tennis together on a sunny day.
A counter filled with coffee, cookies, and bagels.
a baseball player with a bat on a field
A green truck with a canvas tarp over the bed.
A man stands in a large kitchen holding a coffee mug.
An old motorcycle standing in a grassy field.
A table with a white plate of food that includes salad and sausage.
A cat on top of the counter sitting next to vegetables.
A small green leafy plant in the ground.
Two people eating hot dogs on a busy sidewalk.
A bird perched on the limb of a tree
a person riding a snow board on a snowy surface
A boy doing a trick on a skateboard off a rail.
Two woman are standing behind a large teddy bear.
A couple of people standing in the water under a kite.
A close up of the front of an old locomotive.
The man in the hat is carrying an umbrella.
A red brick building next to a green door.
A dog looking at a book called "The Marriage of True Minds" by Stephen Evans.
This is an image of an Air Canada plane flying.
A bird perched on a plant in the middle of a forest.
A living room filled with brown furniture on top of hard wood flooring.
A black computer keyboard in a dim room
The traffic lights are clearly visible for us to see.
A couple of birds sitting on top of a rocky beach cliff.
A couple of people throwing a Frisbee in a field.
A sandwich with a dipping sauce served on a plate
Road sign for the corner of Jackson and Montgomery
A large group of giraffes roaming around in an enclosure.
Stainless steel industrial stove sitting in a white and black kitchen.
A little girl is posing for a picture and holding an umbrella.
A couple of people with surfboards on a beach.
a woman is standing in front of a giraffe
A man in a blue shirt looking at his cell phone.
A man on a skate board jumps high in the air for a trick.
A woman sitting on the grass behind a pile of stuffed animals.
The barbecue sandwich is on a plate near a glass of wine.
Wrapped utensils are a part of a sterile and healthy meal.
A metallic refrigerator freezer sitting in a kitchen.
The child is putting the tooth brush in his mouth.
A white comforter with a toy, book and child shirt on the top of it.
A picture of a room in a house.
The wildflower is sitting in the glass of water,
A girl showing parrots to a group of children
Two zebras fighting outside in an opening near some trees.
Two surfers walk down the beach holding their boards.
A group of people in a courtyard next to a pavilion.
A renovated kitchen with wooden cabinets and white refridgerator
Some soldiers are standing in line for food
a man on a surfboard surfing a wave
Two giraffes are standing together in the wild.
The boat and the truck are parked by the dock.
Oranges and bananas sitting in a stack together.
An intersection with traffic lights and a street sign.
Three horses standing close but in an open field.
A person is riding a motorcycle in the mud.
A statue of a giraffe is in a Children 's Hospital.
A man is standing in a room with something yellow.
A mother elephant and her tiny calf walk through the trees.
A breakfast plate with eggs and meats, served with a gourmet coffee.
a black and white photo of a person holding a skate board
A boy swinging a baseball bat at a ball.
A meter maid car is by a fire hydrant.
A person flying a kite over another person on a roof.
A car parked behind a wooden bench.
A young skateboarder rides down the street alone.
A row of bikes parked along a sidewalk beside some cars
The bathroom in the home was just cleaned.
A circus act with five elephants and some women put on a show.
There is a muffin with white frosting and walnut bits on it.
A curious giraffe leaning over into a car at a zoo field.
Two signs one with the speed limit and one telling what freeway is which way.
a lady that is on a tennis court with a racket
A man sitting on his couch using his laptop
A statue of a cowboy on a horse in the middle of building.
There are street signs that show a direction of travel
A couple of small beds and mirror in a room.
A couple of large jetliner sitting on top of an airport tarmac.
The room is decorated in terra cotta tile.
A white plate topped with a pizza next to a bowl of salad.
Many suit cases are stacked on top one another
A gray and white cat sitting in front of a mirror.
A dog riding on the back of a motorcycle down a street.
A coffe and plate of bread sit next to a pillar.
a red and white tail of a large plane
Several pilots walking as a group across a street.
A man riding a skateboard on the side of a ramp.
a woman walking by a display with teddy beas and bottles
A street sign on a light pole near on a city street.
A male standing behind eight pieces of luggage.
a vintage black and white picture of a train
Two colorful umbrellas open against a blue sky.
A small bookshelf is filled with books and decorative items.
Several people walking in the snow, some carrying skis.
a bottle of whiskey and a bottle in a brown bag on top of a fridge
Women waiting for luggage at an airport luggage carousel.
Two sheep standing side by side at a petting zoo.
A pizza pie sitting on a board on a table
A couple of airplanes that are on a runway.
a bathroom with white walls and brown tile
A woman walks down the water with a surfboard.
this is an image of a train with black smoke.
A lady is on the entrance of a train holding her luggage.
A man is catching a frisbee while playing a game.
A skateboarder with his skateboard is sitting on the side of a ramp.
On a bright day, a young elephant in partial shade near a tree.
Young people stand near a bus with a large amount of luggage.
A bear costume cutting some cake with a Park ranger.
a large clock reading 5 54 on the side of a building
An unfurnished room contains a sleeping bag on the carpet.
A little girl that is standing next to a horse.
Two white bowls with vegetables, meats and herbs and chopsticks nearby.
A kitchen with a stove, refrigerator and cabinets.
a small child is sitting on a bench outside
Brown, white, and black rams eating on a hill.
A skateboarder performing in front of a crowd riding a rail.
This is an image of scooters and bicycles.
A cell phone peeks out of a crocheted cell phone holder.
A kitchen that has white cabinets and black counters.
Man on cellphone behind curtain while art displayed in front.
Two men in bucket hats taking frisbees out of a frisbee golf bucket.
A snowboarder grabs his board while high up in the air.
A woman's eyes are hidden by the cast of a shadow.
A black and white cat sitting in a bathroom sink.
A stop sign in the grass beside an old farm silo.
An Asian family that is eating pizza together.
A yellow train traveling through the green countryside.
A man and woman are standing beside each other playing a video game.
Two cats lounging on the back of a couch.
This picture shows sand, water, and some type of silver and red pole equipment.
A cut dog in a basket with orange ears.
An adult and child are skiing in the snow.
Two children playing with the knob on money meters.
Flowers sitting in a glass vase on a desk.
A laptop computer is seen sitting next to a television.
A small bathroom has a vanity, mirror, toilet and bathtub.
a black and white photo of people eating
a group of zebra standing in the sand in a fenced area
A man standing by a kitchen counter doing something
A bird is sitting on a silver truck
A mother and son sitting in a bed with two cats
A large piece of meat surrounded by vegetables.
White oatmeal sitting next to toast, coffee, and orange juice.
A bathroom with a shower combination tub and sink.
A white and brown cat sitting on the shelf in a cabinet.
A man is driving a small train with children.
A man and a woman cutting a sheet cake with a knife.
a man cooking some hot dogs on a grill
some kind of chicken, rice, and vegetable dish on a pizza tray being served to a man.
One man stands on top of the train while another man stands on the platform.
A piece of cake is served on a plate.
a close up of a child on a skate board
Fruit juice is spilled all over a counter next to a knife and two pastries.
A junk pile that looks to be piled with old bathroom sinks.
Two black and yellow circular clocks affixed to an office building.
There is a single bed in an old room with a window.
An a kitchen is being cleaned and decluttered.
Colorado Rockies' pitcher about to release ball from mound.
A bird perched on top of a tree branch under a light blue sky.
There's a desk with a laptop, phone charging, and other various electronics.
The two men are standing outside by the tail of the airplane.
A couple of brown horses pulling people on a wagon.
A small plane flying over an ocean with waves
The large SUV drives along a busy street.
A row of motorcycles parked on a city street.
a kitchen decorated with a couple american flags
A room with a chair, a piano, and a laptop.
A cat sitting on the side of a car door window.
Two pelicans on the sidewalk in the foreground with several more in the water in the background
A black and white photo of a man and woman sitting on a bench.
A picture of a thick crust pizza and a bottle of wine, setting on a table.
A MAN WEARING A SUIT AND A TIE STARING
Male surfer riding a large wave with sun low in the sky
A snowboarder hitting a trick on a trail, jumping over a person.
The man is feeding the elephant with milk
A bathroom with white fixtures and blue accessories
two brown horses in a field gazing around
Several people that are playing video games together.
A plate with beans, broccoli, small sausages, fork and a small container.
A black and grey double decker bus next to a building.
A smoking women in a scarf makes a phone call.
A person is traveling down the road on a motorcycle.
A group of men in colorful jackets skiing down a hill
A man and two others skiing across a snow covered field.
A man is standing over a black motorcycle.
A KITHCEH WITH A MICROWAVE SINK AND REFG
A jar of peanuts and a cell phone sit on a laptop computer on a cluttered table top.
A woman holding her child so she can see her birthday cake.
there are two giraffes that seem to be embracing each other
A table with wine glasses and people on the counter
A wooden bench sitting on top of a green grass covered ground.
A long couch with many pillows, a table and some seat cushions around it.
Six people are paddle boarding in the ocean.
Two young men play a game of soccer on a field.
A black and white image of tennis players.
This is an aerial view of a tennis player hitting the ball.
An item is capture here in the photo.
A cow grazing in a field next to a fence.
An individual is taken in this very picture.
People are outside flying kites in the sun.
a person riding a skate board on a street
There is a flower display in the corner of a room
A man pulling a sled behind him while using ski poles.
A person playing a game of tennis and other people watching.
A decorative congratulations cake for a graduating student.
A group of young people standing next to each other on top of a field.
a semi truck loaded to the top with sheep
A white truck crosses an intersection behind a traffic light.
Two street signs sitting on top of a metal pole.
The man in the red shirt is going to hit the ball with his racket.
A shop called Pendulum with a clock out front.
a traffic light on the side walk of a city street
Two signs above a blue pole under a blue sky.
A skateboarder is getting ready to skate down a ramp.
A man wearing a black vest and black glasses.
A bicyclist stopped beside a fence feeding or petting sheep.
An orange and white bus crossing under a blue footbridge.
A flock of birds landing in a field of grass
A man reaching into a bucket near an elephant while another elephant stands near a pond in the back.
A cat standing on the keyboard of a laptop.
An empty and open silver metallic refrigerator in a kitchen
Couple of people about to share kiss in front of wooden building
A person para-sailing in the water with mountains in the background.
a yellow taxi riding down a street that has a building with clock
a snall toilet and a sink in a bathroom
A zebra standing on a grassy pasture in the daytime.
A group of people playing a game with remote controllers.
A fighter jet with two streams of smoke coming out the back.
A bike parked on the side of a city street.
A glass plate topped with sliced apples and caramel.
A player swings at the ball during a baseball game.
A dog and man sit on rocks by water.
A bunch of food on a tortia in some foil
A woman tennis player is in a cropped photo.
A plate of chicken, rice, and some vegetables.
A man is staring at the viewer while a man plays a guitar and a woman sticks her thumb up sitting on a busy sidewalk.
A large jetliner sitting on top of a runway.
A person presenting a birthday cake to another.
A woman with a child on skis go down the snow.
A fridge in the middle of some cabinets
Kitchen knives and scissors are stored in a wooden holder.
A man speaks to some children on a farm.
Two zebras are walking along a path outdoors.
A woman lying in a bed looking at a laptop.
A lot of motorcycle people that are on the road.
A dog sits on a rug with its eyes closed.
A pick up truck parked near a strange house
A deformed orange sitting on top of an orange tree.
peeled banana sits on a table uneaten and ripe
A clock hangs from the wall of a beat up room
A woman sitting on a chair blow drying her hair.
A white plane with two people standing in front of it
A young girl with a cape holds onto a kite.
The puppy is eating food from the tiny bowl.
A hummingbird is floating next to the feeder.
A man riding a surfboard on a wave in the ocean.
A werid skirt like outfit on a person.
A security officer is setting up traffic guiding signs
A tropical beach with a banana tree in the forefront.
Military officer in dress uniform with many medals.
A boy doing a trick on a skateboard on a ramp.
A young boy is eating a meal in his pajamas.
This is a vintage photo with four men in it.
A dog is laying on the bed like a person.
Players react to the ball being hit at a baseball game.
A toilet with its lid raised in a stall.
Young boy and his plastic skateboard at home
Set of toy animals sitting in front of a red wooden wagon.
A silly brown dog wears sunglasses as it sits in a car
Broccoli is on a cutting board and is being cut in to smaller pieces.
an image of a tennis racket and tennis ball
A snowboarder sitting down with his snowboard on his feet.
A tennis player pauses during a game in a public tennis court.
A group of people on skis and snowboards outside.
a couple of trains parked on some tracks under a closed roof
Red double decker buses on a city roundabout.
there is a game that is ging on at thte gym and people aer looking
The man is wearing a tee shirt and a tie-dyed tie.
A group of motor cycles parked on the street
A set of two pictures showing a group of young people standing under a gazebo and next to surfboards.
A man is shown feeding an baby elephant.
There is no image here to provide a caption for.
Three zebras are shown in a black and white photo.
A Chinese public train waiting at the station.
A man walking along the shore with a surf board.
Two giraffes looking at a photographer inside of a barn.
A dog looks up at a flying disk.
A group of men standing on a city street.
A dog stares intently off to the left in front of a glaring TV.
A small pizza sitting in a frying pan of food.
A mirror that is on a tiled wall.
A black and white photo of people waiting at a boat ramp
Modern jet airplanes lined up on the runway ready for take off
Two white cows sitting in a farm area.
A stop sigm at an intersection with some graffitti on it.
A seagull at the beach with food in its mouth
A passenger bus that is driving down the street.
An umbrella strapped to the cross bar of a bicycle
View off the wingtip of a passenger airliner on a taxiway.
A cute little girl smiles for the camera
A city with traffic lights, cars and buses.
A man skate boarding in a pool with another man looking on.
a young woman cuts up some food on a trey
Two men skateboarding with a light and a camera.
A group of drinking glasses sit along a bar, with two people nearby.
A person on a motorcycle on a track near another person.
A food item is shown on a napkin.
two giraffes are standing in the open field.
A man riding the back of a brown horse.
A bunch of statues that are in the grass.
A man riding a snowboard down a snow covered slope.
A man swinging a baseball bat at a ball.
A cat sticking its head out of a cement wall looking up.
a few cowboys stand watching some animals outside
The woman is riding the horse on the course.
a woman sitting on a wooden park bench smiling at the camera
A cat sitting on a wooden chair in a room.
The animals are grazing on the wheat grain
Two men playing frisbee in a park
Two people standing in a market by a fruit stand.
Several cars are seen going down a city street.
A grown elephant and a young elephant roam freely together in an open field.
Woman in sunglasses hugging a red fire hydrant.
a teen standing on a skateboard while riding part of the wall
a close up of a cat laying in a luggage bag
A big family pose for a picture with a surfboard
two motorcycles line up as they lean against some seats
Two puffins sitting in some grass on a mountain.
Many young men pose for a picture.
a person showing cellphones on sale in a shop
A YOUNG GIRL ON A SKATEBOARD IN A PARKING LOT
A man is posing excitedly on a surfboard.
A very nice boat on the water with a dog on it.
A young man holding a Wii mote plays a video game
A stack of suitcases stacked in a front lawn.
A gang of bikers riding down a street.
Little girls play soccer on a field on a sunny day.
A living room and dining area with hard wood floors.
A bunch of ripe oranges are stacked neatly on top of each other.
Someone is making a sandwich consisting of carrots and alfalfa sprouts.
A brown cardboard box filled with bananas, apples, oranges and kiwis.
The young kids are playing a game of soccer.
The kitchen bar is near a dining room table.
A food container with five sections filled with various items.
A woman sits on a brick wall, holding her umbrella, looking out at the city.
Woman talking on cellphone in a dining room.
A small industrial machine car on train tracks.
A desk witgmh a telephone, laptop, cell phone and a book on it.
a man in glasses is playing with a white controller
A BIG BOX OF TOMATO AND BASIL PIZZA.
A large group of people on a field playing soccer.
A yellow and black train is on a train track.
A black and white cat curled up on a brown checked sofa.
A man is talking a picture of a bus.
Two horses standing near each other in a field
A lone swan swims in a river near a bridge.
Woman playing tennis with bleachers in the background.
A vintage photograph of a war plane flying
Two food items are displayed on separate plates.
A brown and gold fire hydrant in front of a brick building.
THIS IS A PICTURE OF A FEW ZEBRAS GRAZING IN A LARGE ENCLOSER
an image of umbrellas lined up with tables
A group of sheep walk along a dirt path.
A desk with a pc, monitor, laptop, mouse, and stuffed animal
A gray and white cat laying on it's back with it's head looking up in a open drawer.
A man walking a bike near a train station.
Photo of a living room with a Christmas tree in the corner.
A toiler and some buckets in a small room.
Large group of ships tied together at a peer.
An empty road with a red stoplight that spans voer the road.
A black dog playing in the ocean while barking.
A dark gray bird flying towards a palm tree
A motor home parked along side an outdoor flea market.
A closeup of a wine glass and a wine bottle
A boy jumping up over a bench on a skateboard.
A huge, captive fish gapes his mouth open at a woman taking a photograph in an aquarium.
a person reading a book and cooking food on a stove
Onlookers watch as a skateboarder performs a jump.
Some wooden benches are in the middle of the forest.
A man standing on top of a sidewalk holding a skateboard.
A laptop sitting on a living space table with a spacious desert view.
four colorful vases of different types are sitting on a shelf.
A close up of a stop light positioned against a high rise building.
A room features two identical beds with stools at the end.
A computer screen showing photos on it while a smokestack is visible out the window
Night shot of skateboarders in wide open area with lights above.
A couple of giraffe standing next to a zebra near a rock wall.
A table holding a white plate with bananas and a brown glass.
A bus that is travelling on a road in a town that has many houses and buildings.
A pair of giraffes grazing on hay by a fence.
A couple of plates of sausages, broccoli and purple food.
A family of giraffe on a wild field next to zebras.
A large cow standing in a grassy field near other cows.
A tennis player is jumping and reaching to hit the ball.
A couple of people on a wall playing with a Frisbee.
a laptop on the ground near a turn table
An old clock with a flower design in a small room.
a kitchen with a refrigerator near a sink
Men loading luggage from a train onto a cart.
A fan closely watches the professional baseball batter
Little boy and girl sitting on the porch eating their meal.
A man standing behind a display case filled with jewelry.
A black and white photo of a man fixing anthers tie.
a person preparing an authentic pizza on a wooden spoon
A street sign next to a traffic sign next to tall buildings..
Herd of wild cattle walking along the beach
A city street with people out and two large buses
a small dog with some glasses over its eyes
a dormitory consisting of many beds lined up along the wall
A kitchen has a stove,microwave, and wooden cabinets.
An electric commuter train on the tracks under a cloudy sky
The person is wearing black clothes, shoes, and hose.
There is a child that is walking in the gradd
Hundreds of bicycle enthusiasts embark on a race on a city street.
A man in the air skateboarding at the park
A close up of a Harley Davidson parked on the road.
A man holding video game controllers and playing.
Gray and white bird with red crest using bird feeder.
A white car passing a person in a black jacket.
a large train is going down the tracks outside
Two ponies together standing on a mountainous terrain.
A small bathroom with a shower, sink, and wooden medicine cabinet.
Small train coming out of a tunnel on an overpass.
A group of people who are standing in the dirt.
bread with banana milk and nutella on a table
A clean and tidy kitchen with a stove, dishwasher, microwave, widow and a door.
A cat sleeping on top of an open laptop computer.
Two motorcycle riders talking on the side of the road.
A bunch of people is watching something and a man in a brown and blue stripped shirt has his fingers in his ears.
A ukelele is passed over a table with cake and lots of food.
A giraffe is standing near its fenced area observing.
A pasture with sheep in front of a large home
A large group of birds sitting on metal pipes in the water.
A group of people sit down at a table to share a meal.
A man pinning a number to a child's shirt.
A dog sleeping on bed against the wall.
a room with wood flooring filled with furniture.
Two zebras stand close to each other in a field.
a person on a bicycle a bus a truck and a child
a vandalized stop sign in the dark with a sky background
a red and yellow trains engine pulling its cars and some tracks
A woman sitting on a bed with a laptop.
Two people with surfboards are standing in a sandy parking lot.
A PERSON JUMPING FROM A SLOPE ON A SNOWBOARD
Long bamboo poles with umbrella tops in front of the sky
A stove is away from the wall in a kitchen area.
A trolley driving down a street lined with tall buildings.
A giraffe looking concerned on a grass field.
Two metal lamps are placed beside a window.
A close-up photo of a pool table with a man playing.
A group of different parking meters displayed together.
A boy is doing a trick on a skateboard.
A black and white photo of a city street with old cars and people on it.
a number of people standing around a large group of luggage bags
piece of cake with a plate and fork
Large giraffe roams in the lush green vegetation.
a blue and pink kit with streamers flying in a clear blue sky
A man pushes a brightly smiling little girl on a swing.
Two stuffed bears that are next to each other.
A car that is parked in some snow.
A zebra standing in some brush without leaves.
A bunch of people walking across the air field to get to their plane.
A man hitting a tennis ball with a racquet.
a close up of stuffed animal with metal pieces on his chest
A person is on skis in a very snowy place.
airport coming in to dock at the airport
a person on a city street operating a cell phone
Two man standing near each other in a park.
A man is eating a hot dog and talking to a young girl.
A person bending over to adjust a child's skis.
A woman in a boat eating a sandwich.
A person standing on a mountain top with some skis.
A group of cattle walking across a lush green field.
two giraffes standing under a tree to get some shade
An owner plays tug-of-war with their Golden Retriever
A dog looking up and running to catch a frisbee.
an open toilet on the side walk of a street
A man with a very bright orange hat sitting in a car.
A traffic light next to a busy street in front of a brick highrise building.
a person standing near a bush near an elephant
A woman that is standing on a sidewalk.
Three park benches are in a garden type setting.
a bathroom with a toilet and a bath tub
A flower vase in the center of the kitchen table.
A bull walks up to a pile of wood and a teddy bear.
a couple of coaches in a cluttered living room
THREE BOYS RIDING THEIR BICYCLES ON A STREET.
there is a male baseball player about to throw the ball
A couple of people standing around holding snowboards.
A photograph of a highly decorated cake on a table.
A passenger bus that is driving down the street.
A large building with a railroad crossing near it
A bike is covered and parked on a street.
A small bird in a tree with red fruit on the tree
A cat looking out a window at a bird.
High school girls soccer game action shot of green versus red team.
A person with a lighter lighting several sticks.
Reflection of a school bus in its own side view mirror.
two people in costume pose for a photo
brown bathroom with white toilet and white sink
A pretty young lady eating a hot dog on a bun.
An elderly man blowing out birthday candles on his cake.
A plate filled with breakfast foods sits on top of a wooden table.
This clean bathroom has a tile floor and a brown toilet lid
A woman with a painted face is on a phone.
A green bird bath decorated with various jewels
A fancy clock graces the corner of this old building.
A cat sitting in front of a television watching a hockey game.
A chair and a blue umbrella are attached to a wheel.
People sitting around an oval table in a restaurant posing for a photo.
A street scene with a truck and trailer in the foreground.
A locomotive on train tracks in a wooded countryside.
A train riding pass a platform and buildings.
a stuffed sandwich with meat, cheese and pickles
A man riding on top of a board on a wave.
A man and woman making a cut into a wedding cake
Some cows stand beneath the shade of some trees.
Pink lunch box with compartments for all types of food
two white birds flying over the sea water
The lobby has a few people in it but for the most part it isn't very busy.
A double oven with one side completely full and the other empty
Man are standing near a couch holding Wii controllers.
A pizza on a board with a pizza cutter
A BABY EATING A MEAL WITH HIS TOY DRUMMER BEAR
A tan dog laying next to a park bench.
A skateboarder performing a jump off the edge of a stone wall.
a cat sits on the floor looking at the camera
THERE IS A CITY BUS ON THE STREET
a couple of people that are sitting on a bench
A person sitting in bed with a dog on his lap.
A seaplane is docked near a residential area.
An umbrella and rain boots in a corner
A laptop and a desktop computer sitting on a table.
A zebra and a giraffe walking in opposite directions.
Two children staring out a window while on public transportation.
Giraffe and zebra grazing in a field next to plants.
A stop sign is shown on the side of a corner.
A modernist kitchen, with a white and aluminum color theme.
a large room that has a big kitchen table in it
A baseball player hitting a baseball with a bat.
A baseball player running to catch a baseball during a game.
A large white bus on a city street.
A woman putting post it notes on a wall in a room.
The baseball player is practicing his swing for his favorite game.
Assorted pastries and tongs have been arranged above stacks of plates.
A cellphone and a remote control sitting on top of a book.
A woman is skiing down a high mountain.
A man standing on a tennis court holding a racquet.
A herd of elephants with birds at sunset.
A white plate topped with broccoli and meat covered in sauce.
A woman is smiling and holding a monkey.
A black and white photo shows workers working on a road.
A small girl holding skies in the snow
A person is running with a kite in the air.
People watching two elephants from behind a cement platform.
A man flips a skateboard while doing a trick.
The toothbrushes have a holder on the bathroom sink.
a train station with a train sitting parked in it
A guy on a skateboard at the top of a concrete bowl.
Many stuffed animals hanging and sticking to a tree.
Several "One Way" Signs are placed near an "All Way" Stop sign.
A man riding a surfboard on a wave in the ocean.
Two young boys eating carrots while sitting on a bed.
a long train is going down the rail road outside
Five benches in the park in an area surrounded by trees
some people are pushing a truck in a lot
A group of small children having a birthday party.
A dish contains carrots, onions and other vegetables.
The two baseball players are walking on the sidewalk.
A room with decorations on a shelf and a painting on the wall.
a close up of a laptop on a desk
A laptop computer is sitting on a table top.
a couple of people on skate boards do a trick
A closeup photo of a bulldog wearing an Army style hat.
A sprinkled doughnut with pink icing sitting on a plate.
A kitchen area with refrigerator in the background and a sink and stovetop oven on the side surrounded with wooden cabinets.
two zebras are in their pen at the zoo
A baseball player holding a bat on top of a field.
A couple of skateboards, two sitting on the sidewalk, the other on the board.
A red stop sign sitting above a traffic light.
A desk with two computers, phone, and other accoutrements.
A teenager in wild clothing playing a video game
Blue, pink, purple, and yellow flowers are in a red vase.
A hot dog with a large amount of cheese.
A city street filled with traffic at night
The box of a dozen donuts has two different flavors.
A living room setting with furniture and lamp
The three men are dressed in costumes.
A red double-decker bus driving down the road.
two giraffes and one is eating some food
An iPod and a laptop computer on a desk
an orange and white cat and its orange play toy
The closeup of a clock on the face of a tower.
Large poster on wall behind white commode in dark tiled bathroom.
A dish with shrimp and cucumbers and lettuce.
A man with a skateboard that is up in the air.
Children are looking at a zebra in an enclosure.
People are sitting on a motorcycle with a woman standing behind them
Oriental woman preparing to put a toothbrush into her mouth.
A table with a laptop, bag of coffee and cellphone on it.
A girl excited about a cake at her table.
Dog laying down on a grey and yellow striped couch.
The top of a desk with a keyboard, computer and phone.
A coal fired train with passengers behind a split rail fence.
A collection of fine furniture is displayed in a room.
A transit train badly in need of a paint job
A plate with a roasted carrot and broccoli on it.
A woman holding a tennis racquet prepares to play tennis.
A person gets ready to swing their racket.
a girafee looking around by some people
A girl stands on a bed and appears to be crying.
A very large building with a tower near some water.
a close up of person sitting with a laptop
a cream colored dog lying on a brown carpet.
White toilet with a shower with a tree on it beside it.
A catcher has his mitt out as a baseball batter swings his bat and hits the ball.
A man who is sitting at a table with a plate in front of him.
a lady covering herself from rain with an umbrella
A man wearing a gas mask and a suit and yellow striped tie.
A glass bowl filled with noodle salad on to of a table.
Two elephants are standing on the grass near some trees.
Three boys sitting in chairs with game controllers.
A city intersection with a sign redirecting traffic.
Nice looking front room with brown furniture to decorate it with.
A train with a red caboose sitting on tracks.
Military looking truck parked in an old warehouse
The living room actually features several different colors.
Small pizza sits on a plate on a restaurant table.
A man holding a bat next to a catcher and umpire.
The teddy bear was left on the empty bench.
very many pizzas in a plate in a kitchen
A black microwave on a cabinet in a hotel room.
Man flying a tailed kite high into the sky
A man that has a gold tie on.
The outdoor furniture with a table umbrella is made out of wood.
A family sitting at a booth in a restaurant looking up.
Two women standing on tree stumps with a boy and a teddy bear
A group of men let their horses drink from a fountain.
The girl is eating her pizza with a fork.
a grey dog seated on a chair of a vehicle
A brown cat lying at the back of a car
A group of kids standing beside an opened fire hydrant.
A herd of giraffe running across a field.
A person rides a horse in front of a large group of people.
A woman sitting with her legs crossed on a bench in a green field.
A man riding a skateboard on top of a cement park.
BRIGHT RED FIRE HYDRANT WITH A SIGN NEXT TO IT
The cat is laying partially in the light with its eyes closed.
A couple of men playing soccer against each other on a field.
Two people work on a shed while standing on a tractor.
there are two grizzly bears walking down the gravel road
Two men running and playing baseball with plate and grass
A couple women with remotes in a room.
A red trolley passing by a group of people under umbrellas.
A young girl standing on top of a tennis court holding a racquet.
A large open concept living room leads into the dining room.
A person with a red umbrella walking towards a bike chained to a lamppost.
A bunch of broccoli spread out on a table
A closeup view of food on a plate
a dried out tree with fruit hanging on it
A small and a large teddy bear sitting in plants
View from the stands of sparsely attended tennis match
A man that is sitting down next to a cops motorcycle.
a brown table with a toaster a plate and a black microwave
A snowy road with snow covered trees on which a skier is traveling.
two guys are outside moving a refrigerator
An Asian woman in front of a body of water with two umbrellas
A man standing on top of a blue tennis court.
Signs at a city intersection indicate no turning is allowed.
Two elephants walking in water next to grassy area.
A man on a skateboard doing a trick.
Woman in a white uniform holding a pencil to wall.
A small boat with several flags on it moving across the water.
a big building with a clock built inside of it
A market has many fruits and vegetables on display for sale
there is a large truck and a yellow truck behind it
a store front has many stuffed animals on display
a tennis getting ready to hit the tennis ball
A group of sheep walking down a path with a few stopping to eat grass along the side.
A small cat laying on a couch in a room.
A fire hydrant behind a gate on the sidewalk.
Giraffes eating leaves from bushes near logs on sand.
A man sitting in a chair looking at someone's food.
A zebra with its mouth open and lip in the air.
A man holding skis and poles and walking up a snow covered mountain slope.
A man is cross country skiing on a bright day.
a woman in white is cutting into a cake
A person surfing a white water rapid.
A glass vase with yellow flowers in it
A rear view mirror on the side of a car reflecting a mountain range.
Two sheep are in a barn standing next to each other.
A double Decker bus is traveling down a street.
An old steam locomotive waits at a country station.
A snow covered parking lot meter in front of a building
London double decker bus in motion on street
The horse is grazing in the fenced coral.
a zebra is laying down in some dirt
A man in his skiing gear is on his board looking on.
a guy on a surfboard with a kite attached to it.
A sheep with its new born lamb in a field.
A toy ship made out of Legos is attached to the side of the refrigerator.
A person up in the air on a skateboard.
Elderly man sitting on a bench facing the beach.
A bathroom has pictures hanging on the wall.
A small hot pink bathroom with a few touches of royal blue on the toilet is shown.
A father and son in a kitchen preparing a meal.
The parking meters are posted beside a cement wall.
these men are playing a sport in a field
A large city bus making a turn at a crosswalk with a clock tower behind it.
Two woman play Wii video game with wireless controllers.
A square of cheesecake on a marble cutting board with a two-pronged fork.
A plant in a blue cup on a windowsill.
A bright red bench sitting in front of a decorated store front.
A man has some food hanging out of his mouth.
A group of people standing around each other near a street.
A child at a table sitting in front of a birthday cake.
two giraffes standing next to some trees
Many people are standing next to a very large plane with its bottom doors open
A man in black shirt and white shorts playing tennis.
Two different transit trains can be seen in this photograph.
A group of people around a table with a blue tablecloth
A bedroom with two beds and a table with a lamp.
A bear jumping into a pool of water.
a man with a napkin at his neck eating a dangling food
An elephant walking by a group of ATVs.
Two people that are sitting on a table.
Two photos of a young man in a suit and tie
A young boy with a helmet rolling down the street on his skateboard
Commercial airplane flying in the air on a cloudy day.
The neat bedroom has a large window in it.
Two cows on a grass covered hillside on a sunny day.
bathroom with white toilet and white sink berside each oher
A bowl filled with yellow bananas and green apples.
An aircraft soars over a beach near a city.
a person sitting on a bench while the rest look somehwere else
A lot of people that are on a sidewalk.
The sun is blocked by a statue holding a round object.
A man with an umbrella hat stands next to another man.
Four horses walking across grass on a lake with mountains in the background.
Outside view of the MGM Grand in Las Vegas with people sitting and walking.
a brown and white cat is looking in a mirror with glowing yellow eyes
A fork sticks out of a parking meter.
A man in a bathroom on an airplane.
Bunches of bananas in yellow and green hang from a ceiling.
A white and red double decker bus on street next to car.
ACCIDENT SCENE WITH FIRE TRUCK, AMBULANCE, VEHICLES, AND PEOPLE
View of jet airliner taking off over tree top.
A train sits on the tracks while people stand near by.
A professional baseball player about to hit the ball
A full view of an outdoor space with many things to see.
a red motorcycle with a windshield parked on the sidewalk
A dog with a tiara on and his head rested on an armrest.
Two guys standing on the right hand side of a motorcycle.
A bath tub in the center of a large bathroom.
A stop sign and two fire hydrants set up in the woods.
A condiment filled hotdog is in a red basket next to an iced beverage.
Two slices of pizza on a table with one beverage.
a store sits in front of a fire hydrant
A set of three cow statues siting above a crowded walkway.
A large plate of doughnuts on a table.
a bunch of sheep in a field eating
A child on a blanket with an apple.
A woman leads a race horse down a cobblestone path.
A man drinking a beverage with his sandwich.
A person is squatting by a banana tree.
a small group of fish about to be cleaned
Two men standing in a parking lot dressed in business atire
An arrangement of fruits and vegetables are laid out on a counter.
A kitchen with a large wooden table and clutter on it's counter.
A slightly dirty room that has green items on the floor
A cat is laying on the lap of a man playing video games.
People sitting around a long table using laptops
A bear is next to a body of water outside.
Girl on phone looking up a statue of Ronald McDonald.
White living room furniture looks very modern and clean.
A hose sitting next to a fire hydrant on the street.
A large clock stands on a post on a city street.
Two giraffes standing in a rocky area by a river.
A group of women are gathered by a long table of food.
A stop sign that has been covered with graffiti.
A dog with its mouth open about to ear pizza crust .
A shelf with donuts being sold six for five dollars.
A muscular man surfing on a vast blue ocean
Herd of elephants crossing a water hole next to another herd of elephants.
A collaboration of people in different pictures doing things
Airplanes on the tarmac in the rain at an island airport
A person jumping a skateboard at a skateboard competition.
there is a man pointing up standing on a building
A boy and dog sitting on a recliner the boy looking at a laptop.
Men on horses herding a group of cows down a road.
A skier looks up to the camera above her.
A row of urinals with air freshener boxes on a wall.
a person standing in a door way and a horse in the foreground
A baseball batter readies himself waiting for the pitch.
kids out on the field playing soccer together
A man flying through the air while riding a surfboard on a wave.
Man in red shirt standing in front of a man holding a frisbee.
Two mountain peaks rise above a large meadow.
A bike in view in a living room with a Christmas Tree in the background.
a group of horses standing next to a tree in an open field
A player sliding onto bass while an opposing player tries to grab the ball at a baseball game.
a big bear that is staring at a camera
To people sit on benches in the rain, holding umbrellas.
a person in a kitchen with a pizza
A mans toilet attached to a black pole.
Someone holding a stuffed teddy bear in their arm.
A crowded city street is full of big umbrellas.
A naked baby is on a bench in a backyard.
people standing outside of a building with a fire truck
A meat filled pizza sitting on a pan on a table.
A rainbow colored kite caught in the branches of a tree.
A young boy riding a skateboard up a ramp.
She is eating a sandwich and having a drink.
A kitchen with marble counter tops and black appliances
a stop sign graffiti written on the front
a train yard with several stopped trains waiting to go
Street signs, including a stop sign, where someone wrote "Don't stop believin!"
Two pillows sitting on the ground next to furniture.
A person is holding something donut shaped in their hands.
A woman with glasses and a scarf skateboards along Hollywood's Walk of Fame.
A glider gliding in the sky over the ocean.
a group of people sit around a table
The pastry has a substance in the middle of it
A group of baseball player congratulating each other.
A man strikes a tennis ball during game.
a number of people on horses playing polo
some baseball players on some grass and some trees
Two people climbing a mountain on their skiis
A view of a oven with the food flipped over in it.
A woman sitting at a table while using a laptop.
A counter topped with lots of pizza and sandwiches.
Several zebras walking in the shade near some trees.
A kitchen has light wood and shiny floors.
Plate of food including chicken, pasta and vegetables.
Girl competing in a horse competition at the county fair.
A white train sitting in a train station next to a Bologna sign.
A zebra standing on top of a grass field.
a motor bike sits parked on a cracked street
A number of food items and two beverage atop a wooden table.
Vases of flowers sit among plates of pastries.
An airplane is on a snowy runway at an airport.
A dark colored dog sitting on blanket and looking up.
A bunch of different fruits sitting in baskets and on a table.
Vegetables and fruits are on a brown cutting board.
A low angle view of a church clock.
A man and woman sitting by a pile of bananas
a person sitting in a boat with a dalmation
A group of people near a table full of bananas.
A large flock of sheep are in a grassy meadow.
A person sitting on a machine with wheels in the middle above a pedal.
This lamp is standing near a wall that is painted red.
A toddler laying in a bed with pink sheets.
A person on skateboard in a parking ramp looking area.
An old, dilapidated toilet with a broken seat
A smiling clothed man sitting on a toilet.
A huge white and blue airplane sits on the runway.
Two men shaking hands and one being presented with a key.
Stuffed animals on a shelf with some books.
All of the donuts each have a different flavor of icing.
A close of a bobble head doll with a computer in the background.
A bathroom with toilet glass sink, mirror and extra toilet paper.
A very cute orange cat laying with some shoes.
A clock tower sitting behind an illuminated star display on a tree.
A paper plate topped with a slice of cake next to a spoon.
a shop with a bunch of signs sitting out front
A room with wooden floors and wooden walls
A school bus that is made by Chevrolet has a few bumper stickers.
A suitcase full of random assorted food items
A living room with couches, a table, and a fireplace.
A plane takes off from a runway while a large building stands in the background.
A trolley with people on tracks in a rural area.
The batter prepares to hit the ball, while the fans watch from the side.
Young snowboarder spending time on slope in ski area.
a sink with a microwave oven on top of it
A delta airlines jet sitting next to a truck on a runway.
Two people standing in the reflection of a mirror.
Two children on a soccer field kicking a soccer ball during a game.
Group of motorcycle riders looking over traffic on the street
A man holds an enormous sandwich in front of his face.
Group of motorcyclist riding motorcycles down a highway.
A man skiing down a snow covered ski slope with two ski poles.
Small boy in green shirt touching a yellow fire hydrant.
A small herd of cows near a water bank.
Decorated coffee cup with spoon next to miniature bicycle.
A man standing next to a woman in a kitchen preparing food.
two street signs on a pole on a sidewalk next to a street.
A man walks out of a colorful train onto a platform.
A pudgy man holds a huge hot dog and chips.
Donuts and a cell phone laying on a table.
there is a man with tattoos talking on the phone
A man with a racket goes to hit a tennis ball.
A high speed train pulls into a platform while people watch.
A bed in a room with two windows.
two plates side by side, one with a roll and jam.
A young zebra stands away from the zebra in the light.
There is a white stove with pans on top of it and next to it, a refrigerator.
A lady sitting at a kitchen table alone.
A tennis player serving a tennis ball on the court.
A typical living room with couch, glass coffee table, television and water dispenser.
A cop leading a gang of bikers down a street.
A couple of giraffe standing next to each other in a forest.
Laptop computer sitting on a table with a sticky note on it.
An animal grazing under a wide, gnarled tree.
A woman laying on a surf board is riding a wave.
a group of people next to a train with a sky background
A cat staring at a another cat hidden in a travel bag
Several people gathered around a table that has a cake on it.
A coffee cup sitting on a pad of paper next to a keyboard.
A white plate is filled with a variety of doughnuts.
An aisle in a store that is selling holiday items.
The player is hitting the ball with strength.
The man is holding a glass pan full of liquid mix.
There is a row of cows with baby cows next to them.
The black cat is turning away from the large computer screen.
The window to the store has graphics on it.
A plate of food and a cup of coffee.
a girl with a microphone talking about a cow
Carrots and cucumber on wooden cutting board near knives.
2 buses and numerous cars move down the street.
a male in a brown shirt sitting on a bench with a laptop
A painting of several flowers in a vase sitting on a shiny surface.
A large yellow dump truck driving on top of a sandy beach.
A person is riding a horse inside an obstacle course.
A man is standing near a computer giving a presentation.
A black cat with green eyes rests on colorful blankets.
PERSON GOING FOR THE RETURN ON A TENNIS COURT
a view of a keyboard, remotes sitting on a desk
A man riding a skateboard down the side of a ramp.
the sandwich is on the plate and has been cut in two
A man is standing at the base of a ski hill.
A refrigerator and a stove in a kitchen.
The bottom of a large airplane flying overhead.
a man wearing a yellow snow jacket and black snow pants snow boarding.
A piece of chocolate cake is in a plastic container.
A small airplane flying over a body of water.
A child holding the hand of an adult while moving on skis.
People are walking on cobblestone with umbrellas and shadows.
A child is under the covers reading a book.
a plate with some food in it on a table.
A man is riding on skis down a snowy mountain.
A batter, catcher and umpire in a baseball game.
A line of black and white cows are lined up and grazing.
a woman is working at a pastry shop
A cat is sitting on top of an entertainment system
A woman sitting on a bench with a mean look on her face
A large group of people on a grass field.
A person sitting in front of a laptop computer.
a desk with a bag and a bunch of other things sitting on the floor
A dog runs alongside a skateboard with one paw on.
A skateboarder balances on his skateboard, then balances on the board at the edge of a low wall.
A man riding skis down a snow covered ski slope.
a close up of a plate of food with broccoli
A man wearing a wet suit riding a wave on a surfboard.
a police on a big white horse in front of a retail store
A small cat standing by a mirror on the ground.
A bedroom with a white bed on a frame next to a window.
A white table topped with lots of plates and food.
A suitcase surrounded by some items on a floor
A man holding a Wii game controller while standing in a living room.
A fried dish is pictured on a plate.
A tall clock tower sitting on at the end of a street.
A herd of wild elephants walking along a dry grass filled hillside.
A group of people sitting at a table with plates and soda.
four woman standing next to each other with bike helmets on and holding bananas
A woman walks in the road shimmering with rain past the city lights.
A man making a cut into a celebratory cake
There are cars parked along the side of the snowy street.
A red crafted bird is pasted to a parking sign.
close up of a cow standing on the other side of a barbed wire fence
A small boat rests on wooden planks by the water.
Man on skateboard on top of wall in factory.
A plate of food featuring burger patties, potatoes and carrots.
A girl lying in bed and playing a handheld game.
Two clocks on post next to building in street.
Looking down at cookies baking in a home oven
Colorful flags hanging lined up in a row.
A black and white image of an older air plane.
A stuffed animal dog birching out in front of people at the beach
A box is full of old items as a tribute to Forrest Gump.
A vase that has flowers in it on the table.
A dog on a bed looking at something.
A man on a surfboard that just caught a wave
A bird stands next to many black benches.
A woman with makeup bruises is in a suitcase.
a man lifting the lid of a square shaped toilet
A man is pulled by an unseen boat while water skiing.
Small cup of baked brownies being scooped out into small snack sized dishes.
a group of people sitting at a table to eat at the beach
a couple of people that are in a kitchen
The train can be seen through a chain link fence.
Birds stand on a side walk under the large trees.
A view of a great room consisting of a living room and dinning room.
a street light with street signs in front of trees
A photo of some cows standing in a field.
many luggage bags near each other on the ground
A line of people in suits holding roses.
A BATHROOM WITH A TOILET AND A SINK
That collage of nude women probably means this bathroom belongs to a guy.
A man standing in a room holding a drink and a game controller.
A white toilet and sink in a room.
A child showing a banana to the camera.
A close up of a cats profile is shown.
A man is standing next to another man who is laying on the floor
A man is looking at a bus stop sign
A baseball player holding a bat standing near home plate.
A man holding a laptop sitting beside a woman with a small child.
a toilet with a remote control mounted on the side
A couple of women riding on the back of a horse drawn carriage.
A man at a campground eating a sandwich.
A man sitting at a table with food and beverages in front of him.
A bride, groom, and minister at a wedding ceremony.
A TV sitting on top of a stand in a living room.
Four people riding on horses along the beach shore line
A train engine carrying carts across a bridge over water.
A black train sits on the tracks as people stop to admire it.
A kitchen with two stoves, an island, and appliances.
a woman walking down a crosswalk next to woman riding a skateboard
A double length metro bus drives down a city street.
A tray covered in tin foil on top of a counter.
A clock sitting on top of a sidewalk.
A park bench by a body of water.
Two cats laying next to a cup of coffee.
A hairy man is holding a frisbee on the beach.
Two people hold their colorful pastries next to each other.
Many skiers are going up a snow hill
A picture of a baseball game being played in a stadium.
A collage of pastries, and a boxed of donuts.
A triple layer cake sitting on top of a table.
A red and yellow traffic sign sitting on the side of a road.
A bowl with red and green apples and an orange.
A living room with furniture, television thrown rug and a window.
a small child standing in a living room eating something
a dog moving towards the horses at the mountains
man with skull decorated surfboard eyeing the ocean
A young man standing on top of a snow board in the snow.
A cyclist passes a bus while it picks up passengers.
a big living room with stained glass windows leading to a piano
Men's doubles tennis players shaking hands on the court
A white cat is sitting on a white sofa.
A woman wearing a white shit and apron standing by a man in front of a traffic light.
A white plane sitting on top of a runway near a building.
An old black and white photo of a man holding skis.
Cows in pasture within a fence on a field.
a broken toilet bowl base overturned in a shrubbery next to dirt and rocks.
Bathroom with a toilet, glass sink and a mirror.
A couple of animals grazing on a dry grass field.
Electronic and personal items from a back pack laid out neatly
Female flying a kite in an open field.
a woman posing on a bench in front of stony ruins
four giraffe stand at a tree all with their noses stuck into some kind of nest
A group of elephants walking through the street with a pepsi stand in the background.
A man holding white surf board on the beach
A walk in shower next to a tub in a bathroom.
A kids baseball game with a runner sliding into home
A black, blond and white cat crouches on the side of a table with a cake on it .
A man on a bike balancing quite a bit on his head.
A group of female soccer players at the pitch playing
Horse jumping over an obstacle on a course with a rider.
Man cooking marshmallows over an electric stove with fancy tongs.
A plane on a runway drives off to the air
A group of people playing Wii in a family room.
Flowers in a vase full of water next to a window.
Many different piece of luggage that are open on the floor.
two people with two dogs on a surf board and one dog swimming
a plate filled with assorted veggies and cheese
A train engine is sitting at a train station.
A couple of people on skis in the snow.
A bathroom with a toilet, towel rack and a tub in it.
A man in wet suit surfing wave on a surfboard.
A cat is curled up on a bed beside a remote control.
A couch with a cat and toy teddy bears on it.
a number of horses standing near one another
A child in snow gear and skis on a ski slope.
An old truck with no passenger door with tires and body painted in different colors.
A close up of a plant center surrounded by leaves
A couple of kids are skate boarding down a street.
A yellow train is stopped against a barrier on the tracks.
The soccer player is kicking the ball while a crowd watches.
A silver pan filled with food on top of a stove top.
A man riding a dirt bike on top of a sandy beach.
A cat is stretched out on a couch under a window.
Close up images of bikes parked next to the highway.
a table with some glasses of beer and some pizzas on it
Two horses giving each other a loving nose kiss.
A monkey with a banana sitting in the dirt.
A table that has a plate of food and a glass of wine on it.
A bowl filled with ice cream, sprinkles, cherries and other toppings.
half a dozen giraffe in a wooded area
Two skiiers jump down a snowy slope towards a ski lodge.
A full, black and white coffee cup held in front of a computer keyboard.
This kitchen has white cabinets and counters and silver appliances
a man that is walking down a sidewalk
A beautiful young woman riding a pink skateboard.
A commuter train makes a left-hand track change to change direction.
A beautiful Asian girl with a white rose in her black hair. She is holding an open blue umbrella over her head.
A man riding a motorcycle on the street.
a group of people holding wooden utensils a smiling at he camera
A bear made out of gummy bears in a candy store.
This aerial shot shows several people using a cross walk while holding umbrellas.
A group of people sitting on a couch in front of a cluttered table.
A white bed topped with pillows sitting next to a wooden night stand.
A boy is playing tennis with other people in the background
Many people on the beach with large colorful kites flying in the air.
A women is holding an ID and holding a pair of scissors to it.
The elephant is walking outside by himself along the wall.
A woman with nice legs laying next to a purple umbrella.
A group of teddy bears all dressed in Pilgrim and Halloween outfits.
A man in light clothing stands near a boy with sunglasses and jeans and they are both by a white glider.
Display of ornamental vases and figurines with oranges stacked on stands.
Athlete in motion during attended competition on gray and blue court.
A large jetliner flying over a body of water.
A kitchen with stove, refrigerator, and cabinets in it.
Two people riding bicycles alongside the river on a sunny day
An older gentleman flies a kite on the beach.
A variety of items are spread out on the bed.
a bathroom with a sink right next to the shower
Two girls in pink robes standing in front of a television.
Trays of party food lined up on a table.
A copious amount of food are served up in the kitchen wares.
A white horse is out eating in a field
Three donuts piled together on a small plate.
An airplane on the runway either just landed or ready to take off.
The cat was laying in the sun on top of the zippered bag.
A train with two cars is on a railroad track that splits into several directions.
A desk nook area has a desk, a chair and a book shelf.
a man is arranging a set of appetizers on a tray
A train is parked at a depot on the tracks.
A man hitting a tennis ball with a racquet on a court.
a person riding a skate board at a skate park
A silver truck driving past a giant arch from a mcdonalds.
A man in green shirt riding on an elephant.
A man is wearing a robe and a tie.
A man is standing in front of a grill with an umbrella.
A young boy aims his video game controller as a man watches.
A group of cows standing around in an open field.
Orange and white cat laying down and chewing on some cups.
Woman on tennis court grasping racket with both hands.
A piece of pizza being held in a persons hands.
a red fire hydrant at the corner of a street
A green and red semi trailer truck front without a load.
A couple of men standing on a lush green park playing a game of frisbee.
the duck is looking over the side walk
A group of men standing next to each other.
A zebra in an open ground near a bench.
A toddler brushing his teeth and gums at the sink.
A group of zebras that are standing in the grass.
Man mid swing playing Tennis on tennis court
Boxed hotdog, fries and a drink are set out for daytime reading.
Wooden mantle holding two vases of flowers and a picture.
Tilted pic of a mountain road with a street sign.
A couple of people kneeling over a pile of snow.
A bird with outstretched blue wings is sitting on some bird feeder.
a kitchen with a table a stove and an oven
A red stop sign sitting on the side of a road.
A bed sitting in bedroom under a picture.
a living room with big couches and a ceiling fan
A person with glasses on the phone in a restaurant.
An elephant is standing in a grassy field in front of trees.
Four boxes of donuts of various descriptions on a table
The baseball pitcher has wound up his arm to pitch that ball.
A little girl is holding a Minnie Mouse umbrella above her head.
A man is looking at hanging fruit arrangements.
There is plenty of clutter by the computer on the desk.
A cat in a bathroom stands on the rim of the toilet.
a red fire hydrant with two nozzles on it
A giraffe is standing in a field with a group of zebras.
Someone who is holding a hot dog in front of a box of teddy bears.
a man in a uniform is cutting a cake
A man on cellphone and woman walking by building.
a teen girl sitting at a table with some pizza in front of her
The ingredients represented in the meal might include pineapple.
A small group of men playing with a frisbee.
Several people are swimming in a blue lake
A train emits thick steam as it moves on the rails through a flowing plains.
An orange tabby cat stands in a doorway with a bookshelf in the background.
A group of skateboarders standing around while another skates.
A family of elephants stand close to each other.
some yellow signs attached to a building wall
A variety of boats are shown in the water.
A woman speaks into her microphone while looking at the cow.
A green umbrella over some chairs and tables
The pitcher is winding up to make the pitch.
A very cute girl holding up some scissors.
A male and two females jumping to catch a Frisbee.
There is a train moving along a railroad track.
A couple of people that are sitting on a bench.
The man is watching hockey on his computer.
Man on a boat carrying large quantities of cabbages.
a parking meter that has been drawn on
A group of people standing around a white cake.
A white and black potted plant with a mirror behind it.
some kids are standing outside with an umbrella
A train car traveling on a bridge over water.
A boy with two marks on his back stands on a skateboard.
a surfer runs into the waves on a beaching with his surfboard
a tattooed man with a skateboard thinking about doing a trick
Two cats who are laying down on a bed.
A plate of food, that appears to a small omelet and other pieces of meat.
A dog that is sitting in a window.
A cake shaped like an elephant squishing a horse.
A WOMAN SITTING ON A BENCH EATING PIZZA WITH A LITTLE BOY
a pepperoni pizza sitting on an oven done cooking
A pitcher standing on a mound on top of a baseball field.
A man riding a snowboard down a snow covered slope.
A man kneeling down next to a little girl.
A dog with a frisbee in its mouth is jumping over a man lying on the ground.
A giraffe looking over the corral fence in his zoo habitat.
A horse and foal are standing in the meadow.
This is a picture of a black furry cat on a laptop.
The man is riding down the ramp on his skateboard.
A couple of people walking in a parking lot by several motorcycles.
A man holding an umbrella light on a beach.
A man in a red and white baseball uniform holds out a bat toward a baseball on a baseball field.
A man standing in a kitchen in front of a stove top white oven.
A small bathroom with a toilet and flushing system.
A living room with a fireplace and contemporary furnishings.
A pizza that is sitting on a table.
A cat in a chair peeking above the table's edge at a drink.
Leaves sitting on a street next to a parking meter.
Young man gliding along rail on his skateboard.
A mother and child carry kites through a park.
A blender with something in it to blend
A batter is getting ready to take a swing.
A man flying through the air while swinging from a pole.
A small green boat at a dock in the water.
A desert topped with whipped cream is sitting on a plate.
Two women who are riding in a horse drawn carriage.
A vase sitting on top of a roof top.
Pizza sitting on top of a table next to a couple of wine glasses.
a kitchen with a refrigerator a sink and a stove
Blue and purple vase sitting not he side of a white wall.
A boy eating a doughnut in a diner.
A line of traffic beside a metro bullet style train indoors.
A woman is on snow skis on top of a mountain.
A large black bear walking through a forest.
a bench dedicated to someone with a weird edge
She is eating a slice and watching the small countertop TV.
A river with rocks in the middle and a train trestle in the background.
A boy in a yellow shirt is riding the edge of a half-pipe on his skateboard.
A plane flying over the beach with a mountain in the background.
the man has returned a server of a tennis ball
A large Japan Airlines jet landing on a runway.
The back legs of a cat dangling over a keyboard.
there is a large wooden platform bed in this room
Residential bathroom with wooden cabinet and mirror next to shower.
A dog plays with a frizbee in a pile of snow
A man is standing up, taking a shot of the water, while a pigeon looks on.
A man wearing a bandana, holding a skateboard.
A woman is riding the waves on a surfboard.
A giraffe is in a field of grass eating leaves off a tree.
A black and a white horse are grazing in a green pasture.
Kites being flown from the water in the ocean
A man is riding a bike while using a cell phone.
a group of people are at a market
A room with a table, chairs and a doll in it.
The woman is eating breakfast in the kitchen.
This shows an innovative Apple device and a keyboard.
a small bus sits parked as a kid runs across the street
a building with some windows next to a street
A man surfing a nice wave on a bright day with a ship in the background.
A wet bear stands in the river looking for fish to eat
A white table topped with a flower surrounded by chairs.
a woman skiing down a ski slope in the slope
A smiling man stirring something in a kitchen.
a male with a beard a book and a child in bed
A bird sitting next to a dried cob of corn.
Man walking up the side of a mountain with his skis on.
an oven outfitted with several Christmas lights
A girl on a bicycle is stopped before crossing traffic.
Man sitting on chair in kitchen with baked pizza on table.
A little girl buying a small teddy bear.
four men in an office working on their computers
A skateboarder is riding the green ramp.
A skateboarder performs a trick in a skate park.
Several people are talking next to a yellow plane in a hangar.
A person points a remote control at the television.
A brown and white dog laying on top of a green field.
A red and black motorcycle with people in the background.
A boy that is on top of a skateboard.
Three giraffes tower above trees and brush as they feed.
There are small trees with oranges growing on them.
Older black and white photo of a woman playing baseball and swinging a bat.
A white frisbee laying on top of a dirt field.
Group of giraffes standing by a pile of wood in an exhibit.
Two brown bears walking on an unpaved forest road.
A bear walking on a fallen tree in the woods.
Two horses that are pulling a piece of farm equipment.
People on a tarmac board a Qantas airplane.
Up close to a giraffe in its natural habitat.
A red truck is parked on the lawn of this house
A man's feet resting on a skateboard
A child standing between two luggage carts behind a car.
People sitting around a table as someone puts stuff in a blender.
A city intersection displays a clock on a long tall stand.
Four giraffes encircle the palm tree within the fence.
a stop sign with some graffit on it
A lit birthday cake has some penguin candles.
A building displaying a clock showing the time to be 6 oclock.
Some very pretty whit bowls with some food in them.
A man is eating a peanut butter and jelly sandwich.
A black and white cat sitting on top of cabinets.
An elephant stands in weeds with trees in the background.
A man and woman sitting on a motorcycle.
A shirtless man reading a book and eating.
Park bench near tree during fall in open area.
Two people standing on the beach with a kite.
A man making a surprised face is getting a hair cut.
A young boy learns the meaning of the word strike.
There is a batch of doughnuts being made
a man sitting at a table with a plate full of food
a white horse is standing near a train
The bus is parked at the bus stop.
a man taking a picture of a truck parked next to a building
A group of young people standing next to each other on a beach.
A train traveling down tracks next to a power grid.
Three giraffes in a field with an Egyptian theme in the background.
Someone on a snowboard holding the bottom of it in mid air.
A gourmet style pizza with a variety of vegetables.
Cows graze in a field in front of a lake.
A room with a sunny window contains a bed and a desk.
A toddler holding an electric toothbrush to his mouth.
a close up of a clock on a pole with a wind tool
A white refrigerator and cabinets in a grey kitchen.
A partially eaten plate of eggs, bacon and toast.
Garbage and police trucks on a city street
A small gray goat standing on large rocks.
An orange and yellow flower sitting in a see through humming bird.
A yellow and orange fire hydrant in front of a building.
A group of snowboarders snowboarding down a mountain.
Man stands up on his bike and looks up next to a parked car.
A herd of animals standing on top of rocks.
A bus is traveling down a street near a building.
A few birds are on the roof of a house.
A woman sitting on a rail next to skis
A kitchen with a microwave, cabinets, stove and dishes on the counter.
A child skier standing at the bottom of a slope.
A teddy bear sitting on a tricycle on a sidewalk next to a flower bed.
A man standing next to a woman in ski equipment.
An acrobatic dog catching a frisbee mid air.
A blender is full of food being prepared to puree.
Girls walking in a park talking and taking pictures.
A group of people sitting around a living room together.
a couple of people that have tennis rackets in hand
A group of people sitting outside at a restaurant table.
A woman standing over a stove cooking food.
A little league pitcher standing in a field holding a catchers mitt.
A colorful doll-house bedroom with one girl doll occupant.
People walk across a footbridge that stretches over a river.
A person holding a dog who is looking at it's self in a mirror.
Overripe bananas on plates with breakfast food packages.
Two double decker buses passing each other on the street
There are several people riding mopeds and motorcycles traveling down the street.
A man holding a flying disc in a park.
A large man is holding a black suitcase.
An elephant throws dirt on his back with his trunk
Two giraffe, two zebra, a monkey, and two flamingo are searching for food.
a young boy wearing ski equipment in the snow.
A surfer is on the water and is waiting for a wave.
A herd of elephants walking through a lush green field.
A woman with a tennis racket tosses a tennis ball.
Police car parked behind a car illegally parked at fire hydrant.
A herd of elephants splashing and playing in a waterfall.
A group of people sitting at a table with beverages in front of a window with ocean view.
A woman with a pen is writing while a man in a tie is watching.
A bathroom scene with the sink and shower.
A cheesecake on a plate with a croissant behind it.
a woman reaching up her arm as she looks at tennis ball
Round mirrors above clean sinks in a public bathroom.
A man playing tennis, ready with racket in hand.
A photo taken in a mirror showing the side of a truck.
a man in a surfer suit walks down a street
A gray airplane with metal petals on the wings takes off from an airport.
A European tour bus with luggage on top on a brick city street.
A close up of a glass bowl full of small oranges.
A very beautiful woman wearing a black hat, black shirt and tie.
An ipod plugged into a dock inside of a kitchen.
A man sitting on a bench waiting to get a ride from a bus.
an elephant behind a fence at the zoo
A cat sleeping on a bed with its head on a teddy bear.
A person viewing a picture on their cellphone.
A meal with two plates full of broccoli and other items.
A refrigerator adorned with several magnets and clippings.
A few people are getting to know one another in affection.
A street light turned green on a dark street.
Small bird sitting on a skateboard posed in front of dark blue background cloth.
A man leading a horse around the town.
A sign that has a camel on it.
Color fruit is on a stand including pears and apples.
A giraffe standing alone next to some trees.
A man is holding a military medal in a bar.
A silver and green train stopped at a train station near kids.
A couple of knitting books sit on a couch.
Single zebra standing in a field of semi dried grass.
some blue and orange surfboards on the sand water and rocks
Small child in baseball uniform standing next to players.
A boy swinging a bat at a ball on a field.
The man is on a horse pointing his finger.
A small elephant lawn decoration near a plant.
A child dressed in random clothing standing barefoot in the kitchen.
A woman in short shorts standing next to a young man.
some people some buildings and some are flying kites
The back end of three zebras walking in a group.
A man in a red shirt motions toward his cell phone.
a corner of a building with the name of the street on it.
A man is checking his cell phone while snowboarding.
A sandwich in a basket accompanied by a beer and a lollipop.
The ships are all docked on the beach by the water.
Skiers on a snowy slope are high above a small town.
A dirty nasty urinal in a very dark rest room.
A family gathered at the table eating breafast
a black and silver trains engine and a car and grass
A steer walking down a busy market street.
A pizza with several toppings sliced and ready to eat.
A child dressed in a skeleton Halloween costume.
Teenage boy about to catch the flying Frisbee.
Soldiers with guns in the back of trucks in a parade.
A boat that has been beached on the shore.
A couple of hot dogs sitting next to a basket of fries.
Four meals have been placed on a table with beverages.
A photo of a couple singing karaoke.
Person in black surfing a wave near the beach.
there are two woman that are walking in the street under a umbrella
A black and white photograph of a skater performing a trick.
A herd of sheep grazing on a lush green field.
A group of people riding bikes down a street.
two high school soccer teams play against each other.
A silver fire hydrant stands in the grass next to shrubbery.
Two people with umbrellas stand at the fence looking over the water.
A woman stands in line at an airport.
A big vase with flowers near a cup and window.
A person in a park playing with a frisbee.
A television sits above a fireplace in a living room.
A single tall flower in a green glass vase sitting on a windowsill.
a close up of a bench surrounded by plant life
A black stereo speaker near a computer monitor and mouse.
A woman standing with a donut and a candy apple in her hands.
A red train sits on the rail road tracks.
a young woman sitting at a table resting her elbow on the table
An elephant in dirt area next to a booth.
Two giraffes eating leaves off the trees in the woods
A variety of fruits and vegetables sit on a table.
Young male baseball player in full uniform and glove alone posing.
a really sad picture of some men with guns sitting next to a dead zebra.
A small plane with the cockpit open and landing gear down
A woman is standing next to a display of giraffes.
A living room filled with lots of furniture and a TV.
The woman in red sunglasses is walking in snow with ski poles.
a close up of a zebra in a field of wheat
A group of people riding horses through a small village.
A sandwich on toast with potato chips on the side.
A brown bear is grazing in the grass.
A multi-colored umbrella that is blocking out the sun
There is a laptop on a crowded desk.
A tennis player is on one foot hitting a tennis ball.
A zebra grazing on dry grass in a field.
Variety of meat and produce displayed for meal preparation.
A red stop sign on the side of a building.
A black and red train engine with train cars behind it.
The lady on the bicycle is waiting for the light to change.
a person with one foot in a snowboard
a bike shop with various bikes in it
A woman is holding an umbrella over her head
A couple of guys playing video games inside
This is a meal made for two people.
a small little plate that has some fruit on it
A large pair of scissors on display next to plaques.
Delicious looking meal of vegetables, cheese and meat on bread.
A public bus near a curb on a wet day.
A red traffic light hanging on a street pole.
a shirtless male surfer is carrying a white board
A man in yellow vest on motorcycle next to a building.
A large tree sitting on top of green grass.
a person is sitting on a couch while on a laptop
A white bathroom with corner shower and tiled floor.
A sausage sits on a takeout plate with spicy carrots.
A bunch of books that are on a bed.
A large red truck visible through the rear view mirror of a car.
A young girls soccer team posing for a picture.
Two lines of bicycles parked on a brick surface.
A snowboarder mid-air above a ramp outside in the snow.
A polar bear goes bobbing for fish at the zoo
A cat lies in a crib next to a small child.
Man pushing a cart loaded with luggage in an airport check in line.
A red and yellow high speed passenger train rolling along the track.
A large, ancient looking clock tower rises above a neighboring structure.
A laptop on a table with a white cloth at an art auction in a hotel ballroom.
A white bird with wings spread under a cloudy sky
many people sitting on the ground with a big container in front of them
Stainless refrigerator and microwave on the counter of a kitchen.
A guy with headphones does a trick with a skate board.
A picture to people and horses in the water.
A baseball player holding a bat over home plate
A Christmas tree sitting inside of a living room.
A woman sitting on a bed talking on the phone.
A subway train with the doors wide open next to a bench and pole.
The clock face on the exterior of a building.
Some animals that are hanging out in the dirt.
A lady holding a camera up near a big black dog.
a small giraffe that is next to some rocks
A dog playing with a toy in the snow
A half full glass of red wine on a table.
A group photo of men and boys from the Goodmayes Boys School dated April 1929.
A white and brown dog laying on carpet under a desk.
I can see one tennis player but I cannot see the other.
A couple holding wine glasses and holding up a tag reading USQ.
Two soccer teams playing a soccer match in a stadium.
a group of people playing frisbee in a field
a cat laying down stretched out near a laptop
An orange kitten is hiding under a blue blanket.
Eight dishes on a platter, each with a different food item
A room with two side by side beds, one of the nightstand lamps are on.
An oven with fire in it and ashes around it.
a small child standing above a skateboard on a tiled patio
a black cat sleeping on some bags of carrots
A cat is looking at a cluttered computer desk.
Adult elephants crossing roadway with young in native land.
A young guy is surfing in the ocean.
Cars and a truck lined up across a train car
A man poses in front of some green wood panels.
A donut frying in oil along a conveyor belt.
Some hands are coming from the closet and reaching for a sleeping woman.
A pizza slice is being removed from a pie.
The umbrella is ready to be installed at the restaurant.
Man with ponytail digging out condiment for sandwich in hand
A plate full of food sitting on the table next to a fork, orange, cup and salt and pepper shakers.
The student is trying to relax on the floor.
there is a man sleeping on a mattress outside
A packet of ramen, remote control, cigarettes and a lighter on table.
A deser plate with cake ice cream and fruit on it.
A table topped with a toothbrush and other items next to a wall.
Cars and buses seen through the reflection of a window
Green cake with a pair of pink pigs next to it.
A young woman is eating a piece of pizza.
A clock tower at seven forty three in the afternoon.
Young boys walking on wet pavement with umbrellas.
A clear tube containing a flower sits on the floor.
Two men sitting on a couch one who is holding a remote.
Three colored beached chairs, yellow, red and blue by the ocean
Antique warplane surrounded by safety cones near person.
A couple of boats floating along a river.
a man is holding a baby and playing with a laptop
a street sign outside near a flag pole
a rusty flatbed truck sitting by a building
A black fire hydrant that has two exits.
An appliance is standing next to cabinets in a kitchen.
The red clock is displayed for the people can see
a close up of a slice of cake on a plate
A hot dog covered in cheese on top of a plate.
A cat laying on top of a pair of shoes.
A laptop on top of a box on a table
A picture of some food and some coffee.
A room with chairs and a couch next to a fireplace
A very dimly lit dining area with some pretty flowers.
A tennis player wearing all white reaches hi racket up to a ball.
Kites laying on the beach on a sunny day
a small candle lit beside a placemat and some glasses
A woman standing alone holding an open umbrella over her head.
There is a place of food on a white table.
A cat and some people on a grass field.
a train stopped at a train station with people near by
two cows in a body of water near a field
A cat sitting on a dresser with a person in the mirror behind it
A pallet holds a display of fresh vegetables.
Two geese and their babies stand together outside.
A military plane is flying upward in the sky.
People standing next to sheep and feeding them.
Rows of green bananas on a tree with big green leaves.
A young woman riding a horse holding a flag
Two boys sitting on a bed playing a video game.
A meal that looks like falafel and hummous.
Three sheep are grazing freely in the open field
A vehicle near a stop sign with a poster.
A living room minimal furniture and a large window.
A view of a bus stop from across the street.
a person dressed in ski gear in the snow coming down a mountain side
Dual digital parking meters are in place and waiting for a visitor.
A female soccer player sits in the bleachers holding her ball.
a black and white picture of a white man singing a song
A man and woman smile while standing beside each other.
There are several holiday teddy bears in a shop window.
Wall with tools hanging on hooks and two litter boxes under alcove
A girl sitting at a table full of bananas.
A man brushes his teeth with a toothbrush.
A tablet PC decorated with a picture of a girl and three baby pandas.
PIZZA, SPOON, BOWL, COFFEE POT ON TOP OF STOVE
A dog in a grass field with a Frisbee.
A person on the beach flying a kite.
An elephant is being taken down a road in the back of a truck
A black cat staring out the window behind a computer
A man with a black tie smiling and holding a white box.
A puzzle picture of a baseball player batting a ball
A cardboard cutout of two boys kicking a soccer ball
A pizza sitting on top of a white plate on a table.
An old fashioned refrigerator in a kitchen next to an old fashioned stove.
A mom and a baby who is holding a teddy bear
A white horse looking through the window of a tall brick building.
A big orange truck driving down a street.
A wooden bench written 'CITY OF LONDON' at the park
A man smiling while slicing into a cake.
A bed with white sheets and a night stand.
A stop sign at the intersection of fifth avenue and fifth street.
The brown dog is riding a wave on a blue surfboard.
A boy and a group of sheep walking away in dirt field with trucks in background.
A picture of a very nice clean living room.
A person with glasses holds a Frisbee standing in the grass.
Locomotive pulling cars on tracks in outdoor area.
a cute happy bright yellow and red bird sitting on a tree branch
A team of horses hitched and ready to pull a wagon.
A man riding a skateboard while a child sits on the front of it
a newly shaved sheep walks away from it shaven fur
there are any kites that are being flown in the sky
Two elephants are in front of a muddy waterway trampling in the wet dirt.
Zebras are grazing on grass by a car.
a row of three ambulances with white and yello paint
this kitchen is all white and all white appliances
A person sitting in a bed with a laptop before them
Someone is wind sailing out at the beach
A man is sitting on a park bench speaking on his cellphone.
A laptop in front of a computer on a desk and a blue chair with a colorful blanket on top of it.
Two men standing and holding video game controllers.
A 18 wheeler truck on a highway carrying a large over-sized covered load.
A WOODEN HAND MADE KEYBOARD WITH A MOUSE
A view of an airplane traveling across the bright sky.
A dog laying in the grass next to the sidewalk.
A baseball player is swinging high in front of the readied umpire and catcher.
a couple of people on the beach playing with their kites
A homemade pizza with toppings served on a plate
Two giraffes in a grassy field with trees in the background.
A flock of sheep are crossing the street next to the cars.
A couple is sleeping in a bed with red sheets.
A young girl smiles for a picture at the beach.
A parking sign and a fire hydrant.
A red stop sign sitting under a green street sign.
a close up of a bird on a beach near water
a girl dressed in red shirt and black pants playing tennis
A girl with glasses curled up under a colorful, crocheted blanket
Some women are talking next to some sheep.
A laptop computer and mouse on top of a desk.
The refrigerator and the kitchen is being cleaned.
Different kinds of food rest on a plate.
A hot dog lays on a white paper next to a can of juice.
The living room has two couches and an easy chair.
A woman on the beach has a pink hat and umbrella.
Horses and carriages are lined up along a walkway awaiting customers.
A piece of wood with bananas and forks on it
Man in white shirt and scarf throwing a frisbee.
a large field full of sheep out in the outdoors
There is a man about to fall off his skateboard
A group of people standing together for a gathering.
A long train yard full of different equipment
A man with a bunch of plates in front of him by a red house with an open door.
A tile bathroom with a large mirror on the back wall.
a person sliding in to home plate when the guy didn't catch the ball
Several potty pieces with a white background and blue design painted on and one is adorned with feathers.
A big city bus parked right beside a building.
Young black cat lying on desk with head on keyboard.
a close up of a baseball player with a glove
a man that has a wii remote in his hand
An applegate hot dog is placed in a bun.
A row of matching planters are arranged on an outside colorful wall.
Group of people walking through a city at night.
an image of a tray of food on a table
a case in a bakery full of doughnuts of different flavors
A vegetable succotash has cashews, broccoli and sauce.
a image of a dessert on a plate with toppings
A man with lots of tattoos sitting in front of a bowl of food.
Adult wearing white shirt and tie holding baby in outdoor scene.
a pair of gray scissors hanging on a nail and another black item
A horse is standing in the green mountainside grass.
A person is flying a kite on a beach.
a toilet in a wooden themed bathr oom is open
A clock on a tall brick and white tower.
A series of images of skateboarders skating and jumping.
a couch in the living room near some stairs
Trio of large birds sitting next to each other on wooden perch.
A painting of a woman sitting in a chair with a laptop computer.
A couple of small birds on a wooden pole.
This is a collection of different kinds of hot dogs and french fries.
Person wearing all white leaned up against a wall with a yellow sign.
A woman at a table in a restaurant
A black and white image of a young woman sitting on a grassy knoll using her lap top.
A person that is playing a tennis game.
A baseball game is being played before a crowd.
A mini refrigerator stocked with bottles and cans of alcohol and soft drinks.
A young boy holds a kite in a grassy park.
The young man races toward the yellow frisbee.
An orange cat licking a blue pair of shoes.
A close-up of a desert with cookies, ice cream and a cherry.
Two semi cabs are parked neatly beside one another in a park area.
a dog begging for food off a table
A living room with low lights, a couch and a tv.
A television stand has a television and vases on it.
A young boy holding a tennis racquet near a house.
A clock, bird with missile, american flag at an area that looks like a flea market.
Three women at a party posing for a photo.
A display of a man with striped tie and a bird on his shoulder utilizing two Instamatic photos
Three inset pictures including bottled water, small pizza, and cup of coffee.
A man riding a motorcycle down a street next to a train car.
Older man rides on a carriage pulled by two horses
Several men are unloading trunks from a Model T.
A tray with a hot dog, fries, ketchup and mustard on it.
A piece of cake is seen on a clean, white plate.
Small boy holding a kite over his head waiting.
A firetruck without emergency lights on cruising through an intersection.
A TV sitting on top of a brown couch next to a pool.
A black and white photo of a person surfing. The picture is from underneath the water.
A train with a red engine in the countryside.
A man riding a skateboard down a street in front of a red car.
A trio of men throwing a Frisbee in a field.
A motorcycle stood up in a forest with melting snow.
a green fire hydrant siting by a yellow pole
A pile of garbage sitting on the curb in front of a wall.
a few pieces of pizza on a pan
Skiers pause for a photo before hitting the slopes.
A woman plays tennis in a tennis court
A zebra standing by a log and container eating grass.
two stuffed teddy bears sitting in a chair
A cat stands alert on a park bench.
Two pedestrian walk signals are lit up at night.
A cow licking its side in an enclosure
Two female tennis players walking in opposite directions on the tennis court.
A man stands in front of a Jamaican food truck in a city.
An airplane flying a in clear sky above a light.
a man is skating around a cement skate park
A orange and yellow freight train traveling down the tracks.
A stew pot holding carrots, celery, and squash.
A blender has some sort of liquid inside.
A lady dressed with a pink hat and unique clothing snow boarding.
A green airplane flying over a lush green field.
Two children at a skateboard park under a blue sky.
A lamp that is on in the corner of a living room.
A man holding a tennis racquet on top of a tennis court.
A man dressed like a zombie with other zombies around him.
An older man and a younger boy play a video game.
A clock is shown on top of a building.
A small baby is biting into a banana.
A very tall clock tower towering above a city at night.
A man in glasses wearing a suit and vest.
a group of women gathered together side by side in front of a table with pastries on it
A man standing on a tennis court holding a racquet and a ball.
Three people riding ponies and horses in a residential area.
a woman and horse walking behind a giant pickup truck
An image of half a bathroom and half stairs.
A calico cat is laying on a laptop computer.
a man and woman are outside taking a picture together
An elephant and it's trainers interact with each other.
An arial vierw of a building with a clock tower.
A woman and two men are having a conversation.
A far off picture of birds flying above a field.
A man and two women with Wii video game controllers.
A couch that is in a living room with pillows on it.
There are three adult giraffees that are walking in the park.
many brown and black sheep bushes grass rocks and trees
Several women sit at a table tasting wine
A cat lays down around some stuffed animals.
a person on a motor bike drives down a street
Young man wearing a suit and tie standing inside a building.
there is a tall sign that is on the side of a building
A busy city intersection with people and cars
A close up of a clock reading 1028 and 54 seconds.
A train traveling past two cars on a road in a rural area.
a person on a surf board rides in the water
Two elephants bathing in a man made environment.
Various tools are sitting on the table together
A small bike laying beside a fire hydrant.
White sheep are grazing in a green pasture.
Male surfer on a red and blue surf board.
A mother elephant and her baby are standing alongside a dry water pool.
The view of green mountains and a valley from a cockpit.
A man and a young boy riding on a donkey while people move behind them.
A ORANGE WITH A WINE BOTTLE ON THE COUNTER
so many elephants moving near some waters in the forest
An image of a baseball player getting ready to take a swing at the ball.
A long river runs alongside the train tracks.
A street sign points in the direction of the road.
Several signs can be read at a pillar in the fence.
A large bear is sitting near a rock in an enclosure.
three people walking a dog in the snow
a guy standing by a fench with his skateboard
A mom and two smaller sheep in a large green field.
A women reading a red book in her bed.
A man riding a motorcycle with another person during a sunny day.
A table in a restaurant covered in plates and mugs.
The man is playing tennis at a very high level.
A fire hydrant sits in a small grassy island near the sidewalk.
An orange kitten laying in a chair with a stuffed bear.
A train is making its way around a snow dusted corner track.
Blueberry stuffed beanie teddy bear sitting on a table.
A black and white zebra stands next to a tree.
Assortment of laptop computers displayed on table with backpacks full of electronic cords.
Two pictures of a stoplight, one is green and one is red.
A large orange bus stopped next to another bus.
a couple of different types of signs on the outside
A group of beautiful woman walking down a street in bathing suits.
a large air plane flying in the sky
Several toy SUV's alongside a toy bus on a highway.
Two parents are helping a baby put on a hat.
Three horses are pulling a wagon full of hay.
A kitchen knife on a cutting board with vegetables and spices beside it.
A boy and a girl posing for a picture.
A variety of Domino's pizzas and a business man selecting a piece.
Two dogs playing tug of war over a frisbee
A gentleman laying on the couch while talking on the phone.
This bathroom is all white and has a framed mirror on the wall
Attractive landscape with picture frames and large white vase.
There is a man cutting something up over what looks like a homemade pizza.
a bunch of bananas hanging on a wall
A female sitting at a table cutting a cake.
A woman sitting at a table with a plate of food.
Large black towel sitting any Penwith hey with people looking at it.
A van is driving through an alley way.
A stop sign is standing on the side of the road in front of houses.
A white fire hydrant is in front of an old couch sitting on a sidewalk in front of a house.
A few mack trucks in a parking lot.
A person wearing all black does a one handed hand stand as he holds a skateboard on his feet.
a close up of a cat laying on a desk
A flooded street with the water up to the traffic lights.
A baseball player waits at the plate for the pitch.
A large green bus transporting passengers through a city
A kitchen with lots of counter space and a black oven stove top.
A table with a stack of orange cups by orange scissors.
A dog is standing on a tile floor.
A large red bus parked in a stationary position.
A boy skate boarding down some steps .
An angled photograph of people flying kites at the beach on a sunny day.
Two dogs are laying next to a bike.
A long silver train traveling through a wooded area.
A light red fire hydrant on the corner of a street.
A person crouching next to a pair of motorcycles
Busy stadium with many people outside near vendor trucks.
Two urinals in a restroom with multicolored tile.
A person watching a sheepdog chase a white disc across a green field with mist covered mountains in the background.
Several people holding umbrellas are lined up near a fence.
A stoplight and street signs beside old buildings
A tennis player getting ready to swing her racket.
a close up of a drink on a table near a laptop
Several pieces of ancient pottery and stoneware on display in an exhibit.
A woman standing in a room holding a Wii game controller.
a group of people with surf board standing on some snow
the ice cream vendor is talking on his cell phone
A pile of TVs sitting next to a brick building.
an image of street signs on a residential
A guy on a skateboard in front of a water fountain.
A giant cake decorated with round discs on a table
a woman on skis is standing in snow with her dog
A woman casually reaches up to hit a tennis ball.
A fat kid enthusiastically enjoying a pizza from a big pan.
An old rusty fire hydrant sitting in the grass near a picnic table.
A new kitchen that has just been built.
A sleek, modern toilet has a backlight and granite counter for storage.
A teddy bear posed sitting holding a book
A train running on train tracks through the wilderness.
A white toilet sits in a bathroom, with the lid open.
a bathroom with dark tiling in iit and a pink bathtub
A machine is on a folding table in a small kitchen.
A person riding a skateboard down a street.
A man kiteboarding over a large body of water.
A man working on a laptop computer at a desk.
Two people pulling a luggage cart down a sidewalk.
A white plate topped with meat and vegetables.
Skiers come down a snowy hill in a row
two glasses of juiced carrots and apples on a white cutting board
A man is seen in a mirror in a bathroom.
A person is holdiing a kite in a field.
A sepia colored room shows vintage furniture with a tendency to the frilly, including a bed with a curtained balcony and a chair, both in matching floral pattern, and a dress form.
a little tourist train pulling three cars of passengers
A mirror is shown with a man driving in it.
A moped parked in front of a yellow wall and traffic sign.
A flock of sheep sitting in the middle of a field.
A skier kicking up a spray of snow.
Yellow and blue fire hydrant in front of a movie theater.
A teenager does not make any expression as he rides a skate board.
A man holding two small green birds in his right hand.
There is a baby elephant with its parent
a truck parked on a beach near water
The neatly made bed is beside an open window.
a big grizzly bear looks toward the camersa
A renovated propeller airplane flying in a blue sky
A giraffe that is eating a piece of food near another giraffe.
A group photo has smiling people and one dog.
Brick houses with brown stairs stand near a wide sidewalk by a line of trees.
A large building with windows and cars parked below
An asian woman holds a sub sandwich near her mouth.
A pizza cut up into many pieces on a white plate.
A red truck with a trailer attached, is parked near a red house.
A plate of food with eggs, meat, salad and a fruit cup on it.
A small table with cups and saucers and a clock on it.
A boy flies a kite on a beach near colorful tents.
A very cute cat laying on a desk.
Several Billabong surfboards make up a nice display.
A cat looking at the television with flowers on the screen.
A group of people in a park playing frisbee.
An airplane hanging from the ceiling of a building.
A table topped with lots of different types of fruit.
A small child's bed sitting next to a window.
Tennis player with white outfit holding a racket.
A person wind sailing next to a person para sailing.
A man is prepared to get on a wake board
A horse pulled carriage on a open street.
a couple of bowls of food sitting on a table
A refrigerator is shut with black duct tape.
a man standing on a surfboard in the water
A large clock rests on the side of a brick building.
A picture of a vase with colorful flowers in it.
A giraffe walks the grasslands by himself at sunset.
A dog heading into the water near a horse.
A woman rared back at a tennis ball with a racquet.
a person at a table with a plate of food
A small child on a bed looking at a lap top computer.
A group of people are looking at something or someonr
A bride waits for something while holding her bouquet.
A white cloth with scissors, a needle, thread, and measuring tape resting on top.
A tennis player gets ready to hit the ball as a crown watches from the bleachers.
A white truck has a vision sign on it.
A clock on a steeple of a tall building.
a shop with some wine bottles sitting on a counter
The kitten is nesting inside the empty bowl.
A gondola like boat crossing over a bridge
A large clock tower with a roman numeral clock on it's side.
A woman on a court with a tennis racket.
There are three dishes and a vase with two roses on the table.
A boat sailing on a massive lake surrounded by mountains.
A woman in a long dress talks on her cell phone.
A white plate topped with a hamburger next to fries.
A man riding a surfboard in the ocean on a wave.
A LADY FEEDING HER CAT WITH A SPOON.
a man standing at the beach with a surfboard and a paddle
a white building and some people flying a kite
A guy standing in the grass is ready to throw something.
grandma watching two kids playing a video game
A bowl of soup and a sandwich plate on a table.
A photo taken from a boat with a long bridge in the background.
An average hotel room with twin occupancy capabilities.
A woman is eating a pita on the street.
A baseball player holding a baseball bat in a game.
A serving dish has meat and greens in it.
two boys with painted faces laying in a bed
Two men sitting at a table with plates in front of them.
Wooly horse and sheep dog face each other down
A white pitcher filled with orange and purple flowers.
A lady bent over with her tennis racket while another girl looks down court.
A grey and red train next to a train station.
A person standing in a bathroom next to a white toilet.
A counter with various baking ingredients that include bananas, butter and oats.
A small plane is dwarfed by the larger ones in the background.
A couple of dogs standing outside of a wrecked car.
Motocross rider displaying aerial tricks on nice day.
A male child swinging his bat at a ball, another child behind him as the catcher.
a man holds parts of a broken television
A lone bench sits atop a hill looking over the river.
Donuts are going through the mechanical glaze machine.
A white boat sitting next to a dock near a white building.
People sitting on the side of a street next to suitcases.
A group of baseball player standing on top of a baseball field.
A man wearing a brown suit and brown tie.
A train on some tracks with power lines above it.
A boy in a blue and white shirt playing tennis on a brown tennis court.
A toy town with a train on the tracks passing a signal.
A couple of sheep standing on top of a grass hillside.
A man on a stage with ski poles in his hands.
Chef stirring large pot on top of stove.
A young boy is playing tennis at the tennis courts.
A boy riding a skateboard and doing a trick.
Two girls compete in a game involving a frisbee.
The dog is sitting in a chair beside a bright window.
A close up of someone's feet on a skateboard.
A white dog is on top of a bed looking into a box.
Brightly colored oranges, pear and apple in a colander.
Suitcase containing many compact clothes for just one person
a person on a tennis court holding a rackett
Three men on a field playing a sports game.
A bunch of people walking on wet sidewalk by buildings.
A woman holding a tray of food in a kitchen.
The sink counter of the small bathroom is made of wood.
The girl is standing with her laptop in her hand
Three people on snowboards on the slope of a mountain.
A man standing next to his guitar case talking on his cell phone.
a small boy in a black shirt a brown and black dog and a bed
There is an airplane flying by a mountain.
A toilet stall with green marble walls and a painting.
a toilet a tub some pipes and a window
A black and white photo of a train pulling into the station
A lady is running with a tennis racket on a tennis court.
A meal of hot dogs and stuffed vegetables
a person cutting a cake on a table
A woman is sitting down with the light turned down low to take a picture of herself with her cell phone.
A couple of white horses walking along side a rocky hillside.
The motorcyclist is traveling down the busy street.
Park bench on snowy elevated viewing area above city.
A man in a green tennis outfit hits a tennis ball with his raquet.
a man that is standing up on a stage
A room with a picture on a wall and a vase near the window with flowers in it.
A train moving along a track, approaching a light signal.
a small toy truck with a cat peering through a window
Bed with yellow blanket against a wall with hard wood floor.
A group of people are painting a bench in the park.
The pitcher just threw the ball to the batter at the baseball game.
A classic clock sits on a wooden table.
A giraffe on the dirt looks tall among the trees.
a living room with couches covered by sheets
A man in a suit and tie is playing a key board.
a number of oranges in a tree on branches near leaves
A hat is sitting on the top of a bed.
A man eating a hot dog on top of a bun.
Several birds are standing in a large nest.
Two woolly sheep in front of a wooden fence and barn
A couple of trick planes flying by each other.
Guy in shorts and a cap ride along top of wall with his skateboard
A person skiing downhill in the white snow.
Two men looking at a plane on a runway.
two woman sitting on the ground one is on a cell phone
Two Asian men standing in a office with business suits on.
A bunch of used appliances sitting on the street
a clock attached to a green pole on a building
a sheep standing in the grass next to a fene
A row of passenger buses traveling down a lone road.
A black bear lying down near many trees.
a couple of houses that are next to each other
Several broccoli plants planted next to a wall.
Train cars sit on the tracks next to a platform.
A group of lambs are running in the opposite direction of a dog who lays barking.
Fluffy white cat laying on a lightly colored bed.
A living room filled with furniture and a flat screen TV.
An employ looking kitchen has a black refrigerator.
The bathroom is mostly a red color. It looks very old.
A plate of food with a salad and very large chicken sandwich.
an image of a cat next to the feet of a person
A green train sitting along side a train station platform.
A man lays in a hospital bed while holding a teddy bear.
A man stands behind the counter of a restaurant.
A skate boarder jumps off a curb into the street.
A lit up display of teddy bears of different colors and sizes.
A cap that is sitting on a blanket next to a remote control.
a couple of cats are laying on a bench
a group of people standing around a metal briefcase
Several types of wild animals grazing in an open field.
A man sitting at a table with a pizza in front of him.
A large long train on a steel track.
Baseball player preparing to strike ball from the pitcher during game.
The woman is in a ski racing down the path.
A vase filled with flowers sitting on top of a counter.
An old parking meter sets with time expired in front of a parked vehicle.
A large white polar bear sitting on top of a rocky ground.
A kitchen that has white cabinets and a white oven.
a close up of a child near an opened refrigerator
a bedroom with a large window cover with shiny curtains
Some traffic lights suspended over a road by some parked cars and houses.
A row of parked motorcycles on the side of a street.
A goat with red painted horns on its head
A refrigerator packed with lots of food and drinks.
A surfer falling in a wave with other surfers nearby.
A huge cargo ship sits empty in a bay reflecting blue skies.
A man that is sitting at a table.
A slice of pizza with cheese and golden crust.
The pizza is topped with broccoli and onions.
a bunch of plates of food no a table
A tower that has a clock on it.
A man surfboards on a wave in muddy water.
A woman is skiing near a bunch of trees.
A caution light and traffic cones set up to block a street.
a black cat is sitting on a green bench
A narrow city city features colorful buildings and a large green bus with cars behind it.
A man standing next to a beautiful woman.
a kitten laying on a bed next to some phones
A big piece of bread is placed on a white plate.
A small white dog begging at a door to come inside.
A doughnut on a plate and a banana.
A plate that has a cooked pizza on it.
a man carving the turkey for thanksgiving dinner
Three sheep graze in front of a barn.
There is an old street sign leading against a building.
a bear in teh middle of a grassy field
a green and white street sign and a traffic light
Traffic light signaling green at the train tracks
A cell phone held open in a bathroom.
A teddy bear sitting in a very unusual spot high up
A man touches a hammer to the center of a clock.
A group of three people sitting on top of a green couch.
A couple of military men cutting up a giant sheet cake.
A person eating food from a large white dish on a desk.
A man standing in front of a microphone wearing a suit and tie.
A cow laying on top of a grass covered field.
The side of an airplane that is parked, and an Air China sign on the side of the plane.
Shadows dominate the landscape in this dark, dreary scene.
A snowboarder is boarding next to a chairlift.
A woman in a tiara cutting a birthday cake at a party
a desk with a keyboard mouse monitor and a tv
A giraffe is crouching in the grass next to a tree.
A cat sits on the table next to a bowl.
two adults holding a baby while wearing ski wear and standing on a snow bank.
Giraffe looking through a set of bars in a cage.
a white building with a white clock and some trees
there is a red stop sign on this street pole
The tall zebra is following slightly behind the shorter one.
A skier is headed down the steep slope.
A surfer riding a small ocean wave on his surfboard.
A young woman is holding a cell phone open next to her face.
a brown horse with a white stripe on its head
A cat is sitting by a single shoe.
A single giraffe that is walking in a field.
A group of people posing for a picture.
A person is standing on the beach holding a kite.
A group of people in grassy field with kites in the sky.
Two women playing tennis on a tennis court.
There is a man interacting with a black dog.
A parking meter on the curb of a city street
A ceramic object with blue flowers on it.
The dog went all the way into the water to fetch the hat.
Cows and a sheep eating food from a red box.
there is a piece of cake and a fruit on a green late
There is a stop sign covered in snow.
a couple of people holding a martini in their hand
An airplane on a runway with another plane flying overhead and a truck nearby
A very tall white clock tower towering over a lake.
A corner of a rest room with a shower with glass walls.
Three sheep laying in hay in a gated area.
A group of people sit at a table with food.
A desktop computer monitor sitting on top of a desk next to a mouse.
A lot of carrots on a wood board for sale.
A man standing on top of his head while riding a skateboard.
A man dressed in a military style uniform shaking another mans hand.
A empty living room that has a table in the center.
A kitchen that has pots on the stove.
A large two story boat floating in a lake surrounded by mountains.
A person on a motorcycle is doing a wheelie
two white black and brown dogs are lying on a red couch
a vast, grassy field with animals in the distance
a gray cat is sitting on a wooden bench
An iPod with ear buds and a mouse near a book and keyboard.
A black leather case containing several pairs of scissors.
Several boats that are moored at a dock
a man standing on the corner and people walking down the sidewalk
A woman holds a colorful kite in a city park
a close up of a person playing nintendo wii
A commander cuts a cake at a military function.
A boy looking at the camera while sitting at a wooden table.
A large ship making it's way through the water.
A woman in a bustier holding a stuffed animal.
an image of two men standing in front of a Christmas tree
A vase with flowers sitting next to a glass tomato.
The lamps are on next to the pull out couch.
Black and white photograph of two people on a moped.
A kitchen with white cabinets and a stove on the counter top.
President Barrack Obama standing in front of a crowd while giving a speech.
A boy smiling as a large spider walks on his arm.
A giraffe standing outside of a building next to a tree.
The back of a moving truck that has a man standing on a lift with a royalty style chair next to him.
A duck is swimming in the pond to the next destination.
A bathroom with some of the wall removed during a renovation.
a couple of little kids in baseball clothes stand next to each other
A group of people flying kites over a beach.
a person siting on a bench with a dog near by
a black cat sitting on top of a black suitcase on a bed
Two computer monitors, two keyboards and two CPU's on a desk.
A cat looking inquisitively over the top of a car seat.
planes and cars sitting on an airplane tarmac
Trucks and cars going down a commercial retail street in a city
A young woman is preparing to hit a tennis ball.
A man that is at the beach jumping in the air.
There are many books and magazines in the small room.
A framed wedding picture on a crowded wooden table.
A child holds a string over the water.
The train has spots of rust that are obscuring the graffiti.
A series of photographs depicting bathroom before and after minor changes.
Dark cabinets around a white two doors refrigerator.
A man holds a card and wine glass with a woman who also holds a wine glass.
A casserole containing broccoli and topped with cheese.
Woman standing behind open refrigerator door in modern kitchen.
A turquoise and orange station wagon with two surf boards on its top.
A tennis player in black shorts and white shirt looks up and holds back a red racket.
a train is passing over water on a bridge
A woman wearing a maroon sweater standing in front of crates.
A flock of black-faced sheep near a watering trough on a rural hillside.
Two giraffes standing outside while people watch them
Table centerpiece of a tall wine glass shaped vase with flowers
A man is holding a large piece of pizza.
The young child is close enough to pet the cow.
One horse has taken the lead in the race.
A skier struggles in deep snow with their lost ski.
A collection of different smart phones on a table.
Note with listed items on white refrigerator in kitchen area.
A man with a backpack and coat walks by a bus.
An magazine photo of a restroom toilet and sink.
A man choosing a piece of pizza from two boxes
A scenic view overlooking the water at night or early morning
Seagull flying through marina with many boats around .
A blue bird standing on the ground among large green leaves
A male skateboarder does tricks on a half-pipe course.
People ride on the back of an elephant while being guided along with other elephants.
A peeled banana on the front of a car.
Three people ski in a row in the snow.
A woman riding a wave in a wet suit on a surfboard.
A beautiful young woman brushing her teeth in a bathroom.
A scene containing a couch with flowers and a mirror.
An automobile with a timer attached on a city street.
An elephant placing its trunk on some plants and some people watching.
Several elephants dressed for the circus are in line next to people.
Two sheep sitting behind a fenced in area
A man flying through the air while riding a skateboard.
A close shot of a pizza plate with a rubber on it.
A bear observing something on the ground of a field.
A dog in a river chasing a red ball that is thrown into the water.
a person handing a child a plate of food
A bride and groom are cutting their wedding cake.
Two dump trucks driving down a two lane road with a white pick up approaching from the opposite direction.
Lady using oxygen in bed with a little dog.
An elegant kitchen has an attached stone fireplace
Two zebras in a field are eating grass.
there are many computer monitors and things on this desk
A man leaps in the air while on his ski board.
A woman dressed in a button up white shirt, suit and necktie.
The lid is up on the toilet bowl.
A dog is resting on the window sill of the building.
People milling about outside in a busy city
A young boy wearing goggles and a billed hat holding a stick.
A group of people walking under a leafy green tree.
A motorcyclist with a female rider in the back and a dog in a sidecar.
a woman poses in front of a giant pizza
A woman holding her hand over a giant pizza
Sun setting on a dark street and buildings.
Giraffe holding it's head mid way with a wooden gate behind it.
There is an elephant that is lying in the grass
A giraffe presses his head against another giraffe.
A plate with a pastry on it, topped with whipped cream.
The airplane is waiting at the airport for passengers.
A group of people on bicycles riding down a road.
A man and a woman stand in a field with cows and horses.
A bathroom in the process of demolition.
Black and white photo of a small air craft.
A person standing next to some old junk appliances.
a tennis player in a black shirt is wiping his face
A couple of plastic containers filled with lots of food.
A man is holding a banana in his hand.
a cow in a field looking into a camera
A view of a cell phone and a watch on a table.
A bowl with sliced avocado, eggs and tomatoes.
A empty water bottle sitting on the corner of a wooden bench.
A bathroom that has a broken wall in the shower.
A full course meal with meat and mixed vegetables.
A young man in a kitchen shapes dough into balls.
A couple of elephants standing next to each other on a dirt field.
A couple of dogs walking through a large body of water.
Two flat computer keyboards laying on a table
elephants in the wild surrounding a large tree
A large park with people flying kites in the sky.
A man with glasses on and a suit and tie.
A traffic light on a street corner with shops behind it.
A boy soaring into the air, doing tricks on his skateboard.
Smiling people are holding a large white snowboard.
A black cat and a "K" sitting on a green bench.
An attractive young woman holding an umbrella under a tree.
Grass roofed umbrellas on a bay with cliffs
A person holding a banana in front of a basket containing fruit.
two dogs playing in the snow as a one person wearing black uses a snow board to go down a hill.
Two cows are standing on the end of a boat
A picture of several street signs on a post.
A man walking with his surfboard on the beach.
a person on a beach with a kite flying in the sky
The cat stands on the edge of a bed looking at television.
The large scissors are sitting alone on the counter.
A pair of scissors and some stick like things in a bag on a wooden table.
two horses in a field of grass near bushes
Infant in a high chair eating a chocolate frosted chocolate cupcake.
A skateboarder jumping with two others behind him.
A painting that shows a vase with flowers and a table.
A person riding a horse, jumping it over an obstacle.
A family of zebras standing together at a zoo.
There is a train attached between two buildings as a walkway.
A black headed sheep sitting in a field looking onward.
Two people embrace while walking down the street under a pink umbrella
a room that has all kinds of christmas deco in it
A crowd of people standing around an old fashioned train engine.
A couple of very small cute kids in the rest room.
A BLACK AND WHITE PICTURE OF TWO WOMEN BASEBALL PLAYERS
A baseball pitcher delivering a pitch to a batter.
A Harry Potter novel is set next to a plate of eggs and toast.
a person milking a cow next to a wall
a woman watching a dog jump up for a frisbee
A zebra grazing on top of a grass covered field.
A large metal pan filled with peeled food items.
A woman at a baseball game talking on her phone.
White truck with painted words parked at night.
a white box with 12 sugar glazed donuts
A large black bear about to take a swim in a pool
A train has been painted with Christmas decorations and lights.
The large crowd watches a skateboarder descend a rail on a stair case.
A group of people having a picnic on the beach.
A little dog that has a frisbee in their mouth.
A small cup cake and a knife on a plate.
A frosted doughnut with sprinkles on a table.
A man in a yellow jacket is snowboarding
The flowers are in a vase on the table.
A close up of a vary unique looking vase in front of the tree.
A little girl standing and holding a remote in her hand.
A baseball player holding his arm up with a ball in his hand.
A pitcher in the middle of delivering a pitch.
some kind of room with some weird things in it
a bear partially submerged in a body of water
Young girl making funny face in residential home.
A table with a plate of food, utensils and some other items
A plate of cooked broccoli on a long white platter, next to a dipping sauce.
People inspecting a large, shiny semi trailer truck at a park
a couple of men compete for a frisbe
Artistic black and white photo of man on a motorcycle.
a cake made to look like two trains
A group of oranges stacked in a wooden bucket.
Chilled beverage in glass bottle next to orange halves.
A woman in playing with a green frisbee at the beach.
A stuffed bear sitting in a chair with napkins and cup.
A display of wild animals inside a building.
a big train passes under a big bridge
A man sitting on a bench next to a man.
Two kitchen stools sitting in front of an island in a kitchen
A bowl of fruit and a plate on a table.
A phone and a computer on a kitchen counter.
Someone having dinner in a dimly lit restaurant with wine.
A pole, light and traffic signal have all been painted green.
Cat sitting inside kitchen cabinet, near the dishes.
A red and white bus driving on the street
A living room scene with chairs, lamp and a clock.
A girl carrying a kite walks along a beach.
Two children in a fire truck amusement park ride.
A group of plates with grilled meat, bread, and appetizers.
A man in a blue blindfold reaches a doughnut tied to a string with his mouth.
A seagull wading in the surf at the waters edge.
People enjoy a day at a mountain lake.
Police tow truck parked on a city street in front of stores
Living room with TV playing and view of a hand in the picture.
People stand beneath umbrellas on a flooded road.
a dog jumping in the air with a frisbee in its mouth
A tree with a white low trees sign hanging off of it's side.
A man in a dirt field next to a group of sheep.
A baby girl wearing a red shirt holding a tooth brush in her mouth.
An upstairs bathroom is pictured in this image.
Woman laying down on a mattress at a store.
A skateboarder performing a trick on the edge of a ramp.
Man in a kilt and woman and white dress cutting into a cake.
A faded stop sign near a street side.
A snow covered wood bench in a park
Major League Baseball player taking a very fast pitch from the pitcher
A young toddler playing in a suitcase on a bed.
a group of people playing frisby in an open field
Woman kissing little girl's cheek under umbrella indoors.
A man is surprised by a very large doughnut.
People bringing in a loaded boat of vegetables to the market.
Two skiiers ski down a mountain in front of a village while it is snowing.
a close up of a pizza on a wooden spoon
A Bus Stop sign peeking out from a vined wall
Two green animal food bowls sitting on a tile floor in a room being refinished
Two people standing near the water holding surfboards.
The man is standing in the snow with his snow board.
a close up of a broccoli plant with leaves
A cow is standing near a fence in a field.
A sign that is standing in a parking lot.
A boy in white shirt playing with a Nintendo Wii controller.
a red umbrella is inside out in a city
A woman sitting on a bench while reading a magazine.
A dog riding on the back of a horse.
A catcher and an umpire near home plate.
there is a blue and black bus stopped at a bus stop
A young girl riding a skateboard behind a man on a bike.
some baseball players are playing baseball on a field
A black-and-white photo of a person sleeping in a bed.
Two people dressed a refrigerators walk down a crowded street.
a sink a picture a mirror and white tiles
Young boy inspects a picture on a table with construction paper materials.
A man is standing by a movie poster talking on his phone..
A sesame sandwich sits on a white plate with a cup of coffee.
A kitchen with a white stove top oven and a refrigerator.
A man sitting in a chair with a canned beverage in hand.
A motorcycle rider bends down on a track.
Several sandwiches sliced and neatly arranged on a white plate.
A street light pole with many street signs and warning signs.
The girl in a tan skirt is sitting on a bed.
There are electronics and other music equipment around a desk.
a person in a field with a kite flying in the air
Woman talking on cellphone in front of personal computer.
A red stop sign mounted to a wooden pole
A red and yellow fire hydrant in an open field.
A couple of giraffe standing on a grass covered hillside.
A guy on a tennis court holding a raquet.
an image of a woman at a ski slope
Rear-view of a horse as it grazes near concrete.
a cat is sitting on a white keyboard
The plate is loaded down with a lot of food.
A pair of leather chairs beside a table and matching couch.
a hot dog sitting on top of a mound of french fries
A young boy appears hesitant to eat some broccoli.
A woman with glasses making a call with a cell phone
Two bears laying against wood with a sign.
A plate that has broccoli and other food on it.
A blue and silver cell phone with an accessory.
They've gotten off the bus to stretch their legs for a few minutes.
Horses stand saddled in their paddock near the beach.
A man swinging a baseball bat on a field.
Chicken with sauce and broccoli is served in a serving dish.
A couple of boys playing frisbee against each other.
Large white birds with black beaks sit atop benches.
Two women who are standing under an umbrella.
A plate of food, bread and salad, sits on a chair.
a big boat is going down a small river
A caramel apple is sitting next to a jar of french fries.
yes we have no bananas we have no bananas today
a man gives children food to feed an elephant
A table covered in different kinds of baked goods
A bunch of dead, stuffed wild animals on display.
Two men loading up the back of a truck
There is a mug with a fork in it and an unidentifiable liquid.
two red double decked buses side by side
two people riding motorcycles on a street at night
A woman is looking at ribbon for children participating in an art activity.
A box of pepperoni pizza already has two pieces missing.
A room filled with people sitting at tables eating food.
A cutting board with pizza and a glass of wine
A woman with a purple umbrella stands on a brick street.
A man dressed in all white is posing on a motorcycle.
A mixture of food and drinks sitting on a table outside.
A man sitting on a horse in the sun
A man is sitting on a picnic table next to s ski slope.
A woman on a bed kissing a mans face.
A young boy puts together a kite on the floor.
A store has displays of pans and other things.
Several people in a large building that is filled with luggage tagged with yellow tags.
a perishing square tent set up with a bicycle
A carnival occurred on a beautifully sunny day.
A herd at of zebras are grazing in the field
A cow poking its head between skinny tree trunks.
a skier at high speed coming down the mountain
A bunch of vegetables and fruit arranged on a table.
A large slice of angel food cake sitting on top of a plate.
a baseball player swinging a baseball bat at a game
Two guys in suits are having a conversation at the couch.
A large truck driving down a city road.
a whole bunch with luggage standing outside
Multiple people standing in the water on a beach.
Two airplanes lined up on pavement near a building.
A man lounging in a computer room with a laptop on his lap.
A man carrying a kite while walking on the beach.
A young elephant walking in tall grass behind a larger elephant
A snowboarder leans into the snow with their board.
A lady with green hair and red boots sitting in the grass near a horse.
a man looking at the chocolate on his fingers
A group of children running after a soccer ball.
Woman approaching the door of a train at a station.
A group of people sitting on a bench in front of a restaurant.
A lot of animals that are in the grass.
some people are walking down the street with each other
A nutty cake is sitting in the grass.
A car sitting in the middle of the grass in the rain.
A lot of boats parked in a large body of water.
A man in a police uniform sitting on a horse by a traffic light.
A flipped image of 2 toned room with a small chandelier.
Light green and white painted fire hydrant with people walking in background.
A man and a woman sitting on adjacent couches focus on their laptops.
A golden bath area with a chandelier and blue and white bathtub.
The clock is below the dome of the tower.
A close up of a full cooked pizza pie.
two elephants are drinking some water on a sunny day
A small glass of liquid sits on a table.
A sandwich and salad on a plate sitting on a black table.
A woman is getting ready to hit a tennis ball.
Two motorcycles are parked next to each other.
A professional baseball player about to pitch the ball
A modern kitchen with a large window by the sink.
there are two men riding a motorcycle and holding a umbrella
Two racks on top of a white counter topped with cup cakes.
A person with a skateboard on a ramp.
The little girl is standing between the low shrub and the fire plug
A man and a woman beside bicycles with orange train cars behind them.
A snowboarder riding in the air above the snow.
A man and woman in the middle of a conversation.
A woman skier in costume at the beginning of a race.
A store window with stuffed teddy bears in it
A man bent down fixing a toilet .
Group of motorcycle riders being led by a police car.
Red passenger train passing over top of a bridge.
A small coyote is seen in the back of some tall grass.
A large red chair in front of a building.
A man is on snow skis on top of a mountain.
A baseball player is ready to swing at a pitch.
A woman serves out a sauce for her dinner party.
A young man is preparing to throw a Frisbee.
A brown and black dog holding onto a couple of crushed water bottles.
a nice black back splash a plant some body oils and a black Kleenex box
A beautiful young woman laying on top of a bed next to a dog.
Large pizza sitting on a table next to beer glasses.
A fire hydrant with a blurry view in the back of it.
An infant is sitting in front of a computer.
A cook placing two pies in the oven.
A group of people standing around each other in front of a building.
A skateboarder performs a trick on a small ledge.
A boy on his skateboard at the top of a skateboard ramp.
a women that is playing tennis on a court
Very small remote control that fits in the palm of your hand.
A huge elephant is walking down the road.
A woman standing next to a man while wearing a short dress.
A MAN WITH KIDS ARE ON THE FLOOR
A kitchen with an island that has place settings
A moose is getting some shade outside an old building.
Jockey on black horse being walked around infield.
A person cutting into a plate of food on a table.
A long train is going down one of many tracks.
Several stacks of different types of books on a bed.
A giraffe laying on lush green grass next to trees.
Two glazed and one chocolate doughnut placed on a napkin.
a police officer rides a motorcycle on a walkway
A child stands next to a window near a bear.
BABY IN BLUE JEAN OVERALLS HOLDING A CELL PHONE
A view of a Sony remote, next to a laptop.
A person on a skateboard is riding up a ramp
two people riding skis on a snowy slope
A baseball player up to bat swinging at a baseball.
A little girl laying in bed holding a book next to a black cat.
A woman cuts a cake while two dogs watch closely.
A fritter and a donut on a white bag next to a donut box.
Some chefs working together in a big kitchen.
A picture of a person brushing her teeth.
The pizza is topped with very unusual ingredients.
Bicycle parked at meter outside large building with column.
Three of six people standing and sitting at a restaurant table are on cell phones.
A brown teddy bear sitting next to a wall with a painting.
A small room cluttered with piles of books, a portable TV, and stereo equipment.
A yellow rectangle sign stating that pedestrian priority crossing is ahead.
A restaurant clock displays the time of ten twenty.
THERE IS A METER POST ON THE STREET
A group of men that are in the back of a truck.
A man in a orange and yellow outfit juggling tennis rackets.
A sign that is on the side of a building.
A horse wearing a pink hat pulling a carriage.
Many people are scattered together near an Orange stand.
Two men playing a video game inside of a room
A woman riding a surf board through the waves.
A pretty young woman walking a bike with a small dog in a basket.
A man standing in front of a brown horse.
A very big group of happy looking people posing together.
Different kites flying around in a field with a bunch of people.
A wall with a black and gold clock and walkway above.
A plate full of a lot of good food ready to eat.
A slice of cake with icing on three sides, a knife and fork beside it, on a wooden table surface with a knot area visible in the wood.
man jumping up super high in a grey jacket
A person on a sidewalk holding a kite for the camera.
A very big pretty green vase with some flowers.
A polar bear standing near a tree on grass
A kitchen island has a farmhouse sink on it.
A sheep looks at the camera, by the side of the road.
Two pieces of bread coated with a dark brown spread.
The train car is used as an office by railroad personnel.
City scene of cars at sunset going past stoplights.
A red and white street sign that reads "no parking any time."
The towel bar is above the toilet in the bathroom.
Baseball batter hitting ball standing near catcher with mitt.
Two skiis and poles stand upright in the snow.
This kitchen table has fruits and vegetables on it
A cluttered room with a televisions that is surrounded by shelves that have various games and supplies all over them.
A view of a narrow kitchen with the only light coming from a glass door.
A woman standing on the sidewalk, looking at her phone.
A tall clock sitting next to a barren tree.
A vase that has flowers inside of it on a glass table.
A man in a blue shirt, blue hat and gray shorts playing tennis.
A person is near a row of luggage carts as one man pushes a cart.
A boy blowing out candles on a birthday cake.
A small locomotive on small train tracks with people inside.
A girl is standing against a wall in a room.
A breakfast plate of scrambled eggs and fruit.
Baseball player swinging a bat during a game
a large plane is parked at the runway
A man in a wet suit on a surfboard in the water.
Clock tower sitting in a pier with clear blue water.
Large group of motorcycles on brick street with trees
Woman standing on a surfboard in calm water.
Man riding a horse in a foreign country.
Woman on a bus looking out the window at another orange bus.
A rusty parking meter that is empty
A woman with blonde hair sitting at a bench in front of a building.
a man is riding a snowboard in the snow
A giraffe hiding behind a grove of very tall trees.
An elephant with no tusks walking in the woods kicking up dirt.
A person in a baseball uniform about to catch a flying baseball.
A pizza that is sitting on a table.
A man eating a hot dog and holding up a dollar bill.
A plane up in the sky viewed from below labeled "Cityjet.com"
A cat on the toilet peeks its head into the bowl.
A group of people gathered around a table outdoors having a meeting.
There are several people in this funny boat.
A man slicing pieces of bread with a knife.
A stack of pancakes covered in blueberries and whip cream.
A man is standing close to a tv playing video game bowling.
Two elderly men preparing a motorbike for a journey.
The motorcyclists turn the corner of the road next to the home.
A cat is playing with the bottom part of the umbrella
A traffic light and cars on a street.
A bride and groom teddy bear each in a coffee cup on a saucer.
A laptop computer sits on a girl's lap.
A street sign that reads, "right turn only."
A baseball player is preparing to swing while several people watch.
A man sitting behind a group of different wines ready to taste them.
A black cat rubbing up against a woman laying on a surfboard.
a person walking on a train station platform
A long train traveling past a forest near a road.
a herd of elephants walking down a path in some tall grass
A silver railroad train traveling down the tracks
A man with glasses showing off two cell phones.
A dog looking cautiously at its reflection in a mirror like object.
A man using his laptop sitting on the balcony with a water view
Plate of food with a variety of vegetables.
A blue bullet train stopped at a train station.
A red fire hydrant between two potted plants.
What can only be described as an interesting and presumably authentic dish.
The man has a tennis racket in his hand.
A large jet liner sitting on top of a runway.
A batter, catcher and baseman during a baseball game.
The train drives between the forest trees.
A green city bus traveling by a parked truck.
A woman is using the ingredients to make sushi.
Two men in a living room holding the Nintendo Wii remote.
A clock with roman numerals hanging on the wall next to flower patterned drapes.
A tray with carrots, snap beans, mash potatoes and an egg.
A dressmakers dummy with hat, coat and tie.
A plate of food has carrots and broccoli.
A mini stagecoach being pulled by one horse and driven by one driver.
A young girl holding a tennis racquet on a tennis court.
A dog is in mid air with a frisbee in its mouth.
A skier in the air coming off a jump with a mountain in the background.
A cutting board topped with fruits and vegetables.
A pizza in it box siting on a table with a side dish.
A little bird standing a the twig of a tree.
A polar bear laying down on rocks by some water.
A woman sitting by a man at a restaurant eating food
A group of young men standing on a sandy beach.
People sitting and walking in the patio and grass area of a building with tented sitting tables and lawn chairs.
A man serving a tennis ball on top of a tennis court.
A white toilet sitting on a sidewalk outside.
Multiple skateboarders in the same outfit ride in a demonstration.
A fit young woman enjoying a game of tennis.
A decorative cake with several layers and an animal on top.
A brown dog laying in an open suitcase on floor.
A man bending over on a tennis court.
A slice of cake baside a fancy beverage on a wooden tray.
a car with luggage bags on the roof and in a trailer
A couple of men standing next to each other holding snow boards.
The bathroom is equipped with many electronic devices.
a person standing with a tooth brush and tooth paste
Two giraffes are standing together in a field.
a small cat gets petted in front of a laptop
A cardinal sitting on a small branch of a cherry tree.
There is a man wearing a dress shirt and tie.
A man about to sit at a restaurant table with a woman.
Many people around a chocolate birthday cake with candles.
A man riding down the side of a skateboard ramp.
A man sits on a broken toilet as people walk by.
A person flying a kite on a sunny day.
A couple of elephants standing next to each other.
A rainbow that is above a street corner.
Swans gather in the middle of a parking lot.
The skier is repairing his ski on the slope.
Four dishes of food are organized on a counter.
a kitchen with a double sink, stove and counter top
A small child is enjoying a donut at the table.
These two people are using the phones at a parade
A paper plate holding a piece of cake.
A beautiful young lady standing next to a man on a tennis court.
A clean white bathroom with a simple mirror above the vanity.
A man standing next to friends eating food.
A bathroom toilet with a phone hanging on the wall.
a guy that is on a surfboard flying in the sky
Signs and wooden poles stand in front of houses and lawns.
A mouse pad sitting on top of a desk under a mouse.
A couple of trains move side by side down the tracks.
A man in a yellow shirt stands in a dirt circle.
Two horses standing on the grass near a body of water.
Two giraffes are in the foreground and there is a zebra in the background.
A young man riding a skate board up a ramp.
A small horse with his eyes closed standing on snow covered ground.
A bottle of liquor called Granite next to a half-filled glass.
A flock of sheep standing around in the middle of a pen.
A mans face coming out of a chili dog with a fez.
Several boats in a river with people in each boat.
People sitting in a subway station that is in black and white.
Two kids are holding sprinkled doughnuts at the table.
The man is sitting down resting before his tennis match.
A bowl of beans sitting on next to a sandwich.
Six people in a boat rowing on a body of water.
a plane flying by below a slighly cloudy sky
Old style bed has a cross on the headboard
A dog jumping up in the air to catch a frisbee in it's mouth.
A group of young ladies kicking around a soccer ball.
Two back-lit computer monitors and a keyboard and mouse.
A beautiful woman sitting at a table next to two pizzas.
There is a person jumping high on a snowboard.
A big orange cat sitting on a wooden bench.
A child sitting at a table with a hot dog.
hungry dog inching it's way toward the donut.
A brown ottoman sits near a black counter in a vacant room.
A pretty young lady carrying two large donuts in a restaurant.
A woman is getting ready to dive in to some donuts while two guys watch.
A couple cut their wedding cake while the bride makes a face for the camera.
A large animal laying on top of a lush green field.
Rows of books on bookshelves in a library setting
A room with two woman, a dog laying on the floor and table and chairs in it.
A healthy meal with various fruits and vegetables.
A man that is on the side of the wall with a skateboard.
An adult and young horse interacting in a field of grass.
two trains on a track near a platform
A dog is in the air catching a frisbee with a crowd watching.
a group of people stand by watching a group of elephants
Man with racquet about to hit ball tennis ball.
A man riding on the back of a white horse.
kids are enjoying a nice game of soccer
A man getting ready to take a picture in a field.
Several people in a canoe with oars on the river.
A tower that has a clock on the side of it.
A large clock is next to a pillar.
Cat staring at something while sitting on porch.
a woman plays a video game in a living room
a man snow boarding on a ledge with a snowy field behind him
A woman walking in the rain with an umbrella
Various toys and items on carpet that includes wallets and a camera.
Person holding a string with a white kite on the other end.
Young skier posing for photo in alpine ski area.
A baseball player holds the ball in his glove using his other hand.
A red motor bike is being repaired in the driveway.
A little boy on a skateboard on the road.
The long plate has cookies, fruit, and chocolate on it.
A group of people in a living room playing video games
A man in white jacket rowing a yellow surfboard on water.
a person that is riding around on a horse
A woman walking in a muddy field carrying an umbrella.
There is a birthday cake covered in this guys face.
Several people who are waling on a dirt road.
a nicely decorated living room with a big mirror above the fireplace
A person holding a little girl next to a sheep.
A town full of street signs connected to a building .
Fish, small potatoes and broccoli are arranged on the plate.
a large black sheep who has been shaved
The large detailed cathedral has a clock on it.
A ship in the ocean with a seagull and another bird standing on things on the boat.
Three helicopters are flying through the clouded sky.
cows with ear tags standing in a field
a laptop projecting an image on to a flat screen television
a person cooking a pizza in an outdoor grill
Parasails in the wind in front of a bridge on a gloomy day.
Two men on bicycles riding on the street
A group of skateboarders watch a skater perform a trick.
A rear view mirror view shows a truck coming up behind.
This is a traffic light signaling green in a downtown area.
A man jumping over a blue park bench.
A small infant holds a soft toy bat.
A frisbee that is laying down in the sand.
A man with wide eyes eating a muffin.
a giraffe grazing in a high line of shrubbery.
A batter, catcher, and umpire anticipating the pitch.
A big boat on the water near the shore.
A woman standing on a tennis court holding a racket.
there are two urinals in a public bathroom
A silhouette of a horse is seen against the back drop of the sea.
One lonely person on the platform waiting for train to open for boarding
A tennis player prepares to hit the tennis ball
A black bear walking through a zoo exhibit.
A cat sprawled out over the top of a laptop computer keyboard.
People walking along snow and trees with skis on.
A woman walking a gray horse around a field.
A dark vase is holding pink flowers in front of a window.
A parking meter reads "90" minutes on the window.
a man being feed a cake seated on a yellow chair
Two briefcases are stacked up on a desk chair.
Three horse and buggies are parked out in front of a building that has three steeples.
a woman writing something down on paper while the laptop sits on the table
A green parking meter on a city street.
A group of people on bicycles next to a passing train.
A woman is getting in her car on a busy street.
An empty classroom with four unoccupied desks and writing on a chalkboard.
People are standing by a small passenger train.
A elephant being ridden by a little boy.
an image of a man riding on a skateboard
two computer monitors are sitting on the computer desk
A train on one of multiple parallel tracks passes under a bridge.
A pink and a blue toothbrush are on a white background.
A person on some skis in the snow.
A person on a skateboard going up a small ramp.
Guy jumps high in the air on his skateboard off the hill ramp
Man shopping at a grocery store at the produce section.
Three children posing with their tennis rackets at a tennis court.
a keyboard a persons hand a mouse and a monitor
One building has a clock and the other one doesn't.
a close up of a train on a train track
There is an image of a bear jumping on another bear.
Several trucks and cars are driving on a muddy road.
its raining so all the people are carrying umbrellas
a lady and a man getting ready to fly a kite
Motorized scooter parked in front of a gated roadway.
A computer screen and keyboard on a desk.
A stuffed teddy bear sitting next to hay holds a stuffed dog.
Boats are docked by houses on the shore side.
A young boy riding a skateboard at a skate park.
A man holding a phone that has a picture on it of a man holding a phone.
two people in a body of water near a pier
A couple of young boys riding on the back of wooden bikes.
A man is standing in the snow with skis and ski poles.
Wavy wooden seat bench with a sidewalk, grass, and stones
A dog lying down on a couch next to a nightstand with a wedding picture on top.
it is extremely foggy and theres a truck on the road
A recliner chair sitting next to a table with a lamp.
a person in a kitchen preparing food on a plate
Two men in black wet suits ride surfboards on small waves.
A tennis player running to hit the ball.
A man on stilts is holding a pink, polka dot unbrella over a woman in colorful clothes in a park setting and there is a crowd milling about.
A white bathroom has an aqua colored container.
A very small child on a surf board near a big fake wave.
A large airplane flying through a cloudy sky.
A woman starts to remove something from the oven.
A man watching a single engine plane make an approach to land.
A row of retro kitchen designs in various colors.
A kid with a baseball bat on a field.
a person standing outside of a building with an umbrella
A stove pulled away from the wall in a kitchen.
Two pink roses sitting inside of a blue vase on a table.
A military jet is parked on the runway of the airport
A group of women hanging around a long table
a close up of a large and a small zebra
A surfboard is recycled into a unique planter.
Several colorful trains are parked at a station.
A man holding a surf board standing on rocks.
A black cat resting on a bed wearing a tiny winter hat.
A black and white dog is catching a Frisbee in the air.
A man eating food from a napkin in his hand.
A giraffe with an object in its mouth.
A baseball player up at bat in a game in a stadium.
People walking in the rain on a city street some with umbrellas.
A group of sheep sitting on the ground around a bench.
A crowd of people standing on snow covered ground.
A group of people crossing a street while holding umbrellas.
A glass cup holding three toothbrushes next to a wall.
Two pictures of the same woman playing tennis.
The room has a large china cabinet, and two couches.
Two guys reach high to catch the Frisbee.
People walking their dogs on a park trail.
A large wooden clock by a window in a room.
A brown dog standing next to a toilet in a bathroom.
Pink and white flowers in a blue vase.
A group of three horses standing on a lush green field.
A group of people eating at a table raise their glasses
Two people walking and talking on a huge air strip.
A man riding a skateboard on top of a ramp.
this is a mulicolored stripe sun umbrella near a palm tree
A group of skiers trekking through the snow
A clock that is on the side of a tower.
A boy is holding a video game controller in his hands in a living room.
A stool is inside of a walk in shower.
Some very pretty giraffes standing by a big fence.
A sink is shown in front of a frame covered wall.
Two jets landed at an airport facility with many service trucks.
an old school bus sits in a field in a retro photo
A woman standing over a cake with a knife.
Two young boys play a game of frisbee.
A young woman plays with a frisbee indoors.
A baseball player about to receive a pitch in a stadium full of people.
A man near a curb with a bag and a box.
A picked off cake somewhat resembles the original design.
A crucifix is on the wall next to a clock.
A close up view of a small broccoli plant.
A police officer is riding his motorcycle on duty
A cat sniffing a small teddy bear laying on the floor.
Two birds are standing on park benches outdoors.
Someone chopping up foods and placing them in bowls and plates.
A tow truck hauls a jeep along a busy street.
Woman walking beside a man riding a horse in a yellow shirt.
Adult in suit and tie with markings across back of hands.
A small older bus parked alongside a roadway and another behind it.
The horse is tied to a tree in this snowy yard.
A living room consisting of windows, rugs, chairs, and a coffee table.
A man holding a kite next to another man.
A bird standing on the sand near a body of water.
The bathroom in the house is clean and ready to use.
a toilet with metal walls and a sign
A woman takes a picture of the newspaper with her phone.
A large red bus on a city street.
a lemon sitting on top of some fish with veggies and rice on the side
A woman stands behind her luggage next to a building.
A group of men holding up a white and yellow frosted cake.
A few birds wading in some shallow water.
Herd of cows, walking in a drinking from, a river.
a man in sunglasses and a pilots uniform looking down
A skateboarder grinding down a red and black ramp.
Two men sitting at a restaurant table holding up a tray of pastries.
A food entree is shown on a platter.
This kitchen has wooden ceilings and two tables
Few horses out in the distance eating grass
A picture of a black bag with a motorcycle in the background, on a dirt path.
a train with green and purple on it on a track
a small vase sitting on the table with flowers inside
A stop sign outside of a building with the word Liberty on it.
Two older gentlemen sitting on a public bench in a park.
a close up of a pizza on a pan
A woman with a dog throws a frisbee to a hill.
The inside of a bicycle store with numerous related items on display
two sinks a toilet mirrors and a counter
A baby sitting on a couch next to a brown teddy bear wearing a t shirt.
A dog standing next to a sheep behind a fence.
A man is in a field flying a kite.
A airplane with striped wings is in the air.
A man in snow gear in skis at the side of a snow slope.
Small desk with electronic equipment in office type room.
A plane is flying over a gas station preparing for landing.
A man spins around with his forehead on a baseball bat.
A group of men tours a building that has had fire damage.
A white sink and toilet in a small bathroom.
A man sitting on a sofa using a laptop with his dog curled up next to his shoulder.
A man and a woman dress up in costumes.
A horse is standing behind behind a fence
A red, white and blue train on the tracks beneath a mostly cloudy sky.
A person doing tricks on a skate board at a skate park
A motorcycle sits parked in the corner parking space.
A professional baseball player in a white uniform on a baseball field with a bat in his hand.
We are looking at a photo of buses in a demolition derby.
A man rides a snowboard down a snowy hill.
A baseball player takes a high grip on the bat as a catcher scrambles for the ball.
Two guys are excited to be catching a Frisbee in this tournament.
A glass coffee table sits in a living room.
The man wearing a hat holds a kite near many other kite fliers.
A green plate topped with pasta, broccoli and a salad.
Two shorn sheep graze on tall green grass in a sunny pasture.
A dog on top of a building yawning and an airplane above him.
Various contents laid out on a wooden table
a number of people near many bunches of bananas
A dog is chasing a frisbee in a park.
A man standing on a tennis court holding a racquet.
A toddler with a frisbee in his hand.
four children in a living room with one of the children holding a game controller before a television.
The men are playing a game of baseball in the yard.
A clean living room containing a couch, three tables and other decorations.
A female tennis player is holding the racquet, ready to swing.
Two plastic containers sitting on a table filled with food.
A man standing beside a robot with a camera around his kneck
a kitchen with a sink on a counter top
A woman holding an umbrella while a man walks behind her.
Men are eating hotdogs during an eating competition.
A bed sits in a white room with a window view of a nearby house.
A bus that is parked inside of a building.
A gigantic bird statue outside of a building
a street people cars trees and buildings and police
there is a man with a uniform at the supermarket
Two bananas that grew as one speckled banana
A older woman is fixing a younger man's tie.
Kitty fast asleep on its back on the bed.
A BED NEATLY MADE WITH A TABLE NEXT TO IT
a giraffe sticks out his blue tongue at zoo visitors
Two giraffe sitting on a dirty lot next to a forest.
A cat snooping in a bag on a bathroom counter.
Looking up at the belly of a jet airpline
A young many getting ready to serve a tennis ball on a clay court.
An old man is flying his kite in the middle of no where.
Dog curled up in the bed under covers
A living room area with couches facing a television and windows on the side wall and on the wall behind the television.
Several people are skiing along on a snowy field.
Some bottles and glasses of wine surrounding entrees.
A woman takes a bite of her sandwich.
Food and a cutting board sitting on a table.
Here is a stop sign with graffiti written on it.
a young man is doing a skateboard jump.
A cake on a table with other desserts and pastries.
A baseball player swings at the pitch being thrown.
A zebra standing in a dry field of grass.
This is a nighttime image of a church
A baby in a crib with a nighlight
The brown and white cat is sitting by the computer.
Three pies on separate plates on a table.
Outdoor subway train pulling into an empty station.
Sugar covered doughnuts are heaped in a pile.
A man standing on the grass preparing to throw a frisbee.
A man seated with a mouse, a keyboard and cell phone in front
A calf is laying in a pen as people gather outside to look.
Traffic is stopped on the road because of a red light.
A truck parked on the beach next to the lifeguard station.
A man is on his cell phone outside under an umbrella.
A colander sitting on a countertop in a kitchen next to a microwave.
A man in black shirt doing a trick on a skateboard.
A flight of red brick stairs which lead to an antique bench and a view of historical brick buildings.
a number of small boats in a body of water
A table topped with a giant penny and a tray full of vegetables.
A dirty kitchen stove with a timer located on at it's center.
An electric pole with a single light and two street signs next to a 5 eleven sign.
A yellow train parked at the end of the tracks
A guard with a dog walking around a bus in a parking lot.
A cutting board with a beet cut in half
A tall giraffe rests amidst green grass and trees.
A man is skiing in a snowy forest.
A tennis player dives for an incoming ball on the court.
Smiling man enthusiastically hugging a plush teddy bear.
A full view of some tall buildings in the downtown.
A bird standing on debris in the water
A young boy is skateboarding in the middle of a parking lot.
A man playing tennis with a racket in one hand.
A skateboarder riding on a park bench, on a cloudy day.
A black cat holding a Nintendo Wii controller.
Man smiling while displaying food item in kitchen area.
Two people stand by a motorcycle and a van.
A black and white cat walks near someone's legs.
A group of people gather near a motorcycle.
A man talking to another man sitting at a table in front of a laptop.
A kitchen with refrigerator, sink, and a curtain over a doorway.
Two teams are playing a frisbee sports game.
Carrots, cauliflower and broccoli sitting in a clear container.
A man eating food off of a plate
A tennis player hits the ball up from the racket.
A large jetliner sitting on top of an airport tarmac.
People sitting on a bench above the water.
A kitchen that has wooden cabinets and a kettle on the stove.
An orange and white kitten laying on a chair.
a cook standing in a restaurant kitchen while making a meal
A woman smiles while posing wearing skis and holding ski poles.
A woman in grey sweater lighting a candle at table with hotdogs.
A skateboarder performing a trick on a ramp.
Man and a rowboat next to a misty mountain lake
Several cut up carrots boiling in a pot of water.
A bus all lite up inside and out with diffrent colors .
A television and a cabinet on both side.
Parents and children dressed up as Santa Claus sit on a park bench.
A simple yellow vase holds two red and white tulips.
some people and a long thin boat water and houses
Baseball player coming in for the base, while catcher readies himself to get the ball first
A person on a skateboard and a person walking a bike.
A glass sitting on top of a wooden table. next to a keyboard.
Commuter buses parked in a lot outside an apartment complex.
a table full of vegetables and fruits stacked on top of each other
A plate with a sandwich with people in the background.
a police officer on a red motorcycle in the street
The child is pushing a cart full of luggage bags.
A young toddler is standing next to the high toilet.
A female nurse is standing next to a man in a bed.
a blue and white road sign written in japanese
A small elephant standing next to a wooden tree.
A lone person snowboards down an empty slope.
An open laptop computer sitting on top of a bed.
a street light on a street next to a tree lined median.
a close up of a bench near a ledge with a statue
An antique car being towed on a flatbed trailer
Two guys are having fun while playing the Wii.
The young person in a cap is grabbing his skateboard during a jump.
A dog attempting to use its mouth to pick up a pair of scissors from the floor.
this is a pizza and a fork on a table
A group of women with umbrellas and a couple without umbrellas outside in the rain.
a woman tosses a frisbee in a public park
A train on an overpass over a parking lot.
three kids at the field playing frisbee together
A tennis player is in motion with his racquet raised.
A man who is holding a skateboard in his hands.
a close up of a sink with many dishes in a tray
A man on a phone with a sandwich in his hand
A red fire hydrant sitting in the middle of a forest covered in snow.
Two little girls sitting in the grass with toys.
A kitchen scene with focus on the microwave and oven.
A dog sitting on its dog bed in the middle of a living room.
An adult zebra and a young zebra stand together in a zoo enclosure.
A man is on a paddleboard in rough waters
a man holding a teddy bear standing next to a basketball.
A man flies a kite at the beach.
A sandy beach topped with lots of people and tens.
One cat lying on the floor, and another with its front paws up on a stool
A man holding a plastic gun in his hand.
A train is passing along a hillside during the day.
A baby in pajamas outside, sitting on a skate board and waving to someone.
A street sign hanging from the side of a pole.
This is a photo of a hotel bathroom, all nice and neat.
A pen of five sheep surrounded by other pens.
A person in a large yellow and purple train.
a large air plane on a run way
A herd of sheep shares the road with cars and motorcycles.
A paper mache "bandit" piece of artwork stuck to a pole under a "neighborhood watch area" sign.
People standing in line by several food trucks parked on the street
A man holding a huge slice of cheese pizza with a crying kid on his lap.
Man on purple tennis court swinging at a ball.
A knight riding a horse and greeting a crowd as he clutches his shield.
A broom is hanging on the wall of a house.
Picnic tables under a pavilion in a park.
An assortment of thrift store objects, including two vases and some miniature carousel horses.
A man riding through the air on top of skateboard.
A young child is palying with some books.
A giraffe standing up with its legs crossed.
LOTS OF PEOPLE ON THE STREET IN A DIFFERENT DECADE
A tennis player reacts during a match in a tennis court.
A man is standing by a trolley station as one approaches.
A brown couch sitting in front of a flat screen TV.
a plaza filled with a lot of birds and some cows
The produce section of a grocery store
a couple of boats sit parked by a dock
A white and red moped is parked on the sidewalk.
A young woman with a smile on her face rides her bicycle down the street past some parked cars.
Four Blue Angel jets are flying in formation.
Traffic sign and barricades on roadway near large city building.
A zebra stands alone in some tall grass.
A blue and yellow train in the train station.
Several people sit on top of an elephant as another person watches.
A white toilet in a small tile walled bathroom
two people setting up a table of food
a girl is looking at her cellphone and a blond boy
a big tower that has a clock on top
Someone who is enjoying some rest on the edge of the pier.
A group of people flying kites on a field.
A man that is standing on a court with a racquet.
A sheet cake with a tractor frosted on it.
A very clean, modern and minimalistic style bedroom.
A woman using a Wii controller and playing a game.
Two giraffes in a zoo enclosure with a zebra.
A man wearing a glove pitching a baseball.
A woman with her face painted white and decorated with a dragon.
A traffic signal underneath some tall buildings.
A rear view mirror on the side of a car door.
A bedroom scene with focus on the window with the bed in the reflection.
Four men playing doubles tennis on a court.
A Chanel sign sitting behind a display window at a store.
A man riding a motorcycle with another man hang off it's side.
A dirt road through the woods with a rolling suitcase.
A black motorcycle is outside of a house
The children watch the man and woman cut the cake.
many people in a boat in the water and trees
Glassed in bathroom with the sinks on the outside.
A truck waits in traffic next to a wooded area in the city.
A man standing next to a cat in a kitchen in front of a laptop computer.
A bathroom door is open showing a shower with the shower curtain mostly open.
a brown table and chairs and a vase with flowers
Several students sit at a conference table with their laptops.
A photo of a jetty and a body of water.
A surfer wipes out as the waves break.
Toddler getting ready to hit a t-ball with his bat.
Young lady falling to the ground catching a frisbee.
THERE ARE TWO ANIMALS THAT ARE PLAYING TOGETHER
Large brown bear sitting next to rocks in open area.
two boys with a skateboard and a bicylce
A young boy holding a Nintendo Wii game controller next to a lego controller.
An umpire in the field, talking to the batter.
A group of people riding an elephant on a dirt road.
A group of trucks and cars are coming out of a tunnel.
A man walks past a weathered structure and parking meters.
A small hotel room with a king bed.
A male standing up with a Wii remote control strapped on his hand.
A guy is performing a trick on his skateboard.
A person standing on the river bank by bushes
A picture of an open air zone that looks incredible.
A man pulling a piece of something from a machine
A large stuffed bear is sitting on the ground with a cup next to it.
A man in a beige suit with graying hair.
a couple of vehicles on a busy city street
A man stands with his produce in baskets.
Adult preparing to catch flying disc in open area near trees and water.
People stand in line for an ice cream truck.
A man in a the middle of a bunch of cows.
A female tennis player hitting the ball with racket
People on a busy sidewalk, some on bicycles.
A fat ass sitting on a toilet with lady magazines.
A small white tow truck parked to another small white tow truck.
A man without a shirt squatting on top of a skateboard.
A man on a motorcycle driving beside a van.
There are signs on a cobble stone sidewalk
Black and white photograph of a man on subway with bicycle.
A stop sign in an older residential neighborhood is marked with graffiti.
a couple of large pizzas that are sitting on the table
The man is spraying down the toilet to clean it.
a bunch of people watch a person do a trick on a skate board
a man on a beach tries to fly a geometrically made kite
an image of a clock on a tower high in the air
A large black dog standing near an open suitcase.
A man standing behind a white frisbee on a green field.
A black-and-white photo with a colored red double-decker bus.
Line of people behind plastic fence with umbrellas
The street signs are clearly visible for us to see.
A pair of red scissors sitting on top of a piece of paper.
A baby feeding cake to a man with a fork.
SEVERAL PEOPLE STANDING AROUND APPEARING TO BE LOOKING AT SOMETHING
skateboarder in red helmet jumping on skateboard ramp
A person working at an airport, outside of an airplane.
A birthday cake for a child is sitting on the table with candles.
A dirty, overturned motorbike lays in the mud.
An airplane in the middle of a field with some jeeps parked near it
The front of a store that has a large teddy bear in the window.
Old suitcases piled to the ceiling on a luggage cart make art in an airport
A giraffe standing on a lush green field.
The white and black dog is in front of an open refrigerator
A small boy next to a table upon which sits a birthday cake shaped like a racecar.
A train runs down a track past run down buildings.
A man that is standing on a platform with a frisbee.
A black plate with a hot dog and fries
Two pieces of pastry sitting on a mat next to a spoon and fork.
A bunch of green bananas is on a tree.
A woman holding a video game controller and grinning.
A pan of some kind of food cooking in an oven
A man in a suit and colorful tie in a park.
A close up of a girls boots as she sits on the counter.
a black and white photo of a cow near a tree
Assorted vegetable along with cheese and nuts for food preperation.
Two tennis players are doubled in their pursuit of the two tennis balls.
A man on his skis on a snowy slope.
A comparison photo showing bathroom in regular view and in stretched version.
Small yellow container attached to a digital camera.
Two slices of square pizza on a plate with a fork.
a man in a tie holding a cup
A street scene of an intersection with a street light.
Three wild cows in a field on a nice day.
A small sink inside of a very clean and white bathroom.
a small machine is sitting by a cliff
A wall with words painted on the glass and people behind it.
A laptop sitting in someones lap and a dog lying on the floor.
A little girl posing for a photo next to an elephant.
A man is at an outdoor table under an umbrella.
A bathroom window reveals a snowy day outside.
Animals grazing in grass in front of an industrial landscape.
I THINK THIS IS A RECEPTION HALL AND ITS FULLY DECORATED
A red frisbee has been thrown by a man.
A blender filled with flower and eggs on top of a counter.
Colorful collection of fruits and vegetables with some type of "baby" decorations
A white boat on water with brick wall next to it.
A baseball player up to bat and missing a hit.
A park bench sitting in a snow covered field
A woman cutting thru a pastry on a white cutting surface.
A vase of flowers one being a large sunflower in front of a brick wall.
A woman biting into a sandwich with a happy look on her face.
A man sitting on a couch playing with a game system.
Two people walking down the sidewalk with a "wrong way" street sign directly above them
A couple of horses standing on top of a grass covered field.
An elephant is drinking with its trunk at the watering hole.
a close up of slices of bread on a table near a spoon
A woman with eyeglasses in a kitchen with bowls, spoon and glasses
A person is eating at the kitchen table.
Two women are facing each other and one is blow drying her hair.
a drawing of a big fancy court house
two elephants walking in an stone enclosure.
A cake with a train on a track and a ground made of cookies.
A baby is laying on a bed with the cat next to and a man is looking over in the mirror.
A supply truck in a snowy area driving towards a tunnel.
A bunch of carrots are on a plate next to broccoli.
A fire hydrant on a sidewalk next to grass
A stirfry containing broccoli, carrots and other vegetables.
A wooden bench surrounded by potted plants in front of a house.
a close up of a teddy bear on a balcony
The storefront of a bakery that has been painted green.
Three stuffed animals hanging on the structure of a train track.
Children get off a school bus as a crossing guard stands among them.
Two horses underneath a canopy of green trees
Group of mixed vegetables sitting on a counter top in a kitchen.
a close up of a plate with a sandwich
A carnival atmosphere is effected by these colorful stuffed creatures.
delivery truck dropping off delivery at train depot
A young child laying down in bed with one arm raised up that is wrapped up.
A woman in black jacket with umbrella on a sidewalk.
Different types of fruit are shown on the counter.
Two individuals sit on motorcycles on a busy street in the rain.
two people riding motorcycles, one sliver one white
two girls and a boy standing in a kitchen
a couple of birds stand on top of a rock
A man in a white shirt with a red tie is standing in front of a door way.
a couple of small beds are in a room together
A white bedroom decorated with low level furniture
People looking at zebra and cows behind fences at a zoo.
A man standing on one leg on a baseball mound.
This tennis enthusiast, not using correct form, is practicing on the court in the city.
A large eating and living area inside a house
A lady walking with an umbrella during the day on a rainy day.
A person on a skateboard on the ground of a park.
A person sitting on a bicycle at night outside of a shop.
Two different types of dogs sitting together on a bed
People are riding in a boat on a lake.
Two horses rubbing necks together in a field
A zebra is chasing another zebra inside an enclosure.
Two zebra standing next to each other in a field.
A white toilet sitting in a bathroom next to a wall.
A woman standing on skis and holding poles in the snow.
A GROUP OF SHEEP WITH MOST OF THEM IN INDIVIDUAL CAGES
An empty alley with a street sign at the end of it.
A sandwich that has several toppings on it.
The man is kneeling low to hit the tennis ball.
A lone giraffe bending over to graze within an enclosure
A man driving a scooter with two women sitting on the back of it.
A very up close picture of a sign.
Someone is holding a toy bear in the mans face.
A tour boat on a man made lake under a blue sky
A man hitting a tennis ball with a racquet.
A young boy is doing a trick on a skateboard.
A man working in a market surrounded by produce and meats.
A dog sits in a suitcase with a doll.
this is a group of people eating together
A player is swinging at the ball in a baseball game.
A blue doorway with a clock mounted above it.
a teddy bear sitting in a hanging basket
A man talking on the phone while he walks down the street.
The bear is wondering about in the woods.
Two wooden desks holding keyboards and computer monitors.
A man cross country snow skiing near a wooden post.
There is a young child sitting on the floor in front of the refrigerator.
This bedroom features a bed and chest of drawers.
Two men stand next to a horse near a bus.
A long bookshelf behind the head of a bed.
A large fire truck with a water tank on the side of the road.
A group of people carrying bags of luggage through a lobby.
a baseball player swinging a baseball bat at a ball
There are people riding bikes on the street.
A LARGE PAINTING ON SIDE OF BUILDING WALL OF TOASTERS
a small bird sitting perched on a chain link fence
Tennis players at match standing over net shaking hands.
A city street lined with very tall buildings.
A woman in white shirt holding a kite on beach.
A table with a sandwich, sandwich makings and glasses of red wine.
The unique meal includes both carrots and peppers.
a kitchen with maple cabinets and black appliances
A wine bottle is being used as a flower vase.
The alleyway is lined with many parked motorcycles.
a woman is walking down the street in a sweater
Woman eating a really large sandwich at a dinner table.
BEAUTIFUL VIEW OF A BLUE SKY TOWERING OVER WHITE CAPPED MOUNTAINS
a white plate with three donuts and two drinks
a boat docked at a wooden dock on a lake
A young man uses a fork to eat food.
Motorcyclists perform a pyramid stunt in a darkened auditorium.
A person sitting down in front of a laptop.
there is a young girl that is feeding a giraffe
Cattle grazing and eating grass while looking at the camera.
A child, wearing a cat costume and umbrella, stands before a brick building.
The little league ball player is posing for his picture.
Three men sitting on top of a green bench.
A bouquet of flowers is stuffed inside an arrangement of wine glasses on a table.
Baseball pitcher in the middle of a windup.
A vase sitting on top of a plastic pedestal.
A mannequin wearing a jock strap, unbuttoned shirt and tie
A couple of men sitting on the side of the street.
An old flip cell phone inside a cozy.
two kids battle over a soccer ball while on a field
A red motorcycle on display at a show.
A stuffed animal sits atop a barbed wire fence.
A man sitting in a car on a cellphone.
A tennis player on the court stepping backwards in preparation to swing
A bedroom with a fluffy comforter and lights above the headboard
this is a man skiing down a hill
An older male with white hair holding a flip phone.
a female tennis player diving to hit the ball
A red and white plane sitting on a runway.
A group of people standing around each other.
Mom has to help him eat his hot dog and bun.
A kitchen counter with some bananas and eggs.
A group of people who are sitting on horses.
A small vase of pink and yellow flowers next to a candle holder.
A variety of vegetables laid out on a kitchen counter.
It is out in the open with various things in viewpoint.
An advertisement for Samsung Galaxy Golden cell phone
A man wearing headphones looking at the camera.
Children in the snow with skies and snowboards.
an exhibit featuring various animals under a wooden roof
A big bear standing out in the shade and sun light
A city is lit up at twilight near a river and a clock tower is lit up in the distance as a large boat is seen on the river.
a number of giraffes in a field near one another
Two soccer player on opposing teams playing soccer.
An Asiana Airlines plane taxiing at an airport.
A man riding a red motorcycle on a street next to a crowd.
A blue street sign in an Asian language and English.
Pink lunchbox filled with fruit and vegetables and snacks.
A white refrigerator on the side of a road next to cars.
Various vegetables in a roasting pan in an oven
A giraffe walking through a lush green field.
A bowl filled with apples, limes and lemons.
A man riding a gray elephant holding a ball in it's trunk.
A bus stops on a street corner as pedestrians walk down the street.
a bridge lit up with some blue lights
He is heading for the beach with his surfboard.
A couple of kids looking out of a window on a subway car.
Two dogs are watching a television set intently.
This is a picture of a persons garage sale.
An elephant under trees in the night time
A chair and debt with laptop, monitor and a cat.
A black, brown, and white cat is near a laptop.
A teddy bear wearing green hat and jacket.
Several baseball bats leaning against a fence with a short hanging from the fence.
A person in red jacket skiing down a hill between trees.
A woman dressed in costume is sitting on the motorcycle
A woman on a tennis court is hitting a ball with a racquet.
A man in a traditional African outfit gestures while a black cow is in the background.
A lone skier is seen on the slopes on a cloudy day.
Children flank an old pickup truck in a parade.
There is a bird statue and clocks outside of an apartment building.
A baseball player holding a baseball bat over his shoulder.
A plate of food that includes meat and broccoli.
a person wearing an apron in front of kitchen appliance
The hot dog is loaded with many toppings.
A large jetliner flying through a gray sky under clouds.
A bunch of ripe bananas sitting on top of a table.
some baseball players are playing baseball and some trees
A man talking on a cell phone while sitting down.
2 zebras outside eating grass in a wide open space
A man in India herds a number of cows on the street.
A laptop and desktop computer on a desk with a light on next to them.
A group of baseball players standing on top of a field.
A train that is driving through some houses.
Cat and dog in the windowsill of a building.
A desktop computer is displayed at a wooden table.
A large group poses for a photo in their ski gear.
A man sits in the snow while breaking from snowboarding
A man standing and talking on a phone in a courtyard.
Automobiles stopped at an intersection because of a passing train.
A giraffe standing on a stretch of sand at a zoo.
a woman wearing a crown and a young boy smile at a table with a cake
An older man and a boy are on the beach with their surf boards.
A bench next to a lamp post on a cobble stone street.
Two parking meters that are nearly covered with snow
Cars present at an intersection with traffic lights.
A sign indicates when parking is off limits on West 25 12 street.
A Pizza with red peppers, zucchini and cheese.
A bird with a red face is standing on a rock.
A dog laying on the back of a couch.
a kitchen is decorated with american flags
a tropical bread on a branch surrounded by trees
A zebra standing in a dirt field next to green plants.
A colorful plate with a pizza sitting on top of it.
the people on the beach are flying kits over head
A man in white baseball uniform throwing a pitch.
A boy with a helmet on eating food across from a bicycle.
A large giraffe standing in a dry brush field.
Woman in grey and blue throwing a frisbee.
Dozens of people on a grassy field flying kites.
A man that is standing in the snow.
A cat is standing on a toilet with its front paws inside.
a small baby is biting into some food
Several pieces of pottery in the process of being painted.
Various types of flowers sitting inside of a vase.
A little girl holding a colorful umbrella next to a penguin.
A red piece of luggage sitting on top of a bed.
A black and white shot shows evergreens, bare shade trees, and bushes that slightly obstruct the view of a building with a low roof in comparison to its clock tower, which stands more than twice as tall as the evergreens, against a grey sky.
A very long street with traffic under some cloudy skies.
The men are racing on skis on the snow covered race course.
some white and brown signs a tree and a building
The corner of college street and 5th street
Miniature Poors on the side of the road in a rural mountain.
a "use crosswalk" sign on a post in front of a rain-covered street
a person holding up a cell phone
A
gitextract_nz69m5ai/
├── COCO_caption_prompts_30k.txt
├── DiT-ToCa/
│ ├── cache_functions/
│ │ ├── __init__.py
│ │ ├── attention.py
│ │ ├── cache_cutfresh.py
│ │ ├── cache_init.py
│ │ ├── cal_type.py
│ │ ├── force_init.py
│ │ ├── force_scheduler.py
│ │ ├── fresh_ratio_scheduler.py
│ │ ├── global_force_fresh.py
│ │ ├── score_evaluate.py
│ │ ├── scores.py
│ │ ├── token_merge.py
│ │ └── update_cache.py
│ ├── diffusion/
│ │ ├── __init__.py
│ │ ├── diffusion_utils.py
│ │ ├── gaussian_diffusion.py
│ │ ├── respace.py
│ │ └── timestep_sampler.py
│ ├── download.py
│ ├── environment-dit.yml
│ ├── models.py
│ ├── sample.py
│ ├── sample_ddp.py
│ └── train.py
├── DrawBench200.txt
├── LICENSE
├── Open-Sora/
│ ├── Dockerfile
│ ├── LICENSE
│ ├── README.md
│ ├── assets/
│ │ └── texts/
│ │ ├── VBench/
│ │ │ ├── all_category.txt
│ │ │ ├── all_dimension.txt
│ │ │ ├── all_i2v.txt
│ │ │ ├── prompts_per_category/
│ │ │ │ ├── animal.txt
│ │ │ │ ├── architecture.txt
│ │ │ │ ├── food.txt
│ │ │ │ ├── human.txt
│ │ │ │ ├── lifestyle.txt
│ │ │ │ ├── plant.txt
│ │ │ │ ├── scenery.txt
│ │ │ │ └── vehicles.txt
│ │ │ └── prompts_per_dimension/
│ │ │ ├── appearance_style.txt
│ │ │ ├── color.txt
│ │ │ ├── human_action.txt
│ │ │ ├── multiple_objects.txt
│ │ │ ├── object_class.txt
│ │ │ ├── overall_consistency.txt
│ │ │ ├── scene.txt
│ │ │ ├── spatial_relationship.txt
│ │ │ ├── subject_consistency.txt
│ │ │ ├── temporal_flickering.txt
│ │ │ └── temporal_style.txt
│ │ ├── imagenet_id.txt
│ │ ├── imagenet_labels.txt
│ │ ├── rand_types.txt
│ │ ├── t2i_samples.txt
│ │ ├── t2i_sigma.txt
│ │ ├── t2v_car.txt
│ │ ├── t2v_latte.txt
│ │ ├── t2v_pllava.txt
│ │ ├── t2v_ref.txt
│ │ ├── t2v_samples.txt
│ │ ├── t2v_short.txt
│ │ ├── t2v_sora.txt
│ │ ├── ucf101_id.txt
│ │ └── ucf101_labels.txt
│ ├── build/
│ │ └── lib/
│ │ ├── opensora/
│ │ │ ├── acceleration/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── checkpoint.py
│ │ │ │ ├── communications.py
│ │ │ │ ├── parallel_states.py
│ │ │ │ ├── plugin.py
│ │ │ │ └── shardformer/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── modeling/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── t5.py
│ │ │ │ └── policy/
│ │ │ │ ├── __init__.py
│ │ │ │ └── t5_encoder.py
│ │ │ ├── datasets/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── aspect.py
│ │ │ │ ├── bucket.py
│ │ │ │ ├── dataloader.py
│ │ │ │ ├── datasets.py
│ │ │ │ ├── read_video.py
│ │ │ │ ├── sampler.py
│ │ │ │ ├── utils.py
│ │ │ │ └── video_transforms.py
│ │ │ └── models/
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── dit/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dit.py
│ │ │ ├── latte/
│ │ │ │ ├── __init__.py
│ │ │ │ └── latte.py
│ │ │ ├── layers/
│ │ │ │ ├── __init__.py
│ │ │ │ └── blocks.py
│ │ │ ├── pixart/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── pixart.py
│ │ │ │ └── pixart_sigma.py
│ │ │ ├── stdit/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── stdit.py
│ │ │ │ ├── stdit2.py
│ │ │ │ ├── stdit3 copy.py
│ │ │ │ └── stdit3.py
│ │ │ └── text_encoder/
│ │ │ ├── __init__.py
│ │ │ ├── classes.py
│ │ │ ├── clip.py
│ │ │ └── t5.py
│ │ ├── tools/
│ │ │ ├── caption/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── acceleration/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── llava/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── policies/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── llama.py
│ │ │ │ │ └── mistral.py
│ │ │ │ ├── camera_motion/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── camera_motion.py
│ │ │ │ │ ├── detect.py
│ │ │ │ │ ├── utils.py
│ │ │ │ │ └── visualizer.py
│ │ │ │ ├── camera_motion_detect.py
│ │ │ │ ├── caption_gpt4.py
│ │ │ │ ├── caption_llama3.py
│ │ │ │ ├── caption_llava.py
│ │ │ │ └── utils.py
│ │ │ ├── datasets/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── analyze.py
│ │ │ │ ├── convert.py
│ │ │ │ ├── datautil.py
│ │ │ │ ├── filter_panda10m.py
│ │ │ │ ├── split.py
│ │ │ │ ├── transform.py
│ │ │ │ └── utils.py
│ │ │ ├── frame_interpolation/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── interpolation.py
│ │ │ │ ├── networks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── amt_g.py
│ │ │ │ │ └── blocks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── feat_enc.py
│ │ │ │ │ ├── ifrnet.py
│ │ │ │ │ ├── multi_flow.py
│ │ │ │ │ └── raft.py
│ │ │ │ └── utils/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── dist_utils.py
│ │ │ │ ├── flow_utils.py
│ │ │ │ └── utils.py
│ │ │ ├── scene_cut/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── convert_id_to_path.py
│ │ │ │ ├── cut.py
│ │ │ │ └── scene_detect.py
│ │ │ └── scoring/
│ │ │ ├── aesthetic/
│ │ │ │ ├── __init__.py
│ │ │ │ └── inference.py
│ │ │ └── matching/
│ │ │ ├── __init__.py
│ │ │ └── inference.py
│ │ ├── vbench/
│ │ │ ├── __init__.py
│ │ │ ├── aesthetic_quality.py
│ │ │ ├── appearance_style.py
│ │ │ ├── background_consistency.py
│ │ │ ├── cli/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── evaluate.py
│ │ │ │ ├── static_filter.py
│ │ │ │ └── vbench.py
│ │ │ ├── color.py
│ │ │ ├── dynamic_degree.py
│ │ │ ├── human_action.py
│ │ │ ├── imaging_quality.py
│ │ │ ├── motion_smoothness.py
│ │ │ ├── multiple_objects.py
│ │ │ ├── object_class.py
│ │ │ ├── overall_consistency.py
│ │ │ ├── scene.py
│ │ │ ├── spatial_relationship.py
│ │ │ ├── subject_consistency.py
│ │ │ ├── temporal_flickering.py
│ │ │ ├── temporal_style.py
│ │ │ ├── third_pary/
│ │ │ │ ├── 0.txt
│ │ │ │ ├── RAFT/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ └── core/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── corr.py
│ │ │ │ │ ├── datasets.py
│ │ │ │ │ ├── extractor.py
│ │ │ │ │ ├── raft.py
│ │ │ │ │ ├── update.py
│ │ │ │ │ └── utils_core/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── augmentor.py
│ │ │ │ │ ├── flow_viz.py
│ │ │ │ │ ├── frame_utils.py
│ │ │ │ │ └── utils.py
│ │ │ │ ├── ViCLIP/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── simple_tokenizer.py
│ │ │ │ │ ├── viclip.py
│ │ │ │ │ ├── viclip_text.py
│ │ │ │ │ └── viclip_vision.py
│ │ │ │ ├── __init__.py
│ │ │ │ ├── amt/
│ │ │ │ │ ├── benchmarks/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── adobe240.py
│ │ │ │ │ │ ├── gopro.py
│ │ │ │ │ │ ├── snu_film.py
│ │ │ │ │ │ ├── speed_parameters.py
│ │ │ │ │ │ ├── ucf101.py
│ │ │ │ │ │ ├── vimeo90k.py
│ │ │ │ │ │ ├── vimeo90k_tta.py
│ │ │ │ │ │ └── xiph.py
│ │ │ │ │ ├── datasets/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── adobe_datasets.py
│ │ │ │ │ │ ├── gopro_datasets.py
│ │ │ │ │ │ └── vimeo_datasets.py
│ │ │ │ │ ├── flow_generation/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── gen_flow.py
│ │ │ │ │ │ └── liteflownet/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── run.py
│ │ │ │ │ ├── losses/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── loss.py
│ │ │ │ │ ├── metrics/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── psnr_ssim.py
│ │ │ │ │ └── networks/
│ │ │ │ │ ├── AMT-G.py
│ │ │ │ │ ├── AMT-L.py
│ │ │ │ │ ├── AMT-S.py
│ │ │ │ │ └── blocks/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── feat_enc.py
│ │ │ │ │ ├── ifrnet.py
│ │ │ │ │ ├── multi_flow.py
│ │ │ │ │ └── raft.py
│ │ │ │ ├── grit_model.py
│ │ │ │ ├── grit_src/
│ │ │ │ │ └── centernet2/
│ │ │ │ │ └── centernet/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── config.py
│ │ │ │ │ └── modeling/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── backbone/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── bifpn.py
│ │ │ │ │ │ ├── bifpn_fcos.py
│ │ │ │ │ │ ├── dla.py
│ │ │ │ │ │ ├── dlafpn.py
│ │ │ │ │ │ ├── fpn_p5.py
│ │ │ │ │ │ └── res2net.py
│ │ │ │ │ ├── debug.py
│ │ │ │ │ ├── dense_heads/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── centernet.py
│ │ │ │ │ │ ├── centernet_head.py
│ │ │ │ │ │ └── utils.py
│ │ │ │ │ ├── layers/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ ├── deform_conv.py
│ │ │ │ │ │ ├── heatmap_focal_loss.py
│ │ │ │ │ │ ├── iou_loss.py
│ │ │ │ │ │ └── ml_nms.py
│ │ │ │ │ ├── meta_arch/
│ │ │ │ │ │ ├── __init__.py
│ │ │ │ │ │ └── centernet_detector.py
│ │ │ │ │ └── roi_heads/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── custom_fast_rcnn.py
│ │ │ │ │ ├── custom_roi_heads.py
│ │ │ │ │ └── fed_loss.py
│ │ │ │ ├── tag2Text/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── med.py
│ │ │ │ │ ├── swin_transformer.py
│ │ │ │ │ ├── tag2text.py
│ │ │ │ │ ├── tag_class.py
│ │ │ │ │ └── vit.py
│ │ │ │ └── umt/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── datasets/
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── build.py
│ │ │ │ │ ├── kinetics.py
│ │ │ │ │ ├── kinetics_sparse.py
│ │ │ │ │ ├── mae.py
│ │ │ │ │ ├── masking_generator.py
│ │ │ │ │ ├── mixup.py
│ │ │ │ │ ├── rand_augment.py
│ │ │ │ │ ├── random_erasing.py
│ │ │ │ │ ├── ssv2.py
│ │ │ │ │ ├── transforms.py
│ │ │ │ │ ├── video_transforms.py
│ │ │ │ │ └── volume_transforms.py
│ │ │ │ ├── functional.py
│ │ │ │ └── models/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── clip.py
│ │ │ │ ├── modeling_finetune.py
│ │ │ │ ├── modeling_pretrain.py
│ │ │ │ └── modeling_pretrain_umt.py
│ │ │ └── utils.py
│ │ └── vbench2_beta_i2v/
│ │ ├── __init__.py
│ │ ├── camera_motion.py
│ │ ├── crop_to_diff_ratio.py
│ │ ├── i2v_background.py
│ │ ├── i2v_subject.py
│ │ └── utils.py
│ ├── configs/
│ │ ├── dit/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256.py
│ │ │ │ ├── 1x256x256-class.py
│ │ │ │ └── 1x256x256.py
│ │ │ └── train/
│ │ │ ├── 16x256x256.py
│ │ │ └── 1x256x256.py
│ │ ├── latte/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256-class.py
│ │ │ │ └── 16x256x256.py
│ │ │ └── train/
│ │ │ └── 16x256x256.py
│ │ ├── opensora/
│ │ │ ├── inference/
│ │ │ │ ├── 16x256x256.py
│ │ │ │ ├── 16x512x512-rflow.py
│ │ │ │ ├── 16x512x512.py
│ │ │ │ └── 64x512x512.py
│ │ │ └── train/
│ │ │ ├── 16x256x256-mask.py
│ │ │ ├── 16x256x256-spee-rflow.py
│ │ │ ├── 16x256x256-spee.py
│ │ │ ├── 16x256x256.py
│ │ │ ├── 16x512x512.py
│ │ │ ├── 360x512x512.py
│ │ │ ├── 64x512x512-sp.py
│ │ │ └── 64x512x512.py
│ │ ├── opensora-v1-1/
│ │ │ ├── inference/
│ │ │ │ ├── sample-ref.py
│ │ │ │ └── sample.py
│ │ │ └── train/
│ │ │ ├── benchmark.py
│ │ │ ├── image.py
│ │ │ ├── image_rflow.py
│ │ │ ├── stage1.py
│ │ │ ├── stage2.py
│ │ │ ├── stage3.py
│ │ │ └── video.py
│ │ └── opensora-v1-2/
│ │ └── inference/
│ │ └── sample.py
│ ├── docs/
│ │ ├── acceleration.md
│ │ ├── commands.md
│ │ ├── config.md
│ │ ├── data_processing.md
│ │ ├── datasets.md
│ │ ├── installation.md
│ │ ├── report_01.md
│ │ ├── report_02.md
│ │ ├── report_03.md
│ │ ├── structure.md
│ │ ├── vae.md
│ │ └── zh_CN/
│ │ ├── README.md
│ │ ├── READMEv1.1.md
│ │ ├── acceleration.md
│ │ ├── commands.md
│ │ ├── datasets.md
│ │ ├── report_v1.md
│ │ ├── report_v2.md
│ │ ├── report_v3.md
│ │ ├── structure.md
│ │ └── vae.md
│ ├── environment-opensora.yml
│ ├── eval/
│ │ ├── README.md
│ │ ├── human_eval/
│ │ │ ├── generate.sh
│ │ │ └── launch.sh
│ │ ├── loss/
│ │ │ ├── eval_loss.py
│ │ │ ├── launch.sh
│ │ │ └── tabulate_rl_loss.py
│ │ ├── sample.sh
│ │ ├── vae/
│ │ │ ├── cal_flolpips.py
│ │ │ ├── cal_lpips.py
│ │ │ ├── cal_psnr.py
│ │ │ ├── cal_ssim.py
│ │ │ ├── eval_common_metric.py
│ │ │ ├── flolpips/
│ │ │ │ ├── correlation/
│ │ │ │ │ └── correlation.py
│ │ │ │ ├── flolpips.py
│ │ │ │ ├── pretrained_networks.py
│ │ │ │ ├── pwcnet.py
│ │ │ │ └── utils.py
│ │ │ └── script/
│ │ │ └── eval.sh
│ │ ├── vbench/
│ │ │ ├── VBench_full_info.json
│ │ │ ├── calc_vbench.py
│ │ │ ├── launch.sh
│ │ │ ├── launch_calc.sh
│ │ │ └── tabulate_vbench_scores.py
│ │ └── vbench_i2v/
│ │ ├── calc_vbench_i2v.py
│ │ ├── json_to_txt.py
│ │ ├── launch.sh
│ │ └── launch_calc.sh
│ ├── gradio/
│ │ ├── README.md
│ │ ├── app.py
│ │ └── requirements.txt
│ ├── notebooks/
│ │ ├── inference.ipynb
│ │ └── launch.ipynb
│ ├── opensora/
│ │ ├── __init__.py
│ │ ├── acceleration/
│ │ │ ├── __init__.py
│ │ │ ├── checkpoint.py
│ │ │ ├── communications.py
│ │ │ ├── parallel_states.py
│ │ │ ├── plugin.py
│ │ │ └── shardformer/
│ │ │ ├── __init__.py
│ │ │ ├── modeling/
│ │ │ │ ├── __init__.py
│ │ │ │ └── t5.py
│ │ │ └── policy/
│ │ │ ├── __init__.py
│ │ │ └── t5_encoder.py
│ │ ├── datasets/
│ │ │ ├── __init__.py
│ │ │ ├── aspect.py
│ │ │ ├── bucket.py
│ │ │ ├── dataloader.py
│ │ │ ├── datasets.py
│ │ │ ├── read_video.py
│ │ │ ├── sampler.py
│ │ │ ├── utils.py
│ │ │ └── video_transforms.py
│ │ ├── models/
│ │ │ ├── __init__.py
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── dit/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dit.py
│ │ │ ├── latte/
│ │ │ │ ├── __init__.py
│ │ │ │ └── latte.py
│ │ │ ├── layers/
│ │ │ │ ├── __init__.py
│ │ │ │ └── blocks.py
│ │ │ ├── pixart/
│ │ │ │ └── pixart.py
│ │ │ ├── stdit/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── stdit.py
│ │ │ │ ├── stdit2.py
│ │ │ │ └── stdit3.py
│ │ │ ├── text_encoder/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── classes.py
│ │ │ │ ├── clip.py
│ │ │ │ └── t5.py
│ │ │ └── vae/
│ │ │ ├── __init__.py
│ │ │ ├── discriminator.py
│ │ │ ├── losses.py
│ │ │ ├── lpips.py
│ │ │ ├── utils.py
│ │ │ ├── vae.py
│ │ │ ├── vae_temporal.py
│ │ │ └── video_sdxl/
│ │ │ └── blocks.py
│ │ ├── registry.py
│ │ ├── schedulers/
│ │ │ ├── __init__.py
│ │ │ ├── dpms/
│ │ │ │ ├── __init__.py
│ │ │ │ └── dpm_solver.py
│ │ │ ├── iddpm/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── diffusion_utils.py
│ │ │ │ ├── gaussian_diffusion.py
│ │ │ │ ├── respace.py
│ │ │ │ ├── speed.py
│ │ │ │ └── timestep_sampler.py
│ │ │ └── rf/
│ │ │ ├── __init__.py
│ │ │ └── rectified_flow.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── ckpt_utils.py
│ │ ├── config_utils.py
│ │ ├── inference_utils.py
│ │ ├── lr_scheduler.py
│ │ ├── misc.py
│ │ └── train_utils.py
│ ├── opensora.egg-info/
│ │ ├── PKG-INFO
│ │ ├── SOURCES.txt
│ │ ├── dependency_links.txt
│ │ ├── requires.txt
│ │ └── top_level.txt
│ ├── pyproject.toml
│ ├── requirements/
│ │ ├── requirements-cu121.txt
│ │ ├── requirements-data.txt
│ │ ├── requirements-eval.txt
│ │ ├── requirements-pllava.txt
│ │ ├── requirements-vae.txt
│ │ └── requirements.txt
│ ├── scripts/
│ │ ├── inference.py
│ │ ├── inference_vae.py
│ │ └── misc/
│ │ ├── extract_feat.py
│ │ └── launch_extract_feat.sh
│ ├── setup.py
│ ├── tests/
│ │ ├── test_attn.py
│ │ └── test_lr_scheduler.py
│ └── tools/
│ ├── __init__.py
│ ├── caption/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── acceleration/
│ │ │ ├── __init__.py
│ │ │ └── llava/
│ │ │ ├── __init__.py
│ │ │ └── policies/
│ │ │ ├── __init__.py
│ │ │ ├── llama.py
│ │ │ └── mistral.py
│ │ ├── camera_motion/
│ │ │ ├── __init__.py
│ │ │ ├── camera_motion.py
│ │ │ ├── detect.py
│ │ │ ├── requirements.txt
│ │ │ ├── utils.py
│ │ │ └── visualizer.py
│ │ ├── camera_motion_detect.py
│ │ ├── caption_gpt4.py
│ │ ├── caption_llama3.py
│ │ ├── caption_llava.py
│ │ ├── pllava_dir/
│ │ │ └── caption_pllava.py
│ │ └── utils.py
│ ├── datasets/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── analyze.py
│ │ ├── convert.py
│ │ ├── datautil.py
│ │ ├── filter_panda10m.py
│ │ ├── split.py
│ │ ├── transform.py
│ │ └── utils.py
│ ├── frame_interpolation/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── interpolation.py
│ │ ├── networks/
│ │ │ ├── __init__.py
│ │ │ ├── amt_g.py
│ │ │ └── blocks/
│ │ │ ├── __init__.py
│ │ │ ├── feat_enc.py
│ │ │ ├── ifrnet.py
│ │ │ ├── multi_flow.py
│ │ │ └── raft.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── dist_utils.py
│ │ ├── flow_utils.py
│ │ └── utils.py
│ ├── scene_cut/
│ │ ├── README.md
│ │ ├── __init__.py
│ │ ├── convert_id_to_path.py
│ │ ├── cut.py
│ │ └── scene_detect.py
│ └── scoring/
│ ├── README.md
│ ├── __init__.py
│ ├── aesthetic/
│ │ ├── __init__.py
│ │ └── inference.py
│ ├── matching/
│ │ ├── __init__.py
│ │ └── inference.py
│ ├── ocr/
│ │ ├── __init__.py
│ │ ├── dbnetpp.py
│ │ └── inference.py
│ └── optical_flow/
│ ├── __init__.py
│ ├── inference.py
│ └── unimatch/
│ ├── __init__.py
│ ├── attention.py
│ ├── backbone.py
│ ├── geometry.py
│ ├── matching.py
│ ├── position.py
│ ├── reg_refine.py
│ ├── transformer.py
│ ├── trident_conv.py
│ ├── unimatch.py
│ └── utils.py
├── PixArt-alpha-ToCa/
│ ├── Dockerfile
│ ├── README(PixArt-alpha).md
│ ├── app/
│ │ ├── app.py
│ │ ├── app_512.py
│ │ ├── app_controlnet.py
│ │ ├── app_lcm.py
│ │ ├── style.css
│ │ └── style_controlnet.css
│ ├── asset/
│ │ ├── docs/
│ │ │ ├── pixart-dreambooth.md
│ │ │ ├── pixart.md
│ │ │ ├── pixart_comfyui.md
│ │ │ ├── pixart_controlnet.md
│ │ │ ├── pixart_inpaint.md
│ │ │ ├── pixart_lcm.md
│ │ │ └── sasolver.md
│ │ ├── examples.py
│ │ └── samples.txt
│ ├── configs/
│ │ ├── PixArt_xl2_internal.py
│ │ ├── PixArt_xl2_sam.py
│ │ ├── pixart_app_config/
│ │ │ ├── PixArt_xl2_img1024_controlHed.py
│ │ │ ├── PixArt_xl2_img1024_dreambooth.py
│ │ │ └── PixArt_xl2_img512_controlHed.py
│ │ └── pixart_config/
│ │ ├── PixArt_xl2_img1024_internal.py
│ │ ├── PixArt_xl2_img1024_internalms.py
│ │ ├── PixArt_xl2_img1024_lcm.py
│ │ ├── PixArt_xl2_img256_SAM.py
│ │ ├── PixArt_xl2_img256_internal.py
│ │ ├── PixArt_xl2_img512_internal.py
│ │ └── PixArt_xl2_img512_internalms.py
│ ├── diffusion/
│ │ ├── __init__.py
│ │ ├── data/
│ │ │ ├── __init__.py
│ │ │ ├── builder.py
│ │ │ ├── datasets/
│ │ │ │ ├── Dreambooth.py
│ │ │ │ ├── InternalData.py
│ │ │ │ ├── InternalData_ms.py
│ │ │ │ ├── SA.py
│ │ │ │ ├── __init__.py
│ │ │ │ ├── pixart_control.py
│ │ │ │ └── utils.py
│ │ │ └── transforms.py
│ │ ├── dpm_solver.py
│ │ ├── iddpm.py
│ │ ├── lcm_scheduler.py
│ │ ├── model/
│ │ │ ├── __init__.py
│ │ │ ├── builder.py
│ │ │ ├── cache_functions/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── attention.py
│ │ │ │ ├── cache_cutfresh.py
│ │ │ │ ├── cache_init.py
│ │ │ │ ├── force_init.py
│ │ │ │ ├── force_scheduler.py
│ │ │ │ ├── fresh_ratio_scheduler.py
│ │ │ │ ├── global_force_fresh.py
│ │ │ │ ├── score_evaluate.py
│ │ │ │ ├── scores.py
│ │ │ │ ├── token_merge.py
│ │ │ │ └── update_cache.py
│ │ │ ├── diffusion_utils.py
│ │ │ ├── dpm_solver.py
│ │ │ ├── edm_sample.py
│ │ │ ├── gaussian_diffusion.py
│ │ │ ├── hed.py
│ │ │ ├── llava/
│ │ │ │ ├── __init__.py
│ │ │ │ ├── llava_mpt.py
│ │ │ │ └── mpt/
│ │ │ │ ├── attention.py
│ │ │ │ ├── blocks.py
│ │ │ │ ├── configuration_mpt.py
│ │ │ │ ├── modeling_mpt.py
│ │ │ │ ├── norm.py
│ │ │ │ └── param_init_fns.py
│ │ │ ├── nets/
│ │ │ │ ├── PixArt.py
│ │ │ │ ├── PixArtMS.py
│ │ │ │ ├── PixArt_blocks.py
│ │ │ │ ├── __init__.py
│ │ │ │ └── pixart_controlnet.py
│ │ │ ├── respace.py
│ │ │ ├── sa_solver.py
│ │ │ ├── t5.py
│ │ │ ├── timestep_sampler.py
│ │ │ └── utils.py
│ │ ├── sa_sampler.py
│ │ ├── sa_solver_diffusers.py
│ │ └── utils/
│ │ ├── __init__.py
│ │ ├── checkpoint.py
│ │ ├── data_sampler.py
│ │ ├── dist_utils.py
│ │ ├── logger.py
│ │ ├── lr_scheduler.py
│ │ ├── misc.py
│ │ └── optimizer.py
│ ├── docker-compose.yml
│ ├── docker-entrypoint.sh
│ ├── docker-readme.md
│ ├── environment-pixart.yml
│ ├── environment.yml
│ ├── notebooks/
│ │ ├── PixArt_xl2_img512_internal_for_pokemon_sample_training.py
│ │ ├── convert-checkpoint-to-diffusers.ipynb
│ │ ├── infer.ipynb
│ │ └── train.ipynb
│ ├── requirements.txt
│ ├── scripts/
│ │ ├── infer_pixart_8_bits.py
│ │ ├── inference.py
│ │ ├── inference_ddp.py
│ │ ├── inference_lcm.py
│ │ ├── interface.py
│ │ ├── interface_controlnet.py
│ │ ├── pipeline_pixart_inpaint.py
│ │ └── pipeline_pixart_reference.py
│ ├── timing_analysis.py
│ ├── timing_info.json
│ ├── tools/
│ │ ├── VLM_caption_lightning.py
│ │ ├── convert_pixart_alpha_to_diffusers.py
│ │ ├── download.py
│ │ └── extract_features.py
│ ├── train.sh
│ ├── train_latents.py
│ └── train_scripts/
│ ├── train.py
│ ├── train_controlnet.py
│ ├── train_diffusers.py
│ ├── train_dreambooth.py
│ ├── train_pixart_lcm.py
│ ├── train_pixart_lcm_lora.py
│ └── train_pixart_lora_hf.py
├── PixArt-alpha-ToCa-tools/
│ └── clip_score.py
├── README.md
└── flux-ToCa/
├── .gitignore
├── LICENSE
├── README.md
├── demo_gr.py
├── demo_st.py
├── demo_st_fill.py
├── docs/
│ ├── fill.md
│ ├── image-variation.md
│ ├── structural-conditioning.md
│ └── text-to-image.md
├── model_cards/
│ ├── FLUX.1-dev.md
│ └── FLUX.1-schnell.md
├── model_licenses/
│ ├── LICENSE-FLUX1-dev
│ └── LICENSE-FLUX1-schnell
├── pyproject.toml
├── setup.py
└── src/
├── flux/
│ ├── __init__.py
│ ├── __main__.py
│ ├── _version.py
│ ├── api.py
│ ├── cli.py
│ ├── cli_control.py
│ ├── cli_fill.py
│ ├── cli_redux.py
│ ├── ideas/
│ │ ├── __init__.py
│ │ └── cache_denoise.py
│ ├── math.py
│ ├── model.py
│ ├── modules/
│ │ ├── autoencoder.py
│ │ ├── cache_functions/
│ │ │ ├── __init__.py
│ │ │ ├── attention.py
│ │ │ ├── cache_cutfresh.py
│ │ │ ├── cache_init.py
│ │ │ ├── cal_type.py
│ │ │ ├── force_init.py
│ │ │ ├── force_scheduler.py
│ │ │ ├── fresh_ratio_scheduler.py
│ │ │ ├── global_force_fresh.py
│ │ │ ├── score_evaluate.py
│ │ │ ├── scores.py
│ │ │ ├── support_set_selection.py
│ │ │ ├── token_merge.py
│ │ │ └── update_cache.py
│ │ ├── conditioner.py
│ │ ├── image_embedders.py
│ │ ├── layers.py
│ │ └── lora.py
│ ├── sampling.py
│ └── util.py
├── geneval_flux.py
└── sample.py
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SYMBOL INDEX (3978 symbols across 424 files)
FILE: DiT-ToCa/cache_functions/attention.py
class Attention (line 9) | class Attention(nn.Module):
method __init__ (line 12) | def __init__(
method forward (line 35) | def forward(self, x: torch.Tensor, cache_dic, current, fresh_indices=N...
FILE: DiT-ToCa/cache_functions/cache_cutfresh.py
function cache_cutfresh (line 5) | def cache_cutfresh(cache_dic, tokens, current):
function local_selection_with_bonus (line 52) | def local_selection_with_bonus(score, bonus_ratio, grid_size=2):
FILE: DiT-ToCa/cache_functions/cache_init.py
function cache_init (line 1) | def cache_init(model_kwargs, num_steps):
FILE: DiT-ToCa/cache_functions/cal_type.py
function cal_type (line 1) | def cal_type(cache_dic, current):
FILE: DiT-ToCa/cache_functions/force_init.py
function force_init (line 3) | def force_init(cache_dic, current, tokens):
FILE: DiT-ToCa/cache_functions/force_scheduler.py
function force_scheduler (line 2) | def force_scheduler(cache_dic, current):
FILE: DiT-ToCa/cache_functions/fresh_ratio_scheduler.py
function fresh_ratio_scheduler (line 2) | def fresh_ratio_scheduler(cache_dic, current):
FILE: DiT-ToCa/cache_functions/global_force_fresh.py
function global_force_fresh (line 2) | def global_force_fresh(cache_dic, current):
FILE: DiT-ToCa/cache_functions/score_evaluate.py
function score_evaluate (line 4) | def score_evaluate(cache_dic, tokens, current) -> torch.Tensor:
FILE: DiT-ToCa/cache_functions/scores.py
function attn_score (line 5) | def attn_score(cache_dic, current):
function similarity_score (line 18) | def similarity_score(cache_dic, current, tokens):
function norm_score (line 23) | def norm_score(cache_dic, current, tokens):
function kv_norm_score (line 27) | def kv_norm_score(cache_dic, current):
FILE: DiT-ToCa/cache_functions/token_merge.py
function token_merge (line 2) | def token_merge(cache_dic, tokens, current, fresh_indices, stale_indices):
FILE: DiT-ToCa/cache_functions/update_cache.py
function update_cache (line 2) | def update_cache(fresh_indices, fresh_tokens, cache_dic, current, fresh_...
FILE: DiT-ToCa/diffusion/__init__.py
function create_diffusion (line 10) | def create_diffusion(
FILE: DiT-ToCa/diffusion/diffusion_utils.py
function normal_kl (line 10) | def normal_kl(mean1, logvar1, mean2, logvar2):
function approx_standard_normal_cdf (line 39) | def approx_standard_normal_cdf(x):
function continuous_gaussian_log_likelihood (line 47) | def continuous_gaussian_log_likelihood(x, *, means, log_scales):
function discretized_gaussian_log_likelihood (line 62) | def discretized_gaussian_log_likelihood(x, *, means, log_scales):
FILE: DiT-ToCa/diffusion/gaussian_diffusion.py
function mean_flat (line 17) | def mean_flat(tensor):
class ModelMeanType (line 24) | class ModelMeanType(enum.Enum):
class ModelVarType (line 34) | class ModelVarType(enum.Enum):
class LossType (line 47) | class LossType(enum.Enum):
method is_vb (line 55) | def is_vb(self):
function _warmup_beta (line 59) | def _warmup_beta(beta_start, beta_end, num_diffusion_timesteps, warmup_f...
function get_beta_schedule (line 66) | def get_beta_schedule(beta_schedule, *, beta_start, beta_end, num_diffus...
function get_named_beta_schedule (line 99) | def get_named_beta_schedule(schedule_name, num_diffusion_timesteps):
function betas_for_alpha_bar (line 126) | def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.9...
class GaussianDiffusion (line 145) | class GaussianDiffusion:
method __init__ (line 154) | def __init__(
method q_mean_variance (line 206) | def q_mean_variance(self, x_start, t):
method q_sample (line 218) | def q_sample(self, x_start, t, noise=None):
method q_posterior_mean_variance (line 235) | def q_posterior_mean_variance(self, x_start, x_t, t):
method p_mean_variance (line 257) | def p_mean_variance(self, model, x, t, current=None, cache_dic=None, c...
method _predict_xstart_from_eps (line 339) | def _predict_xstart_from_eps(self, x_t, t, eps):
method _predict_eps_from_xstart (line 346) | def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
method condition_mean (line 351) | def condition_mean(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
method condition_score (line 363) | def condition_score(self, cond_fn, p_mean_var, x, t, model_kwargs=None):
method p_sample (line 381) | def p_sample(
method p_sample_loop (line 428) | def p_sample_loop(
method p_sample_loop_progressive (line 473) | def p_sample_loop_progressive(
method ddim_sample (line 531) | def ddim_sample(
method ddim_reverse_sample (line 584) | def ddim_reverse_sample(
method ddim_sample_loop (line 622) | def ddim_sample_loop(
method ddim_sample_loop_progressive (line 655) | def ddim_sample_loop_progressive(
method _vb_terms_bpd (line 712) | def _vb_terms_bpd(
method training_losses (line 745) | def training_losses(self, model, x_start, t, model_kwargs=None, noise=...
method _prior_bpd (line 819) | def _prior_bpd(self, x_start):
method calc_bpd_loop (line 835) | def calc_bpd_loop(self, model, x_start, clip_denoised=True, model_kwar...
function _extract_into_tensor (line 891) | def _extract_into_tensor(arr, timesteps, broadcast_shape):
FILE: DiT-ToCa/diffusion/respace.py
function space_timesteps (line 12) | def space_timesteps(num_timesteps, section_counts):
class SpacedDiffusion (line 65) | class SpacedDiffusion(GaussianDiffusion):
method __init__ (line 73) | def __init__(self, use_timesteps, **kwargs):
method p_mean_variance (line 89) | def p_mean_variance(
method training_losses (line 94) | def training_losses(
method condition_mean (line 99) | def condition_mean(self, cond_fn, *args, **kwargs):
method condition_score (line 102) | def condition_score(self, cond_fn, *args, **kwargs):
method _wrap_model (line 105) | def _wrap_model(self, model):
method _scale_timesteps (line 112) | def _scale_timesteps(self, t):
class _WrappedModel (line 117) | class _WrappedModel:
method __init__ (line 118) | def __init__(self, model, timestep_map, original_num_steps):
method __call__ (line 124) | def __call__(self, x, ts, **kwargs):
FILE: DiT-ToCa/diffusion/timestep_sampler.py
function create_named_schedule_sampler (line 13) | def create_named_schedule_sampler(name, diffusion):
class ScheduleSampler (line 27) | class ScheduleSampler(ABC):
method weights (line 38) | def weights(self):
method sample (line 44) | def sample(self, batch_size, device):
class UniformSampler (line 62) | class UniformSampler(ScheduleSampler):
method __init__ (line 63) | def __init__(self, diffusion):
method weights (line 67) | def weights(self):
class LossAwareSampler (line 71) | class LossAwareSampler(ScheduleSampler):
method update_with_local_losses (line 72) | def update_with_local_losses(self, local_ts, local_losses):
method update_with_all_losses (line 106) | def update_with_all_losses(self, ts, losses):
class LossSecondMomentResampler (line 120) | class LossSecondMomentResampler(LossAwareSampler):
method __init__ (line 121) | def __init__(self, diffusion, history_per_term=10, uniform_prob=0.001):
method weights (line 130) | def weights(self):
method update_with_all_losses (line 139) | def update_with_all_losses(self, ts, losses):
method _warmed_up (line 149) | def _warmed_up(self):
FILE: DiT-ToCa/download.py
function find_model (line 18) | def find_model(model_name):
function download_model (line 32) | def download_model(model_name):
FILE: DiT-ToCa/models.py
function modulate (line 22) | def modulate(x, shift, scale):
class TimestepEmbedder (line 30) | class TimestepEmbedder(nn.Module):
method __init__ (line 34) | def __init__(self, hidden_size, frequency_embedding_size=256):
method timestep_embedding (line 44) | def timestep_embedding(t, dim, max_period=10000):
method forward (line 64) | def forward(self, t):
class LabelEmbedder (line 70) | class LabelEmbedder(nn.Module):
method __init__ (line 74) | def __init__(self, num_classes, hidden_size, dropout_prob):
method token_drop (line 81) | def token_drop(self, labels, force_drop_ids=None):
method forward (line 92) | def forward(self, labels, train, force_drop_ids=None):
class DiTBlock (line 105) | class DiTBlock(nn.Module):
method __init__ (line 109) | def __init__(self, hidden_size, num_heads, mlp_ratio=4.0, **block_kwar...
method forward (line 122) | def forward(self, x, c, current, cache_dic):
class FinalLayer (line 230) | class FinalLayer(nn.Module):
method __init__ (line 234) | def __init__(self, hidden_size, patch_size, out_channels):
method forward (line 243) | def forward(self, x, c):
class DiT (line 250) | class DiT(nn.Module):
method __init__ (line 254) | def __init__(
method initialize_weights (line 287) | def initialize_weights(self):
method unpatchify (line 323) | def unpatchify(self, x):
method forward (line 338) | def forward(self, x, t, current, cache_dic, y):
method forward_with_cfg (line 360) | def forward_with_cfg(self, x, t, current, cache_dic, y, cfg_scale, **k...
function get_2d_sincos_pos_embed (line 388) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False, extra...
function get_2d_sincos_pos_embed_from_grid (line 406) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
function get_1d_sincos_pos_embed_from_grid (line 417) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
function DiT_XL_2 (line 442) | def DiT_XL_2(**kwargs):
function DiT_XL_4 (line 445) | def DiT_XL_4(**kwargs):
function DiT_XL_8 (line 448) | def DiT_XL_8(**kwargs):
function DiT_L_2 (line 451) | def DiT_L_2(**kwargs):
function DiT_L_4 (line 454) | def DiT_L_4(**kwargs):
function DiT_L_8 (line 457) | def DiT_L_8(**kwargs):
function DiT_B_2 (line 460) | def DiT_B_2(**kwargs):
function DiT_B_4 (line 463) | def DiT_B_4(**kwargs):
function DiT_B_8 (line 466) | def DiT_B_8(**kwargs):
function DiT_S_2 (line 469) | def DiT_S_2(**kwargs):
function DiT_S_4 (line 472) | def DiT_S_4(**kwargs):
function DiT_S_8 (line 475) | def DiT_S_8(**kwargs):
FILE: DiT-ToCa/sample.py
function main (line 21) | def main(args):
FILE: DiT-ToCa/sample_ddp.py
function create_npz_from_sample_folder (line 28) | def create_npz_from_sample_folder(sample_dir, num=50_000):
function main (line 44) | def main(args):
FILE: DiT-ToCa/train.py
function update_ema (line 40) | def update_ema(ema_model, model, decay=0.9999):
function requires_grad (line 52) | def requires_grad(model, flag=True):
function cleanup (line 60) | def cleanup():
function create_logger (line 67) | def create_logger(logging_dir):
function center_crop_arr (line 85) | def center_crop_arr(pil_image, image_size):
function main (line 110) | def main(args):
FILE: Open-Sora/build/lib/opensora/acceleration/checkpoint.py
function set_grad_checkpoint (line 7) | def set_grad_checkpoint(model, use_fp32_attention=False, gc_step=1):
function auto_grad_checkpoint (line 18) | def auto_grad_checkpoint(module, *args, **kwargs):
FILE: Open-Sora/build/lib/opensora/acceleration/communications.py
function _all_to_all (line 8) | def _all_to_all(
class _AllToAll (line 21) | class _AllToAll(torch.autograd.Function):
method forward (line 32) | def forward(ctx, input_, process_group, scatter_dim, gather_dim):
method backward (line 41) | def backward(ctx, grad_output):
function all_to_all (line 57) | def all_to_all(
function _gather (line 66) | def _gather(
function _split (line 83) | def _split(input_, pg: dist.ProcessGroup, dim=-1):
function _gather (line 103) | def _gather(input_, pg: dist.ProcessGroup, dim=-1):
class _GatherForwardSplitBackward (line 123) | class _GatherForwardSplitBackward(torch.autograd.Function):
method symbolic (line 133) | def symbolic(graph, input_):
method forward (line 137) | def forward(ctx, input_, process_group, dim, grad_scale):
method backward (line 144) | def backward(ctx, grad_output):
class _SplitForwardGatherBackward (line 153) | class _SplitForwardGatherBackward(torch.autograd.Function):
method symbolic (line 164) | def symbolic(graph, input_):
method forward (line 168) | def forward(ctx, input_, process_group, dim, grad_scale):
method backward (line 175) | def backward(ctx, grad_output):
function split_forward_gather_backward (line 183) | def split_forward_gather_backward(input_, process_group, dim, grad_scale...
function gather_forward_split_backward (line 187) | def gather_forward_split_backward(input_, process_group, dim, grad_scale...
FILE: Open-Sora/build/lib/opensora/acceleration/parallel_states.py
function set_data_parallel_group (line 6) | def set_data_parallel_group(group: dist.ProcessGroup):
function get_data_parallel_group (line 10) | def get_data_parallel_group():
function set_sequence_parallel_group (line 14) | def set_sequence_parallel_group(group: dist.ProcessGroup):
function get_sequence_parallel_group (line 18) | def get_sequence_parallel_group():
FILE: Open-Sora/build/lib/opensora/acceleration/plugin.py
class ZeroSeqParallelPlugin (line 14) | class ZeroSeqParallelPlugin(LowLevelZeroPlugin):
method __init__ (line 15) | def __init__(
method __del__ (line 64) | def __del__(self):
method prepare_dataloader (line 68) | def prepare_dataloader(
FILE: Open-Sora/build/lib/opensora/acceleration/shardformer/modeling/t5.py
class T5LayerNorm (line 5) | class T5LayerNorm(nn.Module):
method __init__ (line 6) | def __init__(self, hidden_size, eps=1e-6):
method forward (line 14) | def forward(self, hidden_states):
method from_native_module (line 30) | def from_native_module(module, *args, **kwargs):
FILE: Open-Sora/build/lib/opensora/acceleration/shardformer/policy/t5_encoder.py
class T5EncoderPolicy (line 6) | class T5EncoderPolicy(Policy):
method config_sanity_check (line 7) | def config_sanity_check(self):
method preprocess (line 11) | def preprocess(self):
method module_policy (line 14) | def module_policy(self):
method postprocess (line 66) | def postprocess(self):
FILE: Open-Sora/build/lib/opensora/datasets/aspect.py
function get_h_w (line 5) | def get_h_w(a, ts, eps=1e-4):
function get_aspect_ratios_dict (line 15) | def get_aspect_ratios_dict(ars, ts=360 * 640):
function get_ar (line 20) | def get_ar(ratio):
function get_closest_ratio (line 440) | def get_closest_ratio(height: float, width: float, ratios: dict):
function get_num_pixels (line 463) | def get_num_pixels(name):
function get_image_size (line 467) | def get_image_size(resolution, ar_ratio):
function get_num_frames (line 491) | def get_num_frames(num_frames):
FILE: Open-Sora/build/lib/opensora/datasets/bucket.py
function find_approximate_hw (line 10) | def find_approximate_hw(hw, hw_dict, approx=0.8):
function find_closet_smaller_bucket (line 17) | def find_closet_smaller_bucket(t, t_dict, frame_interval):
class Bucket (line 31) | class Bucket:
method __init__ (line 32) | def __init__(self, bucket_config):
method get_bucket_id (line 74) | def get_bucket_id(self, T, H, W, frame_interval=1, seed=None):
method get_thw (line 122) | def get_thw(self, bucket_id):
method get_prob (line 128) | def get_prob(self, bucket_id):
method get_batch_size (line 131) | def get_batch_size(self, bucket_id):
method __len__ (line 134) | def __len__(self):
function closet_smaller_bucket (line 138) | def closet_smaller_bucket(value, bucket):
FILE: Open-Sora/build/lib/opensora/datasets/dataloader.py
function get_seed_worker (line 16) | def get_seed_worker(seed):
function prepare_dataloader (line 26) | def prepare_dataloader(
function collate_fn_default (line 113) | def collate_fn_default(batch):
function collate_fn_batch (line 134) | def collate_fn_batch(batch):
FILE: Open-Sora/build/lib/opensora/datasets/datasets.py
class VideoTextDataset (line 19) | class VideoTextDataset(torch.utils.data.Dataset):
method __init__ (line 28) | def __init__(
method _print_data_number (line 47) | def _print_data_number(self):
method get_type (line 57) | def get_type(self, path):
method getitem (line 65) | def getitem(self, index):
method __getitem__ (line 101) | def __getitem__(self, index):
method __len__ (line 111) | def __len__(self):
class VariableVideoTextDataset (line 116) | class VariableVideoTextDataset(VideoTextDataset):
method __init__ (line 117) | def __init__(
method get_data_info (line 131) | def get_data_info(self, index):
method getitem (line 137) | def getitem(self, index):
method __getitem__ (line 192) | def __getitem__(self, index):
class BatchFeatureDataset (line 200) | class BatchFeatureDataset(torch.utils.data.Dataset):
method __init__ (line 209) | def __init__(self, data_path=None):
method num_buffers (line 220) | def num_buffers(self):
method len_buffer (line 224) | def len_buffer(self):
method _load_buffer (line 227) | def _load_buffer(self, idx):
method __len__ (line 233) | def __len__(self):
method __getitem__ (line 236) | def __getitem__(self, idx):
FILE: Open-Sora/build/lib/opensora/datasets/read_video.py
function read_video_av (line 19) | def read_video_av(
function _read_from_stream (line 119) | def _read_from_stream(
function read_video_cv2 (line 213) | def read_video_cv2(video_path):
function read_video (line 250) | def read_video(video_path, backend="av"):
FILE: Open-Sora/build/lib/opensora/datasets/sampler.py
function apply (line 19) | def apply(data, method=None, frame_interval=None, seed=None, num_bucket=...
class StatefulDistributedSampler (line 29) | class StatefulDistributedSampler(DistributedSampler):
method __init__ (line 30) | def __init__(
method __iter__ (line 42) | def __iter__(self) -> Iterator:
method __len__ (line 48) | def __len__(self) -> int:
method reset (line 51) | def reset(self) -> None:
method state_dict (line 54) | def state_dict(self, step) -> dict:
method load_state_dict (line 57) | def load_state_dict(self, state_dict: dict) -> None:
class VariableVideoBatchSampler (line 61) | class VariableVideoBatchSampler(DistributedSampler):
method __init__ (line 62) | def __init__(
method __iter__ (line 86) | def __iter__(self) -> Iterator[List[int]]:
method __len__ (line 190) | def __len__(self) -> int:
method group_by_bucket (line 193) | def group_by_bucket(self) -> dict:
method get_num_batch (line 220) | def get_num_batch(self) -> int:
method _print_bucket_info (line 229) | def _print_bucket_info(self, bucket_sample_dict: dict) -> None:
method reset (line 275) | def reset(self):
method state_dict (line 278) | def state_dict(self, num_steps: int) -> dict:
method load_state_dict (line 285) | def load_state_dict(self, state_dict: dict) -> None:
class BatchDistributedSampler (line 289) | class BatchDistributedSampler(DistributedSampler):
method __init__ (line 300) | def __init__(self, dataset: Dataset, **kwargs):
method __iter__ (line 304) | def __iter__(self):
method reset (line 315) | def reset(self):
method state_dict (line 318) | def state_dict(self, step) -> dict:
method load_state_dict (line 321) | def load_state_dict(self, state_dict: dict):
FILE: Open-Sora/build/lib/opensora/datasets/utils.py
function is_img (line 30) | def is_img(path):
function is_vid (line 35) | def is_vid(path):
function is_url (line 40) | def is_url(url):
function read_file (line 44) | def read_file(input_path):
function download_url (line 53) | def download_url(input_path):
function temporal_random_crop (line 65) | def temporal_random_crop(vframes, num_frames, frame_interval):
function get_transforms_video (line 77) | def get_transforms_video(name="center", image_size=(256, 256)):
function get_transforms_image (line 103) | def get_transforms_image(name="center", image_size=(256, 256)):
function read_image_from_path (line 129) | def read_image_from_path(path, transform=None, transform_name="center", ...
function read_video_from_path (line 139) | def read_video_from_path(path, transform=None, transform_name="center", ...
function read_from_path (line 148) | def read_from_path(path, image_size, transform_name="center"):
function save_sample (line 159) | def save_sample(x, save_path=None, fps=8, normalize=True, value_range=(-...
function center_crop_arr (line 184) | def center_crop_arr(pil_image, image_size):
function resize_crop_to_fill (line 201) | def resize_crop_to_fill(pil_image, image_size):
FILE: Open-Sora/build/lib/opensora/datasets/video_transforms.py
function _is_tensor_video_clip (line 25) | def _is_tensor_video_clip(clip):
function crop (line 35) | def crop(clip, i, j, h, w):
function resize (line 45) | def resize(clip, target_size, interpolation_mode):
function resize_scale (line 51) | def resize_scale(clip, target_size, interpolation_mode):
function resized_crop (line 59) | def resized_crop(clip, i, j, h, w, size, interpolation_mode="bilinear"):
function center_crop (line 79) | def center_crop(clip, crop_size):
function center_crop_using_short_edge (line 92) | def center_crop_using_short_edge(clip):
function resize_crop_to_fill (line 107) | def resize_crop_to_fill(clip, target_size):
function random_shift_crop (line 127) | def random_shift_crop(clip):
function to_tensor (line 147) | def to_tensor(clip):
function normalize (line 163) | def normalize(clip, mean, std, inplace=False):
function hflip (line 183) | def hflip(clip):
class ResizeCrop (line 195) | class ResizeCrop:
method __init__ (line 196) | def __init__(self, size):
method __call__ (line 202) | def __call__(self, clip):
method __repr__ (line 206) | def __repr__(self) -> str:
class RandomCropVideo (line 210) | class RandomCropVideo:
method __init__ (line 211) | def __init__(self, size):
method __call__ (line 217) | def __call__(self, clip):
method get_params (line 228) | def get_params(self, clip):
method __repr__ (line 243) | def __repr__(self) -> str:
class CenterCropResizeVideo (line 247) | class CenterCropResizeVideo:
method __init__ (line 253) | def __init__(
method __call__ (line 267) | def __call__(self, clip):
method __repr__ (line 281) | def __repr__(self) -> str:
class UCFCenterCropVideo (line 285) | class UCFCenterCropVideo:
method __init__ (line 291) | def __init__(
method __call__ (line 305) | def __call__(self, clip):
method __repr__ (line 317) | def __repr__(self) -> str:
class KineticsRandomCropResizeVideo (line 321) | class KineticsRandomCropResizeVideo:
method __init__ (line 326) | def __init__(
method __call__ (line 340) | def __call__(self, clip):
class CenterCropVideo (line 346) | class CenterCropVideo:
method __init__ (line 347) | def __init__(
method __call__ (line 361) | def __call__(self, clip):
method __repr__ (line 372) | def __repr__(self) -> str:
class NormalizeVideo (line 376) | class NormalizeVideo:
method __init__ (line 385) | def __init__(self, mean, std, inplace=False):
method __call__ (line 390) | def __call__(self, clip):
method __repr__ (line 397) | def __repr__(self) -> str:
class ToTensorVideo (line 401) | class ToTensorVideo:
method __init__ (line 407) | def __init__(self):
method __call__ (line 410) | def __call__(self, clip):
method __repr__ (line 419) | def __repr__(self) -> str:
class RandomHorizontalFlipVideo (line 423) | class RandomHorizontalFlipVideo:
method __init__ (line 430) | def __init__(self, p=0.5):
method __call__ (line 433) | def __call__(self, clip):
method __repr__ (line 444) | def __repr__(self) -> str:
class TemporalRandomCrop (line 451) | class TemporalRandomCrop(object):
method __init__ (line 458) | def __init__(self, size):
method __call__ (line 461) | def __call__(self, total_frames):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/attention.py
function cached_attention_forward (line 8) | def cached_attention_forward(
FILE: Open-Sora/build/lib/opensora/models/cache_functions/cache_cutfresh.py
function cache_cutfresh (line 5) | def cache_cutfresh(cache_dic, tokens, current):
function local_selection_with_space_time_bonus (line 63) | def local_selection_with_space_time_bonus(cache_dic, score, bonus_ratio,...
FILE: Open-Sora/build/lib/opensora/models/cache_functions/cache_init.py
function cache_init (line 1) | def cache_init(model_kwargs, num_steps):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/force_init.py
function force_init (line 3) | def force_init(cache_dic, current, tokens):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/force_scheduler.py
function force_scheduler (line 2) | def force_scheduler(cache_dic, current):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/fresh_ratio_scheduler.py
function fresh_ratio_scheduler (line 2) | def fresh_ratio_scheduler(cache_dic, current):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/global_force_fresh.py
function global_force_fresh (line 2) | def global_force_fresh(cache_dic, current):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/score_evaluate.py
function score_evaluate (line 4) | def score_evaluate(cache_dic, tokens, current) -> torch.Tensor:
FILE: Open-Sora/build/lib/opensora/models/cache_functions/scores.py
function attn_score (line 5) | def attn_score(cache_dic, current):
function similarity_score (line 23) | def similarity_score(cache_dic, current, tokens):
function norm_score (line 28) | def norm_score(cache_dic, current, tokens):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/token_merge.py
function token_merge (line 2) | def token_merge(cache_dic, tokens, current, fresh_indices, stale_indices):
FILE: Open-Sora/build/lib/opensora/models/cache_functions/update_cache.py
function update_cache (line 2) | def update_cache(fresh_indices, fresh_tokens, cache_dic, current, fresh_...
FILE: Open-Sora/build/lib/opensora/models/dit/dit.py
class DiTBlock (line 37) | class DiTBlock(nn.Module):
method __init__ (line 42) | def __init__(
method forward (line 67) | def forward(self, x, c):
class DiT (line 75) | class DiT(nn.Module):
method __init__ (line 80) | def __init__(
method get_spatial_pos_embed (line 158) | def get_spatial_pos_embed(self):
method get_temporal_pos_embed (line 166) | def get_temporal_pos_embed(self):
method unpatchify (line 174) | def unpatchify(self, x):
method forward (line 184) | def forward(self, x, t, y):
method initialize_weights (line 226) | def initialize_weights(self):
function DiT_XL_2 (line 264) | def DiT_XL_2(from_pretrained=None, **kwargs):
function DiT_XL_2x2 (line 278) | def DiT_XL_2x2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/latte/latte.py
class Latte (line 33) | class Latte(DiT):
method forward (line 34) | def forward(self, x, t, y):
function Latte_XL_2 (line 88) | def Latte_XL_2(from_pretrained=None, **kwargs):
function Latte_XL_2x2 (line 102) | def Latte_XL_2x2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/layers/blocks.py
class LlamaRMSNorm (line 34) | class LlamaRMSNorm(nn.Module):
method __init__ (line 35) | def __init__(self, hidden_size, eps=1e-6):
method forward (line 43) | def forward(self, hidden_states):
function get_layernorm (line 51) | def get_layernorm(hidden_size: torch.Tensor, eps: float, affine: bool, u...
function modulate (line 63) | def modulate(norm_func, x, shift, scale):
function t2i_modulate (line 72) | def t2i_modulate(x, shift, scale):
class PatchEmbed3D (line 81) | class PatchEmbed3D(nn.Module):
method __init__ (line 91) | def __init__(
method forward (line 112) | def forward(self, x):
class Attention (line 134) | class Attention(nn.Module):
method __init__ (line 135) | def __init__(
method forward (line 171) | def forward(self, x: torch.Tensor) -> torch.Tensor:
class KVCompressAttention (line 232) | class KVCompressAttention(nn.Module):
method __init__ (line 233) | def __init__(
method downsample_2d (line 276) | def downsample_2d(self, tensor, H, W, scale_factor, sampling=None):
method forward (line 300) | def forward(self, x: torch.Tensor, mask=None, HW=None, block_id=None, ...
class SeqParallelAttention (line 362) | class SeqParallelAttention(Attention):
method __init__ (line 363) | def __init__(
method forward (line 387) | def forward(self, x: torch.Tensor) -> torch.Tensor:
class MultiHeadCrossAttention (line 455) | class MultiHeadCrossAttention(nn.Module):
method __init__ (line 456) | def __init__(self, d_model, num_heads, attn_drop=0.0, proj_drop=0.0):
method forward (line 470) | def forward(self, x, cond, mask=None):
class SeqParallelMultiHeadCrossAttention (line 496) | class SeqParallelMultiHeadCrossAttention(MultiHeadCrossAttention):
method __init__ (line 497) | def __init__(
method forward (line 511) | def forward(self, x, cond, mask=None):
class FinalLayer (line 549) | class FinalLayer(nn.Module):
method __init__ (line 554) | def __init__(self, hidden_size, num_patch, out_channels):
method forward (line 560) | def forward(self, x, c):
class T2IFinalLayer (line 567) | class T2IFinalLayer(nn.Module):
method __init__ (line 572) | def __init__(self, hidden_size, num_patch, out_channels, d_t=None, d_s...
method t_mask_select (line 581) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 591) | def forward(self, x, t, x_mask=None, t0=None, T=None, S=None):
class TimestepEmbedder (line 611) | class TimestepEmbedder(nn.Module):
method __init__ (line 616) | def __init__(self, hidden_size, frequency_embedding_size=256):
method timestep_embedding (line 626) | def timestep_embedding(t, dim, max_period=10000):
method forward (line 645) | def forward(self, t, dtype):
class LabelEmbedder (line 653) | class LabelEmbedder(nn.Module):
method __init__ (line 658) | def __init__(self, num_classes, hidden_size, dropout_prob):
method token_drop (line 665) | def token_drop(self, labels, force_drop_ids=None):
method forward (line 676) | def forward(self, labels, train, force_drop_ids=None):
class SizeEmbedder (line 683) | class SizeEmbedder(TimestepEmbedder):
method __init__ (line 688) | def __init__(self, hidden_size, frequency_embedding_size=256):
method forward (line 698) | def forward(self, s, bs):
method dtype (line 713) | def dtype(self):
class CaptionEmbedder (line 717) | class CaptionEmbedder(nn.Module):
method __init__ (line 722) | def __init__(
method token_drop (line 744) | def token_drop(self, caption, force_drop_ids=None):
method forward (line 755) | def forward(self, caption, train, force_drop_ids=None):
class PositionEmbedding2D (line 765) | class PositionEmbedding2D(nn.Module):
method __init__ (line 766) | def __init__(self, dim: int) -> None:
method _get_sin_cos_emb (line 774) | def _get_sin_cos_emb(self, t: torch.Tensor):
method _get_cached_emb (line 781) | def _get_cached_emb(
method forward (line 806) | def forward(
function get_2d_sincos_pos_embed (line 823) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False, extra...
function get_2d_sincos_pos_embed_from_grid (line 847) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
function get_1d_sincos_pos_embed (line 858) | def get_1d_sincos_pos_embed(embed_dim, length, scale=1.0):
function get_1d_sincos_pos_embed_from_grid (line 863) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
FILE: Open-Sora/build/lib/opensora/models/pixart/pixart.py
class PixArtBlock (line 53) | class PixArtBlock(nn.Module):
method __init__ (line 58) | def __init__(
method forward (line 95) | def forward(self, x, y, t, mask=None):
class PixArt (line 109) | class PixArt(nn.Module):
method __init__ (line 114) | def __init__(
method forward (line 200) | def forward(self, x, timestep, y, mask=None, **kwargs):
method unpatchify (line 249) | def unpatchify(self, x):
method get_spatial_pos_embed (line 259) | def get_spatial_pos_embed(self, grid_size=None):
method get_temporal_pos_embed (line 271) | def get_temporal_pos_embed(self):
method freeze_text (line 280) | def freeze_text(self):
method initialize_weights (line 285) | def initialize_weights(self):
class PixArtMS (line 319) | class PixArtMS(PixArt):
method __init__ (line 320) | def __init__(self, *args, **kwargs):
method forward (line 327) | def forward(self, x, timestep, y, mask=None, data_info=None):
function PixArt_XL_2 (line 385) | def PixArt_XL_2(from_pretrained=None, **kwargs):
function PixArt_1B_2 (line 393) | def PixArt_1B_2(from_pretrained=None, **kwargs):
function PixArtMS_XL_2 (line 401) | def PixArtMS_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/pixart/pixart_sigma.py
class PixArtBlock (line 50) | class PixArtBlock(nn.Module):
method __init__ (line 55) | def __init__(
method forward (line 98) | def forward(self, x, y, t, hw, mask=None):
class PixArt_Sigma (line 114) | class PixArt_Sigma(nn.Module):
method __init__ (line 119) | def __init__(
method forward (line 219) | def forward(self, x, timestep, y, mask=None):
method unpatchify (line 268) | def unpatchify(self, x):
method get_spatial_pos_embed (line 278) | def get_spatial_pos_embed(self, grid_size=None):
method get_temporal_pos_embed (line 290) | def get_temporal_pos_embed(self):
method freeze_text (line 299) | def freeze_text(self):
method initialize_weights (line 304) | def initialize_weights(self):
function PixArt_Sigma_XL_2 (line 338) | def PixArt_Sigma_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/stdit/stdit.py
class STDiTBlock (line 31) | class STDiTBlock(nn.Module):
method __init__ (line 32) | def __init__(
method t_mask_select (line 88) | def t_mask_select(self, x, masked_x, x_mask):
method forward (line 98) | def forward(self, x, y, t, mask=None, tpe=None, x_mask=None, t0=None):
class STDiT (line 157) | class STDiT(nn.Module):
method __init__ (line 158) | def __init__(
method forward (line 258) | def forward(self, x, timestep, y, mask=None, x_mask=None, **kwargs):
method unpatchify (line 331) | def unpatchify(self, x):
method unpatchify_old (line 355) | def unpatchify_old(self, x):
method get_spatial_pos_embed (line 365) | def get_spatial_pos_embed(self, grid_size=None):
method get_temporal_pos_embed (line 376) | def get_temporal_pos_embed(self):
method freeze_not_temporal (line 385) | def freeze_not_temporal(self):
method freeze_text (line 390) | def freeze_text(self):
method initialize_temporal (line 395) | def initialize_temporal(self):
method initialize_weights (line 400) | def initialize_weights(self):
function STDiT_XL_2 (line 434) | def STDiT_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/stdit/stdit2.py
class STDiT2Block (line 31) | class STDiT2Block(nn.Module):
method __init__ (line 32) | def __init__(
method t_mask_select (line 85) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 95) | def forward(self, x, y, t, t_tmp, mask=None, x_mask=None, t0=None, t0_...
class STDiT2Config (line 170) | class STDiT2Config(PretrainedConfig):
method __init__ (line 173) | def __init__(
class STDiT2 (line 219) | class STDiT2(PreTrainedModel):
method __init__ (line 222) | def __init__(self, config):
method get_dynamic_size (line 292) | def get_dynamic_size(self, x):
method forward (line 305) | def forward(
method unpatchify (line 413) | def unpatchify(self, x, N_t, N_h, N_w, R_t, R_h, R_w):
method unpatchify_old (line 439) | def unpatchify_old(self, x):
method get_spatial_pos_embed (line 449) | def get_spatial_pos_embed(self, H, W, scale=1.0, base_size=None):
method freeze_not_temporal (line 459) | def freeze_not_temporal(self):
method freeze_text (line 464) | def freeze_text(self):
method initialize_temporal (line 469) | def initialize_temporal(self):
method initialize_weights (line 474) | def initialize_weights(self):
function STDiT2_XL_2 (line 509) | def STDiT2_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/stdit/stdit3 copy.py
class STDiT3Block (line 37) | class STDiT3Block(nn.Module):
method __init__ (line 38) | def __init__(
method t_mask_select (line 81) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 91) | def forward(
class STDiT3Config (line 263) | class STDiT3Config(PretrainedConfig):
method __init__ (line 266) | def __init__(
class STDiT3 (line 313) | class STDiT3(PreTrainedModel):
method __init__ (line 316) | def __init__(self, config):
method initialize_weights (line 410) | def initialize_weights(self):
method get_dynamic_size (line 432) | def get_dynamic_size(self, x):
method encode_text (line 445) | def encode_text(self, y, mask=None):
method forward (line 458) | def forward(self, x, timestep, y, mask=None, x_mask=None, fps=None, he...
method unpatchify (line 546) | def unpatchify(self, x, N_t, N_h, N_w, R_t, R_h, R_w):
function STDiT3_XL_2 (line 574) | def STDiT3_XL_2(from_pretrained=None, **kwargs):
function STDiT3_3B_2 (line 587) | def STDiT3_3B_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/stdit/stdit3.py
class STDiT3Block (line 37) | class STDiT3Block(nn.Module):
method __init__ (line 38) | def __init__(
method t_mask_select (line 81) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 91) | def forward(
class STDiT3Config (line 213) | class STDiT3Config(PretrainedConfig):
method __init__ (line 216) | def __init__(
class STDiT3 (line 263) | class STDiT3(PreTrainedModel):
method __init__ (line 266) | def __init__(self, config):
method initialize_weights (line 360) | def initialize_weights(self):
method get_dynamic_size (line 382) | def get_dynamic_size(self, x):
method encode_text (line 395) | def encode_text(self, y, mask=None):
method forward (line 408) | def forward(self, x, timestep, y, mask=None, x_mask=None, fps=None, he...
method unpatchify (line 496) | def unpatchify(self, x, N_t, N_h, N_w, R_t, R_h, R_w):
function STDiT3_XL_2 (line 524) | def STDiT3_XL_2(from_pretrained=None, **kwargs):
function STDiT3_3B_2 (line 537) | def STDiT3_3B_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/build/lib/opensora/models/text_encoder/classes.py
class ClassEncoder (line 7) | class ClassEncoder:
method __init__ (line 8) | def __init__(self, num_classes, model_max_length=None, device="cuda", ...
method encode (line 16) | def encode(self, text):
method null (line 19) | def null(self, n):
FILE: Open-Sora/build/lib/opensora/models/text_encoder/clip.py
class AbstractEncoder (line 36) | class AbstractEncoder(nn.Module):
method __init__ (line 37) | def __init__(self):
method encode (line 40) | def encode(self, *args, **kwargs):
class FrozenCLIPEmbedder (line 44) | class FrozenCLIPEmbedder(AbstractEncoder):
method __init__ (line 47) | def __init__(self, path="openai/clip-vit-huge-patch14", device="cuda",...
method _freeze (line 55) | def _freeze(self):
method forward (line 60) | def forward(self, text):
method encode (line 77) | def encode(self, text):
class ClipEncoder (line 82) | class ClipEncoder:
method __init__ (line 87) | def __init__(
method encode (line 103) | def encode(self, text):
method null (line 108) | def null(self, n):
method to (line 112) | def to(self, dtype):
FILE: Open-Sora/build/lib/opensora/models/text_encoder/t5.py
class T5Embedder (line 34) | class T5Embedder:
method __init__ (line 35) | def __init__(
method get_text_embeddings (line 113) | def get_text_embeddings(self, texts):
class T5Encoder (line 135) | class T5Encoder:
method __init__ (line 136) | def __init__(
method shardformer_t5 (line 166) | def shardformer_t5(self):
method encode (line 189) | def encode(self, text):
method null (line 194) | def null(self, n):
function basic_clean (line 199) | def basic_clean(text):
function clean_caption (line 210) | def clean_caption(caption):
function text_preprocessing (line 328) | def text_preprocessing(text, use_text_preprocessing: bool = True):
FILE: Open-Sora/build/lib/tools/caption/acceleration/llava/policies/llama.py
class LlavaLlamaPolicy (line 10) | class LlavaLlamaPolicy(Policy):
method config_sanity_check (line 11) | def config_sanity_check(self):
method preprocess (line 14) | def preprocess(self):
method module_policy (line 26) | def module_policy(self) -> Dict[Union[str, nn.Module], ModulePolicyDes...
method postprocess (line 77) | def postprocess(self):
class LlavaLlamaForCausalLMPolicy (line 81) | class LlavaLlamaForCausalLMPolicy(LlavaLlamaPolicy):
method module_policy (line 82) | def module_policy(self):
FILE: Open-Sora/build/lib/tools/caption/acceleration/llava/policies/mistral.py
class LlavaMistralPolicy (line 11) | class LlavaMistralPolicy(Policy):
method config_sanity_check (line 12) | def config_sanity_check(self):
method preprocess (line 15) | def preprocess(self):
method module_policy (line 27) | def module_policy(self) -> Dict[Union[str, nn.Module], ModulePolicyDes...
method postprocess (line 91) | def postprocess(self):
class LlavaMistralForCausalLMPolicy (line 95) | class LlavaMistralForCausalLMPolicy(LlavaMistralPolicy):
method module_policy (line 96) | def module_policy(self):
FILE: Open-Sora/build/lib/tools/caption/camera_motion/camera_motion.py
function transform (line 10) | def transform(vector):
class CameraPredict (line 16) | class CameraPredict:
method __init__ (line 17) | def __init__(self, device, submodules_list, factor=0.25):
method infer (line 30) | def infer(self, video_path, save_video=False, save_dir="./saved_videos"):
method transform_class (line 46) | def transform_class(self, vector, min_reso): # 768*0.05
method get_edge_point (line 62) | def get_edge_point(self, track):
method get_edge_direction (line 71) | def get_edge_direction(self, track1, track2):
method classify_top_down (line 84) | def classify_top_down(self, top, down):
method classify_left_right (line 100) | def classify_left_right(self, left, right):
method camera_classify (line 115) | def camera_classify(self, track1, track2):
method predict (line 130) | def predict(self, video_path):
function compute_camera_motion (line 138) | def compute_camera_motion(device, submodules_dict, video_paths, factor):
FILE: Open-Sora/build/lib/tools/caption/camera_motion/detect.py
function process (line 11) | def process(paths: List[str], threshold: float) -> List[str]:
function main (line 18) | def main(args):
FILE: Open-Sora/build/lib/tools/caption/camera_motion/utils.py
function get_frame_indices (line 7) | def get_frame_indices(num_frames, vlen, sample="rand", fix_start=None, i...
function load_video (line 48) | def load_video(video_path, data_transform=None, num_frames=None, return_...
FILE: Open-Sora/build/lib/tools/caption/camera_motion/visualizer.py
function read_video_from_path (line 17) | def read_video_from_path(path):
function draw_circle (line 29) | def draw_circle(rgb, coord, radius, color=(255, 0, 0), visible=True):
function draw_line (line 44) | def draw_line(rgb, coord_y, coord_x, color, linewidth):
function add_weighted (line 54) | def add_weighted(rgb, alpha, original, beta, gamma):
class Visualizer (line 58) | class Visualizer:
method __init__ (line 59) | def __init__(
method visualize (line 83) | def visualize(
method save_video (line 133) | def save_video(self, video, filename, writer=None, step=0):
method draw_tracks_on_video (line 160) | def draw_tracks_on_video(
method _draw_pred_tracks (line 277) | def _draw_pred_tracks(
method _draw_gt_tracks (line 306) | def _draw_gt_tracks(
FILE: Open-Sora/build/lib/tools/caption/camera_motion_detect.py
function apply (line 13) | def apply(df, func, **kwargs):
function make_empty (line 28) | def make_empty(new_w, new_h):
function get_type (line 40) | def get_type(mag, ang, zoom_in, tau_static=1.0, tau_zoom=(0.4, 0.6)):
function get_video_type (line 58) | def get_video_type(frame_types):
function process (line 79) | def process(path: str, frame_interval=15) -> str:
function main (line 117) | def main(args):
FILE: Open-Sora/build/lib/tools/caption/caption_gpt4.py
function to_base64 (line 13) | def to_base64(image):
function get_caption (line 19) | def get_caption(frame, prompt, api_key):
function main (line 45) | def main(args):
FILE: Open-Sora/build/lib/tools/caption/caption_llama3.py
class CSVTextDataset (line 22) | class CSVTextDataset(Dataset):
method __init__ (line 23) | def __init__(self, csv_path):
method __len__ (line 28) | def __len__(self):
method __getitem__ (line 31) | def __getitem__(self, idx):
method set_rank_and_world_size (line 36) | def set_rank_and_world_size(self, rank, world_size):
method write_to_csv (line 44) | def write_to_csv(self, output_file, data, new_key):
function pad_left (line 56) | def pad_left(sequences, padding_value=0):
function main (line 75) | def main(args):
FILE: Open-Sora/build/lib/tools/caption/caption_llava.py
class NoPaddingDistributedSampler (line 27) | class NoPaddingDistributedSampler(DistributedSampler):
method __init__ (line 28) | def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True...
method __iter__ (line 41) | def __iter__(self):
function main (line 60) | def main(args):
FILE: Open-Sora/build/lib/tools/caption/utils.py
function read_file (line 59) | def read_file(input_path):
class VideoTextDataset (line 68) | class VideoTextDataset(torch.utils.data.Dataset):
method __init__ (line 69) | def __init__(self, csv_path, transform=None, num_frames=3, get_text_in...
method getitem (line 81) | def getitem(self, index):
method __len__ (line 114) | def __len__(self):
method __getitem__ (line 117) | def __getitem__(self, index):
function collate_fn (line 121) | def collate_fn(batch):
class Timer (line 130) | class Timer:
method __init__ (line 131) | def __init__(self):
method __enter__ (line 136) | def __enter__(self):
method __exit__ (line 140) | def __exit__(self, exc_type, exc_value, exc_tb):
FILE: Open-Sora/build/lib/tools/datasets/analyze.py
function read_file (line 8) | def read_file(input_path):
function parse_args (line 17) | def parse_args():
function plot_data (line 24) | def plot_data(data, column, bins, name):
function plot_categorical_data (line 32) | def plot_categorical_data(data, column, name):
function main (line 51) | def main(args):
FILE: Open-Sora/build/lib/tools/datasets/convert.py
function scan_recursively (line 12) | def scan_recursively(root):
function get_filelist (line 24) | def get_filelist(file_path, exts=None):
function split_by_capital (line 48) | def split_by_capital(name):
function process_imagenet (line 58) | def process_imagenet(root, split):
function process_ucf101 (line 69) | def process_ucf101(root, split):
function process_vidprom (line 82) | def process_vidprom(root, info):
function process_general_images (line 95) | def process_general_images(root, output):
function process_general_videos (line 108) | def process_general_videos(root, output):
FILE: Open-Sora/build/lib/tools/datasets/datautil.py
function apply (line 30) | def apply(df, func, **kwargs):
function get_video_length (line 43) | def get_video_length(cap, method="header"):
function get_info_old (line 53) | def get_info_old(path):
function get_info (line 77) | def get_info(path):
function get_image_info (line 88) | def get_image_info(path, backend="pillow"):
function get_video_info (line 117) | def get_video_info(path, backend="torchvision"):
function remove_caption_prefix (line 174) | def remove_caption_prefix(caption):
function merge_cmotion (line 215) | def merge_cmotion(caption, cmotion):
function build_lang_detector (line 228) | def build_lang_detector(lang_to_detect):
function basic_clean (line 251) | def basic_clean(text):
function clean_caption (line 264) | def clean_caption(caption):
function text_preprocessing (line 382) | def text_preprocessing(text, use_text_preprocessing: bool = True):
function load_caption (line 397) | def load_caption(path, ext):
function score_to_text (line 416) | def score_to_text(data):
function read_file (line 440) | def read_file(input_path):
function save_file (line 449) | def save_file(data, output_path):
function read_data (line 461) | def read_data(input_paths):
function main (line 490) | def main(args):
function parse_args (line 685) | def parse_args():
function get_output_path (line 769) | def get_output_path(args, input_name):
FILE: Open-Sora/build/lib/tools/datasets/filter_panda10m.py
function apply (line 22) | def apply(df, func, **kwargs):
function basic_clean (line 28) | def basic_clean(text):
function clean_caption (line 41) | def clean_caption(caption):
function get_10m_set (line 159) | def get_10m_set():
function filter_panda10m_text (line 191) | def filter_panda10m_text(meta_path, text_set):
function filter_panda10m_timestamp (line 212) | def filter_panda10m_timestamp(meta_path):
function parse_args (line 248) | def parse_args():
FILE: Open-Sora/build/lib/tools/datasets/split.py
function split_by_bucket (line 10) | def split_by_bucket(
FILE: Open-Sora/build/lib/tools/datasets/transform.py
function apply (line 23) | def apply(df, func, **kwargs):
function get_new_path (line 29) | def get_new_path(path, input_dir, output):
function resize (line 35) | def resize(path, length, input_dir, output):
function rand_crop (line 56) | def rand_crop(path, input_dir, output):
function main (line 79) | def main(args):
function parse_args (line 104) | def parse_args():
FILE: Open-Sora/build/lib/tools/datasets/utils.py
function is_video (line 11) | def is_video(filename):
function extract_frames (line 16) | def extract_frames(
FILE: Open-Sora/build/lib/tools/frame_interpolation/interpolation.py
function init (line 29) | def init():
function get_input_video_from_path (line 50) | def get_input_video_from_path(input_path):
function load_model (line 93) | def load_model(ckpt):
function interpolater (line 105) | def interpolater(model, inputs, scale, padder, iters=1):
function write (line 136) | def write(outputs, input_path, output_path, fps=30):
function process (line 162) | def process(
function parse_args (line 174) | def parse_args():
FILE: Open-Sora/build/lib/tools/frame_interpolation/networks/amt_g.py
class Model (line 10) | class Model(nn.Module):
method __init__ (line 11) | def __init__(self, corr_radius=3, corr_lvls=4, num_flows=5, channels=[...
method _get_updateblock (line 37) | def _get_updateblock(self, cdim, scale_factor=None):
method _corr_scale_lookup (line 50) | def _corr_scale_lookup(self, corr_fn, coord, flow0, flow1, embt, downs...
method forward (line 65) | def forward(self, img0, img1, embt, scale_factor=1.0, eval=False, **kw...
FILE: Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/feat_enc.py
class BottleneckBlock (line 5) | class BottleneckBlock(nn.Module):
method __init__ (line 6) | def __init__(self, in_planes, planes, norm_fn="group", stride=1):
method forward (line 50) | def forward(self, x):
class ResidualBlock (line 62) | class ResidualBlock(nn.Module):
method __init__ (line 63) | def __init__(self, in_planes, planes, norm_fn="group", stride=1):
method forward (line 102) | def forward(self, x):
class SmallEncoder (line 113) | class SmallEncoder(nn.Module):
method __init__ (line 114) | def __init__(self, output_dim=128, norm_fn="batch", dropout=0.0):
method _make_layer (line 153) | def _make_layer(self, dim, stride=1):
method forward (line 161) | def forward(self, x):
class BasicEncoder (line 186) | class BasicEncoder(nn.Module):
method __init__ (line 187) | def __init__(self, output_dim=128, norm_fn="batch", dropout=0.0):
method _make_layer (line 227) | def _make_layer(self, dim, stride=1):
method forward (line 235) | def forward(self, x):
class LargeEncoder (line 261) | class LargeEncoder(nn.Module):
method __init__ (line 262) | def __init__(self, output_dim=128, norm_fn="batch", dropout=0.0):
method _make_layer (line 303) | def _make_layer(self, dim, stride=1):
method forward (line 311) | def forward(self, x):
FILE: Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/ifrnet.py
function resize (line 8) | def resize(x, scale_factor):
function convrelu (line 12) | def convrelu(in_channels, out_channels, kernel_size=3, stride=1, padding...
class ResBlock (line 19) | class ResBlock(nn.Module):
method __init__ (line 20) | def __init__(self, in_channels, side_channels, bias=True):
method forward (line 40) | def forward(self, x):
class Encoder (line 57) | class Encoder(nn.Module):
method __init__ (line 58) | def __init__(self, channels, large=False):
method forward (line 70) | def forward(self, in_x):
class InitDecoder (line 79) | class InitDecoder(nn.Module):
method __init__ (line 80) | def __init__(self, in_ch, out_ch, skip_ch) -> None:
method forward (line 88) | def forward(self, f0, f1, embt):
class IntermediateDecoder (line 97) | class IntermediateDecoder(nn.Module):
method __init__ (line 98) | def __init__(self, in_ch, out_ch, skip_ch) -> None:
method forward (line 106) | def forward(self, ft_, f0, f1, flow0_in, flow1_in):
FILE: Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/multi_flow.py
function multi_flow_combine (line 9) | def multi_flow_combine(comb_block, img0, img1, flow0, flow1, mask=None, ...
class MultiFlowDecoder (line 41) | class MultiFlowDecoder(nn.Module):
method __init__ (line 42) | def __init__(self, in_ch, skip_ch, num_flows=3):
method forward (line 51) | def forward(self, ft_, f0, f1, flow0, flow1):
FILE: Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/raft.py
function resize (line 6) | def resize(x, scale_factor):
function bilinear_sampler (line 10) | def bilinear_sampler(img, coords, mask=False):
function coords_grid (line 27) | def coords_grid(batch, ht, wd, device):
class SmallUpdateBlock (line 33) | class SmallUpdateBlock(nn.Module):
method __init__ (line 34) | def __init__(self, cdim, hidden_dim, flow_dim, corr_dim, fc_dim, corr_...
method forward (line 64) | def forward(self, net, flow, corr):
class BasicUpdateBlock (line 84) | class BasicUpdateBlock(nn.Module):
method __init__ (line 85) | def __init__(
method forward (line 128) | def forward(self, net, flow, corr):
class BidirCorrBlock (line 148) | class BidirCorrBlock:
method __init__ (line 149) | def __init__(self, fmap1, fmap2, num_levels=4, radius=4):
method __call__ (line 171) | def __call__(self, coords0, coords1):
method corr (line 206) | def corr(fmap1, fmap2):
FILE: Open-Sora/build/lib/tools/frame_interpolation/utils/dist_utils.py
function get_world_size (line 6) | def get_world_size():
function get_global_rank (line 18) | def get_global_rank():
function get_local_rank (line 30) | def get_local_rank():
function get_master_ip (line 42) | def get_master_ip():
FILE: Open-Sora/build/lib/tools/frame_interpolation/utils/flow_utils.py
function warp (line 9) | def warp(img, flow):
function make_colorwheel (line 20) | def make_colorwheel():
function flow_uv_to_colors (line 68) | def flow_uv_to_colors(u, v, convert_to_bgr=False):
function flow_to_image (line 104) | def flow_to_image(flow_uv, clip_flow=None, convert_to_bgr=False):
FILE: Open-Sora/build/lib/tools/frame_interpolation/utils/utils.py
class AverageMeter (line 14) | class AverageMeter:
method __init__ (line 15) | def __init__(self):
method reset (line 18) | def reset(self):
method update (line 24) | def update(self, val, n=1):
class AverageMeterGroups (line 31) | class AverageMeterGroups:
method __init__ (line 32) | def __init__(self) -> None:
method update (line 35) | def update(self, dict, n=1):
method reset (line 41) | def reset(self, name=None):
method avg (line 50) | def avg(self, name):
class InputPadder (line 56) | class InputPadder:
method __init__ (line 59) | def __init__(self, dims, divisor=16):
method pad (line 65) | def pad(self, *inputs):
method unpad (line 71) | def unpad(self, *inputs):
method _unpad (line 77) | def _unpad(self, x):
function img2tensor (line 83) | def img2tensor(img):
function tensor2img (line 89) | def tensor2img(img_t):
function seed_all (line 93) | def seed_all(seed):
function read (line 100) | def read(file):
function write (line 119) | def write(file, data):
function readPFM (line 138) | def readPFM(file):
function writePFM (line 176) | def writePFM(file, image, scale=1):
function readFlow (line 206) | def readFlow(name):
function readImage (line 224) | def readImage(name):
function writeImage (line 234) | def writeImage(name, data):
function writeFlow (line 240) | def writeFlow(name, flow):
function readFloat (line 248) | def readFloat(name):
function writeFloat (line 273) | def writeFloat(name, data):
function check_dim_and_resize (line 299) | def check_dim_and_resize(tensor_list):
FILE: Open-Sora/build/lib/tools/scene_cut/convert_id_to_path.py
function is_intact_video (line 17) | def is_intact_video(video_path, mode="moviepy", verbose=False, logger=No...
function has_downloaded_success (line 50) | def has_downloaded_success(json_path):
function parse_args (line 65) | def parse_args():
function main (line 76) | def main():
FILE: Open-Sora/build/lib/tools/scene_cut/cut.py
function print_log (line 17) | def print_log(s, logger=None):
function process_single_row (line 24) | def process_single_row(row, args):
function split_video (line 71) | def split_video(
function parse_args (line 157) | def parse_args():
function main (line 178) | def main():
FILE: Open-Sora/build/lib/tools/scene_cut/scene_detect.py
function process_single_row (line 13) | def process_single_row(row):
function parse_args (line 34) | def parse_args():
function main (line 43) | def main():
FILE: Open-Sora/build/lib/tools/scoring/aesthetic/inference.py
function merge_scores (line 30) | def merge_scores(gathered_list: list, meta: pd.DataFrame, column):
class VideoTextDataset (line 53) | class VideoTextDataset(torch.utils.data.Dataset):
method __init__ (line 54) | def __init__(self, meta_path, transform=None, num_frames=3):
method __getitem__ (line 60) | def __getitem__(self, index):
method __len__ (line 80) | def __len__(self):
class MLP (line 84) | class MLP(nn.Module):
method __init__ (line 85) | def __init__(self, input_size):
method forward (line 99) | def forward(self, x):
class AestheticScorer (line 103) | class AestheticScorer(nn.Module):
method __init__ (line 104) | def __init__(self, input_size, device):
method forward (line 112) | def forward(self, x):
function parse_args (line 118) | def parse_args():
function main (line 131) | def main():
FILE: Open-Sora/build/lib/tools/scoring/matching/inference.py
function merge_scores (line 18) | def merge_scores(gathered_list: list, meta: pd.DataFrame, column):
class VideoTextDataset (line 38) | class VideoTextDataset(torch.utils.data.Dataset):
method __init__ (line 39) | def __init__(self, meta_path, transform):
method __getitem__ (line 44) | def __getitem__(self, index):
method __len__ (line 60) | def __len__(self):
function parse_args (line 64) | def parse_args():
function main (line 74) | def main():
FILE: Open-Sora/build/lib/vbench/__init__.py
class VBench (line 8) | class VBench(object):
method __init__ (line 9) | def __init__(self, device, full_info_dir, output_path):
method build_full_dimension_list (line 16) | def build_full_dimension_list(self, ):
method check_dimension_requires_extra_info (line 19) | def check_dimension_requires_extra_info(self, dimension_list):
method build_full_info_json (line 26) | def build_full_info_json(self, videos_path, name, dimension_list, prom...
method evaluate (line 134) | def evaluate(self, videos_path, name, prompt_list=[], dimension_list=N...
FILE: Open-Sora/build/lib/vbench/aesthetic_quality.py
function get_aesthetic_model (line 12) | def get_aesthetic_model(cache_folder):
function laion_aesthetic (line 36) | def laion_aesthetic(aesthetic_model, clip_model, video_list, device):
function compute_aesthetic_quality (line 59) | def compute_aesthetic_quality(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/appearance_style.py
function get_text_features (line 11) | def get_text_features(model, input_text, tokenizer, text_feature_dict={}):
function get_vid_features (line 21) | def get_vid_features(model, input_frames):
function get_predict_label (line 27) | def get_predict_label(clip_feature, text_feats_tensor, top=5):
function appearance_style (line 32) | def appearance_style(clip_model, video_dict, device, sample="rand"):
function compute_appearance_style (line 62) | def compute_appearance_style(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/background_consistency.py
function background_consistency (line 14) | def background_consistency(clip_model, preprocess, video_list, device, r...
function compute_background_consistency (line 53) | def compute_background_consistency(json_dir, device, submodules_list, **...
FILE: Open-Sora/build/lib/vbench/cli/evaluate.py
function register_subparsers (line 9) | def register_subparsers(subparser):
function evaluate (line 108) | def evaluate(args):
FILE: Open-Sora/build/lib/vbench/cli/static_filter.py
class StaticFilter (line 24) | class StaticFilter:
method __init__ (line 25) | def __init__(self, args, device):
method load_model (line 31) | def load_model(self):
method get_score (line 40) | def get_score(self, img, flo):
method check_static (line 57) | def check_static(self, score_list):
method set_params (line 72) | def set_params(self, frame, count):
method infer (line 77) | def infer(self, path):
method get_frames (line 92) | def get_frames(self, video_path):
function check_and_move (line 108) | def check_and_move(args, filter_results, target_path=None):
function static_filter (line 120) | def static_filter(args):
function register_subparsers (line 164) | def register_subparsers(subparser):
FILE: Open-Sora/build/lib/vbench/cli/vbench.py
function main (line 7) | def main():
function help (line 18) | def help(args):
FILE: Open-Sora/build/lib/vbench/color.py
function get_dect_from_grit (line 14) | def get_dect_from_grit(model, image_arrays):
function check_generate (line 30) | def check_generate(color_key, object_key, predictions):
function color (line 47) | def color(model, video_dict, device):
function compute_color (line 70) | def compute_color(json_dir, device, submodules_dict, **kwargs):
FILE: Open-Sora/build/lib/vbench/dynamic_degree.py
class DynamicDegree (line 15) | class DynamicDegree:
method __init__ (line 16) | def __init__(self, args, device):
method load_model (line 22) | def load_model(self):
method get_score (line 32) | def get_score(self, img, flo):
method set_params (line 49) | def set_params(self, frame, count):
method infer (line 54) | def infer(self, video_path):
method check_move (line 74) | def check_move(self, score_list):
method get_frames (line 86) | def get_frames(self, video_path):
method extract_frame (line 106) | def extract_frame(self, frame_list, interval=1):
method get_frames_from_img_folder (line 113) | def get_frames_from_img_folder(self, img_folder):
function dynamic_degree (line 131) | def dynamic_degree(dynamic, video_list):
function compute_dynamic_degree (line 143) | def compute_dynamic_degree(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/human_action.py
function build_dict (line 21) | def build_dict():
function human_action (line 34) | def human_action(umt_path, video_list, device):
function compute_human_action (line 98) | def compute_human_action(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/imaging_quality.py
function transform (line 7) | def transform(images, preprocess_mode='shorter'):
function technical_quality (line 29) | def technical_quality(model, video_list, device, **kwargs):
function compute_imaging_quality (line 46) | def compute_imaging_quality(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/motion_smoothness.py
class FrameProcess (line 19) | class FrameProcess:
method __init__ (line 20) | def __init__(self):
method get_frames (line 24) | def get_frames(self, video_path):
method get_frames_from_img_folder (line 39) | def get_frames_from_img_folder(self, img_folder):
method extract_frame (line 54) | def extract_frame(self, frame_list, start_from=0):
class MotionSmoothness (line 61) | class MotionSmoothness:
method __init__ (line 62) | def __init__(self, config, ckpt, device):
method load_model (line 71) | def load_model(self):
method initialization (line 84) | def initialization(self):
method motion_score (line 102) | def motion_score(self, video_path):
method vfi_score (line 147) | def vfi_score(self, ori_frames, interpolate_frames):
method get_diff (line 156) | def get_diff(self, img1, img2):
function motion_smoothness (line 162) | def motion_smoothness(motion, video_list):
function compute_motion_smoothness (line 174) | def compute_motion_smoothness(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/multiple_objects.py
function get_dect_from_grit (line 14) | def get_dect_from_grit(model, image_arrays):
function check_generate (line 27) | def check_generate(key_info, predictions):
function multiple_objects (line 37) | def multiple_objects(model, video_dict, device):
function compute_multiple_objects (line 56) | def compute_multiple_objects(json_dir, device, submodules_dict, **kwargs):
FILE: Open-Sora/build/lib/vbench/object_class.py
function get_dect_from_grit (line 14) | def get_dect_from_grit(model, image_arrays):
function check_generate (line 26) | def check_generate(key_info, predictions):
function object_class (line 33) | def object_class(model, video_dict, device):
function compute_object_class (line 52) | def compute_object_class(json_dir, device, submodules_dict, **kwargs):
FILE: Open-Sora/build/lib/vbench/overall_consistency.py
function get_text_features (line 12) | def get_text_features(model, input_text, tokenizer, text_feature_dict={}):
function get_vid_features (line 22) | def get_vid_features(model, input_frames):
function get_predict_label (line 28) | def get_predict_label(clip_feature, text_feats_tensor, top=5):
function overall_consistency (line 33) | def overall_consistency(clip_model, video_dict, tokenizer, device, sampl...
function compute_overall_consistency (line 56) | def compute_overall_consistency(json_dir, device, submodules_list, **kwa...
FILE: Open-Sora/build/lib/vbench/scene.py
function get_caption (line 14) | def get_caption(model, image_arrays):
function check_generate (line 18) | def check_generate(key_info, predictions):
function scene (line 27) | def scene(model, video_dict, device):
function compute_scene (line 51) | def compute_scene(json_dir, device, submodules_dict, **kwargs):
FILE: Open-Sora/build/lib/vbench/spatial_relationship.py
function get_position_score (line 14) | def get_position_score(locality, obj1,obj2, iou_threshold=0.1):
function get_dect_from_grit (line 73) | def get_dect_from_grit(model, image_arrays):
function check_generate (line 87) | def check_generate(key_info, predictions):
function spatial_relationship (line 106) | def spatial_relationship(model, video_dict, device):
function compute_spatial_relationship (line 124) | def compute_spatial_relationship(json_dir, device, submodules_dict, **kw...
FILE: Open-Sora/build/lib/vbench/subject_consistency.py
function subject_consistency (line 19) | def subject_consistency(model, video_list, device, read_frame):
function compute_subject_consistency (line 60) | def compute_subject_consistency(json_dir, device, submodules_list, **kwa...
FILE: Open-Sora/build/lib/vbench/temporal_flickering.py
function get_frames (line 7) | def get_frames(video_path):
function mae_seq (line 21) | def mae_seq(frames):
function calculate_mae (line 28) | def calculate_mae(img1, img2):
function cal_score (line 36) | def cal_score(video_path):
function temporal_flickering (line 43) | def temporal_flickering(video_list):
function compute_temporal_flickering (line 57) | def compute_temporal_flickering(json_dir, device, submodules_list, **kwa...
FILE: Open-Sora/build/lib/vbench/temporal_style.py
function get_text_features (line 12) | def get_text_features(model, input_text, tokenizer, text_feature_dict={}):
function get_vid_features (line 22) | def get_vid_features(model, input_frames):
function get_predict_label (line 28) | def get_predict_label(clip_feature, text_feats_tensor, top=5):
function temporal_style (line 33) | def temporal_style(clip_model, video_dict, tokenizer, device, sample="mi...
function compute_temporal_style (line 57) | def compute_temporal_style(json_dir, device, submodules_list, **kwargs):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/corr.py
class CorrBlock (line 12) | class CorrBlock:
method __init__ (line 13) | def __init__(self, fmap1, fmap2, num_levels=4, radius=4):
method __call__ (line 29) | def __call__(self, coords):
method corr (line 53) | def corr(fmap1, fmap2):
class AlternateCorrBlock (line 63) | class AlternateCorrBlock:
method __init__ (line 64) | def __init__(self, fmap1, fmap2, num_levels=4, radius=4):
method __call__ (line 74) | def __call__(self, coords):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/datasets.py
class FlowDataset (line 18) | class FlowDataset(data.Dataset):
method __init__ (line 19) | def __init__(self, aug_params=None, sparse=False):
method __getitem__ (line 34) | def __getitem__(self, index):
method __rmul__ (line 93) | def __rmul__(self, v):
method __len__ (line 98) | def __len__(self):
class MpiSintel (line 102) | class MpiSintel(FlowDataset):
method __init__ (line 103) | def __init__(self, aug_params=None, split='training', root='datasets/S...
class FlyingChairs (line 121) | class FlyingChairs(FlowDataset):
method __init__ (line 122) | def __init__(self, aug_params=None, split='train', root='datasets/Flyi...
class FlyingThings3D (line 137) | class FlyingThings3D(FlowDataset):
method __init__ (line 138) | def __init__(self, aug_params=None, root='datasets/FlyingThings3D', ds...
class KITTI (line 161) | class KITTI(FlowDataset):
method __init__ (line 162) | def __init__(self, aug_params=None, split='training', root='datasets/K...
class HD1K (line 180) | class HD1K(FlowDataset):
method __init__ (line 181) | def __init__(self, aug_params=None, root='datasets/HD1k'):
function fetch_dataloader (line 199) | def fetch_dataloader(args, TRAIN_DS='C+T+K+S+H'):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/extractor.py
class ResidualBlock (line 6) | class ResidualBlock(nn.Module):
method __init__ (line 7) | def __init__(self, in_planes, planes, norm_fn='group', stride=1):
method forward (line 48) | def forward(self, x):
class BottleneckBlock (line 60) | class BottleneckBlock(nn.Module):
method __init__ (line 61) | def __init__(self, in_planes, planes, norm_fn='group', stride=1):
method forward (line 107) | def forward(self, x):
class BasicEncoder (line 118) | class BasicEncoder(nn.Module):
method __init__ (line 119) | def __init__(self, output_dim=128, norm_fn='batch', dropout=0.0):
method _make_layer (line 159) | def _make_layer(self, dim, stride=1):
method forward (line 168) | def forward(self, x):
class SmallEncoder (line 195) | class SmallEncoder(nn.Module):
method __init__ (line 196) | def __init__(self, output_dim=128, norm_fn='batch', dropout=0.0):
method _make_layer (line 235) | def _make_layer(self, dim, stride=1):
method forward (line 244) | def forward(self, x):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/raft.py
class autocast (line 15) | class autocast:
method __init__ (line 16) | def __init__(self, enabled):
method __enter__ (line 18) | def __enter__(self):
method __exit__ (line 20) | def __exit__(self, *args):
class RAFT (line 24) | class RAFT(nn.Module):
method __init__ (line 25) | def __init__(self, args):
method freeze_bn (line 58) | def freeze_bn(self):
method initialize_flow (line 63) | def initialize_flow(self, img):
method upsample_flow (line 72) | def upsample_flow(self, flow, mask):
method forward (line 86) | def forward(self, image1, image2, iters=12, flow_init=None, upsample=T...
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/update.py
class FlowHead (line 6) | class FlowHead(nn.Module):
method __init__ (line 7) | def __init__(self, input_dim=128, hidden_dim=256):
method forward (line 13) | def forward(self, x):
class ConvGRU (line 16) | class ConvGRU(nn.Module):
method __init__ (line 17) | def __init__(self, hidden_dim=128, input_dim=192+128):
method forward (line 23) | def forward(self, h, x):
class SepConvGRU (line 33) | class SepConvGRU(nn.Module):
method __init__ (line 34) | def __init__(self, hidden_dim=128, input_dim=192+128):
method forward (line 45) | def forward(self, h, x):
class SmallMotionEncoder (line 62) | class SmallMotionEncoder(nn.Module):
method __init__ (line 63) | def __init__(self, args):
method forward (line 71) | def forward(self, flow, corr):
class BasicMotionEncoder (line 79) | class BasicMotionEncoder(nn.Module):
method __init__ (line 80) | def __init__(self, args):
method forward (line 89) | def forward(self, flow, corr):
class SmallUpdateBlock (line 99) | class SmallUpdateBlock(nn.Module):
method __init__ (line 100) | def __init__(self, args, hidden_dim=96):
method forward (line 106) | def forward(self, net, inp, corr, flow):
class BasicUpdateBlock (line 114) | class BasicUpdateBlock(nn.Module):
method __init__ (line 115) | def __init__(self, args, hidden_dim=128, input_dim=128):
method forward (line 127) | def forward(self, net, inp, corr, flow, upsample=True):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/augmentor.py
class FlowAugmentor (line 15) | class FlowAugmentor:
method __init__ (line 16) | def __init__(self, crop_size, min_scale=-0.2, max_scale=0.5, do_flip=T...
method color_transform (line 36) | def color_transform(self, img1, img2):
method eraser_transform (line 52) | def eraser_transform(self, img1, img2, bounds=[50, 100]):
method spatial_transform (line 67) | def spatial_transform(self, img1, img2, flow):
method __call__ (line 111) | def __call__(self, img1, img2, flow):
class SparseFlowAugmentor (line 122) | class SparseFlowAugmentor:
method __init__ (line 123) | def __init__(self, crop_size, min_scale=-0.2, max_scale=0.5, do_flip=F...
method color_transform (line 142) | def color_transform(self, img1, img2):
method eraser_transform (line 148) | def eraser_transform(self, img1, img2):
method resize_sparse_flow_map (line 161) | def resize_sparse_flow_map(self, flow, valid, fx=1.0, fy=1.0):
method spatial_transform (line 195) | def spatial_transform(self, img1, img2, flow, valid):
method __call__ (line 236) | def __call__(self, img1, img2, flow, valid):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/flow_viz.py
function make_colorwheel (line 20) | def make_colorwheel():
function flow_uv_to_colors (line 70) | def flow_uv_to_colors(u, v, convert_to_bgr=False):
function flow_to_image (line 109) | def flow_to_image(flow_uv, clip_flow=None, convert_to_bgr=False):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/frame_utils.py
function readFlow (line 12) | def readFlow(fn):
function readPFM (line 33) | def readPFM(file):
function writeFlow (line 70) | def writeFlow(filename,uv,v=None):
function readFlowKITTI (line 102) | def readFlowKITTI(filename):
function readDispKITTI (line 109) | def readDispKITTI(filename):
function writeFlowKITTI (line 116) | def writeFlowKITTI(filename, uv):
function read_gen (line 123) | def read_gen(file_name, pil=False):
FILE: Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/utils.py
class InputPadder (line 7) | class InputPadder:
method __init__ (line 9) | def __init__(self, dims, mode='sintel'):
method pad (line 18) | def pad(self, *inputs):
method unpad (line 21) | def unpad(self,x):
function forward_interpolate (line 26) | def forward_interpolate(flow):
function bilinear_sampler (line 57) | def bilinear_sampler(img, coords, mode='bilinear', mask=False):
function coords_grid (line 74) | def coords_grid(batch, ht, wd, device):
function upflow8 (line 80) | def upflow8(flow, mode='bilinear'):
FILE: Open-Sora/build/lib/vbench/third_pary/ViCLIP/simple_tokenizer.py
function default_bpe (line 10) | def default_bpe():
function bytes_to_unicode (line 20) | def bytes_to_unicode():
function get_pairs (line 42) | def get_pairs(word):
function basic_clean (line 54) | def basic_clean(text):
function whitespace_clean (line 60) | def whitespace_clean(text):
class SimpleTokenizer (line 66) | class SimpleTokenizer(object):
method __init__ (line 67) | def __init__(self, bpe_path: str = default_bpe()):
method bpe (line 84) | def bpe(self, token):
method encode (line 125) | def encode(self, text):
method decode (line 133) | def decode(self, tokens):
FILE: Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip.py
class ViCLIP (line 16) | class ViCLIP(nn.Module):
method __init__ (line 19) | def __init__(self, tokenizer=None, pretrain=os.path.join(os.path.dirn...
method freeze_text (line 67) | def freeze_text(self):
method no_weight_decay (line 72) | def no_weight_decay(self):
method forward (line 83) | def forward(self, image, text, raw_text, idx, log_generation=None, ret...
method encode_vision (line 114) | def encode_vision(self, image, test=False):
method encode_text (line 138) | def encode_text(self, text):
method clip_contrastive_temperature (line 158) | def clip_contrastive_temperature(self, min_val=0.001, max_val=0.5):
method build_vision_encoder (line 162) | def build_vision_encoder(self):
method build_text_encoder (line 181) | def build_text_encoder(self):
method get_text_encoder (line 199) | def get_text_encoder(self):
method get_text_features (line 204) | def get_text_features(self, input_text, tokenizer, text_feature_dict={}):
method get_vid_features (line 215) | def get_vid_features(self, input_frames):
method get_predict_label (line 221) | def get_predict_label(self, clip_feature, text_feats_tensor, top=5):
FILE: Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip_text.py
class LayerNorm (line 23) | class LayerNorm(nn.LayerNorm):
method forward (line 26) | def forward(self, x: torch.Tensor):
class QuickGELU (line 32) | class QuickGELU(nn.Module):
method forward (line 33) | def forward(self, x: torch.Tensor):
class ResidualAttentionBlock (line 37) | class ResidualAttentionBlock(nn.Module):
method __init__ (line 38) | def __init__(self, d_model: int, n_head: int, attn_mask: torch.Tensor ...
method attention (line 51) | def attention(self, x: torch.Tensor):
method forward (line 55) | def forward(self, x: torch.Tensor):
class Transformer (line 61) | class Transformer(nn.Module):
method __init__ (line 62) | def __init__(self, width: int, layers: int, heads: int, attn_mask: tor...
method forward (line 71) | def forward(self, x: torch.Tensor):
class CLIP_TEXT (line 79) | class CLIP_TEXT(nn.Module):
method __init__ (line 80) | def __init__(
method no_weight_decay (line 110) | def no_weight_decay(self):
method build_attention_mask (line 114) | def build_attention_mask(self):
method tokenize (line 122) | def tokenize(self, texts, context_length=77, truncate=True):
method forward (line 160) | def forward(self, text):
function clip_text_b16 (line 176) | def clip_text_b16(
function clip_text_l14 (line 200) | def clip_text_l14(
function clip_text_l14_336 (line 243) | def clip_text_l14_336(
function build_clip (line 267) | def build_clip(config):
FILE: Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip_vision.py
function load_temp_embed_with_mismatch (line 16) | def load_temp_embed_with_mismatch(temp_embed_old, temp_embed_new, add_ze...
class QuickGELU (line 49) | class QuickGELU(nn.Module):
method forward (line 50) | def forward(self, x):
class ResidualAttentionBlock (line 54) | class ResidualAttentionBlock(nn.Module):
method __init__ (line 55) | def __init__(self, d_model, n_head, drop_path=0., attn_mask=None, drop...
method attention (line 72) | def attention(self, x):
method forward (line 76) | def forward(self, x):
class Transformer (line 82) | class Transformer(nn.Module):
method __init__ (line 83) | def __init__(self, width, layers, heads, drop_path=0., checkpoint_num=...
method forward (line 91) | def forward(self, x):
class VisionTransformer (line 100) | class VisionTransformer(nn.Module):
method __init__ (line 101) | def __init__(
method get_num_layers (line 134) | def get_num_layers(self):
method no_weight_decay (line 138) | def no_weight_decay(self):
method mask_tokens (line 141) | def mask_tokens(self, inputs, masking_prob=0.0):
method forward (line 157) | def forward(self, x, masking_prob=0.0):
function inflate_weight (line 197) | def inflate_weight(weight_2d, time_dim, center=True):
function load_state_dict (line 210) | def load_state_dict(model, state_dict, input_resolution=224, patch_size=...
function clip_joint_b16 (line 242) | def clip_joint_b16(
function clip_joint_l14 (line 261) | def clip_joint_l14(
function clip_joint_l14_336 (line 285) | def clip_joint_l14_336(
function interpolate_pos_embed_vit (line 303) | def interpolate_pos_embed_vit(state_dict, new_model):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/benchmarks/snu_film.py
function parse_path (line 16) | def parse_path(path):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/datasets/adobe_datasets.py
class Adobe240_Dataset (line 19) | class Adobe240_Dataset(Dataset):
method __init__ (line 20) | def __init__(self, dataset_dir='data/adobe240/test_frames', interFrame...
method __getitem__ (line 36) | def __getitem__(self, idx):
method __len__ (line 74) | def __len__(self):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/datasets/gopro_datasets.py
function random_resize_woflow (line 14) | def random_resize_woflow(img0, imgt, img1, p=0.1):
function random_crop_woflow (line 21) | def random_crop_woflow(img0, imgt, img1, crop_size=(224, 224)):
function center_crop_woflow (line 31) | def center_crop_woflow(img0, imgt, img1, crop_size=(512, 512)):
function random_reverse_channel_woflow (line 39) | def random_reverse_channel_woflow(img0, imgt, img1, p=0.5):
function random_vertical_flip_woflow (line 46) | def random_vertical_flip_woflow(img0, imgt, img1, p=0.3):
function random_horizontal_flip_woflow (line 53) | def random_horizontal_flip_woflow(img0, imgt, img1, p=0.5):
function random_rotate_woflow (line 60) | def random_rotate_woflow(img0, imgt, img1, p=0.05):
function random_reverse_time_woflow (line 67) | def random_reverse_time_woflow(img0, imgt, img1, embt, p=0.5):
class GoPro_Train_Dataset (line 75) | class GoPro_Train_Dataset(Dataset):
method __init__ (line 76) | def __init__(self, dataset_dir='data/GOPRO', interFrames=7, augment=Tr...
method __len__ (line 98) | def __len__(self):
method __getitem__ (line 101) | def __getitem__(self, idx):
class GoPro_Test_Dataset (line 139) | class GoPro_Test_Dataset(Dataset):
method __init__ (line 140) | def __init__(self, dataset_dir='data/GOPRO', interFrames=7):
method __len__ (line 159) | def __len__(self):
method __getitem__ (line 162) | def __getitem__(self, idx):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/datasets/vimeo_datasets.py
function random_resize (line 13) | def random_resize(img0, imgt, img1, flow, p=0.1):
function random_crop (line 21) | def random_crop(img0, imgt, img1, flow, crop_size=(224, 224)):
function random_reverse_channel (line 32) | def random_reverse_channel(img0, imgt, img1, flow, p=0.5):
function random_vertical_flip (line 39) | def random_vertical_flip(img0, imgt, img1, flow, p=0.3):
function random_horizontal_flip (line 48) | def random_horizontal_flip(img0, imgt, img1, flow, p=0.5):
function random_rotate (line 57) | def random_rotate(img0, imgt, img1, flow, p=0.05):
function random_reverse_time (line 66) | def random_reverse_time(img0, imgt, img1, flow, p=0.5):
class Vimeo90K_Train_Dataset (line 75) | class Vimeo90K_Train_Dataset(Dataset):
method __init__ (line 76) | def __init__(self,
method __len__ (line 102) | def __len__(self):
method __getitem__ (line 105) | def __getitem__(self, idx):
class Vimeo90K_Test_Dataset (line 132) | class Vimeo90K_Test_Dataset(Dataset):
method __init__ (line 133) | def __init__(self, dataset_dir='data/vimeo_triplet'):
method __len__ (line 151) | def __len__(self):
method __getitem__ (line 154) | def __getitem__(self, idx):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/flow_generation/gen_flow.py
function pred_flow (line 24) | def pred_flow(img1, img2):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/flow_generation/liteflownet/run.py
function backwarp (line 43) | def backwarp(tenInput, tenFlow):
class Network (line 58) | class Network(torch.nn.Module):
method __init__ (line 59) | def __init__(self):
method forward (line 301) | def forward(self, tenOne, tenTwo):
function estimate (line 337) | def estimate(tenOne, tenTwo):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/losses/loss.py
class Loss (line 7) | class Loss(nn.Module):
method __init__ (line 8) | def __init__(self, loss_weight, keys, mapping=None) -> None:
method forward (line 20) | def forward(self, **kwargs):
method _forward (line 29) | def _forward(self, **kwargs):
class CharbonnierLoss (line 33) | class CharbonnierLoss(Loss):
method __init__ (line 34) | def __init__(self, loss_weight, keys) -> None:
method _forward (line 37) | def _forward(self, imgt_pred, imgt):
class AdaCharbonnierLoss (line 43) | class AdaCharbonnierLoss(Loss):
method __init__ (line 44) | def __init__(self, loss_weight, keys) -> None:
method _forward (line 47) | def _forward(self, imgt_pred, imgt, weight):
class TernaryLoss (line 56) | class TernaryLoss(Loss):
method __init__ (line 57) | def __init__(self, loss_weight, keys, patch_size=7):
method transform (line 65) | def transform(self, tensor):
method valid_mask (line 73) | def valid_mask(self, tensor):
method _forward (line 80) | def _forward(self, imgt_pred, imgt):
class GeometryLoss (line 90) | class GeometryLoss(Loss):
method __init__ (line 91) | def __init__(self, loss_weight, keys, patch_size=3):
method transform (line 99) | def transform(self, tensor):
method valid_mask (line 109) | def valid_mask(self, tensor):
method _forward (line 116) | def _forward(self, ft_pred, ft_gt):
class IFRFlowLoss (line 128) | class IFRFlowLoss(Loss):
method __init__ (line 129) | def __init__(self, loss_weight, keys, beta=0.3) -> None:
method _forward (line 134) | def _forward(self, flow0_pred, flow1_pred, flow):
method resize (line 153) | def resize(self, x, scale_factor):
method get_robust_weight (line 156) | def get_robust_weight(self, flow_pred, flow_gt):
class MultipleFlowLoss (line 162) | class MultipleFlowLoss(Loss):
method __init__ (line 163) | def __init__(self, loss_weight, keys, beta=0.3) -> None:
method _forward (line 168) | def _forward(self, flow0_pred, flow1_pred, flow):
method resize (line 187) | def resize(self, x, scale_factor):
method get_mutli_flow_robust_weight (line 190) | def get_mutli_flow_robust_weight(self, flow_pred, flow_gt):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/metrics/psnr_ssim.py
function gaussian (line 7) | def gaussian(window_size, sigma):
function create_window (line 12) | def create_window(window_size, channel=1):
function create_window_3d (line 19) | def create_window_3d(window_size, channel=1):
function ssim (line 27) | def ssim(img1, img2, window_size=11, window=None, size_average=True, ful...
function calculate_ssim (line 78) | def calculate_ssim(img1, img2, window_size=11, window=None, size_average...
function calculate_psnr (line 133) | def calculate_psnr(img1, img2):
function calculate_ie (line 138) | def calculate_ie(img1, img2):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/AMT-G.py
class Model (line 23) | class Model(nn.Module):
method __init__ (line 24) | def __init__(self,
method _get_updateblock (line 55) | def _get_updateblock(self, cdim, scale_factor=None):
method _corr_scale_lookup (line 61) | def _corr_scale_lookup(self, corr_fn, coord, flow0, flow1, embt, downs...
method forward (line 76) | def forward(self, img0, img1, embt, scale_factor=1.0, eval=False, **kw...
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/AMT-L.py
class Model (line 21) | class Model(nn.Module):
method __init__ (line 22) | def __init__(self,
method _get_updateblock (line 52) | def _get_updateblock(self, cdim, scale_factor=None):
method _corr_scale_lookup (line 58) | def _corr_scale_lookup(self, corr_fn, coord, flow0, flow1, embt, downs...
method forward (line 73) | def forward(self, img0, img1, embt, scale_factor=1.0, eval=False, **kw...
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/AMT-S.py
class Model (line 22) | class Model(nn.Module):
method __init__ (line 23) | def __init__(self,
method _get_updateblock (line 54) | def _get_updateblock(self, cdim, scale_factor=None):
method _corr_scale_lookup (line 59) | def _corr_scale_lookup(self, corr_fn, coord, flow0, flow1, embt, downs...
method forward (line 74) | def forward(self, img0, img1, embt, scale_factor=1.0, eval=False, **kw...
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/blocks/feat_enc.py
class BottleneckBlock (line 5) | class BottleneckBlock(nn.Module):
method __init__ (line 6) | def __init__(self, in_planes, planes, norm_fn='group', stride=1):
method forward (line 52) | def forward(self, x):
class ResidualBlock (line 64) | class ResidualBlock(nn.Module):
method __init__ (line 65) | def __init__(self, in_planes, planes, norm_fn='group', stride=1):
method forward (line 106) | def forward(self, x):
class SmallEncoder (line 117) | class SmallEncoder(nn.Module):
method __init__ (line 118) | def __init__(self, output_dim=128, norm_fn='batch', dropout=0.0):
method _make_layer (line 157) | def _make_layer(self, dim, stride=1):
method forward (line 166) | def forward(self, x):
class BasicEncoder (line 191) | class BasicEncoder(nn.Module):
method __init__ (line 192) | def __init__(self, output_dim=128, norm_fn='batch', dropout=0.0):
method _make_layer (line 232) | def _make_layer(self, dim, stride=1):
method forward (line 241) | def forward(self, x):
class LargeEncoder (line 267) | class LargeEncoder(nn.Module):
method __init__ (line 268) | def __init__(self, output_dim=128, norm_fn='batch', dropout=0.0):
method _make_layer (line 309) | def _make_layer(self, dim, stride=1):
method forward (line 318) | def forward(self, x):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/blocks/ifrnet.py
function resize (line 7) | def resize(x, scale_factor):
function convrelu (line 10) | def convrelu(in_channels, out_channels, kernel_size=3, stride=1, padding...
class ResBlock (line 16) | class ResBlock(nn.Module):
method __init__ (line 17) | def __init__(self, in_channels, side_channels, bias=True):
method forward (line 39) | def forward(self, x):
class Encoder (line 55) | class Encoder(nn.Module):
method __init__ (line 56) | def __init__(self, channels, large=False):
method forward (line 70) | def forward(self, in_x):
class InitDecoder (line 78) | class InitDecoder(nn.Module):
method __init__ (line 79) | def __init__(self, in_ch, out_ch, skip_ch) -> None:
method forward (line 86) | def forward(self, f0, f1, embt):
class IntermediateDecoder (line 94) | class IntermediateDecoder(nn.Module):
method __init__ (line 95) | def __init__(self, in_ch, out_ch, skip_ch) -> None:
method forward (line 102) | def forward(self, ft_, f0, f1, flow0_in, flow1_in):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/blocks/multi_flow.py
function multi_flow_combine (line 10) | def multi_flow_combine(comb_block, img0, img1, flow0, flow1,
class MultiFlowDecoder (line 46) | class MultiFlowDecoder(nn.Module):
method __init__ (line 47) | def __init__(self, in_ch, skip_ch, num_flows=3):
method forward (line 56) | def forward(self, ft_, f0, f1, flow0, flow1):
FILE: Open-Sora/build/lib/vbench/third_pary/amt/networks/blocks/raft.py
function resize (line 6) | def resize(x, scale_factor):
function bilinear_sampler (line 10) | def bilinear_sampler(img, coords, mask=False):
function coords_grid (line 27) | def coords_grid(batch, ht, wd, device):
class SmallUpdateBlock (line 35) | class SmallUpdateBlock(nn.Module):
method __init__ (line 36) | def __init__(self, cdim, hidden_dim, flow_dim, corr_dim, fc_dim,
method forward (line 67) | def forward(self, net, flow, corr):
class BasicUpdateBlock (line 88) | class BasicUpdateBlock(nn.Module):
method __init__ (line 89) | def __init__(self, cdim, hidden_dim, flow_dim, corr_dim, corr_dim2,
method forward (line 121) | def forward(self, net, flow, corr):
class BidirCorrBlock (line 142) | class BidirCorrBlock:
method __init__ (line 143) | def __init__(self, fmap1, fmap2, num_levels=4, radius=4):
method __call__ (line 165) | def __call__(self, coords0, coords1):
method corr (line 200) | def corr(fmap1, fmap2):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_model.py
class DenseCaptioning (line 7) | class DenseCaptioning():
method __init__ (line 8) | def __init__(self, device):
method initialize_model (line 13) | def initialize_model(self, model_weight):
method initialize_model_det (line 16) | def initialize_model_det(self, model_weight):
method image_dense_caption (line 19) | def image_dense_caption(self, image_src):
method run_caption_api (line 27) | def run_caption_api(self,image_src):
method run_caption_tensor (line 34) | def run_caption_tensor(self,img):
method run_det_tensor (line 39) | def run_det_tensor(self,img):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/config.py
function add_centernet_config (line 3) | def add_centernet_config(cfg):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/bifpn.py
function get_fpn_config (line 22) | def get_fpn_config(base_reduction=8):
function swish (line 40) | def swish(x, inplace: bool = False):
class Swish (line 46) | class Swish(nn.Module):
method __init__ (line 47) | def __init__(self, inplace: bool = False):
method forward (line 51) | def forward(self, x):
class SequentialAppend (line 55) | class SequentialAppend(nn.Sequential):
method __init__ (line 56) | def __init__(self, *args):
method forward (line 59) | def forward(self, x):
class SequentialAppendLast (line 65) | class SequentialAppendLast(nn.Sequential):
method __init__ (line 66) | def __init__(self, *args):
method forward (line 70) | def forward(self, x):
class ConvBnAct2d (line 76) | class ConvBnAct2d(nn.Module):
method __init__ (line 77) | def __init__(self, in_channels, out_channels, kernel_size, stride=1, d...
method forward (line 88) | def forward(self, x):
class SeparableConv2d (line 97) | class SeparableConv2d(nn.Module):
method __init__ (line 100) | def __init__(self, in_channels, out_channels, kernel_size=3, stride=1,...
method forward (line 125) | def forward(self, x):
class ResampleFeatureMap (line 135) | class ResampleFeatureMap(nn.Sequential):
method __init__ (line 136) | def __init__(self, in_channels, out_channels, reduction_ratio=1., pad_...
class FpnCombine (line 174) | class FpnCombine(nn.Module):
method __init__ (line 175) | def __init__(self, feature_info, fpn_config, fpn_channels, inputs_offs...
method forward (line 205) | def forward(self, x):
class BiFpnLayer (line 229) | class BiFpnLayer(nn.Module):
method __init__ (line 230) | def __init__(self, feature_info, fpn_config, fpn_channels, num_levels=...
method forward (line 274) | def forward(self, x):
class BiFPN (line 279) | class BiFPN(Backbone):
method __init__ (line 280) | def __init__(
method size_divisibility (line 363) | def size_divisibility(self):
method forward (line 366) | def forward(self, x):
function build_resnet_bifpn_backbone (line 381) | def build_resnet_bifpn_backbone(cfg, input_shape: ShapeSpec):
function build_p37_dla_bifpn_backbone (line 404) | def build_p37_dla_bifpn_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/bifpn_fcos.py
function swish (line 16) | def swish(x):
function split_name (line 20) | def split_name(name):
class FeatureMapResampler (line 27) | class FeatureMapResampler(nn.Module):
method __init__ (line 28) | def __init__(self, in_channels, out_channels, stride, norm=""):
method forward (line 43) | def forward(self, x):
class BackboneWithTopLevels (line 59) | class BackboneWithTopLevels(Backbone):
method __init__ (line 60) | def __init__(self, backbone, out_channels, num_top_levels, norm=""):
method forward (line 89) | def forward(self, x):
class SingleBiFPN (line 103) | class SingleBiFPN(Backbone):
method __init__ (line 109) | def __init__(
method forward (line 192) | def forward(self, feats):
class BiFPN (line 268) | class BiFPN(Backbone):
method __init__ (line 274) | def __init__(
method size_divisibility (line 337) | def size_divisibility(self):
method forward (line 340) | def forward(self, x):
function _assert_strides_are_log2_contiguous (line 361) | def _assert_strides_are_log2_contiguous(strides):
function build_fcos_resnet_bifpn_backbone (line 372) | def build_fcos_resnet_bifpn_backbone(cfg, input_shape: ShapeSpec):
function build_p35_fcos_resnet_bifpn_backbone (line 398) | def build_p35_fcos_resnet_bifpn_backbone(cfg, input_shape: ShapeSpec):
function build_p35_fcos_dla_bifpn_backbone (line 423) | def build_p35_fcos_dla_bifpn_backbone(cfg, input_shape: ShapeSpec):
function build_p37_fcos_dla_bifpn_backbone (line 447) | def build_p37_fcos_dla_bifpn_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/dla.py
function get_model_url (line 38) | def get_model_url(data, name, hash):
class BasicBlock (line 41) | class BasicBlock(nn.Module):
method __init__ (line 42) | def __init__(self, inplanes, planes, stride=1, dilation=1, norm='BN'):
method forward (line 55) | def forward(self, x, residual=None):
class Bottleneck (line 71) | class Bottleneck(nn.Module):
method __init__ (line 74) | def __init__(self, inplanes, planes, stride=1, dilation=1, norm='BN'):
method forward (line 91) | def forward(self, x, residual=None):
class Root (line 111) | class Root(nn.Module):
method __init__ (line 112) | def __init__(self, in_channels, out_channels, kernel_size, residual, n...
method forward (line 121) | def forward(self, *x):
class Tree (line 132) | class Tree(nn.Module):
method __init__ (line 133) | def __init__(self, levels, block, in_channels, out_channels, stride=1,
method forward (line 174) | def forward(self, x, residual=None, children=None):
class DLA (line 189) | class DLA(nn.Module):
method __init__ (line 190) | def __init__(self, num_layers, levels, channels,
method load_pretrained_model (line 223) | def load_pretrained_model(self, data, name, hash):
method _make_conv_level (line 233) | def _make_conv_level(self, inplanes, planes, convs, stride=1, dilation...
method forward (line 245) | def forward(self, x):
function fill_up_weights (line 254) | def fill_up_weights(up):
class _DeformConv (line 266) | class _DeformConv(nn.Module):
method __init__ (line 267) | def __init__(self, chi, cho, norm='BN'):
method forward (line 290) | def forward(self, x):
class IDAUp (line 304) | class IDAUp(nn.Module):
method __init__ (line 305) | def __init__(self, o, channels, up_f, norm='BN'):
method forward (line 323) | def forward(self, layers, startp, endp):
class DLAUp (line 332) | class DLAUp(nn.Module):
method __init__ (line 333) | def __init__(self, startp, channels, scales, in_channels=None, norm='B...
method forward (line 349) | def forward(self, layers):
class DLASeg (line 363) | class DLASeg(Backbone):
method __init__ (line 364) | def __init__(self, num_layers, out_features, use_dla_up=True,
method size_divisibility (line 396) | def size_divisibility(self):
method forward (line 399) | def forward(self, x):
function build_dla_backbone (line 425) | def build_dla_backbone(cfg, input_shape):
class LastLevelP6P7 (line 439) | class LastLevelP6P7(nn.Module):
method __init__ (line 445) | def __init__(self, in_channels, out_channels):
method forward (line 454) | def forward(self, c5):
function build_retinanet_dla_fpn_backbone (line 460) | def build_retinanet_dla_fpn_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/dlafpn.py
function get_model_url (line 25) | def get_model_url(data, name, hash):
function conv3x3 (line 30) | def conv3x3(in_planes, out_planes, stride=1):
class BasicBlock (line 36) | class BasicBlock(nn.Module):
method __init__ (line 37) | def __init__(self, cfg, inplanes, planes, stride=1, dilation=1):
method forward (line 50) | def forward(self, x, residual=None):
class Bottleneck (line 67) | class Bottleneck(nn.Module):
method __init__ (line 70) | def __init__(self, cfg, inplanes, planes, stride=1, dilation=1):
method forward (line 87) | def forward(self, x, residual=None):
class Root (line 108) | class Root(nn.Module):
method __init__ (line 109) | def __init__(self, cfg, in_channels, out_channels, kernel_size, residu...
method forward (line 118) | def forward(self, *x):
class Tree (line 129) | class Tree(nn.Module):
method __init__ (line 130) | def __init__(self, cfg, levels, block, in_channels, out_channels, stri...
method forward (line 169) | def forward(self, x, residual=None, children=None):
class DLA (line 187) | class DLA(Backbone):
method __init__ (line 188) | def __init__(self, cfg, levels, channels, block=BasicBlock, residual_r...
method load_pretrained_model (line 224) | def load_pretrained_model(self, data, name, hash):
method _make_conv_level (line 232) | def _make_conv_level(self, inplanes, planes, convs, stride=1, dilation...
method forward (line 244) | def forward(self, x):
function fill_up_weights (line 254) | def fill_up_weights(up):
class Conv (line 266) | class Conv(nn.Module):
method __init__ (line 267) | def __init__(self, chi, cho, norm):
method forward (line 274) | def forward(self, x):
class DeformConv (line 278) | class DeformConv(nn.Module):
method __init__ (line 279) | def __init__(self, chi, cho, norm):
method forward (line 294) | def forward(self, x):
class IDAUp (line 304) | class IDAUp(nn.Module):
method __init__ (line 305) | def __init__(self, o, channels, up_f, norm='FrozenBN', node_type=Conv):
method forward (line 323) | def forward(self, layers, startp, endp):
class DLAUP (line 337) | class DLAUP(Backbone):
method __init__ (line 338) | def __init__(self, bottom_up, in_features, norm, dlaup_node='conv'):
method size_divisibility (line 376) | def size_divisibility(self):
method forward (line 379) | def forward(self, x):
function dla34 (line 394) | def dla34(cfg, pretrained=None): # DLA-34
class LastLevelP6P7 (line 401) | class LastLevelP6P7(nn.Module):
method __init__ (line 407) | def __init__(self, in_channels, out_channels):
method forward (line 416) | def forward(self, c5):
function build_dla_fpn3_backbone (line 423) | def build_dla_fpn3_backbone(cfg, input_shape: ShapeSpec):
function build_dla_fpn5_backbone (line 448) | def build_dla_fpn5_backbone(cfg, input_shape: ShapeSpec):
function build_dlaup_backbone (line 475) | def build_dlaup_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/fpn_p5.py
class LastLevelP6P7_P5 (line 15) | class LastLevelP6P7_P5(nn.Module):
method __init__ (line 21) | def __init__(self, in_channels, out_channels):
method forward (line 30) | def forward(self, c5):
function build_p67_resnet_fpn_backbone (line 37) | def build_p67_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):
function build_p35_resnet_fpn_backbone (line 59) | def build_p35_resnet_fpn_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/backbone/res2net.py
class BasicBlock (line 43) | class BasicBlock(CNNBlockBase):
method __init__ (line 49) | def __init__(self, in_channels, out_channels, *, stride=1, norm="BN"):
method forward (line 96) | def forward(self, x):
class BottleneckBlock (line 111) | class BottleneckBlock(CNNBlockBase):
method __init__ (line 116) | def __init__(
method forward (line 233) | def forward(self, x):
class DeformBottleneckBlock (line 266) | class DeformBottleneckBlock(ResNetBlockBase):
method __init__ (line 272) | def __init__(
method forward (line 429) | def forward(self, x):
function make_stage (line 483) | def make_stage(block_class, num_blocks, first_stride, *, in_channels, ou...
class BasicStem (line 511) | class BasicStem(CNNBlockBase):
method __init__ (line 516) | def __init__(self, in_channels=3, out_channels=64, norm="BN"):
method forward (line 560) | def forward(self, x):
class ResNet (line 568) | class ResNet(Backbone):
method __init__ (line 569) | def __init__(self, stem, stages, num_classes=None, out_features=None):
method forward (line 624) | def forward(self, x):
method output_shape (line 641) | def output_shape(self):
method freeze (line 649) | def freeze(self, freeze_at=0):
function build_res2net_backbone (line 670) | def build_res2net_backbone(cfg, input_shape):
function build_p67_res2net_fpn_backbone (line 759) | def build_p67_res2net_fpn_backbone(cfg, input_shape: ShapeSpec):
function build_res2net_bifpn_backbone (line 782) | def build_res2net_bifpn_backbone(cfg, input_shape: ShapeSpec):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/debug.py
function _get_color_image (line 9) | def _get_color_image(heatmap):
function _blend_image (line 20) | def _blend_image(image, color_map, a=0.7):
function _blend_image_heatmaps (line 25) | def _blend_image_heatmaps(image, color_maps, a=0.7):
function _decompose_level (line 33) | def _decompose_level(x, shapes_per_level, N):
function _imagelist_to_tensor (line 50) | def _imagelist_to_tensor(images):
function _ind2il (line 63) | def _ind2il(ind, shapes_per_level, N):
function debug_train (line 73) | def debug_train(
function debug_test (line 141) | def debug_test(
function debug_second_stage (line 218) | def debug_second_stage(images, instances, proposals=None, vis_thresh=0.3,
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/dense_heads/centernet.py
class CenterNet (line 31) | class CenterNet(nn.Module):
method __init__ (line 33) | def __init__(self,
method from_config (line 131) | def from_config(cls, cfg, input_shape):
method forward (line 179) | def forward(self, images, features_dict, gt_instances):
method losses (line 237) | def losses(
method compute_grids (line 317) | def compute_grids(self, features):
method _get_ground_truth (line 338) | def _get_ground_truth(self, grids, shapes_per_level, gt_instances):
method _get_label_inds (line 439) | def _get_label_inds(self, gt_instances, shapes_per_level):
method assign_fpn_level (line 486) | def assign_fpn_level(self, boxes):
method assign_reg_fpn (line 505) | def assign_reg_fpn(self, reg_targets_per_im, size_ranges):
method _get_reg_targets (line 519) | def _get_reg_targets(self, reg_targets, dist, mask, area):
method _create_heatmaps_from_dist (line 533) | def _create_heatmaps_from_dist(self, dist, labels, channels):
method _create_agn_heatmaps_from_dist (line 551) | def _create_agn_heatmaps_from_dist(self, dist):
method _flatten_outputs (line 565) | def _flatten_outputs(self, clss, reg_pred, agn_hm_pred):
method get_center3x3 (line 576) | def get_center3x3(self, locations, centers, strides):
method inference (line 595) | def inference(self, images, clss_per_level, reg_pred_per_level,
method predict_instances (line 626) | def predict_instances(
method predict_single_level (line 641) | def predict_single_level(
method nms_and_topK (line 708) | def nms_and_topK(self, boxlists, nms=True):
method _add_more_pos (line 736) | def _add_more_pos(self, reg_pred, gt_instances, shapes_per_level):
method _get_c33_inds (line 768) | def _get_c33_inds(self, gt_instances, shapes_per_level):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/dense_heads/centernet_head.py
class Scale (line 13) | class Scale(nn.Module):
method __init__ (line 14) | def __init__(self, init_value=1.0):
method forward (line 18) | def forward(self, input):
class CenterNetHead (line 21) | class CenterNetHead(nn.Module):
method __init__ (line 23) | def __init__(self,
method from_config (line 124) | def from_config(cls, cfg, input_shape):
method forward (line 141) | def forward(self, x):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/dense_heads/utils.py
function _transpose (line 15) | def _transpose(training_targets, num_loc_list):
function reduce_sum (line 32) | def reduce_sum(tensor):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/layers/deform_conv.py
class _NewEmptyTensorOp (line 7) | class _NewEmptyTensorOp(torch.autograd.Function):
method forward (line 9) | def forward(ctx, x, new_shape):
method backward (line 14) | def backward(ctx, grad):
class DFConv2d (line 19) | class DFConv2d(nn.Module):
method __init__ (line 21) | def __init__(
method forward (line 91) | def forward(self, x, return_offset=False):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/layers/heatmap_focal_loss.py
function heatmap_focal_loss (line 5) | def heatmap_focal_loss(
function binary_heatmap_focal_loss (line 51) | def binary_heatmap_focal_loss(
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/layers/iou_loss.py
class IOULoss (line 5) | class IOULoss(nn.Module):
method __init__ (line 6) | def __init__(self, loc_loss_type='iou'):
method forward (line 10) | def forward(self, pred, target, weight=None, reduction='sum'):
function giou_loss (line 66) | def giou_loss(
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/layers/ml_nms.py
function ml_nms (line 4) | def ml_nms(boxlist, nms_thresh, max_proposals=-1,
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/meta_arch/centernet_detector.py
class CenterNetDetector (line 13) | class CenterNetDetector(nn.Module):
method __init__ (line 14) | def __init__(self, cfg):
method forward (line 25) | def forward(self, batched_inputs):
method device (line 38) | def device(self):
method inference (line 43) | def inference(self, batched_inputs, do_postprocess=True):
method preprocess_image (line 62) | def preprocess_image(self, batched_inputs):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/roi_heads/custom_fast_rcnn.py
class CustomFastRCNNOutputLayers (line 25) | class CustomFastRCNNOutputLayers(FastRCNNOutputLayers):
method __init__ (line 26) | def __init__(
method losses (line 36) | def losses(self, predictions, proposals):
method sigmoid_cross_entropy_loss (line 65) | def sigmoid_cross_entropy_loss(self, pred_class_logits, gt_classes):
method softmax_cross_entropy_loss (line 84) | def softmax_cross_entropy_loss(self, pred_class_logits, gt_classes):
method inference (line 96) | def inference(self, predictions, proposals):
method predict_probs (line 117) | def predict_probs(self, predictions, proposals):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/roi_heads/custom_roi_heads.py
class CustomROIHeads (line 23) | class CustomROIHeads(StandardROIHeads):
method _init_box_head (line 25) | def _init_box_head(self, cfg, input_shape):
method forward (line 41) | def forward(self, images, features, proposals, targets=None):
class CustomCascadeROIHeads (line 71) | class CustomCascadeROIHeads(CascadeROIHeads):
method _init_box_head (line 73) | def _init_box_head(self, cfg, input_shape):
method _forward_box (line 98) | def _forward_box(self, features, proposals, targets=None):
method forward (line 156) | def forward(self, images, features, proposals, targets=None):
FILE: Open-Sora/build/lib/vbench/third_pary/grit_src/centernet2/centernet/modeling/roi_heads/fed_loss.py
function load_class_freq (line 6) | def load_class_freq(
function get_fed_loss_inds (line 15) | def get_fed_loss_inds(
FILE: Open-Sora/build/lib/vbench/third_pary/tag2Text/med.py
class BertEmbeddings_nopos (line 52) | class BertEmbeddings_nopos(nn.Module):
method __init__ (line 55) | def __init__(self, config):
method forward (line 71) | def forward(
class BertEmbeddings (line 100) | class BertEmbeddings(nn.Module):
method __init__ (line 103) | def __init__(self, config):
method forward (line 119) | def forward(
class BertSelfAttention (line 146) | class BertSelfAttention(nn.Module):
method __init__ (line 147) | def __init__(self, config, is_cross_attention):
method save_attn_gradients (line 175) | def save_attn_gradients(self, attn_gradients):
method get_attn_gradients (line 178) | def get_attn_gradients(self):
method save_attention_map (line 181) | def save_attention_map(self, attention_map):
method get_attention_map (line 184) | def get_attention_map(self):
method transpose_for_scores (line 187) | def transpose_for_scores(self, x):
method forward (line 192) | def forward(
class BertSelfOutput (line 284) | class BertSelfOutput(nn.Module):
method __init__ (line 285) | def __init__(self, config):
method forward (line 291) | def forward(self, hidden_states, input_tensor):
class BertAttention (line 298) | class BertAttention(nn.Module):
method __init__ (line 299) | def __init__(self, config, is_cross_attention=False):
method prune_heads (line 305) | def prune_heads(self, heads):
method forward (line 323) | def forward(
class BertIntermediate (line 347) | class BertIntermediate(nn.Module):
method __init__ (line 348) | def __init__(self, config):
method forward (line 356) | def forward(self, hidden_states):
class BertOutput (line 362) | class BertOutput(nn.Module):
method __init__ (line 363) | def __init__(self, config):
method forward (line 369) | def forward(self, hidden_states, input_tensor):
class BertLayer (line 376) | class BertLayer(nn.Module):
method __init__ (line 377) | def __init__(self, config, layer_num):
method forward (line 389) | def forward(
method feed_forward_chunk (line 457) | def feed_forward_chunk(self, attention_output):
class BertEncoder (line 463) | class BertEncoder(nn.Module):
method __init__ (line 464) | def __init__(self, config):
method forward (line 470) | def forward(
class BertPooler (line 563) | class BertPooler(nn.Module):
method __init__ (line 564) | def __init__(self, config):
method forward (line 569) | def forward(self, hidden_states):
class BertPredictionHeadTransform (line 578) | class BertPredictionHeadTransform(nn.Module):
method __init__ (line 579) | def __init__(self, config):
method forward (line 588) | def forward(self, hidden_states):
class BertLMPredictionHead (line 595) | class BertLMPredictionHead(nn.Module):
method __init__ (line 596) | def __init__(self, config):
method forward (line 609) | def forward(self, hidden_states):
class BertOnlyMLMHead (line 615) | class BertOnlyMLMHead(nn.Module):
method __init__ (line 616) | def __init__(self, config):
method forward (line 620) | def forward(self, sequence_output):
class BertPreTrainedModel (line 625) | class BertPreTrainedModel(PreTrainedModel):
method _init_weights (line 635) | def _init_weights(self, module):
class BertModel (line 648) | class BertModel(BertPreTrainedModel):
method __init__ (line 658) | def __init__(self, config, add_pooling_layer=True):
method get_input_embeddings (line 671) | def get_input_embeddings(self):
method set_input_embeddings (line 674) | def set_input_embeddings(self, value):
method _prune_heads (line 677) | def _prune_heads(self, heads_to_prune):
method get_extended_attention_mask (line 686) | def get_extended_attention_mask(self, attention_mask: Tensor, input_sh...
method forward (line 747) | def forward(
class BertLMHeadModel (line 887) | class BertLMHeadModel(BertPreTrainedModel):
method __init__ (line 892) | def __init__(self, config):
method get_output_embeddings (line 900) | def get_output_embeddings(self):
method set_output_embeddings (line 903) | def set_output_embeddings(self, new_embeddings):
method forward (line 906) | def forward(
method prepare_inputs_for_generation (line 1012) | def prepare_inputs_for_generation(self, input_ids, past=None, attentio...
method _reorder_cache (line 1031) | def _reorder_cache(self, past, beam_idx):
FILE: Open-Sora/build/lib/vbench/third_pary/tag2Text/swin_transformer.py
class Mlp (line 17) | class Mlp(nn.Module):
method __init__ (line 18) | def __init__(self, in_features, hidden_features=None, out_features=Non...
method forward (line 27) | def forward(self, x):
function window_partition (line 36) | def window_partition(x, window_size):
function window_reverse (line 51) | def window_reverse(windows, window_size, H, W):
class WindowAttention (line 68) | class WindowAttention(nn.Module):
method __init__ (line 82) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
method forward (line 116) | def forward(self, x, mask=None):
method extra_repr (line 149) | def extra_repr(self) -> str:
method flops (line 152) | def flops(self, N):
class SwinTransformerBlock (line 166) | class SwinTransformerBlock(nn.Module):
method __init__ (line 185) | def __init__(self, dim, input_resolution, num_heads, window_size=7, sh...
method forward (line 236) | def forward(self, x):
method extra_repr (line 275) | def extra_repr(self) -> str:
method flops (line 279) | def flops(self):
class PatchMerging (line 294) | class PatchMerging(nn.Module):
method __init__ (line 303) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
method forward (line 310) | def forward(self, x):
method extra_repr (line 333) | def extra_repr(self) -> str:
method flops (line 336) | def flops(self):
class BasicLayer (line 343) | class BasicLayer(nn.Module):
method __init__ (line 363) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
method forward (line 391) | def forward(self, x):
method extra_repr (line 401) | def extra_repr(self) -> str:
method flops (line 404) | def flops(self):
class PatchEmbed (line 413) | class PatchEmbed(nn.Module):
method __init__ (line 424) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
method forward (line 443) | def forward(self, x):
method flops (line 453) | def flops(self):
class SwinTransformer (line 461) | class SwinTransformer(nn.Module):
method __init__ (line 487) | def __init__(self, img_size=224, patch_size=4, in_chans=3, num_classes...
method _init_weights (line 545) | def _init_weights(self, m):
method no_weight_decay (line 555) | def no_weight_decay(self):
method no_weight_decay_keywords (line 559) | def no_weight_decay_keywords(self):
method forward (line 562) | def forward(self, x, idx_to_group_img=None, image_atts=None, **kwargs):
method flops (line 586) | def flops(self):
function interpolate_relative_pos_embed (line 596) | def interpolate_relative_pos_embed(rel_pos_bias, dst_num_pos, param_name...
FILE: Open-Sora/build/lib/vbench/third_pary/tag2Text/tag2text.py
function read_json (line 26) | def read_json(rpath):
class Tag2Text_Caption (line 32) | class Tag2Text_Caption(nn.Module):
method __init__ (line 33) | def __init__(self,
method del_selfattention (line 109) | def del_selfattention(self):
method generate (line 114) | def generate(self, image, sample=False, num_beams=3, max_length=30, mi...
function tag2text_caption (line 213) | def tag2text_caption(pretrained='',**kwargs):
function tie_encoder_decoder_weights (line 226) | def tie_encoder_decoder_weights(encoder: nn.Module, decoder: nn.Module, ...
class GroupWiseLinear (line 298) | class GroupWiseLinear(nn.Module):
method __init__ (line 302) | def __init__(self, num_class, hidden_dim, bias=True):
method reset_parameters (line 313) | def reset_parameters(self):
method forward (line 321) | def forward(self, x):
function init_tokenizer (line 329) | def init_tokenizer():
function create_vit (line 337) | def create_vit(vit, image_size, use_grad_checkpointing=False, ckpt_layer...
function is_url (line 354) | def is_url(url_or_filename):
function load_checkpoint (line 358) | def load_checkpoint(model,url_or_filename):
function load_checkpoint_swinbase (line 383) | def load_checkpoint_swinbase(model,url_or_filename,kwargs):
FILE: Open-Sora/build/lib/vbench/third_pary/tag2Text/vit.py
class Mlp (line 23) | class Mlp(nn.Module):
method __init__ (line 26) | def __init__(self, in_features, hidden_features=None, out_features=Non...
method forward (line 35) | def forward(self, x):
class Attention (line 44) | class Attention(nn.Module):
method __init__ (line 45) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
method save_attn_gradients (line 58) | def save_attn_gradients(self, attn_gradients):
method get_attn_gradients (line 61) | def get_attn_gradients(self):
method save_attention_map (line 64) | def save_attention_map(self, attention_map):
method get_attention_map (line 67) | def get_attention_map(self):
method forward (line 70) | def forward(self, x, register_hook=False):
class Block (line 89) | class Block(nn.Module):
method __init__ (line 91) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
method forward (line 107) | def forward(self, x, register_hook=False):
class VisionTransformer (line 113) | class VisionTransformer(nn.Module):
method __init__ (line 118) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
method _init_weights (line 167) | def _init_weights(self, m):
method no_weight_decay (line 177) | def no_weight_decay(self):
method forward (line 180) | def forward(self, x, register_blk=-1):
method load_pretrained (line 197) | def load_pretrained(self, checkpoint_path, prefix=''):
function _load_weights (line 202) | def _load_weights(model: VisionTransformer, checkpoint_path: str, prefix...
function interpolate_pos_embed (line 281) | def interpolate_pos_embed(pos_embed_checkpoint, visual_encoder):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/build.py
class DataAugmentationForVideoMAE (line 11) | class DataAugmentationForVideoMAE(object):
method __init__ (line 12) | def __init__(self, args):
method __call__ (line 45) | def __call__(self, images):
method __repr__ (line 52) | def __repr__(self):
function build_pretraining_dataset (line 60) | def build_pretraining_dataset(args):
function build_dataset (line 83) | def build_dataset(is_train, test_mode, args):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/kinetics.py
class VideoClsDataset (line 26) | class VideoClsDataset(Dataset):
method __init__ (line 29) | def __init__(self, anno_path, prefix='', split=' ', mode='train', clip...
method __getitem__ (line 100) | def __getitem__(self, index):
method _aug_frame (line 177) | def _aug_frame(
method loadvideo_decord (line 239) | def loadvideo_decord(self, sample, sample_rate_scale=1, chunk_nb=0):
method __len__ (line 306) | def __len__(self):
function spatial_sampling (line 313) | def spatial_sampling(
function tensor_normalize (line 387) | def tensor_normalize(tensor, mean, std):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/kinetics_sparse.py
class VideoClsDataset_sparse (line 27) | class VideoClsDataset_sparse(Dataset):
method __init__ (line 30) | def __init__(self, anno_path, prefix='', split=' ', mode='train', clip...
method __getitem__ (line 101) | def __getitem__(self, index):
method _aug_frame (line 176) | def _aug_frame(
method _get_seq_frames (line 237) | def _get_seq_frames(self, video_size, num_frames, clip_idx=-1):
method loadvideo_decord (line 260) | def loadvideo_decord(self, sample, chunk_nb=0):
method __len__ (line 294) | def __len__(self):
function spatial_sampling (line 301) | def spatial_sampling(
function tensor_normalize (line 375) | def tensor_normalize(tensor, mean, std):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/mae.py
class VideoMAE (line 18) | class VideoMAE(torch.utils.data.Dataset):
method __init__ (line 72) | def __init__(self,
method __getitem__ (line 134) | def __getitem__(self, index):
method __len__ (line 197) | def __len__(self):
method _make_dataset (line 200) | def _make_dataset(self, directory, setting):
method _sample_train_indices (line 226) | def _sample_train_indices(self, num_frames):
method _get_frame_id_list (line 248) | def _get_frame_id_list(self, duration, indices, skip_offsets):
method _video_TSN_decord_batch_loader (line 262) | def _video_TSN_decord_batch_loader(self, directory, video_reader, dura...
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/masking_generator.py
class TubeMaskingGenerator (line 4) | class TubeMaskingGenerator:
method __init__ (line 5) | def __init__(self, input_size, mask_ratio):
method __repr__ (line 12) | def __repr__(self):
method __call__ (line 18) | def __call__(self):
class RandomMaskingGenerator (line 28) | class RandomMaskingGenerator:
method __init__ (line 29) | def __init__(self, input_size, mask_ratio):
method __repr__ (line 38) | def __repr__(self):
method __call__ (line 43) | def __call__(self):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/mixup.py
function one_hot (line 17) | def one_hot(x, num_classes, on_value=1., off_value=0., device='cuda'):
function mixup_target (line 22) | def mixup_target(target, num_classes, lam=1., smoothing=0.0, device='cud...
function rand_bbox (line 30) | def rand_bbox(img_shape, lam, margin=0., count=None):
function rand_bbox_minmax (line 54) | def rand_bbox_minmax(img_shape, minmax, count=None):
function cutmix_bbox_and_lam (line 77) | def cutmix_bbox_and_lam(img_shape, lam, ratio_minmax=None, correct_lam=T...
class Mixup (line 90) | class Mixup:
method __init__ (line 104) | def __init__(self, mixup_alpha=1., cutmix_alpha=0., cutmix_minmax=None...
method _params_per_elem (line 121) | def _params_per_elem(self, batch_size):
method _params_per_batch (line 141) | def _params_per_batch(self):
method _mix_elem (line 159) | def _mix_elem(self, x):
method _mix_pair (line 176) | def _mix_pair(self, x):
method _mix_batch (line 196) | def _mix_batch(self, x):
method __call__ (line 209) | def __call__(self, x, target):
class FastCollateMixup (line 221) | class FastCollateMixup(Mixup):
method _mix_elem_collate (line 227) | def _mix_elem_collate(self, output, batch, half=False):
method _mix_pair_collate (line 252) | def _mix_pair_collate(self, output, batch):
method _mix_batch_collate (line 280) | def _mix_batch_collate(self, output, batch):
method __call__ (line 299) | def __call__(self, batch, _=None):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/rand_augment.py
function _interpolation (line 50) | def _interpolation(kwargs):
function _check_args_tf (line 58) | def _check_args_tf(kwargs):
function shear_x (line 64) | def shear_x(img, factor, **kwargs):
function shear_y (line 71) | def shear_y(img, factor, **kwargs):
function translate_x_rel (line 78) | def translate_x_rel(img, pct, **kwargs):
function translate_y_rel (line 86) | def translate_y_rel(img, pct, **kwargs):
function translate_x_abs (line 94) | def translate_x_abs(img, pixels, **kwargs):
function translate_y_abs (line 101) | def translate_y_abs(img, pixels, **kwargs):
function rotate (line 108) | def rotate(img, degrees, **kwargs):
function auto_contrast (line 142) | def auto_contrast(img, **__):
function invert (line 146) | def invert(img, **__):
function equalize (line 150) | def equalize(img, **__):
function solarize (line 154) | def solarize(img, thresh, **__):
function solarize_add (line 158) | def solarize_add(img, add, thresh=128, **__):
function posterize (line 173) | def posterize(img, bits_to_keep, **__):
function contrast (line 179) | def contrast(img, factor, **__):
function color (line 183) | def color(img, factor, **__):
function brightness (line 187) | def brightness(img, factor, **__):
function sharpness (line 191) | def sharpness(img, factor, **__):
function _randomly_negate (line 195) | def _randomly_negate(v):
function _rotate_level_to_arg (line 200) | def _rotate_level_to_arg(level, _hparams):
function _enhance_level_to_arg (line 207) | def _enhance_level_to_arg(level, _hparams):
function _enhance_increasing_level_to_arg (line 212) | def _enhance_increasing_level_to_arg(level, _hparams):
function _shear_level_to_arg (line 220) | def _shear_level_to_arg(level, _hparams):
function _translate_abs_level_to_arg (line 227) | def _translate_abs_level_to_arg(level, hparams):
function _translate_rel_level_to_arg (line 234) | def _translate_rel_level_to_arg(level, hparams):
function _posterize_level_to_arg (line 242) | def _posterize_level_to_arg(level, _hparams):
function _posterize_increasing_level_to_arg (line 249) | def _posterize_increasing_level_to_arg(level, hparams):
function _posterize_original_level_to_arg (line 256) | def _posterize_original_level_to_arg(level, _hparams):
function _solarize_level_to_arg (line 263) | def _solarize_level_to_arg(level, _hparams):
function _solarize_increasing_level_to_arg (line 269) | def _solarize_increasing_level_to_arg(level, _hparams):
function _solarize_add_level_to_arg (line 275) | def _solarize_add_level_to_arg(level, _hparams):
class AugmentOp (line 337) | class AugmentOp:
method __init__ (line 342) | def __init__(self, name, prob=0.5, magnitude=10, hparams=None):
method __call__ (line 364) | def __call__(self, img_list):
function _select_rand_weights (line 444) | def _select_rand_weights(weight_idx=0, transforms=None):
function rand_augment_ops (line 453) | def rand_augment_ops(magnitude=10, hparams=None, transforms=None):
class RandAugment (line 462) | class RandAugment:
method __init__ (line 463) | def __init__(self, ops, num_layers=2, choice_weights=None):
method __call__ (line 468) | def __call__(self, img):
function rand_augment_transform (line 481) | def rand_augment_transform(config_str, hparams):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/random_erasing.py
function _get_pixels (line 11) | def _get_pixels(
class RandomErasing (line 27) | class RandomErasing:
method __init__ (line 46) | def __init__(
method _erase (line 80) | def _erase(self, img, chan, img_h, img_w, dtype):
method _erase_cube (line 109) | def _erase_cube(
method __call__ (line 151) | def __call__(self, input):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/ssv2.py
class SSRawFrameClsDataset (line 26) | class SSRawFrameClsDataset(Dataset):
method __init__ (line 29) | def __init__(self, anno_path, prefix='', split=' ', mode='train', clip...
method __getitem__ (line 105) | def __getitem__(self, index):
method _aug_frame (line 195) | def _aug_frame(
method load_frame (line 252) | def load_frame(self, sample, num_frames, sample_rate_scale=1):
method __len__ (line 315) | def __len__(self):
class SSVideoClsDataset (line 322) | class SSVideoClsDataset(Dataset):
method __init__ (line 325) | def __init__(self, anno_path, prefix='', split=' ', mode='train', clip...
method __getitem__ (line 394) | def __getitem__(self, index):
method _aug_frame (line 470) | def _aug_frame(
method loadvideo_decord (line 532) | def loadvideo_decord(self, sample, sample_rate_scale=1):
method __len__ (line 591) | def __len__(self):
function spatial_sampling (line 598) | def spatial_sampling(
function tensor_normalize (line 672) | def tensor_normalize(tensor, mean, std):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/transforms.py
class GroupRandomCrop (line 11) | class GroupRandomCrop(object):
method __init__ (line 12) | def __init__(self, size):
method __call__ (line 18) | def __call__(self, img_tuple):
class GroupCenterCrop (line 39) | class GroupCenterCrop(object):
method __init__ (line 40) | def __init__(self, size):
method __call__ (line 43) | def __call__(self, img_tuple):
class GroupRandomHorizontalFlip (line 48) | class GroupRandomHorizontalFlip(object):
method __init__ (line 49) | def __init__(self, flip=False):
method __call__ (line 52) | def __call__(self, img_tuple):
class GroupNormalize (line 62) | class GroupNormalize(object):
method __init__ (line 63) | def __init__(self, mean, std):
method __call__ (line 67) | def __call__(self, tensor_tuple):
class GroupGrayScale (line 79) | class GroupGrayScale(object):
method __init__ (line 80) | def __init__(self, size):
method __call__ (line 83) | def __call__(self, img_tuple):
class GroupColorJitter (line 88) | class GroupColorJitter(object):
method __init__ (line 89) | def __init__(self, size):
method __call__ (line 94) | def __call__(self, img_tuple):
class GroupScale (line 99) | class GroupScale(object):
method __init__ (line 108) | def __init__(self, size, interpolation=Image.BILINEAR):
method __call__ (line 111) | def __call__(self, img_tuple):
class GroupMultiScaleCrop (line 116) | class GroupMultiScaleCrop(object):
method __init__ (line 118) | def __init__(self, input_size, scales=None, max_distort=1, fix_crop=Tr...
method __call__ (line 126) | def __call__(self, img_tuple):
method _sample_crop_size (line 136) | def _sample_crop_size(self, im_size):
method _sample_fix_offset (line 160) | def _sample_fix_offset(self, image_w, image_h, crop_w, crop_h):
method fill_fix_offset (line 165) | def fill_fix_offset(more_fix_crop, image_w, image_h, crop_w, crop_h):
class Stack (line 189) | class Stack(object):
method __init__ (line 191) | def __init__(self, roll=False):
method __call__ (line 194) | def __call__(self, img_tuple):
class ToTorchFormatTensor (line 206) | class ToTorchFormatTensor(object):
method __init__ (line 209) | def __init__(self, div=True):
method __call__ (line 212) | def __call__(self, pic_tuple):
class IdentityTransform (line 228) | class IdentityTransform(object):
method __call__ (line 230) | def __call__(self, data):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/video_transforms.py
function _pil_interp (line 32) | def _pil_interp(method):
function random_short_side_scale_jitter (line 43) | def random_short_side_scale_jitter(
function crop_boxes (line 100) | def crop_boxes(boxes, x_offset, y_offset):
function random_crop (line 119) | def random_crop(images, size, boxes=None):
function horizontal_flip (line 155) | def horizontal_flip(prob, images, boxes=None):
function uniform_crop (line 190) | def uniform_crop(images, size, spatial_idx, boxes=None, scale_size=None):
function clip_boxes_to_image (line 253) | def clip_boxes_to_image(boxes, height, width):
function blend (line 275) | def blend(images1, images2, alpha):
function grayscale (line 291) | def grayscale(images):
function color_jitter (line 313) | def color_jitter(images, img_brightness=0, img_contrast=0, img_saturatio...
function brightness_jitter (line 348) | def brightness_jitter(var, images):
function contrast_jitter (line 367) | def contrast_jitter(var, images):
function saturation_jitter (line 387) | def saturation_jitter(var, images):
function lighting_jitter (line 406) | def lighting_jitter(images, alphastd, eigval, eigvec):
function color_normalization (line 454) | def color_normalization(images, mean, stddev):
function _get_param_spatial_crop (line 498) | def _get_param_spatial_crop(
function random_resized_crop (line 540) | def random_resized_crop(
function random_resized_crop_with_shift (line 575) | def random_resized_crop_with_shift(
function create_random_augment (line 620) | def create_random_augment(
function random_sized_crop_img (line 656) | def random_sized_crop_img(
class RandomResizedCropAndInterpolation (line 691) | class RandomResizedCropAndInterpolation:
method __init__ (line 704) | def __init__(
method get_params (line 726) | def get_params(img, scale, ratio):
method __call__ (line 766) | def __call__(self, img):
method __repr__ (line 780) | def __repr__(self):
function transforms_imagenet_train (line 798) | def transforms_imagenet_train(
class Compose (line 901) | class Compose(object):
method __init__ (line 908) | def __init__(self, transforms):
method __call__ (line 911) | def __call__(self, clip):
class RandomHorizontalFlip (line 917) | class RandomHorizontalFlip(object):
method __call__ (line 922) | def __call__(self, clip):
class RandomResize (line 943) | class RandomResize(object):
method __init__ (line 953) | def __init__(self, ratio=(3. / 4., 4. / 3.), interpolation='nearest'):
method __call__ (line 957) | def __call__(self, clip):
class Resize (line 973) | class Resize(object):
method __init__ (line 983) | def __init__(self, size, interpolation='nearest'):
method __call__ (line 987) | def __call__(self, clip):
class RandomCrop (line 993) | class RandomCrop(object):
method __init__ (line 1000) | def __init__(self, size):
method __call__ (line 1006) | def __call__(self, clip):
class ThreeCrop (line 1037) | class ThreeCrop(object):
method __init__ (line 1044) | def __init__(self, size):
method __call__ (line 1050) | def __call__(self, clip):
class RandomRotation (line 1084) | class RandomRotation(object):
method __init__ (line 1093) | def __init__(self, degrees):
method __call__ (line 1106) | def __call__(self, clip):
class CenterCrop (line 1127) | class CenterCrop(object):
method __init__ (line 1134) | def __init__(self, size):
method __call__ (line 1140) | def __call__(self, clip):
class ColorJitter (line 1171) | class ColorJitter(object):
method __init__ (line 1184) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
method get_params (line 1190) | def get_params(self, brightness, contrast, saturation, hue):
method __call__ (line 1215) | def __call__(self, clip):
class Normalize (line 1254) | class Normalize(object):
method __init__ (line 1266) | def __init__(self, mean, std):
method __call__ (line 1270) | def __call__(self, clip):
method __repr__ (line 1279) | def __repr__(self):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/datasets/volume_transforms.py
function convert_img (line 6) | def convert_img(img):
class ClipToTensor (line 16) | class ClipToTensor(object):
method __init__ (line 21) | def __init__(self, channel_nb=3, div_255=True, numpy=False):
method __call__ (line 26) | def __call__(self, clip):
class ClipToTensor_K (line 71) | class ClipToTensor_K(object):
method __init__ (line 76) | def __init__(self, channel_nb=3, div_255=True, numpy=False):
method __call__ (line 81) | def __call__(self, clip):
class ToTensor (line 125) | class ToTensor(object):
method __call__ (line 129) | def __call__(self, array):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/functional.py
function _is_tensor_clip (line 8) | def _is_tensor_clip(clip):
function crop_clip (line 12) | def crop_clip(clip, min_h, min_w, h, w):
function resize_clip (line 26) | def resize_clip(clip, size, interpolation='bilinear'):
function get_resize_sizes (line 67) | def get_resize_sizes(im_h, im_w, size):
function normalize (line 77) | def normalize(clip, mean, std, inplace=False):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/models/clip.py
class LayerNorm (line 18) | class LayerNorm(nn.LayerNorm):
method forward (line 21) | def forward(self, x):
class QuickGELU (line 27) | class QuickGELU(nn.Module):
method forward (line 28) | def forward(self, x):
class ResidualAttentionBlock (line 32) | class ResidualAttentionBlock(nn.Module):
method __init__ (line 33) | def __init__(self, d_model, n_head, attn_mask=None):
method attention (line 46) | def attention(self, x, return_attn=False):
method forward (line 53) | def forward(self, x, return_attn=False):
class Transformer (line 65) | class Transformer(nn.Module):
method __init__ (line 66) | def __init__(
method forward (line 85) | def forward(self, x):
class VisionTransformer (line 99) | class VisionTransformer(nn.Module):
method __init__ (line 100) | def __init__(
method forward (line 135) | def forward(self, x, mask=None):
function inflate_weight (line 175) | def inflate_weight(weight_2d, time_dim, center=True):
function load_state_dict (line 188) | def load_state_dict(model, state_dict, input_resolution=224, patch_size=...
function clip_b16 (line 218) | def clip_b16(
function clip_l14 (line 239) | def clip_l14(
function clip_l14_336 (line 260) | def clip_l14_336(
FILE: Open-Sora/build/lib/vbench/third_pary/umt/models/modeling_finetune.py
function _cfg (line 11) | def _cfg(url='', **kwargs):
class DropPath (line 21) | class DropPath(nn.Module):
method __init__ (line 24) | def __init__(self, drop_prob=None):
method forward (line 28) | def forward(self, x):
method extra_repr (line 31) | def extra_repr(self) -> str:
class Mlp (line 35) | class Mlp(nn.Module):
method __init__ (line 36) | def __init__(self, in_features, hidden_features=None, out_features=Non...
method forward (line 45) | def forward(self, x):
class Attention (line 55) | class Attention(nn.Module):
method __init__ (line 56) | def __init__(
method forward (line 79) | def forward(self, x):
class Block (line 101) | class Block(nn.Module):
method __init__ (line 102) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
method forward (line 122) | def forward(self, x):
class PatchEmbed (line 132) | class PatchEmbed(nn.Module):
method __init__ (line 135) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
method forward (line 148) | def forward(self, x, **kwargs):
function get_sinusoid_encoding_table (line 158) | def get_sinusoid_encoding_table(n_position, d_hid, cur_frame=-1, pre_n_p...
class VisionTransformer (line 205) | class VisionTransformer(nn.Module):
method __init__ (line 208) | def __init__(self,
method _init_weights (line 280) | def _init_weights(self, m):
method get_num_layers (line 289) | def get_num_layers(self):
method no_weight_decay (line 293) | def no_weight_decay(self):
method get_classifier (line 296) | def get_classifier(self):
method reset_classifier (line 299) | def reset_classifier(self, num_classes, global_pool=''):
method forward_features (line 303) | def forward_features(self, x):
method forward (line 323) | def forward(self, x):
function vit_large_patch16_224 (line 348) | def vit_large_patch16_224(pretrained=False, **kwargs):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/models/modeling_pretrain.py
function trunc_normal_ (line 13) | def trunc_normal_(tensor, mean=0., std=1.):
class PretrainVisionTransformerEncoder (line 17) | class PretrainVisionTransformerEncoder(nn.Module):
method __init__ (line 20) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
method _init_weights (line 57) | def _init_weights(self, m):
method get_num_layers (line 66) | def get_num_layers(self):
method no_weight_decay (line 70) | def no_weight_decay(self):
method get_classifier (line 73) | def get_classifier(self):
method reset_classifier (line 76) | def reset_classifier(self, num_classes, global_pool=''):
method forward_features (line 80) | def forward_features(self, x, mask):
method forward (line 99) | def forward(self, x, mask):
class PretrainVisionTransformerDecoder (line 105) | class PretrainVisionTransformerDecoder(nn.Module):
method __init__ (line 108) | def __init__(self, patch_size=16, num_classes=768, embed_dim=768, dept...
method _init_weights (line 131) | def _init_weights(self, m):
method get_num_layers (line 140) | def get_num_layers(self):
method no_weight_decay (line 144) | def no_weight_decay(self):
method get_classifier (line 147) | def get_classifier(self):
method reset_classifier (line 150) | def reset_classifier(self, num_classes, global_pool=''):
method forward (line 154) | def forward(self, x, return_token_num):
class PretrainVisionTransformer (line 170) | class PretrainVisionTransformer(nn.Module):
method __init__ (line 173) | def __init__(self,
method _init_weights (line 248) | def _init_weights(self, m):
method get_num_layers (line 257) | def get_num_layers(self):
method no_weight_decay (line 261) | def no_weight_decay(self):
method forward (line 264) | def forward(self, x, mask):
function pretrain_videomae_base_patch16_224 (line 281) | def pretrain_videomae_base_patch16_224(pretrained=False, **kwargs):
function pretrain_videomae_large_patch16_224 (line 306) | def pretrain_videomae_large_patch16_224(pretrained=False, **kwargs):
function pretrain_videomae_huge_patch16_224 (line 331) | def pretrain_videomae_huge_patch16_224(pretrained=False, **kwargs):
FILE: Open-Sora/build/lib/vbench/third_pary/umt/models/modeling_pretrain_umt.py
function trunc_normal_ (line 14) | def trunc_normal_(tensor, mean=0., std=1.):
function get_sinusoid_encoding_table (line 20) | def get_sinusoid_encoding_table(n_position, d_hid):
class PretrainVisionTransformerEncoder (line 33) | class PretrainVisionTransformerEncoder(nn.Module):
method __init__ (line 36) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
method _init_weights (line 81) | def _init_weights(self, m):
method get_num_layers (line 90) | def get_num_layers(self):
method no_weight_decay (line 94) | def no_weight_decay(self):
method get_classifier (line 97) | def get_classifier(self):
method reset_classifier (line 100) | def reset_classifier(self, num_classes, global_pool=''):
method forward_features (line 104) | def forward_features(self, x, mask):
method forward (line 128) | def forward(self, x, mask):
class Linear_Decoder (line 135) | class Linear_Decoder(nn.Module):
method __init__ (line 136) | def __init__(self, num_classes=768, embed_dim=768,
method _init_weights (line 147) | def _init_weights(self, m):
method forward (line 156) | def forward(self, x):
class PretrainVisionTransformer (line 169) | class PretrainVisionTransformer(nn.Module):
method __init__ (line 172) | def __init__(self,
method _init_weights (line 239) | def _init_weights(self, m):
method get_num_layers (line 248) | def get_num_layers(self):
method no_weight_decay (line 252) | def no_weight_decay(self):
method forward (line 255) | def forward(self, x, mask):
function pretrain_umt_base_patch16_224 (line 273) | def pretrain_umt_base_patch16_224(pretrained=False, **kwargs):
function pretrain_umt_large_patch16_224 (line 295) | def pretrain_umt_large_patch16_224(pretrained=False, **kwargs):
FILE: Open-Sora/build/lib/vbench/utils.py
function clip_transform (line 28) | def clip_transform(n_px):
function clip_transform_Image (line 36) | def clip_transform_Image(n_px):
function dino_transform (line 44) | def dino_transform(n_px):
function dino_transform_Image (line 51) | def dino_transform_Image(n_px):
function tag2text_transform (line 58) | def tag2text_transform(n_px):
function get_frame_indices (line 63) | def get_frame_indices(num_frames, vlen, sample='rand', fix_start=None, i...
function load_video (line 103) | def load_video(video_path, data_transform=None, num_frames=None, return_...
function read_frames_decord_by_fps (line 170) | def read_frames_decord_by_fps(
function load_dimension_info (line 193) | def load_dimension_info(json_dir, dimension, lang):
function init_submodules (line 227) | def init_submodules(dimension_list, local=False, read_frame=False):
function get_prompt_from_filename (line 360) | def get_prompt_from_filename(path: str):
function save_json (line 371) | def save_json(data, path, indent=4):
function load_json (line 375) | def load_json(path):
FILE: Open-Sora/build/lib/vbench2_beta_i2v/__init__.py
class VBenchI2V (line 8) | class VBenchI2V(VBench):
method build_full_dimension_list (line 9) | def build_full_dimension_list(self, ):
method evaluate (line 12) | def evaluate(self, videos_path, name, dimension_list=None, local=False...
FILE: Open-Sora/build/lib/vbench2_beta_i2v/camera_motion.py
function transform (line 10) | def transform(vector):
function transform_class (line 16) | def transform_class(vector, min_reso, factor=0.005): # 768*0.05
class CameraPredict (line 35) | class CameraPredict:
method __init__ (line 36) | def __init__(self, device, submodules_list):
method infer (line 47) | def infer(self, video_path, save_video=False, save_dir="./saved_videos"):
method get_edge_point (line 64) | def get_edge_point(self, track):
method get_edge_direction (line 74) | def get_edge_direction(self, track1, track2):
method classify_top_down (line 88) | def classify_top_down(self, top, down):
method classify_left_right (line 105) | def classify_left_right(self, left, right):
method camera_classify (line 122) | def camera_classify(self, track1, track2):
method predict (line 137) | def predict(self, video_path):
function get_type (line 146) | def get_type(video_name):
function camera_motion (line 165) | def camera_motion(camera, video_list):
function compute_camera_motion (line 194) | def compute_camera_motion(json_dir, device, submodules_list):
FILE: Open-Sora/build/lib/vbench2_beta_i2v/crop_to_diff_ratio.py
function save_json (line 15) | def save_json(data, save_file):
function crop (line 19) | def crop(img_path, bbox, save_root):
function get_other_ratio_crop (line 27) | def get_other_ratio_crop(second_crop_info, ratio="8-5"):
function transfer_bbox_to_origin_img (line 56) | def transfer_bbox_to_origin_img(first_crop_info, old_bbox):
function get_target_crop (line 63) | def get_target_crop(args):
FILE: Open-Sora/build/lib/vbench2_beta_i2v/i2v_background.py
function i2v_background (line 19) | def i2v_background(model, video_pair_list, device):
function compute_i2v_background (line 67) | def compute_i2v_background(json_dir, device, submodules_list):
FILE: Open-Sora/build/lib/vbench2_beta_i2v/i2v_subject.py
function i2v_subject (line 19) | def i2v_subject(model, video_pair_list, device):
function compute_i2v_subject (line 67) | def compute_i2v_subject(json_dir, device, submodules_list):
FILE: Open-Sora/build/lib/vbench2_beta_i2v/utils.py
function clip_transform (line 26) | def clip_transform(n_px):
function clip_transform_Image (line 34) | def clip_transform_Image(n_px):
function dino_transform (line 42) | def dino_transform(n_px):
function dino_transform_Image (line 49) | def dino_transform_Image(n_px):
function tag2text_transform (line 56) | def tag2text_transform(n_px):
function get_frame_indices (line 61) | def get_frame_indices(num_frames, vlen, sample='rand', fix_start=None, i...
function load_video (line 101) | def load_video(video_path, data_transform=None, num_frames=None, return_...
function read_frames_decord_by_fps (line 168) | def read_frames_decord_by_fps(
function load_dimension_info (line 191) | def load_dimension_info(json_dir, dimension, lang):
function load_i2v_dimension_info (line 226) | def load_i2v_dimension_info(json_dir, dimension, lang, resolution):
function init_submodules (line 267) | def init_submodules(dimension_list, local=False, read_frame=False, resol...
function save_json (line 309) | def save_json(data, path, indent=4):
function load_json (line 313) | def load_json(path):
FILE: Open-Sora/eval/loss/eval_loss.py
function main (line 18) | def main():
FILE: Open-Sora/eval/loss/tabulate_rl_loss.py
function parse_args (line 15) | def parse_args():
FILE: Open-Sora/eval/vae/cal_flolpips.py
function trans (line 16) | def trans(x):
function calculate_flolpips (line 20) | def calculate_flolpips(videos1, videos2, device):
function main (line 74) | def main():
FILE: Open-Sora/eval/vae/cal_lpips.py
function trans (line 13) | def trans(x):
function calculate_lpips (line 24) | def calculate_lpips(videos1, videos2, device):
function main (line 82) | def main():
FILE: Open-Sora/eval/vae/cal_psnr.py
function img_psnr (line 8) | def img_psnr(img1, img2):
function trans (line 20) | def trans(x):
function calculate_psnr (line 24) | def calculate_psnr(videos1, videos2):
function main (line 77) | def main():
FILE: Open-Sora/eval/vae/cal_ssim.py
function ssim (line 7) | def ssim(img1, img2):
function calculate_ssim_function (line 26) | def calculate_ssim_function(img1, img2):
function trans (line 45) | def trans(x):
function calculate_ssim (line 49) | def calculate_ssim(videos1, videos2):
function main (line 103) | def main():
FILE: Open-Sora/eval/vae/eval_common_metric.py
function tqdm (line 54) | def tqdm(x):
class VideoDataset (line 58) | class VideoDataset(Dataset):
method __init__ (line 59) | def __init__(
method __len__ (line 76) | def __len__(self):
method __getitem__ (line 79) | def __getitem__(self, index):
method _load_video (line 89) | def _load_video(self, video_path):
method _combine_without_prefix (line 116) | def _combine_without_prefix(self, folder_path, prefix="."):
function _preprocess (line 128) | def _preprocess(video_data, short_size=128, crop_size=None):
function calculate_common_metric (line 141) | def calculate_common_metric(args, dataloader, device):
function main (line 170) | def main():
FILE: Open-Sora/eval/vae/flolpips/correlation/correlation.py
function cupy_kernel (line 236) | def cupy_kernel(strFunction, objVariables):
function cupy_launch (line 285) | def cupy_launch(strFunction, strKernel):
class _FunctionCorrelation (line 292) | class _FunctionCorrelation(torch.autograd.Function):
method forward (line 294) | def forward(self, first, second):
method backward (line 349) | def backward(self, gradOutput):
function FunctionCorrelation (line 442) | def FunctionCorrelation(tenFirst, tenSecond):
class ModuleCorrelation (line 449) | class ModuleCorrelation(torch.nn.Module):
method __init__ (line 450) | def __init__(self):
method forward (line 455) | def forward(self, tenFirst, tenSecond):
FILE: Open-Sora/eval/vae/flolpips/flolpips.py
function spatial_average (line 25) | def spatial_average(in_tens, keepdim=True):
function mw_spatial_average (line 29) | def mw_spatial_average(in_tens, flow, keepdim=True):
function mtw_spatial_average (line 37) | def mtw_spatial_average(in_tens, flow, texture, keepdim=True):
function m2w_spatial_average (line 49) | def m2w_spatial_average(in_tens, flow, keepdim=True):
function upsample (line 57) | def upsample(in_tens, out_HW=(64, 64)): # assumes scale factor is same ...
function md5_hash (line 62) | def md5_hash(path):
function download (line 68) | def download(url, local_path, chunk_size=1024):
function get_ckpt_path (line 80) | def get_ckpt_path(name, root, check=False):
class LPIPS (line 92) | class LPIPS(nn.Module):
method __init__ (line 93) | def __init__(
method load_from_pretrained (line 159) | def load_from_pretrained(self, version, net):
method forward (line 163) | def forward(self, in0, in1, retPerLayer=False, normalize=False):
class ScalingLayer (line 211) | class ScalingLayer(nn.Module):
method __init__ (line 212) | def __init__(self):
method forward (line 217) | def forward(self, inp):
class NetLinLayer (line 221) | class NetLinLayer(nn.Module):
method __init__ (line 224) | def __init__(self, chn_in, chn_out=1, use_dropout=False):
method forward (line 239) | def forward(self, x):
class Dist2LogitLayer (line 243) | class Dist2LogitLayer(nn.Module):
method __init__ (line 246) | def __init__(self, chn_mid=32, use_sigmoid=True):
method forward (line 270) | def forward(self, d0, d1, eps=0.1):
class BCERankingLoss (line 274) | class BCERankingLoss(nn.Module):
method __init__ (line 275) | def __init__(self, chn_mid=32):
method forward (line 281) | def forward(self, d0, d1, judge):
class FakeNet (line 288) | class FakeNet(nn.Module):
method __init__ (line 289) | def __init__(self, use_gpu=True, colorspace="Lab"):
class L2 (line 295) | class L2(FakeNet):
method forward (line 296) | def forward(self, in0, in1, retPerLayer=None):
class DSSIM (line 317) | class DSSIM(FakeNet):
method forward (line 318) | def forward(self, in0, in1, retPerLayer=None):
function print_network (line 335) | def print_network(net):
class FloLPIPS (line 343) | class FloLPIPS(LPIPS):
method __init__ (line 344) | def __init__(
method forward (line 362) | def forward(self, in0, in1, flow, retPerLayer=False, normalize=False):
class Flolpips (line 382) | class Flolpips(nn.Module):
method __init__ (line 383) | def __init__(self):
method forward (line 389) | def forward(self, I0, I1, frame_dis, frame_ref):
FILE: Open-Sora/eval/vae/flolpips/pretrained_networks.py
class squeezenet (line 7) | class squeezenet(torch.nn.Module):
method __init__ (line 8) | def __init__(self, requires_grad=False, pretrained=True):
method forward (line 37) | def forward(self, X):
class alexnet (line 58) | class alexnet(torch.nn.Module):
method __init__ (line 59) | def __init__(self, requires_grad=False, pretrained=True):
method forward (line 82) | def forward(self, X):
class vgg16 (line 99) | class vgg16(torch.nn.Module):
method __init__ (line 100) | def __init__(self, requires_grad=False, pretrained=True):
method forward (line 123) | def forward(self, X):
class resnet (line 140) | class resnet(torch.nn.Module):
method __init__ (line 141) | def __init__(self, requires_grad=False, pretrained=True, num=18):
method forward (line 164) | def forward(self, X):
FILE: Open-Sora/eval/vae/flolpips/pwcnet.py
function backwarp (line 39) | def backwarp(tenInput, tenFlow):
class Network (line 92) | class Network(torch.nn.Module):
method __init__ (line 93) | def __init__(self):
method forward (line 361) | def forward(self, tenFirst, tenSecond):
function estimate (line 403) | def estimate(tenFirst, tenSecond):
FILE: Open-Sora/eval/vae/flolpips/utils.py
function normalize_tensor (line 6) | def normalize_tensor(in_feat, eps=1e-10):
function l2 (line 11) | def l2(p0, p1, range=255.0):
function dssim (line 15) | def dssim(p0, p1, range=255.0):
function tensor2im (line 21) | def tensor2im(image_tensor, imtype=np.uint8, cent=1.0, factor=255.0 / 2.0):
function tensor2np (line 27) | def tensor2np(tensor_obj):
function np2tensor (line 32) | def np2tensor(np_obj):
function tensor2tensorlab (line 37) | def tensor2tensorlab(image_tensor, to_norm=True, mc_only=False):
function read_frame_yuv2rgb (line 52) | def read_frame_yuv2rgb(stream, width, height, iFrame, bit_depth, pix_fmt...
FILE: Open-Sora/eval/vbench/calc_vbench.py
function parse_args (line 37) | def parse_args():
FILE: Open-Sora/eval/vbench/tabulate_vbench_scores.py
function parse_args (line 91) | def parse_args():
FILE: Open-Sora/eval/vbench_i2v/calc_vbench_i2v.py
function str2bool (line 22) | def str2bool(v):
function parse_args (line 33) | def parse_args():
FILE: Open-Sora/gradio/app.py
function install_dependencies (line 33) | def install_dependencies(enable_optimization=False):
function read_config (line 76) | def read_config(config_path):
function build_models (line 85) | def build_models(model_type, config, enable_optimization=False):
function parse_args (line 125) | def parse_args():
function run_inference (line 200) | def run_inference(
function run_image_inference (line 396) | def run_image_inference(
function run_video_inference (line 436) | def run_video_inference(
function generate_random_prompt (line 479) | def generate_random_prompt():
function main (line 488) | def main():
FILE: Open-Sora/opensora/acceleration/checkpoint.py
function set_grad_checkpoint (line 7) | def set_grad_checkpoint(model, use_fp32_attention=False, gc_step=1):
function auto_grad_checkpoint (line 18) | def auto_grad_checkpoint(module, *args, **kwargs):
FILE: Open-Sora/opensora/acceleration/communications.py
function _all_to_all (line 8) | def _all_to_all(
class _AllToAll (line 21) | class _AllToAll(torch.autograd.Function):
method forward (line 32) | def forward(ctx, input_, process_group, scatter_dim, gather_dim):
method backward (line 41) | def backward(ctx, grad_output):
function all_to_all (line 57) | def all_to_all(
function _gather (line 66) | def _gather(
function _split (line 83) | def _split(input_, pg: dist.ProcessGroup, dim=-1):
function _gather (line 103) | def _gather(input_, pg: dist.ProcessGroup, dim=-1):
class _GatherForwardSplitBackward (line 123) | class _GatherForwardSplitBackward(torch.autograd.Function):
method symbolic (line 133) | def symbolic(graph, input_):
method forward (line 137) | def forward(ctx, input_, process_group, dim, grad_scale):
method backward (line 144) | def backward(ctx, grad_output):
class _SplitForwardGatherBackward (line 153) | class _SplitForwardGatherBackward(torch.autograd.Function):
method symbolic (line 164) | def symbolic(graph, input_):
method forward (line 168) | def forward(ctx, input_, process_group, dim, grad_scale):
method backward (line 175) | def backward(ctx, grad_output):
function split_forward_gather_backward (line 183) | def split_forward_gather_backward(input_, process_group, dim, grad_scale...
function gather_forward_split_backward (line 187) | def gather_forward_split_backward(input_, process_group, dim, grad_scale...
FILE: Open-Sora/opensora/acceleration/parallel_states.py
function set_data_parallel_group (line 6) | def set_data_parallel_group(group: dist.ProcessGroup):
function get_data_parallel_group (line 10) | def get_data_parallel_group():
function set_sequence_parallel_group (line 14) | def set_sequence_parallel_group(group: dist.ProcessGroup):
function get_sequence_parallel_group (line 18) | def get_sequence_parallel_group():
FILE: Open-Sora/opensora/acceleration/plugin.py
class ZeroSeqParallelPlugin (line 14) | class ZeroSeqParallelPlugin(LowLevelZeroPlugin):
method __init__ (line 15) | def __init__(
method __del__ (line 64) | def __del__(self):
method prepare_dataloader (line 68) | def prepare_dataloader(
FILE: Open-Sora/opensora/acceleration/shardformer/modeling/t5.py
class T5LayerNorm (line 5) | class T5LayerNorm(nn.Module):
method __init__ (line 6) | def __init__(self, hidden_size, eps=1e-6):
method forward (line 14) | def forward(self, hidden_states):
method from_native_module (line 30) | def from_native_module(module, *args, **kwargs):
FILE: Open-Sora/opensora/acceleration/shardformer/policy/t5_encoder.py
class T5EncoderPolicy (line 6) | class T5EncoderPolicy(Policy):
method config_sanity_check (line 7) | def config_sanity_check(self):
method preprocess (line 11) | def preprocess(self):
method module_policy (line 14) | def module_policy(self):
method postprocess (line 66) | def postprocess(self):
FILE: Open-Sora/opensora/datasets/aspect.py
function get_h_w (line 5) | def get_h_w(a, ts, eps=1e-4):
function get_aspect_ratios_dict (line 15) | def get_aspect_ratios_dict(ars, ts=360 * 640):
function get_ar (line 20) | def get_ar(ratio):
function get_closest_ratio (line 440) | def get_closest_ratio(height: float, width: float, ratios: dict):
function get_num_pixels (line 463) | def get_num_pixels(name):
function get_image_size (line 467) | def get_image_size(resolution, ar_ratio):
function get_num_frames (line 491) | def get_num_frames(num_frames):
FILE: Open-Sora/opensora/datasets/bucket.py
function find_approximate_hw (line 10) | def find_approximate_hw(hw, hw_dict, approx=0.8):
function find_closet_smaller_bucket (line 17) | def find_closet_smaller_bucket(t, t_dict, frame_interval):
class Bucket (line 31) | class Bucket:
method __init__ (line 32) | def __init__(self, bucket_config):
method get_bucket_id (line 74) | def get_bucket_id(self, T, H, W, frame_interval=1, seed=None):
method get_thw (line 122) | def get_thw(self, bucket_id):
method get_prob (line 128) | def get_prob(self, bucket_id):
method get_batch_size (line 131) | def get_batch_size(self, bucket_id):
method __len__ (line 134) | def __len__(self):
function closet_smaller_bucket (line 138) | def closet_smaller_bucket(value, bucket):
FILE: Open-Sora/opensora/datasets/dataloader.py
function get_seed_worker (line 16) | def get_seed_worker(seed):
function prepare_dataloader (line 26) | def prepare_dataloader(
function collate_fn_default (line 113) | def collate_fn_default(batch):
function collate_fn_batch (line 134) | def collate_fn_batch(batch):
FILE: Open-Sora/opensora/datasets/datasets.py
class VideoTextDataset (line 19) | class VideoTextDataset(torch.utils.data.Dataset):
method __init__ (line 28) | def __init__(
method _print_data_number (line 47) | def _print_data_number(self):
method get_type (line 57) | def get_type(self, path):
method getitem (line 65) | def getitem(self, index):
method __getitem__ (line 101) | def __getitem__(self, index):
method __len__ (line 111) | def __len__(self):
class VariableVideoTextDataset (line 116) | class VariableVideoTextDataset(VideoTextDataset):
method __init__ (line 117) | def __init__(
method get_data_info (line 131) | def get_data_info(self, index):
method getitem (line 137) | def getitem(self, index):
method __getitem__ (line 192) | def __getitem__(self, index):
class BatchFeatureDataset (line 200) | class BatchFeatureDataset(torch.utils.data.Dataset):
method __init__ (line 209) | def __init__(self, data_path=None):
method num_buffers (line 220) | def num_buffers(self):
method len_buffer (line 224) | def len_buffer(self):
method _load_buffer (line 227) | def _load_buffer(self, idx):
method __len__ (line 233) | def __len__(self):
method __getitem__ (line 236) | def __getitem__(self, idx):
FILE: Open-Sora/opensora/datasets/read_video.py
function read_video_av (line 19) | def read_video_av(
function _read_from_stream (line 119) | def _read_from_stream(
function read_video_cv2 (line 213) | def read_video_cv2(video_path):
function read_video (line 250) | def read_video(video_path, backend="av"):
FILE: Open-Sora/opensora/datasets/sampler.py
function apply (line 19) | def apply(data, method=None, frame_interval=None, seed=None, num_bucket=...
class StatefulDistributedSampler (line 29) | class StatefulDistributedSampler(DistributedSampler):
method __init__ (line 30) | def __init__(
method __iter__ (line 42) | def __iter__(self) -> Iterator:
method __len__ (line 48) | def __len__(self) -> int:
method reset (line 51) | def reset(self) -> None:
method state_dict (line 54) | def state_dict(self, step) -> dict:
method load_state_dict (line 57) | def load_state_dict(self, state_dict: dict) -> None:
class VariableVideoBatchSampler (line 61) | class VariableVideoBatchSampler(DistributedSampler):
method __init__ (line 62) | def __init__(
method __iter__ (line 86) | def __iter__(self) -> Iterator[List[int]]:
method __len__ (line 190) | def __len__(self) -> int:
method group_by_bucket (line 193) | def group_by_bucket(self) -> dict:
method get_num_batch (line 220) | def get_num_batch(self) -> int:
method _print_bucket_info (line 229) | def _print_bucket_info(self, bucket_sample_dict: dict) -> None:
method reset (line 275) | def reset(self):
method state_dict (line 278) | def state_dict(self, num_steps: int) -> dict:
method load_state_dict (line 285) | def load_state_dict(self, state_dict: dict) -> None:
class BatchDistributedSampler (line 289) | class BatchDistributedSampler(DistributedSampler):
method __init__ (line 300) | def __init__(self, dataset: Dataset, **kwargs):
method __iter__ (line 304) | def __iter__(self):
method reset (line 315) | def reset(self):
method state_dict (line 318) | def state_dict(self, step) -> dict:
method load_state_dict (line 321) | def load_state_dict(self, state_dict: dict):
FILE: Open-Sora/opensora/datasets/utils.py
function is_img (line 30) | def is_img(path):
function is_vid (line 35) | def is_vid(path):
function is_url (line 40) | def is_url(url):
function read_file (line 44) | def read_file(input_path):
function download_url (line 53) | def download_url(input_path):
function temporal_random_crop (line 65) | def temporal_random_crop(vframes, num_frames, frame_interval):
function get_transforms_video (line 77) | def get_transforms_video(name="center", image_size=(256, 256)):
function get_transforms_image (line 103) | def get_transforms_image(name="center", image_size=(256, 256)):
function read_image_from_path (line 129) | def read_image_from_path(path, transform=None, transform_name="center", ...
function read_video_from_path (line 139) | def read_video_from_path(path, transform=None, transform_name="center", ...
function read_from_path (line 148) | def read_from_path(path, image_size, transform_name="center"):
function save_sample (line 159) | def save_sample(x, save_path=None, fps=8, normalize=True, value_range=(-...
function center_crop_arr (line 184) | def center_crop_arr(pil_image, image_size):
function resize_crop_to_fill (line 201) | def resize_crop_to_fill(pil_image, image_size):
FILE: Open-Sora/opensora/datasets/video_transforms.py
function _is_tensor_video_clip (line 25) | def _is_tensor_video_clip(clip):
function crop (line 35) | def crop(clip, i, j, h, w):
function resize (line 45) | def resize(clip, target_size, interpolation_mode):
function resize_scale (line 51) | def resize_scale(clip, target_size, interpolation_mode):
function resized_crop (line 59) | def resized_crop(clip, i, j, h, w, size, interpolation_mode="bilinear"):
function center_crop (line 79) | def center_crop(clip, crop_size):
function center_crop_using_short_edge (line 92) | def center_crop_using_short_edge(clip):
function resize_crop_to_fill (line 107) | def resize_crop_to_fill(clip, target_size):
function random_shift_crop (line 127) | def random_shift_crop(clip):
function to_tensor (line 147) | def to_tensor(clip):
function normalize (line 163) | def normalize(clip, mean, std, inplace=False):
function hflip (line 183) | def hflip(clip):
class ResizeCrop (line 195) | class ResizeCrop:
method __init__ (line 196) | def __init__(self, size):
method __call__ (line 202) | def __call__(self, clip):
method __repr__ (line 206) | def __repr__(self) -> str:
class RandomCropVideo (line 210) | class RandomCropVideo:
method __init__ (line 211) | def __init__(self, size):
method __call__ (line 217) | def __call__(self, clip):
method get_params (line 228) | def get_params(self, clip):
method __repr__ (line 243) | def __repr__(self) -> str:
class CenterCropResizeVideo (line 247) | class CenterCropResizeVideo:
method __init__ (line 253) | def __init__(
method __call__ (line 267) | def __call__(self, clip):
method __repr__ (line 281) | def __repr__(self) -> str:
class UCFCenterCropVideo (line 285) | class UCFCenterCropVideo:
method __init__ (line 291) | def __init__(
method __call__ (line 305) | def __call__(self, clip):
method __repr__ (line 317) | def __repr__(self) -> str:
class KineticsRandomCropResizeVideo (line 321) | class KineticsRandomCropResizeVideo:
method __init__ (line 326) | def __init__(
method __call__ (line 340) | def __call__(self, clip):
class CenterCropVideo (line 346) | class CenterCropVideo:
method __init__ (line 347) | def __init__(
method __call__ (line 361) | def __call__(self, clip):
method __repr__ (line 372) | def __repr__(self) -> str:
class NormalizeVideo (line 376) | class NormalizeVideo:
method __init__ (line 385) | def __init__(self, mean, std, inplace=False):
method __call__ (line 390) | def __call__(self, clip):
method __repr__ (line 397) | def __repr__(self) -> str:
class ToTensorVideo (line 401) | class ToTensorVideo:
method __init__ (line 407) | def __init__(self):
method __call__ (line 410) | def __call__(self, clip):
method __repr__ (line 419) | def __repr__(self) -> str:
class RandomHorizontalFlipVideo (line 423) | class RandomHorizontalFlipVideo:
method __init__ (line 430) | def __init__(self, p=0.5):
method __call__ (line 433) | def __call__(self, clip):
method __repr__ (line 444) | def __repr__(self) -> str:
class TemporalRandomCrop (line 451) | class TemporalRandomCrop(object):
method __init__ (line 458) | def __init__(self, size):
method __call__ (line 461) | def __call__(self, total_frames):
FILE: Open-Sora/opensora/models/cache_functions/attention.py
function cached_attention_forward (line 8) | def cached_attention_forward(
FILE: Open-Sora/opensora/models/cache_functions/cache_cutfresh.py
function cache_cutfresh (line 5) | def cache_cutfresh(cache_dic, tokens, current):
function local_selection_with_space_time_bonus (line 51) | def local_selection_with_space_time_bonus(cache_dic, score, bonus_ratio,...
FILE: Open-Sora/opensora/models/cache_functions/cache_init.py
function cache_init (line 1) | def cache_init(model_kwargs, num_steps):
FILE: Open-Sora/opensora/models/cache_functions/force_init.py
function force_init (line 3) | def force_init(cache_dic, current, tokens):
FILE: Open-Sora/opensora/models/cache_functions/force_scheduler.py
function force_scheduler (line 2) | def force_scheduler(cache_dic, current):
FILE: Open-Sora/opensora/models/cache_functions/fresh_ratio_scheduler.py
function fresh_ratio_scheduler (line 2) | def fresh_ratio_scheduler(cache_dic, current):
FILE: Open-Sora/opensora/models/cache_functions/global_force_fresh.py
function global_force_fresh (line 2) | def global_force_fresh(cache_dic, current):
FILE: Open-Sora/opensora/models/cache_functions/score_evaluate.py
function score_evaluate (line 4) | def score_evaluate(cache_dic, tokens, current) -> torch.Tensor:
FILE: Open-Sora/opensora/models/cache_functions/scores.py
function attn_score (line 5) | def attn_score(cache_dic, current):
function similarity_score (line 24) | def similarity_score(cache_dic, current, tokens):
function norm_score (line 29) | def norm_score(cache_dic, current, tokens):
FILE: Open-Sora/opensora/models/cache_functions/token_merge.py
function token_merge (line 2) | def token_merge(cache_dic, tokens, current, fresh_indices, stale_indices):
FILE: Open-Sora/opensora/models/cache_functions/update_cache.py
function update_cache (line 2) | def update_cache(fresh_indices, fresh_tokens, cache_dic, current, fresh_...
FILE: Open-Sora/opensora/models/dit/dit.py
class DiTBlock (line 37) | class DiTBlock(nn.Module):
method __init__ (line 42) | def __init__(
method forward (line 67) | def forward(self, x, c):
class DiT (line 75) | class DiT(nn.Module):
method __init__ (line 80) | def __init__(
method get_spatial_pos_embed (line 158) | def get_spatial_pos_embed(self):
method get_temporal_pos_embed (line 166) | def get_temporal_pos_embed(self):
method unpatchify (line 174) | def unpatchify(self, x):
method forward (line 184) | def forward(self, x, t, y):
method initialize_weights (line 226) | def initialize_weights(self):
function DiT_XL_2 (line 264) | def DiT_XL_2(from_pretrained=None, **kwargs):
function DiT_XL_2x2 (line 278) | def DiT_XL_2x2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/latte/latte.py
class Latte (line 33) | class Latte(DiT):
method forward (line 34) | def forward(self, x, t, y):
function Latte_XL_2 (line 88) | def Latte_XL_2(from_pretrained=None, **kwargs):
function Latte_XL_2x2 (line 102) | def Latte_XL_2x2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/layers/blocks.py
class LlamaRMSNorm (line 34) | class LlamaRMSNorm(nn.Module):
method __init__ (line 35) | def __init__(self, hidden_size, eps=1e-6):
method forward (line 43) | def forward(self, hidden_states):
function get_layernorm (line 51) | def get_layernorm(hidden_size: torch.Tensor, eps: float, affine: bool, u...
function modulate (line 63) | def modulate(norm_func, x, shift, scale):
function t2i_modulate (line 72) | def t2i_modulate(x, shift, scale):
class PatchEmbed3D (line 81) | class PatchEmbed3D(nn.Module):
method __init__ (line 91) | def __init__(
method forward (line 112) | def forward(self, x):
class Attention (line 134) | class Attention(nn.Module):
method __init__ (line 135) | def __init__(
method forward (line 171) | def forward(self, x: torch.Tensor) -> torch.Tensor:
class KVCompressAttention (line 232) | class KVCompressAttention(nn.Module):
method __init__ (line 233) | def __init__(
method downsample_2d (line 276) | def downsample_2d(self, tensor, H, W, scale_factor, sampling=None):
method forward (line 300) | def forward(self, x: torch.Tensor, mask=None, HW=None, block_id=None, ...
class SeqParallelAttention (line 362) | class SeqParallelAttention(Attention):
method __init__ (line 363) | def __init__(
method forward (line 387) | def forward(self, x: torch.Tensor) -> torch.Tensor:
class MultiHeadCrossAttention (line 455) | class MultiHeadCrossAttention(nn.Module):
method __init__ (line 456) | def __init__(self, d_model, num_heads, attn_drop=0.0, proj_drop=0.0):
method forward (line 470) | def forward(self, x, cond, mask=None):
class SeqParallelMultiHeadCrossAttention (line 496) | class SeqParallelMultiHeadCrossAttention(MultiHeadCrossAttention):
method __init__ (line 497) | def __init__(
method forward (line 511) | def forward(self, x, cond, mask=None):
class FinalLayer (line 549) | class FinalLayer(nn.Module):
method __init__ (line 554) | def __init__(self, hidden_size, num_patch, out_channels):
method forward (line 560) | def forward(self, x, c):
class T2IFinalLayer (line 567) | class T2IFinalLayer(nn.Module):
method __init__ (line 572) | def __init__(self, hidden_size, num_patch, out_channels, d_t=None, d_s...
method t_mask_select (line 581) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 591) | def forward(self, x, t, x_mask=None, t0=None, T=None, S=None):
class TimestepEmbedder (line 611) | class TimestepEmbedder(nn.Module):
method __init__ (line 616) | def __init__(self, hidden_size, frequency_embedding_size=256):
method timestep_embedding (line 626) | def timestep_embedding(t, dim, max_period=10000):
method forward (line 645) | def forward(self, t, dtype):
class LabelEmbedder (line 653) | class LabelEmbedder(nn.Module):
method __init__ (line 658) | def __init__(self, num_classes, hidden_size, dropout_prob):
method token_drop (line 665) | def token_drop(self, labels, force_drop_ids=None):
method forward (line 676) | def forward(self, labels, train, force_drop_ids=None):
class SizeEmbedder (line 683) | class SizeEmbedder(TimestepEmbedder):
method __init__ (line 688) | def __init__(self, hidden_size, frequency_embedding_size=256):
method forward (line 698) | def forward(self, s, bs):
method dtype (line 713) | def dtype(self):
class CaptionEmbedder (line 717) | class CaptionEmbedder(nn.Module):
method __init__ (line 722) | def __init__(
method token_drop (line 744) | def token_drop(self, caption, force_drop_ids=None):
method forward (line 755) | def forward(self, caption, train, force_drop_ids=None):
class PositionEmbedding2D (line 765) | class PositionEmbedding2D(nn.Module):
method __init__ (line 766) | def __init__(self, dim: int) -> None:
method _get_sin_cos_emb (line 774) | def _get_sin_cos_emb(self, t: torch.Tensor):
method _get_cached_emb (line 781) | def _get_cached_emb(
method forward (line 806) | def forward(
function get_2d_sincos_pos_embed (line 823) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False, extra...
function get_2d_sincos_pos_embed_from_grid (line 847) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
function get_1d_sincos_pos_embed (line 858) | def get_1d_sincos_pos_embed(embed_dim, length, scale=1.0):
function get_1d_sincos_pos_embed_from_grid (line 863) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
FILE: Open-Sora/opensora/models/pixart/pixart.py
class PixArtBlock (line 53) | class PixArtBlock(nn.Module):
method __init__ (line 58) | def __init__(
method forward (line 95) | def forward(self, x, y, t, mask=None):
class PixArt (line 109) | class PixArt(nn.Module):
method __init__ (line 114) | def __init__(
method forward (line 200) | def forward(self, x, timestep, y, mask=None, **kwargs):
method unpatchify (line 249) | def unpatchify(self, x):
method get_spatial_pos_embed (line 259) | def get_spatial_pos_embed(self, grid_size=None):
method get_temporal_pos_embed (line 271) | def get_temporal_pos_embed(self):
method freeze_text (line 280) | def freeze_text(self):
method initialize_weights (line 285) | def initialize_weights(self):
class PixArtMS (line 319) | class PixArtMS(PixArt):
method __init__ (line 320) | def __init__(self, *args, **kwargs):
method forward (line 327) | def forward(self, x, timestep, y, mask=None, data_info=None):
function PixArt_XL_2 (line 385) | def PixArt_XL_2(from_pretrained=None, **kwargs):
function PixArt_1B_2 (line 393) | def PixArt_1B_2(from_pretrained=None, **kwargs):
function PixArtMS_XL_2 (line 401) | def PixArtMS_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/stdit/stdit.py
class STDiTBlock (line 31) | class STDiTBlock(nn.Module):
method __init__ (line 32) | def __init__(
method t_mask_select (line 88) | def t_mask_select(self, x, masked_x, x_mask):
method forward (line 98) | def forward(self, x, y, t, mask=None, tpe=None, x_mask=None, t0=None):
class STDiT (line 157) | class STDiT(nn.Module):
method __init__ (line 158) | def __init__(
method forward (line 258) | def forward(self, x, timestep, y, mask=None, x_mask=None, **kwargs):
method unpatchify (line 331) | def unpatchify(self, x):
method unpatchify_old (line 355) | def unpatchify_old(self, x):
method get_spatial_pos_embed (line 365) | def get_spatial_pos_embed(self, grid_size=None):
method get_temporal_pos_embed (line 376) | def get_temporal_pos_embed(self):
method freeze_not_temporal (line 385) | def freeze_not_temporal(self):
method freeze_text (line 390) | def freeze_text(self):
method initialize_temporal (line 395) | def initialize_temporal(self):
method initialize_weights (line 400) | def initialize_weights(self):
function STDiT_XL_2 (line 434) | def STDiT_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/stdit/stdit2.py
class STDiT2Block (line 31) | class STDiT2Block(nn.Module):
method __init__ (line 32) | def __init__(
method t_mask_select (line 85) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 95) | def forward(self, x, y, t, t_tmp, mask=None, x_mask=None, t0=None, t0_...
class STDiT2Config (line 170) | class STDiT2Config(PretrainedConfig):
method __init__ (line 173) | def __init__(
class STDiT2 (line 219) | class STDiT2(PreTrainedModel):
method __init__ (line 222) | def __init__(self, config):
method get_dynamic_size (line 292) | def get_dynamic_size(self, x):
method forward (line 305) | def forward(
method unpatchify (line 413) | def unpatchify(self, x, N_t, N_h, N_w, R_t, R_h, R_w):
method unpatchify_old (line 439) | def unpatchify_old(self, x):
method get_spatial_pos_embed (line 449) | def get_spatial_pos_embed(self, H, W, scale=1.0, base_size=None):
method freeze_not_temporal (line 459) | def freeze_not_temporal(self):
method freeze_text (line 464) | def freeze_text(self):
method initialize_temporal (line 469) | def initialize_temporal(self):
method initialize_weights (line 474) | def initialize_weights(self):
function STDiT2_XL_2 (line 509) | def STDiT2_XL_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/stdit/stdit3.py
class STDiT3Block (line 37) | class STDiT3Block(nn.Module):
method __init__ (line 38) | def __init__(
method t_mask_select (line 81) | def t_mask_select(self, x_mask, x, masked_x, T, S):
method forward (line 91) | def forward(
class STDiT3Config (line 208) | class STDiT3Config(PretrainedConfig):
method __init__ (line 211) | def __init__(
class STDiT3 (line 258) | class STDiT3(PreTrainedModel):
method __init__ (line 261) | def __init__(self, config):
method initialize_weights (line 355) | def initialize_weights(self):
method get_dynamic_size (line 377) | def get_dynamic_size(self, x):
method encode_text (line 390) | def encode_text(self, y, mask=None):
method forward (line 403) | def forward(self, x, timestep, y, mask=None, x_mask=None, fps=None, he...
method unpatchify (line 491) | def unpatchify(self, x, N_t, N_h, N_w, R_t, R_h, R_w):
function STDiT3_XL_2 (line 519) | def STDiT3_XL_2(from_pretrained=None, **kwargs):
function STDiT3_3B_2 (line 532) | def STDiT3_3B_2(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/text_encoder/classes.py
class ClassEncoder (line 7) | class ClassEncoder:
method __init__ (line 8) | def __init__(self, num_classes, model_max_length=None, device="cuda", ...
method encode (line 16) | def encode(self, text):
method null (line 19) | def null(self, n):
FILE: Open-Sora/opensora/models/text_encoder/clip.py
class AbstractEncoder (line 36) | class AbstractEncoder(nn.Module):
method __init__ (line 37) | def __init__(self):
method encode (line 40) | def encode(self, *args, **kwargs):
class FrozenCLIPEmbedder (line 44) | class FrozenCLIPEmbedder(AbstractEncoder):
method __init__ (line 47) | def __init__(self, path="openai/clip-vit-huge-patch14", device="cuda",...
method _freeze (line 55) | def _freeze(self):
method forward (line 60) | def forward(self, text):
method encode (line 77) | def encode(self, text):
class ClipEncoder (line 82) | class ClipEncoder:
method __init__ (line 87) | def __init__(
method encode (line 103) | def encode(self, text):
method null (line 108) | def null(self, n):
method to (line 112) | def to(self, dtype):
FILE: Open-Sora/opensora/models/text_encoder/t5.py
class T5Embedder (line 34) | class T5Embedder:
method __init__ (line 35) | def __init__(
method get_text_embeddings (line 113) | def get_text_embeddings(self, texts):
class T5Encoder (line 135) | class T5Encoder:
method __init__ (line 136) | def __init__(
method shardformer_t5 (line 166) | def shardformer_t5(self):
method encode (line 189) | def encode(self, text):
method null (line 194) | def null(self, n):
function basic_clean (line 199) | def basic_clean(text):
function clean_caption (line 210) | def clean_caption(caption):
function text_preprocessing (line 328) | def text_preprocessing(text, use_text_preprocessing: bool = True):
FILE: Open-Sora/opensora/models/vae/discriminator.py
function cast_tuple (line 13) | def cast_tuple(t, length=1):
function xavier_uniform_weight_init (line 17) | def xavier_uniform_weight_init(m):
function n_layer_disc_weights_init (line 26) | def n_layer_disc_weights_init(m):
class BlurPool3D (line 36) | class BlurPool3D(nn.Module):
method __init__ (line 37) | def __init__(
method forward (line 90) | def forward(self, inp):
class ResBlockDown (line 100) | class ResBlockDown(nn.Module):
method __init__ (line 103) | def __init__(
method forward (line 135) | def forward(self, x):
class NLayerDiscriminator (line 153) | class NLayerDiscriminator(nn.Module):
method __init__ (line 158) | def __init__(self, input_nc=3, ndf=64, n_layers=3, use_actnorm=False, ...
method forward (line 205) | def forward(self, input):
class NLayerDiscriminator3D (line 210) | class NLayerDiscriminator3D(nn.Module):
method __init__ (line 213) | def __init__(self, input_nc=1, ndf=64, n_layers=3, use_actnorm=False):
method forward (line 269) | def forward(self, input):
class StyleGANDiscriminatorBlur (line 274) | class StyleGANDiscriminatorBlur(nn.Module):
method __init__ (line 282) | def __init__(
method forward (line 343) | def forward(self, x):
function load_checkpoint_with_inflation (line 368) | def load_checkpoint_with_inflation(model, ckpt_path):
function DISCRIMINATOR_3D (line 391) | def DISCRIMINATOR_3D(from_pretrained=None, inflate_from_2d=False, use_pr...
function DISCRIMINATOR_3D_N_Layer (line 407) | def DISCRIMINATOR_3D_N_Layer(from_pretrained=None, inflate_from_2d=False...
FILE: Open-Sora/opensora/models/vae/losses.py
function hinge_d_loss (line 9) | def hinge_d_loss(logits_real, logits_fake):
function vanilla_d_loss (line 16) | def vanilla_d_loss(logits_real, logits_fake):
function sigmoid_cross_entropy_with_logits (line 24) | def sigmoid_cross_entropy_with_logits(labels, logits):
function lecam_reg (line 33) | def lecam_reg(real_pred, fake_pred, ema_real_pred, ema_fake_pred):
function gradient_penalty_fn (line 40) | def gradient_penalty_fn(images, output):
class VAELoss (line 54) | class VAELoss(nn.Module):
method __init__ (line 55) | def __init__(
method forward (line 80) | def forward(
function adopt_weight (line 127) | def adopt_weight(weight, global_step, threshold=0, value=0.0):
class AdversarialLoss (line 133) | class AdversarialLoss(nn.Module):
method __init__ (line 134) | def __init__(
method calculate_adaptive_weight (line 147) | def calculate_adaptive_weight(self, nll_loss, g_loss, last_layer):
method forward (line 155) | def forward(
class LeCamEMA (line 190) | class LeCamEMA:
method __init__ (line 191) | def __init__(self, ema_real=0.0, ema_fake=0.0, decay=0.999, dtype=torc...
method update (line 196) | def update(self, ema_real, ema_fake):
method get (line 200) | def get(self):
class DiscriminatorLoss (line 204) | class DiscriminatorLoss(nn.Module):
method __init__ (line 205) | def __init__(
method forward (line 222) | def forward(
FILE: Open-Sora/opensora/models/vae/lpips.py
function md5_hash (line 18) | def md5_hash(path):
function download (line 24) | def download(url, local_path, chunk_size=1024):
function get_ckpt_path (line 36) | def get_ckpt_path(name, root, check=False):
class LPIPS (line 47) | class LPIPS(nn.Module):
method __init__ (line 49) | def __init__(self, use_dropout=True):
method load_from_pretrained (line 63) | def load_from_pretrained(self, name="vgg_lpips"):
method from_pretrained (line 69) | def from_pretrained(cls, name="vgg_lpips"):
method forward (line 77) | def forward(self, input, target):
class ScalingLayer (line 93) | class ScalingLayer(nn.Module):
method __init__ (line 94) | def __init__(self):
method forward (line 99) | def forward(self, inp):
class NetLinLayer (line 103) | class NetLinLayer(nn.Module):
method __init__ (line 106) | def __init__(self, chn_in, chn_out=1, use_dropout=False):
class vgg16 (line 121) | class vgg16(torch.nn.Module):
method __init__ (line 122) | def __init__(self, requires_grad=False, pretrained=True):
method forward (line 145) | def forward(self, X):
function normalize_tensor (line 161) | def normalize_tensor(x, eps=1e-10):
function spatial_average (line 166) | def spatial_average(x, keepdim=True):
FILE: Open-Sora/opensora/models/vae/utils.py
class DiagonalGaussianDistribution (line 7) | class DiagonalGaussianDistribution(object):
method __init__ (line 8) | def __init__(
method sample (line 22) | def sample(self):
method kl (line 27) | def kl(self, other=None):
method nll (line 43) | def nll(self, sample, dims=[1, 2, 3, 4]):
method mode (line 49) | def mode(self):
FILE: Open-Sora/opensora/models/vae/vae.py
class VideoAutoencoderKL (line 14) | class VideoAutoencoderKL(nn.Module):
method __init__ (line 15) | def __init__(
method encode (line 36) | def encode(self, x):
method decode (line 55) | def decode(self, x, **kwargs):
method get_latent_size (line 73) | def get_latent_size(self, input_size):
method device (line 83) | def device(self):
method dtype (line 87) | def dtype(self):
class VideoAutoencoderKLTemporalDecoder (line 92) | class VideoAutoencoderKLTemporalDecoder(nn.Module):
method __init__ (line 93) | def __init__(self, from_pretrained=None, cache_dir=None, local_files_o...
method encode (line 101) | def encode(self, x):
method decode (line 104) | def decode(self, x, **kwargs):
method get_latent_size (line 111) | def get_latent_size(self, input_size):
method device (line 121) | def device(self):
method dtype (line 125) | def dtype(self):
class VideoAutoencoderPipelineConfig (line 129) | class VideoAutoencoderPipelineConfig(PretrainedConfig):
method __init__ (line 132) | def __init__(
class VideoAutoencoderPipeline (line 155) | class VideoAutoencoderPipeline(PreTrainedModel):
method __init__ (line 158) | def __init__(self, config: VideoAutoencoderPipelineConfig):
method encode (line 182) | def encode(self, x):
method decode (line 201) | def decode(self, z, num_frames=None):
method forward (line 223) | def forward(self, x):
method get_latent_size (line 229) | def get_latent_size(self, input_size):
method get_temporal_last_layer (line 242) | def get_temporal_last_layer(self):
method device (line 246) | def device(self):
method dtype (line 250) | def dtype(self):
function OpenSoraVAE_V1_2 (line 255) | def OpenSoraVAE_V1_2(
FILE: Open-Sora/opensora/models/vae/vae_temporal.py
function cast_tuple (line 13) | def cast_tuple(t, length=1):
function divisible_by (line 17) | def divisible_by(num, den):
function is_odd (line 21) | def is_odd(n):
function pad_at_dim (line 25) | def pad_at_dim(t, pad, dim=-1):
function exists (line 31) | def exists(v):
class CausalConv3d (line 35) | class CausalConv3d(nn.Module):
method __init__ (line 36) | def __init__(
method forward (line 67) | def forward(self, x):
class ResBlock (line 73) | class ResBlock(nn.Module):
method __init__ (line 74) | def __init__(
method forward (line 100) | def forward(self, x):
function get_activation_fn (line 113) | def get_activation_fn(activation):
class Encoder (line 123) | class Encoder(nn.Module):
method __init__ (line 126) | def __init__(
method forward (line 204) | def forward(self, x):
class Decoder (line 221) | class Decoder(nn.Module):
method __init__ (line 224) | def __init__(
method forward (line 301) | def forward(self, x):
class VAE_Temporal (line 326) | class VAE_Temporal(nn.Module):
method __init__ (line 327) | def __init__(
method get_latent_size (line 371) | def get_latent_size(self, input_size):
method encode (line 388) | def encode(self, x):
method decode (line 400) | def decode(self, z, num_frames=None):
method forward (line 411) | def forward(self, x, sample_posterior=True):
function VAE_Temporal_SD (line 422) | def VAE_Temporal_SD(from_pretrained=None, **kwargs):
FILE: Open-Sora/opensora/models/vae/video_sdxl/blocks.py
function video_to_image (line 15) | def video_to_image(func):
class VideoConv2d (line 36) | class VideoConv2d(nn.Conv2d):
method __init__ (line 37) | def __init__(self, *args, micro_batch_size=None, **kwargs):
method forward (line 42) | def forward(self, x):
class ResnetBlock2D (line 46) | class ResnetBlock2D(nn.Module):
method __init__ (line 53) | def __init__(
method forward (line 89) | def forward(self, x):
class ResnetBlock3D (line 105) | class ResnetBlock3D(nn.Module):
method __init__ (line 111) | def __init__(
method forward (line 144) | def forward(self, x):
class SpatialDownsample2x (line 160) | class SpatialDownsample2x(nn.Module):
method __init__ (line 166) | def __init__(
method forward (line 185) | def forward(self, x):
class SpatialUpsample2x (line 194) | class SpatialUpsample2x(nn.Module):
method __init__ (line 200) | def __init__(
method forward (line 217) | def forward(self, x):
method forward_BCHW (
Condensed preview — 713 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (7,276K chars).
[
{
"path": "COCO_caption_prompts_30k.txt",
"chars": 1600263,
"preview": "A man about to return a serve with his tennis racket\nA horse drawn carriage in a historic city.\nTwo gray fire hydrants s"
},
{
"path": "DiT-ToCa/cache_functions/__init__.py",
"chars": 409,
"preview": "from .cache_cutfresh import cache_cutfresh\nfrom .fresh_ratio_scheduler import fresh_ratio_scheduler\nfrom .score_evaluate"
},
{
"path": "DiT-ToCa/cache_functions/attention.py",
"chars": 3056,
"preview": "# Besides, re-arrange the attention module\nfrom torch.jit import Final\nfrom timm.layers import use_fused_attn\nimport tor"
},
{
"path": "DiT-ToCa/cache_functions/cache_cutfresh.py",
"chars": 4000,
"preview": "from .fresh_ratio_scheduler import fresh_ratio_scheduler\nfrom .score_evaluate import score_evaluate\nfrom .token_merge im"
},
{
"path": "DiT-ToCa/cache_functions/cache_init.py",
"chars": 1324,
"preview": "def cache_init(model_kwargs, num_steps): \n '''\n Initialization for cache.\n '''\n cache_dic = {}\n cache ="
},
{
"path": "DiT-ToCa/cache_functions/cal_type.py",
"chars": 656,
"preview": "def cal_type(cache_dic, current):\n '''\n Determine calculation type for this step\n '''\n last_steps = (current"
},
{
"path": "DiT-ToCa/cache_functions/force_init.py",
"chars": 613,
"preview": "import torch\nfrom .force_scheduler import force_scheduler\ndef force_init(cache_dic, current, tokens):\n '''\n Initia"
},
{
"path": "DiT-ToCa/cache_functions/force_scheduler.py",
"chars": 768,
"preview": "import torch\ndef force_scheduler(cache_dic, current):\n '''\n Force Activation Cycle Scheduler\n '''\n if cache_"
},
{
"path": "DiT-ToCa/cache_functions/fresh_ratio_scheduler.py",
"chars": 4064,
"preview": "import torch\ndef fresh_ratio_scheduler(cache_dic, current):\n '''\n Return the fresh ratio for the current step.\n "
},
{
"path": "DiT-ToCa/cache_functions/global_force_fresh.py",
"chars": 923,
"preview": "from .force_scheduler import force_scheduler\ndef global_force_fresh(cache_dic, current):\n '''\n Return whether to f"
},
{
"path": "DiT-ToCa/cache_functions/score_evaluate.py",
"chars": 4654,
"preview": "import torch\nimport torch.nn as nn\nfrom .scores import attn_score, similarity_score, norm_score, kv_norm_score\ndef score"
},
{
"path": "DiT-ToCa/cache_functions/scores.py",
"chars": 1143,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\ndef attn_score(cache_dic, current):\n '''\n Atte"
},
{
"path": "DiT-ToCa/cache_functions/token_merge.py",
"chars": 1762,
"preview": "import torch\ndef token_merge(cache_dic, tokens, current, fresh_indices, stale_indices):\n '''\n An abandoned branch "
},
{
"path": "DiT-ToCa/cache_functions/update_cache.py",
"chars": 913,
"preview": "import torch\ndef update_cache(fresh_indices, fresh_tokens, cache_dic, current, fresh_attn_map=None):\n '''\n Update "
},
{
"path": "DiT-ToCa/diffusion/__init__.py",
"chars": 1668,
"preview": "# Modified from OpenAI's diffusion repos\r\n# GLIDE: https://github.com/openai/glide-text2im/blob/main/glide_text2im/g"
},
{
"path": "DiT-ToCa/diffusion/diffusion_utils.py",
"chars": 3277,
"preview": "# Modified from OpenAI's diffusion repos\r\n# GLIDE: https://github.com/openai/glide-text2im/blob/main/glide_text2im/g"
},
{
"path": "DiT-ToCa/diffusion/gaussian_diffusion.py",
"chars": 36377,
"preview": "# Modified from OpenAI's diffusion repos\r\n# GLIDE: https://github.com/openai/glide-text2im/blob/main/glide_text2im/g"
},
{
"path": "DiT-ToCa/diffusion/respace.py",
"chars": 5614,
"preview": "# Modified from OpenAI's diffusion repos\r\n# GLIDE: https://github.com/openai/glide-text2im/blob/main/glide_text2im/g"
},
{
"path": "DiT-ToCa/diffusion/timestep_sampler.py",
"chars": 6163,
"preview": "# Modified from OpenAI's diffusion repos\r\n# GLIDE: https://github.com/openai/glide-text2im/blob/main/glide_text2im/g"
},
{
"path": "DiT-ToCa/download.py",
"chars": 1782,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\r\n# All rights reserved.\r\n\r\n# This source code is licensed under the"
},
{
"path": "DiT-ToCa/environment-dit.yml",
"chars": 9888,
"preview": "name: base\nchannels:\n - pytorch\n - nvidia\n - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main\n - https://mirr"
},
{
"path": "DiT-ToCa/models.py",
"chars": 20155,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\r\n# All rights reserved.\r\n\r\n# This source code is licensed under the"
},
{
"path": "DiT-ToCa/sample.py",
"chars": 5936,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\r\n# All rights reserved.\r\n\r\n# This source code is licensed under the"
},
{
"path": "DiT-ToCa/sample_ddp.py",
"chars": 10112,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\r\n# All rights reserved.\r\n\r\n# This source code is licensed under the"
},
{
"path": "DiT-ToCa/train.py",
"chars": 11218,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\r\n# All rights reserved.\r\n\r\n# This source code is licensed under the"
},
{
"path": "DrawBench200.txt",
"chars": 13116,
"preview": "A red colored car.\nA black colored car.\nA pink colored car.\nA black colored dog.\nA red colored dog.\nA blue colored dog.\n"
},
{
"path": "LICENSE",
"chars": 35149,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
},
{
"path": "Open-Sora/Dockerfile",
"chars": 993,
"preview": "FROM hpcaitech/pytorch-cuda:2.1.0-12.1.0\n\n# metainformation\nLABEL org.opencontainers.image.source = \"https://github.com/"
},
{
"path": "Open-Sora/LICENSE",
"chars": 34843,
"preview": "Copyright 2024 HPC-AI Technology Inc. All rights reserved.\n Apache License\n "
},
{
"path": "Open-Sora/README.md",
"chars": 41015,
"preview": "<p align=\"center\">\n <img src=\"./assets/readme/icon.png\" width=\"250\"/>\n</p>\n<div align=\"center\">\n <a href=\"https://"
},
{
"path": "Open-Sora/assets/texts/VBench/all_category.txt",
"chars": 29212,
"preview": "a black dog wearing halloween costume\nspider making a web\nbat eating fruits while hanging\na snake crawling on a wooden f"
},
{
"path": "Open-Sora/assets/texts/VBench/all_dimension.txt",
"chars": 39728,
"preview": "In a still frame, a stop sign\na toilet, frozen in time\na laptop, frozen in time\nA tranquil tableau of alley\nA tranquil t"
},
{
"path": "Open-Sora/assets/texts/VBench/all_i2v.txt",
"chars": 221513,
"preview": "a close up of a blue and orange liquid{\"reference_path\": \"/mnt/jfs-hdd/sora/data/vbench-i2v/crop/1-1/a close up of a blu"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/animal.txt",
"chars": 3300,
"preview": "a black dog wearing halloween costume\nspider making a web\nbat eating fruits while hanging\na snake crawling on a wooden f"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/architecture.txt",
"chars": 3861,
"preview": "an apartment building with balcony\nasian garden and medieval castle\nilluminated tower in berlin\na wooden house overseein"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/food.txt",
"chars": 3481,
"preview": "freshly baked finger looking cookies\nvideo of fake blood in wine glass\nhalloween food art\na person slicing a vegetable\na"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/human.txt",
"chars": 3787,
"preview": "people carving a pumpkin\npeople sitting on a sofa\na man with a muertos face painting\nman walking in the dark\nmen in fron"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/lifestyle.txt",
"chars": 3914,
"preview": "kids celebrating halloween at home\nlittle boy helping mother in kitchen\nvideo of a indoor green plant\na girl arranges a "
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/plant.txt",
"chars": 3323,
"preview": "video of a indoor green plant\nclose up view of a plant\nclose up shot of a burning plant\nplucking leaves from plant\na pla"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/scenery.txt",
"chars": 3712,
"preview": "scenery of desert landscape\nlandscape agriculture farm tractor\nburning slash piles in the forest\ngraveyard at sunset\nvie"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_category/vehicles.txt",
"chars": 3834,
"preview": "a modern railway station in malaysia use for public transportation\ndrone footage of amsterdam metro station\ntrain arrivi"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/appearance_style.txt",
"chars": 6989,
"preview": "A beautiful coastal beach in spring, waves lapping on sand, Van Gogh style\nA beautiful coastal beach in spring, waves la"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/color.txt",
"chars": 1212,
"preview": "a red bicycle\na green bicycle\na blue bicycle\na yellow bicycle\nan orange bicycle\na purple bicycle\na pink bicycle\na black "
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/human_action.txt",
"chars": 2648,
"preview": "A person is riding a bike\nA person is marching\nA person is roller skating\nA person is tasting beer\nA person is clapping\n"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/multiple_objects.txt",
"chars": 1935,
"preview": "a bird and a cat\na cat and a dog\na dog and a horse\na horse and a sheep\na sheep and a cow\na cow and an elephant\nan elepha"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/object_class.txt",
"chars": 773,
"preview": "a person\na bicycle\na car\na motorcycle\nan airplane\na bus\na train\na truck\na boat\na traffic light\na fire hydrant\na stop sig"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/overall_consistency.txt",
"chars": 5068,
"preview": "Close up of grapes on a rotating table.\nTurtle swimming in ocean.\nA storm trooper vacuuming the beach.\nA panda standing "
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/scene.txt",
"chars": 876,
"preview": "alley\namusement park\naquarium\narch\nart gallery\nbathroom\nbakery shop\nballroom\nbar\nbarn\nbasement\nbeach\nbedroom\nbridge\nbota"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/spatial_relationship.txt",
"chars": 3936,
"preview": "a bicycle on the left of a car, front view\na car on the right of a motorcycle, front view\na motorcycle on the left of a "
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/subject_consistency.txt",
"chars": 2595,
"preview": "a person swimming in ocean\na person giving a presentation to a room full of colleagues\na person washing the dishes\na per"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/temporal_flickering.txt",
"chars": 6066,
"preview": "In a still frame, a stop sign\na toilet, frozen in time\na laptop, frozen in time\nA tranquil tableau of alley\nA tranquil t"
},
{
"path": "Open-Sora/assets/texts/VBench/prompts_per_dimension/temporal_style.txt",
"chars": 7630,
"preview": "A beautiful coastal beach in spring, waves lapping on sand, in super slow motion\nA beautiful coastal beach in spring, wa"
},
{
"path": "Open-Sora/assets/texts/imagenet_id.txt",
"chars": 31,
"preview": "207\n360\n387\n974\n88\n979\n417\n279\n"
},
{
"path": "Open-Sora/assets/texts/imagenet_labels.txt",
"chars": 77,
"preview": "golden retriever\notter\nlesser panda\ngeyser\nmacaw\nvalley\nballoon\ngolden panda\n"
},
{
"path": "Open-Sora/assets/texts/rand_types.txt",
"chars": 280,
"preview": "随机电影镜头\n随机电影镜头\n随机电影镜头\n随机电影镜头\n随机电影镜头\n随机任务镜头\n随机任务镜头\n随机任务镜头\n随机任务镜头\n随机任务镜头\n随机游戏镜头\n随机游戏镜头\n随机游戏镜头\n随机游戏镜头\n随机游戏镜头\n随机开车镜头\n随机开车镜头\n随"
},
{
"path": "Open-Sora/assets/texts/t2i_samples.txt",
"chars": 448,
"preview": "A small cactus with a happy face in the Sahara desert.\nBright scene, aerial view,ancient city, fantasy, gorgeous light, "
},
{
"path": "Open-Sora/assets/texts/t2i_sigma.txt",
"chars": 1784,
"preview": "Eiffel Tower was Made up of more than 2 million translucent straws to look like a cloud, with the bell tower at the top "
},
{
"path": "Open-Sora/assets/texts/t2v_car.txt",
"chars": 383,
"preview": "|0|A car driving on the in forest.|2|A car driving in the desert.|4|A car driving near the coast.|6|A car driving in the"
},
{
"path": "Open-Sora/assets/texts/t2v_latte.txt",
"chars": 361,
"preview": "Yellow and black tropical fish dart through the sea.\nAn epic tornado attacking above aglowing city at night.\nSlow pan up"
},
{
"path": "Open-Sora/assets/texts/t2v_pllava.txt",
"chars": 8485,
"preview": "a close-up shot of a woman standing in a room with a white wall and a plant on the left side. the woman has curly hair a"
},
{
"path": "Open-Sora/assets/texts/t2v_ref.txt",
"chars": 1389,
"preview": "Drone view of waves crashing against the rugged cliffs along Big Sur’s garay point beach. The crashing blue waters creat"
},
{
"path": "Open-Sora/assets/texts/t2v_samples.txt",
"chars": 6036,
"preview": "A soaring drone footage captures the majestic beauty of a coastal cliff, its red and yellow stratified rock faces rich i"
},
{
"path": "Open-Sora/assets/texts/t2v_short.txt",
"chars": 1167,
"preview": "A fat rabbit wearing a purple robe walking through a fantasy landscape\nWaves crashing against a lone lighthouse, ominous"
},
{
"path": "Open-Sora/assets/texts/t2v_sora.txt",
"chars": 11570,
"preview": "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black lea"
},
{
"path": "Open-Sora/assets/texts/ucf101_id.txt",
"chars": 12,
"preview": "0\n1\n2\n3\n4\n5\n"
},
{
"path": "Open-Sora/assets/texts/ucf101_labels.txt",
"chars": 81,
"preview": "Apply Eye Makeup\nApply Lipstick\nArchery\nBaby Crawling\nBalance Beam\nBand Marching\n"
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/checkpoint.py",
"chars": 841,
"preview": "from collections.abc import Iterable\n\nimport torch.nn as nn\nfrom torch.utils.checkpoint import checkpoint, checkpoint_se"
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/communications.py",
"chars": 5329,
"preview": "import torch\nimport torch.distributed as dist\n\n\n# ====================\n# All-To-All\n# ====================\ndef _all_to_a"
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/parallel_states.py",
"chars": 469,
"preview": "import torch.distributed as dist\n\n_GLOBAL_PARALLEL_GROUPS = dict()\n\n\ndef set_data_parallel_group(group: dist.ProcessGrou"
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/plugin.py",
"chars": 3364,
"preview": "import random\nfrom typing import Optional\n\nimport numpy as np\nimport torch\nfrom colossalai.booster.plugin import LowLeve"
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/shardformer/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/shardformer/modeling/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/shardformer/modeling/t5.py",
"chars": 1778,
"preview": "import torch\nimport torch.nn as nn\n\n\nclass T5LayerNorm(nn.Module):\n def __init__(self, hidden_size, eps=1e-6):\n "
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/shardformer/policy/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/opensora/acceleration/shardformer/policy/t5_encoder.py",
"chars": 2595,
"preview": "from colossalai.shardformer.modeling.jit import get_jit_fused_dropout_add_func\nfrom colossalai.shardformer.modeling.t5 i"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/__init__.py",
"chars": 186,
"preview": "from .datasets import IMG_FPS, BatchFeatureDataset, VariableVideoTextDataset, VideoTextDataset\nfrom .utils import get_tr"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/aspect.py",
"chars": 11354,
"preview": "import math\n\n\n# computation\ndef get_h_w(a, ts, eps=1e-4):\n h = (ts * a) ** 0.5\n h = h + eps\n h = math.ceil(h) i"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/bucket.py",
"chars": 4683,
"preview": "from collections import OrderedDict\n\nimport numpy as np\n\nfrom opensora.utils.misc import get_logger\n\nfrom .aspect import"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/dataloader.py",
"chars": 4599,
"preview": "import collections\nimport random\nfrom typing import Optional\n\nimport numpy as np\nimport torch\nfrom torch.distributed imp"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/datasets.py",
"chars": 7818,
"preview": "import os\nfrom glob import glob\n\nimport numpy as np\nimport torch\nfrom PIL import ImageFile\nfrom torchvision.datasets.fol"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/read_video.py",
"chars": 9544,
"preview": "import gc\nimport math\nimport os\nimport re\nimport warnings\nfrom fractions import Fraction\nfrom typing import Any, Dict, L"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/sampler.py",
"chars": 12704,
"preview": "from collections import OrderedDict, defaultdict\nfrom pprint import pformat\nfrom typing import Iterator, List, Optional\n"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/utils.py",
"chars": 7771,
"preview": "import os\nimport re\n\nimport numpy as np\nimport pandas as pd\nimport requests\nimport torch\nimport torchvision\nimport torch"
},
{
"path": "Open-Sora/build/lib/opensora/datasets/video_transforms.py",
"chars": 16348,
"preview": "# Copyright 2024 Vchitect/Latte\n\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use thi"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/__init__.py",
"chars": 393,
"preview": "from .cache_cutfresh import cache_cutfresh\nfrom .fresh_ratio_scheduler import fresh_ratio_scheduler\nfrom .score_evaluate"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/attention.py",
"chars": 1118,
"preview": "# Besides, re-arrange the attention module\nfrom torch.jit import Final\nimport torch\nimport torch.nn as nn\nimport torch.n"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/cache_cutfresh.py",
"chars": 5734,
"preview": "from .fresh_ratio_scheduler import fresh_ratio_scheduler\nfrom .score_evaluate import score_evaluate\n#from .token_merge i"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/cache_init.py",
"chars": 1557,
"preview": "def cache_init(model_kwargs, num_steps): \n cache_dic = {}\n cache = {}\n indices_cache = {}\n cache_index = {"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/force_init.py",
"chars": 495,
"preview": "import torch\nfrom .force_scheduler import force_scheduler\ndef force_init(cache_dic, current, tokens):\n cache_dic['cac"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/force_scheduler.py",
"chars": 1670,
"preview": "import torch\ndef force_scheduler(cache_dic, current):\n thresholds = {}\n if cache_dic['fresh_ratio'] == 0:\n "
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/fresh_ratio_scheduler.py",
"chars": 2304,
"preview": "import torch\ndef fresh_ratio_scheduler(cache_dic, current):\n '''\n Return the fresh ratio for the current step.\n "
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/global_force_fresh.py",
"chars": 1776,
"preview": "from .force_scheduler import force_scheduler\ndef global_force_fresh(cache_dic, current):\n '''\n Return whether to f"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/score_evaluate.py",
"chars": 3451,
"preview": "import torch\nimport torch.nn as nn\nfrom .scores import attn_score, similarity_score, norm_score\ndef score_evaluate(cache"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/scores.py",
"chars": 1624,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\ndef attn_score(cache_dic, current):\n #self_attn_s"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/token_merge.py",
"chars": 2916,
"preview": "import torch\ndef token_merge(cache_dic, tokens, current, fresh_indices, stale_indices):\n #fresh_tokens = torch.ze"
},
{
"path": "Open-Sora/build/lib/opensora/models/cache_functions/update_cache.py",
"chars": 1953,
"preview": "import torch\ndef update_cache(fresh_indices, fresh_tokens, cache_dic, current, fresh_attn_map=None):\n \"\"\"\n Update "
},
{
"path": "Open-Sora/build/lib/opensora/models/dit/__init__.py",
"chars": 43,
"preview": "from .dit import DiT, DiT_XL_2, DiT_XL_2x2\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/dit/dit.py",
"chars": 10317,
"preview": "# Modified from Meta DiT\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root direc"
},
{
"path": "Open-Sora/build/lib/opensora/models/latte/__init__.py",
"chars": 51,
"preview": "from .latte import Latte, Latte_XL_2, Latte_XL_2x2\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/latte/latte.py",
"chars": 3784,
"preview": "# Copyright 2024 Vchitect/Latte\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use th"
},
{
"path": "Open-Sora/build/lib/opensora/models/layers/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/opensora/models/layers/blocks.py",
"chars": 31552,
"preview": "# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/pixart/__init__.py",
"chars": 97,
"preview": "from .pixart import PixArt, PixArt_1B_2, PixArt_XL_2\nfrom .pixart_sigma import PixArt_Sigma_XL_2\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/pixart/pixart.py",
"chars": 15026,
"preview": "# Adapted from PixArt\n#\n# Copyright (C) 2023 PixArt-alpha/PixArt-alpha\n#\n# This program is free software: you can redis"
},
{
"path": "Open-Sora/build/lib/opensora/models/pixart/pixart_sigma.py",
"chars": 12814,
"preview": "# Adapted from PixArt\n#\n# Copyright (C) 2023 PixArt-alpha/PixArt-alpha\n#\n# This program is free software: you can redis"
},
{
"path": "Open-Sora/build/lib/opensora/models/stdit/__init__.py",
"chars": 79,
"preview": "from .stdit import STDiT\nfrom .stdit2 import STDiT2\nfrom .stdit3 import STDiT3\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/stdit/stdit.py",
"chars": 16134,
"preview": "import numpy as np\nimport torch\nimport torch.distributed as dist\nimport torch.nn as nn\nfrom einops import rearrange\nfrom"
},
{
"path": "Open-Sora/build/lib/opensora/models/stdit/stdit2.py",
"chars": 19300,
"preview": "import os\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nfrom einops import rearrange\nfrom rotary_embedding_torc"
},
{
"path": "Open-Sora/build/lib/opensora/models/stdit/stdit3 copy.py",
"chars": 24020,
"preview": "import os\n\nimport numpy as np\nimport torch\nimport torch.distributed as dist\nimport torch.nn as nn\nimport torch.nn.functi"
},
{
"path": "Open-Sora/build/lib/opensora/models/stdit/stdit3.py",
"chars": 21436,
"preview": "import os\n\nimport numpy as np\nimport torch\nimport torch.distributed as dist\nimport torch.nn as nn\nimport torch.nn.functi"
},
{
"path": "Open-Sora/build/lib/opensora/models/text_encoder/__init__.py",
"chars": 90,
"preview": "from .classes import ClassEncoder\nfrom .clip import ClipEncoder\nfrom .t5 import T5Encoder\n"
},
{
"path": "Open-Sora/build/lib/opensora/models/text_encoder/classes.py",
"chars": 579,
"preview": "import torch\n\nfrom opensora.registry import MODELS\n\n\n@MODELS.register_module(\"classes\")\nclass ClassEncoder:\n def __in"
},
{
"path": "Open-Sora/build/lib/opensora/models/text_encoder/clip.py",
"chars": 3654,
"preview": "# Copyright 2024 Vchitect/Latte\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use th"
},
{
"path": "Open-Sora/build/lib/opensora/models/text_encoder/t5.py",
"chars": 11745,
"preview": "# Adapted from PixArt\n#\n# Copyright (C) 2023 PixArt-alpha/PixArt-alpha\n#\n# This program is free software: you can redis"
},
{
"path": "Open-Sora/build/lib/tools/caption/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/caption/acceleration/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/caption/acceleration/llava/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/caption/acceleration/llava/policies/__init__.py",
"chars": 98,
"preview": "from .llama import LlavaLlamaForCausalLMPolicy\nfrom .mistral import LlavaMistralForCausalLMPolicy\n"
},
{
"path": "Open-Sora/build/lib/tools/caption/acceleration/llava/policies/llama.py",
"chars": 3867,
"preview": "from typing import Dict, Union\n\nimport torch.nn as nn\nfrom colossalai.shardformer.layer import Linear1D_Col, Linear1D_Ro"
},
{
"path": "Open-Sora/build/lib/tools/caption/acceleration/llava/policies/mistral.py",
"chars": 4442,
"preview": "import warnings\nfrom typing import Dict, Union\n\nimport torch.nn as nn\nfrom colossalai.shardformer.layer import Linear1D_"
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion/camera_motion.py",
"chars": 5695,
"preview": "import os\n\nimport numpy as np\nimport torch\n\nfrom .utils import load_video\nfrom .visualizer import Visualizer\n\n\ndef trans"
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion/detect.py",
"chars": 1000,
"preview": "# Originally developed by https://github.com/Vchitect/VBench based on https://github.com/facebookresearch/co-tracker.\n\ni"
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion/utils.py",
"chars": 4974,
"preview": "import numpy as np\nimport torch\nfrom decord import VideoReader\nfrom PIL import Image, ImageSequence\n\n\ndef get_frame_indi"
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion/visualizer.py",
"chars": 12419,
"preview": "# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the li"
},
{
"path": "Open-Sora/build/lib/tools/caption/camera_motion_detect.py",
"chars": 3848,
"preview": "# ref: https://github.com/antiboredom/camera-motion-detector\n\nimport argparse\n\nimport cv2\nimport numpy as np\nimport pand"
},
{
"path": "Open-Sora/build/lib/tools/caption/caption_gpt4.py",
"chars": 3213,
"preview": "import argparse\nimport base64\nimport csv\nimport os\nfrom io import BytesIO\n\nimport requests\nimport tqdm\n\nfrom .utils impo"
},
{
"path": "Open-Sora/build/lib/tools/caption/caption_llama3.py",
"chars": 10049,
"preview": "import argparse\nimport csv\nimport os\nimport warnings\nfrom datetime import timedelta\n\nimport pandas as pd\nimport torch\nim"
},
{
"path": "Open-Sora/build/lib/tools/caption/caption_llava.py",
"chars": 13956,
"preview": "import argparse\nimport csv\nimport time\nimport warnings\nfrom datetime import timedelta\n\nimport torch\nimport torch.distrib"
},
{
"path": "Open-Sora/build/lib/tools/caption/utils.py",
"chars": 12686,
"preview": "import time\n\nimport pandas as pd\nimport torch\nimport torchvision.transforms as transforms\nfrom torchvision.datasets.fold"
},
{
"path": "Open-Sora/build/lib/tools/datasets/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/datasets/analyze.py",
"chars": 3146,
"preview": "import argparse\nimport os\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n\ndef read_file(input_path):\n if input"
},
{
"path": "Open-Sora/build/lib/tools/datasets/convert.py",
"chars": 4922,
"preview": "import argparse\nimport os\nimport time\n\nimport pandas as pd\nfrom torchvision.datasets import ImageNet\n\nIMG_EXTENSIONS = ("
},
{
"path": "Open-Sora/build/lib/tools/datasets/datautil.py",
"chars": 31062,
"preview": "import argparse\nimport html\nimport json\nimport os\nimport random\nimport re\nfrom functools import partial\nfrom glob import"
},
{
"path": "Open-Sora/build/lib/tools/datasets/filter_panda10m.py",
"chars": 8326,
"preview": "# TODO: remove this file before releasing\n\nimport argparse\nimport html\nimport os\nimport re\n\nimport pandas as pd\nfrom tqd"
},
{
"path": "Open-Sora/build/lib/tools/datasets/split.py",
"chars": 2425,
"preview": "import argparse\nfrom typing import List\n\nimport pandas as pd\nfrom mmengine.config import Config\n\nfrom opensora.datasets."
},
{
"path": "Open-Sora/build/lib/tools/datasets/transform.py",
"chars": 4194,
"preview": "import argparse\nimport os\nimport random\n\nimport cv2\nimport numpy as np\nimport pandas as pd\nfrom tqdm import tqdm\n\nfrom ."
},
{
"path": "Open-Sora/build/lib/tools/datasets/utils.py",
"chars": 4311,
"preview": "import os\n\nimport cv2\nimport numpy as np\nfrom PIL import Image\n\nIMG_EXTENSIONS = (\".jpg\", \".jpeg\", \".png\", \".ppm\", \".bmp"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/interpolation.py",
"chars": 7181,
"preview": "# this script is modified from https://github.com/MCG-NKU/AMT/blob/main/demos/demo_2x.py\nimport argparse\nimport os\nimpor"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/__init__.py",
"chars": 25,
"preview": "from .amt_g import Model\n"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/amt_g.py",
"chars": 7411,
"preview": "import torch\nimport torch.nn as nn\n\nfrom .blocks.feat_enc import LargeEncoder\nfrom .blocks.ifrnet import Encoder, InitDe"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/feat_enc.py",
"chars": 11158,
"preview": "import torch\nimport torch.nn as nn\n\n\nclass BottleneckBlock(nn.Module):\n def __init__(self, in_planes, planes, norm_fn"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/ifrnet.py",
"chars": 4231,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom tools.frame_interpolation.utils.flow_utils impo"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/multi_flow.py",
"chars": 2583,
"preview": "import torch\nimport torch.nn as nn\n\nfrom tools.frame_interpolation.utils.flow_utils import warp\n\nfrom .ifrnet import Res"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/networks/blocks/raft.py",
"chars": 8078,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef resize(x, scale_factor):\n return F.interpola"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/utils/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/utils/dist_utils.py",
"chars": 1460,
"preview": "import os\n\nimport torch\n\n\ndef get_world_size():\n \"\"\"Find OMPI world size without calling mpi functions\n :rtype: in"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/utils/flow_utils.py",
"chars": 4424,
"preview": "import numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom PIL import ImageFile\n\nImageFile.LOAD_TRUNCATED_IMAG"
},
{
"path": "Open-Sora/build/lib/tools/frame_interpolation/utils/utils.py",
"chars": 8342,
"preview": "import random\nimport re\nimport sys\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom imageio import "
},
{
"path": "Open-Sora/build/lib/tools/scene_cut/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/scene_cut/convert_id_to_path.py",
"chars": 4164,
"preview": "import argparse\nimport json\nimport os\nfrom functools import partial\n\nimport cv2\nimport numpy as np\nimport pandas as pd\nf"
},
{
"path": "Open-Sora/build/lib/tools/scene_cut/cut.py",
"chars": 7048,
"preview": "import cv2 # isort:skip\n\nimport argparse\nimport os\nimport subprocess\nfrom functools import partial\n\nimport pandas as pd"
},
{
"path": "Open-Sora/build/lib/tools/scene_cut/scene_detect.py",
"chars": 1861,
"preview": "import argparse\nimport os\n\nimport numpy as np\nimport pandas as pd\nfrom pandarallel import pandarallel\nfrom scenedetect i"
},
{
"path": "Open-Sora/build/lib/tools/scoring/aesthetic/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/scoring/aesthetic/inference.py",
"chars": 6748,
"preview": "# adapted from https://github.com/christophschuhmann/improved-aesthetic-predictor/blob/main/simple_inference.py\nimport c"
},
{
"path": "Open-Sora/build/lib/tools/scoring/matching/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/tools/scoring/matching/inference.py",
"chars": 4220,
"preview": "import argparse\nimport os\n\nimport clip\nimport colossalai\nimport numpy as np\nimport pandas as pd\nimport torch\nimport torc"
},
{
"path": "Open-Sora/build/lib/vbench/__init__.py",
"chars": 8626,
"preview": "import os\n\nfrom .utils import get_prompt_from_filename, init_submodules, save_json, load_json\nimport importlib\nfrom iter"
},
{
"path": "Open-Sora/build/lib/vbench/aesthetic_quality.py",
"chars": 2842,
"preview": "import os\nimport clip\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport subprocess\nfrom urllib.r"
},
{
"path": "Open-Sora/build/lib/vbench/appearance_style.py",
"chars": 2884,
"preview": "import os\nimport json\nimport numpy as np\nfrom tqdm import tqdm\n\nimport torch\nimport clip\nfrom PIL import Image\nfrom vben"
},
{
"path": "Open-Sora/build/lib/vbench/background_consistency.py",
"chars": 2438,
"preview": "import os\nimport json\nimport logging\nimport numpy as np\nimport clip\nfrom PIL import Image\nimport torch\nimport torch.nn a"
},
{
"path": "Open-Sora/build/lib/vbench/cli/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/vbench/cli/evaluate.py",
"chars": 5262,
"preview": "import torch\nimport os\nfrom vbench import VBench\nfrom datetime import datetime\nimport argparse\nimport json\n\nCUR_DIR = os"
},
{
"path": "Open-Sora/build/lib/vbench/cli/static_filter.py",
"chars": 7316,
"preview": "import os\nimport cv2\nimport glob\nimport numpy as np\nimport torch\nfrom tqdm import tqdm\nfrom pathlib import Path\nimport j"
},
{
"path": "Open-Sora/build/lib/vbench/cli/vbench.py",
"chars": 563,
"preview": "import argparse\nimport importlib\nimport subprocess\n\nvbench_cmd = ['evaluate', 'static_filter']\n\ndef main():\n parser ="
},
{
"path": "Open-Sora/build/lib/vbench/color.py",
"chars": 3268,
"preview": "import os\nimport json\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom vbench.utils import load_video, load_d"
},
{
"path": "Open-Sora/build/lib/vbench/dynamic_degree.py",
"chars": 5046,
"preview": "import argparse\nimport os\nimport cv2\nimport glob\nimport numpy as np\nimport torch\nfrom tqdm import tqdm\nfrom easydict imp"
},
{
"path": "Open-Sora/build/lib/vbench/human_action.py",
"chars": 3731,
"preview": "import os\nimport json\nimport numpy as np\nimport clip\nfrom PIL import Image\nimport torch\nimport torch.nn as nn\nimport tor"
},
{
"path": "Open-Sora/build/lib/vbench/imaging_quality.py",
"chars": 2153,
"preview": "import torch\nfrom tqdm import tqdm\nfrom torchvision import transforms\nfrom pyiqa.archs.musiq_arch import MUSIQ\nfrom vben"
},
{
"path": "Open-Sora/build/lib/vbench/motion_smoothness.py",
"chars": 6662,
"preview": "import os\nimport cv2\nimport glob\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom omegaconf import OmegaConf\n\n"
},
{
"path": "Open-Sora/build/lib/vbench/multiple_objects.py",
"chars": 2485,
"preview": "import os\nimport json\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom vbench.utils import load_video, load_d"
},
{
"path": "Open-Sora/build/lib/vbench/object_class.py",
"chars": 2324,
"preview": "import os\nimport json\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom vbench.utils import load_video, load_d"
},
{
"path": "Open-Sora/build/lib/vbench/overall_consistency.py",
"chars": 2786,
"preview": "import os\nimport json\nimport numpy as np\n\nimport torch\nimport clip\nfrom tqdm import tqdm\nfrom vbench.utils import load_v"
},
{
"path": "Open-Sora/build/lib/vbench/scene.py",
"chars": 2432,
"preview": "import os\nimport json\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom vbench.utils import load_video, load_d"
},
{
"path": "Open-Sora/build/lib/vbench/spatial_relationship.py",
"chars": 5257,
"preview": "import os\nimport json\n\nimport torch\nimport numpy as np\nfrom tqdm import tqdm\nfrom vbench.utils import load_video, load_d"
},
{
"path": "Open-Sora/build/lib/vbench/subject_consistency.py",
"chars": 2677,
"preview": "import io\nimport os\nimport cv2\nimport json\nimport numpy as np\nfrom PIL import Image\nfrom tqdm import tqdm\n\nimport torch\n"
},
{
"path": "Open-Sora/build/lib/vbench/temporal_flickering.py",
"chars": 1804,
"preview": "import numpy as np\nfrom tqdm import tqdm\nimport cv2\nfrom vbench.utils import load_dimension_info\n\n\ndef get_frames(video_"
},
{
"path": "Open-Sora/build/lib/vbench/temporal_style.py",
"chars": 2830,
"preview": "import os\nimport json\nimport numpy as np\n\nimport torch\nimport clip\nfrom tqdm import tqdm\nfrom vbench.utils import load_v"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/0.txt",
"chars": 1,
"preview": "\n"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/corr.py",
"chars": 3091,
"preview": "import torch\nimport torch.nn.functional as F\nfrom .utils_core.utils import bilinear_sampler, coords_grid\n\ntry:\n impor"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/datasets.py",
"chars": 9255,
"preview": "# Data loading based on https://github.com/NVIDIA/flownet2-pytorch\n\nimport numpy as np\nimport torch\nimport torch.utils.d"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/extractor.py",
"chars": 8847,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass ResidualBlock(nn.Module):\n def __init__(se"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/raft.py",
"chars": 4933,
"preview": "import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom .update import BasicUpdateBl"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/update.py",
"chars": 5227,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass FlowHead(nn.Module):\n def __init__(self, i"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/augmentor.py",
"chars": 9108,
"preview": "import numpy as np\nimport random\nimport math\nfrom PIL import Image\n\nimport cv2\ncv2.setNumThreads(0)\ncv2.ocl.setUseOpenCL"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/flow_viz.py",
"chars": 4318,
"preview": "# Flow visualization code used from https://github.com/tomrunia/OpticalFlow_Visualization\n\n\n# MIT License\n#\n# Copyright "
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/frame_utils.py",
"chars": 4024,
"preview": "import numpy as np\nfrom PIL import Image\nfrom os.path import *\nimport re\n\nimport cv2\ncv2.setNumThreads(0)\ncv2.ocl.setUse"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/RAFT/core/utils_core/utils.py",
"chars": 2489,
"preview": "import torch\nimport torch.nn.functional as F\nimport numpy as np\nfrom scipy import interpolate\n\n\nclass InputPadder:\n \""
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/ViCLIP/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/ViCLIP/simple_tokenizer.py",
"chars": 4982,
"preview": "import gzip\nimport html\nimport os\nimport subprocess\nfrom functools import lru_cache\nimport ftfy\nimport regex as re\nfrom "
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip.py",
"chars": 7935,
"preview": "import os\nimport logging\n\nimport torch\nfrom einops import rearrange\nfrom torch import nn\nimport math\n\nfrom .simple_token"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip_text.py",
"chars": 9344,
"preview": "import os\nimport logging\nfrom collections import OrderedDict\nfrom pkg_resources import packaging\nfrom .simple_tokenizer "
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/ViCLIP/viclip_vision.py",
"chars": 12460,
"preview": "#!/usr/bin/env python\nimport os\nimport logging\nfrom collections import OrderedDict\n\nimport torch\nfrom torch import nn\nfr"
},
{
"path": "Open-Sora/build/lib/vbench/third_pary/__init__.py",
"chars": 0,
"preview": ""
}
]
// ... and 513 more files (download for full content)
About this extraction
This page contains the full source code of the Shenyi-Z/ToCa GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 713 files (6.6 MB), approximately 1.8M tokens, and a symbol index with 3978 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.