Full Code of yichen928/SparseFusion for AI

gitextract_232uyltz/

├── .gitignore
├── LICENSE
├── MANIFEST.in
├── README.md
├── README_zh-CN.md
├── configs/
│   ├── 3dssd/
│   │   ├── 3dssd_kitti-3d-car.py
│   │   └── README.md
│   ├── _base_/
│   │   ├── datasets/
│   │   │   ├── coco_instance.py
│   │   │   ├── kitti-3d-3class.py
│   │   │   ├── kitti-3d-car.py
│   │   │   ├── lyft-3d.py
│   │   │   ├── nuim_instance.py
│   │   │   ├── nus-3d.py
│   │   │   ├── range100_lyft-3d.py
│   │   │   ├── scannet-3d-18class.py
│   │   │   ├── sunrgbd-3d-10class.py
│   │   │   ├── waymoD5-3d-3class.py
│   │   │   └── waymoD5-3d-car.py
│   │   ├── default_runtime.py
│   │   ├── models/
│   │   │   ├── 3dssd.py
│   │   │   ├── cascade_mask_rcnn_r50_fpn.py
│   │   │   ├── centerpoint_01voxel_second_secfpn_nus.py
│   │   │   ├── centerpoint_02pillar_second_secfpn_nus.py
│   │   │   ├── h3dnet.py
│   │   │   ├── hv_pointpillars_fpn_lyft.py
│   │   │   ├── hv_pointpillars_fpn_nus.py
│   │   │   ├── hv_pointpillars_fpn_range100_lyft.py
│   │   │   ├── hv_pointpillars_secfpn_kitti.py
│   │   │   ├── hv_pointpillars_secfpn_waymo.py
│   │   │   ├── hv_second_secfpn_kitti.py
│   │   │   ├── hv_second_secfpn_waymo.py
│   │   │   ├── imvotenet_image.py
│   │   │   ├── mask_rcnn_r50_fpn.py
│   │   │   └── votenet.py
│   │   └── schedules/
│   │       ├── cyclic_20e.py
│   │       ├── cyclic_40e.py
│   │       ├── mmdet_schedule_1x.py
│   │       ├── schedule_2x.py
│   │       └── schedule_3x.py
│   ├── benchmark/
│   │   ├── hv_PartA2_secfpn_4x8_cyclic_80e_pcdet_kitti-3d-3class.py
│   │   ├── hv_pointpillars_secfpn_3x8_100e_det3d_kitti-3d-car.py
│   │   ├── hv_pointpillars_secfpn_4x8_80e_pcdet_kitti-3d-3class.py
│   │   └── hv_second_secfpn_4x8_80e_pcdet_kitti-3d-3class.py
│   ├── centerpoint/
│   │   ├── README.md
│   │   ├── centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_flip-tta_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_tta_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_flip-tta_20e_nus.py
│   │   ├── centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_01voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
│   │   ├── centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus.py
│   │   └── centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
│   ├── dynamic_voxelization/
│   │   ├── README.md
│   │   ├── dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py
│   │   ├── dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py
│   │   └── dv_second_secfpn_6x8_80e_kitti-3d-car.py
│   ├── fp16/
│   │   ├── README.md
│   │   ├── hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_fpn_sbn-all_fp16_2x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d.py
│   │   ├── hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py
│   │   └── hv_second_secfpn_fp16_6x8_80e_kitti-3d-car.py
│   ├── free_anchor/
│   │   ├── README.md
│   │   ├── hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
│   │   └── hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
│   ├── h3dnet/
│   │   ├── README.md
│   │   └── h3dnet_3x8_scannet-3d-18class.py
│   ├── imvotenet/
│   │   ├── README.md
│   │   ├── imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py
│   │   └── imvotenet_stage2_16x8_sunrgbd-3d-10class.py
│   ├── mvxnet/
│   │   ├── README.md
│   │   └── dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
│   ├── nuimages/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r101_fpn_1x_nuim.py
│   │   ├── cascade_mask_rcnn_r50_fpn_1x_nuim.py
│   │   ├── cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim.py
│   │   ├── cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py
│   │   ├── htc_r50_fpn_1x_nuim.py
│   │   ├── htc_r50_fpn_coco-20e_1x_nuim.py
│   │   ├── htc_r50_fpn_coco-20e_20e_nuim.py
│   │   ├── htc_without_semantic_r50_fpn_1x_nuim.py
│   │   ├── htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim.py
│   │   ├── mask_rcnn_r101_fpn_1x_nuim.py
│   │   ├── mask_rcnn_r50_caffe_fpn_1x_nuim.py
│   │   ├── mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py
│   │   ├── mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py
│   │   ├── mask_rcnn_r50_fpn_1x_nuim.py
│   │   ├── mask_rcnn_r50_fpn_coco-2x_1x_nuim.py
│   │   ├── mask_rcnn_r50_fpn_coco-2x_1x_nus-2d.py
│   │   ├── mask_rcnn_swinT_coco-2x_1x_nuim.py
│   │   └── mask_rcnn_x101_32x4d_fpn_1x_nuim.py
│   ├── nuscenes.md
│   ├── parta2/
│   │   ├── README.md
│   │   ├── hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py
│   │   └── hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car.py
│   ├── pointpillars/
│   │   ├── README.md
│   │   ├── hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_fpn_sbn-all_range100_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class.py
│   │   ├── hv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py
│   │   ├── hv_pointpillars_secfpn_sbn-all_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_secfpn_sbn-all_range100_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-3class.py
│   │   ├── hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-car.py
│   │   ├── hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
│   │   └── hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car.py
│   ├── regnet/
│   │   ├── README.md
│   │   ├── hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d.py
│   │   ├── hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d.py
│   │   └── hv_pointpillars_regnet-400mf_secfpn_sbn-all_range100_2x8_2x_lyft-3d.py
│   ├── second/
│   │   ├── README.md
│   │   ├── hv_second_secfpn_6x8_80e_kitti-3d-3class.py
│   │   ├── hv_second_secfpn_6x8_80e_kitti-3d-car.py
│   │   └── hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
│   ├── sparsefusion_nusc_voxel_LC_SwinT.py
│   ├── sparsefusion_nusc_voxel_LC_r50.py
│   ├── ssn/
│   │   ├── README.md
│   │   ├── hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py
│   │   ├── hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d.py
│   │   ├── hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py
│   │   └── hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py
│   ├── transfusion_nusc_pillar_L.py
│   ├── transfusion_nusc_pillar_LC.py
│   ├── transfusion_nusc_voxel_L.py
│   ├── transfusion_nusc_voxel_LC.py
│   ├── transfusion_waymo_voxel_L.py
│   ├── transfusion_waymo_voxel_LC.py
│   ├── votenet/
│   │   ├── README.md
│   │   ├── votenet_16x8_sunrgbd-3d-10class.py
│   │   ├── votenet_8x8_scannet-3d-18class.py
│   │   └── votenet_iouloss_8x8_scannet-3d-18class.py
│   └── waymo.md
├── demo/
│   └── pcd_demo.py
├── docker/
│   └── Dockerfile
├── mmdet3d/
│   ├── __init__.py
│   ├── apis/
│   │   ├── __init__.py
│   │   ├── inference.py
│   │   └── test.py
│   ├── core/
│   │   ├── __init__.py
│   │   ├── anchor/
│   │   │   ├── __init__.py
│   │   │   └── anchor_3d_generator.py
│   │   ├── bbox/
│   │   │   ├── __init__.py
│   │   │   ├── assigners/
│   │   │   │   ├── __init__.py
│   │   │   │   └── hungarian_assigner.py
│   │   │   ├── box_np_ops.py
│   │   │   ├── coders/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── anchor_free_bbox_coder.py
│   │   │   │   ├── camera_bbox_coder.py
│   │   │   │   ├── centerpoint_bbox_coders.py
│   │   │   │   ├── delta_xyzwhlr_bbox_coder.py
│   │   │   │   ├── partial_bin_based_bbox_coder.py
│   │   │   │   └── transfusion_bbox_coder.py
│   │   │   ├── iou_calculators/
│   │   │   │   ├── __init__.py
│   │   │   │   └── iou3d_calculator.py
│   │   │   ├── samplers/
│   │   │   │   ├── __init__.py
│   │   │   │   └── iou_neg_piecewise_sampler.py
│   │   │   ├── structures/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_box3d.py
│   │   │   │   ├── box_3d_mode.py
│   │   │   │   ├── cam_box3d.py
│   │   │   │   ├── coord_3d_mode.py
│   │   │   │   ├── depth_box3d.py
│   │   │   │   ├── lidar_box3d.py
│   │   │   │   └── utils.py
│   │   │   └── transforms.py
│   │   ├── evaluation/
│   │   │   ├── __init__.py
│   │   │   ├── indoor_eval.py
│   │   │   ├── kitti_utils/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── eval.py
│   │   │   │   └── rotate_iou.py
│   │   │   ├── lyft_eval.py
│   │   │   ├── seg_eval.py
│   │   │   └── waymo_utils/
│   │   │       └── prediction_kitti_to_waymo.py
│   │   ├── points/
│   │   │   ├── __init__.py
│   │   │   ├── base_points.py
│   │   │   ├── cam_points.py
│   │   │   ├── depth_points.py
│   │   │   └── lidar_points.py
│   │   ├── post_processing/
│   │   │   ├── __init__.py
│   │   │   ├── box3d_nms.py
│   │   │   └── merge_augs.py
│   │   ├── utils/
│   │   │   ├── __init__.py
│   │   │   └── gaussian.py
│   │   ├── visualizer/
│   │   │   ├── __init__.py
│   │   │   ├── open3d_vis.py
│   │   │   └── show_result.py
│   │   └── voxel/
│   │       ├── __init__.py
│   │       ├── builder.py
│   │       └── voxel_generator.py
│   ├── datasets/
│   │   ├── __init__.py
│   │   ├── builder.py
│   │   ├── custom_3d.py
│   │   ├── dataset_wrappers.py
│   │   ├── kitti2d_dataset.py
│   │   ├── kitti_dataset.py
│   │   ├── lyft_dataset.py
│   │   ├── nuscenes_dataset.py
│   │   ├── nuscenes_dataset_viewInfo.py
│   │   ├── pipelines/
│   │   │   ├── __init__.py
│   │   │   ├── data_augment_utils.py
│   │   │   ├── dbsampler.py
│   │   │   ├── formating.py
│   │   │   ├── loading.py
│   │   │   ├── test_time_aug.py
│   │   │   ├── transforms_2d.py
│   │   │   └── transforms_3d.py
│   │   ├── registry.py
│   │   ├── scannet_dataset.py
│   │   ├── semantickitti_dataset.py
│   │   ├── sunrgbd_dataset.py
│   │   └── waymo_dataset.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── backbones/
│   │   │   ├── DLA.py
│   │   │   ├── __init__.py
│   │   │   ├── base_pointnet.py
│   │   │   ├── multi_backbone.py
│   │   │   ├── nostem_regnet.py
│   │   │   ├── pointnet2_sa_msg.py
│   │   │   ├── pointnet2_sa_ssg.py
│   │   │   ├── second.py
│   │   │   └── swin.py
│   │   ├── builder.py
│   │   ├── dense_heads/
│   │   │   ├── __init__.py
│   │   │   ├── anchor3d_head.py
│   │   │   ├── base_conv_bbox_head.py
│   │   │   ├── centerpoint_head.py
│   │   │   ├── free_anchor3d_head.py
│   │   │   ├── parta2_rpn_head.py
│   │   │   ├── shape_aware_head.py
│   │   │   ├── sparsefusion_head_deform.py
│   │   │   ├── ssd_3d_head.py
│   │   │   ├── train_mixins.py
│   │   │   ├── transfusion_head.py
│   │   │   └── vote_head.py
│   │   ├── detectors/
│   │   │   ├── __init__.py
│   │   │   ├── base.py
│   │   │   ├── centerpoint.py
│   │   │   ├── dynamic_voxelnet.py
│   │   │   ├── h3dnet.py
│   │   │   ├── imvotenet.py
│   │   │   ├── mvx_faster_rcnn.py
│   │   │   ├── mvx_two_stage.py
│   │   │   ├── parta2.py
│   │   │   ├── single_stage.py
│   │   │   ├── sparsefusion.py
│   │   │   ├── ssd3dnet.py
│   │   │   ├── transfusion.py
│   │   │   ├── two_stage.py
│   │   │   ├── votenet.py
│   │   │   └── voxelnet.py
│   │   ├── fusion_layers/
│   │   │   ├── __init__.py
│   │   │   ├── coord_transform.py
│   │   │   ├── point_fusion.py
│   │   │   └── vote_fusion.py
│   │   ├── losses/
│   │   │   ├── __init__.py
│   │   │   ├── axis_aligned_iou_loss.py
│   │   │   ├── chamfer_distance.py
│   │   │   └── uncertainty_loss.py
│   │   ├── middle_encoders/
│   │   │   ├── __init__.py
│   │   │   ├── pillar_scatter.py
│   │   │   ├── sparse_encoder.py
│   │   │   └── sparse_unet.py
│   │   ├── model_utils/
│   │   │   ├── __init__.py
│   │   │   └── vote_module.py
│   │   ├── necks/
│   │   │   ├── __init__.py
│   │   │   └── second_fpn.py
│   │   ├── registry.py
│   │   ├── roi_heads/
│   │   │   ├── __init__.py
│   │   │   ├── base_3droi_head.py
│   │   │   ├── bbox_heads/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── h3d_bbox_head.py
│   │   │   │   └── parta2_bbox_head.py
│   │   │   ├── h3d_roi_head.py
│   │   │   ├── mask_heads/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── pointwise_semantic_head.py
│   │   │   │   └── primitive_head.py
│   │   │   ├── part_aggregation_roi_head.py
│   │   │   └── roi_extractors/
│   │   │       ├── __init__.py
│   │   │       └── single_roiaware_extractor.py
│   │   ├── utils/
│   │   │   ├── __init__.py
│   │   │   ├── clip_sigmoid.py
│   │   │   ├── deformable_decoder.py
│   │   │   ├── depth_encoder.py
│   │   │   ├── drop.py
│   │   │   ├── ffn.py
│   │   │   ├── inverse_sigmoid.py
│   │   │   ├── mlp.py
│   │   │   ├── network_modules.py
│   │   │   ├── ops/
│   │   │   │   ├── functions/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   └── ms_deform_attn_func.py
│   │   │   │   ├── make.sh
│   │   │   │   ├── modules/
│   │   │   │   │   ├── __init__.py
│   │   │   │   │   └── ms_deform_attn.py
│   │   │   │   ├── setup.py
│   │   │   │   ├── src/
│   │   │   │   │   ├── cpu/
│   │   │   │   │   │   ├── ms_deform_attn_cpu.cpp
│   │   │   │   │   │   └── ms_deform_attn_cpu.h
│   │   │   │   │   ├── cuda/
│   │   │   │   │   │   ├── ms_deform_attn_cuda.cu
│   │   │   │   │   │   ├── ms_deform_attn_cuda.h
│   │   │   │   │   │   └── ms_deform_im2col_cuda.cuh
│   │   │   │   │   ├── ms_deform_attn.h
│   │   │   │   │   └── vision.cpp
│   │   │   │   └── test.py
│   │   │   ├── projection.py
│   │   │   ├── sparsefusion_models.py
│   │   │   ├── transformer.py
│   │   │   └── transformerdecoder.py
│   │   └── voxel_encoders/
│   │       ├── __init__.py
│   │       ├── pillar_encoder.py
│   │       ├── utils.py
│   │       └── voxel_encoder.py
│   ├── ops/
│   │   ├── __init__.py
│   │   ├── ball_query/
│   │   │   ├── __init__.py
│   │   │   ├── ball_query.py
│   │   │   └── src/
│   │   │       ├── ball_query.cpp
│   │   │       └── ball_query_cuda.cu
│   │   ├── furthest_point_sample/
│   │   │   ├── __init__.py
│   │   │   ├── furthest_point_sample.py
│   │   │   ├── points_sampler.py
│   │   │   ├── src/
│   │   │   │   ├── furthest_point_sample.cpp
│   │   │   │   └── furthest_point_sample_cuda.cu
│   │   │   └── utils.py
│   │   ├── gather_points/
│   │   │   ├── __init__.py
│   │   │   ├── gather_points.py
│   │   │   └── src/
│   │   │       ├── gather_points.cpp
│   │   │       └── gather_points_cuda.cu
│   │   ├── group_points/
│   │   │   ├── __init__.py
│   │   │   ├── group_points.py
│   │   │   └── src/
│   │   │       ├── group_points.cpp
│   │   │       └── group_points_cuda.cu
│   │   ├── interpolate/
│   │   │   ├── __init__.py
│   │   │   ├── src/
│   │   │   │   ├── interpolate.cpp
│   │   │   │   ├── three_interpolate_cuda.cu
│   │   │   │   └── three_nn_cuda.cu
│   │   │   ├── three_interpolate.py
│   │   │   └── three_nn.py
│   │   ├── iou3d/
│   │   │   ├── __init__.py
│   │   │   ├── iou3d_utils.py
│   │   │   └── src/
│   │   │       ├── iou3d.cpp
│   │   │       └── iou3d_kernel.cu
│   │   ├── knn/
│   │   │   ├── __init__.py
│   │   │   ├── knn.py
│   │   │   └── src/
│   │   │       ├── knn.cpp
│   │   │       └── knn_cuda.cu
│   │   ├── norm.py
│   │   ├── pointnet_modules/
│   │   │   ├── __init__.py
│   │   │   ├── builder.py
│   │   │   ├── point_fp_module.py
│   │   │   ├── point_sa_module.py
│   │   │   └── registry.py
│   │   ├── roiaware_pool3d/
│   │   │   ├── __init__.py
│   │   │   ├── points_in_boxes.py
│   │   │   ├── roiaware_pool3d.py
│   │   │   └── src/
│   │   │       ├── points_in_boxes_cpu.cpp
│   │   │       ├── points_in_boxes_cuda.cu
│   │   │       ├── roiaware_pool3d.cpp
│   │   │       └── roiaware_pool3d_kernel.cu
│   │   ├── sparse_block.py
│   │   ├── spconv/
│   │   │   ├── __init__.py
│   │   │   ├── conv.py
│   │   │   ├── functional.py
│   │   │   ├── include/
│   │   │   │   ├── paramsgrid.h
│   │   │   │   ├── prettyprint.h
│   │   │   │   ├── pybind11_utils.h
│   │   │   │   ├── spconv/
│   │   │   │   │   ├── fused_spconv_ops.h
│   │   │   │   │   ├── geometry.h
│   │   │   │   │   ├── indice.cu.h
│   │   │   │   │   ├── indice.h
│   │   │   │   │   ├── maxpool.h
│   │   │   │   │   ├── mp_helper.h
│   │   │   │   │   ├── point2voxel.h
│   │   │   │   │   ├── pool_ops.h
│   │   │   │   │   ├── reordering.cu.h
│   │   │   │   │   ├── reordering.h
│   │   │   │   │   └── spconv_ops.h
│   │   │   │   ├── tensorview/
│   │   │   │   │   ├── helper_kernel.cu.h
│   │   │   │   │   ├── helper_launch.h
│   │   │   │   │   └── tensorview.h
│   │   │   │   ├── torch_utils.h
│   │   │   │   └── utility/
│   │   │   │       └── timer.h
│   │   │   ├── modules.py
│   │   │   ├── ops.py
│   │   │   ├── overwrite_spconv/
│   │   │   │   └── write_spconv2.py
│   │   │   ├── pool.py
│   │   │   ├── src/
│   │   │   │   ├── all.cc
│   │   │   │   ├── indice.cc
│   │   │   │   ├── indice_cuda.cu
│   │   │   │   ├── maxpool.cc
│   │   │   │   ├── maxpool_cuda.cu
│   │   │   │   ├── reordering.cc
│   │   │   │   └── reordering_cuda.cu
│   │   │   ├── structure.py
│   │   │   └── test_utils.py
│   │   └── voxel/
│   │       ├── __init__.py
│   │       ├── scatter_points.py
│   │       ├── src/
│   │       │   ├── scatter_points_cpu.cpp
│   │       │   ├── scatter_points_cuda.cu
│   │       │   ├── voxelization.cpp
│   │       │   ├── voxelization.h
│   │       │   ├── voxelization_cpu.cpp
│   │       │   └── voxelization_cuda.cu
│   │       └── voxelize.py
│   ├── utils/
│   │   ├── __init__.py
│   │   └── collect_env.py
│   └── version.py
├── requirements/
│   ├── build.txt
│   ├── docs.txt
│   ├── optional.txt
│   ├── readthedocs.txt
│   ├── runtime.txt
│   └── tests.txt
├── requirements.txt
├── setup.cfg
├── setup.py
├── tests/
│   ├── test_data/
│   │   ├── test_datasets/
│   │   │   ├── test_dataset_wrappers.py
│   │   │   ├── test_kitti_dataset.py
│   │   │   ├── test_lyft_dataset.py
│   │   │   ├── test_nuscene_dataset.py
│   │   │   ├── test_scannet_dataset.py
│   │   │   ├── test_semantickitti_dataset.py
│   │   │   └── test_sunrgbd_dataset.py
│   │   └── test_pipelines/
│   │       ├── test_augmentations/
│   │       │   ├── test_data_augment_utils.py
│   │       │   ├── test_test_augment_utils.py
│   │       │   └── test_transforms_3d.py
│   │       ├── test_indoor_pipeline.py
│   │       ├── test_indoor_sample.py
│   │       ├── test_loadings/
│   │       │   ├── test_load_points_from_multi_sweeps.py
│   │       │   └── test_loading.py
│   │       └── test_outdoor_pipeline.py
│   ├── test_metrics/
│   │   ├── test_indoor_eval.py
│   │   ├── test_kitti_eval.py
│   │   ├── test_losses.py
│   │   └── test_seg_eval.py
│   ├── test_models/
│   │   ├── test_backbones.py
│   │   ├── test_common_modules/
│   │   │   ├── test_middle_encoders.py
│   │   │   ├── test_pointnet_modules.py
│   │   │   ├── test_pointnet_ops.py
│   │   │   ├── test_roiaware_pool3d.py
│   │   │   ├── test_sparse_unet.py
│   │   │   └── test_vote_module.py
│   │   ├── test_detectors.py
│   │   ├── test_forward.py
│   │   ├── test_fusion/
│   │   │   ├── test_fusion_coord_trans.py
│   │   │   ├── test_point_fusion.py
│   │   │   └── test_vote_fusion.py
│   │   ├── test_heads/
│   │   │   ├── test_heads.py
│   │   │   ├── test_parta2_bbox_head.py
│   │   │   ├── test_roi_extractors.py
│   │   │   └── test_semantic_heads.py
│   │   ├── test_necks/
│   │   │   ├── test_fpn.py
│   │   │   └── test_necks.py
│   │   └── test_voxel_encoder/
│   │       ├── test_dynamic_scatter.py
│   │       ├── test_voxel_encoders.py
│   │       ├── test_voxel_generator.py
│   │       └── test_voxelize.py
│   ├── test_runtime/
│   │   ├── test_apis.py
│   │   └── test_config.py
│   ├── test_samples/
│   │   └── parta2_roihead_inputs.npz
│   └── test_utils/
│       ├── test_anchors.py
│       ├── test_assigners.py
│       ├── test_bbox_coders.py
│       ├── test_box3d.py
│       ├── test_box_np_ops.py
│       ├── test_coord_3d_mode.py
│       ├── test_merge_augs.py
│       ├── test_nms.py
│       ├── test_points.py
│       ├── test_samplers.py
│       └── test_utils.py
├── tools/
│   ├── analysis_tools/
│   │   ├── analyze_logs.py
│   │   ├── benchmark.py
│   │   └── get_flops.py
│   ├── combine_view_info.py
│   ├── create_data.py
│   ├── create_data.sh
│   ├── data_converter/
│   │   ├── __init__.py
│   │   ├── create_gt_database.py
│   │   ├── indoor_converter.py
│   │   ├── kitti_converter.py
│   │   ├── kitti_data_utils.py
│   │   ├── lyft_converter.py
│   │   ├── nuimage_converter.py
│   │   ├── nuscenes_converter.py
│   │   ├── scannet_data_utils.py
│   │   ├── sunrgbd_data_utils.py
│   │   └── waymo_converter.py
│   ├── dist_test.sh
│   ├── dist_train.sh
│   ├── misc/
│   │   ├── fuse_conv_bn.py
│   │   ├── print_config.py
│   │   └── visualize_results.py
│   ├── model_converters/
│   │   ├── convert_votenet_checkpoints.py
│   │   ├── publish_model.py
│   │   └── regnet2mmdet.py
│   ├── slurm_test.sh
│   ├── slurm_train.sh
│   ├── test.py
│   └── train.py
└── train.sh

SYMBOL INDEX (1948 symbols across 277 files)

FILE: demo/pcd_demo.py
  function main (line 6) | def main():

FILE: mmdet3d/__init__.py
  function digit_version (line 7) | def digit_version(version_str):

FILE: mmdet3d/apis/inference.py
  function convert_SyncBN (line 14) | def convert_SyncBN(config):
  function init_detector (line 30) | def init_detector(config, checkpoint=None, device='cuda:0'):
  function inference_detector (line 64) | def inference_detector(model, pcd):
  function show_result_meshlab (line 109) | def show_result_meshlab(data, result, out_dir):

FILE: mmdet3d/apis/test.py
  function single_gpu_test (line 5) | def single_gpu_test(model, data_loader, show=False, out_dir=None):

FILE: mmdet3d/core/anchor/anchor_3d_generator.py
  class Anchor3DRangeGenerator (line 8) | class Anchor3DRangeGenerator(object):
    method __init__ (line 32) | def __init__(self,
    method __repr__ (line 60) | def __repr__(self):
    method num_base_anchors (line 71) | def num_base_anchors(self):
    method num_levels (line 78) | def num_levels(self):
    method grid_anchors (line 82) | def grid_anchors(self, featmap_sizes, device='cuda'):
    method single_level_grid_anchors (line 107) | def single_level_grid_anchors(self, featmap_size, scale, device='cuda'):
    method anchors_single_range (line 147) | def anchors_single_range(self,
  class AlignedAnchor3DRangeGenerator (line 213) | class AlignedAnchor3DRangeGenerator(Anchor3DRangeGenerator):
    method __init__ (line 239) | def __init__(self, align_corner=False, **kwargs):
    method anchors_single_range (line 243) | def anchors_single_range(self,
  class AlignedAnchor3DRangeGeneratorPerCls (line 329) | class AlignedAnchor3DRangeGeneratorPerCls(AlignedAnchor3DRangeGenerator):
    method __init__ (line 340) | def __init__(self, **kwargs):
    method grid_anchors (line 345) | def grid_anchors(self, featmap_sizes, device='cuda'):
    method multi_cls_grid_anchors (line 366) | def multi_cls_grid_anchors(self, featmap_sizes, scale, device='cuda'):

FILE: mmdet3d/core/bbox/assigners/hungarian_assigner.py
  class BBox3DL1Cost (line 17) | class BBox3DL1Cost(object):
    method __init__ (line 18) | def __init__(self, weight):
    method __call__ (line 21) | def __call__(self, bboxes, gt_bboxes, train_cfg=None):
  class BBoxBEVL1Cost (line 27) | class BBoxBEVL1Cost(object):
    method __init__ (line 28) | def __init__(self, weight):
    method __call__ (line 31) | def __call__(self, bboxes, gt_bboxes, train_cfg):
  class IoU3DCost (line 42) | class IoU3DCost(object):
    method __init__ (line 43) | def __init__(self, weight):
    method __call__ (line 46) | def __call__(self, iou):
  class HeuristicAssigner3D (line 52) | class HeuristicAssigner3D(BaseAssigner):
    method __init__ (line 53) | def __init__(self,
    method assign (line 60) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...
  class HungarianAssigner3D (line 95) | class HungarianAssigner3D(BaseAssigner):
    method __init__ (line 96) | def __init__(self,
    method assign (line 107) | def assign(self, bboxes, gt_bboxes, gt_labels, cls_pred, train_cfg):
  class HungarianAssignerView2D (line 161) | class HungarianAssignerView2D(HungarianAssigner):
    method __init__ (line 162) | def __init__(self,
    method assign (line 169) | def assign(self,
  class HungarianAssignerViewProj2D (line 273) | class HungarianAssignerViewProj2D(HungarianAssigner):
    method __init__ (line 274) | def __init__(self,
    method assign (line 281) | def assign(self,
  class ViewCost (line 398) | class ViewCost:
    method __init__ (line 399) | def __init__(self, weight=1000):
    method __call__ (line 402) | def __call__(self, view_pred, gt_views):
  class HungarianAssignerCameraBox (line 409) | class HungarianAssignerCameraBox(BaseAssigner):
    method __init__ (line 410) | def __init__(self,
    method assign (line 422) | def assign(self, bboxes, gt_bboxes, gt_labels, cls_pred, view, train_c...

FILE: mmdet3d/core/bbox/box_np_ops.py
  function camera_to_lidar (line 8) | def camera_to_lidar(points, r_rect, velo2cam):
  function box_camera_to_lidar (line 28) | def box_camera_to_lidar(data, r_rect, velo2cam):
  function corners_nd (line 48) | def corners_nd(dims, origin=0.5):
  function rotation_2d (line 81) | def rotation_2d(points, angles):
  function center_to_corner_box2d (line 98) | def center_to_corner_box2d(centers, dims, angles=None, origin=0.5):
  function depth_to_points (line 122) | def depth_to_points(depth, trunc_pixel):
  function depth_to_lidar_points (line 146) | def depth_to_lidar_points(depth, trunc_pixel, P2, r_rect, velo2cam):
  function rotation_3d_in_axis (line 170) | def rotation_3d_in_axis(points, angles, axis=0):
  function center_to_corner_box3d (line 201) | def center_to_corner_box3d(centers,
  function box2d_to_corner_jit (line 231) | def box2d_to_corner_jit(boxes):
  function corner_to_standup_nd_jit (line 262) | def corner_to_standup_nd_jit(boxes_corner):
  function corner_to_surfaces_3d_jit (line 283) | def corner_to_surfaces_3d_jit(corners):
  function rotation_points_single_angle (line 306) | def rotation_points_single_angle(points, angle, axis=0):
  function points_cam2img (line 338) | def points_cam2img(points_3d, proj_mat,  with_depth=False):
  function box3d_to_bbox (line 374) | def box3d_to_bbox(box3d, P2):
  function corner_to_surfaces_3d (line 394) | def corner_to_surfaces_3d(corners):
  function points_in_rbbox (line 416) | def points_in_rbbox(points, rbbox, z_axis=2, origin=(0.5, 0.5, 0)):
  function minmax_to_corner_2d (line 437) | def minmax_to_corner_2d(minmax_box):
  function limit_period (line 452) | def limit_period(val, offset=0.5, period=np.pi):
  function create_anchors_3d_range (line 468) | def create_anchors_3d_range(feature_size,
  function center_to_minmax_2d (line 516) | def center_to_minmax_2d(centers, dims, origin=0.5):
  function rbbox2d_to_near_bbox (line 534) | def rbbox2d_to_near_bbox(rbboxes):
  function iou_jit (line 554) | def iou_jit(boxes, query_boxes, mode='iou', eps=0.0):
  function projection_matrix_to_CRT_kitti (line 592) | def projection_matrix_to_CRT_kitti(proj):
  function remove_outside_points (line 616) | def remove_outside_points(points, rect, Trv2c, P2, image_shape):
  function get_frustum (line 644) | def get_frustum(bbox_image, C, near_clip=0.001, far_clip=100):
  function surface_equ_3d (line 675) | def surface_equ_3d(polygon_surfaces):
  function _points_in_convex_polygon_3d_jit (line 700) | def _points_in_convex_polygon_3d_jit(points, polygon_surfaces, normal_ve...
  function points_in_convex_polygon_3d_jit (line 737) | def points_in_convex_polygon_3d_jit(points,
  function points_in_convex_polygon_jit (line 767) | def points_in_convex_polygon_jit(points, polygon, clockwise=True):
  function boxes3d_to_corners3d_lidar (line 811) | def boxes3d_to_corners3d_lidar(boxes3d, bottom_center=True):

FILE: mmdet3d/core/bbox/coders/anchor_free_bbox_coder.py
  class AnchorFreeBBoxCoder (line 9) | class AnchorFreeBBoxCoder(PartialBinBasedBBoxCoder):
    method __init__ (line 17) | def __init__(self, num_dir_bins, with_rot=True):
    method encode (line 23) | def encode(self, gt_bboxes_3d, gt_labels_3d):
    method decode (line 53) | def decode(self, bbox_out):
    method split_pred (line 87) | def split_pred(self, cls_preds, reg_preds, base_xyz):

FILE: mmdet3d/core/bbox/coders/camera_bbox_coder.py
  class CameraBBoxCoder (line 8) | class CameraBBoxCoder(BaseBBoxCoder):
    method __init__ (line 9) | def __init__(self, code_size=8):
    method encode (line 12) | def encode(self, dst_boxes):
    method decode (line 28) | def decode(self, cls, rot, dim, center, vel):
    method decode_yaw (line 78) | def decode_yaw(bbox, centers2d, cam2img):

FILE: mmdet3d/core/bbox/coders/centerpoint_bbox_coders.py
  class CenterPointBBoxCoder (line 8) | class CenterPointBBoxCoder(BaseBBoxCoder):
    method __init__ (line 23) | def __init__(self,
    method _gather_feat (line 40) | def _gather_feat(self, feats, inds, feat_masks=None):
    method _topk (line 61) | def _topk(self, scores, K=80):
    method _transpose_and_gather_feat (line 96) | def _transpose_and_gather_feat(self, feat, ind):
    method encode (line 112) | def encode(self):
    method decode (line 115) | def decode(self,

FILE: mmdet3d/core/bbox/coders/delta_xyzwhlr_bbox_coder.py
  class DeltaXYZWLHRBBoxCoder (line 8) | class DeltaXYZWLHRBBoxCoder(BaseBBoxCoder):
    method __init__ (line 15) | def __init__(self, code_size=7):
    method encode (line 20) | def encode(src_boxes, dst_boxes):
    method decode (line 57) | def decode(anchors, deltas):

FILE: mmdet3d/core/bbox/coders/partial_bin_based_bbox_coder.py
  class PartialBinBasedBBoxCoder (line 9) | class PartialBinBasedBBoxCoder(BaseBBoxCoder):
    method __init__ (line 19) | def __init__(self, num_dir_bins, num_sizes, mean_sizes, with_rot=True):
    method encode (line 27) | def encode(self, gt_bboxes_3d, gt_labels_3d):
    method decode (line 58) | def decode(self, bbox_out, suffix=''):
    method decode_corners (line 101) | def decode_corners(self, center, size_res, size_class):
    method split_pred (line 139) | def split_pred(self, cls_preds, reg_preds, base_xyz):
    method angle2class (line 203) | def angle2class(self, angle):
    method class2angle (line 224) | def class2angle(self, angle_cls, angle_res, limit_period=True):

FILE: mmdet3d/core/bbox/coders/transfusion_bbox_coder.py
  class TransFusionBBoxCoder (line 8) | class TransFusionBBoxCoder(BaseBBoxCoder):
    method __init__ (line 9) | def __init__(self,
    method encode (line 24) | def encode(self, dst_boxes):
    method decode (line 39) | def decode(self, heatmap, rot, dim, center, height, vel, filter=False):

FILE: mmdet3d/core/bbox/iou_calculators/iou3d_calculator.py
  class BboxOverlapsNearest3D (line 9) | class BboxOverlapsNearest3D(object):
    method __init__ (line 20) | def __init__(self, coordinate='lidar'):
    method __call__ (line 24) | def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
    method __repr__ (line 47) | def __repr__(self):
  class BboxOverlaps3D (line 55) | class BboxOverlaps3D(object):
    method __init__ (line 63) | def __init__(self, coordinate):
    method __call__ (line 67) | def __call__(self, bboxes1, bboxes2, mode='iou'):
    method __repr__ (line 87) | def __repr__(self):
  function bbox_overlaps_nearest_3d (line 94) | def bbox_overlaps_nearest_3d(bboxes1,
  function bbox_overlaps_3d (line 141) | def bbox_overlaps_3d(bboxes1, bboxes2, mode='iou', coordinate='camera'):
  class AxisAlignedBboxOverlaps3D (line 171) | class AxisAlignedBboxOverlaps3D(object):
    method __call__ (line 174) | def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
    method __repr__ (line 195) | def __repr__(self):
  function axis_aligned_bbox_overlaps_3d (line 201) | def axis_aligned_bbox_overlaps_3d(bboxes1,

FILE: mmdet3d/core/bbox/samplers/iou_neg_piecewise_sampler.py
  class IoUNegPiecewiseSampler (line 8) | class IoUNegPiecewiseSampler(RandomSampler):
    method __init__ (line 28) | def __init__(self,
    method _sample_pos (line 46) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 56) | def _sample_neg(self, assign_result, num_expected, **kwargs):
    method sample (line 98) | def sample(self,

FILE: mmdet3d/core/bbox/structures/base_box3d.py
  class BaseInstance3DBoxes (line 9) | class BaseInstance3DBoxes(object):
    method __init__ (line 36) | def __init__(self, tensor, box_dim=7, with_yaw=True, origin=(0.5, 0.5,...
    method volume (line 68) | def volume(self):
    method dims (line 73) | def dims(self):
    method yaw (line 78) | def yaw(self):
    method height (line 83) | def height(self):
    method top_height (line 88) | def top_height(self):
    method bottom_height (line 93) | def bottom_height(self):
    method center (line 98) | def center(self):
    method bottom_center (line 117) | def bottom_center(self):
    method gravity_center (line 122) | def gravity_center(self):
    method corners (line 127) | def corners(self):
    method rotate (line 132) | def rotate(self, angles, axis=0):
    method flip (line 142) | def flip(self, bev_direction='horizontal'):
    method translate (line 146) | def translate(self, trans_vector):
    method in_range_3d (line 156) | def in_range_3d(self, box_range):
    method in_range_bev (line 181) | def in_range_bev(self, box_range):
    method convert_to (line 195) | def convert_to(self, dst, rt_mat=None):
    method scale (line 212) | def scale(self, scale_factor):
    method limit_yaw (line 221) | def limit_yaw(self, offset=0.5, period=np.pi):
    method nonempty (line 230) | def nonempty(self, threshold: float = 0.0):
    method __getitem__ (line 251) | def __getitem__(self, item):
    method __len__ (line 280) | def __len__(self):
    method __repr__ (line 284) | def __repr__(self):
    method cat (line 289) | def cat(cls, boxes_list):
    method to (line 311) | def to(self, device):
    method clone (line 327) | def clone(self):
    method device (line 339) | def device(self):
    method __iter__ (line 343) | def __iter__(self):
    method height_overlaps (line 352) | def height_overlaps(cls, boxes1, boxes2, mode='iou'):
    method overlaps (line 384) | def overlaps(cls, boxes1, boxes2, mode='iou'):
    method new_box (line 440) | def new_box(self, data):

FILE: mmdet3d/core/bbox/structures/box_3d_mode.py
  class Box3DMode (line 12) | class Box3DMode(IntEnum):
    method convert (line 63) | def convert(box, src, dst, rt_mat=None):

FILE: mmdet3d/core/bbox/structures/cam_box3d.py
  class CameraInstance3DBoxes (line 9) | class CameraInstance3DBoxes(BaseInstance3DBoxes):
    method __init__ (line 38) | def __init__(self,
    method height (line 74) | def height(self):
    method top_height (line 79) | def top_height(self):
    method bottom_height (line 85) | def bottom_height(self):
    method gravity_center (line 90) | def gravity_center(self):
    method corners (line 99) | def corners(self):
    method bev (line 142) | def bev(self):
    method nearest_bev (line 148) | def nearest_bev(self):
    method rotate (line 168) | def rotate(self, angle, points=None):
    method flip (line 204) | def flip(self, bev_direction='horizontal', points=None):
    method in_range_bev (line 238) | def in_range_bev(self, box_range):
    method height_overlaps (line 261) | def height_overlaps(cls, boxes1, boxes2, mode='iou'):
    method convert_to (line 291) | def convert_to(self, dst, rt_mat=None):

FILE: mmdet3d/core/bbox/structures/coord_3d_mode.py
  class Coord3DMode (line 14) | class Coord3DMode(IntEnum):
    method convert (line 66) | def convert(input, src, dst, rt_mat=None):
    method convert_box (line 76) | def convert_box(box, src, dst, rt_mat=None):
    method convert_point (line 181) | def convert_point(point, src, dst, rt_mat=None):

FILE: mmdet3d/core/bbox/structures/depth_box3d.py
  class DepthInstance3DBoxes (line 10) | class DepthInstance3DBoxes(BaseInstance3DBoxes):
    method gravity_center (line 37) | def gravity_center(self):
    method corners (line 46) | def corners(self):
    method bev (line 87) | def bev(self):
    method nearest_bev (line 93) | def nearest_bev(self):
    method rotate (line 113) | def rotate(self, angle, points=None):
    method flip (line 159) | def flip(self, bev_direction='horizontal', points=None):
    method in_range_bev (line 193) | def in_range_bev(self, box_range):
    method convert_to (line 215) | def convert_to(self, dst, rt_mat=None):
    method points_in_boxes (line 234) | def points_in_boxes(self, points):
    method enlarged_box (line 262) | def enlarged_box(self, extra_width):
    method get_surface_line_center (line 277) | def get_surface_line_center(self):

FILE: mmdet3d/core/bbox/structures/lidar_box3d.py
  class LiDARInstance3DBoxes (line 10) | class LiDARInstance3DBoxes(BaseInstance3DBoxes):
    method gravity_center (line 37) | def gravity_center(self):
    method corners (line 46) | def corners(self):
    method bev (line 87) | def bev(self):
    method nearest_bev (line 93) | def nearest_bev(self):
    method rotate (line 113) | def rotate(self, angle, points=None):
    method flip (line 153) | def flip(self, bev_direction='horizontal', points=None):
    method in_range_bev (line 187) | def in_range_bev(self, box_range):
    method convert_to (line 208) | def convert_to(self, dst, rt_mat=None):
    method enlarged_box (line 227) | def enlarged_box(self, extra_width):
    method points_in_boxes (line 242) | def points_in_boxes(self, points):

FILE: mmdet3d/core/bbox/structures/utils.py
  function limit_period (line 5) | def limit_period(val, offset=0.5, period=np.pi):
  function rotation_3d_in_axis (line 21) | def rotation_3d_in_axis(points, angles, axis=0):
  function xywhr2xyxyr (line 64) | def xywhr2xyxyr(boxes_xywhr):
  function get_box_type (line 85) | def get_box_type(box_type):
  function points_cam2img (line 114) | def points_cam2img(points_3d, proj_mat):

FILE: mmdet3d/core/bbox/transforms.py
  function bbox3d_mapping_back (line 4) | def bbox3d_mapping_back(bboxes, scale_factor, flip_horizontal, flip_vert...
  function bbox3d2roi (line 26) | def bbox3d2roi(bbox_list):
  function bbox3d2result (line 49) | def bbox3d2result(bboxes, scores, labels):

FILE: mmdet3d/core/evaluation/indoor_eval.py
  function average_precision (line 7) | def average_precision(recalls, precisions, mode='area'):
  function eval_det_cls (line 55) | def eval_det_cls(pred, gt, iou_thr=None):
  function eval_map_recall (line 163) | def eval_map_recall(pred, gt, ovthresh=None):
  function indoor_eval (line 203) | def indoor_eval(gt_annos,

FILE: mmdet3d/core/evaluation/kitti_utils/eval.py
  function get_thresholds (line 8) | def get_thresholds(scores: np.ndarray, num_gt, num_sample_pts=41):
  function clean_data (line 28) | def clean_data(gt_anno, dt_anno, current_class, difficulty):
  function image_box_overlap (line 84) | def image_box_overlap(boxes, query_boxes, criterion=-1):
  function bev_box_overlap (line 115) | def bev_box_overlap(boxes, qboxes, criterion=-1):
  function d3_box_overlap_kernel (line 122) | def d3_box_overlap_kernel(boxes, qboxes, rinc, criterion=-1):
  function d3_box_overlap (line 153) | def d3_box_overlap(boxes, qboxes, criterion=-1):
  function compute_statistics_jit (line 162) | def compute_statistics_jit(overlaps,
  function get_split_parts (line 282) | def get_split_parts(num, num_part):
  function fused_compute_statistics (line 292) | def fused_compute_statistics(overlaps,
  function calculate_iou_partly (line 341) | def calculate_iou_partly(gt_annos, dt_annos, metric, num_parts=50):
  function _prepare_data (line 419) | def _prepare_data(gt_annos, dt_annos, current_class, difficulty):
  function eval_class (line 450) | def eval_class(gt_annos,
  function get_mAP (line 571) | def get_mAP(prec):
  function print_str (line 578) | def print_str(value, *arg, sstream=None):
  function do_eval (line 587) | def do_eval(gt_annos,
  function do_coco_style_eval (line 624) | def do_coco_style_eval(gt_annos, dt_annos, current_classes, overlap_ranges,
  function kitti_eval (line 643) | def kitti_eval(gt_annos,
  function kitti_eval_coco_style (line 776) | def kitti_eval_coco_style(gt_annos, dt_annos, current_classes):

FILE: mmdet3d/core/evaluation/kitti_utils/rotate_iou.py
  function div_up (line 13) | def div_up(m, n):
  function trangle_area (line 18) | def trangle_area(a, b, c):
  function area (line 24) | def area(int_pts, num_of_inter):
  function sort_vertex_in_convex_polygon (line 34) | def sort_vertex_in_convex_polygon(int_pts, num_of_inter):
  function line_segment_intersection (line 77) | def line_segment_intersection(pts1, pts2, i, j, temp_pts):
  function line_segment_intersection_v1 (line 123) | def line_segment_intersection_v1(pts1, pts2, i, j, temp_pts):
  function point_in_quadrilateral (line 162) | def point_in_quadrilateral(pt_x, pt_y, corners):
  function quadrilateral_intersection (line 181) | def quadrilateral_intersection(pts1, pts2, int_pts):
  function rbbox_to_corners (line 205) | def rbbox_to_corners(corners, rbbox):
  function inter (line 231) | def inter(rbbox1, rbbox2):
  function devRotateIoUEval (line 257) | def devRotateIoUEval(rbox1, rbox2, criterion=-1):
  function rotate_iou_kernel_eval (line 287) | def rotate_iou_kernel_eval(N,
  function rotate_iou_gpu_eval (line 340) | def rotate_iou_gpu_eval(boxes, query_boxes, criterion=-1, device_id=0):

FILE: mmdet3d/core/evaluation/lyft_eval.py
  function load_lyft_gts (line 13) | def load_lyft_gts(lyft, data_root, eval_split, logger=None):
  function load_lyft_predictions (line 72) | def load_lyft_predictions(res_path):
  function lyft_eval (line 89) | def lyft_eval(lyft, data_root, res_path, eval_set, output_dir, logger=No...
  function get_classwise_aps (line 141) | def get_classwise_aps(gt, predictions, class_names, iou_thresholds):
  function get_single_class_aps (line 198) | def get_single_class_aps(gt, predictions, iou_thresholds):

FILE: mmdet3d/core/evaluation/seg_eval.py
  function fast_hist (line 6) | def fast_hist(preds, labels, num_classes):
  function per_class_iou (line 27) | def per_class_iou(hist):
  function get_acc (line 41) | def get_acc(hist):
  function get_acc_cls (line 55) | def get_acc_cls(hist):
  function seg_eval (line 69) | def seg_eval(gt_labels, seg_preds, label2cat, logger=None):

FILE: mmdet3d/core/evaluation/waymo_utils/prediction_kitti_to_waymo.py
  class KITTI2Waymo (line 21) | class KITTI2Waymo(object):
    method __init__ (line 39) | def __init__(self,
    method get_file_names (line 77) | def get_file_names(self):
    method create_folder (line 83) | def create_folder(self):
    method parse_objects (line 87) | def parse_objects(self, kitti_result, T_k2w, context_name,
    method convert_one (line 169) | def convert_one(self, file_idx):
    method convert (line 209) | def convert(self):
    method __len__ (line 223) | def __len__(self):
    method transform (line 227) | def transform(self, T, x, y, z):
    method combine (line 243) | def combine(self, pathnames):

FILE: mmdet3d/core/points/__init__.py
  function get_points_type (line 9) | def get_points_type(points_type):

FILE: mmdet3d/core/points/base_points.py
  class BasePoints (line 6) | class BasePoints(object):
    method __init__ (line 25) | def __init__(self, tensor, points_dim=3, attribute_dims=None):
    method coord (line 45) | def coord(self):
    method height (line 50) | def height(self):
    method color (line 59) | def color(self):
    method shape (line 68) | def shape(self):
    method shuffle (line 72) | def shuffle(self):
    method rotate (line 77) | def rotate(self, rotation, axis=None):
    method flip (line 118) | def flip(self, bev_direction='horizontal'):
    method translate (line 122) | def translate(self, trans_vector):
    method in_range_3d (line 143) | def in_range_3d(self, point_range):
    method in_range_bev (line 168) | def in_range_bev(self, point_range):
    method convert_to (line 182) | def convert_to(self, dst, rt_mat=None):
    method scale (line 199) | def scale(self, scale_factor):
    method __getitem__ (line 207) | def __getitem__(self, item):
    method __len__ (line 273) | def __len__(self):
    method __repr__ (line 277) | def __repr__(self):
    method cat (line 282) | def cat(cls, points_list):
    method to (line 304) | def to(self, device):
    method clone (line 320) | def clone(self):
    method device (line 334) | def device(self):
    method __iter__ (line 338) | def __iter__(self):
    method new_point (line 346) | def new_point(self, data):

FILE: mmdet3d/core/points/cam_points.py
  class CameraPoints (line 4) | class CameraPoints(BasePoints):
    method __init__ (line 23) | def __init__(self, tensor, points_dim=3, attribute_dims=None):
    method flip (line 28) | def flip(self, bev_direction='horizontal'):
    method in_range_bev (line 35) | def in_range_bev(self, point_range):
    method convert_to (line 52) | def convert_to(self, dst, rt_mat=None):

FILE: mmdet3d/core/points/depth_points.py
  class DepthPoints (line 4) | class DepthPoints(BasePoints):
    method __init__ (line 23) | def __init__(self, tensor, points_dim=3, attribute_dims=None):
    method flip (line 28) | def flip(self, bev_direction='horizontal'):
    method in_range_bev (line 35) | def in_range_bev(self, point_range):
    method convert_to (line 52) | def convert_to(self, dst, rt_mat=None):

FILE: mmdet3d/core/points/lidar_points.py
  class LiDARPoints (line 4) | class LiDARPoints(BasePoints):
    method __init__ (line 23) | def __init__(self, tensor, points_dim=3, attribute_dims=None):
    method flip (line 28) | def flip(self, bev_direction='horizontal'):
    method in_range_bev (line 35) | def in_range_bev(self, point_range):
    method convert_to (line 52) | def convert_to(self, dst, rt_mat=None):

FILE: mmdet3d/core/post_processing/box3d_nms.py
  function box3d_multiclass_nms (line 8) | def box3d_multiclass_nms(mlvl_bboxes,
  function aligned_3d_nms (line 91) | def aligned_3d_nms(boxes, scores, classes, thresh):
  function circle_nms (line 142) | def circle_nms(dets, thresh, socre_thre=0, post_max_size=83):

FILE: mmdet3d/core/post_processing/merge_augs.py
  function merge_aug_bboxes_3d (line 7) | def merge_aug_bboxes_3d(aug_results, img_metas, test_cfg):

FILE: mmdet3d/core/utils/gaussian.py
  function gaussian_2d (line 5) | def gaussian_2d(shape, sigma=1):
  function draw_heatmap_gaussian (line 25) | def draw_heatmap_gaussian(heatmap, center, radius, k=1):
  function gaussian_radius (line 57) | def gaussian_radius(det_size, min_overlap=0.5):

FILE: mmdet3d/core/visualizer/open3d_vis.py
  function _draw_points (line 14) | def _draw_points(points,
  function _draw_bboxes (line 56) | def _draw_bboxes(bbox3d,
  function show_pts_boxes (line 119) | def show_pts_boxes(points,
  function _draw_bboxes_ind (line 181) | def _draw_bboxes_ind(bbox3d,
  function show_pts_index_boxes (line 251) | def show_pts_index_boxes(points,
  function project_pts_on_img (line 317) | def project_pts_on_img(points,
  function project_bbox3d_on_img (line 368) | def project_bbox3d_on_img(bboxes3d,
  class Visualizer (line 410) | class Visualizer(object):
    method __init__ (line 437) | def __init__(self,
    method add_bboxes (line 477) | def add_bboxes(self, bbox3d, bbox_color=None, points_in_box_color=None):
    method show (line 497) | def show(self, save_path=None):

FILE: mmdet3d/core/visualizer/show_result.py
  function _write_ply (line 7) | def _write_ply(points, out_filename):
  function _write_oriented_bbox (line 29) | def _write_oriented_bbox(scene_bbox, out_filename):
  function show_result (line 71) | def show_result(points, gt_bboxes, pred_bboxes, out_dir, filename, show=...

FILE: mmdet3d/core/voxel/builder.py
  function build_voxel_generator (line 6) | def build_voxel_generator(cfg, **kwargs):

FILE: mmdet3d/core/voxel/voxel_generator.py
  class VoxelGenerator (line 5) | class VoxelGenerator(object):
    method __init__ (line 16) | def __init__(self,
    method generate (line 35) | def generate(self, points):
    method voxel_size (line 42) | def voxel_size(self):
    method max_num_points_per_voxel (line 47) | def max_num_points_per_voxel(self):
    method point_cloud_range (line 52) | def point_cloud_range(self):
    method grid_size (line 57) | def grid_size(self):
    method __repr__ (line 61) | def __repr__(self):
  function points_to_voxel (line 75) | def points_to_voxel(points,
  function _points_to_voxel_reverse_kernel (line 137) | def _points_to_voxel_reverse_kernel(points,
  function _points_to_voxel_kernel (line 211) | def _points_to_voxel_kernel(points,

FILE: mmdet3d/datasets/builder.py
  function build_dataset (line 16) | def build_dataset(cfg, default_args=None):

FILE: mmdet3d/datasets/custom_3d.py
  class Custom3DDataset (line 13) | class Custom3DDataset(Dataset):
    method __init__ (line 42) | def __init__(self,
    method load_annotations (line 70) | def load_annotations(self, ann_file):
    method get_data_info (line 81) | def get_data_info(self, index):
    method pre_pipeline (line 112) | def pre_pipeline(self, results):
    method prepare_train_data (line 138) | def prepare_train_data(self, index):
    method prepare_test_data (line 158) | def prepare_test_data(self, index):
    method get_classes (line 173) | def get_classes(cls, classes=None):
    method format_results (line 199) | def format_results(self,
    method evaluate (line 223) | def evaluate(self,
    method __len__ (line 269) | def __len__(self):
    method _rand_another (line 277) | def _rand_another(self, idx):
    method __getitem__ (line 286) | def __getitem__(self, idx):
    method _set_group_flag (line 301) | def _set_group_flag(self):

FILE: mmdet3d/datasets/dataset_wrappers.py
  class CBGSDataset (line 7) | class CBGSDataset(object):
    method __init__ (line 18) | def __init__(self, dataset):
    method _get_sample_indices (line 29) | def _get_sample_indices(self):
    method __getitem__ (line 60) | def __getitem__(self, idx):
    method __len__ (line 69) | def __len__(self):

FILE: mmdet3d/datasets/kitti2d_dataset.py
  class Kitti2DDataset (line 8) | class Kitti2DDataset(CustomDataset):
    method load_annotations (line 79) | def load_annotations(self, ann_file):
    method _filter_imgs (line 95) | def _filter_imgs(self, min_size=32):
    method get_ann_info (line 103) | def get_ann_info(self, index):
    method prepare_train_img (line 135) | def prepare_train_img(self, idx):
    method prepare_test_img (line 156) | def prepare_test_img(self, idx):
    method drop_arrays_by_name (line 174) | def drop_arrays_by_name(self, gt_names, used_classes):
    method keep_arrays_by_name (line 188) | def keep_arrays_by_name(self, gt_names, used_classes):
    method reformat_bbox (line 202) | def reformat_bbox(self, outputs, out=None):
    method evaluate (line 219) | def evaluate(self, result_files, eval_types=None):

FILE: mmdet3d/datasets/kitti_dataset.py
  class KittiDataset (line 18) | class KittiDataset(Custom3DDataset):
    method __init__ (line 53) | def __init__(self,
    method _get_pts_filename (line 81) | def _get_pts_filename(self, idx):
    method get_data_info (line 94) | def get_data_info(self, index):
    method get_ann_info (line 137) | def get_ann_info(self, index):
    method drop_arrays_by_name (line 194) | def drop_arrays_by_name(self, gt_names, used_classes):
    method keep_arrays_by_name (line 208) | def keep_arrays_by_name(self, gt_names, used_classes):
    method remove_dontcare (line 222) | def remove_dontcare(self, ann_info):
    method format_results (line 241) | def format_results(self,
    method evaluate (line 296) | def evaluate(self,
    method bbox2result_kitti (line 360) | def bbox2result_kitti(self,
    method bbox2result_kitti2d (line 475) | def bbox2result_kitti2d(self,
    method convert_valid_bboxes (line 587) | def convert_valid_bboxes(self, box_dict, info):
    method show (line 673) | def show(self, results, out_dir, show=True):

FILE: mmdet3d/datasets/lyft_dataset.py
  class LyftDataset (line 18) | class LyftDataset(Custom3DDataset):
    method __init__ (line 76) | def __init__(self,
    method load_annotations (line 106) | def load_annotations(self, ann_file):
    method get_data_info (line 122) | def get_data_info(self, index):
    method get_ann_info (line 181) | def get_ann_info(self, index):
    method _format_bbox (line 223) | def _format_bbox(self, results, jsonfile_prefix=None):
    method _evaluate_single (line 266) | def _evaluate_single(self,
    method format_results (line 307) | def format_results(self, results, jsonfile_prefix=None, csv_savepath=N...
    method evaluate (line 351) | def evaluate(self,
    method show (line 401) | def show(self, results, out_dir):
    method json2csv (line 426) | def json2csv(self, json_path, csv_savepath):
  function output_to_lyft_box (line 463) | def output_to_lyft_box(detection):
  function lidar_lyft_box_to_global (line 496) | def lidar_lyft_box_to_global(info, boxes):

FILE: mmdet3d/datasets/nuscenes_dataset.py
  class NuScenesDataset (line 15) | class NuScenesDataset(Custom3DDataset):
    method __init__ (line 104) | def __init__(self,
    method get_cat_ids (line 145) | def get_cat_ids(self, idx):
    method load_annotations (line 169) | def load_annotations(self, ann_file):
    method get_data_info (line 185) | def get_data_info(self, index):
    method get_ann_info (line 256) | def get_ann_info(self, index):
    method _format_bbox (line 305) | def _format_bbox(self, results, jsonfile_prefix=None):
    method _evaluate_single (line 374) | def _evaluate_single(self,
    method format_results (line 427) | def format_results(self, results, jsonfile_prefix=None):
    method evaluate (line 465) | def evaluate(self,
    method show (line 509) | def show(self, results, out_dir):
  function output_to_nusc_box (line 535) | def output_to_nusc_box(detection):
  function lidar_nusc_box_to_global (line 578) | def lidar_nusc_box_to_global(info,

FILE: mmdet3d/datasets/nuscenes_dataset_viewInfo.py
  class NuScenesDataset_ViewInfo (line 15) | class NuScenesDataset_ViewInfo(NuScenesDataset):
    method get_ann_info (line 20) | def get_ann_info(self, index):
    method get_data_info (line 132) | def get_data_info(self, index):

FILE: mmdet3d/datasets/pipelines/data_augment_utils.py
  function _rotation_box2d_jit_ (line 12) | def _rotation_box2d_jit_(corners, angle, rot_mat_T):
  function box_collision_test (line 30) | def box_collision_test(boxes, qboxes, clockwise=True):
  function noise_per_box (line 127) | def noise_per_box(boxes, valid_mask, loc_noises, rot_noises):
  function noise_per_box_v2_ (line 168) | def noise_per_box_v2_(boxes, valid_mask, loc_noises, rot_noises,
  function _select_transform (line 234) | def _select_transform(transform, indices):
  function _rotation_matrix_3d_ (line 253) | def _rotation_matrix_3d_(rot_mat_T, angle, axis):
  function points_transform_ (line 282) | def points_transform_(points, centers, point_masks, loc_transform,
  function box3d_transform_ (line 312) | def box3d_transform_(boxes, loc_transform, rot_transform, valid_mask):
  function noise_per_object_v3_ (line 328) | def noise_per_object_v3_(gt_boxes,

FILE: mmdet3d/datasets/pipelines/dbsampler.py
  class BatchSampler (line 12) | class BatchSampler:
    method __init__ (line 23) | def __init__(self,
    method _sample (line 41) | def _sample(self, num):
    method _reset (line 58) | def _reset(self):
    method sample (line 66) | def sample(self, num):
  class DataBaseSampler (line 80) | class DataBaseSampler(object):
    method __init__ (line 94) | def __init__(self,
    method filter_by_difficulty (line 150) | def filter_by_difficulty(db_infos, removed_difficulty):
    method filter_by_min_points (line 169) | def filter_by_min_points(db_infos, min_gt_points_dict):
    method sample_all (line 190) | def sample_all(self, gt_bboxes, gt_labels, img=None):
    method sample_class_v2 (line 279) | def sample_class_v2(self, name, num, gt_bboxes):

FILE: mmdet3d/datasets/pipelines/formating.py
  class DefaultFormatBundle (line 13) | class DefaultFormatBundle(object):
    method __init__ (line 30) | def __init__(self, ):
    method __call__ (line 33) | def __call__(self, results):
    method __repr__ (line 95) | def __repr__(self):
  class Collect3D (line 100) | class Collect3D(object):
    method __init__ (line 150) | def __init__(self,
    method __call__ (line 163) | def __call__(self, results):
    method __repr__ (line 186) | def __repr__(self):
  class DefaultFormatBundle3D (line 193) | class DefaultFormatBundle3D(DefaultFormatBundle):
    method __init__ (line 208) | def __init__(self, class_names, with_gt=True, with_label=True):
    method __call__ (line 214) | def __call__(self, results):
    method __repr__ (line 274) | def __repr__(self):

FILE: mmdet3d/datasets/pipelines/loading.py
  class MyResize (line 13) | class MyResize(object):
    method __init__ (line 53) | def __init__(self,
    method random_select (line 86) | def random_select(img_scales):
    method random_sample (line 104) | def random_sample(img_scales):
    method random_sample_ratio (line 131) | def random_sample_ratio(img_scale, ratio_range):
    method _random_scale (line 157) | def _random_scale(self, results):
    method _resize_img (line 190) | def _resize_img(self, results):
    method _resize_bboxes (line 227) | def _resize_bboxes(self, results):
    method _resize_centers (line 237) | def _resize_centers(self, results):
    method _resize_masks (line 245) | def _resize_masks(self, results):
    method _resize_seg (line 255) | def _resize_seg(self, results):
    method _resize_camera (line 272) | def _resize_camera(self, results):
    method __call__ (line 284) | def __call__(self, results):
    method __repr__ (line 327) | def __repr__(self):
  class MyNormalize (line 338) | class MyNormalize(object):
    method __init__ (line 350) | def __init__(self, mean, std, to_rgb=True):
    method __call__ (line 355) | def __call__(self, results):
    method __repr__ (line 373) | def __repr__(self):
  class MyPad (line 380) | class MyPad(object):
    method __init__ (line 393) | def __init__(self, size=None, size_divisor=None, pad_val=0):
    method _pad_img (line 401) | def _pad_img(self, results):
    method _pad_masks (line 416) | def _pad_masks(self, results):
    method _pad_seg (line 422) | def _pad_seg(self, results):
    method __call__ (line 429) | def __call__(self, results):
    method __repr__ (line 443) | def __repr__(self):
  class LoadMultiViewImageFromFiles (line 452) | class LoadMultiViewImageFromFiles(object):
    method __init__ (line 463) | def __init__(self, to_float32=False, img_scale=None, color_type='uncha...
    method pad (line 468) | def pad(self, img):
    method __call__ (line 474) | def __call__(self, results):
    method __repr__ (line 518) | def __repr__(self):
  class LoadPointsFromMultiSweeps (line 525) | class LoadPointsFromMultiSweeps(object):
    method __init__ (line 546) | def __init__(self,
    method _load_points (line 563) | def _load_points(self, pts_filename):
    method _remove_close (line 585) | def _remove_close(self, points, radius=1.0):
    method __call__ (line 607) | def __call__(self, results):
    method __repr__ (line 657) | def __repr__(self):
  class PointSegClassMapping (line 663) | class PointSegClassMapping(object):
    method __init__ (line 673) | def __init__(self, valid_cat_ids):
    method __call__ (line 676) | def __call__(self, results):
    method __repr__ (line 702) | def __repr__(self):
  class NormalizePointsColor (line 710) | class NormalizePointsColor(object):
    method __init__ (line 717) | def __init__(self, color_mean):
    method __call__ (line 720) | def __call__(self, results):
    method __repr__ (line 739) | def __repr__(self):
  class LoadPointsFromFile (line 747) | class LoadPointsFromFile(object):
    method __init__ (line 769) | def __init__(self,
    method _load_points (line 788) | def _load_points(self, pts_filename):
    method __call__ (line 811) | def __call__(self, results):
    method __repr__ (line 842) | def __repr__(self):
  class LoadAnnotations3D (line 853) | class LoadAnnotations3D(LoadAnnotations):
    method __init__ (line 885) | def __init__(self,
    method _load_bboxes_3d (line 910) | def _load_bboxes_3d(self, results):
    method _load_labels_3d (line 923) | def _load_labels_3d(self, results):
    method _load_masks_3d (line 935) | def _load_masks_3d(self, results):
    method _load_semantic_seg_3d (line 960) | def _load_semantic_seg_3d(self, results):
    method __call__ (line 987) | def __call__(self, results):
    method __repr__ (line 1011) | def __repr__(self):
  class MyLoadAnnotations3D (line 1028) | class MyLoadAnnotations3D(LoadAnnotations3D):
    method __init__ (line 1029) | def __init__(self, with_bbox_3d=True, with_label_3d=True, with_mask_3d...
    method __call__ (line 1048) | def __call__(self, results):
    method _load_centers_2d (line 1070) | def _load_centers_2d(self, results):
    method _load_cam_box (line 1084) | def _load_cam_box(self, results):
    method _load_visible (line 1098) | def _load_visible(self, results):
  class SparseDepth (line 1105) | class SparseDepth(object):
    method __init__ (line 1109) | def __init__(self, scale_factors, depth_mean=14.41, depth_var=156.89, ...
    method __call__ (line 1115) | def __call__(self, results):

FILE: mmdet3d/datasets/pipelines/test_time_aug.py
  class MultiScaleFlipAug3D (line 10) | class MultiScaleFlipAug3D(object):
    method __init__ (line 32) | def __init__(self,
    method __call__ (line 69) | def __call__(self, results):
    method __repr__ (line 118) | def __repr__(self):

FILE: mmdet3d/datasets/pipelines/transforms_2d.py
  class OurRandomAffine (line 15) | class OurRandomAffine:
    method __init__ (line 52) | def __init__(self,
    method _transform_bbox (line 76) | def _transform_bbox(self, results, warp_mats, flips, width, height):
    method _transform_camera (line 170) | def _transform_camera(self, results, warp_mats, flips, width):
    method __call__ (line 196) | def __call__(self, results):
    method __repr__ (line 278) | def __repr__(self):
    method _get_scaling_matrix (line 288) | def _get_scaling_matrix(scale_ratio):
    method _get_translation_matrix (line 295) | def _get_translation_matrix(x, y):
    method _get_flip_matrix (line 301) | def _get_flip_matrix(flip, width):
  class PhotoMetricDistortionMultiViewImage (line 314) | class PhotoMetricDistortionMultiViewImage:
    method __init__ (line 333) | def __init__(self,
    method __call__ (line 345) | def __call__(self, results):
    method __repr__ (line 413) | def __repr__(self):

FILE: mmdet3d/datasets/pipelines/transforms_3d.py
  class RandomFlip3D (line 14) | class RandomFlip3D(RandomFlip):
    method __init__ (line 32) | def __init__(self,
    method random_flip_data_3d (line 50) | def random_flip_data_3d(self, input_dict, direction='horizontal'):
    method __call__ (line 71) | def __call__(self, input_dict):
    method __repr__ (line 110) | def __repr__(self):
  class OurRandomFlip3D (line 119) | class OurRandomFlip3D(object):
    method __init__ (line 137) | def __init__(self,
    method random_flip_data_3d (line 156) | def random_flip_data_3d(self, input_dict, direction='horizontal'):
    method __call__ (line 194) | def __call__(self, input_dict):
    method __repr__ (line 233) | def __repr__(self):
  class ObjectSample (line 243) | class ObjectSample(object):
    method __init__ (line 253) | def __init__(self, db_sampler, sample_2d=False):
    method remove_points_in_boxes (line 261) | def remove_points_in_boxes(points, boxes):
    method __call__ (line 275) | def __call__(self, input_dict):
    method __repr__ (line 333) | def __repr__(self):
  class ObjectNoise (line 347) | class ObjectNoise(object):
    method __init__ (line 362) | def __init__(self,
    method __call__ (line 372) | def __call__(self, input_dict):
    method __repr__ (line 401) | def __repr__(self):
  class GlobalRotScaleTrans (line 412) | class GlobalRotScaleTrans(object):
    method __init__ (line 429) | def __init__(self,
    method _trans_bbox_points (line 439) | def _trans_bbox_points(self, input_dict):
    method _rot_bbox_points (line 465) | def _rot_bbox_points(self, input_dict):
    method _scale_bbox_points (line 489) | def _scale_bbox_points(self, input_dict):
    method _random_scale (line 510) | def _random_scale(self, input_dict):
    method __call__ (line 524) | def __call__(self, input_dict):
    method __repr__ (line 550) | def __repr__(self):
  class OurGlobalRotScaleTrans (line 560) | class OurGlobalRotScaleTrans(object):
    method __init__ (line 577) | def __init__(self,
    method _trans_bbox_points (line 587) | def _trans_bbox_points(self, input_dict):
    method _rot_bbox_points (line 622) | def _rot_bbox_points(self, input_dict):
    method _scale_bbox_points (line 653) | def _scale_bbox_points(self, input_dict):
    method _random_scale (line 688) | def _random_scale(self, input_dict):
    method _random_rotation (line 702) | def _random_rotation(self, input_dict):
    method __call__ (line 709) | def __call__(self, input_dict):
    method __repr__ (line 737) | def __repr__(self):
  class PointShuffle (line 748) | class PointShuffle(object):
    method __call__ (line 751) | def __call__(self, input_dict):
    method __repr__ (line 764) | def __repr__(self):
  class ObjectRangeFilter (line 769) | class ObjectRangeFilter(object):
    method __init__ (line 776) | def __init__(self, point_cloud_range):
    method __call__ (line 780) | def __call__(self, input_dict):
    method __repr__ (line 807) | def __repr__(self):
  class OurObjectRangeFilter (line 816) | class OurObjectRangeFilter(object):
    method __init__ (line 823) | def __init__(self, point_cloud_range):
    method __call__ (line 827) | def __call__(self, input_dict):
    method __repr__ (line 872) | def __repr__(self):
  class PointsRangeFilter (line 880) | class PointsRangeFilter(object):
    method __init__ (line 887) | def __init__(self, point_cloud_range):
    method __call__ (line 890) | def __call__(self, input_dict):
    method __repr__ (line 906) | def __repr__(self):
  class ObjectNameFilter (line 914) | class ObjectNameFilter(object):
    method __init__ (line 921) | def __init__(self, classes):
    method __call__ (line 925) | def __call__(self, input_dict):
    method __repr__ (line 964) | def __repr__(self):
  class IndoorPointSample (line 972) | class IndoorPointSample(object):
    method __init__ (line 982) | def __init__(self, num_points):
    method points_random_sampling (line 985) | def points_random_sampling(self,
    method __call__ (line 1016) | def __call__(self, results):
    method __repr__ (line 1042) | def __repr__(self):
  class BackgroundPointsFilter (line 1050) | class BackgroundPointsFilter(object):
    method __init__ (line 1057) | def __init__(self, bbox_enlarge_range):
    method __call__ (line 1068) | def __call__(self, input_dict):
    method __repr__ (line 1105) | def __repr__(self):
  class VoxelBasedPointSampler (line 1114) | class VoxelBasedPointSampler(object):
    method __init__ (line 1126) | def __init__(self, cur_sweep_cfg, prev_sweep_cfg=None, time_dim=3):
    method _sample_points (line 1139) | def _sample_points(self, points, sampler, point_dim):
    method __call__ (line 1165) | def __call__(self, results):
    method __repr__ (line 1233) | def __repr__(self):

FILE: mmdet3d/datasets/scannet_dataset.py
  class ScanNetDataset (line 11) | class ScanNetDataset(Custom3DDataset):
    method __init__ (line 46) | def __init__(self,
    method get_ann_info (line 65) | def get_ann_info(self, index):
    method show (line 109) | def show(self, results, out_dir, show=True):

FILE: mmdet3d/datasets/semantickitti_dataset.py
  class SemanticKITTIDataset (line 8) | class SemanticKITTIDataset(Custom3DDataset):
    method __init__ (line 43) | def __init__(self,
    method get_ann_info (line 62) | def get_ann_info(self, index):

FILE: mmdet3d/datasets/sunrgbd_dataset.py
  class SUNRGBDDataset (line 13) | class SUNRGBDDataset(Custom3DDataset):
    method __init__ (line 46) | def __init__(self,
    method get_data_info (line 68) | def get_data_info(self, index):
    method get_ann_info (line 112) | def get_ann_info(self, index):
    method show (line 154) | def show(self, results, out_dir, show=True):
    method evaluate (line 176) | def evaluate(self,

FILE: mmdet3d/datasets/waymo_dataset.py
  class WaymoDataset (line 15) | class WaymoDataset(KittiDataset):
    method __init__ (line 54) | def __init__(self,
    method _get_pts_filename (line 88) | def _get_pts_filename(self, idx):
    method get_data_info (line 93) | def get_data_info(self, index):
    method format_results (line 165) | def format_results(self,
    method evaluate (line 247) | def evaluate(self,
    method bbox2result_kitti (line 384) | def bbox2result_kitti(self,
    method convert_valid_bboxes (line 499) | def convert_valid_bboxes(self, box_dict, info):

FILE: mmdet3d/models/backbones/DLA.py
  function get_model_url (line 24) | def get_model_url(data='imagenet', name='dla34', hash='ba72cf86'):
  function conv3x3 (line 28) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 34) | class BasicBlock(nn.Module):
    method __init__ (line 35) | def __init__(self, inplanes, planes, stride=1, dilation=1):
    method forward (line 48) | def forward(self, x, residual=None):
  class Bottleneck (line 65) | class Bottleneck(nn.Module):
    method __init__ (line 68) | def __init__(self, inplanes, planes, stride=1, dilation=1):
    method forward (line 85) | def forward(self, x, residual=None):
  class BottleneckX (line 106) | class BottleneckX(nn.Module):
    method __init__ (line 110) | def __init__(self, inplanes, planes, stride=1, dilation=1):
    method forward (line 129) | def forward(self, x, residual=None):
  class Root (line 150) | class Root(nn.Module):
    method __init__ (line 151) | def __init__(self, in_channels, out_channels, kernel_size, residual):
    method forward (line 160) | def forward(self, *x):
  class Tree (line 171) | class Tree(nn.Module):
    method __init__ (line 172) | def __init__(self, levels, block, in_channels, out_channels, stride=1,
    method forward (line 211) | def forward(self, x, residual=None, children=None):
  class DLA (line 227) | class DLA(nn.Module):
    method __init__ (line 228) | def __init__(self, levels, channels, num_classes=1000,
    method _make_level (line 272) | def _make_level(self, block, inplanes, planes, blocks, stride=1):
    method _make_conv_level (line 289) | def _make_conv_level(self, inplanes, planes, convs, stride=1, dilation...
    method forward (line 301) | def forward(self, x, pre_img=None, pre_hm=None):
    method load_pretrained_model (line 314) | def load_pretrained_model(self, data='imagenet', name='dla34', hash='b...
  function dla34 (line 329) | def dla34(pretrained=True, **kwargs):  # DLA-34
  function dla102 (line 341) | def dla102(pretrained=None, **kwargs):  # DLA-102
  function dla46_c (line 351) | def dla46_c(pretrained=None, **kwargs):  # DLA-46-C
  function dla46x_c (line 362) | def dla46x_c(pretrained=None, **kwargs):  # DLA-X-46-C
  function dla60x_c (line 373) | def dla60x_c(pretrained=None, **kwargs):  # DLA-X-60-C
  function dla60 (line 384) | def dla60(pretrained=None, **kwargs):  # DLA-60
  function dla60x (line 395) | def dla60x(pretrained=None, **kwargs):  # DLA-X-60
  function dla102x (line 406) | def dla102x(pretrained=None, **kwargs):  # DLA-X-102
  function dla102x2 (line 416) | def dla102x2(pretrained=None, **kwargs):  # DLA-X-102 64
  function dla169 (line 426) | def dla169(pretrained=None, **kwargs):  # DLA-169
  class Identity (line 436) | class Identity(nn.Module):
    method __init__ (line 438) | def __init__(self):
    method forward (line 441) | def forward(self, x):
  function fill_fc_weights (line 445) | def fill_fc_weights(layers):
  function fill_up_weights (line 452) | def fill_up_weights(up):
  class Conv (line 464) | class Conv(nn.Module):
    method __init__ (line 465) | def __init__(self, chi, cho):
    method forward (line 472) | def forward(self, x):
  class GlobalConv (line 476) | class GlobalConv(nn.Module):
    method __init__ (line 477) | def __init__(self, chi, cho, k=7, d=1):
    method forward (line 498) | def forward(self, x):
  class DeformConv (line 504) | class DeformConv(nn.Module):
    method __init__ (line 505) | def __init__(self, chi, cho):
    method forward (line 513) | def forward(self, x):
  class IDAUp (line 519) | class IDAUp(nn.Module):
    method __init__ (line 520) | def __init__(self, o, channels, up_f, node_type=(DeformConv, DeformCon...
    method forward (line 537) | def forward(self, layers, startp, endp):
  class DLAUp (line 546) | class DLAUp(nn.Module):
    method __init__ (line 547) | def __init__(self, startp, channels, scales, in_channels=None,
    method forward (line 565) | def forward(self, layers):
  class Interpolate (line 574) | class Interpolate(nn.Module):
    method __init__ (line 575) | def __init__(self, scale, mode):
    method forward (line 580) | def forward(self, x):
  class BaseModel (line 592) | class BaseModel(nn.Module):
    method __init__ (line 593) | def __init__(self, heads, head_convs, num_stacks, last_channel, opt=No...
    method img2feats (line 645) | def img2feats(self, x):
    method imgpre2feats (line 648) | def imgpre2feats(self, x, pre_img=None, pre_hm=None):
    method forward (line 651) | def forward(self, x, pre_img=None, pre_hm=None):
  class DLASeg (line 674) | class DLASeg(BaseModel):
    method __init__ (line 675) | def __init__(self, num_layers, heads, head_convs):
    method init_weights (line 699) | def init_weights(self, pretrained=None):
    method img2feats (line 706) | def img2feats(self, x):
    method imgpre2feats (line 717) | def imgpre2feats(self, x, pre_img=None, pre_hm=None):
  class Opt (line 729) | class Opt:

FILE: mmdet3d/models/backbones/base_pointnet.py
  class BasePointNet (line 6) | class BasePointNet(nn.Module, metaclass=ABCMeta):
    method __init__ (line 9) | def __init__(self):
    method init_weights (line 13) | def init_weights(self, pretrained=None):
    method _split_point_feats (line 23) | def _split_point_feats(points):

FILE: mmdet3d/models/backbones/multi_backbone.py
  class MultiBackbone (line 11) | class MultiBackbone(nn.Module):
    method __init__ (line 26) | def __init__(self,
    method init_weights (line 80) | def init_weights(self, pretrained=None):
    method forward (line 90) | def forward(self, points):

FILE: mmdet3d/models/backbones/nostem_regnet.py
  class NoStemRegNet (line 6) | class NoStemRegNet(RegNet):
    method __init__ (line 60) | def __init__(self, arch, **kwargs):
    method _make_stem_layer (line 63) | def _make_stem_layer(self, in_channels, base_channels):
    method forward (line 68) | def forward(self, x):

FILE: mmdet3d/models/backbones/pointnet2_sa_msg.py
  class PointNet2SAMSG (line 12) | class PointNet2SAMSG(BasePointNet):
    method __init__ (line 40) | def __init__(self,
    method forward (line 116) | def forward(self, points):

FILE: mmdet3d/models/backbones/pointnet2_sa_ssg.py
  class PointNet2SASSG (line 11) | class PointNet2SASSG(BasePointNet):
    method __init__ (line 33) | def __init__(self,
    method forward (line 88) | def forward(self, points):

FILE: mmdet3d/models/backbones/second.py
  class SECOND (line 9) | class SECOND(nn.Module):
    method __init__ (line 21) | def __init__(self,
    method init_weights (line 64) | def init_weights(self, pretrained=None):
    method forward (line 73) | def forward(self, x):

FILE: mmdet3d/models/backbones/swin.py
  function _no_grad_trunc_normal_ (line 23) | def _no_grad_trunc_normal_(tensor: Tensor, mean: float, std: float, a: f...
  function trunc_normal_ (line 63) | def trunc_normal_(tensor: Tensor,
  function trunc_normal_init (line 85) | def trunc_normal_init(module: nn.Module,
  class AdaptivePadding (line 97) | class AdaptivePadding(nn.Module):
    method __init__ (line 127) | def __init__(self, kernel_size=1, stride=1, dilation=1, padding='corne...
    method get_pad_shape (line 143) | def get_pad_shape(self, input_shape):
    method forward (line 155) | def forward(self, x):
  class PatchEmbed (line 168) | class PatchEmbed(BaseModule):
    method __init__ (line 194) | def __init__(
    method forward (line 268) | def forward(self, x):
  class PatchMerging (line 289) | class PatchMerging(BaseModule):
    method __init__ (line 318) | def __init__(self,
    method forward (line 367) | def forward(self, x, input_size):
  function swin_converter (line 412) | def swin_converter(ckpt):
  class WindowMSA (line 467) | class WindowMSA(BaseModule):
    method __init__ (line 486) | def __init__(self,
    method init_weights (line 523) | def init_weights(self):
    method forward (line 526) | def forward(self, x, mask=None):
    method double_step_seq (line 567) | def double_step_seq(step1, len1, step2, len2):
  class ShiftWindowMSA (line 573) | class ShiftWindowMSA(BaseModule):
    method __init__ (line 596) | def __init__(self,
    method forward (line 625) | def forward(self, query, hw_shape):
    method window_reverse (line 701) | def window_reverse(self, windows, H, W):
    method window_partition (line 717) | def window_partition(self, x):
  class SwinBlock (line 733) | class SwinBlock(BaseModule):
    method __init__ (line 758) | def __init__(self,
    method forward (line 803) | def forward(self, x, hw_shape):
  class SwinBlockSequence (line 826) | class SwinBlockSequence(BaseModule):
    method __init__ (line 855) | def __init__(self,
    method forward (line 900) | def forward(self, x, hw_shape):
  class SwinTransformer (line 912) | class SwinTransformer(BaseModule):
    method __init__ (line 969) | def __init__(self,
    method train (line 1087) | def train(self, mode=True):
    method _freeze_stages (line 1092) | def _freeze_stages(self):
    method init_weights (line 1114) | def init_weights(self, pretrained=None):
    method forward (line 1191) | def forward(self, x):

FILE: mmdet3d/models/builder.py
  function build_backbone (line 8) | def build_backbone(cfg):
  function build_neck (line 13) | def build_neck(cfg):
  function build_roi_extractor (line 18) | def build_roi_extractor(cfg):
  function build_shared_head (line 23) | def build_shared_head(cfg):
  function build_head (line 28) | def build_head(cfg):
  function build_loss (line 33) | def build_loss(cfg):
  function build_detector (line 38) | def build_detector(cfg, train_cfg=None, test_cfg=None):
  function build_voxel_encoder (line 51) | def build_voxel_encoder(cfg):
  function build_middle_encoder (line 56) | def build_middle_encoder(cfg):
  function build_fusion_layer (line 61) | def build_fusion_layer(cfg):

FILE: mmdet3d/models/dense_heads/anchor3d_head.py
  class Anchor3DHead (line 17) | class Anchor3DHead(nn.Module, AnchorTrainMixin):
    method __init__ (line 43) | def __init__(self,
    method _init_assigner_sampler (line 106) | def _init_assigner_sampler(self):
    method _init_layers (line 122) | def _init_layers(self):
    method init_weights (line 132) | def init_weights(self):
    method forward_single (line 138) | def forward_single(self, x):
    method forward (line 155) | def forward(self, feats):
    method get_anchors (line 168) | def get_anchors(self, featmap_sizes, input_metas, device='cuda'):
    method loss_single (line 188) | def loss_single(self, cls_score, bbox_pred, dir_cls_preds, labels,
    method add_sin_difference (line 275) | def add_sin_difference(boxes1, boxes2):
    method loss (line 299) | def loss(self,
    method get_bboxes (line 370) | def get_bboxes(self,
    method get_bboxes_single (line 421) | def get_bboxes_single(self,

FILE: mmdet3d/models/dense_heads/base_conv_bbox_head.py
  class BaseConvBboxHead (line 9) | class BaseConvBboxHead(nn.Module):
    method __init__ (line 20) | def __init__(self,
    method _add_conv_branch (line 81) | def _add_conv_branch(self, in_channels, conv_channels):
    method init_weights (line 101) | def init_weights(self):
    method forward (line 105) | def forward(self, feats):

FILE: mmdet3d/models/dense_heads/centerpoint_head.py
  class SeparateHead (line 18) | class SeparateHead(nn.Module):
    method __init__ (line 36) | def __init__(self,
    method init_weights (line 81) | def init_weights(self):
    method forward (line 91) | def forward(self, x):
  class DCNSeparateHead (line 122) | class DCNSeparateHead(nn.Module):
    method __init__ (line 146) | def __init__(self,
    method init_weights (line 196) | def init_weights(self):
    method forward (line 201) | def forward(self, x):
  class CenterHead (line 235) | class CenterHead(nn.Module):
    method __init__ (line 266) | def __init__(self,
    method init_weights (line 319) | def init_weights(self):
    method forward_single (line 324) | def forward_single(self, x):
    method forward (line 343) | def forward(self, feats):
    method _gather_feat (line 355) | def _gather_feat(self, feat, ind, mask=None):
    method get_targets (line 380) | def get_targets(self, gt_bboxes_3d, gt_labels_3d):
    method get_targets_single (line 417) | def get_targets_single(self, gt_bboxes_3d, gt_labels_3d):
    method loss (line 556) | def loss(self, gt_bboxes_3d, gt_labels_3d, preds_dicts, **kwargs):
    method get_bboxes (line 605) | def get_bboxes(self, preds_dicts, img_metas, img=None, rescale=False):
    method get_task_detections (line 699) | def get_task_detections(self, num_class_with_bg, batch_cls_preds,

FILE: mmdet3d/models/dense_heads/free_anchor3d_head.py
  class FreeAnchor3DHead (line 12) | class FreeAnchor3DHead(Anchor3DHead):
    method __init__ (line 30) | def __init__(self,
    method loss (line 43) | def loss(self,
    method positive_bag_loss (line 244) | def positive_bag_loss(self, matched_cls_prob, matched_box_prob):
    method negative_bag_loss (line 266) | def negative_bag_loss(self, cls_prob, box_prob):

FILE: mmdet3d/models/dense_heads/parta2_rpn_head.py
  class PartA2RPNHead (line 14) | class PartA2RPNHead(Anchor3DHead):
    method __init__ (line 51) | def __init__(self,
    method loss (line 86) | def loss(self,
    method get_bboxes_single (line 126) | def get_bboxes_single(self,
    method class_agnostic_nms (line 222) | def class_agnostic_nms(self, mlvl_bboxes, mlvl_bboxes_for_nms,

FILE: mmdet3d/models/dense_heads/shape_aware_head.py
  class BaseShapeHead (line 14) | class BaseShapeHead(nn.Module):
    method __init__ (line 41) | def __init__(self,
    method init_weights (line 88) | def init_weights(self):
    method forward (line 97) | def forward(self, x):
  class ShapeAwareHead (line 141) | class ShapeAwareHead(Anchor3DHead):
    method __init__ (line 152) | def __init__(self, tasks, assign_per_class=True, **kwargs):
    method _init_layers (line 157) | def _init_layers(self):
    method init_weights (line 178) | def init_weights(self):
    method forward_single (line 183) | def forward_single(self, x):
    method loss_single (line 216) | def loss_single(self, cls_score, bbox_pred, dir_cls_preds, labels,
    method loss (line 278) | def loss(self,
    method get_bboxes (line 345) | def get_bboxes(self,
    method get_bboxes_single (line 397) | def get_bboxes_single(self,

FILE: mmdet3d/models/dense_heads/sparsefusion_head_deform.py
  class SparseFusionHead2D_Deform (line 30) | class SparseFusionHead2D_Deform(nn.Module):
    method __init__ (line 31) | def __init__(self,
    method create_2D_grid (line 260) | def create_2D_grid(self, x_size, y_size):
    method init_bn_momentum (line 269) | def init_bn_momentum(self):
    method init_weights (line 274) | def init_weights(self):
    method _init_assigner_sampler (line 292) | def _init_assigner_sampler(self):
    method forward_single (line 314) | def forward_single(self, inputs, img_inputs, img_metas, sparse_depth):
    method forward (line 473) | def forward(self, feats, img_feats, img_metas, sparse_depth=None):
    method construct_input_padding_mask (line 496) | def construct_input_padding_mask(self, img_feats, img_metas):
    method construction_view_projection_matrix (line 529) | def construction_view_projection_matrix(self, proj_matrix, img_query_v...
    method construct_projection_matrix (line 538) | def construct_projection_matrix(self, img_metas, device):
    method build_heatmap_LN (line 555) | def build_heatmap_LN(self, hidden_channel, bias, num_classes, layer_nu...
    method build_heatmap (line 575) | def build_heatmap(self, hidden_channel, bias, num_classes, layer_num=2...
    method generate_heatmap_deform (line 598) | def generate_heatmap_deform(self, lidar_feat, img_feat, voxel_height, ...
    method generate_heatmap (line 762) | def generate_heatmap(self, lidar_feat, min_voxel_height, max_voxel_hei...
    method generate_heatmap_img (line 797) | def generate_heatmap_img(self, img_feats, batch_size):
    method get_targets (line 837) | def get_targets(self, gt_bboxes_3d, gt_labels_3d, gt_bboxes, gt_labels...
    method get_targets_single_2d (line 916) | def get_targets_single_2d(self, gt_bboxes, gt_labels, gt_centers_2d, g...
    method get_targets_single (line 1129) | def get_targets_single(self, gt_bboxes_3d, gt_labels_3d, gt_visible, p...
    method get_targets_single_view (line 1293) | def get_targets_single_view(self, gt_bboxes_3d, gt_labels_3d, gt_visib...
    method loss (line 1411) | def loss(self, gt_bboxes_3d, gt_labels_3d, gt_bboxes, gt_labels, gt_pt...
    method get_bboxes (line 1615) | def get_bboxes(self, preds_dicts, img_metas, img=None, rescale=False, ...
    method get_layer_num_proposal (line 1737) | def get_layer_num_proposal(self, idx_layer):

FILE: mmdet3d/models/dense_heads/ssd_3d_head.py
  class SSD3DHead (line 16) | class SSD3DHead(VoteHead):
    method __init__ (line 42) | def __init__(self,
    method _get_cls_out_channels (line 83) | def _get_cls_out_channels(self):
    method _get_reg_out_channels (line 88) | def _get_reg_out_channels(self):
    method _extract_input (line 95) | def _extract_input(self, feat_dict):
    method loss (line 113) | def loss(self,
    method get_targets (line 219) | def get_targets(self,
    method get_targets_single (line 307) | def get_targets_single(self,
    method get_bboxes (line 439) | def get_bboxes(self, points, bbox_preds, input_metas, rescale=False):
    method multiclass_nms_single (line 471) | def multiclass_nms_single(self, obj_scores, sem_scores, bbox, points,
    method _assign_targets_by_points_inside (line 545) | def _assign_targets_by_points_inside(self, bboxes_3d, points):

FILE: mmdet3d/models/dense_heads/train_mixins.py
  class AnchorTrainMixin (line 8) | class AnchorTrainMixin(object):
    method anchor_target_3d (line 11) | def anchor_target_3d(self,
    method anchor_target_3d_single (line 101) | def anchor_target_3d_single(self,
    method anchor_target_single_assigner (line 237) | def anchor_target_single_assigner(self,
  function get_direction_target (line 317) | def get_direction_target(anchors,

FILE: mmdet3d/models/dense_heads/transfusion_head.py
  class PositionEmbeddingLearned (line 25) | class PositionEmbeddingLearned(nn.Module):
    method __init__ (line 30) | def __init__(self, input_channel, num_pos_feats=288):
    method forward (line 38) | def forward(self, xyz):
  class TransformerDecoderLayer (line 44) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 45) | def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, ...
    method with_pos_embed (line 79) | def with_pos_embed(self, tensor, pos_embed):
    method forward (line 82) | def forward(self, query, key, query_pos, key_pos, attn_mask=None):
  class MultiheadAttention (line 125) | class MultiheadAttention(nn.Module):
    method __init__ (line 149) | def __init__(self, embed_dim, num_heads, dropout=0., bias=True, add_bi...
    method _reset_parameters (line 185) | def _reset_parameters(self):
    method forward (line 201) | def forward(self, query, key, value, key_padding_mask=None, need_weigh...
  function multi_head_attention_forward (line 255) | def multi_head_attention_forward(query,  # type: Tensor
  class FFN (line 516) | class FFN(nn.Module):
    method __init__ (line 517) | def __init__(self,
    method init_weights (line 562) | def init_weights(self):
    method forward (line 572) | def forward(self, x):
  class TransFusionHead (line 603) | class TransFusionHead(nn.Module):
    method __init__ (line 604) | def __init__(self,
    method create_2D_grid (line 768) | def create_2D_grid(self, x_size, y_size):
    method init_weights (line 777) | def init_weights(self):
    method init_bn_momentum (line 786) | def init_bn_momentum(self):
    method _init_assigner_sampler (line 791) | def _init_assigner_sampler(self):
    method forward_single (line 807) | def forward_single(self, inputs, img_inputs, img_metas):
    method forward (line 1043) | def forward(self, feats, img_feats, img_metas):
    method get_targets (line 1059) | def get_targets(self, gt_bboxes_3d, gt_labels_3d, preds_dict):
    method get_targets_single (line 1100) | def get_targets_single(self, gt_bboxes_3d, gt_labels_3d, preds_dict, b...
    method loss (line 1229) | def loss(self, gt_bboxes_3d, gt_labels_3d, preds_dicts, **kwargs):
    method get_bboxes (line 1296) | def get_bboxes(self, preds_dicts, img_metas, img=None, rescale=False, ...

FILE: mmdet3d/models/dense_heads/vote_head.py
  class VoteHead (line 18) | class VoteHead(nn.Module):
    method __init__ (line 42) | def __init__(self,
    method init_weights (line 95) | def init_weights(self):
    method _get_cls_out_channels (line 99) | def _get_cls_out_channels(self):
    method _get_reg_out_channels (line 104) | def _get_reg_out_channels(self):
    method _extract_input (line 111) | def _extract_input(self, feat_dict):
    method forward (line 138) | def forward(self, feat_dict, sample_mod):
    method loss (line 225) | def loss(self,
    method get_targets (line 353) | def get_targets(self,
    method get_targets_single (line 442) | def get_targets_single(self,
    method get_bboxes (line 566) | def get_bboxes(self,
    method multiclass_nms_single (line 608) | def multiclass_nms_single(self, obj_scores, sem_scores, bbox, points,

FILE: mmdet3d/models/detectors/base.py
  class Base3DDetector (line 11) | class Base3DDetector(BaseDetector):
    method forward_test (line 14) | def forward_test(self, points, img_metas, img=None, **kwargs):
    method forward (line 46) | def forward(self, return_loss=True, **kwargs):
    method show_results (line 62) | def show_results(self, data, result, out_dir):

FILE: mmdet3d/models/detectors/centerpoint.py
  class CenterPoint (line 9) | class CenterPoint(MVXTwoStageDetector):
    method __init__ (line 12) | def __init__(self,
    method extract_pts_feat (line 34) | def extract_pts_feat(self, pts, img_feats, img_metas):
    method forward_pts_train (line 48) | def forward_pts_train(self,
    method simple_test_pts (line 74) | def simple_test_pts(self, x, img_metas, rescale=False):
    method aug_test_pts (line 85) | def aug_test_pts(self, feats, img_metas, rescale=False):
    method aug_test (line 186) | def aug_test(self, points, img_metas, imgs=None, rescale=False):

FILE: mmdet3d/models/detectors/dynamic_voxelnet.py
  class DynamicVoxelNet (line 10) | class DynamicVoxelNet(VoxelNet):
    method __init__ (line 14) | def __init__(self,
    method extract_feat (line 36) | def extract_feat(self, points, img_metas):
    method voxelize (line 49) | def voxelize(self, points):

FILE: mmdet3d/models/detectors/h3dnet.py
  class H3DNet (line 9) | class H3DNet(TwoStage3DDetector):
    method __init__ (line 15) | def __init__(self,
    method forward_train (line 32) | def forward_train(self,
    method simple_test (line 98) | def simple_test(self, points, img_metas, imgs=None, rescale=False):
    method aug_test (line 130) | def aug_test(self, points, img_metas, imgs=None, rescale=False):
    method extract_feats (line 168) | def extract_feats(self, points, img_metas):

FILE: mmdet3d/models/detectors/imvotenet.py
  function sample_valid_seeds (line 12) | def sample_valid_seeds(mask, num_sampled_seed=1024):
  class ImVoteNet (line 53) | class ImVoteNet(Base3DDetector):
    method __init__ (line 56) | def __init__(self,
    method init_weights (line 137) | def init_weights(self, pretrained=None):
    method freeze_img_branch_params (line 173) | def freeze_img_branch_params(self):
    method _load_from_state_dict (line 191) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
    method train (line 205) | def train(self, mode=True):
    method with_img_bbox (line 221) | def with_img_bbox(self):
    method with_img_bbox_head (line 228) | def with_img_bbox_head(self):
    method with_img_backbone (line 234) | def with_img_backbone(self):
    method with_img_neck (line 239) | def with_img_neck(self):
    method with_img_rpn (line 244) | def with_img_rpn(self):
    method with_img_roi_head (line 249) | def with_img_roi_head(self):
    method with_pts_bbox (line 254) | def with_pts_bbox(self):
    method with_pts_backbone (line 260) | def with_pts_backbone(self):
    method with_pts_neck (line 265) | def with_pts_neck(self):
    method extract_feat (line 269) | def extract_feat(self, imgs):
    method extract_img_feat (line 273) | def extract_img_feat(self, img):
    method extract_img_feats (line 280) | def extract_img_feats(self, imgs):
    method extract_pts_feat (line 294) | def extract_pts_feat(self, pts):
    method extract_pts_feats (line 306) | def extract_pts_feats(self, pts):
    method extract_bboxes_2d (line 312) | def extract_bboxes_2d(self,
    method forward_train (line 370) | def forward_train(self,
    method forward_test (line 525) | def forward_test(self,
    method simple_test_img_only (line 610) | def simple_test_img_only(self,
    method simple_test (line 649) | def simple_test(self,
    method aug_test_img_only (line 718) | def aug_test_img_only(self, img, img_metas, rescale=False):
    method aug_test (line 752) | def aug_test(self,

FILE: mmdet3d/models/detectors/mvx_faster_rcnn.py
  class MVXFasterRCNN (line 10) | class MVXFasterRCNN(MVXTwoStageDetector):
    method __init__ (line 13) | def __init__(self, **kwargs):
  class DynamicMVXFasterRCNN (line 18) | class DynamicMVXFasterRCNN(MVXTwoStageDetector):
    method __init__ (line 21) | def __init__(self, **kwargs):
    method voxelize (line 26) | def voxelize(self, points):
    method extract_pts_feat (line 48) | def extract_pts_feat(self, points, img_feats, img_metas):

FILE: mmdet3d/models/detectors/mvx_two_stage.py
  class MVXTwoStageDetector (line 20) | class MVXTwoStageDetector(Base3DDetector):
    method __init__ (line 23) | def __init__(self,
    method init_weights (line 80) | def init_weights(self, pretrained=None):
    method with_pts_roi_head (line 121) | def with_pts_roi_head(self):
    method with_img_shared_head (line 127) | def with_img_shared_head(self):
    method with_pts_bbox (line 133) | def with_pts_bbox(self):
    method with_img_bbox (line 139) | def with_img_bbox(self):
    method with_img_backbone (line 145) | def with_img_backbone(self):
    method with_pts_backbone (line 150) | def with_pts_backbone(self):
    method with_fusion (line 155) | def with_fusion(self):
    method with_img_neck (line 161) | def with_img_neck(self):
    method with_pts_neck (line 166) | def with_pts_neck(self):
    method with_img_rpn (line 171) | def with_img_rpn(self):
    method with_img_roi_head (line 176) | def with_img_roi_head(self):
    method with_voxel_encoder (line 181) | def with_voxel_encoder(self):
    method with_middle_encoder (line 187) | def with_middle_encoder(self):
    method extract_img_feat (line 192) | def extract_img_feat(self, img, img_metas):
    method extract_pts_feat (line 213) | def extract_pts_feat(self, pts, img_feats, img_metas):
    method extract_feat (line 227) | def extract_feat(self, points, img, img_metas):
    method voxelize (line 236) | def voxelize(self, points):
    method forward_train (line 261) | def forward_train(self,
    method forward_pts_train (line 315) | def forward_pts_train(self,
    method forward_img_train (line 342) | def forward_img_train(self,
    method simple_test_img (line 396) | def simple_test_img(self, x, img_metas, proposals=None, rescale=False):
    method simple_test_rpn (line 407) | def simple_test_rpn(self, x, img_metas, rpn_test_cfg):
    method simple_test_pts (line 414) | def simple_test_pts(self, x, x_img, img_metas, rescale=False):
    method simple_test (line 425) | def simple_test(self, points, img_metas, img=None, rescale=False):
    method aug_test (line 443) | def aug_test(self, points, img_metas, imgs=None, rescale=False):
    method extract_feats (line 453) | def extract_feats(self, points, img_metas, imgs=None):
    method aug_test_pts (line 461) | def aug_test_pts(self, feats, img_metas, rescale=False):
    method show_results (line 480) | def show_results(self, data, result, out_dir):

FILE: mmdet3d/models/detectors/parta2.py
  class PartA2 (line 11) | class PartA2(TwoStage3DDetector):
    method __init__ (line 17) | def __init__(self,
    method extract_feat (line 41) | def extract_feat(self, points, img_metas):
    method voxelize (line 57) | def voxelize(self, points):
    method forward_train (line 87) | def forward_train(self,
    method simple_test (line 136) | def simple_test(self, points, img_metas, proposals=None, rescale=False):

FILE: mmdet3d/models/detectors/single_stage.py
  class SingleStage3DDetector (line 8) | class SingleStage3DDetector(Base3DDetector):
    method __init__ (line 25) | def __init__(self,
    method init_weights (line 43) | def init_weights(self, pretrained=None):
    method extract_feat (line 55) | def extract_feat(self, points, img_metas=None):
    method extract_feats (line 66) | def extract_feats(self, points, img_metas):

FILE: mmdet3d/models/detectors/sparsefusion.py
  class SparseFusionDetector (line 21) | class SparseFusionDetector(MVXTwoStageDetector):
    method __init__ (line 24) | def __init__(self, **kwargs):
    method init_weights (line 32) | def init_weights(self, pretrained=None):
    method extract_img_feat (line 51) | def extract_img_feat(self, img, img_metas):
    method extract_voxel_heights (line 73) | def extract_voxel_heights(self, voxels, coors):
    method extract_pts_feat (line 114) | def extract_pts_feat(self, pts, img_feats, img_metas):
    method voxelize (line 135) | def voxelize(self, points):
    method forward_train (line 163) | def forward_train(self,
    method forward_pts_train (line 223) | def forward_pts_train(self,
    method simple_test_pts (line 259) | def simple_test_pts(self, x, x_img, img_metas, rescale=False, sparse_d...
    method simple_test (line 273) | def simple_test(self, points, img_metas, img=None, sparse_depth=None, ...
    method forward_test (line 292) | def forward_test(self, points, img_metas, img=None, sparse_depth=None,...

FILE: mmdet3d/models/detectors/ssd3dnet.py
  class SSD3DNet (line 6) | class SSD3DNet(VoteNet):
    method __init__ (line 12) | def __init__(self,

FILE: mmdet3d/models/detectors/transfusion.py
  class TransFusionDetector (line 20) | class TransFusionDetector(MVXTwoStageDetector):
    method __init__ (line 23) | def __init__(self, **kwargs):
    method init_weights (line 29) | def init_weights(self, pretrained=None):
    method extract_img_feat (line 41) | def extract_img_feat(self, img, img_metas):
    method extract_pts_feat (line 62) | def extract_pts_feat(self, pts, img_feats, img_metas):
    method voxelize (line 80) | def voxelize(self, points):
    method forward_train (line 105) | def forward_train(self,
    method forward_pts_train (line 159) | def forward_pts_train(self,
    method simple_test_pts (line 186) | def simple_test_pts(self, x, x_img, img_metas, rescale=False):
    method simple_test (line 197) | def simple_test(self, points, img_metas, img=None, rescale=False):

FILE: mmdet3d/models/detectors/two_stage.py
  class TwoStage3DDetector (line 6) | class TwoStage3DDetector(Base3DDetector, TwoStageDetector):
    method __init__ (line 14) | def __init__(self, **kwargs):

FILE: mmdet3d/models/detectors/votenet.py
  class VoteNet (line 9) | class VoteNet(SingleStage3DDetector):
    method __init__ (line 12) | def __init__(self,
    method forward_train (line 25) | def forward_train(self,
    method simple_test (line 60) | def simple_test(self, points, img_metas, imgs=None, rescale=False):
    method aug_test (line 83) | def aug_test(self, points, img_metas, imgs=None, rescale=False):

FILE: mmdet3d/models/detectors/voxelnet.py
  class VoxelNet (line 13) | class VoxelNet(SingleStage3DDetector):
    method __init__ (line 16) | def __init__(self,
    method extract_feat (line 38) | def extract_feat(self, points, img_metas):
    method voxelize (line 51) | def voxelize(self, points):
    method forward_train (line 68) | def forward_train(self,
    method simple_test (line 96) | def simple_test(self, points, img_metas, imgs=None, rescale=False):
    method aug_test (line 108) | def aug_test(self, points, img_metas, imgs=None, rescale=False):

FILE: mmdet3d/models/fusion_layers/coord_transform.py
  function apply_3d_transformation (line 7) | def apply_3d_transformation(pcd, coords_type, img_meta, reverse=False):
  function extract_2d_info (line 93) | def extract_2d_info(img_meta, tensor):
  function bbox_2d_transform (line 121) | def bbox_2d_transform(img_meta, bbox_2d, ori2new):
  function coord_2d_transform (line 175) | def coord_2d_transform(img_meta, coord_2d, ori2new):

FILE: mmdet3d/models/fusion_layers/point_fusion.py
  function point_sample (line 10) | def point_sample(
  class PointFusion (line 99) | class PointFusion(nn.Module):
    method __init__ (line 132) | def __init__(self,
    method init_weights (line 206) | def init_weights(self):
    method forward (line 212) | def forward(self, img_feats, pts, pts_feats, img_metas):
    method obtain_mlvl_feats (line 239) | def obtain_mlvl_feats(self, img_feats, pts, img_metas):
    method sample_single (line 272) | def sample_single(self, img_feats, pts, img_meta):

FILE: mmdet3d/models/fusion_layers/vote_fusion.py
  class VoteFusion (line 12) | class VoteFusion(nn.Module):
    method __init__ (line 20) | def __init__(self, num_classes=10, max_imvote_per_pixel=3):
    method forward (line 25) | def forward(self, imgs, bboxes_2d_rescaled, seeds_3d_depth, img_metas,

FILE: mmdet3d/models/losses/axis_aligned_iou_loss.py
  function axis_aligned_iou_loss (line 10) | def axis_aligned_iou_loss(pred, target):
  class AxisAlignedIoULoss (line 29) | class AxisAlignedIoULoss(nn.Module):
    method __init__ (line 38) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 44) | def forward(self,

FILE: mmdet3d/models/losses/chamfer_distance.py
  function chamfer_distance (line 8) | def chamfer_distance(src,
  class ChamferDistance (line 75) | class ChamferDistance(nn.Module):
    method __init__ (line 87) | def __init__(self,
    method forward (line 101) | def forward(self,

FILE: mmdet3d/models/losses/uncertainty_loss.py
  function laplacian_aleatoric_uncertainty_loss (line 8) | def laplacian_aleatoric_uncertainty_loss(pred, target):
  class LaplaceL1Loss (line 27) | class LaplaceL1Loss(nn.Module):
    method __init__ (line 35) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 40) | def forward(self,

FILE: mmdet3d/models/middle_encoders/pillar_scatter.py
  class PointPillarsScatter (line 9) | class PointPillarsScatter(nn.Module):
    method __init__ (line 19) | def __init__(self, in_channels, output_shape):
    method forward (line 28) | def forward(self, voxel_features, coors, batch_size=None):
    method forward_single (line 37) | def forward_single(self, voxel_features, coors):
    method forward_batch (line 61) | def forward_batch(self, voxel_features, coors, batch_size):

FILE: mmdet3d/models/middle_encoders/sparse_encoder.py
  class SparseEncoder (line 10) | class SparseEncoder(nn.Module):
    method __init__ (line 31) | def __init__(self,
    method forward (line 96) | def forward(self, voxel_features, coors, batch_size):
    method make_encoder_layers (line 129) | def make_encoder_layers(self,

FILE: mmdet3d/models/middle_encoders/sparse_unet.py
  class SparseUNet (line 11) | class SparseUNet(nn.Module):
    method __init__ (line 30) | def __init__(self,
    method forward (line 97) | def forward(self, voxel_features, coors, batch_size):
    method decoder_layer_forward (line 149) | def decoder_layer_forward(self, x_lateral, x_bottom, lateral_layer,
    method reduce_channel (line 172) | def reduce_channel(x, out_channels):
    method make_encoder_layers (line 191) | def make_encoder_layers(self, make_block, norm_cfg, in_channels):
    method make_decoder_layers (line 237) | def make_decoder_layers(self, make_block, norm_cfg, in_channels):

FILE: mmdet3d/models/model_utils/vote_module.py
  class VoteModule (line 9) | class VoteModule(nn.Module):
    method __init__ (line 34) | def __init__(self,
    method forward (line 85) | def forward(self, seed_points, seed_feats):
    method get_loss (line 149) | def get_loss(self, seed_points, vote_points, seed_indices,

FILE: mmdet3d/models/necks/second_fpn.py
  class SECONDFPN (line 12) | class SECONDFPN(nn.Module):
    method __init__ (line 26) | def __init__(self,
    method init_weights (line 67) | def init_weights(self):
    method forward (line 76) | def forward(self, x):

FILE: mmdet3d/models/roi_heads/base_3droi_head.py
  class Base3DRoIHead (line 5) | class Base3DRoIHead(nn.Module, metaclass=ABCMeta):
    method __init__ (line 8) | def __init__(self,
    method with_bbox (line 27) | def with_bbox(self):
    method with_mask (line 32) | def with_mask(self):
    method init_weights (line 37) | def init_weights(self, pretrained):
    method init_bbox_head (line 42) | def init_bbox_head(self):
    method init_mask_head (line 47) | def init_mask_head(self):
    method init_assigner_sampler (line 52) | def init_assigner_sampler(self):
    method forward_train (line 57) | def forward_train(self,
    method simple_test (line 83) | def simple_test(self,
    method aug_test (line 93) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):

FILE: mmdet3d/models/roi_heads/bbox_heads/h3d_bbox_head.py
  class H3DBboxHead (line 16) | class H3DBboxHead(nn.Module):
    method __init__ (line 56) | def __init__(self,
    method init_weights (line 201) | def init_weights(self, pretrained=None):
    method forward (line 210) | def forward(self, feats_dict, sample_mod):
    method loss (line 318) | def loss(self,
    method get_bboxes (line 446) | def get_bboxes(self,
    method multiclass_nms_single (line 492) | def multiclass_nms_single(self, obj_scores, sem_scores, bbox, points,
    method get_proposal_stage_loss (line 552) | def get_proposal_stage_loss(self,
    method get_targets (line 661) | def get_targets(self,
    method get_targets_single (line 761) | def get_targets_single(self,

FILE: mmdet3d/models/roi_heads/bbox_heads/parta2_bbox_head.py
  class PartA2BboxHead (line 17) | class PartA2BboxHead(nn.Module):
    method __init__ (line 47) | def __init__(self,
    method init_weights (line 225) | def init_weights(self):
    method forward (line 233) | def forward(self, seg_feats, part_feats):
    method loss (line 283) | def loss(self, cls_score, bbox_pred, rois, labels, bbox_targets,
    method get_targets (line 356) | def get_targets(self, sampling_results, rcnn_train_cfg, concat=True):
    method _get_target_single (line 396) | def _get_target_single(self, pos_bboxes, pos_gt_bboxes, ious, cfg):
    method get_corner_loss_lidar (line 462) | def get_corner_loss_lidar(self, pred_bbox3d, gt_bbox3d, delta=1):
    method get_bboxes (line 497) | def get_bboxes(self,
    method multi_class_nms (line 556) | def multi_class_nms(self,

FILE: mmdet3d/models/roi_heads/h3d_roi_head.py
  class H3DRoIHead (line 8) | class H3DRoIHead(Base3DRoIHead):
    method __init__ (line 18) | def __init__(self,
    method init_weights (line 31) | def init_weights(self, pretrained):
    method init_mask_head (line 36) | def init_mask_head(self):
    method init_bbox_head (line 41) | def init_bbox_head(self, bbox_head):
    method init_assigner_sampler (line 47) | def init_assigner_sampler(self):
    method forward_train (line 51) | def forward_train(self,
    method simple_test (line 119) | def simple_test(self, feats_dict, img_metas, points, rescale=False):

FILE: mmdet3d/models/roi_heads/mask_heads/pointwise_semantic_head.py
  class PointwiseSemanticHead (line 12) | class PointwiseSemanticHead(nn.Module):
    method __init__ (line 26) | def __init__(self,
    method forward (line 52) | def forward(self, x):
    method get_targets_single (line 78) | def get_targets_single(self, voxel_centers, gt_bboxes_3d, gt_labels_3d):
    method get_targets (line 127) | def get_targets(self, voxels_dict, gt_bboxes_3d, gt_labels_3d):
    method loss (line 159) | def loss(self, semantic_results, semantic_targets):

FILE: mmdet3d/models/roi_heads/mask_heads/primitive_head.py
  class PrimitiveHead (line 14) | class PrimitiveHead(nn.Module):
    method __init__ (line 39) | def __init__(self,
    method init_weights (line 113) | def init_weights(self):
    method forward (line 117) | def forward(self, feats_dict, sample_mod):
    method loss (line 188) | def loss(self,
    method get_targets (line 259) | def get_targets(self,
    method get_targets_single (line 327) | def get_targets_single(self,
    method primitive_decode_scores (line 603) | def primitive_decode_scores(self, predictions, aggregated_points):
    method check_horizon (line 631) | def check_horizon(self, points):
    method check_dist (line 644) | def check_dist(self, plane_equ, points):
    method point2line_dist (line 657) | def point2line_dist(self, points, pts_a, pts_b):
    method match_point2line (line 676) | def match_point2line(self, points, corners, with_yaw, mode='bottom'):
    method match_point2plane (line 717) | def match_point2plane(self, plane, points):
    method compute_primitive_loss (line 735) | def compute_primitive_loss(self, primitive_center, primitive_semantic,
    method get_primitive_center (line 784) | def get_primitive_center(self, pred_flag, center):
    method _assign_primitive_line_targets (line 803) | def _assign_primitive_line_targets(self,
    method _assign_primitive_surface_targets (line 868) | def _assign_primitive_surface_targets(self,
    method _get_plane_fomulation (line 952) | def _get_plane_fomulation(self, vector1, vector2, point):

FILE: mmdet3d/models/roi_heads/part_aggregation_roi_head.py
  class PartAggregationROIHead (line 12) | class PartAggregationROIHead(Base3DRoIHead):
    method __init__ (line 25) | def __init__(self,
    method init_weights (line 46) | def init_weights(self, pretrained):
    method init_mask_head (line 51) | def init_mask_head(self):
    method init_bbox_head (line 56) | def init_bbox_head(self, bbox_head):
    method init_assigner_sampler (line 60) | def init_assigner_sampler(self):
    method with_semantic (line 74) | def with_semantic(self):
    method forward_train (line 79) | def forward_train(self, feats_dict, voxels_dict, img_metas, proposal_l...
    method simple_test (line 121) | def simple_test(self, feats_dict, voxels_dict, img_metas, proposal_list,
    method _bbox_forward_train (line 164) | def _bbox_forward_train(self, seg_feats, part_feats, voxels_dict,
    method _bbox_forward (line 191) | def _bbox_forward(self, seg_feats, part_feats, voxels_dict, rois):
    method _assign_and_sample (line 222) | def _assign_and_sample(self, proposal_list, gt_bboxes_3d, gt_labels_3d):
    method _semantic_forward_train (line 296) | def _semantic_forward_train(self, x, voxels_dict, gt_bboxes_3d,

FILE: mmdet3d/models/roi_heads/roi_extractors/single_roiaware_extractor.py
  class Single3DRoIAwareExtractor (line 9) | class Single3DRoIAwareExtractor(nn.Module):
    method __init__ (line 18) | def __init__(self, roi_layer=None):
    method build_roi_layers (line 22) | def build_roi_layers(self, layer_cfg):
    method forward (line 31) | def forward(self, feats, coordinate, batch_inds, rois):

FILE: mmdet3d/models/utils/clip_sigmoid.py
  function clip_sigmoid (line 4) | def clip_sigmoid(x, eps=1e-4):

FILE: mmdet3d/models/utils/deformable_decoder.py
  class DeformableTransformerDecoderLayer (line 20) | class DeformableTransformerDecoderLayer(nn.Module):
    method __init__ (line 21) | def __init__(self, d_model, nhead, level_num=4, dim_feedforward=2048, ...
    method with_pos_embed (line 56) | def with_pos_embed(self, tensor, pos_embed):
    method forward (line 59) | def forward(self, query, key, query_pos, key_pos, reference_points, le...

FILE: mmdet3d/models/utils/depth_encoder.py
  class DepthEncoderResNet (line 9) | class DepthEncoderResNet(nn.Module):
    method __init__ (line 10) | def __init__(self, input_channel, input_channel_img, hidden_channel, d...
    method _make_layer (line 37) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 54) | def forward(self, sparse_depth, img_inputs):

FILE: mmdet3d/models/utils/drop.py
  function drop_path (line 11) | def drop_path(x: torch.Tensor,
  class DropPath (line 32) | class DropPath(nn.Module):
    method __init__ (line 43) | def __init__(self, drop_prob: float = 0.1):
    method forward (line 47) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Dropout (line 52) | class Dropout(nn.Dropout):
    method __init__ (line 63) | def __init__(self, drop_prob: float = 0.5, inplace: bool = False):
  function build_dropout (line 67) | def build_dropout(cfg: Dict, default_args: Optional[Dict] = None) -> Any:

FILE: mmdet3d/models/utils/ffn.py
  class FFN (line 13) | class FFN(nn.Module):
    method __init__ (line 14) | def __init__(self,
    method init_weights (line 75) | def init_weights(self):
    method forward (line 85) | def forward(self, x):
  class FFNLN (line 115) | class FFNLN(nn.Module):
    method __init__ (line 116) | def __init__(self,
    method init_weights (line 167) | def init_weights(self):
    method forward (line 177) | def forward(self, x):
  class FFNReg (line 208) | class FFNReg(nn.Module):
    method __init__ (line 209) | def __init__(self,
    method init_weights (line 248) | def init_weights(self):
    method forward (line 258) | def forward(self, x):

FILE: mmdet3d/models/utils/inverse_sigmoid.py
  function inverse_sigmoid (line 3) | def inverse_sigmoid(x, eps=1e-5):

FILE: mmdet3d/models/utils/mlp.py
  class MLP (line 5) | class MLP(nn.Module):
    method __init__ (line 23) | def __init__(self,
    method forward (line 47) | def forward(self, img_features):

FILE: mmdet3d/models/utils/network_modules.py
  function denormalize_pos (line 7) | def denormalize_pos(normal_pos, x_max, y_max, sigmoid=True):
  function normalize_pos (line 16) | def normalize_pos(pos, x_max, y_max):
  class LayerNorm (line 22) | class LayerNorm(nn.Module):
    method __init__ (line 29) | def __init__(self, normalized_shape, eps=1e-6, data_format="channels_l...
    method forward (line 39) | def forward(self, x):
  class ConvLN (line 49) | class ConvLN(nn.Module):
    method __init__ (line 50) | def __init__(self, input_channel, hidden_channel, kernel_size=3,  stri...
    method forward (line 64) | def forward(self, x):
  class SE_Block (line 69) | class SE_Block(nn.Module):
    method __init__ (line 70) | def __init__(self, c):
    method forward (line 77) | def forward(self, x):

FILE: mmdet3d/models/utils/ops/functions/ms_deform_attn_func.py
  class MSDeformAttnFunction (line 21) | class MSDeformAttnFunction(Function):
    method forward (line 23) | def forward(ctx, value, value_spatial_shapes, value_level_start_index,...
    method backward (line 32) | def backward(ctx, grad_output):
  function ms_deform_attn_core_pytorch (line 41) | def ms_deform_attn_core_pytorch(value, value_spatial_shapes, sampling_lo...

FILE: mmdet3d/models/utils/ops/modules/ms_deform_attn.py
  function _is_power_of_2 (line 24) | def _is_power_of_2(n):
  class MSDeformAttn (line 30) | class MSDeformAttn(nn.Module):
    method __init__ (line 31) | def __init__(self, d_model=256, n_levels=4, n_heads=8, n_points=4):
    method _reset_parameters (line 62) | def _reset_parameters(self):
    method forward (line 78) | def forward(self, query, reference_points, input_flatten, input_spatia...

FILE: mmdet3d/models/utils/ops/setup.py
  function get_extensions (line 23) | def get_extensions():

FILE: mmdet3d/models/utils/ops/src/cpu/ms_deform_attn_cpu.cpp
  function ms_deform_attn_cpu_forward (line 17) | at::Tensor
  function ms_deform_attn_cpu_backward (line 29) | std::vector<at::Tensor>

FILE: mmdet3d/models/utils/ops/src/ms_deform_attn.h
  function im2col_step (line 27) | int im2col_step)

FILE: mmdet3d/models/utils/ops/src/vision.cpp
  function PYBIND11_MODULE (line 13) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/models/utils/ops/test.py
  function check_forward_equal_with_pytorch_double (line 32) | def check_forward_equal_with_pytorch_double():
  function check_forward_equal_with_pytorch_float (line 48) | def check_forward_equal_with_pytorch_float():
  function check_gradient_numerical (line 63) | def check_gradient_numerical(channels=4, grad_value=True, grad_sampling_...

FILE: mmdet3d/models/utils/projection.py
  class PointProjection (line 5) | class PointProjection(nn.Module):
    method __init__ (line 6) | def __init__(self, pos_channel, hidden_channel):
    method forward (line 20) | def forward(self, query_feat, query_pos):
  class ImageProjection (line 26) | class ImageProjection(nn.Module):
    method __init__ (line 27) | def __init__(self, pos_channel, hidden_channel):
    method forward (line 41) | def forward(self, query_feat, query_pos):
  class ProjectionL2Norm (line 48) | class ProjectionL2Norm(nn.Module):
    method __init__ (line 49) | def __init__(self, hidden_channel):
    method forward (line 54) | def forward(self, query_feat):
  class ProjectionLayerNorm (line 60) | class ProjectionLayerNorm(nn.Module):
    method __init__ (line 61) | def __init__(self, hidden_channel, norm=True, input_channel=None):
    method forward (line 71) | def forward(self, query_feat):
  class Projection_wPos (line 79) | class Projection_wPos(nn.Module):
    method __init__ (line 80) | def __init__(self, hidden_channel, pos_embed):
    method forward (line 86) | def forward(self, query_feat, query_pos):

FILE: mmdet3d/models/utils/sparsefusion_models.py
  class PointTransformer2D_3D (line 14) | class PointTransformer2D_3D(nn.Module):
    method __init__ (line 15) | def __init__(self, hidden_channel, num_heads, num_decoder_layers, pred...
    method forward (line 33) | def forward(self, pts_query_feat, pts_query_pos, lidar_feat_flatten, b...
  class CameraSE (line 54) | class CameraSE(nn.Module):
    method __init__ (line 55) | def __init__(self, cam_dim, hidden_channel):
    method forward (line 68) | def forward(self, feat, cam_info):
  class ImageTransformer_Cam_3D_MS (line 74) | class ImageTransformer_Cam_3D_MS(nn.Module):
    method __init__ (line 75) | def __init__(self, num_views, hidden_channel, num_heads, num_decoder_l...
    method forward (line 101) | def forward(self, img_query_feat, normal_img_query_pos, img_query_view...
    method transform_bbox (line 227) | def transform_bbox(self, ret_dict, camera_info, width, img_metas):
  class ViewTransformer (line 260) | class ViewTransformer(nn.Module):
    method __init__ (line 261) | def __init__(self, hidden_channel, num_heads, prediction_heads, ffn_ch...
    method forward (line 284) | def forward(self, img_query_feat, img_query_pos_bev, normal_img_query_...
  class FusionTransformer2D_3D_Self (line 335) | class FusionTransformer2D_3D_Self(nn.Module):
    method __init__ (line 336) | def __init__(self, hidden_channel, num_heads, num_decoder_layers, pred...
    method forward (line 359) | def forward(self, pts_query_feat, pts_query_pos, img_query_feat, img_q...
  class ImageTransformer2D_3D_MS (line 394) | class ImageTransformer2D_3D_MS(nn.Module):
    method __init__ (line 395) | def __init__(self, num_views, hidden_channel, num_heads, num_decoder_l...
    method forward (line 416) | def forward(self, img_query_feat, normal_img_query_pos, img_query_view...
    method camera2lidar (line 482) | def camera2lidar(self, camera_coords, lidar2img, img_meta, batch_size):

FILE: mmdet3d/models/utils/transformer.py
  function _ntuple (line 23) | def _ntuple(n):
  class GELU (line 33) | class GELU(nn.Module):
    method forward (line 50) | def forward(self, input: torch.Tensor) -> torch.Tensor:
  class ModuleList (line 59) | class ModuleList(BaseModule, nn.ModuleList):
    method __init__ (line 66) | def __init__(self,
  class Sequential (line 72) | class Sequential(BaseModule, nn.Sequential):
    method __init__ (line 78) | def __init__(self, *args, init_cfg: Optional[dict] = None):
  function build_positional_encoding (line 82) | def build_positional_encoding(cfg, default_args=None):
  function build_attention (line 87) | def build_attention(cfg, default_args=None):
  function build_feedforward_network (line 92) | def build_feedforward_network(cfg, default_args=None):
  function build_transformer_layer (line 97) | def build_transformer_layer(cfg, default_args=None):
  function build_transformer_layer_sequence (line 102) | def build_transformer_layer_sequence(cfg, default_args=None):
  class AdaptivePadding (line 107) | class AdaptivePadding(nn.Module):
    method __init__ (line 142) | def __init__(self, kernel_size=1, stride=1, dilation=1, padding='corne...
    method get_pad_shape (line 155) | def get_pad_shape(self, input_shape):
    method forward (line 176) | def forward(self, x):
  class PatchEmbed (line 197) | class PatchEmbed(BaseModule):
    method __init__ (line 225) | def __init__(self,
    method forward (line 297) | def forward(self, x):
  class PatchMerging (line 321) | class PatchMerging(BaseModule):
    method __init__ (line 353) | def __init__(self,
    method forward (line 402) | def forward(self, x, input_size):
  class MultiheadAttention (line 451) | class MultiheadAttention(BaseModule):
    method __init__ (line 473) | def __init__(self,
    method forward (line 505) | def forward(self,
  class FFN (line 599) | class FFN(BaseModule):
    method __init__ (line 627) | def __init__(self,
    method forward (line 662) | def forward(self, x, identity=None):
  class BaseTransformerLayer (line 676) | class BaseTransformerLayer(BaseModule):
    method __init__ (line 712) | def __init__(self,
    method forward (line 805) | def forward(self,
  class TransformerLayerSequence (line 907) | class TransformerLayerSequence(BaseModule):
    method __init__ (line 926) | def __init__(self, transformerlayers=None, num_layers=None, init_cfg=N...
    method forward (line 942) | def forward(self,

FILE: mmdet3d/models/utils/transformerdecoder.py
  class PositionEmbeddingLearnedLN (line 25) | class PositionEmbeddingLearnedLN(nn.Module):
    method __init__ (line 30) | def __init__(self, input_channel, num_pos_feats=288):
    method forward (line 39) | def forward(self, xyz):
  class PositionEmbeddingLearned (line 44) | class PositionEmbeddingLearned(nn.Module):
    method __init__ (line 49) | def __init__(self, input_channel, num_pos_feats=288):
    method forward (line 57) | def forward(self, xyz):
  class PositionEmbeddingLearnedwoNorm (line 62) | class PositionEmbeddingLearnedwoNorm(nn.Module):
    method __init__ (line 67) | def __init__(self, input_channel, num_pos_feats=288):
    method forward (line 75) | def forward(self, xyz):
  class PositionEmbeddingLearnedMulti (line 80) | class PositionEmbeddingLearnedMulti(nn.Module):
    method __init__ (line 85) | def __init__(self, input_channel, num_pos_feats=288, pos_num=2):
    method forward (line 97) | def forward(self, xyzs):
  class PositionEmbeddingLearnedMultiInput (line 110) | class PositionEmbeddingLearnedMultiInput(nn.Module):
    method __init__ (line 111) | def __init__(self, input_channels, num_pos_feats=288):
    method forward (line 119) | def forward(self, xyzs):
  class TransformerDecoderLayer (line 130) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 131) | def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, ...
    method with_pos_embed (line 166) | def with_pos_embed(self, tensor, pos_embed):
    method forward (line 169) | def forward(self, query, key, query_pos, key_pos, attn_mask=None, need...
  class MultiheadAttention (line 215) | class MultiheadAttention(nn.Module):
    method __init__ (line 239) | def __init__(self, embed_dim, num_heads, dropout=0., bias=True, add_bi...
    method _reset_parameters (line 275) | def _reset_parameters(self):
    method forward (line 291) | def forward(self, query, key, value, key_padding_mask=None, need_weigh...
  function multi_head_attention_forward (line 345) | def multi_head_attention_forward(query,  # type: Tensor

FILE: mmdet3d/models/voxel_encoders/pillar_encoder.py
  class PillarFeatureNet (line 12) | class PillarFeatureNet(nn.Module):
    method __init__ (line 39) | def __init__(self,
    method forward (line 91) | def forward(self, features, num_points, coors):
  class DynamicPillarFeatureNet (line 154) | class DynamicPillarFeatureNet(PillarFeatureNet):
    method __init__ (line 181) | def __init__(self,
    method map_voxel_center_to_point (line 223) | def map_voxel_center_to_point(self, pts_coors, voxel_mean, voxel_coors):
    method forward (line 263) | def forward(self, features, coors):

FILE: mmdet3d/models/voxel_encoders/utils.py
  function get_paddings_indicator (line 8) | def get_paddings_indicator(actual_num, max_num, axis=0):
  class VFELayer (line 31) | class VFELayer(nn.Module):
    method __init__ (line 48) | def __init__(self,
    method forward (line 64) | def forward(self, inputs):
  class PFNLayer (line 106) | class PFNLayer(nn.Module):
    method __init__ (line 122) | def __init__(self,
    method forward (line 144) | def forward(self, inputs, num_voxels=None, aligned_distance=None):

FILE: mmdet3d/models/voxel_encoders/voxel_encoder.py
  class HardSimpleVFE (line 13) | class HardSimpleVFE(nn.Module):
    method __init__ (line 22) | def __init__(self, num_features=4):
    method forward (line 28) | def forward(self, features, num_points, coors):
  class DynamicSimpleVFE (line 48) | class DynamicSimpleVFE(nn.Module):
    method __init__ (line 59) | def __init__(self,
    method forward (line 68) | def forward(self, features, coors):
  class DynamicVFE (line 87) | class DynamicVFE(nn.Module):
    method __init__ (line 116) | def __init__(self,
    method map_voxel_center_to_point (line 176) | def map_voxel_center_to_point(self, pts_coors, voxel_mean, voxel_coors):
    method forward (line 219) | def forward(self,
  class HardVFE (line 287) | class HardVFE(nn.Module):
    method __init__ (line 315) | def __init__(self,
    method forward (line 384) | def forward(self,
    method fusion_with_mask (line 452) | def fusion_with_mask(self, features, mask, voxel_feats, coors, img_feats,

FILE: mmdet3d/ops/ball_query/ball_query.py
  class BallQuery (line 7) | class BallQuery(Function):
    method forward (line 14) | def forward(ctx, min_radius: float, max_radius: float, sample_num: int,
    method backward (line 43) | def backward(ctx, a=None):

FILE: mmdet3d/ops/ball_query/src/ball_query.cpp
  function ball_query_wrapper (line 30) | int ball_query_wrapper(int b, int n, int m, float min_radius, float max_...
  function PYBIND11_MODULE (line 45) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/furthest_point_sample/furthest_point_sample.py
  class FurthestPointSampling (line 7) | class FurthestPointSampling(Function):
    method forward (line 15) | def forward(ctx, points_xyz: torch.Tensor,
    method backward (line 38) | def backward(xyz, a=None):
  class FurthestPointSamplingWithDist (line 42) | class FurthestPointSamplingWithDist(Function):
    method forward (line 50) | def forward(ctx, points_dist: torch.Tensor,
    method backward (line 73) | def backward(xyz, a=None):

FILE: mmdet3d/ops/furthest_point_sample/points_sampler.py
  function get_sampler_type (line 11) | def get_sampler_type(sampler_type):
  class Points_Sampler (line 34) | class Points_Sampler(nn.Module):
    method __init__ (line 48) | def __init__(self,
    method forward (line 66) | def forward(self, points_xyz, features):
  class DFPS_Sampler (line 102) | class DFPS_Sampler(nn.Module):
    method __init__ (line 108) | def __init__(self):
    method forward (line 111) | def forward(self, points, features, npoint):
  class FFPS_Sampler (line 117) | class FFPS_Sampler(nn.Module):
    method __init__ (line 123) | def __init__(self):
    method forward (line 126) | def forward(self, points, features, npoint):
  class FS_Sampler (line 135) | class FS_Sampler(nn.Module):
    method __init__ (line 141) | def __init__(self):
    method forward (line 144) | def forward(self, points, features, npoint):

FILE: mmdet3d/ops/furthest_point_sample/src/furthest_point_sample.cpp
  function furthest_point_sampling_wrapper (line 32) | int furthest_point_sampling_wrapper(int b, int n, int m,
  function furthest_point_sampling_with_dist_wrapper (line 45) | int furthest_point_sampling_with_dist_wrapper(int b, int n, int m,
  function PYBIND11_MODULE (line 59) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/furthest_point_sample/utils.py
  function calc_square_dist (line 4) | def calc_square_dist(point_feat_a, point_feat_b, norm=True):

FILE: mmdet3d/ops/gather_points/gather_points.py
  class GatherPoints (line 7) | class GatherPoints(Function):
    method forward (line 14) | def forward(ctx, features: torch.Tensor,
    method backward (line 40) | def backward(ctx, grad_out):

FILE: mmdet3d/ops/gather_points/src/gather_points.cpp
  function gather_points_wrapper (line 28) | int gather_points_wrapper(int b, int c, int n, int npoints,
  function gather_points_grad_wrapper (line 40) | int gather_points_grad_wrapper(int b, int c, int n, int npoints,
  function PYBIND11_MODULE (line 54) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/group_points/group_points.py
  class QueryAndGroup (line 10) | class QueryAndGroup(nn.Module):
    method __init__ (line 32) | def __init__(self,
    method forward (line 53) | def forward(self, points_xyz, center_xyz, features=None):
  class GroupAll (line 112) | class GroupAll(nn.Module):
    method __init__ (line 121) | def __init__(self, use_xyz: bool = True):
    method forward (line 125) | def forward(self,
  class GroupingOperation (line 153) | class GroupingOperation(Function):
    method forward (line 160) | def forward(ctx, features: torch.Tensor,
    method backward (line 186) | def backward(ctx,

FILE: mmdet3d/ops/group_points/src/group_points.cpp
  function group_points_grad_wrapper (line 31) | int group_points_grad_wrapper(int b, int c, int n, int npoints, int nsam...
  function group_points_wrapper (line 45) | int group_points_wrapper(int b, int c, int n, int npoints, int nsample,
  function PYBIND11_MODULE (line 59) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/interpolate/src/interpolate.cpp
  function three_nn_wrapper (line 46) | void three_nn_wrapper(int b, int n, int m, at::Tensor unknown_tensor,
  function three_interpolate_wrapper (line 58) | void three_interpolate_wrapper(int b, int c, int m, int n,
  function three_interpolate_grad_wrapper (line 72) | void three_interpolate_grad_wrapper(int b, int c, int n, int m,
  function PYBIND11_MODULE (line 87) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/interpolate/three_interpolate.py
  class ThreeInterpolate (line 8) | class ThreeInterpolate(Function):
    method forward (line 11) | def forward(ctx, features: torch.Tensor, indices: torch.Tensor,
    method backward (line 39) | def backward(

FILE: mmdet3d/ops/interpolate/three_nn.py
  class ThreeNN (line 8) | class ThreeNN(Function):
    method forward (line 11) | def forward(ctx, target: torch.Tensor,
    method backward (line 41) | def backward(ctx, a=None, b=None):

FILE: mmdet3d/ops/iou3d/iou3d_utils.py
  function boxes_iou_bev (line 6) | def boxes_iou_bev(boxes_a, boxes_b):
  function nms_gpu (line 25) | def nms_gpu(boxes, scores, thresh, pre_maxsize=None, post_max_size=None):
  function nms_normal_gpu (line 53) | def nms_normal_gpu(boxes, scores, thresh):

FILE: mmdet3d/ops/iou3d/src/iou3d.cpp
  function gpuAssert (line 29) | inline void gpuAssert(cudaError_t code, const char *file, int line,
  function boxes_overlap_bev_gpu (line 50) | int boxes_overlap_bev_gpu(at::Tensor boxes_a, at::Tensor boxes_b,
  function boxes_iou_bev_gpu (line 73) | int boxes_iou_bev_gpu(at::Tensor boxes_a, at::Tensor boxes_b,
  function nms_gpu (line 95) | int nms_gpu(at::Tensor boxes, at::Tensor keep,
  function nms_normal_gpu (line 149) | int nms_normal_gpu(at::Tensor boxes, at::Tensor keep,
  function PYBIND11_MODULE (line 203) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/knn/knn.py
  class KNN (line 7) | class KNN(Function):
    method forward (line 14) | def forward(ctx,
    method backward (line 65) | def backward(ctx, a=None):

FILE: mmdet3d/ops/knn/src/knn.cpp
  function knn_wrapper (line 26) | void knn_wrapper(
  function PYBIND11_MODULE (line 60) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/norm.py
  class AllReduce (line 9) | class AllReduce(Function):
    method forward (line 12) | def forward(ctx, input):
    method backward (line 22) | def backward(ctx, grad_output):
  class NaiveSyncBatchNorm1d (line 28) | class NaiveSyncBatchNorm1d(nn.BatchNorm1d):
    method __init__ (line 46) | def __init__(self, *args, **kwargs):
    method forward (line 54) | def forward(self, input):
  class NaiveSyncBatchNorm2d (line 82) | class NaiveSyncBatchNorm2d(nn.BatchNorm2d):
    method __init__ (line 100) | def __init__(self, *args, **kwargs):
    method forward (line 108) | def forward(self, input):

FILE: mmdet3d/ops/pointnet_modules/builder.py
  function build_sa_module (line 4) | def build_sa_module(cfg, *args, **kwargs):

FILE: mmdet3d/ops/pointnet_modules/point_fp_module.py
  class PointFPModule (line 10) | class PointFPModule(nn.Module):
    method __init__ (line 21) | def __init__(self,
    method forward (line 39) | def forward(self, target: torch.Tensor, source: torch.Tensor,

FILE: mmdet3d/ops/pointnet_modules/point_sa_module.py
  class PointSAModuleMSG (line 12) | class PointSAModuleMSG(nn.Module):
    method __init__ (line 44) | def __init__(self,
    method forward (line 121) | def forward(
  class PointSAModule (line 183) | class PointSAModule(PointSAModuleMSG):
    method __init__ (line 209) | def __init__(self,

FILE: mmdet3d/ops/roiaware_pool3d/points_in_boxes.py
  function points_in_boxes_gpu (line 6) | def points_in_boxes_gpu(points, boxes):
  function points_in_boxes_cpu (line 53) | def points_in_boxes_cpu(points, boxes):
  function points_in_boxes_batch (line 85) | def points_in_boxes_batch(points, boxes):

FILE: mmdet3d/ops/roiaware_pool3d/roiaware_pool3d.py
  class RoIAwarePool3d (line 9) | class RoIAwarePool3d(nn.Module):
    method __init__ (line 11) | def __init__(self, out_size, max_pts_per_voxel=128, mode='max'):
    method forward (line 26) | def forward(self, rois, pts, pts_feature):
  class RoIAwarePool3dFunction (line 44) | class RoIAwarePool3dFunction(Function):
    method forward (line 47) | def forward(ctx, rois, pts, pts_feature, out_size, max_pts_per_voxel,
    method backward (line 91) | def backward(ctx, grad_out):

FILE: mmdet3d/ops/roiaware_pool3d/src/points_in_boxes_cpu.cpp
  function lidar_to_local_coords_cpu (line 16) | inline void lidar_to_local_coords_cpu(float shift_x, float shift_y, floa...
  function check_pt_in_box3d_cpu (line 25) | inline int check_pt_in_box3d_cpu(const float *pt, const float *box3d,
  function points_in_boxes_cpu (line 42) | int points_in_boxes_cpu(at::Tensor boxes_tensor, at::Tensor pts_tensor,

FILE: mmdet3d/ops/roiaware_pool3d/src/roiaware_pool3d.cpp
  function roiaware_pool3d_gpu (line 49) | int roiaware_pool3d_gpu(at::Tensor rois, at::Tensor pts, at::Tensor pts_...
  function roiaware_pool3d_gpu_backward (line 92) | int roiaware_pool3d_gpu_backward(at::Tensor pts_idx_of_voxels,
  function PYBIND11_MODULE (line 126) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/sparse_block.py
  function replace_feature (line 7) | def replace_feature(out, new_features):
  class SparseBottleneck (line 15) | class SparseBottleneck(Bottleneck, spconv.SparseModule):
    method __init__ (line 33) | def __init__(self,
    method forward (line 51) | def forward(self, x):
  class SparseBasicBlock (line 81) | class SparseBasicBlock(BasicBlock, spconv.SparseModule):
    method __init__ (line 99) | def __init__(self,
    method forward (line 116) | def forward(self, x):
  function make_sparse_convmodule (line 142) | def make_sparse_convmodule(in_channels,

FILE: mmdet3d/ops/spconv/conv.py
  function _calculate_fan_in_and_fan_out_hwio (line 27) | def _calculate_fan_in_and_fan_out_hwio(tensor):
  class SparseConvolution (line 48) | class SparseConvolution(SparseModule):
    method __init__ (line 50) | def __init__(self,
    method reset_parameters (line 106) | def reset_parameters(self):
    method forward (line 113) | def forward(self, input):
  class SparseConv2d (line 208) | class SparseConv2d(SparseConvolution):
    method __init__ (line 210) | def __init__(self,
  class SparseConv3d (line 234) | class SparseConv3d(SparseConvolution):
    method __init__ (line 236) | def __init__(self,
  class SparseConv4d (line 260) | class SparseConv4d(SparseConvolution):
    method __init__ (line 262) | def __init__(self,
  class SparseConvTranspose2d (line 286) | class SparseConvTranspose2d(SparseConvolution):
    method __init__ (line 288) | def __init__(self,
  class SparseConvTranspose3d (line 313) | class SparseConvTranspose3d(SparseConvolution):
    method __init__ (line 315) | def __init__(self,
  class SparseInverseConv2d (line 340) | class SparseInverseConv2d(SparseConvolution):
    method __init__ (line 342) | def __init__(self,
  class SparseInverseConv3d (line 359) | class SparseInverseConv3d(SparseConvolution):
    method __init__ (line 361) | def __init__(self,
  class SubMConv2d (line 378) | class SubMConv2d(SparseConvolution):
    method __init__ (line 380) | def __init__(self,
  class SubMConv3d (line 405) | class SubMConv3d(SparseConvolution):
    method __init__ (line 407) | def __init__(self,
  class SubMConv4d (line 432) | class SubMConv4d(SparseConvolution):
    method __init__ (line 434) | def __init__(self,

FILE: mmdet3d/ops/spconv/functional.py
  class SparseConvFunction (line 20) | class SparseConvFunction(Function):
    method forward (line 23) | def forward(ctx, features, filters, indice_pairs, indice_pair_num,
    method backward (line 30) | def backward(ctx, grad_output):
  class SparseInverseConvFunction (line 39) | class SparseInverseConvFunction(Function):
    method forward (line 42) | def forward(ctx, features, filters, indice_pairs, indice_pair_num,
    method backward (line 49) | def backward(ctx, grad_output):
  class SubMConvFunction (line 58) | class SubMConvFunction(Function):
    method forward (line 61) | def forward(ctx, features, filters, indice_pairs, indice_pair_num,
    method backward (line 68) | def backward(ctx, grad_output):
  class SparseMaxPoolFunction (line 77) | class SparseMaxPoolFunction(Function):
    method forward (line 80) | def forward(ctx, features, indice_pairs, indice_pair_num,
    method backward (line 88) | def backward(ctx, grad_output):

FILE: mmdet3d/ops/spconv/include/paramsgrid.h
  function namespace (line 20) | namespace detail {

FILE: mmdet3d/ops/spconv/include/prettyprint.h
  function namespace (line 25) | namespace pretty_print {
  type custom_delims_base (line 385) | struct custom_delims_base {
  type T (line 429) | typedef const T *const_iterator;
  type T (line 430) | typedef T value_type;
  type typename (line 447) | typedef typename T::const_local_iterator const_iterator;
  type typename (line 448) | typedef typename T::size_type size_type;
  function namespace (line 480) | namespace std {

FILE: mmdet3d/ops/spconv/include/spconv/fused_spconv_ops.h
  function namespace (line 25) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/geometry.h
  function namespace (line 23) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/indice.cu.h
  function namespace (line 21) | namespace spconv {
  function assignGridAndIndiceOutKernel (line 113) | void assignGridAndIndiceOutKernel(
  function prepareSubMGridKernel (line 148) | void prepareSubMGridKernel(
  function resetGridKernel (line 206) | void resetGridKernel(const Index *indicePairUnique,

FILE: mmdet3d/ops/spconv/include/spconv/indice.h
  function namespace (line 19) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/maxpool.h
  function namespace (line 19) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/mp_helper.h
  function namespace (line 6) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/point2voxel.h
  function namespace (line 28) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/pool_ops.h
  function namespace (line 24) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/reordering.cu.h
  function namespace (line 20) | namespace spconv {
  function gatherVecKernel (line 49) | void gatherVecKernel(T *buffer, const T *features,
  function scatterAddGenericKernel (line 100) | void scatterAddGenericKernel(T *outFeatures, const T *buffer,

FILE: mmdet3d/ops/spconv/include/spconv/reordering.h
  function namespace (line 19) | namespace spconv {

FILE: mmdet3d/ops/spconv/include/spconv/spconv_ops.h
  function indicePairUnique (line 70) | auto indicePairUnique = torch::full(

FILE: mmdet3d/ops/spconv/include/tensorview/helper_kernel.cu.h
  function namespace (line 3) | namespace tv {

FILE: mmdet3d/ops/spconv/include/tensorview/helper_launch.h
  function namespace (line 4) | namespace tv

FILE: mmdet3d/ops/spconv/include/tensorview/tensorview.h
  function namespace (line 28) | namespace tv {
  type GPU (line 104) | struct GPU {
  type CPU (line 109) | struct CPU {}
  type size_type (line 188) | typedef size_t size_type;
  function class (line 190) | class iterator {
  function rowArrayIdx (line 401) | unsigned rowArrayIdx(std::vector<int> &shape,
  function rowArrayIdx (line 417) | TV_HOST_DEVICE_INLINE unsigned rowArrayIdx(std::vector<int> &shape,
  function rowArrayIdx (line 429) | unsigned rowArrayIdx(const Shape &shape,
  function rowArrayIdx (line 442) | TV_HOST_DEVICE_INLINE unsigned rowArrayIdx(const Shape &shape,
  function rowArrayIdx (line 454) | unsigned rowArrayIdx(const Index *indexes,
  function Index (line 467) | Index rowArrayIdxInv(Index index, Index *output,
  function TV_HOST_DEVICE_INLINE (line 481) | TV_HOST_DEVICE_INLINE static unsigned run(const Shape &shape,
  type ArrayIndexRowMajor (line 489) | struct ArrayIndexRowMajor
  function TV_HOST_DEVICE_INLINE (line 490) | TV_HOST_DEVICE_INLINE static unsigned run(const Shape &shape,
  function namespace (line 496) | namespace detail {
  function TV_HOST_DEVICE_INLINE (line 527) | TV_HOST_DEVICE_INLINE TensorView() {}
  function explicit (line 528) | explicit TV_HOST_DEVICE_INLINE TensorView(T *ptr, Shape shape)
  function TV_HOST_DEVICE_INLINE (line 534) | TV_HOST_DEVICE_INLINE TensorView(T *ptr, Integers... shapes)
  function TV_HOST_DEVICE_INLINE (line 589) | TV_HOST_DEVICE_INLINE T &operator()() {
  function TV_HOST_DEVICE_INLINE (line 828) | TV_HOST_DEVICE_INLINE T &operator[](int idx) {
  function TV_HOST_DEVICE_INLINE (line 866) | TV_HOST_DEVICE_INLINE T *data() { return mPtr; }
  function TV_HOST_DEVICE_INLINE (line 867) | TV_HOST_DEVICE_INLINE const T *data() const { return mPtr; }
  function TV_HOST_DEVICE_INLINE (line 869) | TV_HOST_DEVICE_INLINE int dim(int idx) const { return mShape[idx]; }
  function Shape (line 873) | Shape shapes{int(newShapes)...};
  function Shape (line 885) | Shape shapes{int(newShapes)...};
  function Shape (line 916) | Shape new_shape{to_slice(slices)[0]...};
  function Slice (line 1053) | Slice to_slice(T1 s) const {
  function TV_HOST_DEVICE_INLINE (line 1057) | TV_HOST_DEVICE_INLINE Slice to_slice(Slice s) const { return Slice(s); }
  function namespace (line 1075) | namespace detail {
  function printTensorView (line 1105) | void printTensorView(const TensorView<T> tensor,
  function printTensorView (line 1152) | void printTensorView(const T *ptr, Shape shape) {
  function printTensorView (line 1158) | void printTensorView(const T *ptr, Shape shape,

FILE: mmdet3d/ops/spconv/include/torch_utils.h
  function namespace (line 21) | namespace tv {

FILE: mmdet3d/ops/spconv/modules.py
  function is_spconv_module (line 22) | def is_spconv_module(module):
  function is_sparse_conv (line 27) | def is_sparse_conv(module):
  function _mean_update (line 32) | def _mean_update(vals, m_vals, t):
  class SparseModule (line 46) | class SparseModule(nn.Module):
  class SparseSequential (line 52) | class SparseSequential(SparseModule):
    method __init__ (line 85) | def __init__(self, *args, **kwargs):
    method __getitem__ (line 101) | def __getitem__(self, idx):
    method __len__ (line 111) | def __len__(self):
    method sparity_dict (line 115) | def sparity_dict(self):
    method add (line 118) | def add(self, module, name=None):
    method forward (line 125) | def forward(self, input):
    method fused (line 139) | def fused(self):
  class ToDense (line 190) | class ToDense(SparseModule):
    method forward (line 193) | def forward(self, x: SparseConvTensor):
  class RemoveGrid (line 197) | class RemoveGrid(SparseModule):
    method forward (line 200) | def forward(self, x: SparseConvTensor):

FILE: mmdet3d/ops/spconv/ops.py
  function get_conv_output_size (line 20) | def get_conv_output_size(input_size, kernel_size, stride, padding, dilat...
  function get_deconv_output_size (line 33) | def get_deconv_output_size(input_size, kernel_size, stride, padding, dil...
  function get_indice_pairs (line 46) | def get_indice_pairs(indices,
  function indice_conv (line 108) | def indice_conv(features,
  function fused_indice_conv (line 129) | def fused_indice_conv(features, filters, bias, indice_pairs, indice_pair...
  function indice_conv_backward (line 142) | def indice_conv_backward(features,
  function indice_maxpool (line 161) | def indice_maxpool(features, indice_pairs, indice_pair_num, num_activate...
  function indice_maxpool_backward (line 174) | def indice_maxpool_backward(features, out_features, out_bp, indice_pairs,

FILE: mmdet3d/ops/spconv/overwrite_spconv/write_spconv2.py
  function register_spconv2 (line 8) | def register_spconv2():
  function _save_to_state_dict (line 42) | def _save_to_state_dict(self, destination, prefix, keep_vars):
  function _load_from_state_dict (line 61) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, strict,

FILE: mmdet3d/ops/spconv/pool.py
  class SparseMaxPool (line 21) | class SparseMaxPool(SparseModule):
    method __init__ (line 23) | def __init__(self,
    method forward (line 47) | def forward(self, input):
  class SparseMaxPool2d (line 74) | class SparseMaxPool2d(SparseMaxPool):
    method __init__ (line 76) | def __init__(self, kernel_size, stride=1, padding=0, dilation=1):
  class SparseMaxPool3d (line 81) | class SparseMaxPool3d(SparseMaxPool):
    method __init__ (line 83) | def __init__(self, kernel_size, stride=1, padding=0, dilation=1):

FILE: mmdet3d/ops/spconv/src/all.cc
  function PYBIND11_MODULE (line 21) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/spconv/src/indice.cc
  type spconv (line 20) | namespace spconv {
    type functor (line 22) | namespace functor {
      type CreateConvIndicePairFunctor<tv::CPU, Index, IndexGrid, NDim> (line 24) | struct CreateConvIndicePairFunctor<tv::CPU, Index, IndexGrid, NDim> {
        method Index (line 25) | Index operator()(const tv::CPU& d, tv::TensorView<const Index> ind...
      type CreateSubMIndicePairFunctor<tv::CPU, Index, IndexGrid, NDim> (line 49) | struct CreateSubMIndicePairFunctor<tv::CPU, Index, IndexGrid, NDim> {
        method Index (line 50) | Index operator()(const tv::CPU& d, tv::TensorView<const Index> ind...

FILE: mmdet3d/ops/spconv/src/maxpool.cc
  type spconv (line 18) | namespace spconv {
    type functor (line 20) | namespace functor {
      type SparseMaxPoolForwardFunctor<tv::CPU, T, Index> (line 22) | struct SparseMaxPoolForwardFunctor<tv::CPU, T, Index> {
      type SparseMaxPoolBackwardFunctor<tv::CPU, T, Index> (line 43) | struct SparseMaxPoolBackwardFunctor<tv::CPU, T, Index> {

FILE: mmdet3d/ops/spconv/src/reordering.cc
  type spconv (line 18) | namespace spconv {
    type functor (line 19) | namespace functor {
      type SparseGatherFunctor<tv::CPU, T, Index> (line 21) | struct SparseGatherFunctor<tv::CPU, T, Index> {
      type SparseScatterAddFunctor<tv::CPU, T, Index> (line 35) | struct SparseScatterAddFunctor<tv::CPU, T, Index> {

FILE: mmdet3d/ops/spconv/structure.py
  function scatter_nd (line 5) | def scatter_nd(indices, updates, shape):
  class SparseConvTensor (line 21) | class SparseConvTensor(object):
    method __init__ (line 23) | def __init__(self,
    method spatial_size (line 45) | def spatial_size(self):
    method find_indice_pair (line 48) | def find_indice_pair(self, key):
    method dense (line 55) | def dense(self, channels_first=True):
    method sparity (line 67) | def sparity(self):

FILE: mmdet3d/ops/spconv/test_utils.py
  class TestCase (line 18) | class TestCase(unittest.TestCase):
    method _GetNdArray (line 20) | def _GetNdArray(self, a):
    method assertAllEqual (line 25) | def assertAllEqual(self, a, b):
    method assertAllClose (line 56) | def assertAllClose(self, a, b, rtol=1e-6, atol=1e-6):
    method _assertArrayLikeAllClose (line 90) | def _assertArrayLikeAllClose(self, a, b, rtol=1e-6, atol=1e-6, msg=None):
  function params_grid (line 123) | def params_grid(*params):
  function generate_sparse_data (line 144) | def generate_sparse_data(shape,

FILE: mmdet3d/ops/voxel/scatter_points.py
  class _dynamic_scatter (line 9) | class _dynamic_scatter(Function):
    method forward (line 12) | def forward(ctx, feats, coors, reduce_type='max'):
    method backward (line 37) | def backward(ctx, grad_voxel_feats, grad_voxel_coors=None):
  class DynamicScatter (line 53) | class DynamicScatter(nn.Module):
    method __init__ (line 55) | def __init__(self, voxel_size, point_cloud_range, average_points: bool):
    method forward_single (line 74) | def forward_single(self, points, coors):
    method forward (line 78) | def forward(self, points, coors):
    method __repr__ (line 101) | def __repr__(self):

FILE: mmdet3d/ops/voxel/src/scatter_points_cpu.cpp
  function determin_max_points_kernel (line 8) | void determin_max_points_kernel(
  function scatter_point_to_voxel_kernel (line 39) | void scatter_point_to_voxel_kernel(
  type voxelization (line 61) | namespace voxelization {
    function dynamic_point_to_voxel_cpu (line 63) | std::vector<at::Tensor> dynamic_point_to_voxel_cpu(

FILE: mmdet3d/ops/voxel/src/voxelization.cpp
  type voxelization (line 4) | namespace voxelization {
    function PYBIND11_MODULE (line 6) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdet3d/ops/voxel/src/voxelization.h
  type reduce_t (line 4) | typedef enum { SUM = 0, MEAN = 1, MAX = 2 } reduce_t;
  function namespace (line 6) | namespace voxelization {
  function reduce_t (line 85) | inline reduce_t convert_reduce_type(const std::string &reduce_type) {
  function std (line 96) | inline std::vector<torch::Tensor> dynamic_point_to_voxel_forward(const t...
  function dynamic_point_to_voxel_backward (line 110) | inline void dynamic_point_to_voxel_backward(torch::Tensor &grad_feats,

FILE: mmdet3d/ops/voxel/src/voxelization_cpu.cpp
  function dynamic_voxelize_kernel (line 8) | void dynamic_voxelize_kernel(const torch::TensorAccessor<T, 2> points,
  function hard_voxelize_kernel (line 44) | void hard_voxelize_kernel(const torch::TensorAccessor<T, 2> points,
  type voxelization (line 103) | namespace voxelization {
    function hard_voxelize_cpu (line 105) | int hard_voxelize_cpu(const at::Tensor& points, at::Tensor& voxels,
    function dynamic_voxelize_cpu (line 144) | void dynamic_voxelize_cpu(const at::Tensor& points, at::Tensor& coors,

FILE: mmdet3d/ops/voxel/voxelize.py
  class _Voxelization (line 10) | class _Voxelization(Function):
    method forward (line 13) | def forward(ctx,
  class Voxelization (line 64) | class Voxelization(nn.Module):
    method __init__ (line 66) | def __init__(self,
    method forward (line 102) | def forward(self, input):
    method __repr__ (line 115) | def __repr__(self):

FILE: mmdet3d/utils/collect_env.py
  function collect_env (line 8) | def collect_env():

FILE: mmdet3d/version.py
  function parse_version_info (line 7) | def parse_version_info(version_str):

FILE: setup.py
  function readme (line 9) | def readme():
  function get_version (line 18) | def get_version():
  function make_cuda_ext (line 30) | def make_cuda_ext(name,
  function parse_requirements (line 62) | def parse_requirements(fname='requirements.txt', with_version=True):

FILE: tests/test_data/test_datasets/test_dataset_wrappers.py
  function test_getitem (line 7) | def test_getitem():

FILE: tests/test_data/test_datasets/test_kitti_dataset.py
  function _generate_kitti_dataset_config (line 11) | def _generate_kitti_dataset_config():
  function test_getitem (line 50) | def test_getitem():
  function test_evaluate (line 116) | def test_evaluate():
  function test_show (line 138) | def test_show():
  function test_format_results (line 169) | def test_format_results():
  function test_bbox2result_kitti (line 207) | def test_bbox2result_kitti():
  function test_bbox2result_kitti2d (line 252) | def test_bbox2result_kitti2d():

FILE: tests/test_data/test_datasets/test_lyft_dataset.py
  function test_getitem (line 8) | def test_getitem():
  function test_evaluate (line 109) | def test_evaluate():

FILE: tests/test_data/test_datasets/test_nuscene_dataset.py
  function test_getitem (line 6) | def test_getitem():

FILE: tests/test_data/test_datasets/test_scannet_dataset.py
  function test_getitem (line 8) | def test_getitem():
  function test_evaluate (line 115) | def test_evaluate():
  function test_show (line 168) | def test_show():

FILE: tests/test_data/test_datasets/test_semantickitti_dataset.py
  function test_getitem (line 6) | def test_getitem():

FILE: tests/test_data/test_datasets/test_sunrgbd_dataset.py
  function test_getitem (line 8) | def test_getitem():
  function test_evaluate (line 99) | def test_evaluate():
  function test_show (line 126) | def test_show():

FILE: tests/test_data/test_pipelines/test_augmentations/test_data_augment_utils.py
  function test_noise_per_object_v3_ (line 8) | def test_noise_per_object_v3_():
  function test_points_transform (line 30) | def test_points_transform():

FILE: tests/test_data/test_pipelines/test_augmentations/test_test_augment_utils.py
  function test_multi_scale_flip_aug_3D (line 8) | def test_multi_scale_flip_aug_3D():

FILE: tests/test_data/test_pipelines/test_augmentations/test_transforms_3d.py
  function test_remove_points_in_boxes (line 13) | def test_remove_points_in_boxes():
  function test_object_sample (line 41) | def test_object_sample():
  function test_object_noise (line 106) | def test_object_noise():
  function test_random_flip_3d (line 142) | def test_random_flip_3d():
  function test_background_points_filter (line 199) | def test_background_points_filter():
  function test_voxel_based_point_filter (line 242) | def test_voxel_based_point_filter():

FILE: tests/test_data/test_pipelines/test_indoor_pipeline.py
  function test_scannet_pipeline (line 10) | def test_scannet_pipeline():
  function test_sunrgbd_pipeline (line 107) | def test_sunrgbd_pipeline():

FILE: tests/test_data/test_pipelines/test_indoor_sample.py
  function test_indoor_sample (line 7) | def test_indoor_sample():

FILE: tests/test_data/test_pipelines/test_loadings/test_load_points_from_multi_sweeps.py
  function test_load_points_from_multi_sweeps (line 7) | def test_load_points_from_multi_sweeps():

FILE: tests/test_data/test_pipelines/test_loadings/test_loading.py
  function test_load_points_from_indoor_file (line 12) | def test_load_points_from_indoor_file():
  function test_load_points_from_outdoor_file (line 44) | def test_load_points_from_outdoor_file():
  function test_load_annotations3D (line 69) | def test_load_annotations3D():
  function test_load_points_from_multi_sweeps (line 120) | def test_load_points_from_multi_sweeps():

FILE: tests/test_data/test_pipelines/test_outdoor_pipeline.py
  function test_outdoor_aug_pipeline (line 8) | def test_outdoor_aug_pipeline():
  function test_outdoor_velocity_aug_pipeline (line 128) | def test_outdoor_velocity_aug_pipeline():

FILE: tests/test_metrics/test_indoor_eval.py
  function test_indoor_eval (line 8) | def test_indoor_eval():
  function test_indoor_eval_less_classes (line 133) | def test_indoor_eval_less_classes():
  function test_average_precision (line 183) | def test_average_precision():

FILE: tests/test_metrics/test_kitti_eval.py
  function test_do_eval (line 9) | def test_do_eval():
  function test_kitti_eval (line 112) | def test_kitti_eval():
  function test_eval_class (line 189) | def test_eval_class():

FILE: tests/test_metrics/test_losses.py
  function test_chamfer_disrance (line 5) | def test_chamfer_disrance():

FILE: tests/test_metrics/test_seg_eval.py
  function test_indoor_eval (line 8) | def test_indoor_eval():

FILE: tests/test_models/test_backbones.py
  function test_pointnet2_sa_ssg (line 8) | def test_pointnet2_sa_ssg():
  function test_multi_backbone (line 45) | def test_multi_backbone():
  function test_pointnet2_sa_msg (line 156) | def test_pointnet2_sa_msg():

FILE: tests/test_models/test_common_modules/test_middle_encoders.py
  function test_sparse_encoder (line 7) | def test_sparse_encoder():

FILE: tests/test_models/test_common_modules/test_pointnet_modules.py
  function test_pointnet_sa_module_msg (line 6) | def test_pointnet_sa_module_msg():
  function test_pointnet_sa_module (line 137) | def test_pointnet_sa_module():
  function test_pointnet_fp_module (line 169) | def test_pointnet_fp_module():

FILE: tests/test_models/test_common_modules/test_pointnet_ops.py
  function test_fps (line 9) | def test_fps():
  function test_ball_query (line 26) | def test_ball_query():
  function test_knn (line 76) | def test_knn():
  function test_grouping_points (line 126) | def test_grouping_points():
  function test_gather_points (line 198) | def test_gather_points():
  function test_three_interpolate (line 240) | def test_three_interpolate():
  function test_three_nn (line 310) | def test_three_nn():
  function test_fps_with_dist (line 377) | def test_fps_with_dist():

FILE: tests/test_models/test_common_modules/test_roiaware_pool3d.py
  function test_RoIAwarePool3d (line 9) | def test_RoIAwarePool3d():
  function test_points_in_boxes_gpu (line 43) | def test_points_in_boxes_gpu():
  function test_points_in_boxes_cpu (line 75) | def test_points_in_boxes_cpu():
  function test_points_in_boxes_batch (line 97) | def test_points_in_boxes_batch():

FILE: tests/test_models/test_common_modules/test_sparse_unet.py
  function test_SparseUNet (line 7) | def test_SparseUNet():
  function test_SparseBasicBlock (line 52) | def test_SparseBasicBlock():
  function test_make_sparse_convmodule (line 85) | def test_make_sparse_convmodule():

FILE: tests/test_models/test_common_modules/test_vote_module.py
  function test_vote_module (line 4) | def test_vote_module():

FILE: tests/test_models/test_detectors.py
  function _setup_seed (line 12) | def _setup_seed(seed):
  function _get_config_directory (line 20) | def _get_config_directory():
  function _get_config_module (line 35) | def _get_config_module(fname):
  function _get_model_cfg (line 44) | def _get_model_cfg(fname):
  function _get_detector_cfg (line 56) | def _get_detector_cfg(fname):
  function test_get_dynamic_voxelnet (line 73) | def test_get_dynamic_voxelnet():
  function test_voxel_net (line 87) | def test_voxel_net():
  function test_3dssd (line 124) | def test_3dssd():
  function test_vote_net (line 165) | def test_vote_net():
  function test_parta2 (line 208) | def test_parta2():
  function test_centerpoint (line 250) | def test_centerpoint():

FILE: tests/test_models/test_forward.py
  function _get_config_directory (line 13) | def _get_config_directory():
  function _get_config_module (line 28) | def _get_config_module(fname):
  function _get_detector_cfg (line 37) | def _get_detector_cfg(fname):
  function _test_two_stage_forward (line 48) | def _test_two_stage_forward(cfg_file):
  function _test_single_stage_forward (line 106) | def _test_single_stage_forward(cfg_file):
  function _demo_mm_inputs (line 142) | def _demo_mm_inputs(input_shape=(1, 3, 300, 300),

FILE: tests/test_models/test_fusion/test_fusion_coord_trans.py
  function test_coords_transformation (line 12) | def test_coords_transformation():

FILE: tests/test_models/test_fusion/test_point_fusion.py
  function test_sample_single (line 12) | def test_sample_single():

FILE: tests/test_models/test_fusion/test_vote_fusion.py
  function test_vote_fusion (line 12) | def test_vote_fusion():

FILE: tests/test_models/test_heads/test_heads.py
  function _setup_seed (line 14) | def _setup_seed(seed):
  function _get_config_directory (line 22) | def _get_config_directory():
  function _get_config_module (line 37) | def _get_config_module(fname):
  function _get_head_cfg (line 46) | def _get_head_cfg(fname):
  function _get_rpn_head_cfg (line 64) | def _get_rpn_head_cfg(fname):
  function _get_roi_head_cfg (line 82) | def _get_roi_head_cfg(fname):
  function _get_pts_bbox_head_cfg (line 100) | def _get_pts_bbox_head_cfg(fname):
  function _get_vote_head_cfg (line 118) | def _get_vote_head_cfg(fname):
  function _get_parta2_bbox_head_cfg (line 136) | def _get_parta2_bbox_head_cfg(fname):
  function test_anchor3d_head_loss (line 149) | def test_anchor3d_head_loss():
  function test_anchor3d_head_getboxes (line 201) | def test_anchor3d_head_getboxes():
  function test_parta2_rpnhead_getboxes (line 232) | def test_parta2_rpnhead_getboxes():
  function test_vote_head (line 265) | def test_vote_head():
  function test_parta2_bbox_head (line 360) | def test_parta2_bbox_head():
  function test_part_aggregation_ROI_head (line 372) | def test_part_aggregation_ROI_head():
  function test_free_anchor_3D_head (line 446) | def test_free_anchor_3D_head():
  function test_primitive_head (line 478) | def test_primitive_head():
  function test_h3d_head (line 591) | def test_h3d_head():
  function test_center_head (line 693) | def test_center_head():
  function test_dcn_center_head (line 768) | def test_dcn_center_head():
  function test_ssd3d_head (line 888) | def test_ssd3d_head():
  function test_shape_aware_head_loss (line 950) | def test_shape_aware_head_loss():
  function test_shape_aware_head_getboxes (line 1014) | def test_shape_aware_head_getboxes():

FILE: tests/test_models/test_heads/test_parta2_bbox_head.py
  function test_loss (line 13) | def test_loss():
  function test_get_targets (line 85) | def test_get_targets():
  function test_get_bboxes (line 254) | def test_get_bboxes():
  function test_multi_class_nms (line 359) | def test_multi_class_nms():
  function test_make_sparse_convmodule (line 437) | def test_make_sparse_convmodule():

FILE: tests/test_models/test_heads/test_roi_extractors.py
  function test_single_roiaware_extractor (line 7) | def test_single_roiaware_extractor():

FILE: tests/test_models/test_heads/test_semantic_heads.py
  function test_PointwiseSemanticHead (line 7) | def test_PointwiseSemanticHead():

FILE: tests/test_models/test_necks/test_fpn.py
  function test_secfpn (line 4) | def test_secfpn():

FILE: tests/test_models/test_necks/test_necks.py
  function test_centerpoint_fpn (line 6) | def test_centerpoint_fpn():

FILE: tests/test_models/test_voxel_encoder/test_dynamic_scatter.py
  function test_dynamic_scatter (line 8) | def test_dynamic_scatter():

FILE: tests/test_models/test_voxel_encoder/test_voxel_encoders.py
  function test_pillar_feature_net (line 6) | def test_pillar_feature_net():
  function test_hard_simple_VFE (line 26) | def test_hard_simple_VFE():

FILE: tests/test_models/test_voxel_encoder/test_voxel_generator.py
  function test_voxel_generator (line 6) | def test_voxel_generator():

FILE: tests/test_models/test_voxel_encoder/test_voxelize.py
  function _get_voxel_points_indices (line 10) | def _get_voxel_points_indices(points, coors, voxel):
  function test_voxelization (line 15) | def test_voxelization():

FILE: tests/test_runtime/test_apis.py
  function _get_config_directory (line 17) | def _get_config_directory():
  function _get_config_module (line 32) | def _get_config_module(fname):
  function test_convert_SyncBN (line 41) | def test_convert_SyncBN():
  function test_show_result_meshlab (line 51) | def test_show_result_meshlab():
  function test_inference_detector (line 83) | def test_inference_detector():
  function test_single_gpu_test (line 98) | def test_single_gpu_test():

FILE: tests/test_runtime/test_config.py
  function _get_config_directory (line 4) | def _get_config_directory():
  function test_config_build_detector (line 19) | def test_config_build_detector():
  function test_config_build_pipeline (line 73) | def test_config_build_pipeline():
  function _check_roi_head (line 101) | def _check_roi_head(config, head):
  function _check_roi_extractor (line 129) | def _check_roi_extractor(config, roi_extractor, prev_roi_extractor=None):
  function _check_mask_head (line 156) | def _check_mask_head(mask_cfg, mask_head):
  function _check_bbox_head (line 174) | def _check_bbox_head(bbox_cfg, bbox_head):
  function check_parta2_roi_head (line 198) | def check_parta2_roi_head(config, head):
  function _check_parta2_roi_extractor (line 217) | def _check_parta2_roi_extractor(config, roi_extractor):
  function _check_parta2_bbox_head (line 224) | def _check_parta2_bbox_head(bbox_cfg, bbox_head):
  function check_h3d_roi_head (line 239) | def check_h3d_roi_head(config, head):
  function _check_primitive_extractor (line 261) | def _check_primitive_extractor(config, primitive_extractor):
  function _check_h3d_bbox_head (line 267) | def _check_h3d_bbox_head(bbox_cfg, bbox_head):

FILE: tests/test_utils/test_anchors.py
  function test_anchor_3d_range_generator (line 12) | def test_anchor_3d_range_generator():
  function test_aligned_anchor_generator (line 45) | def test_aligned_anchor_generator():
  function test_aligned_anchor_generator_per_cls (line 186) | def test_aligned_anchor_generator_per_cls():

FILE: tests/test_utils/test_assigners.py
  function test_max_iou_assigner (line 12) | def test_max_iou_assigner():
  function test_max_iou_assigner_with_ignore (line 36) | def test_max_iou_assigner_with_ignore():
  function test_max_iou_assigner_with_empty_gt (line 63) | def test_max_iou_assigner_with_empty_gt():
  function test_max_iou_assigner_with_empty_boxes (line 82) | def test_max_iou_assigner_with_empty_boxes():
  function test_max_iou_assigner_with_empty_boxes_and_ignore (line 106) | def test_max_iou_assigner_with_empty_boxes_and_ignore():
  function test_max_iou_assigner_with_empty_boxes_and_gt (line 140) | def test_max_iou_assigner_with_empty_boxes_and_gt():

FILE: tests/test_utils/test_bbox_coders.py
  function test_partial_bin_based_box_coder (line 7) | def test_partial_bin_based_box_coder():
  function test_anchor_free_box_coder (line 221) | def test_anchor_free_box_coder():
  function test_centerpoint_bbox_coder (line 328) | def test_centerpoint_bbox_coder():

FILE: tests/test_utils/test_box3d.py
  function test_bbox3d_mapping_back (line 16) | def test_bbox3d_mapping_back():
  function test_bbox3d2roi (line 43) | def test_bbox3d2roi():
  function test_base_boxes3d (line 60) | def test_base_boxes3d():
  function test_lidar_boxes3d (line 93) | def test_lidar_boxes3d():
  function test_boxes_conversion (line 471) | def test_boxes_conversion():
  function test_camera_boxes3d (line 616) | def test_camera_boxes3d():
  function test_boxes3d_overlaps (line 897) | def test_boxes3d_overlaps():
  function test_depth_boxes3d (line 964) | def test_depth_boxes3d():
  function test_rotation_3d_in_axis (line 1197) | def test_rotation_3d_in_axis():
  function test_limit_period (line 1215) | def test_limit_period():
  function test_xywhr2xyxyr (line 1224) | def test_xywhr2xyxyr():
  class test_get_box_type (line 1234) | class test_get_box_type(unittest.TestCase):
    method test_get_box_type (line 1236) | def test_get_box_type(self):
    method test_bad_box_type (line 1249) | def test_bad_box_type(self):
  function test_points_cam2img (line 1253) | def test_points_cam2img():

FILE: tests/test_utils/test_box_np_ops.py
  function test_camera_to_lidar (line 4) | def test_camera_to_lidar():
  function test_box_camera_to_lidar (line 20) | def test_box_camera_to_lidar():
  function test_corners_nd (line 37) | def test_corners_nd():
  function test_center_to_corner_box2d (line 46) | def test_center_to_corner_box2d():
  function test_rotation_2d (line 58) | def test_rotation_2d():

FILE: tests/test_utils/test_coord_3d_mode.py
  function test_points_conversion (line 9) | def test_points_conversion():
  function test_boxes_conversion (line 231) | def test_boxes_conversion():

FILE: tests/test_utils/test_merge_augs.py
  function test_merge_aug_bboxes_3d (line 9) | def test_merge_aug_bboxes_3d():

FILE: tests/test_utils/test_nms.py
  function test_aligned_3d_nms (line 5) | def test_aligned_3d_nms():
  function test_circle_nms (line 61) | def test_circle_nms():

FILE: tests/test_utils/test_points.py
  function test_base_points (line 8) | def test_base_points():
  function test_cam_points (line 232) | def test_cam_points():
  function test_lidar_points (line 506) | def test_lidar_points():
  function test_depth_points (line 780) | def test_depth_points():

FILE: tests/test_utils/test_samplers.py
  function test_iou_piecewise_sampler (line 8) | def test_iou_piecewise_sampler():

FILE: tests/test_utils/test_utils.py
  function test_gaussian (line 6) | def test_gaussian():

FILE: tools/analysis_tools/analyze_logs.py
  function cal_train_time (line 9) | def cal_train_time(log_dicts, args):
  function plot_curve (line 32) | def plot_curve(log_dicts, args):
  function add_plot_parser (line 92) | def add_plot_parser(subparsers):
  function add_time_parser (line 122) | def add_time_parser(subparsers):
  function parse_args (line 138) | def parse_args():
  function load_json_logs (line 148) | def load_json_logs(json_logs):
  function main (line 168) | def main():

FILE: tools/analysis_tools/benchmark.py
  function parse_args (line 14) | def parse_args():
  function main (line 30) | def main():

FILE: tools/analysis_tools/get_flops.py
  function parse_args (line 15) | def parse_args():
  function main (line 44) | def main():

FILE: tools/combine_view_info.py
  function project_to_image (line 13) | def project_to_image(points, cam_int, cam_ext, img_h, img_w):
  function combine_data (line 34) | def combine_data(data_root, info_file, coco_file, output_file):

FILE: tools/create_data.py
  function kitti_data_prep (line 11) | def kitti_data_prep(root_path, info_prefix, version, out_dir):
  function nuscenes_data_prep (line 35) | def nuscenes_data_prep(root_path,
  function lyft_data_prep (line 70) | def lyft_data_prep(root_path,
  function scannet_data_prep (line 110) | def scannet_data_prep(root_path, info_prefix, out_dir, workers):
  function sunrgbd_data_prep (line 123) | def sunrgbd_data_prep(root_path, info_prefix, out_dir, workers):
  function waymo_data_prep (line 136) | def waymo_data_prep(root_path,

FILE: tools/data_converter/create_gt_database.py
  function _poly2mask (line 15) | def _poly2mask(mask_ann, img_h, img_w):
  function _parse_coco_ann_info (line 31) | def _parse_coco_ann_info(ann_info):
  function crop_image_patch_v2 (line 68) | def crop_image_patch_v2(pos_proposals, pos_assigned_gt_inds, gt_masks):
  function crop_image_patch (line 88) | def crop_image_patch(pos_proposals, gt_masks, pos_assigned_gt_inds, org_...
  function create_groundtruth_database (line 108) | def create_groundtruth_database(dataset_class_name,

FILE: tools/data_converter/indoor_converter.py
  function create_indoor_info_file (line 8) | def create_indoor_info_file(data_path,

FILE: tools/data_converter/kitti_converter.py
  function convert_to_kitti_info_version2 (line 9) | def convert_to_kitti_info_version2(info):
  function _read_imageset_file (line 34) | def _read_imageset_file(path):
  function _calculate_num_points_in_gt (line 40) | def _calculate_num_points_in_gt(data_path,
  function create_kitti_info_file (line 81) | def create_kitti_info_file(data_path,
  function create_waymo_info_file (line 144) | def create_waymo_info_file(data_path,
  function _create_reduced_point_cloud (line 224) | def _create_reduced_point_cloud(data_path,
  function create_reduced_point_cloud (line 283) | def create_reduced_point_cloud(data_path,

FILE: tools/data_converter/kitti_data_utils.py
  function get_image_index_str (line 9) | def get_image_index_str(img_idx, use_prefix_id=False):
  function get_kitti_info_path (line 16) | def get_kitti_info_path(idx,
  function get_image_path (line 39) | def get_image_path(idx,
  function get_label_path (line 50) | def get_label_path(idx,
  function get_velodyne_path (line 61) | def get_velodyne_path(idx,
  function get_calib_path (line 71) | def get_calib_path(idx,
  function get_pose_path (line 81) | def get_pose_path(idx,
  function get_label_anno (line 91) | def get_label_anno(label_path):
  function _extend_matrix (line 135) | def _extend_matrix(mat):
  function get_kitti_image_info (line 140) | def get_kitti_image_info(path,
  function get_waymo_image_info (line 264) | def get_waymo_image_info(path,
  function kitti_anno_to_label_file (line 443) | def kitti_anno_to_label_file(annos, folder):
  function add_difficulty_to_annos (line 466) | def add_difficulty_to_annos(info):
  function kitti_result_line (line 511) | def kitti_result_line(result_dict, precision=4):

FILE: tools/data_converter/lyft_converter.py
  function create_lyft_infos (line 16) | def create_lyft_infos(root_path,
  function _fill_trainval_infos (line 91) | def _fill_trainval_infos(lyft,
  function export_2d_annotation (line 212) | def export_2d_annotation(root_path, info_path, version):

FILE: tools/data_converter/nuimage_converter.py
  function parse_args (line 31) | def parse_args():
  function get_img_annos (line 62) | def get_img_annos(nuim, img_info, cat2id, out_dir, data_root, seg_root):
  function export_nuim_to_coco (line 149) | def export_nuim_to_coco(nuim, data_root, out_dir, extra_tag, version, np...
  function main (line 214) | def main():

FILE: tools/data_converter/nuscenes_converter.py
  function create_nuscenes_infos (line 19) | def create_nuscenes_infos(root_path,
  function get_available_scenes (line 96) | def get_available_scenes(nusc):
  function _fill_trainval_infos (line 137) | def _fill_trainval_infos(nusc,
  function obtain_sensor2top (line 266) | def obtain_sensor2top(nusc,
  function export_2d_annotation (line 327) | def export_2d_annotation(root_path, info_path, version):
  function get_2d_boxes (line 378) | def get_2d_boxes(nusc, sample_data_token: str,
  function post_process_coords (line 464) | def post_process_coords(
  function generate_record (line 497) | def generate_record(ann_rec: dict, x1: float, y1: float, x2: float, y2: ...

FILE: tools/data_converter/scannet_data_utils.py
  class ScanNetData (line 7) | class ScanNetData(object):
    method __init__ (line 17) | def __init__(self, root_path, split='train'):
    method __len__ (line 41) | def __len__(self):
    method get_box_label (line 44) | def get_box_label(self, idx):
    method get_infos (line 50) | def get_infos(self, num_workers=4, has_label=True, sample_id_list=None):

FILE: tools/data_converter/sunrgbd_data_utils.py
  function random_sampling (line 8) | def random_sampling(points, num_points, replace=None, return_choices=Fal...
  class SUNRGBDInstance (line 32) | class SUNRGBDInstance(object):
    method __init__ (line 34) | def __init__(self, line):
  class SUNRGBDData (line 58) | class SUNRGBDData(object):
    method __init__ (line 69) | def __init__(self, root_path, split='train', use_v1=False):
    method __len__ (line 94) | def __len__(self):
    method get_image (line 97) | def get_image(self, idx):
    method get_image_shape (line 101) | def get_image_shape(self, idx):
    method get_depth (line 105) | def get_depth(self, idx):
    method get_calibration (line 110) | def get_calibration(self, idx):
    method get_label_objects (line 119) | def get_label_objects(self, idx):
    method get_infos (line 125) | def get_infos(self, num_workers=4, has_label=True, sample_id_list=None):

FILE: tools/data_converter/waymo_converter.py
  class Waymo2KITTI (line 22) | class Waymo2KITTI(object):
    method __init__ (line 37) | def __init__(self,
    method convert (line 91) | def convert(self):
    method convert_one (line 98) | def convert_one(self, file_idx):
    method __len__ (line 124) | def __len__(self):
    method save_image (line 128) | def save_image(self, frame, file_idx, frame_idx):
    method save_calib (line 143) | def save_calib(self, frame, file_idx, frame_idx):
    method save_lidar (line 199) | def save_lidar(self, frame, file_idx, frame_idx):
    method save_label (line 249) | def save_label(self, frame, file_idx, frame_idx):
    method save_pose (line 349) | def save_pose(self, frame, file_idx, frame_idx):
    method create_folder (line 368) | def create_folder(self):
    method convert_range_image_to_point_cloud (line 388) | def convert_range_image_to_point_cloud(self,
    method cart_to_homo (line 496) | def cart_to_homo(self, mat):

FILE: tools/misc/fuse_conv_bn.py
  function fuse_conv_bn (line 9) | def fuse_conv_bn(conv, bn):
  function fuse_module (line 25) | def fuse_module(m):
  function parse_args (line 46) | def parse_args():
  function main (line 56) | def main():

FILE: tools/misc/print_config.py
  function parse_args (line 5) | def parse_args():
  function main (line 15) | def main():

FILE: tools/misc/visualize_results.py
  function parse_args (line 8) | def parse_args():
  function main (line 20) | def main():

FILE: tools/model_converters/convert_votenet_checkpoints.py
  function parse_args (line 10) | def parse_args():
  function parse_config (line 19) | def parse_config(config_strings):
  function main (line 69) | def main():

FILE: tools/model_converters/publish_model.py
  function parse_args (line 6) | def parse_args():
  function process_checkpoint (line 15) | def process_checkpoint(in_file, out_file):
  function main (line 28) | def main():

FILE: tools/model_converters/regnet2mmdet.py
  function convert_stem (line 6) | def convert_stem(model_key, model_weight, state_dict, converted_names):
  function convert_head (line 14) | def convert_head(model_key, model_weight, state_dict, converted_names):
  function convert_reslayer (line 21) | def convert_reslayer(model_key, model_weight, state_dict, converted_names):
  function convert (line 53) | def convert(src, dst):
  function main (line 79) | def main():

FILE: tools/test.py
  function parse_args (line 19) | def parse_args():
  function main (line 101) | def main():

FILE: tools/train.py
  function parse_args (line 22) | def parse_args():
  function main (line 91) | def main():

[
  {
    "path": ".gitignore",
    "chars": 1544,
    "preview": "# Byte-compiled / optimized / DLL files\r\n__pycache__/\r\n*.py[cod]\r\n*$py.class\r\n*.ipynb\r\n\r\n# C extensions\r\n*.so\r\n\r\n# Distr"
  },
  {
    "path": "LICENSE",
    "chars": 11400,
    "preview": "Copyright 2018-2019 Open-MMLab. All rights reserved.\n\n                                 Apache License\n                  "
  },
  {
    "path": "MANIFEST.in",
    "chars": 147,
    "preview": "include requirements/*.txt\ninclude mmdet3d/ops/**/*.cpp mmdet3d/ops/**/*.cu\ninclude mmdet3d/ops/**/*.h mmdet3d/ops/**/*."
  },
  {
    "path": "README.md",
    "chars": 6116,
    "preview": "# [ICCV 2023] SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection\n![video](vide"
  },
  {
    "path": "README_zh-CN.md",
    "chars": 6508,
    "preview": "<div align=\"center\">\n  <img src=\"resources/mmdet3d-logo.png\" width=\"600\"/>\n</div>\n\n[![docs](https://img.shields.io/badge"
  },
  {
    "path": "configs/3dssd/3dssd_kitti-3d-car.py",
    "chars": 3773,
    "preview": "_base_ = [\n    '../_base_/models/3dssd.py', '../_base_/datasets/kitti-3d-car.py',\n    '../_base_/default_runtime.py'\n]\n\n"
  },
  {
    "path": "configs/3dssd/README.md",
    "chars": 2802,
    "preview": "# 3DSSD: Point-based 3D Single Stage Object Detector\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement 3DSSD and provide the r"
  },
  {
    "path": "configs/_base_/datasets/coco_instance.py",
    "chars": 1718,
    "preview": "dataset_type = 'CocoDataset'\ndata_root = 'data/coco/'\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.3"
  },
  {
    "path": "configs/_base_/datasets/kitti-3d-3class.py",
    "chars": 4102,
    "preview": "# dataset settings\ndataset_type = 'KittiDataset'\ndata_root = 'data/kitti/'\nclass_names = ['Pedestrian', 'Cyclist', 'Car'"
  },
  {
    "path": "configs/_base_/datasets/kitti-3d-car.py",
    "chars": 4008,
    "preview": "# dataset settings\ndataset_type = 'KittiDataset'\ndata_root = 'data/kitti/'\nclass_names = ['Car']\npoint_cloud_range = [0,"
  },
  {
    "path": "configs/_base_/datasets/lyft-3d.py",
    "chars": 3954,
    "preview": "# If point cloud range is changed, the models should also change their point\n# cloud range accordingly\npoint_cloud_range"
  },
  {
    "path": "configs/_base_/datasets/nuim_instance.py",
    "chars": 1991,
    "preview": "dataset_type = 'CocoDataset'\ndata_root = 'data/nuimages/'\nclass_names = [\n    'car', 'truck', 'trailer', 'bus', 'constru"
  },
  {
    "path": "configs/_base_/datasets/nus-3d.py",
    "chars": 4301,
    "preview": "# If point cloud range is changed, the models should also change their point\n# cloud range accordingly\npoint_cloud_range"
  },
  {
    "path": "configs/_base_/datasets/range100_lyft-3d.py",
    "chars": 3958,
    "preview": "# If point cloud range is changed, the models should also change their point\n# cloud range accordingly\npoint_cloud_range"
  },
  {
    "path": "configs/_base_/datasets/scannet-3d-18class.py",
    "chars": 3366,
    "preview": "# dataset settings\ndataset_type = 'ScanNetDataset'\ndata_root = './data/scannet/'\nclass_names = ('cabinet', 'bed', 'chair"
  },
  {
    "path": "configs/_base_/datasets/sunrgbd-3d-10class.py",
    "chars": 2794,
    "preview": "dataset_type = 'SUNRGBDDataset'\ndata_root = 'data/sunrgbd/'\nclass_names = ('bed', 'table', 'sofa', 'chair', 'toilet', 'd"
  },
  {
    "path": "configs/_base_/datasets/waymoD5-3d-3class.py",
    "chars": 4256,
    "preview": "# dataset settings\n# D5 in the config name means the whole dataset is divided into 5 folds\n# We only use one fold for ef"
  },
  {
    "path": "configs/_base_/datasets/waymoD5-3d-car.py",
    "chars": 4188,
    "preview": "# dataset settings\n# D5 in the config name means the whole dataset is divided into 5 folds\n# We only use one fold for ef"
  },
  {
    "path": "configs/_base_/default_runtime.py",
    "chars": 485,
    "preview": "checkpoint_config = dict(interval=1)\n# yapf:disable push\n# By default we use textlogger hook and tensorboard\n# For more "
  },
  {
    "path": "configs/_base_/models/3dssd.py",
    "chars": 3448,
    "preview": "model = dict(\n    type='SSD3DNet',\n    backbone=dict(\n        type='PointNet2SAMSG',\n        in_channels=4,\n        num_"
  },
  {
    "path": "configs/_base_/models/cascade_mask_rcnn_r50_fpn.py",
    "chars": 6976,
    "preview": "# model settings\nmodel = dict(\n    type='CascadeRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n     "
  },
  {
    "path": "configs/_base_/models/centerpoint_01voxel_second_secfpn_nus.py",
    "chars": 3275,
    "preview": "voxel_size = [0.1, 0.1, 0.2]\nmodel = dict(\n    type='CenterPoint',\n    pts_voxel_layer=dict(\n        max_num_points=10, "
  },
  {
    "path": "configs/_base_/models/centerpoint_02pillar_second_secfpn_nus.py",
    "chars": 3183,
    "preview": "voxel_size = [0.2, 0.2, 8]\nmodel = dict(\n    type='CenterPoint',\n    pts_voxel_layer=dict(\n        max_num_points=20, vo"
  },
  {
    "path": "configs/_base_/models/h3dnet.py",
    "chars": 10970,
    "preview": "primitive_z_cfg = dict(\n    type='PrimitiveHead',\n    num_dims=2,\n    num_classes=18,\n    primitive_mode='z',\n    upper_"
  },
  {
    "path": "configs/_base_/models/hv_pointpillars_fpn_lyft.py",
    "chars": 963,
    "preview": "_base_ = './hv_pointpillars_fpn_nus.py'\n\n# model settings (based on nuScenes model settings)\n# Voxel size for voxel enco"
  },
  {
    "path": "configs/_base_/models/hv_pointpillars_fpn_nus.py",
    "chars": 3314,
    "preview": "# model settings\n# Voxel size for voxel encoder\n# Usually voxel size is changed consistently with the point cloud range\n"
  },
  {
    "path": "configs/_base_/models/hv_pointpillars_fpn_range100_lyft.py",
    "chars": 975,
    "preview": "_base_ = './hv_pointpillars_fpn_nus.py'\n\n# model settings (based on nuScenes model settings)\n# Voxel size for voxel enco"
  },
  {
    "path": "configs/_base_/models/hv_pointpillars_secfpn_kitti.py",
    "chars": 3072,
    "preview": "voxel_size = [0.16, 0.16, 4]\nmodel = dict(\n    type='VoxelNet',\n    voxel_layer=dict(\n        max_num_points=32,\n       "
  },
  {
    "path": "configs/_base_/models/hv_pointpillars_secfpn_waymo.py",
    "chars": 3987,
    "preview": "# model settings\n# Voxel size for voxel encoder\n# Usually voxel size is changed consistently with the point cloud range\n"
  },
  {
    "path": "configs/_base_/models/hv_second_secfpn_kitti.py",
    "chars": 2884,
    "preview": "model = dict(\n    type='VoxelNet',\n    voxel_layer=dict(\n        max_num_points=5,\n        point_cloud_range=[0, -40, -3"
  },
  {
    "path": "configs/_base_/models/hv_second_secfpn_waymo.py",
    "chars": 3503,
    "preview": "# model settings\n# Voxel size for voxel encoder\n# Usually voxel size is changed consistently with the point cloud range\n"
  },
  {
    "path": "configs/_base_/models/imvotenet_image.py",
    "chars": 3499,
    "preview": "model = dict(\n    type='ImVoteNet',\n    img_backbone=dict(\n        type='ResNet',\n        depth=50,\n        num_stages=4"
  },
  {
    "path": "configs/_base_/models/mask_rcnn_r50_fpn.py",
    "chars": 4080,
    "preview": "# model settings\nmodel = dict(\n    type='MaskRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n        "
  },
  {
    "path": "configs/_base_/models/votenet.py",
    "chars": 2576,
    "preview": "model = dict(\n    type='VoteNet',\n    backbone=dict(\n        type='PointNet2SASSG',\n        in_channels=4,\n        num_p"
  },
  {
    "path": "configs/_base_/schedules/cyclic_20e.py",
    "chars": 761,
    "preview": "# For nuScenes dataset, we usually evaluate the model at the end of training.\n# Since the models are trained by 24 epoch"
  },
  {
    "path": "configs/_base_/schedules/cyclic_40e.py",
    "chars": 1540,
    "preview": "# The schedule is usually used by models trained on KITTI dataset\n\n# The learning rate set in the cyclic schedule is the"
  },
  {
    "path": "configs/_base_/schedules/mmdet_schedule_1x.py",
    "chars": 283,
    "preview": "# optimizer\noptimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)\noptimizer_config = dict(grad_clip=N"
  },
  {
    "path": "configs/_base_/schedules/schedule_2x.py",
    "chars": 423,
    "preview": "# optimizer\n# This schedule is mainly used by models on nuScenes dataset\noptimizer = dict(type='AdamW', lr=0.001, weight"
  },
  {
    "path": "configs/_base_/schedules/schedule_3x.py",
    "chars": 363,
    "preview": "# optimizer\n# This schedule is mainly used by models on indoor dataset,\n# e.g., VoteNet on SUNRGBD and ScanNet\nlr = 0.00"
  },
  {
    "path": "configs/benchmark/hv_PartA2_secfpn_4x8_cyclic_80e_pcdet_kitti-3d-3class.py",
    "chars": 10982,
    "preview": "# model settings\nvoxel_size = [0.05, 0.05, 0.1]\npoint_cloud_range = [0, -40, -3, 70.4, 40, 1]  # velodyne coordinates, x"
  },
  {
    "path": "configs/benchmark/hv_pointpillars_secfpn_3x8_100e_det3d_kitti-3d-car.py",
    "chars": 6009,
    "preview": "# model settings\nvoxel_size = [0.16, 0.16, 4]\npoint_cloud_range = [0, -39.68, -3, 69.12, 39.68, 1]\nmodel = dict(\n    typ"
  },
  {
    "path": "configs/benchmark/hv_pointpillars_secfpn_4x8_80e_pcdet_kitti-3d-3class.py",
    "chars": 7208,
    "preview": "# model settings\npoint_cloud_range = [0, -39.68, -3, 69.12, 39.68, 1]\nvoxel_size = [0.16, 0.16, 4]\nmodel = dict(\n    typ"
  },
  {
    "path": "configs/benchmark/hv_second_secfpn_4x8_80e_pcdet_kitti-3d-3class.py",
    "chars": 7238,
    "preview": "# model settings\nvoxel_size = [0.05, 0.05, 0.1]\npoint_cloud_range = [0, -40, -3, 70.4, 40, 1]\n\nmodel = dict(\n    type='V"
  },
  {
    "path": "configs/centerpoint/README.md",
    "chars": 7827,
    "preview": "# Center-based 3D Object Detection and Tracking\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement CenterPoint and provide the "
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py",
    "chars": 4386,
    "preview": "_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\n# If point cloud range is changed, the models sh"
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 131,
    "preview": "_base_ = ['./centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(test_cfg=dict(pts=dict(nms_type='"
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py",
    "chars": 442,
    "preview": "_base_ = ['./centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        "
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_flip-tta_20e_nus.py",
    "chars": 1576,
    "preview": "_base_ = './centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py'\n\npoint_cloud_range = [-54, -54, -5.0, 54, 54,"
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_tta_20e_nus.py",
    "chars": 1653,
    "preview": "_base_ = './centerpoint_0075voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py'\n\ntest_cfg = dict(pts=dict(use_rotate_nms=True"
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 490,
    "preview": "_base_ = ['./centerpoint_0075voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        "
  },
  {
    "path": "configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_flip-tta_20e_nus.py",
    "chars": 1600,
    "preview": "_base_ = './centerpoint_0075voxel_second_secfpn_dcn_' \\\n         'circlenms_4x8_cyclic_20e_nus.py'\n\npoint_cloud_range = "
  },
  {
    "path": "configs/centerpoint/centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py",
    "chars": 4762,
    "preview": "_base_ = [\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/models/centerpoint_01voxel_second_secfpn_nus.py',\n    '../"
  },
  {
    "path": "configs/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 129,
    "preview": "_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(test_cfg=dict(pts=dict(nms_type='ci"
  },
  {
    "path": "configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_4x8_cyclic_20e_nus.py",
    "chars": 440,
    "preview": "_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        se"
  },
  {
    "path": "configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 488,
    "preview": "_base_ = ['./centerpoint_01voxel_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        se"
  },
  {
    "path": "configs/centerpoint/centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py",
    "chars": 4730,
    "preview": "_base_ = [\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/models/centerpoint_02pillar_second_secfpn_nus.py',\n    '.."
  },
  {
    "path": "configs/centerpoint/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 130,
    "preview": "_base_ = ['./centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(test_cfg=dict(pts=dict(nms_type='c"
  },
  {
    "path": "configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus.py",
    "chars": 441,
    "preview": "_base_ = ['./centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        s"
  },
  {
    "path": "configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py",
    "chars": 489,
    "preview": "_base_ = ['./centerpoint_02pillar_second_secfpn_4x8_cyclic_20e_nus.py']\n\nmodel = dict(\n    pts_bbox_head=dict(\n        s"
  },
  {
    "path": "configs/dynamic_voxelization/README.md",
    "chars": 2217,
    "preview": "# Dynamic Voxelization\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement Dynamic Voxelization proposed in  and provide its res"
  },
  {
    "path": "configs/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py",
    "chars": 577,
    "preview": "_base_ = '../pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py'\n\nvoxel_size = [0.16, 0.16, 4]\npoint_cloud_ran"
  },
  {
    "path": "configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py",
    "chars": 906,
    "preview": "_base_ = '../second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py'\n\npoint_cloud_range = [0, -40, -3, 70.4, 40, 1]\nvoxel_si"
  },
  {
    "path": "configs/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car.py",
    "chars": 518,
    "preview": "_base_ = '../second/hv_second_secfpn_6x8_80e_kitti-3d-car.py'\n\npoint_cloud_range = [0, -40, -3, 70.4, 40, 1]\nvoxel_size "
  },
  {
    "path": "configs/fp16/README.md",
    "chars": 3227,
    "preview": "# Mixed Precision Training\n\n## Introduction\n\n[OTHERS]\n\nWe implement mixed precision training and apply it to VoxelNets ("
  },
  {
    "path": "configs/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py",
    "chars": 217,
    "preview": "_base_ = '../pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d.py'\ndata = dict(samples_per_gpu=2, workers_per_gpu=2"
  },
  {
    "path": "configs/fp16/hv_pointpillars_regnet-400mf_fpn_sbn-all_fp16_2x8_2x_nus-3d.py",
    "chars": 224,
    "preview": "_base_ = '../regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py'\ndata = dict(samples_per_gpu=2, workers_pe"
  },
  {
    "path": "configs/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d.py",
    "chars": 220,
    "preview": "_base_ = '../pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d.py'\ndata = dict(samples_per_gpu=2, workers_per_gp"
  },
  {
    "path": "configs/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py",
    "chars": 110,
    "preview": "_base_ = '../second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py'\n# fp16 settings\nfp16 = dict(loss_scale=512.)\n"
  },
  {
    "path": "configs/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-car.py",
    "chars": 107,
    "preview": "_base_ = '../second/hv_second_secfpn_6x8_80e_kitti-3d-car.py'\n# fp16 settings\nfp16 = dict(loss_scale=512.)\n"
  },
  {
    "path": "configs/free_anchor/README.md",
    "chars": 7713,
    "preview": "# FreeAnchor for 3D Object Detection\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement FreeAnchor in 3D detection systems and "
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py",
    "chars": 1605,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py', '../_base_/schedules/s"
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py",
    "chars": 553,
    "preview": "_base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'\n\nmodel = dict(\n    pretrained=dict(pts='open-mmlab"
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py",
    "chars": 2442,
    "preview": "_base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'\n\nmodel = dict(\n    pretrained=dict(pts='open-mmlab"
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py",
    "chars": 554,
    "preview": "_base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'\n\nmodel = dict(\n    pretrained=dict(pts='open-mmlab"
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py",
    "chars": 2441,
    "preview": "_base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'\n\nmodel = dict(\n    pretrained=dict(pts='open-mmlab"
  },
  {
    "path": "configs/free_anchor/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py",
    "chars": 552,
    "preview": "_base_ = './hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py'\n\nmodel = dict(\n    pretrained=dict(pts='open-mmlab"
  },
  {
    "path": "configs/h3dnet/README.md",
    "chars": 1058,
    "preview": "# H3DNet: 3D Object Detection Using Hybrid Geometric Primitives\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement H3DNet and p"
  },
  {
    "path": "configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py",
    "chars": 3099,
    "preview": "_base_ = [\n    '../_base_/datasets/scannet-3d-18class.py', '../_base_/models/h3dnet.py',\n    '../_base_/schedules/schedu"
  },
  {
    "path": "configs/imvotenet/README.md",
    "chars": 1938,
    "preview": "# ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement I"
  },
  {
    "path": "configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py",
    "chars": 1950,
    "preview": "_base_ = [\n    '../_base_/datasets/sunrgbd-3d-10class.py', '../_base_/default_runtime.py',\n    '../_base_/models/imvoten"
  },
  {
    "path": "configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py",
    "chars": 8719,
    "preview": "_base_ = [\n    '../_base_/datasets/sunrgbd-3d-10class.py',\n    '../_base_/schedules/schedule_3x.py', '../_base_/default_"
  },
  {
    "path": "configs/mvxnet/README.md",
    "chars": 1186,
    "preview": "# MVX-Net: Multimodal VoxelNet for 3D Object Detection\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement MVX-Net and provide i"
  },
  {
    "path": "configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py",
    "chars": 8529,
    "preview": "# model settings\nvoxel_size = [0.05, 0.05, 0.1]\npoint_cloud_range = [0, -40, -3, 70.4, 40, 1]\n\nmodel = dict(\n    type='D"
  },
  {
    "path": "configs/nuimages/README.md",
    "chars": 10178,
    "preview": "# NuImages Results\n\n## Introduction\n\n[DATASET]\n\nWe support and provide some baseline results on [nuImages dataset](https"
  },
  {
    "path": "configs/nuimages/cascade_mask_rcnn_r101_fpn_1x_nuim.py",
    "chars": 127,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth"
  },
  {
    "path": "configs/nuimages/cascade_mask_rcnn_r50_fpn_1x_nuim.py",
    "chars": 2335,
    "preview": "_base_ = [\n    '../_base_/models/cascade_mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base"
  },
  {
    "path": "configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim.py",
    "chars": 263,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'\n\nload_from = 'http://download.openmmlab.com/mmdetection/v2.0/cascade_r"
  },
  {
    "path": "configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim.py",
    "chars": 332,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'\n\n# learning policy\nlr_config = dict(step=[16, 19])\ntotal_epochs = 20\n\n"
  },
  {
    "path": "configs/nuimages/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py",
    "chars": 376,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_nuim.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    back"
  },
  {
    "path": "configs/nuimages/htc_r50_fpn_1x_nuim.py",
    "chars": 1466,
    "preview": "_base_ = './htc_without_semantic_r50_fpn_1x_nuim.py'\nmodel = dict(\n    roi_head=dict(\n        semantic_roi_extractor=dic"
  },
  {
    "path": "configs/nuimages/htc_r50_fpn_coco-20e_1x_nuim.py",
    "chars": 174,
    "preview": "_base_ = './htc_r50_fpn_1x_nuim.py'\n\nload_from = 'http://download.openmmlab.com/mmdetection/v2.0/htc/htc_r50_fpn_20e_coc"
  },
  {
    "path": "configs/nuimages/htc_r50_fpn_coco-20e_20e_nuim.py",
    "chars": 113,
    "preview": "_base_ = './htc_r50_fpn_coco-20e_1x_nuim.py'\n# learning policy\nlr_config = dict(step=[16, 19])\ntotal_epochs = 20\n"
  },
  {
    "path": "configs/nuimages/htc_without_semantic_r50_fpn_1x_nuim.py",
    "chars": 7693,
    "preview": "_base_ = [\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default"
  },
  {
    "path": "configs/nuimages/htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim.py",
    "chars": 848,
    "preview": "_base_ = './htc_r50_fpn_1x_nuim.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    backbone=dict(\n   "
  },
  {
    "path": "configs/nuimages/mask_rcnn_r101_fpn_1x_nuim.py",
    "chars": 119,
    "preview": "_base_ = './mask_rcnn_r50_fpn_1x_nuim.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_caffe_fpn_1x_nuim.py",
    "chars": 1636,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py",
    "chars": 1866,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py",
    "chars": 1934,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_fpn_1x_nuim.py",
    "chars": 286,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_fpn_coco-2x_1x_nuim.py",
    "chars": 478,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_r50_fpn_coco-2x_1x_nus-2d.py",
    "chars": 1298,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/nuim_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/nuimages/mask_rcnn_swinT_coco-2x_1x_nuim.py",
    "chars": 5168,
    "preview": "_base_ = [\r\n    '../_base_/datasets/nuim_instance.py', '../_base_/default_runtime.py'\r\n]\r\n\r\nmodel = dict(\r\n    type='Mas"
  },
  {
    "path": "configs/nuimages/mask_rcnn_x101_32x4d_fpn_1x_nuim.py",
    "chars": 368,
    "preview": "_base_ = './mask_rcnn_r50_fpn_1x_nuim.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    backbone=dic"
  },
  {
    "path": "configs/nuscenes.md",
    "chars": 3570,
    "preview": "# MODEL ZOO\n\n## Common settings and notes\n\n- The experiments are run with PyTorch 1.7.0, CUDA 10.1 and CUDNN 7.6\n- The t"
  },
  {
    "path": "configs/parta2/README.md",
    "chars": 1737,
    "preview": "# From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network\n\n## Introducti"
  },
  {
    "path": "configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py",
    "chars": 10495,
    "preview": "_base_ = ['../_base_/schedules/cyclic_40e.py', '../_base_/default_runtime.py']\n\n# model settings\nvoxel_size = [0.05, 0.0"
  },
  {
    "path": "configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car.py",
    "chars": 4737,
    "preview": "_base_ = './hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py'\n\nvoxel_size = [0.05, 0.05, 0.1]\npoint_cloud_range = [0, "
  },
  {
    "path": "configs/pointpillars/README.md",
    "chars": 6852,
    "preview": "# PointPillars: Fast Encoders for Object Detection from Point Clouds\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement PointPi"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_fpn_sbn-all_2x8_2x_lyft-3d.py",
    "chars": 175,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_lyft.py',\n    '../_base_/datasets/lyft-3d.py', '../_base_/schedules"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d.py",
    "chars": 173,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py', '../_base_/schedules/s"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_fpn_sbn-all_range100_2x8_2x_lyft-3d.py",
    "chars": 193,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_range100_lyft.py',\n    '../_base_/datasets/range100_lyft-3d.py',\n  "
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class.py",
    "chars": 3360,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_secfpn_kitti.py',\n    '../_base_/datasets/kitti-3d-3class.py',\n    '../"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py",
    "chars": 3199,
    "preview": "# model settings\n_base_ = './hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class.py'\n\npoint_cloud_range = [0, -39.68, -3, 69"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn-all_2x8_2x_lyft-3d.py",
    "chars": 1756,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_lyft.py',\n    '../_base_/datasets/lyft-3d.py',\n    '../_base_/sched"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d.py",
    "chars": 1754,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/schedul"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn-all_range100_2x8_2x_lyft-3d.py",
    "chars": 1805,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_range100_lyft.py',\n    '../_base_/datasets/range100_lyft-3d.py',\n  "
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-3class.py",
    "chars": 266,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_secfpn_waymo.py',\n    '../_base_/datasets/waymoD5-3d-3class.py',\n    '."
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-car.py",
    "chars": 1171,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_secfpn_waymo.py',\n    '../_base_/datasets/waymoD5-3d-car.py',\n    '../_"
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py",
    "chars": 194,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_secfpn_waymo.py',\n    '../_base_/datasets/waymoD5-3d-3class.py',\n    '."
  },
  {
    "path": "configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car.py",
    "chars": 1099,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_secfpn_waymo.py',\n    '../_base_/datasets/waymoD5-3d-car.py',\n    '../_"
  },
  {
    "path": "configs/regnet/README.md",
    "chars": 5515,
    "preview": "# Designing Network Design Spaces\n\n## Introduction\n\n[BACKBONE]\n\nWe implement RegNetX models in 3D detection systems and "
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py",
    "chars": 703,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/schedul"
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py",
    "chars": 754,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_lyft.py',\n    '../_base_/datasets/lyft-3d.py',\n    '../_base_/sched"
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py",
    "chars": 752,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/schedul"
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py",
    "chars": 772,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_range100_lyft.py',\n    '../_base_/datasets/range100_lyft-3d.py',\n  "
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_2x8_2x_lyft-3d.py",
    "chars": 1677,
    "preview": "_base_ = './hv_pointpillars_regnet-400mf_fpn_sbn-all_2x8_2x_lyft-3d.py'\n# model settings\nmodel = dict(\n    pts_neck=dict"
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d.py",
    "chars": 1676,
    "preview": "_base_ = './hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py'\n# model settings\nmodel = dict(\n    pts_neck=dict("
  },
  {
    "path": "configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_range100_2x8_2x_lyft-3d.py",
    "chars": 1728,
    "preview": "_base_ = \\\n    './hv_pointpillars_regnet-400mf_fpn_sbn-all_range100_2x8_2x_lyft-3d.py'\n# model settings\nmodel = dict(\n  "
  },
  {
    "path": "configs/second/README.md",
    "chars": 2554,
    "preview": "# Second: Sparsely embedded convolutional detection\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement SECOND and provide the r"
  },
  {
    "path": "configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py",
    "chars": 180,
    "preview": "_base_ = [\n    '../_base_/models/hv_second_secfpn_kitti.py',\n    '../_base_/datasets/kitti-3d-3class.py',\n    '../_base_"
  },
  {
    "path": "configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py",
    "chars": 970,
    "preview": "_base_ = [\n    '../_base_/models/hv_second_secfpn_kitti.py',\n    '../_base_/datasets/kitti-3d-car.py', '../_base_/schedu"
  },
  {
    "path": "configs/second/hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py",
    "chars": 3697,
    "preview": "_base_ = [\n    '../_base_/models/hv_second_secfpn_waymo.py',\n    '../_base_/datasets/waymoD5-3d-3class.py',\n    '../_bas"
  },
  {
    "path": "configs/sparsefusion_nusc_voxel_LC_SwinT.py",
    "chars": 14294,
    "preview": "point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]\r\nclass_names = [\r\n    'car', 'truck', 'construction_vehicle', "
  },
  {
    "path": "configs/sparsefusion_nusc_voxel_LC_r50.py",
    "chars": 13961,
    "preview": "point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]\r\nclass_names = [\r\n    'car', 'truck', 'construction_vehicle', "
  },
  {
    "path": "configs/ssn/README.md",
    "chars": 4615,
    "preview": "# SSN: Shape Signature Networks for Multi-class Object Detection from Point Clouds\n\n## Introduction\n\n[ALGORITHM]\n\nWe imp"
  },
  {
    "path": "configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py",
    "chars": 697,
    "preview": "_base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py'\n# model settings\nmodel = dict(\n    type='MVXFasterRCNN',\n    pretr"
  },
  {
    "path": "configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d.py",
    "chars": 627,
    "preview": "_base_ = './hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py'\n# model settings\nmodel = dict(\n    type='MVXFasterRCNN',\n    pretra"
  },
  {
    "path": "configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py",
    "chars": 8730,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_lyft.py',\n    '../_base_/datasets/lyft-3d.py',\n    '../_base_/sched"
  },
  {
    "path": "configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py",
    "chars": 9769,
    "preview": "_base_ = [\n    '../_base_/models/hv_pointpillars_fpn_nus.py',\n    '../_base_/datasets/nus-3d.py',\n    '../_base_/schedul"
  },
  {
    "path": "configs/transfusion_nusc_pillar_L.py",
    "chars": 8832,
    "preview": "point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]\nclass_names = [\n    'car', 'truck', 'construction_vehicle', 'b"
  },
  {
    "path": "configs/transfusion_nusc_pillar_LC.py",
    "chars": 9079,
    "preview": "point_cloud_range = [-51.2, -51.2, -5.0, 51.2, 51.2, 3.0]\nclass_names = [\n    'car', 'truck', 'construction_vehicle', 'b"
  },
  {
    "path": "configs/transfusion_nusc_voxel_L.py",
    "chars": 8895,
    "preview": "point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]\nclass_names = [\n    'car', 'truck', 'construction_vehicle', 'b"
  },
  {
    "path": "configs/transfusion_nusc_voxel_LC.py",
    "chars": 9148,
    "preview": "point_cloud_range = [-54.0, -54.0, -5.0, 54.0, 54.0, 3.0]\nclass_names = [\n    'car', 'truck', 'construction_vehicle', 'b"
  },
  {
    "path": "configs/transfusion_waymo_voxel_L.py",
    "chars": 8163,
    "preview": "point_cloud_range = [-75.2, -75.2, -2, 75.2, 75.2, 4]\nclass_names = ['Car', 'Pedestrian', 'Cyclist']\nvoxel_size = [0.1, "
  },
  {
    "path": "configs/transfusion_waymo_voxel_LC.py",
    "chars": 8903,
    "preview": "point_cloud_range = [-75.2, -75.2, -2, 75.2, 75.2, 4]\nclass_names = ['Car', 'Pedestrian', 'Cyclist']\nvoxel_size = [0.1, "
  },
  {
    "path": "configs/votenet/README.md",
    "chars": 3283,
    "preview": "# Deep Hough Voting for 3D Object Detection in Point Clouds\n\n## Introduction\n\n[ALGORITHM]\n\nWe implement VoteNet and prov"
  },
  {
    "path": "configs/votenet/votenet_16x8_sunrgbd-3d-10class.py",
    "chars": 836,
    "preview": "_base_ = [\n    '../_base_/datasets/sunrgbd-3d-10class.py', '../_base_/models/votenet.py',\n    '../_base_/schedules/sched"
  },
  {
    "path": "configs/votenet/votenet_8x8_scannet-3d-18class.py",
    "chars": 1651,
    "preview": "_base_ = [\n    '../_base_/datasets/scannet-3d-18class.py', '../_base_/models/votenet.py',\n    '../_base_/schedules/sched"
  },
  {
    "path": "configs/votenet/votenet_iouloss_8x8_scannet-3d-18class.py",
    "chars": 232,
    "preview": "_base_ = ['./votenet_8x8_scannet-3d-18class.py']\n\n# model settings, add iou loss\nmodel = dict(\n    bbox_head=dict(\n     "
  },
  {
    "path": "configs/waymo.md",
    "chars": 978,
    "preview": "# MODEL ZOO\n\n## Common settings and notes\n\n- The experiments are run with PyTorch 1.7.0, CUDA 10.1 and CUDNN 7.6\n- The t"
  },
  {
    "path": "demo/pcd_demo.py",
    "chars": 999,
    "preview": "from argparse import ArgumentParser\n\nfrom mmdet3d.apis import inference_detector, init_detector, show_result_meshlab\n\n\nd"
  },
  {
    "path": "docker/Dockerfile",
    "chars": 1038,
    "preview": "ARG PYTORCH=\"1.6.0\"\nARG CUDA=\"10.1\"\nARG CUDNN=\"7\"\n\nFROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel\n\nENV "
  },
  {
    "path": "mmdet3d/__init__.py",
    "chars": 1273,
    "preview": "import mmcv\n\nimport mmdet\nfrom .version import __version__, short_version\n\n\ndef digit_version(version_str):\n    digit_ve"
  },
  {
    "path": "mmdet3d/apis/__init__.py",
    "chars": 275,
    "preview": "from .inference import (convert_SyncBN, inference_detector, init_detector,\n                        show_result_meshlab)\n"
  },
  {
    "path": "mmdet3d/apis/inference.py",
    "chars": 4610,
    "preview": "import mmcv\nimport torch\nfrom copy import deepcopy\nfrom mmcv.parallel import collate, scatter\nfrom mmcv.runner import lo"
  },
  {
    "path": "mmdet3d/apis/test.py",
    "chars": 1134,
    "preview": "import mmcv\nimport torch\n\n\ndef single_gpu_test(model, data_loader, show=False, out_dir=None):\n    \"\"\"Test model with sin"
  },
  {
    "path": "mmdet3d/core/__init__.py",
    "chars": 349,
    "preview": "from .anchor import *  # noqa: F401, F403\nfrom .bbox import *  # noqa: F401, F403\nfrom .evaluation import *  # noqa: F40"
  },
  {
    "path": "mmdet3d/core/anchor/__init__.py",
    "chars": 393,
    "preview": "from mmdet.core.anchor import build_anchor_generator\nfrom .anchor_3d_generator import (AlignedAnchor3DRangeGenerator,\n  "
  },
  {
    "path": "mmdet3d/core/anchor/anchor_3d_generator.py",
    "chars": 17129,
    "preview": "import mmcv\nimport torch\n\nfrom mmdet.core.anchor import ANCHOR_GENERATORS\n\n\n@ANCHOR_GENERATORS.register_module()\nclass A"
  },
  {
    "path": "mmdet3d/core/bbox/__init__.py",
    "chars": 1610,
    "preview": "from .assigners import AssignResult, BaseAssigner, MaxIoUAssigner\nfrom .coders import DeltaXYZWLHRBBoxCoder\n# from .bbox"
  },
  {
    "path": "mmdet3d/core/bbox/assigners/__init__.py",
    "chars": 431,
    "preview": "from mmdet.core.bbox import AssignResult, BaseAssigner, MaxIoUAssigner\nfrom .hungarian_assigner import HungarianAssigner"
  },
  {
    "path": "mmdet3d/core/bbox/assigners/hungarian_assigner.py",
    "chars": 21697,
    "preview": "from mmdet.core.bbox.builder import BBOX_ASSIGNERS\nfrom mmdet.core.bbox.assigners import AssignResult, BaseAssigner\nfrom"
  },
  {
    "path": "mmdet3d/core/bbox/box_np_ops.py",
    "chars": 32421,
    "preview": "# TODO: clean the functions in this file and move the APIs into box structures\n# in the future\n\nimport numba\nimport nump"
  },
  {
    "path": "mmdet3d/core/bbox/coders/__init__.py",
    "chars": 579,
    "preview": "from mmdet.core.bbox import build_bbox_coder\nfrom .anchor_free_bbox_coder import AnchorFreeBBoxCoder\nfrom .centerpoint_b"
  },
  {
    "path": "mmdet3d/core/bbox/coders/anchor_free_bbox_coder.py",
    "chars": 4319,
    "preview": "import numpy as np\nimport torch\n\nfrom mmdet.core.bbox.builder import BBOX_CODERS\nfrom .partial_bin_based_bbox_coder impo"
  },
  {
    "path": "mmdet3d/core/bbox/coders/camera_bbox_coder.py",
    "chars": 2909,
    "preview": "import torch\r\n\r\nfrom mmdet.core.bbox import BaseBBoxCoder\r\nfrom mmdet.core.bbox.builder import BBOX_CODERS\r\n\r\n\r\n@BBOX_CO"
  },
  {
    "path": "mmdet3d/core/bbox/coders/centerpoint_bbox_coders.py",
    "chars": 8543,
    "preview": "import torch\n\nfrom mmdet.core.bbox import BaseBBoxCoder\nfrom mmdet.core.bbox.builder import BBOX_CODERS\n\n\n@BBOX_CODERS.r"
  },
  {
    "path": "mmdet3d/core/bbox/coders/delta_xyzwhlr_bbox_coder.py",
    "chars": 3074,
    "preview": "import torch\n\nfrom mmdet.core.bbox import BaseBBoxCoder\nfrom mmdet.core.bbox.builder import BBOX_CODERS\n\n\n@BBOX_CODERS.r"
  },
  {
    "path": "mmdet3d/core/bbox/coders/partial_bin_based_bbox_coder.py",
    "chars": 9098,
    "preview": "import numpy as np\nimport torch\n\nfrom mmdet.core.bbox import BaseBBoxCoder\nfrom mmdet.core.bbox.builder import BBOX_CODE"
  },
  {
    "path": "mmdet3d/core/bbox/coders/transfusion_bbox_coder.py",
    "chars": 5354,
    "preview": "import torch\n\nfrom mmdet.core.bbox import BaseBBoxCoder\nfrom mmdet.core.bbox.builder import BBOX_CODERS\n\n\n@BBOX_CODERS.r"
  },
  {
    "path": "mmdet3d/core/bbox/iou_calculators/__init__.py",
    "chars": 444,
    "preview": "from .iou3d_calculator import (AxisAlignedBboxOverlaps3D, BboxOverlaps3D,\n                               BboxOverlapsNea"
  },
  {
    "path": "mmdet3d/core/bbox/iou_calculators/iou3d_calculator.py",
    "chars": 12463,
    "preview": "import torch\n\nfrom mmdet.core.bbox import bbox_overlaps\nfrom mmdet.core.bbox.iou_calculators.builder import IOU_CALCULAT"
  },
  {
    "path": "mmdet3d/core/bbox/samplers/__init__.py",
    "chars": 600,
    "preview": "from mmdet.core.bbox.samplers import (BaseSampler, CombinedSampler,\n                                      InstanceBalanc"
  },
  {
    "path": "mmdet3d/core/bbox/samplers/iou_neg_piecewise_sampler.py",
    "chars": 6813,
    "preview": "import torch\n\nfrom mmdet.core.bbox.builder import BBOX_SAMPLERS\nfrom . import RandomSampler, SamplingResult\n\n\n@BBOX_SAMP"
  },
  {
    "path": "mmdet3d/core/bbox/structures/__init__.py",
    "chars": 615,
    "preview": "from .base_box3d import BaseInstance3DBoxes\nfrom .box_3d_mode import Box3DMode\nfrom .cam_box3d import CameraInstance3DBo"
  },
  {
    "path": "mmdet3d/core/bbox/structures/base_box3d.py",
    "chars": 16275,
    "preview": "import numpy as np\nimport torch\nfrom abc import abstractmethod\n\nfrom mmdet3d.ops.iou3d import iou3d_cuda\nfrom .utils imp"
  },
  {
    "path": "mmdet3d/core/bbox/structures/box_3d_mode.py",
    "chars": 5980,
    "preview": "import numpy as np\nimport torch\nfrom enum import IntEnum, unique\n\nfrom .base_box3d import BaseInstance3DBoxes\nfrom .cam_"
  },
  {
    "path": "mmdet3d/core/bbox/structures/cam_box3d.py",
    "chars": 12069,
    "preview": "import numpy as np\nimport torch\n\nfrom mmdet3d.core.points import BasePoints\nfrom .base_box3d import BaseInstance3DBoxes\n"
  },
  {
    "path": "mmdet3d/core/bbox/structures/coord_3d_mode.py",
    "chars": 10972,
    "preview": "import numpy as np\nimport torch\nfrom enum import IntEnum, unique\n\nfrom mmdet3d.core.points import (BasePoints, CameraPoi"
  },
  {
    "path": "mmdet3d/core/bbox/structures/depth_box3d.py",
    "chars": 12942,
    "preview": "import numpy as np\nimport torch\n\nfrom mmdet3d.core.points import BasePoints\nfrom mmdet3d.ops import points_in_boxes_batc"
  },
  {
    "path": "mmdet3d/core/bbox/structures/lidar_box3d.py",
    "chars": 9864,
    "preview": "import numpy as np\nimport torch\n\nfrom mmdet3d.core.points import BasePoints\nfrom mmdet3d.ops.roiaware_pool3d import poin"
  },
  {
    "path": "mmdet3d/core/bbox/structures/utils.py",
    "chars": 4865,
    "preview": "import numpy as np\nimport torch\n\n\ndef limit_period(val, offset=0.5, period=np.pi):\n    \"\"\"Limit the value into a period "
  },
  {
    "path": "mmdet3d/core/bbox/transforms.py",
    "chars": 2081,
    "preview": "import torch\n\n\ndef bbox3d_mapping_back(bboxes, scale_factor, flip_horizontal, flip_vertical):\n    \"\"\"Map bboxes from tes"
  },
  {
    "path": "mmdet3d/core/evaluation/__init__.py",
    "chars": 261,
    "preview": "from .indoor_eval import indoor_eval\nfrom .kitti_utils import kitti_eval, kitti_eval_coco_style\nfrom .lyft_eval import l"
  },
  {
    "path": "mmdet3d/core/evaluation/indoor_eval.py",
    "chars": 11037,
    "preview": "import numpy as np\nimport torch\nfrom mmcv.utils import print_log\nfrom terminaltables import AsciiTable\n\n\ndef average_pre"
  },
  {
    "path": "mmdet3d/core/evaluation/kitti_utils/__init__.py",
    "chars": 103,
    "preview": "from .eval import kitti_eval, kitti_eval_coco_style\n\n__all__ = ['kitti_eval', 'kitti_eval_coco_style']\n"
  },
  {
    "path": "mmdet3d/core/evaluation/kitti_utils/eval.py",
    "chars": 33476,
    "preview": "import gc\nimport io as sysio\nimport numba\nimport numpy as np\n\n\n@numba.jit\ndef get_thresholds(scores: np.ndarray, num_gt,"
  },
  {
    "path": "mmdet3d/core/evaluation/kitti_utils/rotate_iou.py",
    "chars": 13267,
    "preview": "#####################\n# Based on https://github.com/hongzhenwang/RRPN-revise\n# Licensed under The MIT License\n# Author: "
  },
  {
    "path": "mmdet3d/core/evaluation/lyft_eval.py",
    "chars": 10305,
    "preview": "import mmcv\nimport numpy as np\nfrom lyft_dataset_sdk.eval.detection.mAP_evaluation import (Box3D, get_ap,\n              "
  },
  {
    "path": "mmdet3d/core/evaluation/seg_eval.py",
    "chars": 3372,
    "preview": "import numpy as np\nfrom mmcv.utils import print_log\nfrom terminaltables import AsciiTable\n\n\ndef fast_hist(preds, labels,"
  },
  {
    "path": "mmdet3d/core/evaluation/waymo_utils/prediction_kitti_to_waymo.py",
    "chars": 9652,
    "preview": "r\"\"\"Adapted from `Waymo to KITTI converter\n    <https://github.com/caizhongang/waymo_kitti_converter>`_.\n\"\"\"\n\ntry:\n    f"
  },
  {
    "path": "mmdet3d/core/points/__init__.py",
    "chars": 873,
    "preview": "from .base_points import BasePoints\nfrom .cam_points import CameraPoints\nfrom .depth_points import DepthPoints\nfrom .lid"
  },
  {
    "path": "mmdet3d/core/points/base_points.py",
    "chars": 13731,
    "preview": "import numpy as np\nimport torch\nfrom abc import abstractmethod\n\n\nclass BasePoints(object):\n    \"\"\"Base class for Points."
  },
  {
    "path": "mmdet3d/core/points/cam_points.py",
    "chars": 2818,
    "preview": "from .base_points import BasePoints\n\n\nclass CameraPoints(BasePoints):\n    \"\"\"Points of instances in CAM coordinates.\n\n  "
  },
  {
    "path": "mmdet3d/core/points/depth_points.py",
    "chars": 2820,
    "preview": "from .base_points import BasePoints\n\n\nclass DepthPoints(BasePoints):\n    \"\"\"Points of instances in DEPTH coordinates.\n\n "
  },
  {
    "path": "mmdet3d/core/points/lidar_points.py",
    "chars": 2820,
    "preview": "from .base_points import BasePoints\n\n\nclass LiDARPoints(BasePoints):\n    \"\"\"Points of instances in LIDAR coordinates.\n\n "
  },
  {
    "path": "mmdet3d/core/post_processing/__init__.py",
    "chars": 531,
    "preview": "from mmdet.core.post_processing import (merge_aug_bboxes, merge_aug_masks,\n                                        merge"
  },
  {
    "path": "mmdet3d/core/post_processing/box3d_nms.py",
    "chars": 6369,
    "preview": "import numba\nimport numpy as np\nimport torch\n\nfrom mmdet3d.ops.iou3d.iou3d_utils import nms_gpu, nms_normal_gpu\n\n\ndef bo"
  },
  {
    "path": "mmdet3d/core/post_processing/merge_augs.py",
    "chars": 3447,
    "preview": "import torch\n\nfrom mmdet3d.ops.iou3d.iou3d_utils import nms_gpu, nms_normal_gpu\nfrom ..bbox import bbox3d2result, bbox3d"
  },
  {
    "path": "mmdet3d/core/utils/__init__.py",
    "chars": 145,
    "preview": "from .gaussian import draw_heatmap_gaussian, gaussian_2d, gaussian_radius\n\n__all__ = ['gaussian_2d', 'gaussian_radius', "
  }
]

// ... and 316 more files (download for full content)