Full Code of MIV-XJTU/ARTrack for AI

gitextract_o26t4wgy/

├── ARTrack_env_cuda113.yaml
├── LICENSE
├── README.md
├── artrackv2_mindspore/
│   ├── .gitignore
│   ├── README.md
│   ├── experiments/
│   │   └── ostrack/
│   │       ├── 2stage_256_got.yaml
│   │       ├── best_384.yaml
│   │       ├── finetune.yaml
│   │       ├── finetune_384.yaml
│   │       ├── finetune_384_got.yaml
│   │       ├── vitb_256_mae_32x4_ep300.yaml
│   │       ├── vitb_256_mae_ce_32x4_ep300.yaml
│   │       ├── vitb_256_mae_ce_32x4_got10k_ep100.yaml
│   │       ├── vitb_384_mae_32x4_ep300.yaml
│   │       ├── vitb_384_mae_ce_32x4_ep300.yaml
│   │       └── vitb_384_mae_ce_32x4_got10k_ep100.yaml
│   ├── external/
│   │   ├── AR/
│   │   │   ├── README.md
│   │   │   ├── __init__.py
│   │   │   ├── ltr/
│   │   │   │   ├── README.md
│   │   │   │   ├── __init__.py
│   │   │   │   ├── actors/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── base_actor.py
│   │   │   │   │   ├── bbreg.py
│   │   │   │   │   └── tracking.py
│   │   │   │   ├── admin/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── environment.py
│   │   │   │   │   ├── loading.py
│   │   │   │   │   ├── model_constructor.py
│   │   │   │   │   ├── multigpu.py
│   │   │   │   │   ├── settings.py
│   │   │   │   │   ├── stats.py
│   │   │   │   │   └── tensorboard.py
│   │   │   │   ├── data/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── bounding_box_utils.py
│   │   │   │   │   ├── image_loader.py
│   │   │   │   │   ├── loader.py
│   │   │   │   │   ├── processing.py
│   │   │   │   │   ├── processing_utils.py
│   │   │   │   │   ├── processing_utils_SE.py
│   │   │   │   │   ├── sampler.py
│   │   │   │   │   └── transforms.py
│   │   │   │   ├── dataset/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── base_image_dataset.py
│   │   │   │   │   ├── base_video_dataset.py
│   │   │   │   │   ├── coco.py
│   │   │   │   │   ├── coco_seq.py
│   │   │   │   │   ├── davis.py
│   │   │   │   │   ├── ecssd.py
│   │   │   │   │   ├── got10k.py
│   │   │   │   │   ├── hku_is.py
│   │   │   │   │   ├── imagenetvid.py
│   │   │   │   │   ├── lasot.py
│   │   │   │   │   ├── lvis.py
│   │   │   │   │   ├── msra10k.py
│   │   │   │   │   ├── sbd.py
│   │   │   │   │   ├── synthetic_video.py
│   │   │   │   │   ├── synthetic_video_blend.py
│   │   │   │   │   ├── tracking_net.py
│   │   │   │   │   ├── vos_base.py
│   │   │   │   │   └── youtubevos.py
│   │   │   │   ├── external/
│   │   │   │   │   └── PreciseRoIPooling/
│   │   │   │   │       ├── .gitignore
│   │   │   │   │       ├── LICENSE
│   │   │   │   │       ├── README.md
│   │   │   │   │       ├── pytorch/
│   │   │   │   │       │   ├── prroi_pool/
│   │   │   │   │       │   │   ├── .gitignore
│   │   │   │   │       │   │   ├── __init__.py
│   │   │   │   │       │   │   ├── functional.py
│   │   │   │   │       │   │   ├── prroi_pool.py
│   │   │   │   │       │   │   └── src/
│   │   │   │   │       │   │       ├── prroi_pooling_gpu.c
│   │   │   │   │       │   │       ├── prroi_pooling_gpu.h
│   │   │   │   │       │   │       ├── prroi_pooling_gpu_impl.cu
│   │   │   │   │       │   │       └── prroi_pooling_gpu_impl.cuh
│   │   │   │   │       │   └── tests/
│   │   │   │   │       │       └── test_prroi_pooling2d.py
│   │   │   │   │       └── src/
│   │   │   │   │           ├── prroi_pooling_gpu_impl.cu
│   │   │   │   │           └── prroi_pooling_gpu_impl.cuh
│   │   │   │   ├── models/
│   │   │   │   │   ├── AR_seg_mask/
│   │   │   │   │   │   ├── AR_seg_mask.py
│   │   │   │   │   │   └── __init__.py
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── backbone/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── base.py
│   │   │   │   │   │   ├── resnet.py
│   │   │   │   │   │   ├── resnet18_vggm.py
│   │   │   │   │   │   └── resnet_seg.py
│   │   │   │   │   ├── bbreg/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── atom.py
│   │   │   │   │   │   └── atom_iou_net.py
│   │   │   │   │   ├── head/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── seg_network.py
│   │   │   │   │   │   └── utils.py
│   │   │   │   │   ├── layers/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── activation.py
│   │   │   │   │   │   ├── blocks.py
│   │   │   │   │   │   ├── distance.py
│   │   │   │   │   │   ├── filter.py
│   │   │   │   │   │   ├── normalization.py
│   │   │   │   │   │   └── transform.py
│   │   │   │   │   ├── loss/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── kl_regression.py
│   │   │   │   │   │   └── target_classification.py
│   │   │   │   │   ├── meta/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   └── steepestdescent.py
│   │   │   │   │   ├── neck/
│   │   │   │   │   │   ├── CorrNL.py
│   │   │   │   │   │   └── neck_utils.py
│   │   │   │   │   ├── target_classifier/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── features.py
│   │   │   │   │   │   ├── initializer.py
│   │   │   │   │   │   ├── linear_filter.py
│   │   │   │   │   │   ├── optimizer.py
│   │   │   │   │   │   └── residual_modules.py
│   │   │   │   │   └── tracking/
│   │   │   │   │       ├── __init__.py
│   │   │   │   │       └── dimpnet.py
│   │   │   │   ├── run_training.py
│   │   │   │   ├── train_settings/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── bbreg/
│   │   │   │   │   │   ├── __init__.py
│   │   │   │   │   │   ├── atom.py
│   │   │   │   │   │   ├── atom_gmm_sampl.py
│   │   │   │   │   │   ├── atom_paper.py
│   │   │   │   │   │   └── atom_prob_ml.py
│   │   │   │   │   └── dimp/
│   │   │   │   │       ├── __init__.py
│   │   │   │   │       ├── dimp18.py
│   │   │   │   │       ├── dimp50.py
│   │   │   │   │       ├── prdimp18.py
│   │   │   │   │       ├── prdimp50.py
│   │   │   │   │       └── super_dimp.py
│   │   │   │   └── trainers/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── base_trainer.py
│   │   │   │       └── ltr_trainer.py
│   │   │   └── pytracking/
│   │   │       ├── ARcm_seg.py
│   │   │       ├── VOT/
│   │   │       │   ├── tracker_DiMP.m
│   │   │       │   ├── trackers.ini
│   │   │       │   └── vot.py
│   │   │       ├── VOT2020_super_only_mask_384_HP/
│   │   │       │   ├── dimp_alpha_065.py
│   │   │       │   ├── dimp_alpha_seg_class.py
│   │   │       │   ├── mixformer_alpha_seg_class.py
│   │   │       │   ├── mixformer_large_alpha_seg_class.py
│   │   │       │   └── vot.py
│   │   │       ├── __init__.py
│   │   │       ├── analysis/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── evaluate_vos.py
│   │   │       │   ├── extract_results.py
│   │   │       │   ├── playback_results.py
│   │   │       │   ├── plot_results.py
│   │   │       │   └── vos_utils.py
│   │   │       ├── evaluation/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── data.py
│   │   │       │   ├── datasets.py
│   │   │       │   ├── environment.py
│   │   │       │   ├── got10kdataset.py
│   │   │       │   ├── lasotdataset.py
│   │   │       │   ├── mobifacedataset.py
│   │   │       │   ├── multi_object_wrapper.py
│   │   │       │   ├── nfsdataset.py
│   │   │       │   ├── otbdataset.py
│   │   │       │   ├── running.py
│   │   │       │   ├── tpldataset.py
│   │   │       │   ├── tracker.py
│   │   │       │   ├── trackingnetdataset.py
│   │   │       │   ├── uavdataset.py
│   │   │       │   ├── vot.py
│   │   │       │   ├── vot2020.py
│   │   │       │   └── votdataset.py
│   │   │       ├── experiments/
│   │   │       │   ├── __init__.py
│   │   │       │   └── myexperiments.py
│   │   │       ├── features/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── augmentation.py
│   │   │       │   ├── color.py
│   │   │       │   ├── deep.py
│   │   │       │   ├── extractor.py
│   │   │       │   ├── featurebase.py
│   │   │       │   ├── net_wrappers.py
│   │   │       │   ├── preprocessing.py
│   │   │       │   └── util.py
│   │   │       ├── libs/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── complex.py
│   │   │       │   ├── dcf.py
│   │   │       │   ├── fourier.py
│   │   │       │   ├── operation.py
│   │   │       │   ├── optimization.py
│   │   │       │   ├── tensordict.py
│   │   │       │   └── tensorlist.py
│   │   │       ├── parameter/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── atom/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   ├── atom_gmm_sampl.py
│   │   │       │   │   ├── atom_prob_ml.py
│   │   │       │   │   ├── default.py
│   │   │       │   │   ├── default_vot.py
│   │   │       │   │   └── multiscale_no_iounet.py
│   │   │       │   ├── dimp/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   ├── dimp18.py
│   │   │       │   │   ├── dimp18_vot.py
│   │   │       │   │   ├── dimp50.py
│   │   │       │   │   ├── dimp50_vot.py
│   │   │       │   │   ├── dimp50_vot19.py
│   │   │       │   │   ├── prdimp18.py
│   │   │       │   │   ├── prdimp50.py
│   │   │       │   │   └── super_dimp.py
│   │   │       │   └── eco/
│   │   │       │       ├── __init__.py
│   │   │       │       └── default.py
│   │   │       ├── tracker/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── atom/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   ├── atom.py
│   │   │       │   │   └── optim.py
│   │   │       │   ├── base/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   └── basetracker.py
│   │   │       │   ├── dimp/
│   │   │       │   │   ├── __init__.py
│   │   │       │   │   └── dimp.py
│   │   │       │   └── eco/
│   │   │       │       ├── __init__.py
│   │   │       │       ├── eco.py
│   │   │       │       └── optim.py
│   │   │       ├── util_scripts/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── download_results.py
│   │   │       │   ├── pack_got10k_results.py
│   │   │       │   └── pack_trackingnet_results.py
│   │   │       ├── utils/
│   │   │       │   ├── __init__.py
│   │   │       │   ├── convert_vot_anno_to_rect.py
│   │   │       │   ├── load_text.py
│   │   │       │   ├── loading.py
│   │   │       │   ├── params.py
│   │   │       │   ├── plotting.py
│   │   │       │   └── visdom.py
│   │   │       └── vot20_utils.py
│   │   ├── PreciseRoIPooling/
│   │   │   ├── .gitignore
│   │   │   ├── LICENSE
│   │   │   ├── README.md
│   │   │   ├── pytorch/
│   │   │   │   ├── prroi_pool/
│   │   │   │   │   ├── .gitignore
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── functional.py
│   │   │   │   │   ├── prroi_pool.py
│   │   │   │   │   └── src/
│   │   │   │   │       ├── prroi_pooling_gpu.c
│   │   │   │   │       ├── prroi_pooling_gpu.h
│   │   │   │   │       ├── prroi_pooling_gpu_impl.cu
│   │   │   │   │       └── prroi_pooling_gpu_impl.cuh
│   │   │   │   └── tests/
│   │   │   │       └── test_prroi_pooling2d.py
│   │   │   └── src/
│   │   │       ├── prroi_pooling_gpu_impl.cu
│   │   │       └── prroi_pooling_gpu_impl.cuh
│   │   └── vot20/
│   │       └── cttrack/
│   │           ├── config.yaml
│   │           └── trackers.ini
│   ├── lib/
│   │   ├── __init__.py
│   │   ├── config/
│   │   │   ├── __init__.py
│   │   │   └── ostrack/
│   │   │       └── config.py
│   │   ├── models/
│   │   │   ├── __init__.py
│   │   │   ├── component/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── attention.py
│   │   │   │   ├── block.py
│   │   │   │   ├── drop.py
│   │   │   │   ├── mlp.py
│   │   │   │   ├── norm.py
│   │   │   │   ├── patch_embed.py
│   │   │   │   ├── pos_embed.py
│   │   │   │   └── weight_init.py
│   │   │   ├── layers/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── attn.py
│   │   │   │   ├── attn_blocks.py
│   │   │   │   ├── head.py
│   │   │   │   ├── mask_decoder.py
│   │   │   │   ├── patch_embed.py
│   │   │   │   ├── rpe.py
│   │   │   │   └── self_practice.py
│   │   │   ├── ostrack/
│   │   │   │   ├── Vit_model_test.py
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_backbone.py
│   │   │   │   ├── load_parameter_test.py
│   │   │   │   ├── ostrack.py
│   │   │   │   ├── ostrack_test.py
│   │   │   │   ├── utils.py
│   │   │   │   ├── vit.py
│   │   │   │   └── vit_ce.py
│   │   │   └── timm.py
│   │   ├── train/
│   │   │   ├── __init__.py
│   │   │   ├── _init_paths.py
│   │   │   ├── actors/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_actor.py
│   │   │   │   └── ostrack.py
│   │   │   ├── admin/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── environment.py
│   │   │   │   ├── local.py
│   │   │   │   ├── settings.py
│   │   │   │   ├── stats.py
│   │   │   │   └── tensorboard.py
│   │   │   ├── base_functions.py
│   │   │   ├── data/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── bounding_box_utils.py
│   │   │   │   ├── image_loader.py
│   │   │   │   ├── loader.py
│   │   │   │   ├── processing.py
│   │   │   │   ├── processing_utils.py
│   │   │   │   ├── sampler.py
│   │   │   │   ├── sequence_sampler.py
│   │   │   │   ├── transforms.py
│   │   │   │   └── wandb_logger.py
│   │   │   ├── data_specs/
│   │   │   │   ├── README.md
│   │   │   │   ├── got10k_train_full_split.txt
│   │   │   │   ├── got10k_train_split.txt
│   │   │   │   ├── got10k_val_split.txt
│   │   │   │   ├── got10k_vot_exclude.txt
│   │   │   │   ├── got10k_vot_train_split.txt
│   │   │   │   ├── got10k_vot_val_split.txt
│   │   │   │   ├── lasot_train_split.txt
│   │   │   │   └── trackingnet_classmap.txt
│   │   │   ├── dataset/
│   │   │   │   ├── COCO_tool.py
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_image_dataset.py
│   │   │   │   ├── base_video_dataset.py
│   │   │   │   ├── coco.py
│   │   │   │   ├── coco_seq.py
│   │   │   │   ├── coco_seq_lmdb.py
│   │   │   │   ├── got10k.py
│   │   │   │   ├── got10k_lmdb.py
│   │   │   │   ├── imagenetvid.py
│   │   │   │   ├── imagenetvid_lmdb.py
│   │   │   │   ├── lasot.py
│   │   │   │   ├── lasot_lmdb.py
│   │   │   │   ├── tracking_net.py
│   │   │   │   └── tracking_net_lmdb.py
│   │   │   ├── run_training.py
│   │   │   ├── train_script.py
│   │   │   ├── train_script_distill.py
│   │   │   └── trainers/
│   │   │       ├── __init__.py
│   │   │       ├── base_trainer.py
│   │   │       └── ltr_trainer.py
│   │   ├── utils/
│   │   │   ├── __init__.py
│   │   │   ├── box_ops.py
│   │   │   ├── ce_utils.py
│   │   │   ├── focal_loss.py
│   │   │   ├── heapmap_utils.py
│   │   │   ├── image.py
│   │   │   ├── lmdb_utils.py
│   │   │   ├── merge.py
│   │   │   ├── misc.py
│   │   │   ├── tensor.py
│   │   │   └── variable_hook.py
│   │   └── vis/
│   │       ├── __init__.py
│   │       ├── plotting.py
│   │       └── utils.py
│   └── tracking/
│       ├── _init_paths.py
│       ├── analysis_results.ipynb
│       ├── analysis_results.py
│       ├── analysis_results_ITP.py
│       ├── convert_transt.py
│       ├── create_default_local_file.py
│       ├── download_pytracking_results.py
│       ├── pre_read_datasets.py
│       ├── profile_model.py
│       ├── test.py
│       ├── test_exp.py
│       ├── train.py
│       ├── video_demo.py
│       └── vis_results.py
├── experiments/
│   ├── artrack/
│   │   ├── artrack_256_full.yaml
│   │   ├── artrack_256_got.yaml
│   │   ├── artrack_384_full.yaml
│   │   └── artrack_large_384_full.yaml
│   ├── artrack_seq/
│   │   ├── artrack_seq_256_full.yaml
│   │   ├── artrack_seq_256_got.yaml
│   │   ├── artrack_seq_384_full.yaml
│   │   └── artrack_seq_large_384_full.yaml
│   ├── artrackv2/
│   │   ├── artrackv2_256_full.yaml
│   │   ├── artrackv2_256_got.yaml
│   │   └── artrackv2_large_384_got.yaml
│   └── artrackv2_seq/
│       ├── artrackv2_seq_256_full.yaml
│       ├── artrackv2_seq_256_got.yaml
│       └── artrackv2_seq_large_384_got.yaml
├── external/
│   ├── AR/
│   │   ├── README.md
│   │   ├── __init__.py
│   │   ├── ltr/
│   │   │   ├── README.md
│   │   │   ├── __init__.py
│   │   │   ├── actors/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_actor.py
│   │   │   │   ├── bbreg.py
│   │   │   │   └── tracking.py
│   │   │   ├── admin/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── environment.py
│   │   │   │   ├── loading.py
│   │   │   │   ├── model_constructor.py
│   │   │   │   ├── multigpu.py
│   │   │   │   ├── settings.py
│   │   │   │   ├── stats.py
│   │   │   │   └── tensorboard.py
│   │   │   ├── data/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── bounding_box_utils.py
│   │   │   │   ├── image_loader.py
│   │   │   │   ├── loader.py
│   │   │   │   ├── processing.py
│   │   │   │   ├── processing_utils.py
│   │   │   │   ├── processing_utils_SE.py
│   │   │   │   ├── sampler.py
│   │   │   │   └── transforms.py
│   │   │   ├── dataset/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_image_dataset.py
│   │   │   │   ├── base_video_dataset.py
│   │   │   │   ├── coco.py
│   │   │   │   ├── coco_seq.py
│   │   │   │   ├── davis.py
│   │   │   │   ├── ecssd.py
│   │   │   │   ├── got10k.py
│   │   │   │   ├── hku_is.py
│   │   │   │   ├── imagenetvid.py
│   │   │   │   ├── lasot.py
│   │   │   │   ├── lvis.py
│   │   │   │   ├── msra10k.py
│   │   │   │   ├── sbd.py
│   │   │   │   ├── synthetic_video.py
│   │   │   │   ├── synthetic_video_blend.py
│   │   │   │   ├── tracking_net.py
│   │   │   │   ├── vos_base.py
│   │   │   │   └── youtubevos.py
│   │   │   ├── external/
│   │   │   │   └── PreciseRoIPooling/
│   │   │   │       ├── .gitignore
│   │   │   │       ├── LICENSE
│   │   │   │       ├── README.md
│   │   │   │       ├── pytorch/
│   │   │   │       │   ├── prroi_pool/
│   │   │   │       │   │   ├── .gitignore
│   │   │   │       │   │   ├── __init__.py
│   │   │   │       │   │   ├── functional.py
│   │   │   │       │   │   ├── prroi_pool.py
│   │   │   │       │   │   └── src/
│   │   │   │       │   │       ├── prroi_pooling_gpu.c
│   │   │   │       │   │       ├── prroi_pooling_gpu.h
│   │   │   │       │   │       ├── prroi_pooling_gpu_impl.cu
│   │   │   │       │   │       └── prroi_pooling_gpu_impl.cuh
│   │   │   │       │   └── tests/
│   │   │   │       │       └── test_prroi_pooling2d.py
│   │   │   │       └── src/
│   │   │   │           ├── prroi_pooling_gpu_impl.cu
│   │   │   │           └── prroi_pooling_gpu_impl.cuh
│   │   │   ├── models/
│   │   │   │   ├── AR_seg_mask/
│   │   │   │   │   ├── AR_seg_mask.py
│   │   │   │   │   └── __init__.py
│   │   │   │   ├── __init__.py
│   │   │   │   ├── backbone/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── base.py
│   │   │   │   │   ├── resnet.py
│   │   │   │   │   ├── resnet18_vggm.py
│   │   │   │   │   └── resnet_seg.py
│   │   │   │   ├── bbreg/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── atom.py
│   │   │   │   │   └── atom_iou_net.py
│   │   │   │   ├── head/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── seg_network.py
│   │   │   │   │   └── utils.py
│   │   │   │   ├── layers/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── activation.py
│   │   │   │   │   ├── blocks.py
│   │   │   │   │   ├── distance.py
│   │   │   │   │   ├── filter.py
│   │   │   │   │   ├── normalization.py
│   │   │   │   │   └── transform.py
│   │   │   │   ├── loss/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── kl_regression.py
│   │   │   │   │   └── target_classification.py
│   │   │   │   ├── meta/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   └── steepestdescent.py
│   │   │   │   ├── neck/
│   │   │   │   │   ├── CorrNL.py
│   │   │   │   │   └── neck_utils.py
│   │   │   │   ├── target_classifier/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── features.py
│   │   │   │   │   ├── initializer.py
│   │   │   │   │   ├── linear_filter.py
│   │   │   │   │   ├── optimizer.py
│   │   │   │   │   └── residual_modules.py
│   │   │   │   └── tracking/
│   │   │   │       ├── __init__.py
│   │   │   │       └── dimpnet.py
│   │   │   ├── run_training.py
│   │   │   ├── train_settings/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── bbreg/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   ├── atom.py
│   │   │   │   │   ├── atom_gmm_sampl.py
│   │   │   │   │   ├── atom_paper.py
│   │   │   │   │   └── atom_prob_ml.py
│   │   │   │   └── dimp/
│   │   │   │       ├── __init__.py
│   │   │   │       ├── dimp18.py
│   │   │   │       ├── dimp50.py
│   │   │   │       ├── prdimp18.py
│   │   │   │       ├── prdimp50.py
│   │   │   │       └── super_dimp.py
│   │   │   └── trainers/
│   │   │       ├── __init__.py
│   │   │       ├── base_trainer.py
│   │   │       └── ltr_trainer.py
│   │   └── pytracking/
│   │       ├── ARcm_seg.py
│   │       ├── VOT/
│   │       │   ├── tracker_DiMP.m
│   │       │   ├── trackers.ini
│   │       │   └── vot.py
│   │       ├── VOT2020_super_only_mask_384_HP/
│   │       │   ├── dimp_alpha_065.py
│   │       │   ├── dimp_alpha_seg_class.py
│   │       │   ├── mixformer_alpha_seg_class.py
│   │       │   ├── mixformer_large_alpha_seg_class.py
│   │       │   └── vot.py
│   │       ├── __init__.py
│   │       ├── analysis/
│   │       │   ├── __init__.py
│   │       │   ├── evaluate_vos.py
│   │       │   ├── extract_results.py
│   │       │   ├── playback_results.py
│   │       │   ├── plot_results.py
│   │       │   └── vos_utils.py
│   │       ├── evaluation/
│   │       │   ├── __init__.py
│   │       │   ├── data.py
│   │       │   ├── datasets.py
│   │       │   ├── environment.py
│   │       │   ├── got10kdataset.py
│   │       │   ├── lasotdataset.py
│   │       │   ├── mobifacedataset.py
│   │       │   ├── multi_object_wrapper.py
│   │       │   ├── nfsdataset.py
│   │       │   ├── otbdataset.py
│   │       │   ├── running.py
│   │       │   ├── tpldataset.py
│   │       │   ├── tracker.py
│   │       │   ├── trackingnetdataset.py
│   │       │   ├── uavdataset.py
│   │       │   ├── vot.py
│   │       │   ├── vot2020.py
│   │       │   └── votdataset.py
│   │       ├── experiments/
│   │       │   ├── __init__.py
│   │       │   └── myexperiments.py
│   │       ├── features/
│   │       │   ├── __init__.py
│   │       │   ├── augmentation.py
│   │       │   ├── color.py
│   │       │   ├── deep.py
│   │       │   ├── extractor.py
│   │       │   ├── featurebase.py
│   │       │   ├── net_wrappers.py
│   │       │   ├── preprocessing.py
│   │       │   └── util.py
│   │       ├── libs/
│   │       │   ├── __init__.py
│   │       │   ├── complex.py
│   │       │   ├── dcf.py
│   │       │   ├── fourier.py
│   │       │   ├── operation.py
│   │       │   ├── optimization.py
│   │       │   ├── tensordict.py
│   │       │   └── tensorlist.py
│   │       ├── parameter/
│   │       │   ├── __init__.py
│   │       │   ├── atom/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── atom_gmm_sampl.py
│   │       │   │   ├── atom_prob_ml.py
│   │       │   │   ├── default.py
│   │       │   │   ├── default_vot.py
│   │       │   │   └── multiscale_no_iounet.py
│   │       │   ├── dimp/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── dimp18.py
│   │       │   │   ├── dimp18_vot.py
│   │       │   │   ├── dimp50.py
│   │       │   │   ├── dimp50_vot.py
│   │       │   │   ├── dimp50_vot19.py
│   │       │   │   ├── prdimp18.py
│   │       │   │   ├── prdimp50.py
│   │       │   │   └── super_dimp.py
│   │       │   └── eco/
│   │       │       ├── __init__.py
│   │       │       └── default.py
│   │       ├── tracker/
│   │       │   ├── __init__.py
│   │       │   ├── atom/
│   │       │   │   ├── __init__.py
│   │       │   │   ├── atom.py
│   │       │   │   └── optim.py
│   │       │   ├── base/
│   │       │   │   ├── __init__.py
│   │       │   │   └── basetracker.py
│   │       │   ├── dimp/
│   │       │   │   ├── __init__.py
│   │       │   │   └── dimp.py
│   │       │   └── eco/
│   │       │       ├── __init__.py
│   │       │       ├── eco.py
│   │       │       └── optim.py
│   │       ├── util_scripts/
│   │       │   ├── __init__.py
│   │       │   ├── download_results.py
│   │       │   ├── pack_got10k_results.py
│   │       │   └── pack_trackingnet_results.py
│   │       ├── utils/
│   │       │   ├── __init__.py
│   │       │   ├── convert_vot_anno_to_rect.py
│   │       │   ├── load_text.py
│   │       │   ├── loading.py
│   │       │   ├── params.py
│   │       │   ├── plotting.py
│   │       │   └── visdom.py
│   │       └── vot20_utils.py
│   ├── PreciseRoIPooling/
│   │   ├── .gitignore
│   │   ├── LICENSE
│   │   ├── README.md
│   │   ├── pytorch/
│   │   │   ├── prroi_pool/
│   │   │   │   ├── .gitignore
│   │   │   │   ├── __init__.py
│   │   │   │   ├── functional.py
│   │   │   │   ├── prroi_pool.py
│   │   │   │   └── src/
│   │   │   │       ├── prroi_pooling_gpu.c
│   │   │   │       ├── prroi_pooling_gpu.h
│   │   │   │       ├── prroi_pooling_gpu_impl.cu
│   │   │   │       └── prroi_pooling_gpu_impl.cuh
│   │   │   └── tests/
│   │   │       └── test_prroi_pooling2d.py
│   │   └── src/
│   │       ├── prroi_pooling_gpu_impl.cu
│   │       └── prroi_pooling_gpu_impl.cuh
│   └── vot20/
│       └── cttrack/
│           ├── config.yaml
│           └── trackers.ini
├── lib/
│   ├── __init__.py
│   ├── config/
│   │   ├── __init__.py
│   │   ├── artrack/
│   │   │   └── config.py
│   │   ├── artrack_seq/
│   │   │   └── config.py
│   │   ├── artrackv2/
│   │   │   └── config.py
│   │   └── artrackv2_seq/
│   │       └── config.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── artrack/
│   │   │   ├── __init__.py
│   │   │   ├── artrack.py
│   │   │   ├── base_backbone.py
│   │   │   ├── utils.py
│   │   │   ├── vit.py
│   │   │   └── vit_ce.py
│   │   ├── artrack_seq/
│   │   │   ├── __init__.py
│   │   │   ├── artrack_seq.py
│   │   │   ├── base_backbone.py
│   │   │   ├── utils.py
│   │   │   ├── vit.py
│   │   │   └── vit_ce.py
│   │   ├── artrackv2/
│   │   │   ├── __init__.py
│   │   │   ├── artrackv2.py
│   │   │   ├── base_backbone.py
│   │   │   ├── utils.py
│   │   │   └── vit.py
│   │   ├── artrackv2_seq/
│   │   │   ├── __init__.py
│   │   │   ├── artrackv2_seq.py
│   │   │   ├── base_backbone.py
│   │   │   ├── utils.py
│   │   │   └── vit.py
│   │   ├── layers/
│   │   │   ├── __init__.py
│   │   │   ├── attn.py
│   │   │   ├── attn_blocks.py
│   │   │   ├── frozen_bn.py
│   │   │   ├── head.py
│   │   │   ├── head_seq.py
│   │   │   ├── mask_decoder.py
│   │   │   ├── patch_embed.py
│   │   │   └── rpe.py
│   │   └── mask_decoder/
│   │       ├── __init__.py
│   │       ├── attention.py
│   │       ├── block.py
│   │       ├── drop.py
│   │       ├── mlp.py
│   │       ├── norm.py
│   │       ├── patch_embed.py
│   │       ├── pos_embed.py
│   │       └── weight_init.py
│   ├── test/
│   │   ├── __init__.py
│   │   ├── analysis/
│   │   │   ├── __init__.py
│   │   │   ├── extract_results.py
│   │   │   └── plot_results.py
│   │   ├── evaluation/
│   │   │   ├── __init__.py
│   │   │   ├── data.py
│   │   │   ├── datasets.py
│   │   │   ├── environment.py
│   │   │   ├── got10kdataset.py
│   │   │   ├── itbdataset.py
│   │   │   ├── lasot_lmdbdataset.py
│   │   │   ├── lasotdataset.py
│   │   │   ├── lasotextensionsubsetdataset.py
│   │   │   ├── local.py
│   │   │   ├── nfsdataset.py
│   │   │   ├── otbdataset.py
│   │   │   ├── running.py
│   │   │   ├── tc128cedataset.py
│   │   │   ├── tc128dataset.py
│   │   │   ├── tnl2kdataset.py
│   │   │   ├── tracker.py
│   │   │   ├── trackingnetdataset.py
│   │   │   ├── uavdataset.py
│   │   │   └── votdataset.py
│   │   ├── parameter/
│   │   │   ├── __init__.py
│   │   │   ├── artrack.py
│   │   │   ├── artrack_seq.py
│   │   │   ├── artrackv2.py
│   │   │   └── artrackv2_seq.py
│   │   ├── tracker/
│   │   │   ├── __init__.py
│   │   │   ├── artrack.py
│   │   │   ├── artrack_seq.py
│   │   │   ├── artrackv2.py
│   │   │   ├── artrackv2_seq.py
│   │   │   ├── basetracker.py
│   │   │   ├── data_utils.py
│   │   │   └── vis_utils.py
│   │   └── utils/
│   │       ├── __init__.py
│   │       ├── _init_paths.py
│   │       ├── hann.py
│   │       ├── load_text.py
│   │       ├── params.py
│   │       ├── transform_got10k.py
│   │       └── transform_trackingnet.py
│   ├── train/
│   │   ├── __init__.py
│   │   ├── _init_paths.py
│   │   ├── actors/
│   │   │   ├── __init__.py
│   │   │   ├── artrack.py
│   │   │   ├── artrack_seq.py
│   │   │   ├── artrackv2.py
│   │   │   ├── artrackv2_seq.py
│   │   │   └── base_actor.py
│   │   ├── admin/
│   │   │   ├── __init__.py
│   │   │   ├── environment.py
│   │   │   ├── local.py
│   │   │   ├── multigpu.py
│   │   │   ├── settings.py
│   │   │   ├── stats.py
│   │   │   └── tensorboard.py
│   │   ├── base_functions.py
│   │   ├── data/
│   │   │   ├── __init__.py
│   │   │   ├── bounding_box_utils.py
│   │   │   ├── image_loader.py
│   │   │   ├── loader.py
│   │   │   ├── processing.py
│   │   │   ├── processing_utils.py
│   │   │   ├── sampler.py
│   │   │   ├── sequence_sampler.py
│   │   │   ├── sequence_sampler_v2.py
│   │   │   ├── transforms.py
│   │   │   └── wandb_logger.py
│   │   ├── data_specs/
│   │   │   ├── README.md
│   │   │   ├── got10k_train_full_split.txt
│   │   │   ├── got10k_train_split.txt
│   │   │   ├── got10k_val_split.txt
│   │   │   ├── got10k_vot_exclude.txt
│   │   │   ├── got10k_vot_train_split.txt
│   │   │   ├── got10k_vot_val_split.txt
│   │   │   ├── lasot_train_split.txt
│   │   │   └── trackingnet_classmap.txt
│   │   ├── dataset/
│   │   │   ├── COCO_tool.py
│   │   │   ├── __init__.py
│   │   │   ├── base_image_dataset.py
│   │   │   ├── base_video_dataset.py
│   │   │   ├── coco.py
│   │   │   ├── coco_seq.py
│   │   │   ├── coco_seq_lmdb.py
│   │   │   ├── got10k.py
│   │   │   ├── got10k_lmdb.py
│   │   │   ├── imagenetvid.py
│   │   │   ├── imagenetvid_lmdb.py
│   │   │   ├── lasot.py
│   │   │   ├── lasot_lmdb.py
│   │   │   ├── tracking_net.py
│   │   │   └── tracking_net_lmdb.py
│   │   ├── run_training.py
│   │   ├── train_script.py
│   │   ├── train_script_distill.py
│   │   └── trainers/
│   │       ├── __init__.py
│   │       ├── base_trainer.py
│   │       ├── ltr_seq_trainer.py
│   │       ├── ltr_seq_trainer_v2.py
│   │       └── ltr_trainer.py
│   ├── utils/
│   │   ├── __init__.py
│   │   ├── box_ops.py
│   │   ├── ce_utils.py
│   │   ├── focal_loss.py
│   │   ├── heapmap_utils.py
│   │   ├── image.py
│   │   ├── lmdb_utils.py
│   │   ├── merge.py
│   │   ├── misc.py
│   │   ├── tensor.py
│   │   └── variable_hook.py
│   └── vis/
│       ├── __init__.py
│       ├── plotting.py
│       ├── utils.py
│       └── visdom_cus.py
└── tracking/
    ├── _init_paths.py
    ├── analysis_results.py
    ├── analysis_results_ITP.py
    ├── convert_transt.py
    ├── create_default_local_file.py
    ├── download_pytracking_results.py
    ├── pre_read_datasets.py
    ├── test.py
    ├── test_exp.py
    └── train.py

SYMBOL INDEX (4831 symbols across 537 files)

FILE: artrackv2_mindspore/external/AR/ltr/actors/base_actor.py
  class BaseActor (line 4) | class BaseActor:
    method __init__ (line 7) | def __init__(self, net, objective):
    method __call__ (line 16) | def __call__(self, data: TensorDict):
    method to (line 28) | def to(self, device):
    method train (line 35) | def train(self, mode=True):
    method eval (line 42) | def eval(self):

FILE: artrackv2_mindspore/external/AR/ltr/actors/bbreg.py
  class AtomActor (line 4) | class AtomActor(BaseActor):
    method __call__ (line 6) | def __call__(self, data):
  class AtomBBKLActor (line 32) | class AtomBBKLActor(BaseActor):
    method __call__ (line 34) | def __call__(self, data):

FILE: artrackv2_mindspore/external/AR/ltr/actors/tracking.py
  class DiMPActor (line 5) | class DiMPActor(BaseActor):
    method __init__ (line 7) | def __init__(self, net, objective, loss_weight=None):
    method __call__ (line 13) | def __call__(self, data):
  class KLDiMPActor (line 73) | class KLDiMPActor(BaseActor):
    method __init__ (line 75) | def __init__(self, net, objective, loss_weight=None):
    method __call__ (line 81) | def __call__(self, data):

FILE: artrackv2_mindspore/external/AR/ltr/admin/environment.py
  function create_default_local_file (line 6) | def create_default_local_file():
  function env_settings (line 44) | def env_settings():

FILE: artrackv2_mindspore/external/AR/ltr/admin/loading.py
  function load_trained_network (line 10) | def load_trained_network(workspace_dir, network_path, checkpoint=None):
  function load_pretrained (line 19) | def load_pretrained(module, name, checkpoint=None, **kwargs):
  function load_network (line 34) | def load_network(network_dir=None, checkpoint=None, constructor_fun_name...
  function load_weights (line 111) | def load_weights(net, path, strict=True):
  function torch_load_legacy (line 118) | def torch_load_legacy(path):
  function _setup_legacy_env (line 133) | def _setup_legacy_env():
  function _cleanup_legacy_env (line 144) | def _cleanup_legacy_env():

FILE: artrackv2_mindspore/external/AR/ltr/admin/model_constructor.py
  function model_constructor (line 5) | def model_constructor(f):
  class NetConstructor (line 24) | class NetConstructor:
    method __init__ (line 28) | def __init__(self, fun_name, fun_module, args, kwds):
    method get (line 41) | def get(self):

FILE: artrackv2_mindspore/external/AR/ltr/admin/multigpu.py
  function is_multi_gpu (line 4) | def is_multi_gpu(net):
  class MultiGPU (line 8) | class MultiGPU(nn.DataParallel):
    method __getattr__ (line 10) | def __getattr__(self, item):

FILE: artrackv2_mindspore/external/AR/ltr/admin/settings.py
  class Settings (line 4) | class Settings:
    method __init__ (line 6) | def __init__(self):
    method set_default (line 9) | def set_default(self):

FILE: artrackv2_mindspore/external/AR/ltr/admin/stats.py
  class StatValue (line 3) | class StatValue:
    method __init__ (line 4) | def __init__(self):
    method reset (line 7) | def reset(self):
    method clear (line 10) | def clear(self):
    method update (line 14) | def update(self, val):
  class AverageMeter (line 19) | class AverageMeter(object):
    method __init__ (line 21) | def __init__(self):
    method reset (line 25) | def reset(self):
    method clear (line 31) | def clear(self):
    method update (line 35) | def update(self, val, n=1):
    method new_epoch (line 41) | def new_epoch(self):
  function topk_accuracy (line 50) | def topk_accuracy(output, target, topk=(1,)):

FILE: artrackv2_mindspore/external/AR/ltr/admin/tensorboard.py
  class TensorboardWriter (line 10) | class TensorboardWriter:
    method __init__ (line 11) | def __init__(self, directory, loader_names):
    method write_info (line 15) | def write_info(self, module_name, script_name, description):
    method write_epoch (line 22) | def write_epoch(self, stats: OrderedDict, epoch: int, ind=-1):

FILE: artrackv2_mindspore/external/AR/ltr/data/bounding_box_utils.py
  function rect_to_rel (line 4) | def rect_to_rel(bb, sz_norm=None):
  function rel_to_rect (line 21) | def rel_to_rect(bb, sz_norm=None):
  function masks_to_bboxes (line 33) | def masks_to_bboxes(mask, fmt='c'):
  function masks_to_bboxes_multi (line 70) | def masks_to_bboxes_multi(mask, ids, fmt='c'):

FILE: artrackv2_mindspore/external/AR/ltr/data/image_loader.py
  function default_image_loader (line 15) | def default_image_loader(path):
  function jpeg4py_loader (line 34) | def jpeg4py_loader(path):
  function opencv_loader (line 44) | def opencv_loader(path):
  function jpeg4py_loader_w_failsafe (line 57) | def jpeg4py_loader_w_failsafe(path):
  function opencv_seg_loader (line 73) | def opencv_seg_loader(path):
  function imread_indexed (line 83) | def imread_indexed(filename):
  function imwrite_indexed (line 92) | def imwrite_indexed(filename, array, color_palette=None):

FILE: artrackv2_mindspore/external/AR/ltr/data/loader.py
  function _check_use_shared_memory (line 9) | def _check_use_shared_memory():
  function ltr_collate (line 18) | def ltr_collate(batch):
  function ltr_collate_stack1 (line 69) | def ltr_collate_stack1(batch):
  class LTRLoader (line 120) | class LTRLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 172) | def __init__(self, name, dataset, training=True, batch_size=1, shuffle...

FILE: artrackv2_mindspore/external/AR/ltr/data/processing.py
  function stack_tensors (line 7) | def stack_tensors(x):
  class BaseProcessing (line 13) | class BaseProcessing:
    method __init__ (line 17) | def __init__(self, transform=transforms.ToTensor(), train_transform=No...
    method __call__ (line 33) | def __call__(self, data: TensorDict):
  class ATOMProcessing (line 37) | class ATOMProcessing(BaseProcessing):
    method __init__ (line 47) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 69) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 85) | def _generate_proposals(self, box):
    method __call__ (line 114) | def __call__(self, data: TensorDict):
  class KLBBregProcessing (line 157) | class KLBBregProcessing(BaseProcessing):
    method __init__ (line 162) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 184) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 200) | def _generate_proposals(self, box):
    method __call__ (line 213) | def __call__(self, data: TensorDict):
  class ATOMwKLProcessing (line 257) | class ATOMwKLProcessing(BaseProcessing):
    method __init__ (line 259) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 269) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 285) | def _generate_proposals(self, box):
    method __call__ (line 296) | def __call__(self, data: TensorDict):
  class DiMPProcessing (line 334) | class DiMPProcessing(BaseProcessing):
    method __init__ (line 347) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 378) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 394) | def _generate_proposals(self, box):
    method _generate_label_function (line 426) | def _generate_label_function(self, target_bb):
    method __call__ (line 442) | def __call__(self, data: TensorDict):
  class KLDiMPProcessing (line 491) | class KLDiMPProcessing(BaseProcessing):
    method __init__ (line 496) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 530) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 546) | def _generate_proposals(self, box):
    method _generate_label_function (line 560) | def _generate_label_function(self, target_bb):
    method _generate_label_density (line 576) | def _generate_label_density(self, target_bb):
    method __call__ (line 605) | def __call__(self, data: TensorDict):

FILE: artrackv2_mindspore/external/AR/ltr/data/processing_utils.py
  function sample_target (line 9) | def sample_target(im, target_bb, search_area_factor, output_sz=None, mas...
  function transform_image_to_crop (line 68) | def transform_image_to_crop(box_in: torch.Tensor, box_extract: torch.Ten...
  function jittered_center_crop (line 91) | def jittered_center_crop(frames, box_extract, box_gt, search_area_factor...
  function sample_target_adaptive (line 128) | def sample_target_adaptive(im, target_bb, search_area_factor, output_sz,...
  function crop_and_resize (line 240) | def crop_and_resize(im, box, crop_bb, output_sz, mask=None):
  function transform_box_to_crop (line 298) | def transform_box_to_crop(box: torch.Tensor, crop_box: torch.Tensor, cro...
  function target_image_crop (line 319) | def target_image_crop(frames, box_extract, box_gt, search_area_factor, o...
  function iou (line 371) | def iou(reference, proposals):
  function rand_uniform (line 394) | def rand_uniform(a, b, shape=1):
  function perturb_box (line 407) | def perturb_box(box, min_iou=0.5, sigma_factor=0.1):
  function gauss_1d (line 469) | def gauss_1d(sz, sigma, center, end_pad=0, density=False):
  function gauss_2d (line 477) | def gauss_2d(sz, sigma, center, end_pad=(0, 0), density=False):
  function gaussian_label_function (line 484) | def gaussian_label_function(target_bb, sigma_factor, kernel_sz, feat_sz,...
  function gauss_density_centered (line 520) | def gauss_density_centered(x, std):
  function gmm_density_centered (line 529) | def gmm_density_centered(x, std):
  function sample_gmm_centered (line 542) | def sample_gmm_centered(std, num_samples=1):
  function sample_gmm (line 564) | def sample_gmm(mean, std, num_samples=1):
  function sample_box_gmm (line 589) | def sample_box_gmm(mean_box, proposal_sigma, gt_sigma=None, num_samples=...

FILE: artrackv2_mindspore/external/AR/ltr/data/processing_utils_SE.py
  function stack_tensors (line 8) | def stack_tensors(x):
  function sample_target_SE (line 15) | def sample_target_SE(im, target_bb, search_area_factor, output_sz=None, ...
  function map_mask_back (line 66) | def map_mask_back(im, target_bb, search_area_factor, mask, mode=cv.BORDE...
  function transform_image_to_crop_SE (line 114) | def transform_image_to_crop_SE(box_in: torch.Tensor, box_extract: torch....
  function centered_crop (line 146) | def centered_crop(frames, anno, area_factor, output_sz):
  function jittered_center_crop_SE (line 162) | def jittered_center_crop_SE(frames, box_extract, box_gt, search_area_fac...
  function sample_target_nopad (line 196) | def sample_target_nopad(im, target_bb, search_area_factor, output_sz):
  function transform_box_to_crop (line 255) | def transform_box_to_crop(box: torch.Tensor, crop_box: torch.Tensor, cro...
  function jittered_center_crop_nopad (line 276) | def jittered_center_crop_nopad(frames, box_extract, box_gt, search_area_...
  function iou (line 312) | def iou(reference, proposals):
  function rand_uniform (line 335) | def rand_uniform(a, b, shape=1):
  function perturb_box (line 348) | def perturb_box(box, min_iou=0.5, sigma_factor=0.1):
  function gauss_1d (line 410) | def gauss_1d(sz, sigma, center, end_pad=0):
  function gauss_2d (line 415) | def gauss_2d(sz, sigma, center, end_pad=(0, 0)):
  function gaussian_label_function (line 422) | def gaussian_label_function(target_bb, sigma_factor, kernel_sz, feat_sz,...

FILE: artrackv2_mindspore/external/AR/ltr/data/sampler.py
  function no_processing (line 6) | def no_processing(data):
  class TrackingSampler (line 10) | class TrackingSampler(torch.utils.data.Dataset):
    method __init__ (line 25) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
    method __len__ (line 56) | def __len__(self):
    method _sample_visible_ids (line 59) | def _sample_visible_ids(self, visible, num_ids=1, min_id=None, max_id=...
    method __getitem__ (line 86) | def __getitem__(self, index):
  class DiMPSampler (line 172) | class DiMPSampler(TrackingSampler):
    method __init__ (line 175) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
  class ATOMSampler (line 182) | class ATOMSampler(TrackingSampler):
    method __init__ (line 185) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,

FILE: artrackv2_mindspore/external/AR/ltr/data/transforms.py
  class Transform (line 10) | class Transform:
    method __init__ (line 35) | def __init__(self, *transforms):
    method __call__ (line 43) | def __call__(self, **inputs):
    method _split_inputs (line 65) | def _split_inputs(self, inputs):
    method __repr__ (line 77) | def __repr__(self):
  class TransformBase (line 86) | class TransformBase:
    method __init__ (line 88) | def __init__(self):
    method __call__ (line 94) | def __call__(self, **inputs):
    method _get_image_size (line 122) | def _get_image_size(self, inputs):
    method roll (line 138) | def roll(self):
    method transform_image (line 141) | def transform_image(self, image, *rand_params):
    method transform_coords (line 145) | def transform_coords(self, coords, image_shape, *rand_params):
    method transform_bbox (line 149) | def transform_bbox(self, bbox, image_shape, *rand_params):
    method transform_mask (line 171) | def transform_mask(self, mask, *rand_params):
  class ToTensor (line 176) | class ToTensor(TransformBase):
    method transform_image (line 179) | def transform_image(self, image):
    method transfrom_mask (line 191) | def transfrom_mask(self, mask):
  class ToTensorAndJitter (line 197) | class ToTensorAndJitter(TransformBase):
    method __init__ (line 199) | def __init__(self, brightness_jitter=0.0, normalize=True):
    method roll (line 204) | def roll(self):
    method transform_image (line 207) | def transform_image(self, image, brightness_factor):
    method transform_mask (line 217) | def transform_mask(self, mask, brightness_factor):
  class Normalize (line 224) | class Normalize(TransformBase):
    method __init__ (line 226) | def __init__(self, mean, std, inplace=False):
    method transform_image (line 232) | def transform_image(self, image):
  class ToGrayscale (line 236) | class ToGrayscale(TransformBase):
    method __init__ (line 238) | def __init__(self, probability = 0.5):
    method roll (line 243) | def roll(self):
    method transform_image (line 246) | def transform_image(self, image, do_grayscale):
  class ToBGR (line 256) | class ToBGR(TransformBase):
    method transform_image (line 258) | def transform_image(self, image):
  class RandomHorizontalFlip (line 265) | class RandomHorizontalFlip(TransformBase):
    method __init__ (line 267) | def __init__(self, probability = 0.5):
    method roll (line 271) | def roll(self):
    method transform_image (line 274) | def transform_image(self, image, do_flip):
    method transform_coords (line 281) | def transform_coords(self, coords, image_shape, do_flip):
    method transform_mask (line 287) | def transform_mask(self, mask, do_flip):
  class Blur (line 295) | class Blur(TransformBase):
    method __init__ (line 297) | def __init__(self, sigma):
    method transform_image (line 308) | def transform_image(self, image):
  class RandomBlur (line 317) | class RandomBlur(TransformBase):
    method __init__ (line 319) | def __init__(self, sigma, probability=0.1):
    method roll (line 332) | def roll(self):
    method transform (line 335) | def transform(self, image, do_blur=None):
  class RandomAffine (line 350) | class RandomAffine(TransformBase):
    method __init__ (line 352) | def __init__(self, p_flip=0.0, max_rotation=0.0, max_shear=0.0, max_sc...
    method roll (line 370) | def roll(self):
    method _construct_t_mat (line 382) | def _construct_t_mat(self, image_shape, do_flip, theta, shear_values, ...
    method transform_image (line 411) | def transform_image(self, image, do_flip, theta, shear_values, scale_f...
    method transform_coords (line 422) | def transform_coords(self, coords, image_shape, do_flip, theta, shear_...
    method transform_mask (line 433) | def transform_mask(self, mask, do_flip, theta, shear_values, scale_fac...

FILE: artrackv2_mindspore/external/AR/ltr/dataset/base_image_dataset.py
  class BaseImageDataset (line 5) | class BaseImageDataset(torch.utils.data.Dataset):
    method __init__ (line 8) | def __init__(self, name, root, image_loader=jpeg4py_loader):
    method __len__ (line 22) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, index):
    method get_name (line 34) | def get_name(self):
    method get_num_images (line 42) | def get_num_images(self):
    method has_class_info (line 49) | def has_class_info(self):
    method get_class_name (line 52) | def get_class_name(self, image_id):
    method get_num_classes (line 55) | def get_num_classes(self):
    method get_class_list (line 58) | def get_class_list(self):
    method get_images_in_class (line 61) | def get_images_in_class(self, class_name):
    method has_segmentation_info (line 64) | def has_segmentation_info(self):
    method get_image_info (line 67) | def get_image_info(self, seq_id):
    method get_image (line 78) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/base_video_dataset.py
  class BaseVideoDataset (line 5) | class BaseVideoDataset(torch.utils.data.Dataset):
    method __init__ (line 8) | def __init__(self, name, root, image_loader=jpeg4py_loader):
    method __len__ (line 22) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, index):
    method is_video_sequence (line 34) | def is_video_sequence(self):
    method is_synthetic_video_dataset (line 42) | def is_synthetic_video_dataset(self):
    method get_name (line 50) | def get_name(self):
    method get_num_sequences (line 58) | def get_num_sequences(self):
    method has_class_info (line 65) | def has_class_info(self):
    method has_occlusion_info (line 68) | def has_occlusion_info(self):
    method get_num_classes (line 71) | def get_num_classes(self):
    method get_class_list (line 74) | def get_class_list(self):
    method get_sequences_in_class (line 77) | def get_sequences_in_class(self, class_name):
    method has_segmentation_info (line 80) | def has_segmentation_info(self):
    method get_sequence_info (line 83) | def get_sequence_info(self, seq_id):
    method get_frames (line 94) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/coco.py
  class MSCOCO (line 11) | class MSCOCO(BaseImageDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_image_list (line 65) | def _get_image_list(self, min_area=None):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method has_segmentation_info (line 83) | def has_segmentation_info(self):
    method get_class_list (line 86) | def get_class_list(self):
    method _build_im_per_class (line 92) | def _build_im_per_class(self):
    method get_images_in_class (line 103) | def get_images_in_class(self, class_name):
    method get_image_info (line 106) | def get_image_info(self, im_id):
    method _get_anno (line 118) | def _get_anno(self, im_id):
    method _get_image (line 123) | def _get_image(self, im_id):
    method get_meta_info (line 128) | def get_meta_info(self, im_id):
    method get_class_name (line 144) | def get_class_name(self, im_id):
    method get_image (line 148) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/coco_seq.py
  class MSCOCOSeq (line 11) | class MSCOCOSeq(BaseVideoDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_sequence_list (line 65) | def _get_sequence_list(self):
    method is_video_sequence (line 71) | def is_video_sequence(self):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method get_class_list (line 83) | def get_class_list(self):
    method has_segmentation_info (line 89) | def has_segmentation_info(self):
    method get_num_sequences (line 92) | def get_num_sequences(self):
    method _build_seq_per_class (line 95) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 106) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 109) | def get_sequence_info(self, seq_id):
    method _get_anno (line 121) | def _get_anno(self, seq_id):
    method _get_frames (line 126) | def _get_frames(self, seq_id):
    method get_meta_info (line 131) | def get_meta_info(self, seq_id):
    method get_class_name (line 148) | def get_class_name(self, seq_id):
    method get_frames (line 152) | def get_frames(self, seq_id=None, frame_ids=None, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/davis.py
  class Davis (line 8) | class Davis(VOSDatasetBase):
    method __init__ (line 19) | def __init__(self, root=None, sequences=None, version='2017', split='t...
    method _construct_sequence (line 76) | def _construct_sequence(self, sequence_info):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/ecssd.py
  class ECSSD (line 10) | class ECSSD(BaseImageDataset):
    method __init__ (line 22) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _load_dataset (line 39) | def _load_dataset(self, min_area=None):
    method get_name (line 50) | def get_name(self):
    method has_segmentation_info (line 53) | def has_segmentation_info(self):
    method get_image_info (line 56) | def get_image_info(self, im_id):
    method get_meta_info (line 67) | def get_meta_info(self, im_id):
    method get_image (line 76) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/got10k.py
  class Got10k (line 14) | class Got10k(BaseVideoDataset):
    method __init__ (line 26) | def __init__(self, root=None, image_loader=jpeg4py_loader, split=None,...
    method get_name (line 75) | def get_name(self):
    method has_class_info (line 78) | def has_class_info(self):
    method has_occlusion_info (line 81) | def has_occlusion_info(self):
    method _load_meta_info (line 84) | def _load_meta_info(self):
    method _read_meta (line 88) | def _read_meta(self, seq_path):
    method _build_seq_per_class (line 105) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 117) | def get_sequences_in_class(self, class_name):
    method _get_sequence_list (line 120) | def _get_sequence_list(self):
    method _read_bb_anno (line 126) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 131) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 146) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 149) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 159) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 162) | def _get_frame(self, seq_path, frame_id):
    method get_class_name (line 165) | def get_class_name(self, seq_id):
    method get_frames (line 170) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/hku_is.py
  class HKUIS (line 10) | class HKUIS(BaseImageDataset):
    method __init__ (line 23) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _load_dataset (line 40) | def _load_dataset(self, min_area=None):
    method get_name (line 57) | def get_name(self):
    method has_segmentation_info (line 60) | def has_segmentation_info(self):
    method get_image_info (line 63) | def get_image_info(self, im_id):
    method get_meta_info (line 73) | def get_meta_info(self, im_id):
    method get_image (line 82) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/imagenetvid.py
  function get_target_to_image_ratio (line 12) | def get_target_to_image_ratio(seq):
  class ImagenetVID (line 18) | class ImagenetVID(BaseVideoDataset):
    method __init__ (line 30) | def __init__(self, root=None, image_loader=default_image_loader, min_l...
    method get_name (line 62) | def get_name(self):
    method get_num_sequences (line 65) | def get_num_sequences(self):
    method get_sequence_info (line 68) | def get_sequence_info(self, seq_id):
    method _get_frame (line 74) | def _get_frame(self, sequence, frame_id):
    method get_frames (line 83) | def get_frames(self, seq_id, frame_ids, anno=None):
    method _process_anno (line 105) | def _process_anno(self, root):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/lasot.py
  class Lasot (line 14) | class Lasot(BaseVideoDataset):
    method __init__ (line 26) | def __init__(self, root=None, image_loader=jpeg4py_loader, vid_ids=Non...
    method _build_sequence_list (line 52) | def _build_sequence_list(self, vid_ids=None, split=None):
    method _build_class_list (line 69) | def _build_class_list(self):
    method get_name (line 80) | def get_name(self):
    method has_class_info (line 83) | def has_class_info(self):
    method has_occlusion_info (line 86) | def has_occlusion_info(self):
    method get_num_sequences (line 89) | def get_num_sequences(self):
    method get_num_classes (line 92) | def get_num_classes(self):
    method get_sequences_in_class (line 95) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 98) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 103) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 117) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 124) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 133) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 136) | def _get_frame(self, seq_path, frame_id):
    method _get_class (line 139) | def _get_class(self, seq_path):
    method get_class_name (line 143) | def get_class_name(self, seq_id):
    method get_frames (line 149) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/lvis.py
  class LVIS (line 11) | class LVIS(BaseImageDataset):
    method __init__ (line 33) | def __init__(self, root=None, image_loader=jpeg4py_loader_w_failsafe, ...
    method _get_image_list (line 62) | def _get_image_list(self, min_area=None):
    method get_num_classes (line 70) | def get_num_classes(self):
    method get_name (line 73) | def get_name(self):
    method has_class_info (line 76) | def has_class_info(self):
    method get_class_list (line 79) | def get_class_list(self):
    method has_segmentation_info (line 85) | def has_segmentation_info(self):
    method _build_im_per_class (line 88) | def _build_im_per_class(self):
    method get_images_in_class (line 99) | def get_images_in_class(self, class_name):
    method get_image_info (line 102) | def get_image_info(self, im_id):
    method _get_anno (line 114) | def _get_anno(self, im_id):
    method _get_image (line 119) | def _get_image(self, im_id):
    method get_meta_info (line 124) | def get_meta_info(self, im_id):
    method get_class_name (line 140) | def get_class_name(self, im_id):
    method get_image (line 144) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/msra10k.py
  class MSRA10k (line 10) | class MSRA10k(BaseImageDataset):
    method __init__ (line 23) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _load_dataset (line 40) | def _load_dataset(self, min_area=None):
    method get_name (line 54) | def get_name(self):
    method has_segmentation_info (line 57) | def has_segmentation_info(self):
    method get_image_info (line 60) | def get_image_info(self, im_id):
    method get_meta_info (line 70) | def get_meta_info(self, im_id):
    method get_image (line 79) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/sbd.py
  class SBD (line 12) | class SBD(BaseImageDataset):
    method __init__ (line 24) | def __init__(self, root=None, image_loader=jpeg4py_loader_w_failsafe, ...
    method _load_dataset (line 49) | def _load_dataset(self, split):
    method _get_mask_from_mat (line 62) | def _get_mask_from_mat(self, mat):
    method _construct_image_list (line 65) | def _construct_image_list(self, anno_list):
    method get_name (line 75) | def get_name(self):
    method has_segmentation_info (line 78) | def has_segmentation_info(self):
    method get_image_info (line 81) | def get_image_info(self, im_id):
    method _get_image (line 93) | def _get_image(self, im_id):
    method get_meta_info (line 99) | def get_meta_info(self, im_id):
    method get_image (line 107) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/synthetic_video.py
  class SyntheticVideo (line 6) | class SyntheticVideo(BaseVideoDataset):
    method __init__ (line 10) | def __init__(self, base_image_dataset, transform=None):
    method get_name (line 21) | def get_name(self):
    method is_video_sequence (line 24) | def is_video_sequence(self):
    method has_class_info (line 27) | def has_class_info(self):
    method has_occlusion_info (line 30) | def has_occlusion_info(self):
    method get_num_sequences (line 33) | def get_num_sequences(self):
    method get_num_classes (line 36) | def get_num_classes(self):
    method get_sequences_in_class (line 39) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 42) | def get_sequence_info(self, seq_id):
    method get_class_name (line 48) | def get_class_name(self, seq_id):
    method get_frames (line 51) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/synthetic_video_blend.py
  class SyntheticVideoBlend (line 8) | class SyntheticVideoBlend(BaseVideoDataset):
    method __init__ (line 13) | def __init__(self, foreground_image_dataset, background_image_dataset,...
    method get_name (line 33) | def get_name(self):
    method is_video_sequence (line 36) | def is_video_sequence(self):
    method has_class_info (line 39) | def has_class_info(self):
    method has_occlusion_info (line 42) | def has_occlusion_info(self):
    method get_num_sequences (line 45) | def get_num_sequences(self):
    method get_num_classes (line 48) | def get_num_classes(self):
    method get_sequences_in_class (line 51) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 54) | def get_sequence_info(self, seq_id):
    method get_class_name (line 60) | def get_class_name(self, seq_id):
    method _paste_target (line 63) | def _paste_target(self, fg_image, fg_box, fg_mask, bg_image, paste_loc):
    method get_frames (line 100) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/tracking_net.py
  function list_sequences (line 14) | def list_sequences(root, set_ids):
  class TrackingNet (line 35) | class TrackingNet(BaseVideoDataset):
    method __init__ (line 46) | def __init__(self, root=None, image_loader=jpeg4py_loader, set_ids=Non...
    method _load_class_info (line 77) | def _load_class_info(self):
    method get_name (line 94) | def get_name(self):
    method has_class_info (line 97) | def has_class_info(self):
    method get_sequences_in_class (line 100) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 103) | def _read_bb_anno(self, seq_id):
    method get_sequence_info (line 111) | def get_sequence_info(self, seq_id):
    method _get_frame (line 118) | def _get_frame(self, seq_id, frame_id):
    method _get_class (line 124) | def _get_class(self, seq_id):
    method get_class_name (line 128) | def get_class_name(self, seq_id):
    method get_frames (line 133) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/vos_base.py
  class VOSMeta (line 13) | class VOSMeta:
    method __init__ (line 14) | def __init__(self, data=None, filename=None):
    method save (line 22) | def save(self, gen_meta: Path):
    method load (line 26) | def load(self, gen_meta: Path):
    method generate (line 34) | def generate(cls, dset_name: str, dset_images_path: Path, dset_annos_p...
    method _mask_to_bbox (line 108) | def _mask_to_bbox(mask: np.ndarray):
    method _transpose_nested_dict (line 122) | def _transpose_nested_dict(d):
    method select_split (line 130) | def select_split(self, dataset_name, split):
    method get_sequence_names (line 138) | def get_sequence_names(self):
    method get_shape (line 141) | def get_shape(self, seq_name):
    method get_obj_ids (line 146) | def get_obj_ids(self, seq_name):
    method get_frame_names (line 150) | def get_frame_names(self, seq_name):
    method enable_all_frames (line 154) | def enable_all_frames(self, dset_images_path):
    method get_aspect_ratio (line 179) | def get_aspect_ratio(self, seq_name):
    method get_obj_sizes_per_frame (line 184) | def get_obj_sizes_per_frame(self, seq_name):
    method get_bboxes_per_frame (line 188) | def get_bboxes_per_frame(self, seq_name):
    method get_obj_sizes_per_object (line 192) | def get_obj_sizes_per_object(self, seq_name):
    method get_bboxes_per_object (line 196) | def get_bboxes_per_object(self, seq_name):
    method generate_datasets_meta (line 201) | def generate_datasets_meta(src, dst=Path("~/vosdataset_meta").expandus...
  class VOSDatasetBase (line 205) | class VOSDatasetBase(BaseVideoDataset):
    method __init__ (line 209) | def __init__(self, name: str, root: Path, version=None, split='train',
    method _load_image (line 234) | def _load_image(self, path):
    method _load_anno (line 241) | def _load_anno(path):
    method get_num_sequences (line 248) | def get_num_sequences(self):
    method get_sequence_info (line 251) | def get_sequence_info(self, sample_id):
    method get_paths_and_bboxes (line 286) | def get_paths_and_bboxes(self, sequence_info):
    method _construct_sequence (line 308) | def _construct_sequence(self, sequence_info):
    method get_sequence_list (line 311) | def get_sequence_list(self):
    method __len__ (line 317) | def __len__(self):
    method _get_image_path (line 320) | def _get_image_path(self, meta, frame_id):
    method _get_anno_path (line 323) | def _get_anno_path(self, meta, frame_id):
    method get_frames (line 326) | def get_frames(self, sample_id, frame_ids, anno=None):
    method get_name (line 379) | def get_name(self):
    method has_class_info (line 382) | def has_class_info(self):
    method has_occlusion_info (line 385) | def has_occlusion_info(self):
    method get_num_classes (line 388) | def get_num_classes(self):
    method get_class_list (line 391) | def get_class_list(self):
    method get_sequences_in_class (line 394) | def get_sequences_in_class(self, class_name):
    method has_segmentation_info (line 397) | def has_segmentation_info(self):

FILE: artrackv2_mindspore/external/AR/ltr/dataset/youtubevos.py
  class YouTubeVOSMeta (line 10) | class YouTubeVOSMeta:
    method __init__ (line 32) | def __init__(self, dset_split_path):
    method sequences (line 35) | def sequences(self):
    method seq_frames (line 38) | def seq_frames(self, seq_name):
    method object_ids (line 46) | def object_ids(self, seq_name):
    method object_category (line 50) | def object_category(self, seq_name, obj_id):
    method object_frames (line 53) | def object_frames(self, seq_name, obj_id):
    method object_first_frame (line 56) | def object_first_frame(self, seq_name, obj_id):
  class YouTubeVOS (line 60) | class YouTubeVOS(VOSDatasetBase):
    method __init__ (line 72) | def __init__(self, root=None, version='2019', split='train', cleanup=N...
    method _construct_sequence (line 168) | def _construct_sequence(self, sequence_info):

FILE: artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/functional.py
  function _import_prroi_pooling (line 21) | def _import_prroi_pooling():
  class PrRoIPool2DFunction (line 41) | class PrRoIPool2DFunction(ag.Function):
    method forward (line 43) | def forward(ctx, features, rois, pooled_height, pooled_width, spatial_...
    method backward (line 68) | def backward(ctx, grad_output):

FILE: artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/prroi_pool.py
  class PrRoIPool2D (line 19) | class PrRoIPool2D(nn.Module):
    method __init__ (line 20) | def __init__(self, pooled_height, pooled_width, spatial_scale):
    method forward (line 27) | def forward(self, features, rois):
    method extra_repr (line 30) | def extra_repr(self):

FILE: artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c
  function output (line 28) | auto output = at::zeros({nr_rois, nr_channels, pooled_height, pooled_wid...

FILE: artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/tests/test_prroi_pooling2d.py
  class TestPrRoIPool2D (line 20) | class TestPrRoIPool2D(TorchTestCase):
    method test_forward (line 21) | def test_forward(self):
    method test_backward_shapeonly (line 37) | def test_backward_shapeonly(self):

FILE: artrackv2_mindspore/external/AR/ltr/models/AR_seg_mask/AR_seg_mask.py
  class ARnet_seg_mask (line 14) | class ARnet_seg_mask(nn.Module):
    method __init__ (line 16) | def __init__(self, feature_extractor, neck_module, head_module, used_l...
    method forward (line 38) | def forward(self, train_imgs, test_imgs, train_bb, mode='train'):
    method forward_ref (line 47) | def forward_ref(self, train_imgs, train_bb):
    method forward_test (line 63) | def forward_test(self, test_imgs, mode='train'):
    method extract_backbone_features (line 84) | def extract_backbone_features(self, im, layers=None):
    method extract_features (line 89) | def extract_features(self, im, layers):
  function ARnet_seg_mask_resnet50 (line 95) | def ARnet_seg_mask_resnet50(backbone_pretrained=True,used_layers=('layer...

FILE: artrackv2_mindspore/external/AR/ltr/models/backbone/base.py
  class Backbone (line 5) | class Backbone(nn.Module):
    method __init__ (line 10) | def __init__(self, frozen_layers=()):
    method train (line 23) | def train(self, mode=True):
    method _set_frozen_to_eval (line 32) | def _set_frozen_to_eval(self):
    method _set_frozen_to_nograd (line 40) | def _set_frozen_to_nograd(self):

FILE: artrackv2_mindspore/external/AR/ltr/models/backbone/resnet.py
  function conv3x3 (line 9) | def conv3x3(in_planes, out_planes, stride=1, dilation=1):
  class BasicBlock (line 15) | class BasicBlock(nn.Module):
    method __init__ (line 18) | def __init__(self, inplanes, planes, stride=1, downsample=None, dilati...
    method forward (line 33) | def forward(self, x):
  class Bottleneck (line 56) | class Bottleneck(nn.Module):
    method __init__ (line 59) | def __init__(self, inplanes, planes, stride=1, downsample=None, dilati...
    method forward (line 72) | def forward(self, x):
  class ResNet (line 95) | class ResNet(Backbone):
    method __init__ (line 97) | def __init__(self, block, layers, output_layers, num_classes=1000, inp...
    method out_feature_strides (line 141) | def out_feature_strides(self, layer=None):
    method out_feature_channels (line 147) | def out_feature_channels(self, layer=None):
    method _make_layer (line 153) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1):
    method _add_output_and_check (line 170) | def _add_output_and_check(self, name, x, outputs, output_layers):
    method forward (line 175) | def forward(self, x, output_layers=None):
  function resnet_baby (line 224) | def resnet_baby(output_layers=None, pretrained=False, inplanes=16, **kwa...
  function resnet18 (line 242) | def resnet18(output_layers=None, pretrained=False, **kwargs):
  function resnet50 (line 260) | def resnet50(output_layers=None, pretrained=False, **kwargs):

FILE: artrackv2_mindspore/external/AR/ltr/models/backbone/resnet18_vggm.py
  class SpatialCrossMapLRN (line 9) | class SpatialCrossMapLRN(nn.Module):
    method __init__ (line 10) | def __init__(self, local_size=1, alpha=1.0, beta=0.75, k=1, ACROSS_CHA...
    method forward (line 25) | def forward(self, x):
  class ResNetVGGm1 (line 38) | class ResNetVGGm1(Backbone):
    method __init__ (line 40) | def __init__(self, block, layers, output_layers, num_classes=1000, fro...
    method _make_layer (line 67) | def _make_layer(self, block, planes, blocks, stride=1):
    method _add_output_and_check (line 85) | def _add_output_and_check(self, name, x, outputs, output_layers):
    method forward (line 91) | def forward(self, x, output_layers=None):
  function resnet18_vggmconv1 (line 144) | def resnet18_vggmconv1(output_layers=None, path=None, **kwargs):

FILE: artrackv2_mindspore/external/AR/ltr/models/backbone/resnet_seg.py
  function conv3x3 (line 10) | def conv3x3(in_planes, out_planes, stride=1, dilation=1):
  class BasicBlock (line 16) | class BasicBlock(nn.Module):
    method __init__ (line 19) | def __init__(self, inplanes, planes, stride=1, downsample=None, dilati...
    method forward (line 29) | def forward(self, x):
  class Bottleneck (line 48) | class Bottleneck(nn.Module):
    method __init__ (line 51) | def __init__(self, inplanes, planes, stride=1, downsample=None, dilati...
    method forward (line 64) | def forward(self, x):
  class ResNet (line 87) | class ResNet(nn.Module):
    method __init__ (line 89) | def __init__(self, block, layers, output_layers, num_classes=1000, inp...
    method _make_layer (line 121) | def _make_layer(self, block, planes, blocks, stride=1, dilation=1):
    method _add_output_and_check (line 138) | def _add_output_and_check(self, name, x, outputs, output_layers):
    method forward (line 143) | def forward(self, x, output_layers=None):
    method get_out_channels (line 190) | def get_out_channels(self):
  function resnet18 (line 194) | def resnet18(output_layers=None, pretrained=False, dilation_factor=1):
  function resnet50 (line 212) | def resnet50(output_layers=None, pretrained=False, dilation_factor=1):
  function resnet101 (line 229) | def resnet101(output_layers=None, pretrained=False, dilation_factor=1):

FILE: artrackv2_mindspore/external/AR/ltr/models/bbreg/atom.py
  class ATOMnet (line 7) | class ATOMnet(nn.Module):
    method __init__ (line 9) | def __init__(self, feature_extractor, bb_regressor, bb_regressor_layer...
    method forward (line 28) | def forward(self, train_imgs, test_imgs, train_bb, test_proposals):
    method extract_backbone_features (line 50) | def extract_backbone_features(self, im, layers=None):
    method extract_features (line 55) | def extract_features(self, im, layers):
  function atom_resnet18 (line 61) | def atom_resnet18(iou_input_dim=(256,256), iou_inter_dim=(256,256), back...
  function atom_resnet50 (line 75) | def atom_resnet50(iou_input_dim=(256,256), iou_inter_dim=(256,256), back...

FILE: artrackv2_mindspore/external/AR/ltr/models/bbreg/atom_iou_net.py
  function conv (line 7) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  class AtomIoUNet (line 15) | class AtomIoUNet(nn.Module):
    method __init__ (line 23) | def __init__(self, input_dim=(128,256), pred_input_dim=(256,256), pred...
    method forward (line 66) | def forward(self, feat1, feat2, bb1, proposals2):
    method predict_iou (line 96) | def predict_iou(self, modulation, feat, proposals):
    method get_modulation (line 138) | def get_modulation(self, feat, bb):
    method get_iou_feat (line 172) | def get_iou_feat(self, feat2):

FILE: artrackv2_mindspore/external/AR/ltr/models/head/seg_network.py
  class TSE (line 7) | class TSE(nn.Module):
    method __init__ (line 9) | def __init__(self, fc, ic, oc):
    method forward (line 16) | def forward(self, ft, score, x=None):
  class CAB (line 24) | class CAB(nn.Module):
    method __init__ (line 26) | def __init__(self, oc, deepest):
    method forward (line 32) | def forward(self, deeper, shallower, att_vec=None):
  class RRB (line 47) | class RRB(nn.Module):
    method __init__ (line 49) | def __init__(self, oc, use_bn=False):
    method forward (line 57) | def forward(self, x):
  class Upsampler (line 62) | class Upsampler(nn.Module):
    method __init__ (line 64) | def __init__(self, in_channels=64):
    method forward (line 70) | def forward(self, x, image_size):
  class PyrUpBicubic2d (line 79) | class PyrUpBicubic2d(nn.Module):
    method __init__ (line 81) | def __init__(self, channels):
    method forward (line 108) | def forward(self, input):
  class BackwardCompatibleUpsampler (line 133) | class BackwardCompatibleUpsampler(nn.Module):
    method __init__ (line 136) | def __init__(self, in_channels=64):
    method forward (line 144) | def forward(self, x, image_size):
  class SegNetwork (line 153) | class SegNetwork(nn.Module):
    method __init__ (line 155) | def __init__(self, in_channels=1, out_channels=32, ft_channels=None, u...
    method forward (line 180) | def forward(self, scores, features, image_size):

FILE: artrackv2_mindspore/external/AR/ltr/models/head/utils.py
  function text_bargraph (line 9) | def text_bargraph(values):
  class ModuleWrapper (line 25) | class ModuleWrapper:
    method __init__ (line 31) | def __init__(self, wrapped_module):
    method __getattr__ (line 34) | def __getattr__(self, attr):
    method __call__ (line 48) | def __call__(self, *args, **kwargs):
  function conv (line 52) | def conv(ic, oc, ksize, bias=True, dilation=1, stride=1):
  function relu (line 56) | def relu(negative_slope=0.0, inplace=False):
  function interpolate (line 60) | def interpolate(t, sz):
  function adaptive_cat (line 65) | def adaptive_cat(seq, dim=0, ref_tensor=0):
  function get_out_channels (line 71) | def get_out_channels(layer):
  function is_finite (line 89) | def is_finite(t):
  class AverageMeter (line 93) | class AverageMeter:
    method __init__ (line 96) | def __init__(self):
    method reset (line 103) | def reset(self):
    method update (line 106) | def update(self, val, n=1):
    method update_multi (line 113) | def update_multi(self, val):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/activation.py
  function softmax_reg (line 7) | def softmax_reg(x: torch.Tensor, dim, reg=None):
  class MLU (line 20) | class MLU(nn.Module):
    method __init__ (line 23) | def __init__(self, min_val, inplace=False):
    method forward (line 28) | def forward(self, input):
  class LeakyReluPar (line 32) | class LeakyReluPar(nn.Module):
    method forward (line 36) | def forward(self, x, a):
  class LeakyReluParDeriv (line 39) | class LeakyReluParDeriv(nn.Module):
    method forward (line 43) | def forward(self, x, a):
  class BentIdentPar (line 47) | class BentIdentPar(nn.Module):
    method __init__ (line 50) | def __init__(self, b=1.0):
    method forward (line 54) | def forward(self, x, a):
  class BentIdentParDeriv (line 58) | class BentIdentParDeriv(nn.Module):
    method __init__ (line 61) | def __init__(self, b=1.0):
    method forward (line 65) | def forward(self, x, a):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/blocks.py
  function conv_block (line 4) | def conv_block(in_planes, out_planes, kernel_size=3, stride=1, padding=1...
  class LinearBlock (line 23) | class LinearBlock(nn.Module):
    method __init__ (line 24) | def __init__(self, in_planes, out_planes, input_sz, bias=True, batch_n...
    method forward (line 30) | def forward(self, x):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/distance.py
  class DistanceMap (line 6) | class DistanceMap(nn.Module):
    method __init__ (line 12) | def __init__(self, num_bins, bin_displacement=1.0):
    method forward (line 17) | def forward(self, center, output_sz):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/filter.py
  function apply_filter (line 5) | def apply_filter(feat, filter, dilation_factors=None):
  function apply_feat_transpose (line 57) | def apply_feat_transpose(feat, input, filter_ksz, training=True, groups=1):
  function _apply_feat_transpose_v1 (line 76) | def _apply_feat_transpose_v1(feat, input, filter_ksz):
  function _apply_feat_transpose_v2 (line 95) | def _apply_feat_transpose_v2(feat, input, filter_ksz):
  function _apply_feat_transpose_v3 (line 124) | def _apply_feat_transpose_v3(feat, input, filter_ksz):
  function _apply_feat_transpose_v4 (line 151) | def _apply_feat_transpose_v4(feat, input, filter_ksz):
  function filter_gradient (line 169) | def filter_gradient(feat, filter, label=None, training=True):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/normalization.py
  class InstanceL2Norm (line 6) | class InstanceL2Norm(nn.Module):
    method __init__ (line 9) | def __init__(self, size_average=True, eps=1e-5, scale=1.0):
    method forward (line 15) | def forward(self, input):

FILE: artrackv2_mindspore/external/AR/ltr/models/layers/transform.py
  function interpolate (line 7) | def interpolate(x, sz):
  class InterpCat (line 13) | class InterpCat(nn.Module):
    method forward (line 16) | def forward(self, input):

FILE: artrackv2_mindspore/external/AR/ltr/models/loss/kl_regression.py
  class KLRegression (line 7) | class KLRegression(nn.Module):
    method __init__ (line 11) | def __init__(self, eps=0.0):
    method forward (line 15) | def forward(self, scores, sample_density, gt_density, mc_dim=-1):
  class MLRegression (line 30) | class MLRegression(nn.Module):
    method __init__ (line 34) | def __init__(self, eps=0.0):
    method forward (line 38) | def forward(self, scores, sample_density, gt_density=None, mc_dim=-1):
  class KLRegressionGrid (line 55) | class KLRegressionGrid(nn.Module):
    method forward (line 59) | def forward(self, scores, gt_density, grid_dim=-1, grid_scale=1.0):

FILE: artrackv2_mindspore/external/AR/ltr/models/loss/target_classification.py
  class LBHinge (line 6) | class LBHinge(nn.Module):
    method __init__ (line 15) | def __init__(self, error_metric=nn.MSELoss(), threshold=None, clip=None):
    method forward (line 21) | def forward(self, prediction, label, target_bb=None):

FILE: artrackv2_mindspore/external/AR/ltr/models/meta/steepestdescent.py
  class GNSteepestDescent (line 8) | class GNSteepestDescent(nn.Module):
    method __init__ (line 10) | def __init__(self, residual_module, num_iter=1, compute_losses=False, ...
    method _sqr_norm (line 24) | def _sqr_norm(self, x: TensorList, batch_dim=0):
    method _compute_loss (line 29) | def _compute_loss(self, res):
    method forward (line 33) | def forward(self, meta_parameter: TensorList, num_iter=None, *args, **...

FILE: artrackv2_mindspore/external/AR/ltr/models/neck/CorrNL.py
  class CorrNL (line 7) | class CorrNL(nn.Module):
    method __init__ (line 15) | def __init__(self, pool_size=8, use_NL=True):
    method forward (line 22) | def forward(self, feat1, feat2, bb1):
    method get_ref_kernel (line 58) | def get_ref_kernel(self, feat1, bb1):
    method fuse_feat (line 80) | def fuse_feat(self, feat2):
    method corr_fun (line 98) | def corr_fun(self, Kernel_tmp, Feature, KERs=None):

FILE: artrackv2_mindspore/external/AR/ltr/models/neck/neck_utils.py
  function conv (line 5) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  class SEModule (line 13) | class SEModule(nn.Module):
    method __init__ (line 15) | def __init__(self, channels, reduction=4):
    method forward (line 25) | def forward(self, x):
  class _NonLocalBlockND (line 34) | class _NonLocalBlockND(nn.Module):
    method __init__ (line 35) | def __init__(self, in_channels, inter_channels=None, dimension=3, sub_...
    method forward (line 97) | def forward(self, x, return_nl_map=False):
  class NONLocalBlock2D (line 125) | class NONLocalBlock2D(_NonLocalBlockND):
    method __init__ (line 126) | def __init__(self, in_channels, inter_channels=None, sub_sample=True, ...

FILE: artrackv2_mindspore/external/AR/ltr/models/target_classifier/features.py
  function residual_basic_block (line 9) | def residual_basic_block(feature_dim=256, num_blocks=1, l2norm=True, fin...
  function residual_basic_block_pool (line 31) | def residual_basic_block_pool(feature_dim=256, num_blocks=1, l2norm=True...
  function residual_bottleneck (line 50) | def residual_bottleneck(feature_dim=256, num_blocks=1, l2norm=True, fina...

FILE: artrackv2_mindspore/external/AR/ltr/models/target_classifier/initializer.py
  class FilterPool (line 9) | class FilterPool(nn.Module):
    method __init__ (line 16) | def __init__(self, filter_size=1, feature_stride=16, pool_square=False):
    method forward (line 21) | def forward(self, feat, bb):
  class FilterInitializer (line 49) | class FilterInitializer(nn.Module):
    method __init__ (line 60) | def __init__(self, filter_size=1, feature_dim=256, feature_stride=16, ...
    method forward (line 92) | def forward(self, feat, bb):
  class FilterInitializerLinear (line 118) | class FilterInitializerLinear(nn.Module):
    method __init__ (line 128) | def __init__(self, filter_size=1, feature_dim=256, feature_stride=16, ...
    method forward (line 151) | def forward(self, feat, bb):
  class FilterInitializerZero (line 177) | class FilterInitializerZero(nn.Module):
    method __init__ (line 183) | def __init__(self, filter_size=1, feature_dim=256):
    method forward (line 188) | def forward(self, feat, bb):
  class FilterInitializerSiamese (line 202) | class FilterInitializerSiamese(nn.Module):
    method __init__ (line 210) | def __init__(self, filter_size=1, feature_stride=16, pool_square=False...
    method forward (line 228) | def forward(self, feat, bb):

FILE: artrackv2_mindspore/external/AR/ltr/models/target_classifier/linear_filter.py
  class LinearFilter (line 6) | class LinearFilter(nn.Module):
    method __init__ (line 14) | def __init__(self, filter_size, filter_initializer, filter_optimizer=N...
    method forward (line 35) | def forward(self, train_feat, test_feat, train_bb, *args, **kwargs):
    method extract_classification_feat (line 68) | def extract_classification_feat(self, feat, num_sequences=None):
    method classify (line 78) | def classify(self, weights, feat):
    method get_filter (line 85) | def get_filter(self, feat, bb, *args, **kwargs):
    method train_classifier (line 107) | def train_classifier(self, backbone_feat, bb):
    method track_frame (line 120) | def track_frame(self, filter_weights, backbone_feat):

FILE: artrackv2_mindspore/external/AR/ltr/models/target_classifier/optimizer.py
  class DiMPSteepestDescentGN (line 11) | class DiMPSteepestDescentGN(nn.Module):
    method __init__ (line 31) | def __init__(self, num_iter=1, feat_stride=16, init_step_length=1.0,
    method forward (line 85) | def forward(self, weights, feat, bb, sample_weight=None, num_iter=None...
  class DiMPL2SteepestDescentGN (line 174) | class DiMPL2SteepestDescentGN(nn.Module):
    method __init__ (line 187) | def __init__(self, num_iter=1, feat_stride=16, init_step_length=1.0, g...
    method get_label (line 201) | def get_label(self, center, output_sz):
    method forward (line 211) | def forward(self, weights, feat, bb, sample_weight=None, num_iter=None...
  class PrDiMPSteepestDescentNewton (line 294) | class PrDiMPSteepestDescentNewton(nn.Module):
    method __init__ (line 312) | def __init__(self, num_iter=1, feat_stride=16, init_step_length=1.0,
    method get_label_density (line 331) | def get_label_density(self, center, output_sz):
    method forward (line 355) | def forward(self, weights, feat, bb, sample_weight=None, num_iter=None...

FILE: artrackv2_mindspore/external/AR/ltr/models/target_classifier/residual_modules.py
  class LinearFilterLearnGen (line 10) | class LinearFilterLearnGen(nn.Module):
    method __init__ (line 11) | def __init__(self, feat_stride=16, init_filter_reg=1e-2, init_gauss_si...
    method forward (line 52) | def forward(self, meta_parameter: TensorList, feat, bb, sample_weight=...

FILE: artrackv2_mindspore/external/AR/ltr/models/tracking/dimpnet.py
  class DiMPnet (line 15) | class DiMPnet(nn.Module):
    method __init__ (line 24) | def __init__(self, feature_extractor, classifier, bb_regressor, classi...
    method forward (line 35) | def forward(self, train_imgs, test_imgs, train_bb, test_proposals, *ar...
    method get_backbone_clf_feat (line 70) | def get_backbone_clf_feat(self, backbone_feat):
    method get_backbone_bbreg_feat (line 76) | def get_backbone_bbreg_feat(self, backbone_feat):
    method extract_classification_feat (line 79) | def extract_classification_feat(self, backbone_feat):
    method extract_backbone_features (line 82) | def extract_backbone_features(self, im, layers=None):
    method extract_features (line 87) | def extract_features(self, im, layers=None):
  function dimpnet18 (line 100) | def dimpnet18(filter_size=1, optim_iter=5, optim_init_step=1.0, optim_in...
  function dimpnet50 (line 146) | def dimpnet50(filter_size=1, optim_iter=5, optim_init_step=1.0, optim_in...
  function L2dimpnet18 (line 202) | def L2dimpnet18(filter_size=1, optim_iter=5, optim_init_step=1.0, optim_...
  function klcedimpnet18 (line 242) | def klcedimpnet18(filter_size=1, optim_iter=5, optim_init_step=1.0, opti...
  function klcedimpnet50 (line 295) | def klcedimpnet50(filter_size=1, optim_iter=5, optim_init_step=1.0, opti...

FILE: artrackv2_mindspore/external/AR/ltr/run_training.py
  function run_training (line 16) | def run_training(train_module, train_name, cudnn_benchmark=True):
  function main (line 42) | def main():

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom.py
  function run (line 11) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_gmm_sampl.py
  function run (line 11) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_paper.py
  function run (line 11) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_prob_ml.py
  function run (line 11) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/dimp/dimp18.py
  function run (line 13) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/dimp/dimp50.py
  function run (line 13) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/dimp/prdimp18.py
  function run (line 13) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/dimp/prdimp50.py
  function run (line 13) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/train_settings/dimp/super_dimp.py
  function run (line 13) | def run(settings):

FILE: artrackv2_mindspore/external/AR/ltr/trainers/base_trainer.py
  class BaseTrainer (line 8) | class BaseTrainer:
    method __init__ (line 12) | def __init__(self, actor, loaders, optimizer, settings, lr_scheduler=N...
    method update_settings (line 38) | def update_settings(self, settings=None):
    method train (line 52) | def train(self, max_epochs, load_latest=False, fail_safe=True):
    method train_epoch (line 91) | def train_epoch(self):
    method save_checkpoint (line 95) | def save_checkpoint(self):
    method load_checkpoint (line 129) | def load_checkpoint(self, checkpoint = None, fields = None, ignore_fie...

FILE: artrackv2_mindspore/external/AR/ltr/trainers/ltr_trainer.py
  class LTRTrainer (line 10) | class LTRTrainer(BaseTrainer):
    method __init__ (line 11) | def __init__(self, actor, loaders, optimizer, settings, lr_scheduler=N...
    method _set_default_settings (line 34) | def _set_default_settings(self):
    method cycle_dataset (line 44) | def cycle_dataset(self, loader):
    method train_epoch (line 76) | def train_epoch(self):
    method _init_timing (line 85) | def _init_timing(self):
    method _update_stats (line 90) | def _update_stats(self, new_stats: OrderedDict, batch_size, loader):
    method _print_stats (line 100) | def _print_stats(self, i, loader, batch_size):
    method _stats_new_epoch (line 114) | def _stats_new_epoch(self):
    method _write_tensorboard (line 132) | def _write_tensorboard(self):

FILE: artrackv2_mindspore/external/AR/pytracking/ARcm_seg.py
  function mask_torch2numpy (line 14) | def mask_torch2numpy(Pmask):
  class ARcm_seg (line 19) | class ARcm_seg(object):
    method __init__ (line 20) | def __init__(self, refine_net_dir, search_factor=2.0, input_sz=256):
    method initialize (line 27) | def initialize(self, frame1, bbox1):
    method get_mask (line 45) | def get_mask(self, Cframe, Cbbox, dtm=None, vis=False):
    method get_network (line 70) | def get_network(self,checkpoint_dir):
    method img_preprocess (line 76) | def img_preprocess(self,img_arr):
    method gt_preprocess (line 87) | def gt_preprocess(self,gt_arr):
  function add_frame_mask (line 95) | def add_frame_mask(frame, mask, threshold=0.5):
  function add_frame_bbox (line 103) | def add_frame_bbox(frame, refined_box, color):

FILE: artrackv2_mindspore/external/AR/pytracking/VOT/vot.py
  class VOT (line 25) | class VOT(object):
    method __init__ (line 27) | def __init__(self, region_format, channels=None):
    method region (line 59) | def region(self):
    method report (line 70) | def report(self, region, confidence = None):
    method frame (line 87) | def frame(self):
    method quit (line 110) | def quit(self):
    method __del__ (line 114) | def __del__(self):

FILE: artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/dimp_alpha_seg_class.py
  class DIMP_ALPHA (line 22) | class DIMP_ALPHA(object):
    method __init__ (line 23) | def __init__(self, tracker_name='dimp', para_name='dimp50_vot19',
    method initialize (line 41) | def initialize(self, img_RGB, mask):
    method track (line 53) | def track(self, img_RGB):
  function run_vot_exp (line 80) | def run_vot_exp(tracker_name, para_name, refine_model_name, threshold, V...

FILE: artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/mixformer_alpha_seg_class.py
  class MIXFORMER_ALPHA_SEG (line 19) | class MIXFORMER_ALPHA_SEG(object):
    method __init__ (line 20) | def __init__(self, tracker,
    method initialize (line 32) | def initialize(self, image, mask):
    method track (line 45) | def track(self, img_RGB):
  function make_full_size (line 56) | def make_full_size(x, output_sz):

FILE: artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/mixformer_large_alpha_seg_class.py
  class MIXFORMER_ALPHA_SEG (line 19) | class MIXFORMER_ALPHA_SEG(object):
    method __init__ (line 20) | def __init__(self, tracker,
    method initialize (line 32) | def initialize(self, image, mask):
    method track (line 45) | def track(self, img_RGB):
  function make_full_size (line 56) | def make_full_size(x, output_sz):

FILE: artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/vot.py
  class VOT (line 22) | class VOT(object):
    method __init__ (line 24) | def __init__(self, region_format, channels=None):
    method region (line 58) | def region(self):
    method report (line 68) | def report(self, region, confidence = None):
    method frame (line 86) | def frame(self):
    method quit (line 108) | def quit(self):
    method __del__ (line 112) | def __del__(self):

FILE: artrackv2_mindspore/external/AR/pytracking/analysis/evaluate_vos.py
  function evaluate_sequence (line 14) | def evaluate_sequence(seq_name, segmentations, annotations, object_info,...
  function evaluate_dataset (line 47) | def evaluate_dataset(results_path, dset_name, measure='J', to_file=True,...
  function evaluate_vos (line 140) | def evaluate_vos(trackers, dataset='yt2019_jjval', force=False):

FILE: artrackv2_mindspore/external/AR/pytracking/analysis/extract_results.py
  function calc_err_center (line 17) | def calc_err_center(pred_bb, anno_bb, normalized=False):
  function calc_iou_overlap (line 29) | def calc_iou_overlap(pred_bb, anno_bb):
  function calc_seq_err_robust (line 41) | def calc_seq_err_robust(pred_bb, anno_bb, dataset, target_visible=None):
  function extract_results (line 103) | def extract_results(trackers, dataset, report_name, skip_missing_seq=Fal...

FILE: artrackv2_mindspore/external/AR/pytracking/analysis/playback_results.py
  class Display (line 19) | class Display:
    method __init__ (line 20) | def __init__(self, sequence_length, plot_draw_styles, sequence_name):
    method key_callback_fn (line 34) | def key_callback_fn(self, event):
    method _get_speed (line 68) | def _get_speed(self):
    method step (line 77) | def step(self):
    method show (line 86) | def show(self, image, bb_list, trackers, gt=None):
  function read_image (line 118) | def read_image(image_file: str):
  function _get_display_name (line 123) | def _get_display_name(tracker):
  function playback_results (line 133) | def playback_results(trackers, sequence):

FILE: artrackv2_mindspore/external/AR/pytracking/analysis/plot_results.py
  function get_plot_draw_styles (line 12) | def get_plot_draw_styles():
  function check_eval_data_is_valid (line 34) | def check_eval_data_is_valid(eval_data, trackers, dataset):
  function merge_multiple_runs (line 45) | def merge_multiple_runs(eval_data):
  function get_tracker_display_name (line 89) | def get_tracker_display_name(tracker):
  function plot_draw_save (line 102) | def plot_draw_save(y, x, scores, trackers, plot_draw_styles, result_plot...
  function check_and_load_precomputed_results (line 160) | def check_and_load_precomputed_results(trackers, dataset, report_name, f...
  function get_auc_curve (line 187) | def get_auc_curve(ave_success_rate_plot_overlap, valid_sequence):
  function get_prec_curve (line 195) | def get_prec_curve(ave_success_rate_plot_center, valid_sequence):
  function plot_results (line 203) | def plot_results(trackers, dataset, report_name, merge_results=False,
  function generate_formatted_report (line 280) | def generate_formatted_report(row_labels, scores, table_name=''):
  function print_results (line 306) | def print_results(trackers, dataset, report_name, merge_results=False,
  function plot_got_success (line 364) | def plot_got_success(trackers, report_name):
  function print_per_sequence_results (line 425) | def print_per_sequence_results(trackers, dataset, report_name, merge_res...

FILE: artrackv2_mindspore/external/AR/pytracking/analysis/vos_utils.py
  function text_bargraph (line 7) | def text_bargraph(values):
  function davis_jaccard_measure (line 34) | def davis_jaccard_measure(fg_mask, gt_mask):
  function davis_jaccard_measure_torch (line 52) | def davis_jaccard_measure_torch(fg_mask, gt_mask):
  function davis_f_measure (line 70) | def davis_f_measure(foreground_mask, gt_mask, bound_th=0.008):
  function seg2bmap (line 128) | def seg2bmap(seg, width=None, height=None):
  function nanmean (line 189) | def nanmean(*args, **kwargs):
  function mean (line 195) | def mean(X):
  function recall (line 202) | def recall(X, threshold=0.5):
  function decay (line 213) | def decay(X, n_bins=4):
  function std (line 229) | def std(X):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/data.py
  class BaseDataset (line 7) | class BaseDataset:
    method __init__ (line 9) | def __init__(self):
    method __len__ (line 12) | def __len__(self):
    method get_sequence_list (line 16) | def get_sequence_list(self):
  class Sequence (line 21) | class Sequence:
    method __init__ (line 23) | def __init__(self, name, frames, dataset, ground_truth_rect, ground_tr...
    method _ensure_start_frame (line 37) | def _ensure_start_frame(self):
    method _construct_init_data (line 56) | def _construct_init_data(self, init_data):
    method init_info (line 92) | def init_info(self):
    method frame_info (line 96) | def frame_info(self, frame_num):
    method init_bbox (line 100) | def init_bbox(self, frame_num=0):
    method init_mask (line 103) | def init_mask(self, frame_num=0):
    method get_info (line 106) | def get_info(self, keys, frame_num=None):
    method object_init_data (line 114) | def object_init_data(self, frame_num=None) -> dict:
    method target_class (line 139) | def target_class(self, frame_num=None):
    method get (line 142) | def get(self, name, frame_num=None):
    method __repr__ (line 145) | def __repr__(self):
  class SequenceList (line 150) | class SequenceList(list):
    method __getitem__ (line 152) | def __getitem__(self, item):
    method __add__ (line 165) | def __add__(self, other):
    method copy (line 168) | def copy(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/datasets.py
  function load_dataset (line 44) | def load_dataset(name: str):
  function get_dataset (line 56) | def get_dataset(*args):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/environment.py
  class EnvSettings (line 5) | class EnvSettings:
    method __init__ (line 6) | def __init__(self):
  function create_default_local_file (line 29) | def create_default_local_file():
  function env_settings (line 55) | def env_settings():

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/got10kdataset.py
  class GOT10KDataset (line 7) | class GOT10KDataset(BaseDataset):
    method __init__ (line 18) | def __init__(self, split):
    method get_sequence_list (line 29) | def get_sequence_list(self):
    method _construct_sequence (line 32) | def _construct_sequence(self, sequence_name):
    method __len__ (line 44) | def __len__(self):
    method _get_sequence_list (line 47) | def _get_sequence_list(self, split):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/lasotdataset.py
  class LaSOTDataset (line 6) | class LaSOTDataset(BaseDataset):
    method __init__ (line 18) | def __init__(self):
    method clean_seq_list (line 24) | def clean_seq_list(self):
    method get_sequence_list (line 31) | def get_sequence_list(self):
    method _construct_sequence (line 34) | def _construct_sequence(self, sequence_name):
    method __len__ (line 58) | def __len__(self):
    method _get_sequence_list (line 61) | def _get_sequence_list(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/mobifacedataset.py
  class MobifaceDataset (line 9) | class MobifaceDataset(BaseDataset):
    method __init__ (line 19) | def __init__(self, split):
    method get_sequence_list (line 29) | def get_sequence_list(self):
    method _get_sequence_list (line 32) | def _get_sequence_list(self, split):
    method _construct_sequence (line 55) | def _construct_sequence(self, sequence_name):
    method __len__ (line 67) | def __len__(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/multi_object_wrapper.py
  class MultiObjectWrapper (line 7) | class MultiObjectWrapper:
    method __init__ (line 8) | def __init__(self, base_tracker_class, params, visdom=None, fast_load=...
    method create_tracker (line 22) | def create_tracker(self):
    method _split_info (line 34) | def _split_info(self, info):
    method _set_defaults (line 52) | def _set_defaults(self, tracker_out: dict, defaults=None):
    method default_merge (line 61) | def default_merge(self, out_all):
    method merge_outputs (line 90) | def merge_outputs(self, out_all):
    method initialize (line 98) | def initialize(self, image, info: dict) -> dict:
    method track (line 131) | def track(self, image, info: dict = None) -> dict:
    method visdom_draw_tracking (line 179) | def visdom_draw_tracking(self, image, box, segmentation):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/nfsdataset.py
  class NFSDataset (line 6) | class NFSDataset(BaseDataset):
    method __init__ (line 17) | def __init__(self):
    method get_sequence_list (line 22) | def get_sequence_list(self):
    method _construct_sequence (line 25) | def _construct_sequence(self, sequence_info):
    method __len__ (line 46) | def __len__(self):
    method _get_sequence_info_list (line 49) | def _get_sequence_info_list(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/otbdataset.py
  class OTBDataset (line 6) | class OTBDataset(BaseDataset):
    method __init__ (line 17) | def __init__(self):
    method get_sequence_list (line 22) | def get_sequence_list(self):
    method _construct_sequence (line 25) | def _construct_sequence(self, sequence_info):
    method __len__ (line 47) | def __len__(self):
    method _get_sequence_info_list (line 50) | def _get_sequence_info_list(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/running.py
  function _save_tracker_output (line 11) | def _save_tracker_output(seq: Sequence, tracker: Tracker, output: dict):
  function run_sequence (line 76) | def run_sequence(seq: Sequence, tracker: Tracker, debug=False, visdom_in...
  function run_dataset (line 119) | def run_dataset(dataset, trackers, debug=False, threads=0, visdom_info=N...

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/tpldataset.py
  class TPLDataset (line 6) | class TPLDataset(BaseDataset):
    method __init__ (line 18) | def __init__(self, exclude_otb=False):
    method get_sequence_list (line 27) | def get_sequence_list(self):
    method _construct_sequence (line 30) | def _construct_sequence(self, sequence_info):
    method __len__ (line 50) | def __len__(self):
    method _get_sequence_info_list (line 53) | def _get_sequence_info_list(self, exclude_otb=False):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/tracker.py
  function trackerlist (line 23) | def trackerlist(name: str, parameter_name: str, run_ids = None, display_...
  class Tracker (line 36) | class Tracker:
    method __init__ (line 45) | def __init__(self, name: str, parameter_name: str, run_id: int = None,...
    method _init_visdom (line 71) | def _init_visdom(self, visdom_info, debug):
    method _visdom_ui_handler (line 91) | def _visdom_ui_handler(self, data):
    method create_tracker (line 100) | def create_tracker(self, params):
    method run_sequence (line 105) | def run_sequence(self, seq, visualization=None, debug=None, visdom_inf...
    method _track_sequence (line 150) | def _track_sequence(self, tracker, seq, init_info):
    method run_video (line 229) | def run_video(self, videofilepath, optional_box=None, debug=None, visd...
    method run_webcam (line 336) | def run_webcam(self, debug=None, visdom_info=None):
    method run_vot2020 (line 471) | def run_vot2020(self, debug=None, visdom_info=None):
    method run_vot (line 563) | def run_vot(self, debug=None, visdom_info=None):
    method get_parameters (line 633) | def get_parameters(self):
    method init_visualization (line 640) | def init_visualization(self):
    method visualize (line 647) | def visualize(self, image, state, segmentation=None):
    method reset_tracker (line 677) | def reset_tracker(self):
    method press (line 680) | def press(self, event):
    method _read_image (line 688) | def _read_image(self, image_file: str):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/trackingnetdataset.py
  class TrackingNetDataset (line 7) | class TrackingNetDataset(BaseDataset):
    method __init__ (line 18) | def __init__(self):
    method get_sequence_list (line 31) | def get_sequence_list(self):
    method _construct_sequence (line 34) | def _construct_sequence(self, set, sequence_name):
    method __len__ (line 46) | def __len__(self):
    method _list_sequences (line 49) | def _list_sequences(self, root, set_ids):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/uavdataset.py
  class UAVDataset (line 6) | class UAVDataset(BaseDataset):
    method __init__ (line 17) | def __init__(self):
    method get_sequence_list (line 22) | def get_sequence_list(self):
    method _construct_sequence (line 25) | def _construct_sequence(self, sequence_info):
    method __len__ (line 46) | def __len__(self):
    method _get_sequence_info_list (line 49) | def _get_sequence_info_list(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/vot.py
  function parse_region (line 27) | def parse_region(string):
  function encode_region (line 35) | def encode_region(region):
  function convert_region (line 43) | def convert_region(region, to):
  class VOT (line 82) | class VOT(object):
    method __init__ (line 84) | def __init__(self, region_format):
    method region (line 109) | def region(self):
    method report (line 120) | def report(self, region, confidence = 0):
    method frame (line 138) | def frame(self):
    method quit (line 163) | def quit(self):
    method __del__ (line 172) | def __del__(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/vot2020.py
  function make_full_size (line 23) | def make_full_size(x, output_sz):
  class VOT (line 48) | class VOT(object):
    method __init__ (line 50) | def __init__(self, region_format, channels=None):
    method region (line 85) | def region(self):
    method report (line 96) | def report(self, region, confidence = None):
    method frame (line 115) | def frame(self):
    method quit (line 138) | def quit(self):
    method __del__ (line 142) | def __del__(self):

FILE: artrackv2_mindspore/external/AR/pytracking/evaluation/votdataset.py
  class VOTDataset (line 5) | class VOTDataset(BaseDataset):
    method __init__ (line 18) | def __init__(self):
    method get_sequence_list (line 23) | def get_sequence_list(self):
    method _construct_sequence (line 26) | def _construct_sequence(self, sequence_name):
    method __len__ (line 57) | def __len__(self):
    method _get_sequence_list (line 60) | def _get_sequence_list(self):

FILE: artrackv2_mindspore/external/AR/pytracking/experiments/myexperiments.py
  function atom_nfs_uav (line 4) | def atom_nfs_uav():
  function uav_test (line 12) | def uav_test():

FILE: artrackv2_mindspore/external/AR/pytracking/features/augmentation.py
  class Transform (line 10) | class Transform:
    method __init__ (line 13) | def __init__(self, output_sz = None, shift = None):
    method __call__ (line 17) | def __call__(self, image, is_mask=False):
    method crop_to_output (line 20) | def crop_to_output(self, image):
  class Identity (line 39) | class Identity(Transform):
    method __call__ (line 41) | def __call__(self, image, is_mask=False):
  class FlipHorizontal (line 44) | class FlipHorizontal(Transform):
    method __call__ (line 46) | def __call__(self, image, is_mask=False):
  class FlipVertical (line 52) | class FlipVertical(Transform):
    method __call__ (line 54) | def __call__(self, image: torch.Tensor, is_mask=False):
  class Translation (line 60) | class Translation(Transform):
    method __init__ (line 62) | def __init__(self, translation, output_sz = None, shift = None):
    method __call__ (line 66) | def __call__(self, image, is_mask=False):
  class Scale (line 72) | class Scale(Transform):
    method __init__ (line 74) | def __init__(self, scale_factor, output_sz = None, shift = None):
    method __call__ (line 78) | def __call__(self, image, is_mask=False):
  class Affine (line 98) | class Affine(Transform):
    method __init__ (line 100) | def __init__(self, transform_matrix, output_sz = None, shift = None):
    method __call__ (line 104) | def __call__(self, image, is_mask=False):
  class Rotate (line 111) | class Rotate(Transform):
    method __init__ (line 113) | def __init__(self, angle, output_sz = None, shift = None):
    method __call__ (line 117) | def __call__(self, image, is_mask=False):
  class Blur (line 128) | class Blur(Transform):
    method __init__ (line 130) | def __init__(self, sigma, output_sz = None, shift = None):
    method __call__ (line 141) | def __call__(self, image, is_mask=False):
  class RandomAffine (line 150) | class RandomAffine(Transform):
    method __init__ (line 152) | def __init__(self, p_flip=0.0, max_rotation=0.0, max_shear=0.0, max_sc...
    method roll (line 171) | def roll(self):
    method _construct_t_mat (line 183) | def _construct_t_mat(self, image_shape, do_flip, theta, shear_values, ...
    method __call__ (line 212) | def __call__(self, image, is_mask=False):

FILE: artrackv2_mindspore/external/AR/pytracking/features/color.py
  class RGB (line 5) | class RGB(FeatureBase):
    method dim (line 7) | def dim(self):
    method stride (line 10) | def stride(self):
    method extract (line 13) | def extract(self, im: torch.Tensor):
  class Grayscale (line 17) | class Grayscale(FeatureBase):
    method dim (line 19) | def dim(self):
    method stride (line 22) | def stride(self):
    method extract (line 25) | def extract(self, im: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/features/deep.py
  class ResNet18m1 (line 14) | class ResNet18m1(MultiFeatureBase):
    method __init__ (line 22) | def __init__(self, output_layers, net_path=None, use_gpu=True, *args, ...
    method initialize (line 33) | def initialize(self):
    method dim (line 68) | def dim(self):
    method stride (line 71) | def stride(self):
    method extract (line 74) | def extract(self, im: torch.Tensor):
  class ATOMResNet18 (line 86) | class ATOMResNet18(MultiFeatureBase):
    method __init__ (line 94) | def __init__(self, output_layers=('layer3',), net_path='atom_iou', use...
    method initialize (line 101) | def initialize(self):
    method dim (line 125) | def dim(self):
    method stride (line 128) | def stride(self):
    method extract (line 131) | def extract(self, im: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/features/extractor.py
  class ExtractorBase (line 5) | class ExtractorBase:
    method __init__ (line 10) | def __init__(self, features):
    method initialize (line 13) | def initialize(self):
  class SingleResolutionExtractor (line 18) | class SingleResolutionExtractor(ExtractorBase):
    method __init__ (line 23) | def __init__(self, features):
    method stride (line 30) | def stride(self):
    method size (line 33) | def size(self, input_sz):
    method extract (line 36) | def extract(self, im, pos, scales, image_sz):
  class MultiResolutionExtractor (line 49) | class MultiResolutionExtractor(ExtractorBase):
    method __init__ (line 54) | def __init__(self, features, patch_mode='replicate', max_scale_change=...
    method stride (line 60) | def stride(self):
    method size (line 63) | def size(self, input_sz):
    method dim (line 66) | def dim(self):
    method get_fparams (line 69) | def get_fparams(self, name: str = None):
    method get_attribute (line 74) | def get_attribute(self, name: str, ignore_missing: bool = False):
    method get_unique_attribute (line 80) | def get_unique_attribute(self, name: str):
    method _return_feature (line 91) | def _return_feature(self, f):
    method set_is_color (line 94) | def set_is_color(self, is_color: bool):
    method extract (line 97) | def extract(self, im, pos, scales, image_sz, return_patches=False):
    method extract_transformed (line 124) | def extract_transformed(self, im, pos, scale, image_sz, transforms):

FILE: artrackv2_mindspore/external/AR/pytracking/features/featurebase.py
  class FeatureBase (line 6) | class FeatureBase:
    method __init__ (line 16) | def __init__(self, fparams = None, pool_stride = None, output_size = N...
    method initialize (line 24) | def initialize(self):
    method dim (line 27) | def dim(self):
    method stride (line 30) | def stride(self):
    method size (line 33) | def size(self, im_sz):
    method extract (line 40) | def extract(self, im):
    method get_feature (line 44) | def get_feature(self, im: torch.Tensor):
  class MultiFeatureBase (line 72) | class MultiFeatureBase(FeatureBase):
    method size (line 76) | def size(self, im_sz):
    method get_feature (line 82) | def get_feature(self, im: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/features/net_wrappers.py
  class NetWrapper (line 5) | class NetWrapper:
    method __init__ (line 9) | def __init__(self, net_path, use_gpu=True, initialize=False, **kwargs):
    method __getattr__ (line 17) | def __getattr__(self, name):
    method load_network (line 30) | def load_network(self):
    method initialize (line 36) | def initialize(self):
  class NetWithBackbone (line 40) | class NetWithBackbone(NetWrapper):
    method __init__ (line 44) | def __init__(self, net_path, use_gpu=True, initialize=False, image_for...
    method initialize (line 52) | def initialize(self, image_format='rgb', mean=(0.485, 0.456, 0.406), s...
    method preprocess_image (line 55) | def preprocess_image(self, im: torch.Tensor):
    method extract_backbone (line 71) | def extract_backbone(self, im: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/features/preprocessing.py
  function numpy_to_torch (line 6) | def numpy_to_torch(a: np.ndarray):
  function torch_to_numpy (line 10) | def torch_to_numpy(a: torch.Tensor):
  function sample_patch_transformed (line 14) | def sample_patch_transformed(im, pos, scale, image_sz, transforms, is_ma...
  function sample_patch_multiscale (line 33) | def sample_patch_multiscale(im, pos, scales, image_sz, mode: str='replic...
  function sample_patch (line 55) | def sample_patch(im: torch.Tensor, pos: torch.Tensor, sample_sz: torch.T...

FILE: artrackv2_mindspore/external/AR/pytracking/features/util.py
  class Concatenate (line 5) | class Concatenate(FeatureBase):
    method __init__ (line 10) | def __init__(self, features, pool_stride = None, normalize_power = Non...
    method dim (line 20) | def dim(self):
    method stride (line 23) | def stride(self):
    method extract (line 26) | def extract(self, im: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/complex.py
  function is_complex (line 5) | def is_complex(a: torch.Tensor) -> bool:
  function is_real (line 9) | def is_real(a: torch.Tensor) -> bool:
  function mult (line 14) | def mult(a: torch.Tensor, b: torch.Tensor):
  function mult_conj (line 36) | def mult_conj(a: torch.Tensor, b: torch.Tensor):
  function mult_real_cplx (line 58) | def mult_real_cplx(a: torch.Tensor, b: torch.Tensor):
  function div (line 68) | def div(a: torch.Tensor, b: torch.Tensor):
  function div_cplx_real (line 81) | def div_cplx_real(a: torch.Tensor, b: torch.Tensor):
  function abs_sqr (line 91) | def abs_sqr(a: torch.Tensor):
  function abs (line 101) | def abs(a: torch.Tensor):
  function conj (line 111) | def conj(a: torch.Tensor):
  function real (line 122) | def real(a: torch.Tensor):
  function imag (line 132) | def imag(a: torch.Tensor):
  function complex (line 142) | def complex(a: torch.Tensor, b: torch.Tensor = None):
  function mtimes (line 154) | def mtimes(a: torch.Tensor, b: torch.Tensor, conj_a=False, conj_b=False):
  function mtimes_real_complex (line 182) | def mtimes_real_complex(a: torch.Tensor, b: torch.Tensor, conj_b=False):
  function mtimes_complex_real (line 193) | def mtimes_complex_real(a: torch.Tensor, b: torch.Tensor, conj_a=False):
  function exp_imag (line 204) | def exp_imag(a: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/dcf.py
  function hann1d (line 8) | def hann1d(sz: int, centered = True) -> torch.Tensor:
  function hann2d (line 16) | def hann2d(sz: torch.Tensor, centered = True) -> torch.Tensor:
  function hann2d_clipped (line 21) | def hann2d_clipped(sz: torch.Tensor, effective_sz: torch.Tensor, centere...
  function gauss_fourier (line 40) | def gauss_fourier(sz: int, sigma: float, half: bool = False) -> torch.Te...
  function gauss_spatial (line 48) | def gauss_spatial(sz, sigma, center=0, end_pad=0):
  function label_function (line 53) | def label_function(sz: torch.Tensor, sigma: torch.Tensor):
  function label_function_spatial (line 56) | def label_function_spatial(sz: torch.Tensor, sigma: torch.Tensor, center...
  function cubic_spline_fourier (line 62) | def cubic_spline_fourier(f, a):
  function get_interp_fourier (line 74) | def get_interp_fourier(sz: torch.Tensor, method='ideal', bicubic_param=0...
  function interpolate_dft (line 97) | def interpolate_dft(a: torch.Tensor, interp_fs) -> torch.Tensor:
  function get_reg_filter (line 106) | def get_reg_filter(sz: torch.Tensor, target_sz: torch.Tensor, params):
  function max2d (line 156) | def max2d(a: torch.Tensor) -> (torch.Tensor, torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/fourier.py
  function rfftshift2 (line 8) | def rfftshift2(a: torch.Tensor):
  function irfftshift2 (line 14) | def irfftshift2(a: torch.Tensor):
  function cfft2 (line 20) | def cfft2(a):
  function cifft2 (line 28) | def cifft2(a, signal_sizes=None):
  function sample_fs (line 35) | def sample_fs(a: torch.Tensor, grid_sz: torch.Tensor = None, rescale = T...
  function get_frequency_coord (line 64) | def get_frequency_coord(sz, add_complex_dim = False, device='cpu'):
  function shift_fs (line 78) | def shift_fs(a: torch.Tensor, shift: torch.Tensor):
  function sum_fs (line 95) | def sum_fs(a: TensorList) -> torch.Tensor:
  function sum_fs12 (line 117) | def sum_fs12(a: TensorList) -> torch.Tensor:
  function inner_prod_fs (line 140) | def inner_prod_fs(a: torch.Tensor, b: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/operation.py
  function conv2d (line 7) | def conv2d(input: torch.Tensor, weight: torch.Tensor, bias: torch.Tensor...
  function conv1x1 (line 36) | def conv1x1(input: torch.Tensor, weight: torch.Tensor):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/optimization.py
  class L2Problem (line 9) | class L2Problem:
    method __call__ (line 12) | def __call__(self, x: TensorList) -> TensorList:
    method ip_input (line 16) | def ip_input(self, a, b):
    method ip_output (line 20) | def ip_output(self, a, b):
    method M1 (line 24) | def M1(self, x):
    method M2 (line 28) | def M2(self, x):
  class MinimizationProblem (line 32) | class MinimizationProblem:
    method __call__ (line 34) | def __call__(self, x: TensorList) -> TensorList:
    method ip_input (line 38) | def ip_input(self, a, b):
    method M1 (line 42) | def M1(self, x):
    method M2 (line 45) | def M2(self, x):
  class ConjugateGradientBase (line 49) | class ConjugateGradientBase:
    method __init__ (line 52) | def __init__(self, fletcher_reeves = True, standard_alpha = True, dire...
    method reset_state (line 66) | def reset_state(self):
    method run_CG (line 72) | def run_CG(self, num_iter, x=None, eps=0.0):
    method A (line 166) | def A(self, x):
    method ip (line 170) | def ip(self, a, b):
    method residual_norm (line 174) | def residual_norm(self, r):
    method check_zero (line 180) | def check_zero(self, s, eps = 0.0):
    method M1 (line 186) | def M1(self, x):
    method M2 (line 190) | def M2(self, x):
    method evaluate_CG_iteration (line 194) | def evaluate_CG_iteration(self, x):
  class ConjugateGradient (line 199) | class ConjugateGradient(ConjugateGradientBase):
    method __init__ (line 202) | def __init__(self, problem: L2Problem, variable: TensorList, cg_eps = ...
    method clear_temp (line 221) | def clear_temp(self):
    method run (line 227) | def run(self, num_cg_iter):
    method A (line 278) | def A(self, x):
    method ip (line 282) | def ip(self, a, b):
    method M1 (line 285) | def M1(self, x):
    method M2 (line 288) | def M2(self, x):
  class GaussNewtonCG (line 293) | class GaussNewtonCG(ConjugateGradientBase):
    method __init__ (line 296) | def __init__(self, problem: L2Problem, variable: TensorList, cg_eps = ...
    method clear_temp (line 318) | def clear_temp(self):
    method run_GN (line 324) | def run_GN(self, *args, **kwargs):
    method run (line 328) | def run(self, num_cg_iter, num_gn_iter=None):
    method run_GN_iter (line 377) | def run_GN_iter(self, num_cg_iter):
    method A (line 410) | def A(self, x):
    method ip (line 414) | def ip(self, a, b):
    method M1 (line 417) | def M1(self, x):
    method M2 (line 420) | def M2(self, x):
    method evaluate_CG_iteration (line 423) | def evaluate_CG_iteration(self, delta_x):
  class GradientDescentL2 (line 438) | class GradientDescentL2:
    method __init__ (line 441) | def __init__(self, problem: L2Problem, variable: TensorList, step_leng...
    method clear_temp (line 460) | def clear_temp(self):
    method run (line 465) | def run(self, num_iter, dummy = None):
  class NewtonCG (line 522) | class NewtonCG(ConjugateGradientBase):
    method __init__ (line 525) | def __init__(self, problem: MinimizationProblem, variable: TensorList,...
    method clear_temp (line 547) | def clear_temp(self):
    method run (line 552) | def run(self, num_cg_iter, num_newton_iter=None):
    method run_newton_iter (line 589) | def run_newton_iter(self, num_cg_iter):
    method A (line 615) | def A(self, x):
    method ip (line 618) | def ip(self, a, b):
    method M1 (line 622) | def M1(self, x):
    method M2 (line 625) | def M2(self, x):
    method evaluate_CG_iteration (line 628) | def evaluate_CG_iteration(self, delta_x):
  class GradientDescent (line 642) | class GradientDescent:
    method __init__ (line 645) | def __init__(self, problem: MinimizationProblem, variable: TensorList,...
    method clear_temp (line 665) | def clear_temp(self):
    method run (line 669) | def run(self, num_iter, dummy = None):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/tensordict.py
  class TensorDict (line 6) | class TensorDict(OrderedDict):
    method concat (line 9) | def concat(self, other):
    method copy (line 13) | def copy(self):
    method __deepcopy__ (line 16) | def __deepcopy__(self, memodict={}):
    method __getattr__ (line 19) | def __getattr__(self, name):
    method attribute (line 27) | def attribute(self, attr: str, *args):
    method apply (line 30) | def apply(self, fn, *args, **kwargs):
    method _iterable (line 34) | def _iterable(a):

FILE: artrackv2_mindspore/external/AR/pytracking/libs/tensorlist.py
  class TensorList (line 6) | class TensorList(list):
    method __init__ (line 9) | def __init__(self, list_of_tensors = None):
    method __deepcopy__ (line 14) | def __deepcopy__(self, memodict={}):
    method __getitem__ (line 17) | def __getitem__(self, item):
    method __add__ (line 25) | def __add__(self, other):
    method __radd__ (line 30) | def __radd__(self, other):
    method __iadd__ (line 35) | def __iadd__(self, other):
    method __sub__ (line 44) | def __sub__(self, other):
    method __rsub__ (line 49) | def __rsub__(self, other):
    method __isub__ (line 54) | def __isub__(self, other):
    method __mul__ (line 63) | def __mul__(self, other):
    method __rmul__ (line 68) | def __rmul__(self, other):
    method __imul__ (line 73) | def __imul__(self, other):
    method __truediv__ (line 82) | def __truediv__(self, other):
    method __rtruediv__ (line 87) | def __rtruediv__(self, other):
    method __itruediv__ (line 92) | def __itruediv__(self, other):
    method __matmul__ (line 101) | def __matmul__(self, other):
    method __rmatmul__ (line 106) | def __rmatmul__(self, other):
    method __imatmul__ (line 111) | def __imatmul__(self, other):
    method __mod__ (line 120) | def __mod__(self, other):
    method __rmod__ (line 125) | def __rmod__(self, other):
    method __pos__ (line 130) | def __pos__(self):
    method __neg__ (line 133) | def __neg__(self):
    method __le__ (line 136) | def __le__(self, other):
    method __ge__ (line 141) | def __ge__(self, other):
    method concat (line 146) | def concat(self, other):
    method copy (line 149) | def copy(self):
    method unroll (line 152) | def unroll(self):
    method list (line 164) | def list(self):
    method attribute (line 167) | def attribute(self, attr: str, *args):
    method apply (line 170) | def apply(self, fn):
    method __getattr__ (line 173) | def __getattr__(self, name):
    method _iterable (line 183) | def _iterable(a):
  function tensor_operation (line 188) | def tensor_operation(op):

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/atom/atom_gmm_sampl.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/atom/atom_prob_ml.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/atom/default.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/atom/default_vot.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/atom/multiscale_no_iounet.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp18.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp18_vot.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50_vot.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50_vot19.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/prdimp18.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/prdimp50.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/dimp/super_dimp.py
  function parameters (line 4) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/parameter/eco/default.py
  function parameters (line 6) | def parameters():

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/atom/__init__.py
  function get_tracker_class (line 3) | def get_tracker_class():

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/atom/atom.py
  class ATOM (line 16) | class ATOM(BaseTracker):
    method initialize_features (line 20) | def initialize_features(self):
    method initialize (line 26) | def initialize(self, image, info: dict) -> dict:
    method init_optimization (line 138) | def init_optimization(self, train_x, init_y):
    method track (line 225) | def track(self, image, info: dict = None) -> dict:
    method apply_filter (line 301) | def apply_filter(self, sample_x: TensorList):
    method localize_target (line 304) | def localize_target(self, scores_raw):
    method localize_advanced (line 341) | def localize_advanced(self, scores):
    method extract_sample (line 409) | def extract_sample(self, im: torch.Tensor, pos: torch.Tensor, scales, ...
    method get_iou_features (line 412) | def get_iou_features(self):
    method get_iou_backbone_features (line 415) | def get_iou_backbone_features(self):
    method extract_processed_sample (line 418) | def extract_processed_sample(self, im: torch.Tensor, pos: torch.Tensor...
    method preprocess_sample (line 422) | def preprocess_sample(self, x: TensorList) -> (TensorList, TensorList):
    method project_sample (line 427) | def project_sample(self, x: TensorList, proj_matrix = None):
    method init_learning (line 433) | def init_learning(self):
    method generate_init_samples (line 473) | def generate_init_samples(self, im: torch.Tensor) -> TensorList:
    method init_projection_matrix (line 527) | def init_projection_matrix(self, x):
    method init_label_function (line 550) | def init_label_function(self, train_x):
    method init_memory (line 572) | def init_memory(self, train_x):
    method update_memory (line 590) | def update_memory(self, sample_x: TensorList, sample_y: TensorList, le...
    method update_sample_weights (line 603) | def update_sample_weights(self, sample_weights, previous_replace_ind, ...
    method get_label_function (line 641) | def get_label_function(self, sample_pos, sample_scale):
    method update_state (line 650) | def update_state(self, new_pos, new_scale = None):
    method get_iounet_box (line 661) | def get_iounet_box(self, pos, sz, sample_pos, sample_scale):
    method init_iou_net (line 668) | def init_iou_net(self):
    method refine_target_box (line 701) | def refine_target_box(self, sample_pos, sample_scale, scale_ind, updat...
    method optimize_boxes (line 758) | def optimize_boxes(self, iou_features, init_boxes):

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/atom/optim.py
  class FactorizedConvProblem (line 6) | class FactorizedConvProblem(optimization.L2Problem):
    method __init__ (line 7) | def __init__(self, training_samples: TensorList, y:TensorList, filter_...
    method __call__ (line 20) | def __call__(self, x: TensorList):
    method ip_input (line 49) | def ip_input(self, a: TensorList, b: TensorList):
    method M1 (line 67) | def M1(self, x: TensorList):
  class ConvProblem (line 71) | class ConvProblem(optimization.L2Problem):
    method __init__ (line 72) | def __init__(self, training_samples: TensorList, y:TensorList, filter_...
    method __call__ (line 79) | def __call__(self, x: TensorList):
    method ip_input (line 96) | def ip_input(self, a: TensorList, b: TensorList):

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/base/basetracker.py
  class BaseTracker (line 3) | class BaseTracker:
    method __init__ (line 6) | def __init__(self, params):
    method initialize (line 11) | def initialize(self, image, info: dict) -> dict:
    method track (line 16) | def track(self, image, info: dict = None) -> dict:
    method visdom_draw_tracking (line 21) | def visdom_draw_tracking(self, image, box, segmentation=None):

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/dimp/__init__.py
  function get_tracker_class (line 3) | def get_tracker_class():

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/dimp/dimp.py
  class DiMP (line 16) | class DiMP(BaseTracker):
    method initialize_features (line 20) | def initialize_features(self):
    method initialize (line 25) | def initialize(self, image, info: dict) -> dict:
    method track (line 94) | def track(self, image, info: dict = None) -> dict:
    method get_sample_location (line 179) | def get_sample_location(self, sample_coord):
    method get_centered_sample_pos (line 186) | def get_centered_sample_pos(self):
    method classify_target (line 191) | def classify_target(self, sample_x: TensorList):
    method localize_target (line 197) | def localize_target(self, scores, sample_pos, sample_scales):
    method localize_advanced (line 239) | def localize_advanced(self, scores, sample_pos, sample_scales):
    method extract_backbone_features (line 306) | def extract_backbone_features(self, im: torch.Tensor, pos: torch.Tenso...
    method get_classification_features (line 314) | def get_classification_features(self, backbone_feat):
    method get_iou_backbone_features (line 318) | def get_iou_backbone_features(self, backbone_feat):
    method get_iou_features (line 321) | def get_iou_features(self, backbone_feat):
    method get_iou_modulation (line 325) | def get_iou_modulation(self, iou_backbone_feat, target_boxes):
    method generate_init_samples (line 330) | def generate_init_samples(self, im: torch.Tensor) -> TensorList:
    method init_target_boxes (line 400) | def init_target_boxes(self):
    method init_memory (line 411) | def init_memory(self, train_x: TensorList):
    method update_memory (line 431) | def update_memory(self, sample_x: TensorList, target_box, learning_rat...
    method update_sample_weights (line 446) | def update_sample_weights(self, sample_weights, previous_replace_ind, ...
    method update_state (line 487) | def update_state(self, new_pos, new_scale = None):
    method get_iounet_box (line 499) | def get_iounet_box(self, pos, sz, sample_pos, sample_scale):
    method init_iou_net (line 508) | def init_iou_net(self, backbone_feat):
    method init_classifier (line 537) | def init_classifier(self, init_backbone_feat):
    method _overwrite_classifier_params (line 590) | def _overwrite_classifier_params(self, feature_dim):
    method update_classifier (line 606) | def update_classifier(self, train_x, target_box, learning_rate=None, s...
    method refine_target_box (line 651) | def refine_target_box(self, backbone_feat, sample_pos, sample_scale, s...
    method optimize_boxes (line 717) | def optimize_boxes(self, iou_features, init_boxes):
    method optimize_boxes_default (line 726) | def optimize_boxes_default(self, iou_features, init_boxes):
    method optimize_boxes_relative (line 754) | def optimize_boxes_relative(self, iou_features, init_boxes):
    method direct_box_regression (line 791) | def direct_box_regression(self, backbone_feat, sample_pos, sample_scal...
    method visualize_iou_pred (line 830) | def visualize_iou_pred(self, iou_features, center_box):
    method visdom_draw_tracking (line 862) | def visdom_draw_tracking(self, image, box, segmentation=None):

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/eco/__init__.py
  function get_tracker_class (line 3) | def get_tracker_class():

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/eco/eco.py
  class ECO (line 15) | class ECO(BaseTracker):
    method initialize_features (line 19) | def initialize_features(self):
    method initialize (line 25) | def initialize(self, image, info: dict) -> dict:
    method track (line 181) | def track(self, image, info: dict = None) -> dict:
    method apply_filter (line 244) | def apply_filter(self, sample_xf: TensorList) -> torch.Tensor:
    method localize_target (line 247) | def localize_target(self, sf: TensorList):
    method extract_sample (line 290) | def extract_sample(self, im: torch.Tensor, pos: torch.Tensor, scales, ...
    method extract_fourier_sample (line 293) | def extract_fourier_sample(self, im: torch.Tensor, pos: torch.Tensor, ...
    method preprocess_sample (line 297) | def preprocess_sample(self, x: TensorList) -> TensorList:
    method project_sample (line 302) | def project_sample(self, x: TensorList):
    method generate_init_samples (line 311) | def generate_init_samples(self, im: torch.Tensor) -> TensorList:
    method update_memory (line 339) | def update_memory(self, sample_xf: TensorList):
    method update_sample_weights (line 346) | def update_sample_weights(self):
    method update_state (line 372) | def update_state(self, new_pos, new_scale):
    method symmetrize_filter (line 382) | def symmetrize_filter(self):

FILE: artrackv2_mindspore/external/AR/pytracking/tracker/eco/optim.py
  class FactorizedConvProblem (line 8) | class FactorizedConvProblem(optimization.L2Problem):
    method __init__ (line 9) | def __init__(self, training_samples: TensorList, yf:TensorList, reg_fi...
    method __call__ (line 34) | def __call__(self, x: TensorList):
    method ip_input (line 77) | def ip_input(self, a: TensorList, b: TensorList):
    method ip_output (line 94) | def ip_output(self, a: TensorList, b: TensorList):
    method M1 (line 117) | def M1(self, x: TensorList):
  class FilterOptim (line 121) | class FilterOptim(optimization.ConjugateGradientBase):
    method __init__ (line 122) | def __init__(self, params, reg_energy):
    method register (line 134) | def register(self, filter, training_samples, yf, sample_weights, reg_f...
    method run (line 142) | def run(self, num_iter, new_xf: TensorList = None):
    method A (line 168) | def A(self, hf: TensorList):
    method ip (line 203) | def ip(self, a: torch.Tensor, b: torch.Tensor):
    method M1 (line 207) | def M1(self, hf):

FILE: artrackv2_mindspore/external/AR/pytracking/util_scripts/download_results.py
  function _download_file (line 57) | def _download_file(file_id, path):
  function download_results (line 62) | def download_results(download_path, trackers='all'):
  function unpack_tracking_results (line 111) | def unpack_tracking_results(download_path, output_path=None):
  function main (line 150) | def main():

FILE: artrackv2_mindspore/external/AR/pytracking/util_scripts/pack_got10k_results.py
  function pack_got10k_results (line 7) | def pack_got10k_results(tracker_name, param_name, output_name):

FILE: artrackv2_mindspore/external/AR/pytracking/util_scripts/pack_trackingnet_results.py
  function pack_trackingnet_results (line 8) | def pack_trackingnet_results(tracker_name, param_name, run_id=None, outp...

FILE: artrackv2_mindspore/external/AR/pytracking/utils/convert_vot_anno_to_rect.py
  function convert_vot_anno_to_rect (line 4) | def convert_vot_anno_to_rect(vot_anno, type):

FILE: artrackv2_mindspore/external/AR/pytracking/utils/load_text.py
  function load_text_numpy (line 5) | def load_text_numpy(path, delimiter, dtype):
  function load_text_pandas (line 20) | def load_text_pandas(path, delimiter, dtype):
  function load_text (line 37) | def load_text(path, delimiter=' ', dtype=np.float32, backend='numpy'):

FILE: artrackv2_mindspore/external/AR/pytracking/utils/loading.py
  function load_network (line 6) | def load_network(net_path, **kwargs):

FILE: artrackv2_mindspore/external/AR/pytracking/utils/params.py
  class TrackerParams (line 5) | class TrackerParams:
    method set_default_values (line 7) | def set_default_values(self, default_vals: dict):
    method get (line 12) | def get(self, name: str, *default):
    method has (line 23) | def has(self, name: str):
  class FeatureParams (line 28) | class FeatureParams:
    method __init__ (line 30) | def __init__(self, *args, **kwargs):
  function Choice (line 41) | def Choice(*args):

FILE: artrackv2_mindspore/external/AR/pytracking/utils/plotting.py
  function draw_figure (line 7) | def draw_figure(fig):
  function show_tensor (line 13) | def show_tensor(a: torch.Tensor, fig_num = None, title = None, range=(No...
  function plot_graph (line 43) | def plot_graph(a: torch.Tensor, fig_num = None, title = None):
  function show_image_with_boxes (line 61) | def show_image_with_boxes(im, boxes, iou_pred=None, disp_ids=None):
  function _pascal_color_map (line 86) | def _pascal_color_map(N=256, normalized=False):
  function overlay_mask (line 113) | def overlay_mask(im, ann, alpha=0.5, colors=None, contour_thickness=None):

FILE: artrackv2_mindspore/external/AR/pytracking/utils/visdom.py
  class VisBase (line 12) | class VisBase:
    method __init__ (line 13) | def __init__(self, visdom, show_data, title):
    method update (line 19) | def update(self, data, **kwargs):
    method save_data (line 25) | def save_data(self, data, **kwargs):
    method draw_data (line 28) | def draw_data(self):
    method toggle_display (line 31) | def toggle_display(self, new_mode=None):
  class VisImage (line 43) | class VisImage(VisBase):
    method __init__ (line 44) | def __init__(self, visdom, show_data, title):
    method save_data (line 47) | def save_data(self, data):
    method draw_data (line 51) | def draw_data(self):
  class VisHeatmap (line 55) | class VisHeatmap(VisBase):
    method __init__ (line 56) | def __init__(self, visdom, show_data, title):
    method save_data (line 59) | def save_data(self, data):
    method draw_data (line 63) | def draw_data(self):
  class VisFeaturemap (line 67) | class VisFeaturemap(VisBase):
    method __init__ (line 68) | def __init__(self, visdom, show_data, title):
    method block_list_callback_handler (line 72) | def block_list_callback_handler(self, data):
    method save_data (line 77) | def save_data(self, data):
    method draw_data (line 91) | def draw_data(self):
  class VisCostVolume (line 100) | class VisCostVolume(VisBase):
    method __init__ (line 101) | def __init__(self, visdom, show_data, title, flip=False):
    method show_cost_volume (line 107) | def show_cost_volume(self):
    method set_zoom_pos (line 118) | def set_zoom_pos(self, slice_pos):
    method toggle_show_slice (line 121) | def toggle_show_slice(self, new_mode=None):
    method show_cost_volume_slice (line 127) | def show_cost_volume_slice(self):
    method save_data (line 139) | def save_data(self, data):
    method draw_data (line 143) | def draw_data(self):
  class VisCostVolumeUI (line 150) | class VisCostVolumeUI(VisBase):
    method cv_ui_handler (line 151) | def cv_ui_handler(self, data):
    method __init__ (line 178) | def __init__(self, visdom, show_data, title, feat_shape, registered_bl...
    method draw_grid (line 187) | def draw_grid(self, data):
    method shade_cell (line 200) | def shade_cell(self, data):
    method show_image (line 214) | def show_image(self, data=None):
    method save_data (line 222) | def save_data(self, data):
    method draw_data (line 228) | def draw_data(self):
  class VisInfoDict (line 232) | class VisInfoDict(VisBase):
    method __init__ (line 233) | def __init__(self, visdom, show_data, title):
    method generate_display_text (line 237) | def generate_display_text(self, data):
    method save_data (line 250) | def save_data(self, data):
    method draw_data (line 254) | def draw_data(self):
  class VisText (line 260) | class VisText(VisBase):
    method __init__ (line 261) | def __init__(self, visdom, show_data, title):
    method save_data (line 264) | def save_data(self, data):
    method draw_data (line 267) | def draw_data(self):
  class VisLinePlot (line 272) | class VisLinePlot(VisBase):
    method __init__ (line 273) | def __init__(self, visdom, show_data, title):
    method save_data (line 276) | def save_data(self, data):
    method draw_data (line 279) | def draw_data(self):
  class VisTracking (line 290) | class VisTracking(VisBase):
    method __init__ (line 291) | def __init__(self, visdom, show_data, title):
    method save_data (line 294) | def save_data(self, data):
    method draw_data (line 313) | def draw_data(self):
  class VisBBReg (line 337) | class VisBBReg(VisBase):
    method __init__ (line 338) | def __init__(self, visdom, show_data, title):
    method block_list_callback_handler (line 342) | def block_list_callback_handler(self, data):
    method save_data (line 347) | def save_data(self, data):
    method draw_data (line 353) | def draw_data(self):
  class Visdom (line 370) | class Visdom:
    method __init__ (line 371) | def __init__(self, debug=0, ui_info=None, visdom_info=None):
    method block_list_callback_handler (line 383) | def block_list_callback_handler(self, data):
    method register (line 392) | def register(self, data, mode, debug_level=0, title='Data', **kwargs):

FILE: artrackv2_mindspore/external/AR/pytracking/vot20_utils.py
  function make_full_size (line 4) | def make_full_size(x, output_sz):
  function rect_from_mask (line 25) | def rect_from_mask(mask):
  function mask_from_rect (line 39) | def mask_from_rect(rect, output_sz):
  function bbox_clip (line 54) | def bbox_clip(x1, y1, x2, y2, boundary, min_sz=10):

FILE: artrackv2_mindspore/external/PreciseRoIPooling/pytorch/prroi_pool/functional.py
  function _import_prroi_pooling (line 21) | def _import_prroi_pooling():
  class PrRoIPool2DFunction (line 41) | class PrRoIPool2DFunction(ag.Function):
    method forward (line 43) | def forward(ctx, features, rois, pooled_height, pooled_width, spatial_...
    method backward (line 68) | def backward(ctx, grad_output):

FILE: artrackv2_mindspore/external/PreciseRoIPooling/pytorch/prroi_pool/prroi_pool.py
  class PrRoIPool2D (line 19) | class PrRoIPool2D(nn.Module):
    method __init__ (line 20) | def __init__(self, pooled_height, pooled_width, spatial_scale):
    method forward (line 27) | def forward(self, features, rois):
    method extra_repr (line 30) | def extra_repr(self):

FILE: artrackv2_mindspore/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c
  function output (line 26) | auto output = at::zeros({nr_rois, nr_channels, pooled_height, pooled_wid...

FILE: artrackv2_mindspore/external/PreciseRoIPooling/pytorch/tests/test_prroi_pooling2d.py
  class TestPrRoIPool2D (line 20) | class TestPrRoIPool2D(TorchTestCase):
    method test_forward (line 21) | def test_forward(self):
    method test_backward_shapeonly (line 37) | def test_backward_shapeonly(self):

FILE: artrackv2_mindspore/lib/config/ostrack/config.py
  function _edict2dict (line 129) | def _edict2dict(dest_dict, src_edict):
  function gen_config (line 141) | def gen_config(config_file):
  function _update_config (line 148) | def _update_config(base_cfg, exp_cfg):
  function update_config_from_file (line 162) | def update_config_from_file(filename, base_cfg=None):

FILE: artrackv2_mindspore/lib/models/component/attention.py
  class Attention (line 15) | class Attention(nn.Cell):
    method __init__ (line 16) | def __init__(self, dim, num_heads=8, qkv_bias=False, attn_drop=0., pro...
    method construct (line 27) | def construct(self, x, padding_mask=None, **kwargs):
  class ClsMixAttention (line 48) | class ClsMixAttention(nn.Cell):
    method __init__ (line 49) | def __init__(self,
    method construct (line 66) | def construct(self, x, t_h, t_w, s_h, s_w, online_size=1, padding_mask...
  class MixAttention (line 111) | class MixAttention(nn.Cell):
    method __init__ (line 112) | def __init__(self,
    method construct (line 129) | def construct(self, x, t_h, t_w, s_h, s_w, padding_mask=None):
  class NottAttention (line 165) | class NottAttention(nn.Cell):
    method __init__ (line 166) | def __init__(self,
    method construct (line 183) | def construct(self, x, t_h, t_w, s_h, s_w, padding_mask=None):
  class NossAttention (line 219) | class NossAttention(nn.Cell):
    method __init__ (line 220) | def __init__(self,
    method construct (line 237) | def construct(self, x, t_h, t_w, s_h, s_w, padding_mask=None):
  class CrossAttention (line 273) | class CrossAttention(nn.Cell):
    method __init__ (line 274) | def __init__(self,
    method construct (line 291) | def construct(self, x, t_h, t_w, s_h, s_w):

FILE: artrackv2_mindspore/lib/models/component/block.py
  class Block (line 11) | class Block(nn.Cell):
    method __init__ (line 12) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, drop=...
    method construct (line 31) | def construct(self, x, **kwargs):

FILE: artrackv2_mindspore/lib/models/component/drop.py
  function drop_block_2d (line 21) | def drop_block_2d(
  function drop_block_fast_2d (line 69) | def drop_block_fast_2d(
  class DropBlock2d (line 108) | class DropBlock2d(nn.Cell):
    method __init__ (line 111) | def __init__(self,
    method construct (line 128) | def construct(self, x):
  function drop_path (line 139) | def drop_path(x, drop_prob: float = 0., training: bool = False):
  class DropPath (line 158) | class DropPath(nn.Cell):
    method __init__ (line 161) | def __init__(self, drop_prob=None):
    method construct (line 165) | def construct(self, x):

FILE: artrackv2_mindspore/lib/models/component/mlp.py
  class Mlp (line 9) | class Mlp(nn.Cell):
    method __init__ (line 12) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method construct (line 21) | def construct(self, x):
  class MultiLayerMlp (line 29) | class MultiLayerMlp(nn.Cell):
    method __init__ (line 32) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers, BN=F...
    method construct (line 43) | def construct(self, x):
  class GluMlp (line 48) | class GluMlp(nn.Cell):
    method __init__ (line 52) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method init_weights (line 62) | def init_weights(self):
    method construct (line 68) | def construct(self, x):
  class GatedMlp (line 78) | class GatedMlp(nn.Cell):
    method __init__ (line 81) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method construct (line 97) | def construct(self, x):
  class ConvMlp (line 107) | class ConvMlp(nn.Cell):
    method __init__ (line 110) | def __init__(
    method construct (line 121) | def construct(self, x):

FILE: artrackv2_mindspore/lib/models/component/norm.py
  class FrozenBatchNorm2d (line 8) | class FrozenBatchNorm2d(torch.nn.Module):
    method __init__ (line 17) | def __init__(self, n):
    method _load_from_state_dict (line 24) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
    method forward (line 34) | def forward(self, x):

FILE: artrackv2_mindspore/lib/models/component/patch_embed.py
  function _ntuple (line 17) | def _ntuple(n):
  class PatchEmbed (line 32) | class PatchEmbed(nn.Module):
    method __init__ (line 35) | def __init__(self, patch_size=16, in_chans=3, embed_dim=768, norm_laye...
    method forward (line 41) | def forward(self, x):

FILE: artrackv2_mindspore/lib/models/component/pos_embed.py
  function get_2d_sincos_pos_embed (line 18) | def get_2d_sincos_pos_embed(embed_dim, grid_size, cls_token=False):
  function get_2d_sincos_pos_embed_from_grid (line 36) | def get_2d_sincos_pos_embed_from_grid(embed_dim, grid):
  function get_1d_sincos_pos_embed_from_grid (line 47) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos):
  function interpolate_pos_embed (line 74) | def interpolate_pos_embed(model, checkpoint_model):

FILE: artrackv2_mindspore/lib/models/component/weight_init.py
  function _no_grad_trunc_normal_ (line 7) | def _no_grad_trunc_normal_(tensor, mean, std, a, b):
  function trunc_normal_ (line 43) | def trunc_normal_(tensor, mean=0., std=1., a=-2., b=2.):
  function variance_scaling_ (line 64) | def variance_scaling_(tensor, scale=1.0, mode='fan_in', distribution='no...
  function lecun_normal_ (line 87) | def lecun_normal_(tensor):

FILE: artrackv2_mindspore/lib/models/layers/attn.py
  class Attention (line 11) | class Attention(nn.Cell):
    method __init__ (line 12) | def __init__(self, dim, num_heads=8, qkv_bias=False, attn_drop=0., pro...
    method construct (line 36) | def construct(self, x, mask=None, return_attention=False):
  class Attention_talking_head (line 72) | class Attention_talking_head(nn.Cell):
    method __init__ (line 75) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method construct (line 106) | def construct(self, x, mask=None):

FILE: artrackv2_mindspore/lib/models/layers/attn_blocks.py
  function candidate_elimination (line 9) | def candidate_elimination(attn: torch.Tensor, tokens: torch.Tensor, lens...
  class CEBlock (line 77) | class CEBlock(nn.Module):
    method __init__ (line 79) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, drop=...
    method forward (line 92) | def forward(self, x, global_index_template, global_index_search, mask=...
  class Block (line 106) | class Block(nn.Module):
    method __init__ (line 108) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, drop=...
    method forward (line 119) | def forward(self, x, mask=None):

FILE: artrackv2_mindspore/lib/models/layers/head.py
  function top_k_top_p_filtering_batch (line 14) | def top_k_top_p_filtering_batch(logits, top_k=0, top_p=0.0, filter_value...
  function conv (line 47) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  class Corner_Predictor (line 57) | class Corner_Predictor(nn.Cell):
    method __init__ (line 60) | def __init__(self, inplanes=64, channel=256, feat_sz=20, stride=16, fr...
    method construct (line 85) | def construct(self, x, return_dist=False, softmax=True):
    method get_score_map (line 97) | def get_score_map(self, x):
    method soft_argmax (line 113) | def soft_argmax(self, score_map, return_dist=False, softmax=True):
  class CenterPredictor (line 128) | class CenterPredictor(nn.Cell, ):
    method __init__ (line 129) | def __init__(self, inplanes=64, channel=256, feat_sz=20, stride=16, fr...
    method construct (line 160) | def construct(self, x, gt_score_map=None):
    method cal_bbox (line 172) | def cal_bbox(self, score_map_ctr, size_map, offset_map, return_score=F...
    method get_pred (line 192) | def get_pred(self, score_map_ctr, size_map, offset_map):
    method get_score_map (line 205) | def get_score_map(self, x):
  class MLP (line 234) | class MLP(nn.Cell):
    method __init__ (line 237) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers, BN=F...
    method construct (line 248) | def construct(self, x):
  class SelfAttention (line 253) | class SelfAttention(nn.Cell):
    method __init__ (line 254) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method construct (line 276) | def construct(self, x, q_ape, k_ape, attn_pos):
  class CrossAttention (line 314) | class CrossAttention(nn.Cell):
    method __init__ (line 315) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method construct (line 338) | def construct(self, q, kv, q_ape, k_ape, attn_pos):
  class Mlp (line 377) | class Mlp(nn.Cell):
    method __init__ (line 380) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method construct (line 389) | def construct(self, x):
  class FeatureFusion (line 403) | class FeatureFusion(nn.Cell):
    method __init__ (line 404) | def __init__(self,
    method construct (line 430) | def construct(self, z, x, z_self_attn_pos, x_self_attn_pos, z_x_cross_...
  class FeatureFusionEncoder (line 442) | class FeatureFusionEncoder(nn.Cell):
    method __init__ (line 443) | def __init__(self, feature_fusion_layers, z_pos_enc, x_pos_enc,
    method construct (line 464) | def construct(self, z, x, z_pos, x_pos):
  class Learned2DPositionalEncoder (line 507) | class Learned2DPositionalEncoder(nn.Cell):
    method __init__ (line 508) | def __init__(self, dim, w, h):
    method construct (line 515) | def construct(self):
  class Untied2DPositionalEncoder (line 520) | class Untied2DPositionalEncoder(nn.Cell):
    method __init__ (line 521) | def __init__(self, dim, num_heads, w, h, scale=None, with_q=True, with...
    method construct (line 537) | def construct(self):
  function generate_2d_relative_positional_encoding_index (line 553) | def generate_2d_relative_positional_encoding_index(z_shape, x_shape):
  class RelativePosition2DEncoder (line 573) | class RelativePosition2DEncoder(nn.Cell):
    method __init__ (line 574) | def __init__(self, num_heads, embed_size):
    method construct (line 579) | def construct(self, attn_rpe_index):
  class DropPathAllocator (line 588) | class DropPathAllocator:
    method __init__ (line 589) | def __init__(self, max_drop_path_rate, stochastic_depth_decay = True):
    method __enter__ (line 595) | def __enter__(self):
    method __exit__ (line 598) | def __exit__(self, exc_type, exc_val, exc_tb):
    method __len__ (line 616) | def __len__(self):
    method increase_depth (line 624) | def increase_depth(self):
    method get_depth (line 628) | def get_depth(self):
    method allocate (line 631) | def allocate(self):
    method get_all_allocated (line 639) | def get_all_allocated(self):
  function build_encoder (line 646) | def build_encoder(encoder_layer, num_heads, mlp_ratio, qkv_bias, drop_ra...
  class TargetQueryDecoderLayer (line 677) | class TargetQueryDecoderLayer(nn.Cell):
    method __init__ (line 678) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method construct (line 704) | def construct(self, query, memoryz, query_pos, tgt_mask: Optional[Tens...
  function _get_clones (line 735) | def _get_clones(module, N):
  class TargetQueryDecoderBlock (line 738) | class TargetQueryDecoderBlock(nn.Cell):
    method __init__ (line 739) | def __init__(self, dim, decoder_layers, num_layer):
    method construct (line 745) | def construct(self, tgt, z, query_pos: Optional[Tensor] = None,
  function build_decoder (line 768) | def build_decoder(decoder_layer, drop_path, dim, num_heads, mlp_ratio, q...
  function generate_square_subsequent_mask (line 781) | def generate_square_subsequent_mask(sz):
  class Pix2Track (line 794) | class Pix2Track(nn.Cell):
    method __init__ (line 795) | def __init__(self, in_channel=64, feat_sz=20, feat_tz=10, stride=16, e...
    method construct (line 820) | def construct(self, zx_feat, pos_z, pos_x, identity, seqs_input=None, ...
  function build_box_head (line 974) | def build_box_head(cfg, hidden_dim):

FILE: artrackv2_mindspore/lib/models/layers/mask_decoder.py
  class MaskDecoder (line 19) | class MaskDecoder(nn.Cell):
    method __init__ (line 20) | def __init__(self, mask_ratio=0.75, patch_size=16, num_patches=8 ** 2,...
    method random_masking (line 47) | def random_masking(self, x):
    method forward_decoder (line 79) | def forward_decoder(self, x, eval=False):
    method unpatchify (line 101) | def unpatchify(self, x):
    method patchify (line 115) | def patchify(self, imgs):
    method forward_loss (line 130) | def forward_loss(self, imgs, pred, mask=None):
    method construct (line 150) | def construct(self, x, images=None, gt_bboxes=None, eval=False,):
  function mask_decoder (line 165) | def mask_decoder():
  function build_maskdecoder (line 172) | def build_maskdecoder(cfg):

FILE: artrackv2_mindspore/lib/models/layers/patch_embed.py
  class PatchEmbed (line 8) | class PatchEmbed(nn.Cell):
    method __init__ (line 12) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
    method construct (line 25) | def construct(self, x):

FILE: artrackv2_mindspore/lib/models/layers/rpe.py
  function generate_2d_relative_positional_encoding_index (line 6) | def generate_2d_relative_positional_encoding_index(z_shape, x_shape):
  function generate_2d_concatenated_self_attention_relative_positional_encoding_index (line 27) | def generate_2d_concatenated_self_attention_relative_positional_encoding...
  function generate_2d_concatenated_cross_attention_relative_positional_encoding_index (line 59) | def generate_2d_concatenated_cross_attention_relative_positional_encodin...
  class RelativePosition2DEncoder (line 91) | class RelativePosition2DEncoder(nn.Module):
    method __init__ (line 92) | def __init__(self, num_heads, embed_size):
    method forward (line 97) | def forward(self, attn_rpe_index):

FILE: artrackv2_mindspore/lib/models/ostrack/base_backbone.py
  function generate_square_subsequent_mask (line 16) | def generate_square_subsequent_mask(sz, sx, ss):
  class BaseBackbone (line 33) | class BaseBackbone(nn.Cell):
    method __init__ (line 34) | def __init__(self):
    method finetune_track (line 68) | def finetune_track(self, cfg, patch_start_index=1):
    method forward_features (line 144) | def forward_features(self, z_0, z_1_feat, x, identity, seqs_input):
    method construct (line 237) | def construct(self, z_0, z_1_feat, x, identity, seqs_input, **kwargs):

FILE: artrackv2_mindspore/lib/models/ostrack/load_parameter_test.py
  function get_keymap_txt (line 6) | def get_keymap_txt(pth_file):

FILE: artrackv2_mindspore/lib/models/ostrack/ostrack.py
  class OSTrack (line 20) | class OSTrack(nn.Cell):
    method __init__ (line 23) | def __init__(self, transformer,
    method construct (line 44) | def construct(self, template: ms.Tensor,
    method forward_head (line 92) | def forward_head(self, cat_feature, pos_z, pos_x, identity, seq_input=...
  class MlpScoreDecoder (line 123) | class MlpScoreDecoder(nn.Cell):
    method __init__ (line 124) | def __init__(self, in_dim, hidden_dim, num_layers, bn=False):
    method construct (line 140) | def construct(self, reg_tokens):
  function build_score_decoder (line 148) | def build_score_decoder(cfg):
  function build_ostrack (line 156) | def build_ostrack(cfg, training=True):

FILE: artrackv2_mindspore/lib/models/ostrack/utils.py
  function combine_tokens (line 6) | def combine_tokens(template_tokens, search_tokens, mode='direct', return...
  function recover_tokens (line 48) | def recover_tokens(merged_tokens, len_template_token, len_search_token, ...
  function window_partition (line 69) | def window_partition(x, window_size: int):
  function window_reverse (line 84) | def window_reverse(windows, window_size: int, H: int, W: int):

FILE: artrackv2_mindspore/lib/models/ostrack/vit.py
  class Attention (line 40) | class Attention(msnn.Cell):
    method __init__ (line 41) | def __init__(self, dim, num_heads=8, qkv_bias=False, attn_drop=0., pro...
    method construct (line 52) | def construct(self, x, return_attention=False,padding_mask=None):
  class Block (line 81) | class Block(msnn.Cell):
    method __init__ (line 83) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, drop=...
    method construct (line 97) | def construct(self, x, return_attention=False,padding_mask=None):
  class VisionTransformer (line 109) | class VisionTransformer(BaseBackbone):
    method __init__ (line 117) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method init_weights (line 190) | def init_weights(self, mode=''):
    method _init_weights (line 203) | def _init_weights(self, m):
    method load_pretrained (line 208) | def load_pretrained(self, checkpoint_path, prefix=''):
    method no_weight_decay (line 212) | def no_weight_decay(self):
    method get_classifier (line 215) | def get_classifier(self):
    method reset_classifier (line 221) | def reset_classifier(self, num_classes, global_pool=''):
  function _init_vit_weights (line 228) | def _init_vit_weights(Cell: msnn.Cell, name: str = '', head_bias: float ...
  function _load_weights (line 269) | def _load_weights(model: VisionTransformer, checkpoint_path: str, prefix...
  function resize_pos_embed (line 348) | def resize_pos_embed(posemb, posemb_new, num_tokens=1, gs_new=()):
  function checkpoint_filter_fn (line 370) | def checkpoint_filter_fn(state_dict, model):
  function _create_vision_transformer (line 389) | def _create_vision_transformer(variant, pretrained=False, default_cfg=No...
  function vit_base_patch16_224 (line 405) | def vit_base_patch16_224(pretrained=False, **kwargs):
  function vit_large_patch16_224 (line 414) | def vit_large_patch16_224(pretrained=False, **kwargs):

FILE: artrackv2_mindspore/lib/models/ostrack/vit_ce.py
  class VisionTransformerCE (line 21) | class VisionTransformerCE(VisionTransformer):
    method __init__ (line 31) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method forward_features (line 102) | def forward_features(self, z, x, mask_z=None, mask_x=None,
    method forward (line 187) | def forward(self, z, x, ce_template_mask=None, ce_keep_rate=None,
  function _create_vision_transformer (line 196) | def _create_vision_transformer(pretrained=False, **kwargs):
  function vit_base_patch16_224_ce (line 210) | def vit_base_patch16_224_ce(pretrained=False, **kwargs):
  function vit_large_patch16_224_ce (line 219) | def vit_large_patch16_224_ce(pretrained=False, **kwargs):

FILE: artrackv2_mindspore/lib/models/timm.py
  function to_2tuple (line 6) | def to_2tuple(input):
  class Mlp (line 19) | class Mlp(nn.Cell):
    method __init__ (line 22) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method construct (line 35) | def construct(self, x):
  function drop_path (line 43) | def drop_path(x, drop_prob: float = 0., training: bool = False, scale_by...
  class DropPath (line 63) | class DropPath(nn.Cell):
    method __init__ (line 66) | def __init__(self, drop_prob: float = 0., scale_by_keep: bool = True):
    method construct (line 71) | def construct(self, x):
    method extra_repr (line 74) | def extra_repr(self):
  function _trunc_normal_ (line 76) | def _trunc_normal_(tensor, mean, std, a, b):
  function trunc_normal_ (line 115) | def trunc_normal_(tensor, mean=0., std=1., a=-2., b=2.):
  function trunc_normal_tf_ (line 140) | def trunc_normal_tf_(tensor, mean=0., std=1., a=-2., b=2.):
  function variance_scaling_ (line 166) | def variance_scaling_(tensor, scale=1.0, mode='fan_in', distribution='no...
  function lecun_normal_ (line 187) | def lecun_normal_(tensor):
  function adapt_input_conv (line 189) | def adapt_input_conv(in_chans, conv_weight):

FILE: artrackv2_mindspore/lib/train/_init_paths.py
  function add_path (line 9) | def add_path(path):

FILE: artrackv2_mindspore/lib/train/actors/base_actor.py
  class BaseActor (line 4) | class BaseActor:
    method __init__ (line 7) | def __init__(self, net, objective):
    method __call__ (line 16) | def __call__(self, data: TensorDict):
    method to (line 28) | def to(self, device):
    method train (line 35) | def train(self, mode=True):
    method eval (line 42) | def eval(self):

FILE: artrackv2_mindspore/lib/train/actors/ostrack.py
  function IoU (line 17) | def IoU(rect1, rect2):
  function fp16_clamp (line 43) | def fp16_clamp(x, min=None, max=None):
  function generate_sa_simdr (line 50) | def generate_sa_simdr(joints):
  function SIoU_loss (line 100) | def SIoU_loss(test1, test2, theta=4):
  function ciou (line 148) | def ciou(pred, target, eps=1e-7):
  class OSTrackActor (line 192) | class OSTrackActor(BaseActor):
    method __init__ (line 195) | def __init__(self, net, objective, loss_weight, settings, bins, search...
    method __call__ (line 212) | def __call__(self, data):
    method _bbox_clip (line 230) | def _bbox_clip(self, cx, cy, width, height, boundary):
    method get_subwindow (line 237) | def get_subwindow(self, im, pos, model_sz, original_sz, avg_chans):
    method batch_init (line 298) | def batch_init(self, images, template_bbox, initial_bbox) -> dict:
    method batch_track (line 362) | def batch_track(self, img, gt_boxes, template, dz_feat, action_mode='m...
    method explore (line 515) | def explore(self, data):
    method forward_pass (line 662) | def forward_pass(self, data):
    method compute_sequence_losses (line 721) | def compute_sequence_losses(self, data):
    method compute_losses (line 868) | def compute_losses(self, pred_dict, gt_dict, return_status=True):

FILE: artrackv2_mindspore/lib/train/admin/environment.py
  function create_default_local_file (line 6) | def create_default_local_file():
  function create_default_local_file_ITP_train (line 45) | def create_default_local_file_ITP_train(workspace_dir, data_dir):
  function env_settings (line 93) | def env_settings():

FILE: artrackv2_mindspore/lib/train/admin/local.py
  class EnvironmentSettings (line 1) | class EnvironmentSettings:
    method __init__ (line 2) | def __init__(self):

FILE: artrackv2_mindspore/lib/train/admin/settings.py
  class Settings (line 4) | class Settings:
    method __init__ (line 6) | def __init__(self):
    method set_default (line 9) | def set_default(self):

FILE: artrackv2_mindspore/lib/train/admin/stats.py
  class StatValue (line 3) | class StatValue:
    method __init__ (line 4) | def __init__(self):
    method reset (line 7) | def reset(self):
    method clear (line 10) | def clear(self):
    method update (line 14) | def update(self, val):
  class AverageMeter (line 19) | class AverageMeter(object):
    method __init__ (line 21) | def __init__(self):
    method reset (line 25) | def reset(self):
    method clear (line 31) | def clear(self):
    method update (line 35) | def update(self, val, n=1):
    method new_epoch (line 41) | def new_epoch(self):
  function topk_accuracy (line 50) | def topk_accuracy(output, target, topk=(1,)):

FILE: artrackv2_mindspore/lib/train/base_functions.py
  function update_settings (line 11) | def update_settings(settings, cfg):
  function names2datasets (line 27) | def names2datasets(name_list: list, settings, image_loader):
  function build_dataloaders (line 85) | def build_dataloaders(cfg, settings):
  function get_optimizer_scheduler (line 153) | def get_optimizer_scheduler(net, cfg):

FILE: artrackv2_mindspore/lib/train/data/bounding_box_utils.py
  function batch_center2corner (line 4) | def batch_center2corner(boxes):
  function batch_corner2center (line 15) | def batch_corner2center(boxes):
  function batch_xywh2center (line 26) | def batch_xywh2center(boxes):
  function batch_xywh2center2 (line 37) | def batch_xywh2center2(boxes):
  function batch_xywh2corner (line 49) | def batch_xywh2corner(boxes):
  function rect_to_rel (line 60) | def rect_to_rel(bb, sz_norm=None):
  function rel_to_rect (line 77) | def rel_to_rect(bb, sz_norm=None):
  function masks_to_bboxes (line 89) | def masks_to_bboxes(mask, fmt='c'):
  function masks_to_bboxes_multi (line 126) | def masks_to_bboxes_multi(mask, ids, fmt='c'):

FILE: artrackv2_mindspore/lib/train/data/image_loader.py
  function default_image_loader (line 15) | def default_image_loader(path):
  function jpeg4py_loader (line 34) | def jpeg4py_loader(path):
  function opencv_loader (line 44) | def opencv_loader(path):
  function jpeg4py_loader_w_failsafe (line 57) | def jpeg4py_loader_w_failsafe(path):
  function opencv_seg_loader (line 73) | def opencv_seg_loader(path):
  function imread_indexed (line 83) | def imread_indexed(filename):
  function imwrite_indexed (line 92) | def imwrite_indexed(filename, array, color_palette=None):

FILE: artrackv2_mindspore/lib/train/data/loader.py
  function _check_use_shared_memory (line 19) | def _check_use_shared_memory():
  function ltr_collate (line 28) | def ltr_collate(batch):
  function ltr_collate_stack1 (line 79) | def ltr_collate_stack1(batch):
  class LTRLoader (line 130) | class LTRLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 182) | def __init__(self, name, dataset, training=True, batch_size=1, shuffle...

FILE: artrackv2_mindspore/lib/train/data/processing.py
  function stack_tensors (line 8) | def stack_tensors(x):
  class BaseProcessing (line 14) | class BaseProcessing:
    method __init__ (line 18) | def __init__(self, transform=transforms.ToTensor(), template_transform...
    method __call__ (line 34) | def __call__(self, data: TensorDict):
  class STARKProcessing (line 38) | class STARKProcessing(BaseProcessing):
    method __init__ (line 48) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 69) | def _get_jittered_box(self, box, mode):
    method __call__ (line 85) | def __call__(self, data: TensorDict):

FILE: artrackv2_mindspore/lib/train/data/processing_utils.py
  function sample_target (line 12) | def sample_target(im, target_bb, search_area_factor, output_sz=None, mas...
  function transform_image_to_crop (line 82) | def transform_image_to_crop(box_in: ms.Tensor, box_extract: ms.Tensor, r...
  function jittered_center_crop (line 108) | def jittered_center_crop(frames, box_extract, box_gt, search_area_factor...
  function transform_box_to_crop (line 146) | def transform_box_to_crop(box: ms.Tensor, crop_box: ms.Tensor, crop_sz: ...

FILE: artrackv2_mindspore/lib/train/data/sampler.py
  function no_processing (line 7) | def no_processing(data):
  class TrackingSampler (line 11) | class TrackingSampler(torch.utils.data.Dataset):
    method __init__ (line 23) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
    method __len__ (line 57) | def __len__(self):
    method _sample_visible_ids (line 60) | def _sample_visible_ids(self, visible, num_ids=1, min_id=None, max_id=...
    method __getitem__ (line 94) | def __getitem__(self, index):
    method getitem (line 100) | def getitem(self):
    method getitem_cls (line 174) | def getitem_cls(self):
    method get_center_box (line 258) | def get_center_box(self, H, W, ratio=1/8):
    method sample_seq_from_dataset (line 262) | def sample_seq_from_dataset(self, dataset, is_video_dataset):
    method get_one_search (line 280) | def get_one_search(self):
    method get_frame_ids_trident (line 300) | def get_frame_ids_trident(self, visible):
    method get_frame_ids_stark (line 327) | def get_frame_ids_stark(self, visible, valid):

FILE: artrackv2_mindspore/lib/train/data/sequence_sampler.py
  class SequenceSampler (line 7) | class SequenceSampler(torch.utils.data.Dataset):
    method __init__ (line 12) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
    method __len__ (line 47) | def __len__(self):
    method _sample_visible_ids (line 50) | def _sample_visible_ids(self, visible, num_ids=1, min_id=None, max_id=...
    method _sequential_sample (line 78) | def _sequential_sample(self, visible):
    method _random_interval_sample (line 111) | def _random_interval_sample(self, visible):
    method __getitem__ (line 191) | def __getitem__(self, index):

FILE: artrackv2_mindspore/lib/train/data/transforms.py
  class Transform (line 10) | class Transform:
    method __init__ (line 35) | def __init__(self, *transforms):
    method __call__ (line 43) | def __call__(self, **inputs):
    method _split_inputs (line 65) | def _split_inputs(self, inputs):
    method __repr__ (line 77) | def __repr__(self):
  class TransformBase (line 86) | class TransformBase:
    method __init__ (line 88) | def __init__(self):
    method __call__ (line 95) | def __call__(self, **inputs):
    method _get_image_size (line 123) | def _get_image_size(self, inputs):
    method roll (line 139) | def roll(self):
    method transform_image (line 142) | def transform_image(self, image, *rand_params):
    method transform_coords (line 146) | def transform_coords(self, coords, image_shape, *rand_params):
    method transform_bbox (line 150) | def transform_bbox(self, bbox, image_shape, *rand_params):
    method transform_mask (line 172) | def transform_mask(self, mask, *rand_params):
    method transform_att (line 176) | def transform_att(self, att, *rand_params):
  class ToTensor (line 181) | class ToTensor(TransformBase):
    method transform_image (line 184) | def transform_image(self, image):
    method transfrom_mask (line 196) | def transfrom_mask(self, mask):
    method transform_att (line 200) | def transform_att(self, att):
  class ToTensorAndJitter (line 209) | class ToTensorAndJitter(TransformBase):
    method __init__ (line 211) | def __init__(self, brightness_jitter=0.0, normalize=True):
    method roll (line 216) | def roll(self):
    method transform_image (line 219) | def transform_image(self, image, brightness_factor):
    method transform_mask (line 229) | def transform_mask(self, mask, brightness_factor):
    method transform_att (line 234) | def transform_att(self, att, brightness_factor):
  class Normalize (line 243) | class Normalize(TransformBase):
    method __init__ (line 245) | def __init__(self, mean, std, inplace=False):
    method transform_image (line 251) | def transform_image(self, image):
  class ToGrayscale (line 255) | class ToGrayscale(TransformBase):
    method __init__ (line 257) | def __init__(self, probability = 0.5):
    method roll (line 262) | def roll(self):
    method transform_image (line 265) | def transform_image(self, image, do_grayscale):
  class ToBGR (line 275) | class ToBGR(TransformBase):
    method transform_image (line 277) | def transform_image(self, image):
  class RandomHorizontalFlip (line 284) | class RandomHorizontalFlip(TransformBase):
    method __init__ (line 286) | def __init__(self, probability = 0.5):
    method roll (line 290) | def roll(self):
    method transform_image (line 293) | def transform_image(self, image, do_flip):
    method transform_coords (line 300) | def transform_coords(self, coords, image_shape, do_flip):
    method transform_mask (line 307) | def transform_mask(self, mask, do_flip):
    method transform_att (line 314) | def transform_att(self, att, do_flip):
  class RandomHorizontalFlip_Norm (line 322) | class RandomHorizontalFlip_Norm(RandomHorizontalFlip):
    method __init__ (line 325) | def __init__(self, probability = 0.5):
    method transform_coords (line 329) | def transform_coords(self, coords, image_shape, do_flip):

FILE: artrackv2_mindspore/lib/train/data/wandb_logger.py
  class WandbWriter (line 10) | class WandbWriter:
    method __init__ (line 11) | def __init__(self, exp_name, cfg, output_dir, cur_step=0, step_interva...
    method write_log (line 17) | def write_log(self, stats: OrderedDict, epoch=-1):

FILE: artrackv2_mindspore/lib/train/dataset/COCO_tool.py
  function _isArrayLike (line 66) | def _isArrayLike(obj):
  class COCO (line 70) | class COCO:
    method __init__ (line 71) | def __init__(self, dataset):
    method createIndex (line 85) | def createIndex(self):
    method info (line 116) | def info(self):
    method getAnnIds (line 124) | def getAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None):
    method getCatIds (line 152) | def getCatIds(self, catNms=[], supNms=[], catIds=[]):
    method getImgIds (line 174) | def getImgIds(self, imgIds=[], catIds=[]):
    method loadAnns (line 195) | def loadAnns(self, ids=[]):
    method loadCats (line 206) | def loadCats(self, ids=[]):
    method loadImgs (line 217) | def loadImgs(self, ids=[]):
    method showAnns (line 228) | def showAnns(self, anns, draw_bbox=False):
    method loadRes (line 300) | def loadRes(self, resFile):
    method download (line 362) | def download(self, tarDir = None, imgIds = [] ):
    method loadNumpyAnnotations (line 386) | def loadNumpyAnnotations(self, data):
    method annToRLE (line 409) | def annToRLE(self, ann):
    method annToMask (line 430) | def annToMask(self, ann):

FILE: artrackv2_mindspore/lib/train/dataset/base_image_dataset.py
  class BaseImageDataset (line 5) | class BaseImageDataset(torch.utils.data.Dataset):
    method __init__ (line 8) | def __init__(self, name, root, image_loader=jpeg4py_loader):
    method __len__ (line 22) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, index):
    method get_name (line 34) | def get_name(self):
    method get_num_images (line 42) | def get_num_images(self):
    method has_class_info (line 49) | def has_class_info(self):
    method get_class_name (line 52) | def get_class_name(self, image_id):
    method get_num_classes (line 55) | def get_num_classes(self):
    method get_class_list (line 58) | def get_class_list(self):
    method get_images_in_class (line 61) | def get_images_in_class(self, class_name):
    method has_segmentation_info (line 64) | def has_segmentation_info(self):
    method get_image_info (line 67) | def get_image_info(self, seq_id):
    method get_image (line 78) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/base_video_dataset.py
  class BaseVideoDataset (line 6) | class BaseVideoDataset(torch.utils.data.Dataset):
    method __init__ (line 9) | def __init__(self, name, root, image_loader=jpeg4py_loader_w_failsafe):
    method __len__ (line 23) | def __len__(self):
    method __getitem__ (line 30) | def __getitem__(self, index):
    method is_video_sequence (line 35) | def is_video_sequence(self):
    method is_synthetic_video_dataset (line 43) | def is_synthetic_video_dataset(self):
    method get_name (line 51) | def get_name(self):
    method get_num_sequences (line 59) | def get_num_sequences(self):
    method has_class_info (line 66) | def has_class_info(self):
    method has_occlusion_info (line 69) | def has_occlusion_info(self):
    method get_num_classes (line 72) | def get_num_classes(self):
    method get_class_list (line 75) | def get_class_list(self):
    method get_sequences_in_class (line 78) | def get_sequences_in_class(self, class_name):
    method has_segmentation_info (line 81) | def has_segmentation_info(self):
    method get_sequence_info (line 84) | def get_sequence_info(self, seq_id):
    method get_frames (line 95) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/coco.py
  class MSCOCO (line 11) | class MSCOCO(BaseImageDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_image_list (line 65) | def _get_image_list(self, min_area=None):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method has_segmentation_info (line 83) | def has_segmentation_info(self):
    method get_class_list (line 86) | def get_class_list(self):
    method _build_im_per_class (line 92) | def _build_im_per_class(self):
    method get_images_in_class (line 103) | def get_images_in_class(self, class_name):
    method get_image_info (line 106) | def get_image_info(self, im_id):
    method _get_anno (line 118) | def _get_anno(self, im_id):
    method _get_image (line 123) | def _get_image(self, im_id):
    method get_meta_info (line 128) | def get_meta_info(self, im_id):
    method get_class_name (line 144) | def get_class_name(self, im_id):
    method get_image (line 148) | def get_image(self, image_id, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/coco_seq.py
  class MSCOCOSeq (line 11) | class MSCOCOSeq(BaseVideoDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_sequence_list (line 65) | def _get_sequence_list(self):
    method is_video_sequence (line 71) | def is_video_sequence(self):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method get_class_list (line 83) | def get_class_list(self):
    method has_segmentation_info (line 89) | def has_segmentation_info(self):
    method get_num_sequences (line 92) | def get_num_sequences(self):
    method _build_seq_per_class (line 95) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 106) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 109) | def get_sequence_info(self, seq_id):
    method _get_anno (line 123) | def _get_anno(self, seq_id):
    method _get_frames (line 128) | def _get_frames(self, seq_id):
    method get_meta_info (line 133) | def get_meta_info(self, seq_id):
    method get_class_name (line 150) | def get_class_name(self, seq_id):
    method get_frames (line 154) | def get_frames(self, seq_id=None, frame_ids=None, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/coco_seq_lmdb.py
  class MSCOCOSeq_lmdb (line 12) | class MSCOCOSeq_lmdb(BaseVideoDataset):
    method __init__ (line 35) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_sequence_list (line 71) | def _get_sequence_list(self):
    method is_video_sequence (line 77) | def is_video_sequence(self):
    method get_num_classes (line 80) | def get_num_classes(self):
    method get_name (line 83) | def get_name(self):
    method has_class_info (line 86) | def has_class_info(self):
    method get_class_list (line 89) | def get_class_list(self):
    method has_segmentation_info (line 95) | def has_segmentation_info(self):
    method get_num_sequences (line 98) | def get_num_sequences(self):
    method _build_seq_per_class (line 101) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 112) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 115) | def get_sequence_info(self, seq_id):
    method _get_anno (line 129) | def _get_anno(self, seq_id):
    method _get_frames (line 134) | def _get_frames(self, seq_id):
    method get_meta_info (line 140) | def get_meta_info(self, seq_id):
    method get_class_name (line 157) | def get_class_name(self, seq_id):
    method get_frames (line 161) | def get_frames(self, seq_id=None, frame_ids=None, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/got10k.py
  class Got10k (line 14) | class Got10k(BaseVideoDataset):
    method __init__ (line 26) | def __init__(self, root=None, image_loader=jpeg4py_loader, split=None,...
    method get_name (line 78) | def get_name(self):
    method has_class_info (line 81) | def has_class_info(self):
    method has_occlusion_info (line 84) | def has_occlusion_info(self):
    method _load_meta_info (line 87) | def _load_meta_info(self):
    method _read_meta (line 91) | def _read_meta(self, seq_path):
    method _build_seq_per_class (line 108) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 120) | def get_sequences_in_class(self, class_name):
    method _get_sequence_list (line 123) | def _get_sequence_list(self):
    method _read_bb_anno (line 129) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 134) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 149) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 152) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 162) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 165) | def _get_frame(self, seq_path, frame_id):
    method get_class_name (line 168) | def get_class_name(self, seq_id):
    method get_frames (line 173) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/got10k_lmdb.py
  class Got10k_lmdb (line 17) | class Got10k_lmdb(BaseVideoDataset):
    method __init__ (line 19) | def __init__(self, root=None, image_loader=jpeg4py_loader, split=None,...
    method get_name (line 71) | def get_name(self):
    method has_class_info (line 74) | def has_class_info(self):
    method has_occlusion_info (line 77) | def has_occlusion_info(self):
    method _load_meta_info (line 80) | def _load_meta_info(self):
    method _build_seq_per_class (line 103) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 115) | def get_sequences_in_class(self, class_name):
    method _get_sequence_list (line 118) | def _get_sequence_list(self):
    method _read_bb_anno (line 123) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 131) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 146) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 149) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 159) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 162) | def _get_frame(self, seq_path, frame_id):
    method get_class_name (line 165) | def get_class_name(self, seq_id):
    method get_frames (line 170) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/imagenetvid.py
  function get_target_to_image_ratio (line 11) | def get_target_to_image_ratio(seq):
  class ImagenetVID (line 17) | class ImagenetVID(BaseVideoDataset):
    method __init__ (line 29) | def __init__(self, root=None, image_loader=jpeg4py_loader, min_length=...
    method get_name (line 61) | def get_name(self):
    method get_num_sequences (line 64) | def get_num_sequences(self):
    method get_sequence_info (line 67) | def get_sequence_info(self, seq_id):
    method _get_frame (line 73) | def _get_frame(self, sequence, frame_id):
    method get_frames (line 81) | def get_frames(self, seq_id, frame_ids, anno=None):
    method _process_anno (line 103) | def _process_anno(self, root):

FILE: artrackv2_mindspore/lib/train/dataset/imagenetvid_lmdb.py
  function get_target_to_image_ratio (line 10) | def get_target_to_image_ratio(seq):
  class ImagenetVID_lmdb (line 16) | class ImagenetVID_lmdb(BaseVideoDataset):
    method __init__ (line 28) | def __init__(self, root=None, image_loader=jpeg4py_loader, min_length=...
    method get_name (line 49) | def get_name(self):
    method get_num_sequences (line 52) | def get_num_sequences(self):
    method get_sequence_info (line 55) | def get_sequence_info(self, seq_id):
    method _get_frame (line 61) | def _get_frame(self, sequence, frame_id):
    method get_frames (line 69) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/lasot.py
  class Lasot (line 14) | class Lasot(BaseVideoDataset):
    method __init__ (line 26) | def __init__(self, root=None, image_loader=jpeg4py_loader, vid_ids=Non...
    method _build_sequence_list (line 52) | def _build_sequence_list(self, vid_ids=None, split=None):
    method _build_class_list (line 70) | def _build_class_list(self):
    method get_name (line 81) | def get_name(self):
    method has_class_info (line 84) | def has_class_info(self):
    method has_occlusion_info (line 87) | def has_occlusion_info(self):
    method get_num_sequences (line 90) | def get_num_sequences(self):
    method get_num_classes (line 93) | def get_num_classes(self):
    method get_sequences_in_class (line 96) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 99) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 104) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 118) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 125) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 134) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 137) | def _get_frame(self, seq_path, frame_id):
    method _get_class (line 140) | def _get_class(self, seq_path):
    method get_class_name (line 144) | def get_class_name(self, seq_id):
    method get_frames (line 150) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/lasot_lmdb.py
  class Lasot_lmdb (line 16) | class Lasot_lmdb(BaseVideoDataset):
    method __init__ (line 18) | def __init__(self, root=None, image_loader=jpeg4py_loader, vid_ids=Non...
    method _build_sequence_list (line 47) | def _build_sequence_list(self, vid_ids=None, split=None):
    method _build_class_list (line 64) | def _build_class_list(self):
    method get_name (line 75) | def get_name(self):
    method has_class_info (line 78) | def has_class_info(self):
    method has_occlusion_info (line 81) | def has_occlusion_info(self):
    method get_num_sequences (line 84) | def get_num_sequences(self):
    method get_num_classes (line 87) | def get_num_classes(self):
    method get_sequences_in_class (line 90) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 93) | def _read_bb_anno(self, seq_path):
    method _read_target_visible (line 100) | def _read_target_visible(self, seq_path):
    method _get_sequence_path (line 114) | def _get_sequence_path(self, seq_id):
    method get_sequence_info (line 121) | def get_sequence_info(self, seq_id):
    method _get_frame_path (line 130) | def _get_frame_path(self, seq_path, frame_id):
    method _get_frame (line 133) | def _get_frame(self, seq_path, frame_id):
    method _get_class (line 136) | def _get_class(self, seq_path):
    method get_class_name (line 140) | def get_class_name(self, seq_id):
    method get_frames (line 146) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/tracking_net.py
  function list_sequences (line 14) | def list_sequences(root, set_ids):
  class TrackingNet (line 35) | class TrackingNet(BaseVideoDataset):
    method __init__ (line 46) | def __init__(self, root=None, image_loader=jpeg4py_loader, set_ids=Non...
    method _load_class_info (line 77) | def _load_class_info(self):
    method get_name (line 94) | def get_name(self):
    method has_class_info (line 97) | def has_class_info(self):
    method get_sequences_in_class (line 100) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 103) | def _read_bb_anno(self, seq_id):
    method get_sequence_info (line 111) | def get_sequence_info(self, seq_id):
    method _get_frame (line 118) | def _get_frame(self, seq_id, frame_id):
    method _get_class (line 124) | def _get_class(self, seq_id):
    method get_class_name (line 128) | def get_class_name(self, seq_id):
    method get_frames (line 133) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/dataset/tracking_net_lmdb.py
  function list_sequences (line 15) | def list_sequences(root):
  class TrackingNet_lmdb (line 30) | class TrackingNet_lmdb(BaseVideoDataset):
    method __init__ (line 41) | def __init__(self, root=None, image_loader=jpeg4py_loader, set_ids=Non...
    method _load_class_info (line 72) | def _load_class_info(self):
    method get_name (line 89) | def get_name(self):
    method has_class_info (line 92) | def has_class_info(self):
    method get_sequences_in_class (line 95) | def get_sequences_in_class(self, class_name):
    method _read_bb_anno (line 98) | def _read_bb_anno(self, seq_id):
    method get_sequence_info (line 107) | def get_sequence_info(self, seq_id):
    method _get_frame (line 114) | def _get_frame(self, seq_id, frame_id):
    method _get_class (line 120) | def _get_class(self, seq_id):
    method get_class_name (line 124) | def get_class_name(self, seq_id):
    method get_frames (line 129) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: artrackv2_mindspore/lib/train/run_training.py
  function init_seeds (line 17) | def init_seeds(seed):
  function run_training (line 29) | def run_training(script_name, config_name, cudnn_benchmark=True, local_r...
  function main (line 82) | def main():

FILE: artrackv2_mindspore/lib/train/train_script.py
  function names2datasets (line 26) | def names2datasets(name_list: list, settings, image_loader):
  function slt_collate (line 83) | def slt_collate(batch):
  class SLTLoader (line 93) | class SLTLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 101) | def __init__(self, name, dataset, training=True, batch_size=1, shuffle...
  function run (line 117) | def run(settings):

FILE: artrackv2_mindspore/lib/train/train_script_distill.py
  function build_network (line 21) | def build_network(script_name, cfg):
  function run (line 34) | def run(settings):

FILE: artrackv2_mindspore/lib/train/trainers/base_trainer.py
  class BaseTrainer (line 9) | class BaseTrainer:
    method __init__ (line 13) | def __init__(self, actor, loaders, optimizer, settings, lr_scheduler=N...
    method update_settings (line 40) | def update_settings(self, settings=None):
    method train (line 62) | def train(self, max_epochs, load_latest=False, fail_safe=True, load_pr...
    method train_epoch (line 113) | def train_epoch(self):
    method save_checkpoint (line 116) | def save_checkpoint(self):
    method load_checkpoint (line 150) | def load_checkpoint(self, checkpoint = None, fields = None, ignore_fie...
    method load_state_dict (line 232) | def load_state_dict(self, checkpoint=None, distill=False):

FILE: artrackv2_mindspore/lib/train/trainers/ltr_trainer.py
  class LTRTrainer (line 20) | class LTRTrainer(BaseTrainer):
    method __init__ (line 21) | def __init__(self, actor, loaders, optimizer, settings, lr_scheduler=N...
    method _set_default_settings (line 59) | def _set_default_settings(self):
    method cycle_dataset (line 70) | def cycle_dataset(self, loader):
    method train_epoch (line 224) | def train_epoch(self):
    method _init_timing (line 237) | def _init_timing(self):
    method _update_stats (line 245) | def _update_stats(self, new_stats: OrderedDict, batch_size, loader):
    method _print_stats (line 264) | def _print_stats(self, i, loader, batch_size):
    method _stats_new_epoch (line 300) | def _stats_new_epoch(self):

FILE: artrackv2_mindspore/lib/utils/box_ops.py
  function box_xywh_to_cxywh (line 4) | def box_xywh_to_cxywh(x):
  function box_cxcywh_to_xyxy (line 9) | def box_cxcywh_to_xyxy(x):
  function box_xywh_to_xyxy (line 16) | def box_xywh_to_xyxy(x):
  function box_xyxy_to_xywh (line 22) | def box_xyxy_to_xywh(x):
  function box_xyxy_to_cxcywh (line 28) | def box_xyxy_to_cxcywh(x):
  function box_iou (line 39) | def box_iou(boxes1, boxes2):
  function generalized_box_iou (line 64) | def generalized_box_iou(boxes1, boxes2):
  function giou_loss (line 89) | def giou_loss(boxes1, boxes2):
  function clip_box (line 100) | def clip_box(box: list, H, W, margin=0):

FILE: artrackv2_mindspore/lib/utils/ce_utils.py
  function generate_bbox_mask (line 1) | def generate_bbox_mask(bbox_mask, bbox):
  function generate_mask_cond (line 9) | def generate_mask_cond(cfg, bs, device, gt_bbox):
  function adjust_keep_rate (line 62) | def adjust_keep_rate(epoch, warmup_epochs, total_epochs, ITERS_PER_EPOCH...

FILE: artrackv2_mindspore/lib/utils/focal_loss.py
  class FocalLoss (line 8) | class FocalLoss(nn.Module, ABC):
    method __init__ (line 9) | def __init__(self, alpha=2, beta=4):
    method forward (line 14) | def forward(self, prediction, target):
  class LBHinge (line 38) | class LBHinge(nn.Module):
    method __init__ (line 47) | def __init__(self, error_metric=nn.MSELoss(), threshold=None, clip=None):
    method forward (line 53) | def forward(self, prediction, label, target_bb=None):

FILE: artrackv2_mindspore/lib/utils/heapmap_utils.py
  function generate_heatmap (line 5) | def generate_heatmap(bboxes, patch_size=320, stride=16):
  class CenterNetHeatMap (line 29) | class CenterNetHeatMap(object):
    method generate_score_map (line 31) | def generate_score_map(fmap, gt_class, gt_wh, centers_int, min_overlap):
    method get_gaussian_radius (line 40) | def get_gaussian_radius(box_size, min_overlap):
    method gaussian2D (line 71) | def gaussian2D(radius, sigma=1):
    method draw_gaussian (line 81) | def draw_gaussian(fmap, center, radius, k=1):
  function compute_grids (line 99) | def compute_grids(features, strides):
  function get_center3x3 (line 123) | def get_center3x3(locations, centers, strides, range=3):
  function get_pred (line 143) | def get_pred(score_map_ctr, size_map, offset_map, feat_size):

FILE: artrackv2_mindspore/lib/utils/lmdb_utils.py
  function get_lmdb_handle (line 11) | def get_lmdb_handle(name):
  function decode_img (line 23) | def decode_img(lmdb_fname, key_name):
  function decode_str (line 33) | def decode_str(lmdb_fname, key_name):
  function decode_json (line 40) | def decode_json(lmdb_fname, key_name):

FILE: artrackv2_mindspore/lib/utils/merge.py
  function merge_template_search (line 4) | def merge_template_search(inp_list, return_search=False, return_template...
  function get_qkv (line 18) | def get_qkv(inp_list):

FILE: artrackv2_mindspore/lib/utils/misc.py
  class SmoothedValue (line 27) | class SmoothedValue(object):
    method __init__ (line 32) | def __init__(self, window_size=20, fmt=None):
    method update (line 40) | def update(self, value, n=1):
    method synchronize_between_processes (line 45) | def synchronize_between_processes(self):
    method median (line 59) | def median(self):
    method avg (line 64) | def avg(self):
    method global_avg (line 69) | def global_avg(self):
    method max (line 73) | def max(self):
    method value (line 77) | def value(self):
    method __str__ (line 80) | def __str__(self):
  function all_gather (line 89) | def all_gather(data):
  function reduce_dict (line 132) | def reduce_dict(input_dict, average=True):
  class MetricLogger (line 159) | class MetricLogger(object):
    method __init__ (line 160) | def __init__(self, delimiter="\t"):
    method update (line 164) | def update(self, **kwargs):
    method __getattr__ (line 171) | def __getattr__(self, attr):
    method __str__ (line 179) | def __str__(self):
    method synchronize_between_processes (line 187) | def synchronize_between_processes(self):
    method add_meter (line 191) | def add_meter(self, name, meter):
    method log_every (line 194) | def log_every(self, iterable, print_freq, header=None):
  function get_sha (line 249) | def get_sha():
  function collate_fn (line 269) | def collate_fn(batch):
  function _max_by_axis (line 275) | def _max_by_axis(the_list):
  class NestedTensor (line 284) | class NestedTensor(object):
    method __init__ (line 285) | def __init__(self, tensors, mask: Optional[Tensor]):
    method to (line 289) | def to(self, device):
    method decompose (line 300) | def decompose(self):
    method __repr__ (line 303) | def __repr__(self):
  function nested_tensor_from_tensor_list (line 307) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  function _onnx_nested_tensor_from_tensor_list (line 335) | def _onnx_nested_tensor_from_tensor_list(tensor_list: List[Tensor]) -> N...
  function setup_for_distributed (line 363) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 378) | def is_dist_avail_and_initialized():
  function get_world_size (line 386) | def get_world_size():
  function get_rank (line 392) | def get_rank():
  function is_main_process (line 398) | def is_main_process():
  function save_on_master (line 402) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 407) | def init_distributed_mode(args):
  function accuracy (line 433) | def accuracy(output, target, topk=(1,)):
  function interpolate (line 451) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...

FILE: artrackv2_mindspore/lib/utils/tensor.py
  class TensorDict (line 7) | class TensorDict(OrderedDict):
    method concat (line 10) | def concat(self, other):
    method copy (line 14) | def copy(self):
    method __deepcopy__ (line 17) | def __deepcopy__(self, memodict={}):
    method __getattr__ (line 20) | def __getattr__(self, name):
    method attribute (line 28) | def attribute(self, attr: str, *args):
    method apply (line 31) | def apply(self, fn, *args, **kwargs):
    method _iterable (line 35) | def _iterable(a):
  class TensorList (line 39) | class TensorList(list):
    method __init__ (line 42) | def __init__(self, list_of_tensors = None):
    method __deepcopy__ (line 47) | def __deepcopy__(self, memodict={}):
    method __getitem__ (line 50) | def __getitem__(self, item):
    method __add__ (line 58) | def __add__(self, other):
    method __radd__ (line 63) | def __radd__(self, other):
    method __iadd__ (line 68) | def __iadd__(self, other):
    method __sub__ (line 77) | def __sub__(self, other):
    method __rsub__ (line 82) | def __rsub__(self, other):
    method __isub__ (line 87) | def __isub__(self, other):
    method __mul__ (line 96) | def __mul__(self, other):
    method __rmul__ (line 101) | def __rmul__(self, other):
    method __imul__ (line 106) | def __imul__(self, other):
    method __truediv__ (line 115) | def __truediv__(self, other):
    method __rtruediv__ (line 120) | def __rtruediv__(self, other):
    method __itruediv__ (line 125) | def __itruediv__(self, other):
    method __matmul__ (line 134) | def __matmul__(self, other):
    method __rmatmul__ (line 139) | def __rmatmul__(self, other):
    method __imatmul__ (line 144) | def __imatmul__(self, other):
    method __mod__ (line 153) | def __mod__(self, other):
    method __rmod__ (line 158) | def __rmod__(self, other):
    method __pos__ (line 163) | def __pos__(self):
    method __neg__ (line 166) | def __neg__(self):
    method __le__ (line 169) | def __le__(self, other):
    method __ge__ (line 174) | def __ge__(self, other):
    method concat (line 179) | def concat(self, other):
    method copy (line 182) | def copy(self):
    method unroll (line 185) | def unroll(self):
    method list (line 197) | def list(self):
    method attribute (line 200) | def attribute(self, attr: str, *args):
    method apply (line 203) | def apply(self, fn):
    method __getattr__ (line 206) | def __getattr__(self, name):
    method _iterable (line 216) | def _iterable(a):
  function tensor_operation (line 220) | def tensor_operation(op):

FILE: artrackv2_mindspore/lib/utils/variable_hook.py
  class get_local (line 5) | class get_local(object):
    method __init__ (line 9) | def __init__(self, varname):
    method __call__ (line 12) | def __call__(self, func):
    method clear (line 44) | def clear(cls):
    method activate (line 49) | def activate(cls):

FILE: artrackv2_mindspore/lib/vis/plotting.py
  function draw_figure (line 7) | def draw_figure(fig):
  function show_tensor (line 13) | def show_tensor(a: torch.Tensor, fig_num = None, title = None, range=(No...
  function plot_graph (line 43) | def plot_graph(a: torch.Tensor, fig_num = None, title = None):
  function show_image_with_boxes (line 61) | def show_image_with_boxes(im, boxes, iou_pred=None, disp_ids=None):
  function _pascal_color_map (line 86) | def _pascal_color_map(N=256, normalized=False):
  function overlay_mask (line 113) | def overlay_mask(im, ann, alpha=0.5, colors=None, contour_thickness=None):

FILE: artrackv2_mindspore/lib/vis/utils.py
  function numpy_to_torch (line 5) | def numpy_to_torch(a: np.ndarray):

FILE: artrackv2_mindspore/tracking/_init_paths.py
  function add_path (line 9) | def add_path(path):

FILE: artrackv2_mindspore/tracking/analysis_results_ITP.py
  function parse_args (line 7) | def parse_args():

FILE: artrackv2_mindspore/tracking/create_default_local_file.py
  function parse_args (line 8) | def parse_args():

FILE: artrackv2_mindspore/tracking/download_pytracking_results.py
  function _download_file (line 52) | def _download_file(file_id, path):
  function download_results (line 57) | def download_results(download_path, trackers='pytracking'):
  function unpack_tracking_results (line 117) | def unpack_tracking_results(download_path, output_path=None):
  function main (line 155) | def main():

FILE: artrackv2_mindspore/tracking/pre_read_datasets.py
  function parse_args (line 10) | def parse_args():
  function get_trknet_dict (line 22) | def get_trknet_dict(trknet_dir):
  function target (line 34) | def target(lmdb_dir, key_name):

FILE: artrackv2_mindspore/tracking/profile_model.py
  function parse_args (line 17) | def parse_args():
  function evaluate_vit (line 31) | def evaluate_vit(model, template, search, seq_input, stage):
  function evaluate_vit_separate (line 65) | def evaluate_vit_separate(model, template, search):
  function get_data (line 86) | def get_data(bs, sz):

FILE: artrackv2_mindspore/tracking/test.py
  function run_tracker (line 17) | def run_tracker(tracker_name, tracker_param, run_id=None, dataset_name='...
  function main (line 39) | def main():

FILE: artrackv2_mindspore/tracking/test_exp.py
  function run_tracker (line 14) | def run_tracker(tracker_name, tracker_param, run_id=None, dataset_name='...
  function main (line 37) | def main():

FILE: artrackv2_mindspore/tracking/train.py
  function parse_args (line 7) | def parse_args():
  function main (line 39) | def main():

FILE: artrackv2_mindspore/tracking/video_demo.py
  function run_video (line 12) | def run_video(tracker_name, tracker_param, videofile, optional_box=None,...
  function main (line 23) | def main():

FILE: artrackv2_mindspore/tracking/vis_results.py
  class VisResults (line 20) | class VisResults(object):
    method __init__ (line 21) | def __init__(self):
    method vis_dataset (line 24) | def vis_dataset(self, dataset, trackers, skip_missing_seq=False, seq_l...
    method update_boxes (line 79) | def update_boxes(self, data, caption):
    method update_seg_result (line 83) | def update_seg_result(self, frame_img, frame_path):
    method _init_visdom (line 97) | def _init_visdom(self, visdom_info=None):
    method _visdom_ui_handler (line 118) | def _visdom_ui_handler(self, data):

FILE: external/AR/ltr/actors/base_actor.py
  class BaseActor (line 4) | class BaseActor:
    method __init__ (line 7) | def __init__(self, net, objective):
    method __call__ (line 16) | def __call__(self, data: TensorDict):
    method to (line 28) | def to(self, device):
    method train (line 35) | def train(self, mode=True):
    method eval (line 42) | def eval(self):

FILE: external/AR/ltr/actors/bbreg.py
  class AtomActor (line 4) | class AtomActor(BaseActor):
    method __call__ (line 6) | def __call__(self, data):
  class AtomBBKLActor (line 32) | class AtomBBKLActor(BaseActor):
    method __call__ (line 34) | def __call__(self, data):

FILE: external/AR/ltr/actors/tracking.py
  class DiMPActor (line 5) | class DiMPActor(BaseActor):
    method __init__ (line 7) | def __init__(self, net, objective, loss_weight=None):
    method __call__ (line 13) | def __call__(self, data):
  class KLDiMPActor (line 73) | class KLDiMPActor(BaseActor):
    method __init__ (line 75) | def __init__(self, net, objective, loss_weight=None):
    method __call__ (line 81) | def __call__(self, data):

FILE: external/AR/ltr/admin/environment.py
  function create_default_local_file (line 6) | def create_default_local_file():
  function env_settings (line 44) | def env_settings():

FILE: external/AR/ltr/admin/loading.py
  function load_trained_network (line 10) | def load_trained_network(workspace_dir, network_path, checkpoint=None):
  function load_pretrained (line 19) | def load_pretrained(module, name, checkpoint=None, **kwargs):
  function load_network (line 34) | def load_network(network_dir=None, checkpoint=None, constructor_fun_name...
  function load_weights (line 111) | def load_weights(net, path, strict=True):
  function torch_load_legacy (line 118) | def torch_load_legacy(path):
  function _setup_legacy_env (line 133) | def _setup_legacy_env():
  function _cleanup_legacy_env (line 144) | def _cleanup_legacy_env():

FILE: external/AR/ltr/admin/model_constructor.py
  function model_constructor (line 5) | def model_constructor(f):
  class NetConstructor (line 24) | class NetConstructor:
    method __init__ (line 28) | def __init__(self, fun_name, fun_module, args, kwds):
    method get (line 41) | def get(self):

FILE: external/AR/ltr/admin/multigpu.py
  function is_multi_gpu (line 4) | def is_multi_gpu(net):
  class MultiGPU (line 8) | class MultiGPU(nn.DataParallel):
    method __getattr__ (line 10) | def __getattr__(self, item):

FILE: external/AR/ltr/admin/settings.py
  class Settings (line 4) | class Settings:
    method __init__ (line 6) | def __init__(self):
    method set_default (line 9) | def set_default(self):

FILE: external/AR/ltr/admin/stats.py
  class StatValue (line 3) | class StatValue:
    method __init__ (line 4) | def __init__(self):
    method reset (line 7) | def reset(self):
    method clear (line 10) | def clear(self):
    method update (line 14) | def update(self, val):
  class AverageMeter (line 19) | class AverageMeter(object):
    method __init__ (line 21) | def __init__(self):
    method reset (line 25) | def reset(self):
    method clear (line 31) | def clear(self):
    method update (line 35) | def update(self, val, n=1):
    method new_epoch (line 41) | def new_epoch(self):
  function topk_accuracy (line 50) | def topk_accuracy(output, target, topk=(1,)):

FILE: external/AR/ltr/admin/tensorboard.py
  class TensorboardWriter (line 10) | class TensorboardWriter:
    method __init__ (line 11) | def __init__(self, directory, loader_names):
    method write_info (line 15) | def write_info(self, module_name, script_name, description):
    method write_epoch (line 22) | def write_epoch(self, stats: OrderedDict, epoch: int, ind=-1):

FILE: external/AR/ltr/data/bounding_box_utils.py
  function rect_to_rel (line 4) | def rect_to_rel(bb, sz_norm=None):
  function rel_to_rect (line 21) | def rel_to_rect(bb, sz_norm=None):
  function masks_to_bboxes (line 33) | def masks_to_bboxes(mask, fmt='c'):
  function masks_to_bboxes_multi (line 70) | def masks_to_bboxes_multi(mask, ids, fmt='c'):

FILE: external/AR/ltr/data/image_loader.py
  function default_image_loader (line 15) | def default_image_loader(path):
  function jpeg4py_loader (line 34) | def jpeg4py_loader(path):
  function opencv_loader (line 44) | def opencv_loader(path):
  function jpeg4py_loader_w_failsafe (line 57) | def jpeg4py_loader_w_failsafe(path):
  function opencv_seg_loader (line 73) | def opencv_seg_loader(path):
  function imread_indexed (line 83) | def imread_indexed(filename):
  function imwrite_indexed (line 92) | def imwrite_indexed(filename, array, color_palette=None):

FILE: external/AR/ltr/data/loader.py
  function _check_use_shared_memory (line 9) | def _check_use_shared_memory():
  function ltr_collate (line 18) | def ltr_collate(batch):
  function ltr_collate_stack1 (line 69) | def ltr_collate_stack1(batch):
  class LTRLoader (line 120) | class LTRLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 172) | def __init__(self, name, dataset, training=True, batch_size=1, shuffle...

FILE: external/AR/ltr/data/processing.py
  function stack_tensors (line 7) | def stack_tensors(x):
  class BaseProcessing (line 13) | class BaseProcessing:
    method __init__ (line 17) | def __init__(self, transform=transforms.ToTensor(), train_transform=No...
    method __call__ (line 33) | def __call__(self, data: TensorDict):
  class ATOMProcessing (line 37) | class ATOMProcessing(BaseProcessing):
    method __init__ (line 47) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 69) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 85) | def _generate_proposals(self, box):
    method __call__ (line 114) | def __call__(self, data: TensorDict):
  class KLBBregProcessing (line 157) | class KLBBregProcessing(BaseProcessing):
    method __init__ (line 162) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 184) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 200) | def _generate_proposals(self, box):
    method __call__ (line 213) | def __call__(self, data: TensorDict):
  class ATOMwKLProcessing (line 257) | class ATOMwKLProcessing(BaseProcessing):
    method __init__ (line 259) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 269) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 285) | def _generate_proposals(self, box):
    method __call__ (line 296) | def __call__(self, data: TensorDict):
  class DiMPProcessing (line 334) | class DiMPProcessing(BaseProcessing):
    method __init__ (line 347) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 378) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 394) | def _generate_proposals(self, box):
    method _generate_label_function (line 426) | def _generate_label_function(self, target_bb):
    method __call__ (line 442) | def __call__(self, data: TensorDict):
  class KLDiMPProcessing (line 491) | class KLDiMPProcessing(BaseProcessing):
    method __init__ (line 496) | def __init__(self, search_area_factor, output_sz, center_jitter_factor...
    method _get_jittered_box (line 530) | def _get_jittered_box(self, box, mode):
    method _generate_proposals (line 546) | def _generate_proposals(self, box):
    method _generate_label_function (line 560) | def _generate_label_function(self, target_bb):
    method _generate_label_density (line 576) | def _generate_label_density(self, target_bb):
    method __call__ (line 605) | def __call__(self, data: TensorDict):

FILE: external/AR/ltr/data/processing_utils.py
  function sample_target (line 9) | def sample_target(im, target_bb, search_area_factor, output_sz=None, mas...
  function transform_image_to_crop (line 68) | def transform_image_to_crop(box_in: torch.Tensor, box_extract: torch.Ten...
  function jittered_center_crop (line 91) | def jittered_center_crop(frames, box_extract, box_gt, search_area_factor...
  function sample_target_adaptive (line 128) | def sample_target_adaptive(im, target_bb, search_area_factor, output_sz,...
  function crop_and_resize (line 240) | def crop_and_resize(im, box, crop_bb, output_sz, mask=None):
  function transform_box_to_crop (line 298) | def transform_box_to_crop(box: torch.Tensor, crop_box: torch.Tensor, cro...
  function target_image_crop (line 319) | def target_image_crop(frames, box_extract, box_gt, search_area_factor, o...
  function iou (line 371) | def iou(reference, proposals):
  function rand_uniform (line 394) | def rand_uniform(a, b, shape=1):
  function perturb_box (line 407) | def perturb_box(box, min_iou=0.5, sigma_factor=0.1):
  function gauss_1d (line 469) | def gauss_1d(sz, sigma, center, end_pad=0, density=False):
  function gauss_2d (line 477) | def gauss_2d(sz, sigma, center, end_pad=(0, 0), density=False):
  function gaussian_label_function (line 484) | def gaussian_label_function(target_bb, sigma_factor, kernel_sz, feat_sz,...
  function gauss_density_centered (line 520) | def gauss_density_centered(x, std):
  function gmm_density_centered (line 529) | def gmm_density_centered(x, std):
  function sample_gmm_centered (line 542) | def sample_gmm_centered(std, num_samples=1):
  function sample_gmm (line 564) | def sample_gmm(mean, std, num_samples=1):
  function sample_box_gmm (line 589) | def sample_box_gmm(mean_box, proposal_sigma, gt_sigma=None, num_samples=...

FILE: external/AR/ltr/data/processing_utils_SE.py
  function stack_tensors (line 8) | def stack_tensors(x):
  function sample_target_SE (line 15) | def sample_target_SE(im, target_bb, search_area_factor, output_sz=None, ...
  function map_mask_back (line 66) | def map_mask_back(im, target_bb, search_area_factor, mask, mode=cv.BORDE...
  function transform_image_to_crop_SE (line 114) | def transform_image_to_crop_SE(box_in: torch.Tensor, box_extract: torch....
  function centered_crop (line 146) | def centered_crop(frames, anno, area_factor, output_sz):
  function jittered_center_crop_SE (line 162) | def jittered_center_crop_SE(frames, box_extract, box_gt, search_area_fac...
  function sample_target_nopad (line 196) | def sample_target_nopad(im, target_bb, search_area_factor, output_sz):
  function transform_box_to_crop (line 255) | def transform_box_to_crop(box: torch.Tensor, crop_box: torch.Tensor, cro...
  function jittered_center_crop_nopad (line 276) | def jittered_center_crop_nopad(frames, box_extract, box_gt, search_area_...
  function iou (line 312) | def iou(reference, proposals):
  function rand_uniform (line 335) | def rand_uniform(a, b, shape=1):
  function perturb_box (line 348) | def perturb_box(box, min_iou=0.5, sigma_factor=0.1):
  function gauss_1d (line 410) | def gauss_1d(sz, sigma, center, end_pad=0):
  function gauss_2d (line 415) | def gauss_2d(sz, sigma, center, end_pad=(0, 0)):
  function gaussian_label_function (line 422) | def gaussian_label_function(target_bb, sigma_factor, kernel_sz, feat_sz,...

FILE: external/AR/ltr/data/sampler.py
  function no_processing (line 6) | def no_processing(data):
  class TrackingSampler (line 10) | class TrackingSampler(torch.utils.data.Dataset):
    method __init__ (line 25) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
    method __len__ (line 56) | def __len__(self):
    method _sample_visible_ids (line 59) | def _sample_visible_ids(self, visible, num_ids=1, min_id=None, max_id=...
    method __getitem__ (line 86) | def __getitem__(self, index):
  class DiMPSampler (line 172) | class DiMPSampler(TrackingSampler):
    method __init__ (line 175) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,
  class ATOMSampler (line 182) | class ATOMSampler(TrackingSampler):
    method __init__ (line 185) | def __init__(self, datasets, p_datasets, samples_per_epoch, max_gap,

FILE: external/AR/ltr/data/transforms.py
  class Transform (line 10) | class Transform:
    method __init__ (line 35) | def __init__(self, *transforms):
    method __call__ (line 43) | def __call__(self, **inputs):
    method _split_inputs (line 65) | def _split_inputs(self, inputs):
    method __repr__ (line 77) | def __repr__(self):
  class TransformBase (line 86) | class TransformBase:
    method __init__ (line 88) | def __init__(self):
    method __call__ (line 94) | def __call__(self, **inputs):
    method _get_image_size (line 122) | def _get_image_size(self, inputs):
    method roll (line 138) | def roll(self):
    method transform_image (line 141) | def transform_image(self, image, *rand_params):
    method transform_coords (line 145) | def transform_coords(self, coords, image_shape, *rand_params):
    method transform_bbox (line 149) | def transform_bbox(self, bbox, image_shape, *rand_params):
    method transform_mask (line 171) | def transform_mask(self, mask, *rand_params):
  class ToTensor (line 176) | class ToTensor(TransformBase):
    method transform_image (line 179) | def transform_image(self, image):
    method transfrom_mask (line 191) | def transfrom_mask(self, mask):
  class ToTensorAndJitter (line 197) | class ToTensorAndJitter(TransformBase):
    method __init__ (line 199) | def __init__(self, brightness_jitter=0.0, normalize=True):
    method roll (line 204) | def roll(self):
    method transform_image (line 207) | def transform_image(self, image, brightness_factor):
    method transform_mask (line 217) | def transform_mask(self, mask, brightness_factor):
  class Normalize (line 224) | class Normalize(TransformBase):
    method __init__ (line 226) | def __init__(self, mean, std, inplace=False):
    method transform_image (line 232) | def transform_image(self, image):
  class ToGrayscale (line 236) | class ToGrayscale(TransformBase):
    method __init__ (line 238) | def __init__(self, probability = 0.5):
    method roll (line 243) | def roll(self):
    method transform_image (line 246) | def transform_image(self, image, do_grayscale):
  class ToBGR (line 256) | class ToBGR(TransformBase):
    method transform_image (line 258) | def transform_image(self, image):
  class RandomHorizontalFlip (line 265) | class RandomHorizontalFlip(TransformBase):
    method __init__ (line 267) | def __init__(self, probability = 0.5):
    method roll (line 271) | def roll(self):
    method transform_image (line 274) | def transform_image(self, image, do_flip):
    method transform_coords (line 281) | def transform_coords(self, coords, image_shape, do_flip):
    method transform_mask (line 287) | def transform_mask(self, mask, do_flip):
  class Blur (line 295) | class Blur(TransformBase):
    method __init__ (line 297) | def __init__(self, sigma):
    method transform_image (line 308) | def transform_image(self, image):
  class RandomBlur (line 317) | class RandomBlur(TransformBase):
    method __init__ (line 319) | def __init__(self, sigma, probability=0.1):
    method roll (line 332) | def roll(self):
    method transform (line 335) | def transform(self, image, do_blur=None):
  class RandomAffine (line 350) | class RandomAffine(TransformBase):
    method __init__ (line 352) | def __init__(self, p_flip=0.0, max_rotation=0.0, max_shear=0.0, max_sc...
    method roll (line 370) | def roll(self):
    method _construct_t_mat (line 382) | def _construct_t_mat(self, image_shape, do_flip, theta, shear_values, ...
    method transform_image (line 411) | def transform_image(self, image, do_flip, theta, shear_values, scale_f...
    method transform_coords (line 422) | def transform_coords(self, coords, image_shape, do_flip, theta, shear_...
    method transform_mask (line 433) | def transform_mask(self, mask, do_flip, theta, shear_values, scale_fac...

FILE: external/AR/ltr/dataset/base_image_dataset.py
  class BaseImageDataset (line 5) | class BaseImageDataset(torch.utils.data.Dataset):
    method __init__ (line 8) | def __init__(self, name, root, image_loader=jpeg4py_loader):
    method __len__ (line 22) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, index):
    method get_name (line 34) | def get_name(self):
    method get_num_images (line 42) | def get_num_images(self):
    method has_class_info (line 49) | def has_class_info(self):
    method get_class_name (line 52) | def get_class_name(self, image_id):
    method get_num_classes (line 55) | def get_num_classes(self):
    method get_class_list (line 58) | def get_class_list(self):
    method get_images_in_class (line 61) | def get_images_in_class(self, class_name):
    method has_segmentation_info (line 64) | def has_segmentation_info(self):
    method get_image_info (line 67) | def get_image_info(self, seq_id):
    method get_image (line 78) | def get_image(self, image_id, anno=None):

FILE: external/AR/ltr/dataset/base_video_dataset.py
  class BaseVideoDataset (line 5) | class BaseVideoDataset(torch.utils.data.Dataset):
    method __init__ (line 8) | def __init__(self, name, root, image_loader=jpeg4py_loader):
    method __len__ (line 22) | def __len__(self):
    method __getitem__ (line 29) | def __getitem__(self, index):
    method is_video_sequence (line 34) | def is_video_sequence(self):
    method is_synthetic_video_dataset (line 42) | def is_synthetic_video_dataset(self):
    method get_name (line 50) | def get_name(self):
    method get_num_sequences (line 58) | def get_num_sequences(self):
    method has_class_info (line 65) | def has_class_info(self):
    method has_occlusion_info (line 68) | def has_occlusion_info(self):
    method get_num_classes (line 71) | def get_num_classes(self):
    method get_class_list (line 74) | def get_class_list(self):
    method get_sequences_in_class (line 77) | def get_sequences_in_class(self, class_name):
    method has_segmentation_info (line 80) | def has_segmentation_info(self):
    method get_sequence_info (line 83) | def get_sequence_info(self, seq_id):
    method get_frames (line 94) | def get_frames(self, seq_id, frame_ids, anno=None):

FILE: external/AR/ltr/dataset/coco.py
  class MSCOCO (line 11) | class MSCOCO(BaseImageDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_image_list (line 65) | def _get_image_list(self, min_area=None):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method has_segmentation_info (line 83) | def has_segmentation_info(self):
    method get_class_list (line 86) | def get_class_list(self):
    method _build_im_per_class (line 92) | def _build_im_per_class(self):
    method get_images_in_class (line 103) | def get_images_in_class(self, class_name):
    method get_image_info (line 106) | def get_image_info(self, im_id):
    method _get_anno (line 118) | def _get_anno(self, im_id):
    method _get_image (line 123) | def _get_image(self, im_id):
    method get_meta_info (line 128) | def get_meta_info(self, im_id):
    method get_class_name (line 144) | def get_class_name(self, im_id):
    method get_image (line 148) | def get_image(self, image_id, anno=None):

FILE: external/AR/ltr/dataset/coco_seq.py
  class MSCOCOSeq (line 11) | class MSCOCOSeq(BaseVideoDataset):
    method __init__ (line 34) | def __init__(self, root=None, image_loader=jpeg4py_loader, data_fracti...
    method _get_sequence_list (line 65) | def _get_sequence_list(self):
    method is_video_sequence (line 71) | def is_video_sequence(self):
    method get_num_classes (line 74) | def get_num_classes(self):
    method get_name (line 77) | def get_name(self):
    method has_class_info (line 80) | def has_class_info(self):
    method get_class_list (line 83) | def get_class_list(self):
    method has_segmentation_info (line 89) | def has_segmentation_info(self):
    method get_num_sequences (line 92) | def get_num_sequences(self):
    method _build_seq_per_class (line 95) | def _build_seq_per_class(self):
    method get_sequences_in_class (line 106) | def get_sequences_in_class(self, class_name):
    method get_sequence_info (line 109) | def get_sequence_info(self, seq_id):
    method _get_anno (line 121) | def _get_anno(self, seq_id):
    method _get_frames (line 126) | def _get_frames(self, seq_id):
    method get_meta_info (line 131) | def get_meta_info(self, seq_id):
    method get_class_name (line 148) | def get_class_name(self, seq_id):
    method get_frames (line 152) | def get_frames(self, seq_id=None, frame_ids=None, anno=None):

FILE: external/AR/ltr/dataset/davis.py
  class Davis (line 8) | class Davis(VOSDatasetBase):
    method __init__ (line 19) | def __init__(self, root=None, sequences=None, version='2017', split='t...
    method _construct_sequence (line 76) | def _construct

[
  {
    "path": "ARTrack_env_cuda113.yaml",
    "chars": 14787,
    "preview": "name: artrack\nchannels:\n  - http://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch\n  - http://mirrors.tuna.tsinghua."
  },
  {
    "path": "LICENSE",
    "chars": 11357,
    "preview": "                                 Apache License\n                           Version 2.0, January 2004\n                   "
  },
  {
    "path": "README.md",
    "chars": 13756,
    "preview": "# ARTrack\r\n\r\n[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/artrackv2-prompting-autore"
  },
  {
    "path": "artrackv2_mindspore/.gitignore",
    "chars": 172,
    "preview": "test/\nlib/models/__pycache__/\nlib/config/__pycache__/\nlib/test/tracker/__pycache__/\nlib/models/__pycache__/\nlib/config/o"
  },
  {
    "path": "artrackv2_mindspore/README.md",
    "chars": 398,
    "preview": "# ARTrackV2\n\n## Evaluation\n\nMake sure you have installed the GPU version of MindSpore according to [link](https://www.mi"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/2stage_256_got.yaml",
    "chars": 1398,
    "preview": "DATA:\r\n  MAX_SAMPLE_INTERVAL: 200\r\n  MEAN:\r\n  - 0.485\r\n  - 0.456\r\n  - 0.406\r\n  SEARCH:\r\n    CENTER_JITTER: 3\r\n    FACTOR"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/best_384.yaml",
    "chars": 1268,
    "preview": "DATA:\r\n  MAX_SAMPLE_INTERVAL: 200\r\n  MEAN:\r\n  - 0.485\r\n  - 0.456\r\n  - 0.406\r\n  SEARCH:\r\n    CENTER_JITTER: 4.5\r\n    FACT"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/finetune.yaml",
    "chars": 1258,
    "preview": "DATA:\r\n  MAX_SAMPLE_INTERVAL: 200\r\n  MEAN:\r\n  - 0.485\r\n  - 0.456\r\n  - 0.406\r\n  SEARCH:\r\n    CENTER_JITTER: 3\r\n    FACTOR"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/finetune_384.yaml",
    "chars": 1403,
    "preview": "DATA:\r\n  MAX_SAMPLE_INTERVAL: 200\r\n  MEAN:\r\n  - 0.485\r\n  - 0.456\r\n  - 0.406\r\n  SEARCH:\r\n    CENTER_JITTER: 4.5\r\n    FACT"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/finetune_384_got.yaml",
    "chars": 1217,
    "preview": "DATA:\r\n  MAX_SAMPLE_INTERVAL: 200\r\n  MEAN:\r\n  - 0.485\r\n  - 0.456\r\n  - 0.406\r\n  SEARCH:\r\n    CENTER_JITTER: 4.5\r\n    FACT"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_256_mae_32x4_ep300.yaml",
    "chars": 1336,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 3\n    FACTOR: 4.0\n  "
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_256_mae_ce_32x4_ep300.yaml",
    "chars": 1446,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 3\n    FACTOR: 4.0\n  "
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_256_mae_ce_32x4_got10k_ep100.yaml",
    "chars": 1192,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 3\n    FACTOR: 4.0\n  "
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_384_mae_32x4_ep300.yaml",
    "chars": 1317,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 4.5\n    FACTOR: 5.0\n"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_384_mae_ce_32x4_ep300.yaml",
    "chars": 1462,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 4.5\n    FACTOR: 5.0\n"
  },
  {
    "path": "artrackv2_mindspore/experiments/ostrack/vitb_384_mae_ce_32x4_got10k_ep100.yaml",
    "chars": 1404,
    "preview": "DATA:\n  MAX_SAMPLE_INTERVAL: 200\n  MEAN:\n  - 0.485\n  - 0.456\n  - 0.406\n  SEARCH:\n    CENTER_JITTER: 4.5\n    FACTOR: 5.0\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/README.md",
    "chars": 1573,
    "preview": "# Alpha-Refine\n## Introduction\nAlpha-Refine is the winner of the VOT Real-Time Challenge 2020, which has great ability t"
  },
  {
    "path": "artrackv2_mindspore/external/AR/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/README.md",
    "chars": 5509,
    "preview": "# LTR\n\nA general PyTorch based framework for learning tracking representations. \n## Table of Contents\n\n* [Quick Start](#"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/__init__.py",
    "chars": 131,
    "preview": "from .admin.loading import load_network\nfrom .admin.model_constructor import model_constructor\nfrom .admin.multigpu impo"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/actors/__init__.py",
    "chars": 94,
    "preview": "from .base_actor import BaseActor\nfrom .bbreg import AtomActor\nfrom .tracking import DiMPActor"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/actors/base_actor.py",
    "chars": 1336,
    "preview": "from pytracking import TensorDict\n\n\nclass BaseActor:\n    \"\"\" Base class for actor. The actor class handles the passing o"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/actors/bbreg.py",
    "chars": 2174,
    "preview": "from . import BaseActor\n\n\nclass AtomActor(BaseActor):\n    \"\"\" Actor for training the IoU-Net in ATOM\"\"\"\n    def __call__"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/actors/tracking.py",
    "chars": 9035,
    "preview": "from . import BaseActor\nimport torch\n\n\nclass DiMPActor(BaseActor):\n    \"\"\"Actor for training the DiMP network.\"\"\"\n    de"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/environment.py",
    "chars": 1878,
    "preview": "import importlib\nimport os\nfrom collections import OrderedDict\n\n\ndef create_default_local_file():\n    path = os.path.joi"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/loading.py",
    "chars": 5567,
    "preview": "import torch\nimport os\nimport sys\nfrom pathlib import Path\nimport importlib\nimport inspect\nfrom ltr.admin import setting"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/model_constructor.py",
    "chars": 2053,
    "preview": "from functools import wraps\nimport importlib\n\n\ndef model_constructor(f):\n    \"\"\" Wraps the function 'f' which returns th"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/multigpu.py",
    "chars": 365,
    "preview": "import torch.nn as nn\n\n\ndef is_multi_gpu(net):\n    return isinstance(net, (MultiGPU, nn.DataParallel))\n\n\nclass MultiGPU("
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/settings.py",
    "chars": 279,
    "preview": "from ltr.admin.environment import env_settings\n\n\nclass Settings:\n    \"\"\" Training settings, e.g. the paths to datasets a"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/stats.py",
    "chars": 1578,
    "preview": "\n\nclass StatValue:\n    def __init__(self):\n        self.clear()\n\n    def reset(self):\n        self.val = 0\n\n    def clea"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/admin/tensorboard.py",
    "chars": 1251,
    "preview": "import os\nfrom collections import OrderedDict\ntry:\n    from torch.utils.tensorboard import SummaryWriter\nexcept:\n    pri"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/__init__.py",
    "chars": 29,
    "preview": "from .loader import LTRLoader"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/bounding_box_utils.py",
    "chars": 2979,
    "preview": "import torch\n\n\ndef rect_to_rel(bb, sz_norm=None):\n    \"\"\"Convert standard rectangular parametrization of the bounding bo"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/image_loader.py",
    "chars": 3358,
    "preview": "import jpeg4py\nimport cv2 as cv\nfrom PIL import Image\nimport numpy as np\n\ndavis_palette = np.repeat(np.expand_dims(np.ar"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/loader.py",
    "chars": 9377,
    "preview": "import torch\nimport torch.utils.data.dataloader\nimport importlib\nimport collections\nfrom torch._six import string_classe"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/processing.py",
    "chars": 35017,
    "preview": "import torch\nimport torchvision.transforms as transforms\nfrom pytracking import TensorDict\nimport ltr.data.processing_ut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/processing_utils.py",
    "chars": 23093,
    "preview": "import torch\nimport math\nimport cv2 as cv\nimport random\nimport torch.nn.functional as F\nfrom .bounding_box_utils import "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/processing_utils_SE.py",
    "chars": 16646,
    "preview": "import torch\nimport math\nimport cv2 as cv\nimport random\n\nimport numpy as np\n\ndef stack_tensors(x):\n    if isinstance(x, "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/sampler.py",
    "chars": 9665,
    "preview": "import random\nimport torch.utils.data\nfrom pytracking import TensorDict\n\n\ndef no_processing(data):\n    return data\n\n\ncla"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/data/transforms.py",
    "chars": 16893,
    "preview": "import random\nimport numpy as np\nimport math\nimport cv2 as cv\nimport torch\nimport torch.nn.functional as F\nimport torchv"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/__init__.py",
    "chars": 467,
    "preview": "from .lasot import Lasot\nfrom .got10k import Got10k\nfrom .tracking_net import TrackingNet\nfrom .imagenetvid import Image"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/base_image_dataset.py",
    "chars": 2421,
    "preview": "import torch.utils.data\nfrom ltr.data.image_loader import jpeg4py_loader\n\n\nclass BaseImageDataset(torch.utils.data.Datas"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/base_video_dataset.py",
    "chars": 3024,
    "preview": "import torch.utils.data\nfrom ltr.data.image_loader import jpeg4py_loader\n\n\nclass BaseVideoDataset(torch.utils.data.Datas"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/coco.py",
    "chars": 5765,
    "preview": "import os\nfrom .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader\nimport torch"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/coco_seq.py",
    "chars": 6298,
    "preview": "import os\nfrom .base_video_dataset import BaseVideoDataset\nfrom ltr.data.image_loader import jpeg4py_loader\nimport torch"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/davis.py",
    "chars": 3895,
    "preview": "from pathlib import Path\nfrom ltr.dataset.vos_base import VOSDatasetBase, VOSMeta\nfrom pytracking.evaluation import Sequ"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/ecssd.py",
    "chars": 3059,
    "preview": "import os\nfrom .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader, opencv_load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/got10k.py",
    "chars": 7747,
    "preview": "import os\nimport os.path\nimport numpy as np\nimport torch\nimport csv\nimport pandas\nimport random\nfrom collections import "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/hku_is.py",
    "chars": 3080,
    "preview": "import os\nfrom .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader, opencv_load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/imagenetvid.py",
    "chars": 7174,
    "preview": "import os\nfrom .base_video_dataset import BaseVideoDataset\nfrom ltr.data.image_loader import default_image_loader\nimport"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/lasot.py",
    "chars": 6537,
    "preview": "import os\nimport os.path\nimport torch\nimport numpy as np\nimport pandas\nimport csv\nimport random\nfrom collections import "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/lvis.py",
    "chars": 5546,
    "preview": "import os\nfrom .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader_w_failsafe\ni"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/msra10k.py",
    "chars": 3123,
    "preview": "import os\nfrom .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader, imread_inde"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/sbd.py",
    "chars": 3978,
    "preview": "from .base_image_dataset import BaseImageDataset\nfrom ltr.data.image_loader import jpeg4py_loader_w_failsafe\nimport torc"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/synthetic_video.py",
    "chars": 3305,
    "preview": "from collections import OrderedDict\nfrom .base_video_dataset import BaseVideoDataset\nfrom ltr.data.bounding_box_utils im"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/synthetic_video_blend.py",
    "chars": 6943,
    "preview": "from collections import OrderedDict\nfrom .base_video_dataset import BaseVideoDataset\nfrom ltr.data.bounding_box_utils im"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/tracking_net.py",
    "chars": 5878,
    "preview": "import torch\nimport os\nimport os.path\nimport numpy as np\nimport pandas\nimport random\nfrom collections import OrderedDict"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/vos_base.py",
    "chars": 16000,
    "preview": "import torch\nfrom pathlib import Path\nfrom collections import OrderedDict, defaultdict\nimport json\nimport numpy as np\nim"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/dataset/youtubevos.py",
    "chars": 8394,
    "preview": "from pathlib import Path\nimport os\nfrom ltr.dataset.vos_base import VOSDatasetBase, VOSMeta\nfrom pytracking.evaluation i"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/.gitignore",
    "chars": 1219,
    "preview": "# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n.vim-template*\n\n# C extensions\n*.so\n\n# Distri"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/LICENSE",
    "chars": 1068,
    "preview": "MIT License\n\nCopyright (c) 2018 Jiayuan Mao\n\nPermission is hereby granted, free of charge, to any person obtaining a cop"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/README.md",
    "chars": 3938,
    "preview": "# PreciseRoIPooling\nThis repo implements the **Precise RoI Pooling** (PrRoI Pooling), proposed in the paper **Acquisitio"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/.gitignore",
    "chars": 20,
    "preview": "*.o\n/_prroi_pooling\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/__init__.py",
    "chars": 350,
    "preview": "#! /usr/bin/env python3\n# -*- coding: utf-8 -*-\n# File   : __init__.py\n# Author : Jiayuan Mao, Tete Xiao\n# Email  : maoj"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/functional.py",
    "chars": 2837,
    "preview": "#! /usr/bin/env python3\n# -*- coding: utf-8 -*-\n# File   : functional.py\n# Author : Jiayuan Mao, Tete Xiao\n# Email  : ma"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/prroi_pool.py",
    "chars": 972,
    "preview": "#! /usr/bin/env python3\n# -*- coding: utf-8 -*-\n# File   : prroi_pool.py\n# Author : Jiayuan Mao, Tete Xiao\n# Email  : ma"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.c",
    "chars": 3854,
    "preview": "/*\n * File   : prroi_pooling_gpu.c\n * Author : Jiayuan Mao, Tete Xiao\n * Email  : maojiayuan@gmail.com, jasonhsiao97@gma"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu.h",
    "chars": 865,
    "preview": "/*\n * File   : prroi_pooling_gpu.h\n * Author : Jiayuan Mao, Tete Xiao\n * Email  : maojiayuan@gmail.com, jasonhsiao97@gma"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu_impl.cu",
    "chars": 17532,
    "preview": "/*\n * File   : prroi_pooling_gpu_impl.cu\n * Author : Tete Xiao, Jiayuan Mao\n * Email  : jasonhsiao97@gmail.com\n *\n * Dis"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/prroi_pool/src/prroi_pooling_gpu_impl.cuh",
    "chars": 1589,
    "preview": "/*\n * File   : prroi_pooling_gpu_impl.cuh\n * Author : Tete Xiao, Jiayuan Mao\n * Email  : jasonhsiao97@gmail.com\n *\n * Di"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/pytorch/tests/test_prroi_pooling2d.py",
    "chars": 1473,
    "preview": "# -*- coding: utf-8 -*-\n# File   : test_prroi_pooling2d.py\n# Author : Jiayuan Mao\n# Email  : maojiayuan@gmail.com\n# Date"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/src/prroi_pooling_gpu_impl.cu",
    "chars": 17532,
    "preview": "/*\n * File   : prroi_pooling_gpu_impl.cu\n * Author : Tete Xiao, Jiayuan Mao\n * Email  : jasonhsiao97@gmail.com\n *\n * Dis"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/external/PreciseRoIPooling/src/prroi_pooling_gpu_impl.cuh",
    "chars": 1589,
    "preview": "/*\n * File   : prroi_pooling_gpu_impl.cuh\n * Author : Tete Xiao, Jiayuan Mao\n * Email  : jasonhsiao97@gmail.com\n *\n * Di"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/AR_seg_mask/AR_seg_mask.py",
    "chars": 5452,
    "preview": "import torch.nn as nn\nfrom ltr.models.neck import CorrNL\nfrom ltr import model_constructor\nimport torch\nimport ltr.model"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/AR_seg_mask/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/backbone/__init__.py",
    "chars": 98,
    "preview": "from .resnet import resnet18, resnet50, resnet_baby\nfrom .resnet18_vggm import resnet18_vggmconv1\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/backbone/base.py",
    "chars": 1611,
    "preview": "import torch\nimport torch.nn as nn\n\n\nclass Backbone(nn.Module):\n    \"\"\"Base class for backbone networks. Handles freezin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/backbone/resnet.py",
    "chars": 9442,
    "preview": "import math\nimport torch.nn as nn\nfrom collections import OrderedDict\nimport torch.utils.model_zoo as model_zoo\nfrom tor"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/backbone/resnet18_vggm.py",
    "chars": 5522,
    "preview": "import math\nimport torch\nimport torch.nn as nn\nfrom collections import OrderedDict\nfrom torchvision.models.resnet import"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/backbone/resnet_seg.py",
    "chars": 8770,
    "preview": "import math\nimport torch.nn as nn\nfrom collections import OrderedDict\nimport torch.utils.model_zoo as model_zoo\nfrom tor"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/bbreg/__init__.py",
    "chars": 37,
    "preview": "from .atom_iou_net import AtomIoUNet\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/bbreg/atom.py",
    "chars": 3542,
    "preview": "import torch.nn as nn\nimport ltr.models.backbone as backbones\nimport ltr.models.bbreg as bbmodels\nfrom ltr import model_"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/bbreg/atom_iou_net.py",
    "chars": 7601,
    "preview": "import torch.nn as nn\nimport torch\nfrom ltr.models.layers.blocks import LinearBlock\nfrom ltr.external.PreciseRoIPooling."
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/head/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/head/seg_network.py",
    "chars": 6775,
    "preview": "import torch\nfrom torch import nn as nn\nfrom torch.nn import functional as F\nfrom ltr.models.head.utils import conv, rel"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/head/utils.py",
    "chars": 3388,
    "preview": "from collections import OrderedDict as odict\n\nimport numpy as np\nimport torch\nfrom torch import nn as nn\nfrom torch.nn i"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/activation.py",
    "chars": 1860,
    "preview": "import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\ndef softmax_reg(x: torch.Tensor, dim, r"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/blocks.py",
    "chars": 1397,
    "preview": "from torch import nn\n\n\ndef conv_block(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dilation=1, bias=True,\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/distance.py",
    "chars": 1423,
    "preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass DistanceMap(nn.Module):\n    \"\"\"Generate a dis"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/filter.py",
    "chars": 8433,
    "preview": "import torch\nimport torch.nn.functional as F\n\n\ndef apply_filter(feat, filter, dilation_factors=None):\n    \"\"\"Applies the"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/normalization.py",
    "chars": 764,
    "preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass InstanceL2Norm(nn.Module):\n    \"\"\"Instance L2"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/layers/transform.py",
    "chars": 800,
    "preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom collections import OrderedDict\n\n\ndef interpolate"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/loss/__init__.py",
    "chars": 43,
    "preview": "from .target_classification import LBHinge\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/loss/kl_regression.py",
    "chars": 2530,
    "preview": "import math\nimport torch\nimport torch.nn as nn\nfrom torch.nn import functional as F\n\n\nclass KLRegression(nn.Module):\n   "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/loss/target_classification.py",
    "chars": 1191,
    "preview": "import torch.nn as nn\nimport torch\nfrom torch.nn import functional as F\n\n\nclass LBHinge(nn.Module):\n    \"\"\"Loss that use"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/meta/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/meta/steepestdescent.py",
    "chars": 3524,
    "preview": "import math\nimport torch\nimport torch.nn as nn\nfrom pytracking import TensorList\nfrom ltr.models.layers import activatio"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/neck/CorrNL.py",
    "chars": 5179,
    "preview": "import torch.nn as nn\nimport torch\nfrom ltr.external.PreciseRoIPooling.pytorch.prroi_pool import PrRoIPool2D\nfrom torch."
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/neck/neck_utils.py",
    "chars": 4841,
    "preview": "import torch.nn as nn\nimport torch\nfrom torch.nn import functional as F\n\ndef conv(in_planes, out_planes, kernel_size=3, "
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/__init__.py",
    "chars": 40,
    "preview": "from .linear_filter import LinearFilter\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/features.py",
    "chars": 3046,
    "preview": "import torch\nfrom torch import nn\nimport torch.nn.functional as F\nfrom torchvision.models.resnet import BasicBlock, Bott"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/initializer.py",
    "chars": 10465,
    "preview": "import torch.nn as nn\nimport torch\nimport torch.nn.functional as F\nfrom ltr.external.PreciseRoIPooling.pytorch.prroi_poo"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/linear_filter.py",
    "chars": 5405,
    "preview": "import torch.nn as nn\nimport ltr.models.layers.filter as filter_layer\nimport math\n\n\nclass LinearFilter(nn.Module):\n    \""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/optimizer.py",
    "chars": 23277,
    "preview": "import torch.nn as nn\nimport torch\nimport torch.nn.functional as F\nimport ltr.models.layers.filter as filter_layer\nimpor"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/target_classifier/residual_modules.py",
    "chars": 3840,
    "preview": "import torch\nimport torch.nn as nn\nimport math\nimport ltr.models.layers.filter as filter_layer\nimport ltr.models.layers."
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/tracking/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/models/tracking/dimpnet.py",
    "chars": 19303,
    "preview": "import math\nimport torch\nimport torch.nn as nn\nfrom collections import OrderedDict\nfrom ltr.models.meta import steepestd"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/run_training.py",
    "chars": 1817,
    "preview": "import os\nimport sys\nimport argparse\nimport importlib\nimport multiprocessing\nimport cv2 as cv\nimport torch.backends.cudn"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom.py",
    "chars": 5194,
    "preview": "import torch.nn as nn\nimport torch.optim as optim\nfrom ltr.dataset import Lasot, TrackingNet, MSCOCOSeq, Got10k\nfrom ltr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_gmm_sampl.py",
    "chars": 5339,
    "preview": "import torch.nn as nn\nimport torch.optim as optim\nfrom ltr.dataset import Lasot, TrackingNet, MSCOCOSeq, Got10k\nfrom ltr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_paper.py",
    "chars": 5105,
    "preview": "import torch.nn as nn\nimport torch.optim as optim\nfrom ltr.dataset import Lasot, TrackingNet, MSCOCOSeq\nfrom ltr.data im"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/bbreg/atom_prob_ml.py",
    "chars": 5470,
    "preview": "import torch.optim as optim\nfrom ltr.dataset import Lasot, TrackingNet, MSCOCOSeq, Got10k\nfrom ltr.data import processin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/dimp18.py",
    "chars": 6584,
    "preview": "import torch.nn as nn\nimport torch.optim as optim\nfrom ltr.dataset import Lasot, Got10k, TrackingNet, MSCOCOSeq\nfrom ltr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/dimp50.py",
    "chars": 6649,
    "preview": "import torch.nn as nn\nimport torch.optim as optim\nfrom ltr.dataset import Lasot, Got10k, TrackingNet, MSCOCOSeq\nfrom ltr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/prdimp18.py",
    "chars": 6740,
    "preview": "import torch.optim as optim\nfrom ltr.dataset import Lasot, Got10k, TrackingNet, MSCOCOSeq\nfrom ltr.data import processin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/prdimp50.py",
    "chars": 6832,
    "preview": "import torch.optim as optim\nfrom ltr.dataset import Lasot, Got10k, TrackingNet, MSCOCOSeq\nfrom ltr.data import processin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/train_settings/dimp/super_dimp.py",
    "chars": 7949,
    "preview": "import torch.optim as optim\nfrom ltr.dataset import Lasot, Got10k, TrackingNet, MSCOCOSeq\nfrom ltr.data import processin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/trainers/__init__.py",
    "chars": 73,
    "preview": "from .base_trainer import BaseTrainer\nfrom .ltr_trainer import LTRTrainer"
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/trainers/base_trainer.py",
    "chars": 7957,
    "preview": "import os\nimport glob\nimport torch\nimport traceback\nfrom ltr.admin import loading, multigpu\n\n\nclass BaseTrainer:\n    \"\"\""
  },
  {
    "path": "artrackv2_mindspore/external/AR/ltr/trainers/ltr_trainer.py",
    "chars": 5434,
    "preview": "import os\nfrom collections import OrderedDict\nfrom ltr.trainers import BaseTrainer\nfrom ltr.admin.stats import AverageMe"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/ARcm_seg.py",
    "chars": 4059,
    "preview": "import os\nimport sys\nimport torch\nimport numpy as np\nimport cv2\nimport torch.nn as nn\nfrom external.AR.pytracking.utils."
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT/tracker_DiMP.m",
    "chars": 1198,
    "preview": "% Set path to the python in the pytracking conda environment\npython_path = 'PATH_TO_CONDA_INSTALLATION/envs/pytracking/b"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT/trackers.ini",
    "chars": 370,
    "preview": "[DiMP]  # <tracker-name>\nlabel = DiMP\nprotocol = traxpython\n\ncommand = run_vot; run_vot.run_vot2020('dimp', 'dimp50')  #"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT/vot.py",
    "chars": 3282,
    "preview": "\"\"\"\n\\file vot.py\n\n@brief Python utility functions for VOT integration\n\n@author Luka Cehovin, Alessio Dore\n\n@date 2016, 2"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/dimp_alpha_065.py",
    "chars": 354,
    "preview": "from pytracking.VOT2020_super_only_mask_384_HP.dimp_alpha_seg_class import run_vot_exp\nimport os\nos.environ['CUDA_VISIBL"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/dimp_alpha_seg_class.py",
    "chars": 6724,
    "preview": "from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __futu"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/mixformer_alpha_seg_class.py",
    "chars": 3661,
    "preview": "from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __futu"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/mixformer_large_alpha_seg_class.py",
    "chars": 3674,
    "preview": "from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __futu"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/VOT2020_super_only_mask_384_HP/vot.py",
    "chars": 3519,
    "preview": "\"\"\"\n\\file vot.py\n@brief Python utility functions for VOT integration\n@author Luka Cehovin, Alessio Dore\n@date 2016\n\"\"\"\n\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/__init__.py",
    "chars": 51,
    "preview": "from pytracking.libs import TensorList, TensorDict\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/evaluate_vos.py",
    "chars": 7681,
    "preview": "import os\nimport numpy as np\nimport torch\nimport pandas as pd\nfrom collections import OrderedDict\nfrom ltr.data.image_lo"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/extract_results.py",
    "chars": 7751,
    "preview": "import os\nimport sys\nimport importlib\nimport numpy as np\nfrom pytracking.utils.load_text import load_text\nimport torch\ni"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/playback_results.py",
    "chars": 6518,
    "preview": "import os\nimport sys\nimport importlib\nimport numpy as np\nimport torch\nimport time\nimport matplotlib.patches as patches\ni"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/plot_results.py",
    "chars": 22649,
    "preview": "import tikzplotlib\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport os\nimport torch\nimport pickle\nimport json\nfr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/analysis/vos_utils.py",
    "chars": 6689,
    "preview": "import warnings\nimport numpy as np\nfrom skimage.morphology import binary_dilation, disk\nfrom math import floor\n\n\ndef tex"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/__init__.py",
    "chars": 102,
    "preview": "from .data import Sequence\nfrom .tracker import Tracker, trackerlist\nfrom .datasets import get_dataset"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/data.py",
    "chars": 6945,
    "preview": "import numpy as np\nfrom pytracking.evaluation.environment import env_settings\nfrom ltr.data.image_loader import imread_i"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/datasets.py",
    "chars": 3689,
    "preview": "from collections import namedtuple\nimport importlib\nfrom pytracking.evaluation.data import SequenceList\n\nDatasetInfo = n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/environment.py",
    "chars": 2481,
    "preview": "import importlib\nimport os\n\n\nclass EnvSettings:\n    def __init__(self):\n        pytracking_path = os.path.abspath(os.pat"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/got10kdataset.py",
    "chars": 2228,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/lasotdataset.py",
    "chars": 13108,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/mobifacedataset.py",
    "chars": 2824,
    "preview": "from pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nimport glob\nimport numpy as np\nimport os.path"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/multi_object_wrapper.py",
    "chars": 7037,
    "preview": "import numpy as np\nfrom collections import OrderedDict\nimport time\nimport copy\n\n\nclass MultiObjectWrapper:\n    def __ini"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/nfsdataset.py",
    "chars": 23406,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/otbdataset.py",
    "chars": 21468,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/running.py",
    "chars": 5323,
    "preview": "import numpy as np\nimport multiprocessing\nimport os\nimport sys\nfrom itertools import product\nfrom collections import Ord"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/tpldataset.py",
    "chars": 26815,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/tracker.py",
    "chars": 26003,
    "preview": "import importlib\nimport os\nimport numpy as np\nfrom collections import OrderedDict\nfrom pytracking.evaluation.environment"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/trackingnetdataset.py",
    "chars": 2341,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nimport os\nfrom pytracking."
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/uavdataset.py",
    "chars": 27616,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\nfrom pytracking.utils.load"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/vot.py",
    "chars": 5232,
    "preview": "\"\"\"\n\\file vot.py\n\n@brief Python utility functions for VOT integration\n\n@author Luka Cehovin, Alessio Dore\n\n@date 2016\n\n\""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/vot2020.py",
    "chars": 4245,
    "preview": "\"\"\"\n\\file vot.py\n\n@brief Python utility functions for VOT integration\n\n@author Luka Cehovin, Alessio Dore\n\n@date 2016\n\n\""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/evaluation/votdataset.py",
    "chars": 4341,
    "preview": "import numpy as np\nfrom pytracking.evaluation.data import Sequence, BaseDataset, SequenceList\n\n\nclass VOTDataset(BaseDat"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/experiments/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/experiments/myexperiments.py",
    "chars": 574,
    "preview": "from pytracking.evaluation import Tracker, get_dataset, trackerlist\n\n\ndef atom_nfs_uav():\n    # Run three runs of ATOM o"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/augmentation.py",
    "chars": 8872,
    "preview": "import numpy as np\nimport math\nimport torch\nimport torch.nn.functional as F\nimport cv2 as cv\nimport random\nfrom pytracki"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/color.py",
    "chars": 582,
    "preview": "import torch\nfrom pytracking.features.featurebase import FeatureBase\n\n\nclass RGB(FeatureBase):\n    \"\"\"RGB feature normal"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/deep.py",
    "chars": 5566,
    "preview": "from pytracking.features.featurebase import FeatureBase, MultiFeatureBase\nimport torch\nimport torchvision\nfrom pytrackin"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/extractor.py",
    "chars": 5230,
    "preview": "import torch\nfrom pytracking.features.preprocessing import sample_patch\nfrom pytracking import TensorList\n\nclass Extract"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/featurebase.py",
    "chars": 4218,
    "preview": "import torch\nimport torch.nn.functional as F\nfrom pytracking import TensorList\n\n\nclass FeatureBase:\n    \"\"\"Base feature "
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/net_wrappers.py",
    "chars": 2437,
    "preview": "import torch\nfrom pytracking.utils.loading import load_network\n\n\nclass NetWrapper:\n    \"\"\"Used for wrapping networks in "
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/preprocessing.py",
    "chars": 5108,
    "preview": "import torch\nimport torch.nn.functional as F\nimport numpy as np\n\n\ndef numpy_to_torch(a: np.ndarray):\n    return torch.fr"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/features/util.py",
    "chars": 990,
    "preview": "import torch\nfrom pytracking.features.featurebase import FeatureBase\n\n\nclass Concatenate(FeatureBase):\n    \"\"\"A feature "
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/__init__.py",
    "chars": 69,
    "preview": "from .tensorlist import TensorList\nfrom .tensordict import TensorDict"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/complex.py",
    "chars": 5981,
    "preview": "import torch\nfrom pytracking.libs.tensorlist import tensor_operation\n\n\ndef is_complex(a: torch.Tensor) -> bool:\n    retu"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/dcf.py",
    "chars": 6931,
    "preview": "import torch\nimport math\nfrom pytracking import fourier\nfrom pytracking import complex\nimport torch.nn.functional as F\n\n"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/fourier.py",
    "chars": 4537,
    "preview": "import torch\nimport torch.nn.functional as F\nfrom pytracking import complex, TensorList\nfrom pytracking.libs.tensorlist "
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/operation.py",
    "chars": 1509,
    "preview": "import torch\nimport torch.nn.functional as F\nfrom pytracking.libs.tensorlist import tensor_operation, TensorList\n\n\n@tens"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/optimization.py",
    "chars": 21949,
    "preview": "import torch\nimport torch.autograd\nimport math\nfrom pytracking.libs import TensorList\nfrom pytracking.utils.plotting imp"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/tensordict.py",
    "chars": 1228,
    "preview": "from collections import OrderedDict\nimport torch\nimport copy\n\n\nclass TensorDict(OrderedDict):\n    \"\"\"Container mainly us"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/libs/tensorlist.py",
    "chars": 7058,
    "preview": "import functools\nimport torch\nimport copy\n\n\nclass TensorList(list):\n    \"\"\"Container mainly used for lists of torch tens"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/atom_gmm_sampl.py",
    "chars": 6551,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams, Choice\nfrom pytracking.features.extractor import MultiResolut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/atom_prob_ml.py",
    "chars": 6540,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams, Choice\nfrom pytracking.features.extractor import MultiResolut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/default.py",
    "chars": 6482,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams, Choice\nfrom pytracking.features.extractor import MultiResolut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/default_vot.py",
    "chars": 6516,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams, Choice\nfrom pytracking.features.extractor import MultiResolut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/atom/multiscale_no_iounet.py",
    "chars": 6503,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams, Choice\nfrom pytracking.features.extractor import MultiResolut"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp18.py",
    "chars": 2102,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp18_vot.py",
    "chars": 2246,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50.py",
    "chars": 2102,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50_vot.py",
    "chars": 2210,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/dimp50_vot19.py",
    "chars": 2127,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/prdimp18.py",
    "chars": 2692,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/prdimp50.py",
    "chars": 2772,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/dimp/super_dimp.py",
    "chars": 2734,
    "preview": "from pytracking.utils import TrackerParams\nfrom pytracking.features.net_wrappers import NetWithBackbone\n\ndef parameters("
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/eco/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/parameter/eco/default.py",
    "chars": 5595,
    "preview": "from pytracking.utils import TrackerParams, FeatureParams\nfrom pytracking.features.extractor import MultiResolutionExtra"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/tracker/__init__.py",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/tracker/atom/__init__.py",
    "chars": 64,
    "preview": "from .atom import ATOM\n\ndef get_tracker_class():\n    return ATOM"
  },
  {
    "path": "artrackv2_mindspore/external/AR/pytracking/tracker/atom/atom.py",
    "chars": 40346,
    "preview": "from pytracking.tracker.base import BaseTracker\nimport torch\nimport torch.nn.functional as F\nimport torch.nn\nimport math"
  }
]

// ... and 556 more files (download for full content)