Full Code of MCG-NJU/AdaMixer for AI

gitextract_qwmo5r_u/

├── .gitignore
├── LICENSE
├── Makefile
├── README.md
├── README_zh-CN.md
├── configs/
│   ├── _base_/
│   │   ├── datasets/
│   │   │   ├── cityscapes_detection.py
│   │   │   ├── cityscapes_instance.py
│   │   │   ├── coco_detection.py
│   │   │   ├── coco_detection_tiny.py
│   │   │   ├── coco_instance.py
│   │   │   ├── coco_instance_semantic.py
│   │   │   ├── deepfashion.py
│   │   │   ├── lvis_v0.5_instance.py
│   │   │   ├── lvis_v1_instance.py
│   │   │   ├── voc0712.py
│   │   │   └── wider_face.py
│   │   ├── default_runtime.py
│   │   ├── models/
│   │   │   ├── cascade_mask_rcnn_r50_fpn.py
│   │   │   ├── cascade_rcnn_r50_fpn.py
│   │   │   ├── fast_rcnn_r50_fpn.py
│   │   │   ├── faster_rcnn_r50_caffe_c4.py
│   │   │   ├── faster_rcnn_r50_caffe_dc5.py
│   │   │   ├── faster_rcnn_r50_fpn.py
│   │   │   ├── mask_rcnn_r50_caffe_c4.py
│   │   │   ├── mask_rcnn_r50_fpn.py
│   │   │   ├── retinanet_r50_fpn.py
│   │   │   ├── rpn_r50_caffe_c4.py
│   │   │   ├── rpn_r50_fpn.py
│   │   │   └── ssd300.py
│   │   └── schedules/
│   │       ├── schedule_1x.py
│   │       ├── schedule_20e.py
│   │       └── schedule_2x.py
│   ├── adamixer/
│   │   ├── README.md
│   │   ├── adamixer_dx101_300_query_crop_mstrain_480-800_3x_coco.py
│   │   ├── adamixer_r101_300_query_crop_mstrain_480-800_3x_coco.py
│   │   ├── adamixer_r101_mstrain_480-800_3x_coco.py
│   │   ├── adamixer_r50_1x_coco.py
│   │   ├── adamixer_r50_300_query_crop_mstrain_480-800_3x_coco.py
│   │   ├── adamixer_r50_mstrain_480-800_3x_coco.py
│   │   └── adamixer_swin_s_300_query_crop_mstrain_480-800_3x_coco.py
│   ├── albu_example/
│   │   ├── README.md
│   │   └── mask_rcnn_r50_fpn_albu_1x_coco.py
│   ├── atss/
│   │   ├── README.md
│   │   ├── atss_r101_fpn_1x_coco.py
│   │   └── atss_r50_fpn_1x_coco.py
│   ├── autoassign/
│   │   ├── README.md
│   │   └── autoassign_r50_fpn_8x2_1x_coco.py
│   ├── carafe/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_carafe_1x_coco.py
│   │   └── mask_rcnn_r50_fpn_carafe_1x_coco.py
│   ├── cascade_rcnn/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_r101_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_r101_fpn_20e_coco.py
│   │   ├── cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_r50_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_r50_fpn_20e_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_20e_coco.py
│   │   ├── cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_64x4d_fpn_20e_coco.py
│   │   ├── cascade_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── cascade_rcnn_r101_fpn_1x_coco.py
│   │   ├── cascade_rcnn_r101_fpn_20e_coco.py
│   │   ├── cascade_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── cascade_rcnn_r50_fpn_1x_coco.py
│   │   ├── cascade_rcnn_r50_fpn_20e_coco.py
│   │   ├── cascade_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── cascade_rcnn_x101_32x4d_fpn_20e_coco.py
│   │   ├── cascade_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   └── cascade_rcnn_x101_64x4d_fpn_20e_coco.py
│   ├── cascade_rpn/
│   │   ├── README.md
│   │   ├── crpn_fast_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── crpn_faster_rcnn_r50_caffe_fpn_1x_coco.py
│   │   └── crpn_r50_caffe_fpn_1x_coco.py
│   ├── centripetalnet/
│   │   ├── README.md
│   │   └── centripetalnet_hourglass104_mstest_16x6_210e_coco.py
│   ├── cityscapes/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_1x_cityscapes.py
│   │   └── mask_rcnn_r50_fpn_1x_cityscapes.py
│   ├── cornernet/
│   │   ├── README.md
│   │   ├── cornernet_hourglass104_mstest_10x5_210e_coco.py
│   │   ├── cornernet_hourglass104_mstest_32x3_210e_coco.py
│   │   └── cornernet_hourglass104_mstest_8x6_210e_coco.py
│   ├── dcn/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_dpool_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_mdpool_1x_coco.py
│   │   ├── faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py
│   │   └── mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py
│   ├── deepfashion/
│   │   ├── README.md
│   │   └── mask_rcnn_r50_fpn_15e_deepfashion.py
│   ├── deformable_detr/
│   │   ├── README.md
│   │   ├── deformable_detr_r50_16x2_50e_coco.py
│   │   ├── deformable_detr_refine_r50_16x2_50e_coco.py
│   │   └── deformable_detr_twostage_refine_r50_16x2_50e_coco.py
│   ├── detectors/
│   │   ├── README.md
│   │   ├── cascade_rcnn_r50_rfp_1x_coco.py
│   │   ├── cascade_rcnn_r50_sac_1x_coco.py
│   │   ├── detectors_cascade_rcnn_r50_1x_coco.py
│   │   ├── detectors_htc_r50_1x_coco.py
│   │   ├── htc_r50_rfp_1x_coco.py
│   │   └── htc_r50_sac_1x_coco.py
│   ├── detr/
│   │   ├── README.md
│   │   └── detr_r50_8x2_150e_coco.py
│   ├── double_heads/
│   │   ├── README.md
│   │   └── dh_faster_rcnn_r50_fpn_1x_coco.py
│   ├── dynamic_rcnn/
│   │   ├── README.md
│   │   └── dynamic_rcnn_r50_fpn_1x_coco.py
│   ├── empirical_attention/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_attention_0010_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_attention_1111_1x_coco.py
│   │   └── faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py
│   ├── fast_rcnn/
│   │   ├── README.md
│   │   ├── fast_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── fast_rcnn_r101_fpn_1x_coco.py
│   │   ├── fast_rcnn_r101_fpn_2x_coco.py
│   │   ├── fast_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── fast_rcnn_r50_fpn_1x_coco.py
│   │   └── fast_rcnn_r50_fpn_2x_coco.py
│   ├── faster_rcnn/
│   │   ├── README.md
│   │   ├── faster_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── faster_rcnn_r101_fpn_1x_coco.py
│   │   ├── faster_rcnn_r101_fpn_2x_coco.py
│   │   ├── faster_rcnn_r50_caffe_c4_1x_coco.py
│   │   ├── faster_rcnn_r50_caffe_dc5_1x_coco.py
│   │   ├── faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py
│   │   ├── faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py
│   │   ├── faster_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person-bicycle-car.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py
│   │   ├── faster_rcnn_r50_caffe_fpn_mstrain_90k_coco.py
│   │   ├── faster_rcnn_r50_fpn_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_2x_coco.py
│   │   ├── faster_rcnn_r50_fpn_bounded_iou_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_giou_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_iou_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_ohem_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_soft_nms_1x_coco.py
│   │   ├── faster_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── faster_rcnn_x101_32x4d_fpn_2x_coco.py
│   │   ├── faster_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   └── faster_rcnn_x101_64x4d_fpn_2x_coco.py
│   ├── fcos/
│   │   ├── README.md
│   │   ├── fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_1x_coco.py
│   │   ├── fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_1x_coco.py
│   │   ├── fcos_center_r50_caffe_fpn_gn-head_1x_coco.py
│   │   ├── fcos_r101_caffe_fpn_gn-head_1x_coco.py
│   │   ├── fcos_r101_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py
│   │   ├── fcos_r50_caffe_fpn_gn-head_1x_coco.py
│   │   ├── fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py
│   │   ├── fcos_r50_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py
│   │   ├── fcos_r50_torch_fpn_gn-head_4x4_1x_coco.py
│   │   └── fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_2x_coco.py
│   ├── foveabox/
│   │   ├── README.md
│   │   ├── fovea_align_r101_fpn_gn-head_4x4_2x_coco.py
│   │   ├── fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py
│   │   ├── fovea_align_r50_fpn_gn-head_4x4_2x_coco.py
│   │   ├── fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py
│   │   ├── fovea_r101_fpn_4x4_1x_coco.py
│   │   ├── fovea_r101_fpn_4x4_2x_coco.py
│   │   ├── fovea_r50_fpn_4x4_1x_coco.py
│   │   └── fovea_r50_fpn_4x4_2x_coco.py
│   ├── fp16/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_fp16_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_fp16_1x_coco.py
│   │   └── retinanet_r50_fpn_fp16_1x_coco.py
│   ├── fpg/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py
│   │   ├── faster_rcnn_r50_fpg_crop640_50e_coco.py
│   │   ├── faster_rcnn_r50_fpn_crop640_50e_coco.py
│   │   ├── mask_rcnn_r50_fpg-chn128_crop640_50e_coco.py
│   │   ├── mask_rcnn_r50_fpg_crop640_50e_coco.py
│   │   ├── mask_rcnn_r50_fpn_crop640_50e_coco.py
│   │   ├── retinanet_r50_fpg-chn128_crop640_50e_coco.py
│   │   └── retinanet_r50_fpg_crop640_50e_coco.py
│   ├── free_anchor/
│   │   ├── README.md
│   │   ├── retinanet_free_anchor_r101_fpn_1x_coco.py
│   │   ├── retinanet_free_anchor_r50_fpn_1x_coco.py
│   │   └── retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py
│   ├── fsaf/
│   │   ├── README.md
│   │   ├── fsaf_r101_fpn_1x_coco.py
│   │   ├── fsaf_r50_fpn_1x_coco.py
│   │   └── fsaf_x101_64x4d_fpn_1x_coco.py
│   ├── gcnet/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r16_gcb_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r4_gcb_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py
│   │   ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_r16_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_r4_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_syncbn-backbone_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_r16_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_r4_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py
│   │   └── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py
│   ├── gfl/
│   │   ├── README.md
│   │   ├── gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco.py
│   │   ├── gfl_r101_fpn_mstrain_2x_coco.py
│   │   ├── gfl_r50_fpn_1x_coco.py
│   │   ├── gfl_r50_fpn_mstrain_2x_coco.py
│   │   ├── gfl_x101_32x4d_fpn_dconv_c4-c5_mstrain_2x_coco.py
│   │   └── gfl_x101_32x4d_fpn_mstrain_2x_coco.py
│   ├── ghm/
│   │   ├── README.md
│   │   ├── retinanet_ghm_r101_fpn_1x_coco.py
│   │   ├── retinanet_ghm_r50_fpn_1x_coco.py
│   │   ├── retinanet_ghm_x101_32x4d_fpn_1x_coco.py
│   │   └── retinanet_ghm_x101_64x4d_fpn_1x_coco.py
│   ├── gn/
│   │   ├── README.md
│   │   ├── mask_rcnn_r101_fpn_gn-all_2x_coco.py
│   │   ├── mask_rcnn_r101_fpn_gn-all_3x_coco.py
│   │   ├── mask_rcnn_r50_fpn_gn-all_2x_coco.py
│   │   ├── mask_rcnn_r50_fpn_gn-all_3x_coco.py
│   │   ├── mask_rcnn_r50_fpn_gn-all_contrib_2x_coco.py
│   │   └── mask_rcnn_r50_fpn_gn-all_contrib_3x_coco.py
│   ├── gn+ws/
│   │   ├── README.md
│   │   ├── faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py
│   │   ├── faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py
│   │   ├── faster_rcnn_x101_32x4d_fpn_gn_ws-all_1x_coco.py
│   │   ├── faster_rcnn_x50_32x4d_fpn_gn_ws-all_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco.py
│   │   ├── mask_rcnn_r101_fpn_gn_ws-all_2x_coco.py
│   │   ├── mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco.py
│   │   ├── mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco.py
│   │   ├── mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco.py
│   │   └── mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco.py
│   ├── grid_rcnn/
│   │   ├── README.md
│   │   ├── grid_rcnn_r101_fpn_gn-head_2x_coco.py
│   │   ├── grid_rcnn_r50_fpn_gn-head_1x_coco.py
│   │   ├── grid_rcnn_r50_fpn_gn-head_2x_coco.py
│   │   ├── grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py
│   │   └── grid_rcnn_x101_64x4d_fpn_gn-head_2x_coco.py
│   ├── groie/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_groie_1x_coco.py
│   │   ├── grid_rcnn_r50_fpn_gn-head_groie_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_syncbn-backbone_r4_gcb_c3-c5_groie_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_groie_1x_coco.py
│   │   └── mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_groie_1x_coco.py
│   ├── guided_anchoring/
│   │   ├── README.md
│   │   ├── ga_fast_r50_caffe_fpn_1x_coco.py
│   │   ├── ga_faster_r101_caffe_fpn_1x_coco.py
│   │   ├── ga_faster_r50_caffe_fpn_1x_coco.py
│   │   ├── ga_faster_r50_fpn_1x_coco.py
│   │   ├── ga_faster_x101_32x4d_fpn_1x_coco.py
│   │   ├── ga_faster_x101_64x4d_fpn_1x_coco.py
│   │   ├── ga_retinanet_r101_caffe_fpn_1x_coco.py
│   │   ├── ga_retinanet_r101_caffe_fpn_mstrain_2x.py
│   │   ├── ga_retinanet_r50_caffe_fpn_1x_coco.py
│   │   ├── ga_retinanet_r50_fpn_1x_coco.py
│   │   ├── ga_retinanet_x101_32x4d_fpn_1x_coco.py
│   │   ├── ga_retinanet_x101_64x4d_fpn_1x_coco.py
│   │   ├── ga_rpn_r101_caffe_fpn_1x_coco.py
│   │   ├── ga_rpn_r50_caffe_fpn_1x_coco.py
│   │   ├── ga_rpn_r50_fpn_1x_coco.py
│   │   ├── ga_rpn_x101_32x4d_fpn_1x_coco.py
│   │   └── ga_rpn_x101_64x4d_fpn_1x_coco.py
│   ├── hrnet/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_hrnetv2p_w18_20e_coco.py
│   │   ├── cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py
│   │   ├── cascade_mask_rcnn_hrnetv2p_w40_20e_coco.py
│   │   ├── cascade_rcnn_hrnetv2p_w18_20e_coco.py
│   │   ├── cascade_rcnn_hrnetv2p_w32_20e_coco.py
│   │   ├── cascade_rcnn_hrnetv2p_w40_20e_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w18_1x_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w18_2x_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w32_1x_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w32_2x_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w40_1x_coco.py
│   │   ├── faster_rcnn_hrnetv2p_w40_2x_coco.py
│   │   ├── fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py
│   │   ├── fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py
│   │   ├── fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco.py
│   │   ├── fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py
│   │   ├── fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py
│   │   ├── fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py
│   │   ├── fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco.py
│   │   ├── htc_hrnetv2p_w18_20e_coco.py
│   │   ├── htc_hrnetv2p_w32_20e_coco.py
│   │   ├── htc_hrnetv2p_w40_20e_coco.py
│   │   ├── htc_hrnetv2p_w40_28e_coco.py
│   │   ├── htc_x101_64x4d_fpn_16x1_28e_coco.py
│   │   ├── mask_rcnn_hrnetv2p_w18_1x_coco.py
│   │   ├── mask_rcnn_hrnetv2p_w18_2x_coco.py
│   │   ├── mask_rcnn_hrnetv2p_w32_1x_coco.py
│   │   ├── mask_rcnn_hrnetv2p_w32_2x_coco.py
│   │   ├── mask_rcnn_hrnetv2p_w40_1x_coco.py
│   │   └── mask_rcnn_hrnetv2p_w40_2x_coco.py
│   ├── htc/
│   │   ├── README.md
│   │   ├── htc_r101_fpn_20e_coco.py
│   │   ├── htc_r50_fpn_1x_coco.py
│   │   ├── htc_r50_fpn_20e_coco.py
│   │   ├── htc_without_semantic_r50_fpn_1x_coco.py
│   │   ├── htc_x101_32x4d_fpn_16x1_20e_coco.py
│   │   ├── htc_x101_64x4d_fpn_16x1_20e_coco.py
│   │   └── htc_x101_64x4d_fpn_dconv_c3-c5_mstrain_400_1400_16x1_20e_coco.py
│   ├── instaboost/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py
│   │   ├── cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py
│   │   ├── cascade_mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py
│   │   ├── mask_rcnn_r101_fpn_instaboost_4x_coco.py
│   │   ├── mask_rcnn_r50_fpn_instaboost_4x_coco.py
│   │   └── mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py
│   ├── ld/
│   │   ├── README.md
│   │   ├── ld_r101_gflv1_r101dcn_fpn_coco_2x.py
│   │   ├── ld_r18_gflv1_r101_fpn_coco_1x.py
│   │   ├── ld_r34_gflv1_r101_fpn_coco_1x.py
│   │   └── ld_r50_gflv1_r101_fpn_coco_1x.py
│   ├── legacy_1.x/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r50_fpn_1x_coco_v1.py
│   │   ├── faster_rcnn_r50_fpn_1x_coco_v1.py
│   │   ├── mask_rcnn_r50_fpn_1x_coco_v1.py
│   │   ├── retinanet_r50_caffe_fpn_1x_coco_v1.py
│   │   ├── retinanet_r50_fpn_1x_coco_v1.py
│   │   └── ssd300_coco_v1.py
│   ├── libra_rcnn/
│   │   ├── README.md
│   │   ├── libra_fast_rcnn_r50_fpn_1x_coco.py
│   │   ├── libra_faster_rcnn_r101_fpn_1x_coco.py
│   │   ├── libra_faster_rcnn_r50_fpn_1x_coco.py
│   │   ├── libra_faster_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   └── libra_retinanet_r50_fpn_1x_coco.py
│   ├── lvis/
│   │   ├── README.md
│   │   ├── mask_rcnn_r101_fpn_sample1e-3_mstrain_1x_lvis_v1.py
│   │   ├── mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py
│   │   ├── mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py
│   │   ├── mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py
│   │   ├── mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py
│   │   └── mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py
│   ├── mask_rcnn/
│   │   ├── README.md
│   │   ├── mask_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_1x_coco.py
│   │   ├── mask_rcnn_r101_fpn_2x_coco.py
│   │   ├── mask_rcnn_r50_caffe_c4_1x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_mstrain_1x_coco.py
│   │   ├── mask_rcnn_r50_caffe_fpn_poly_1x_coco_v1.py
│   │   ├── mask_rcnn_r50_fpn_1x_coco.py
│   │   ├── mask_rcnn_r50_fpn_2x_coco.py
│   │   ├── mask_rcnn_r50_fpn_poly_1x_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── mask_rcnn_x101_32x4d_fpn_2x_coco.py
│   │   ├── mask_rcnn_x101_32x8d_fpn_1x_coco.py
│   │   ├── mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco.py
│   │   ├── mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco.py
│   │   ├── mask_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   └── mask_rcnn_x101_64x4d_fpn_2x_coco.py
│   ├── ms_rcnn/
│   │   ├── README.md
│   │   ├── ms_rcnn_r101_caffe_fpn_1x_coco.py
│   │   ├── ms_rcnn_r101_caffe_fpn_2x_coco.py
│   │   ├── ms_rcnn_r50_caffe_fpn_1x_coco.py
│   │   ├── ms_rcnn_r50_caffe_fpn_2x_coco.py
│   │   ├── ms_rcnn_r50_fpn_1x_coco.py
│   │   ├── ms_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── ms_rcnn_x101_64x4d_fpn_1x_coco.py
│   │   └── ms_rcnn_x101_64x4d_fpn_2x_coco.py
│   ├── nas_fcos/
│   │   ├── README.md
│   │   ├── nas_fcos_fcoshead_r50_caffe_fpn_gn-head_4x4_1x_coco.py
│   │   └── nas_fcos_nashead_r50_caffe_fpn_gn-head_4x4_1x_coco.py
│   ├── nas_fpn/
│   │   ├── README.md
│   │   ├── retinanet_r50_fpn_crop640_50e_coco.py
│   │   └── retinanet_r50_nasfpn_crop640_50e_coco.py
│   ├── paa/
│   │   ├── README.md
│   │   ├── paa_r101_fpn_1x_coco.py
│   │   ├── paa_r101_fpn_2x_coco.py
│   │   ├── paa_r101_fpn_mstrain_3x_coco.py
│   │   ├── paa_r50_fpn_1.5x_coco.py
│   │   ├── paa_r50_fpn_1x_coco.py
│   │   ├── paa_r50_fpn_2x_coco.py
│   │   └── paa_r50_fpn_mstrain_3x_coco.py
│   ├── pafpn/
│   │   ├── README.md
│   │   └── faster_rcnn_r50_pafpn_1x_coco.py
│   ├── pascal_voc/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_1x_voc0712.py
│   │   ├── faster_rcnn_r50_fpn_1x_voc0712_cocofmt.py
│   │   ├── retinanet_r50_fpn_1x_voc0712.py
│   │   ├── ssd300_voc0712.py
│   │   └── ssd512_voc0712.py
│   ├── pisa/
│   │   ├── README.md
│   │   ├── pisa_faster_rcnn_r50_fpn_1x_coco.py
│   │   ├── pisa_faster_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── pisa_mask_rcnn_r50_fpn_1x_coco.py
│   │   ├── pisa_mask_rcnn_x101_32x4d_fpn_1x_coco.py
│   │   ├── pisa_retinanet_r50_fpn_1x_coco.py
│   │   ├── pisa_retinanet_x101_32x4d_fpn_1x_coco.py
│   │   ├── pisa_ssd300_coco.py
│   │   └── pisa_ssd512_coco.py
│   ├── point_rend/
│   │   ├── README.md
│   │   ├── point_rend_r50_caffe_fpn_mstrain_1x_coco.py
│   │   └── point_rend_r50_caffe_fpn_mstrain_3x_coco.py
│   ├── regnet/
│   │   ├── README.md
│   │   ├── faster_rcnn_regnetx-3.2GF_fpn_1x_coco.py
│   │   ├── faster_rcnn_regnetx-3.2GF_fpn_2x_coco.py
│   │   ├── faster_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py
│   │   ├── mask_rcnn_regnetx-12GF_fpn_1x_coco.py
│   │   ├── mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py
│   │   ├── mask_rcnn_regnetx-3.2GF_fpn_mdconv_c3-c5_1x_coco.py
│   │   ├── mask_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py
│   │   ├── mask_rcnn_regnetx-4GF_fpn_1x_coco.py
│   │   ├── mask_rcnn_regnetx-6.4GF_fpn_1x_coco.py
│   │   ├── mask_rcnn_regnetx-8GF_fpn_1x_coco.py
│   │   ├── retinanet_regnetx-1.6GF_fpn_1x_coco.py
│   │   ├── retinanet_regnetx-3.2GF_fpn_1x_coco.py
│   │   └── retinanet_regnetx-800MF_fpn_1x_coco.py
│   ├── reppoints/
│   │   ├── README.md
│   │   ├── bbox_r50_grid_center_fpn_gn-neck+head_1x_coco.py
│   │   ├── bbox_r50_grid_fpn_gn-neck+head_1x_coco.py
│   │   ├── reppoints_minmax_r50_fpn_gn-neck+head_1x_coco.py
│   │   ├── reppoints_moment_r101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py
│   │   ├── reppoints_moment_r101_fpn_gn-neck+head_2x_coco.py
│   │   ├── reppoints_moment_r50_fpn_1x_coco.py
│   │   ├── reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py
│   │   ├── reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py
│   │   ├── reppoints_moment_x101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py
│   │   └── reppoints_partial_minmax_r50_fpn_gn-neck+head_1x_coco.py
│   ├── res2net/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_r2_101_fpn_20e_coco.py
│   │   ├── cascade_rcnn_r2_101_fpn_20e_coco.py
│   │   ├── faster_rcnn_r2_101_fpn_2x_coco.py
│   │   ├── htc_r2_101_fpn_20e_coco.py
│   │   └── mask_rcnn_r2_101_fpn_2x_coco.py
│   ├── resnest/
│   │   ├── README.md
│   │   ├── cascade_mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py
│   │   ├── cascade_mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py
│   │   ├── cascade_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py
│   │   ├── cascade_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py
│   │   ├── faster_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py
│   │   ├── faster_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py
│   │   ├── mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py
│   │   └── mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py
│   ├── retinanet/
│   │   ├── README.md
│   │   ├── retinanet_r101_caffe_fpn_1x_coco.py
│   │   ├── retinanet_r101_fpn_1x_coco.py
│   │   ├── retinanet_r101_fpn_2x_coco.py
│   │   ├── retinanet_r50_caffe_fpn_1x_coco.py
│   │   ├── retinanet_r50_caffe_fpn_mstrain_1x_coco.py
│   │   ├── retinanet_r50_caffe_fpn_mstrain_2x_coco.py
│   │   ├── retinanet_r50_caffe_fpn_mstrain_3x_coco.py
│   │   ├── retinanet_r50_fpn_1x_coco.py
│   │   ├── retinanet_r50_fpn_2x_coco.py
│   │   ├── retinanet_x101_32x4d_fpn_1x_coco.py
│   │   ├── retinanet_x101_32x4d_fpn_2x_coco.py
│   │   ├── retinanet_x101_64x4d_fpn_1x_coco.py
│   │   └── retinanet_x101_64x4d_fpn_2x_coco.py
│   ├── rpn/
│   │   ├── README.md
│   │   ├── rpn_r101_caffe_fpn_1x_coco.py
│   │   ├── rpn_r101_fpn_1x_coco.py
│   │   ├── rpn_r101_fpn_2x_coco.py
│   │   ├── rpn_r50_caffe_c4_1x_coco.py
│   │   ├── rpn_r50_caffe_fpn_1x_coco.py
│   │   ├── rpn_r50_fpn_1x_coco.py
│   │   ├── rpn_r50_fpn_2x_coco.py
│   │   ├── rpn_x101_32x4d_fpn_1x_coco.py
│   │   ├── rpn_x101_32x4d_fpn_2x_coco.py
│   │   ├── rpn_x101_64x4d_fpn_1x_coco.py
│   │   └── rpn_x101_64x4d_fpn_2x_coco.py
│   ├── sabl/
│   │   ├── README.md
│   │   ├── sabl_cascade_rcnn_r101_fpn_1x_coco.py
│   │   ├── sabl_cascade_rcnn_r50_fpn_1x_coco.py
│   │   ├── sabl_faster_rcnn_r101_fpn_1x_coco.py
│   │   ├── sabl_faster_rcnn_r50_fpn_1x_coco.py
│   │   ├── sabl_retinanet_r101_fpn_1x_coco.py
│   │   ├── sabl_retinanet_r101_fpn_gn_1x_coco.py
│   │   ├── sabl_retinanet_r101_fpn_gn_2x_ms_480_960_coco.py
│   │   ├── sabl_retinanet_r101_fpn_gn_2x_ms_640_800_coco.py
│   │   ├── sabl_retinanet_r50_fpn_1x_coco.py
│   │   └── sabl_retinanet_r50_fpn_gn_1x_coco.py
│   ├── scnet/
│   │   ├── README.md
│   │   ├── scnet_r101_fpn_20e_coco.py
│   │   ├── scnet_r50_fpn_1x_coco.py
│   │   ├── scnet_r50_fpn_20e_coco.py
│   │   ├── scnet_x101_64x4d_fpn_20e_coco.py
│   │   └── scnet_x101_64x4d_fpn_8x1_20e_coco.py
│   ├── scratch/
│   │   ├── README.md
│   │   ├── faster_rcnn_r50_fpn_gn-all_scratch_6x_coco.py
│   │   └── mask_rcnn_r50_fpn_gn-all_scratch_6x_coco.py
│   ├── sparse_rcnn/
│   │   ├── README.md
│   │   ├── sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py
│   │   ├── sparse_rcnn_r101_fpn_mstrain_480-800_3x_coco.py
│   │   ├── sparse_rcnn_r50_fpn_1x_coco.py
│   │   ├── sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py
│   │   └── sparse_rcnn_r50_fpn_mstrain_480-800_3x_coco.py
│   ├── ssd/
│   │   ├── README.md
│   │   ├── ssd300_coco.py
│   │   └── ssd512_coco.py
│   ├── tridentnet/
│   │   ├── README.md
│   │   ├── tridentnet_r50_caffe_1x_coco.py
│   │   ├── tridentnet_r50_caffe_mstrain_1x_coco.py
│   │   └── tridentnet_r50_caffe_mstrain_3x_coco.py
│   ├── vfnet/
│   │   ├── README.md
│   │   ├── vfnet_r101_fpn_1x_coco.py
│   │   ├── vfnet_r101_fpn_2x_coco.py
│   │   ├── vfnet_r101_fpn_mdconv_c3-c5_mstrain_2x_coco.py
│   │   ├── vfnet_r101_fpn_mstrain_2x_coco.py
│   │   ├── vfnet_r2_101_fpn_mdconv_c3-c5_mstrain_2x_coco.py
│   │   ├── vfnet_r2_101_fpn_mstrain_2x_coco.py
│   │   ├── vfnet_r50_fpn_1x_coco.py
│   │   ├── vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco.py
│   │   ├── vfnet_r50_fpn_mstrain_2x_coco.py
│   │   ├── vfnet_x101_32x4d_fpn_mdconv_c3-c5_mstrain_2x_coco.py
│   │   ├── vfnet_x101_32x4d_fpn_mstrain_2x_coco.py
│   │   ├── vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco.py
│   │   └── vfnet_x101_64x4d_fpn_mstrain_2x_coco.py
│   ├── wider_face/
│   │   ├── README.md
│   │   └── ssd300_wider_face.py
│   ├── yolact/
│   │   ├── README.md
│   │   ├── yolact_r101_1x8_coco.py
│   │   ├── yolact_r50_1x8_coco.py
│   │   └── yolact_r50_8x8_coco.py
│   ├── yolo/
│   │   ├── README.md
│   │   ├── yolov3_d53_320_273e_coco.py
│   │   ├── yolov3_d53_mstrain-416_273e_coco.py
│   │   └── yolov3_d53_mstrain-608_273e_coco.py
│   └── yolof/
│       ├── README.md
│       ├── yolof_r50_c5_8x8_1x_coco.py
│       └── yolof_r50_c5_8x8_iter-1x_coco.py
├── demo/
│   ├── MMDet_Tutorial.ipynb
│   ├── create_result_gif.py
│   ├── image_demo.py
│   ├── inference_demo.ipynb
│   ├── video_demo.py
│   └── webcam_demo.py
├── demo.py
├── docker/
│   ├── Dockerfile
│   └── serve/
│       ├── Dockerfile
│       ├── config.properties
│       └── entrypoint.sh
├── docs/
│   ├── 1_exist_data_model.md
│   ├── 2_new_data_model.md
│   ├── 3_exist_data_new_model.md
│   ├── Makefile
│   ├── api.rst
│   ├── changelog.md
│   ├── compatibility.md
│   ├── conf.py
│   ├── conventions.md
│   ├── faq.md
│   ├── get_started.md
│   ├── index.rst
│   ├── make.bat
│   ├── model_zoo.md
│   ├── projects.md
│   ├── robustness_benchmarking.md
│   ├── stat.py
│   ├── tutorials/
│   │   ├── config.md
│   │   ├── customize_dataset.md
│   │   ├── customize_losses.md
│   │   ├── customize_models.md
│   │   ├── customize_runtime.md
│   │   ├── data_pipeline.md
│   │   ├── finetune.md
│   │   ├── index.rst
│   │   ├── onnx2tensorrt.md
│   │   └── pytorch2onnx.md
│   └── useful_tools.md
├── mmdet/
│   ├── __init__.py
│   ├── apis/
│   │   ├── __init__.py
│   │   ├── inference.py
│   │   ├── test.py
│   │   └── train.py
│   ├── core/
│   │   ├── __init__.py
│   │   ├── anchor/
│   │   │   ├── __init__.py
│   │   │   ├── anchor_generator.py
│   │   │   ├── builder.py
│   │   │   ├── point_generator.py
│   │   │   └── utils.py
│   │   ├── bbox/
│   │   │   ├── __init__.py
│   │   │   ├── assigners/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── approx_max_iou_assigner.py
│   │   │   │   ├── assign_result.py
│   │   │   │   ├── atss_assigner.py
│   │   │   │   ├── base_assigner.py
│   │   │   │   ├── center_region_assigner.py
│   │   │   │   ├── grid_assigner.py
│   │   │   │   ├── hungarian_assigner.py
│   │   │   │   ├── max_iou_assigner.py
│   │   │   │   ├── point_assigner.py
│   │   │   │   ├── region_assigner.py
│   │   │   │   └── uniform_assigner.py
│   │   │   ├── builder.py
│   │   │   ├── coder/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_bbox_coder.py
│   │   │   │   ├── bucketing_bbox_coder.py
│   │   │   │   ├── delta_xywh_bbox_coder.py
│   │   │   │   ├── legacy_delta_xywh_bbox_coder.py
│   │   │   │   ├── pseudo_bbox_coder.py
│   │   │   │   ├── tblr_bbox_coder.py
│   │   │   │   └── yolo_bbox_coder.py
│   │   │   ├── demodata.py
│   │   │   ├── iou_calculators/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── builder.py
│   │   │   │   └── iou2d_calculator.py
│   │   │   ├── match_costs/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── builder.py
│   │   │   │   └── match_cost.py
│   │   │   ├── samplers/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_sampler.py
│   │   │   │   ├── combined_sampler.py
│   │   │   │   ├── instance_balanced_pos_sampler.py
│   │   │   │   ├── iou_balanced_neg_sampler.py
│   │   │   │   ├── ohem_sampler.py
│   │   │   │   ├── pseudo_sampler.py
│   │   │   │   ├── random_sampler.py
│   │   │   │   ├── sampling_result.py
│   │   │   │   └── score_hlr_sampler.py
│   │   │   └── transforms.py
│   │   ├── evaluation/
│   │   │   ├── __init__.py
│   │   │   ├── bbox_overlaps.py
│   │   │   ├── class_names.py
│   │   │   ├── eval_hooks.py
│   │   │   ├── mean_ap.py
│   │   │   └── recall.py
│   │   ├── export/
│   │   │   ├── __init__.py
│   │   │   ├── model_wrappers.py
│   │   │   ├── onnx_helper.py
│   │   │   └── pytorch2onnx.py
│   │   ├── mask/
│   │   │   ├── __init__.py
│   │   │   ├── mask_target.py
│   │   │   ├── structures.py
│   │   │   └── utils.py
│   │   ├── post_processing/
│   │   │   ├── __init__.py
│   │   │   ├── bbox_nms.py
│   │   │   └── merge_augs.py
│   │   ├── utils/
│   │   │   ├── __init__.py
│   │   │   ├── dist_utils.py
│   │   │   └── misc.py
│   │   └── visualization/
│   │       ├── __init__.py
│   │       └── image.py
│   ├── datasets/
│   │   ├── __init__.py
│   │   ├── api_wrappers/
│   │   │   ├── __init__.py
│   │   │   └── coco_api.py
│   │   ├── builder.py
│   │   ├── cityscapes.py
│   │   ├── coco.py
│   │   ├── custom.py
│   │   ├── dataset_wrappers.py
│   │   ├── deepfashion.py
│   │   ├── lvis.py
│   │   ├── pipelines/
│   │   │   ├── __init__.py
│   │   │   ├── auto_augment.py
│   │   │   ├── compose.py
│   │   │   ├── formating.py
│   │   │   ├── instaboost.py
│   │   │   ├── loading.py
│   │   │   ├── test_time_aug.py
│   │   │   └── transforms.py
│   │   ├── samplers/
│   │   │   ├── __init__.py
│   │   │   ├── distributed_sampler.py
│   │   │   └── group_sampler.py
│   │   ├── utils.py
│   │   ├── voc.py
│   │   ├── wider_face.py
│   │   └── xml_style.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── backbones/
│   │   │   ├── __init__.py
│   │   │   ├── darknet.py
│   │   │   ├── detectors_resnet.py
│   │   │   ├── detectors_resnext.py
│   │   │   ├── hourglass.py
│   │   │   ├── hrnet.py
│   │   │   ├── regnet.py
│   │   │   ├── res2net.py
│   │   │   ├── resnest.py
│   │   │   ├── resnet.py
│   │   │   ├── resnext.py
│   │   │   ├── ssd_vgg.py
│   │   │   ├── swin.py
│   │   │   └── trident_resnet.py
│   │   ├── builder.py
│   │   ├── dense_heads/
│   │   │   ├── __init__.py
│   │   │   ├── anchor_free_head.py
│   │   │   ├── anchor_head.py
│   │   │   ├── atss_head.py
│   │   │   ├── autoassign_head.py
│   │   │   ├── base_dense_head.py
│   │   │   ├── cascade_rpn_head.py
│   │   │   ├── centripetal_head.py
│   │   │   ├── corner_head.py
│   │   │   ├── deformable_detr_head.py
│   │   │   ├── dense_test_mixins.py
│   │   │   ├── detr_head.py
│   │   │   ├── embedding_rpn_head.py
│   │   │   ├── fcos_head.py
│   │   │   ├── fovea_head.py
│   │   │   ├── free_anchor_retina_head.py
│   │   │   ├── fsaf_head.py
│   │   │   ├── ga_retina_head.py
│   │   │   ├── ga_rpn_head.py
│   │   │   ├── gfl_head.py
│   │   │   ├── guided_anchor_head.py
│   │   │   ├── ld_head.py
│   │   │   ├── nasfcos_head.py
│   │   │   ├── paa_head.py
│   │   │   ├── pisa_retinanet_head.py
│   │   │   ├── pisa_ssd_head.py
│   │   │   ├── query_generator.py
│   │   │   ├── reppoints_head.py
│   │   │   ├── retina_head.py
│   │   │   ├── retina_sepbn_head.py
│   │   │   ├── rpn_head.py
│   │   │   ├── rpn_test_mixin.py
│   │   │   ├── sabl_retina_head.py
│   │   │   ├── ssd_head.py
│   │   │   ├── vfnet_head.py
│   │   │   ├── yolact_head.py
│   │   │   ├── yolo_head.py
│   │   │   └── yolof_head.py
│   │   ├── detectors/
│   │   │   ├── __init__.py
│   │   │   ├── atss.py
│   │   │   ├── autoassign.py
│   │   │   ├── base.py
│   │   │   ├── cascade_rcnn.py
│   │   │   ├── cornernet.py
│   │   │   ├── deformable_detr.py
│   │   │   ├── detr.py
│   │   │   ├── fast_rcnn.py
│   │   │   ├── faster_rcnn.py
│   │   │   ├── fcos.py
│   │   │   ├── fovea.py
│   │   │   ├── fsaf.py
│   │   │   ├── gfl.py
│   │   │   ├── grid_rcnn.py
│   │   │   ├── htc.py
│   │   │   ├── kd_one_stage.py
│   │   │   ├── mask_rcnn.py
│   │   │   ├── mask_scoring_rcnn.py
│   │   │   ├── nasfcos.py
│   │   │   ├── paa.py
│   │   │   ├── point_rend.py
│   │   │   ├── query_based.py
│   │   │   ├── reppoints_detector.py
│   │   │   ├── retinanet.py
│   │   │   ├── rpn.py
│   │   │   ├── scnet.py
│   │   │   ├── single_stage.py
│   │   │   ├── sparse_rcnn.py
│   │   │   ├── trident_faster_rcnn.py
│   │   │   ├── two_stage.py
│   │   │   ├── vfnet.py
│   │   │   ├── yolact.py
│   │   │   ├── yolo.py
│   │   │   └── yolof.py
│   │   ├── losses/
│   │   │   ├── __init__.py
│   │   │   ├── accuracy.py
│   │   │   ├── ae_loss.py
│   │   │   ├── balanced_l1_loss.py
│   │   │   ├── cross_entropy_loss.py
│   │   │   ├── focal_loss.py
│   │   │   ├── gaussian_focal_loss.py
│   │   │   ├── gfocal_loss.py
│   │   │   ├── ghm_loss.py
│   │   │   ├── iou_loss.py
│   │   │   ├── kd_loss.py
│   │   │   ├── mse_loss.py
│   │   │   ├── pisa_loss.py
│   │   │   ├── smooth_l1_loss.py
│   │   │   ├── utils.py
│   │   │   └── varifocal_loss.py
│   │   ├── necks/
│   │   │   ├── __init__.py
│   │   │   ├── bfp.py
│   │   │   ├── channel_mapper.py
│   │   │   ├── dilated_encoder.py
│   │   │   ├── fpg.py
│   │   │   ├── fpn.py
│   │   │   ├── fpn_carafe.py
│   │   │   ├── hrfpn.py
│   │   │   ├── identity_fpn.py
│   │   │   ├── nas_fpn.py
│   │   │   ├── nasfcos_fpn.py
│   │   │   ├── pafpn.py
│   │   │   ├── rfp.py
│   │   │   └── yolo_neck.py
│   │   ├── roi_heads/
│   │   │   ├── __init__.py
│   │   │   ├── adamixer_decoder.py
│   │   │   ├── base_roi_head.py
│   │   │   ├── bbox_heads/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── adamixer_decoder_stage.py
│   │   │   │   ├── adaptive_mixing_operator.py
│   │   │   │   ├── bbox_head.py
│   │   │   │   ├── convfc_bbox_head.py
│   │   │   │   ├── dii_head.py
│   │   │   │   ├── double_bbox_head.py
│   │   │   │   ├── sabl_head.py
│   │   │   │   ├── sampling_3d_operator.py
│   │   │   │   └── scnet_bbox_head.py
│   │   │   ├── cascade_roi_head.py
│   │   │   ├── double_roi_head.py
│   │   │   ├── dynamic_roi_head.py
│   │   │   ├── grid_roi_head.py
│   │   │   ├── htc_roi_head.py
│   │   │   ├── mask_heads/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── coarse_mask_head.py
│   │   │   │   ├── fcn_mask_head.py
│   │   │   │   ├── feature_relay_head.py
│   │   │   │   ├── fused_semantic_head.py
│   │   │   │   ├── global_context_head.py
│   │   │   │   ├── grid_head.py
│   │   │   │   ├── htc_mask_head.py
│   │   │   │   ├── mask_point_head.py
│   │   │   │   ├── maskiou_head.py
│   │   │   │   ├── scnet_mask_head.py
│   │   │   │   └── scnet_semantic_head.py
│   │   │   ├── mask_scoring_roi_head.py
│   │   │   ├── pisa_roi_head.py
│   │   │   ├── point_rend_roi_head.py
│   │   │   ├── roi_extractors/
│   │   │   │   ├── __init__.py
│   │   │   │   ├── base_roi_extractor.py
│   │   │   │   ├── generic_roi_extractor.py
│   │   │   │   └── single_level_roi_extractor.py
│   │   │   ├── scnet_roi_head.py
│   │   │   ├── shared_heads/
│   │   │   │   ├── __init__.py
│   │   │   │   └── res_layer.py
│   │   │   ├── sparse_roi_head.py
│   │   │   ├── standard_roi_head.py
│   │   │   ├── test_mixins.py
│   │   │   └── trident_roi_head.py
│   │   └── utils/
│   │       ├── __init__.py
│   │       ├── builder.py
│   │       ├── gaussian_target.py
│   │       ├── positional_encoding.py
│   │       ├── res_layer.py
│   │       └── transformer.py
│   ├── temp.txt
│   ├── utils/
│   │   ├── __init__.py
│   │   ├── collect_env.py
│   │   ├── contextmanagers.py
│   │   ├── logger.py
│   │   ├── profiling.py
│   │   ├── util_mixins.py
│   │   └── util_random.py
│   └── version.py
├── pytest.ini
├── requirements/
│   ├── build.txt
│   ├── docs.txt
│   ├── optional.txt
│   ├── readthedocs.txt
│   ├── runtime.txt
│   └── tests.txt
├── requirements.txt
├── setup.cfg
├── setup.py
├── test_module.py
├── tests/
│   ├── test_data/
│   │   ├── test_datasets/
│   │   │   ├── test_coco_dataset.py
│   │   │   ├── test_common.py
│   │   │   ├── test_custom_dataset.py
│   │   │   ├── test_dataset_wrapper.py
│   │   │   └── test_xml_dataset.py
│   │   ├── test_pipelines/
│   │   │   ├── test_formatting.py
│   │   │   ├── test_loading.py
│   │   │   ├── test_sampler.py
│   │   │   └── test_transform/
│   │   │       ├── test_img_augment.py
│   │   │       ├── test_models_aug_test.py
│   │   │       ├── test_rotate.py
│   │   │       ├── test_shear.py
│   │   │       ├── test_transform.py
│   │   │       └── test_translate.py
│   │   └── test_utils.py
│   ├── test_metrics/
│   │   ├── test_box_overlap.py
│   │   └── test_losses.py
│   ├── test_models/
│   │   ├── test_backbones/
│   │   │   ├── __init__.py
│   │   │   ├── test_hourglass.py
│   │   │   ├── test_regnet.py
│   │   │   ├── test_renext.py
│   │   │   ├── test_res2net.py
│   │   │   ├── test_resnest.py
│   │   │   ├── test_resnet.py
│   │   │   ├── test_trident_resnet.py
│   │   │   └── utils.py
│   │   ├── test_dense_heads/
│   │   │   ├── test_anchor_head.py
│   │   │   ├── test_atss_head.py
│   │   │   ├── test_autoassign_head.py
│   │   │   ├── test_corner_head.py
│   │   │   ├── test_detr_head.py
│   │   │   ├── test_fcos_head.py
│   │   │   ├── test_fsaf_head.py
│   │   │   ├── test_ga_anchor_head.py
│   │   │   ├── test_gfl_head.py
│   │   │   ├── test_ld_head.py
│   │   │   ├── test_paa_head.py
│   │   │   ├── test_pisa_head.py
│   │   │   ├── test_sabl_retina_head.py
│   │   │   ├── test_vfnet_head.py
│   │   │   ├── test_yolact_head.py
│   │   │   └── test_yolof_head.py
│   │   ├── test_forward.py
│   │   ├── test_loss.py
│   │   ├── test_necks.py
│   │   ├── test_roi_heads/
│   │   │   ├── __init__.py
│   │   │   ├── test_bbox_head.py
│   │   │   ├── test_mask_head.py
│   │   │   ├── test_roi_extractor.py
│   │   │   ├── test_sabl_bbox_head.py
│   │   │   └── utils.py
│   │   └── test_utils/
│   │       ├── test_position_encoding.py
│   │       └── test_transformer.py
│   ├── test_onnx/
│   │   ├── __init__.py
│   │   ├── test_head.py
│   │   ├── test_neck.py
│   │   └── utils.py
│   ├── test_runtime/
│   │   ├── async_benchmark.py
│   │   ├── test_async.py
│   │   ├── test_config.py
│   │   ├── test_eval_hook.py
│   │   └── test_fp16.py
│   └── test_utils/
│       ├── test_anchor.py
│       ├── test_assigner.py
│       ├── test_coder.py
│       ├── test_masks.py
│       ├── test_misc.py
│       ├── test_version.py
│       └── test_visualization.py
├── tools/
│   ├── analysis_tools/
│   │   ├── analyze_logs.py
│   │   ├── analyze_results.py
│   │   ├── benchmark.py
│   │   ├── coco_error_analysis.py
│   │   ├── eval_metric.py
│   │   ├── get_flops.py
│   │   ├── robustness_eval.py
│   │   └── test_robustness.py
│   ├── dataset_converters/
│   │   ├── cityscapes.py
│   │   └── pascal_voc.py
│   ├── deployment/
│   │   ├── mmdet2torchserve.py
│   │   ├── mmdet_handler.py
│   │   ├── onnx2tensorrt.py
│   │   ├── pytorch2onnx.py
│   │   └── test.py
│   ├── dist_test.sh
│   ├── dist_train.sh
│   ├── misc/
│   │   ├── browse_dataset.py
│   │   └── print_config.py
│   ├── model_converters/
│   │   ├── detectron2pytorch.py
│   │   ├── publish_model.py
│   │   ├── regnet2mmdet.py
│   │   └── upgrade_model_version.py
│   ├── slurm_test.sh
│   ├── slurm_train.sh
│   ├── test.py
│   └── train.py
├── visualizations/
│   └── README.md
└── visualize_sampling_points.ipynb

SYMBOL INDEX (2194 symbols across 339 files)

FILE: configs/adamixer/adamixer_r50_1x_coco.py
  function __get_debug (line 1) | def __get_debug():
  function __date (line 185) | def __date():

FILE: demo/create_result_gif.py
  function parse_args (line 16) | def parse_args():
  function _generate_batch_data (line 31) | def _generate_batch_data(sampler, batch_size):
  function create_gif (line 42) | def create_gif(frames, gif_name, duration=2):
  function create_frame_by_matplotlib (line 57) | def create_frame_by_matplotlib(image_dir,
  function main (line 155) | def main():

FILE: demo/image_demo.py
  function parse_args (line 8) | def parse_args():
  function main (line 25) | def main(args):
  function async_main (line 34) | async def async_main(args):

FILE: demo/video_demo.py
  function parse_args (line 9) | def parse_args():
  function main (line 29) | def main():

FILE: demo/webcam_demo.py
  function parse_args (line 9) | def parse_args():
  function main (line 23) | def main():

FILE: docs/conf.py
  function get_version (line 27) | def get_version():
  function builder_inited_handler (line 85) | def builder_inited_handler(app):
  function setup (line 89) | def setup(app):

FILE: mmdet/__init__.py
  function digit_version (line 6) | def digit_version(version_str):

FILE: mmdet/apis/inference.py
  function init_detector (line 16) | def init_detector(config, checkpoint=None, device='cuda:0', cfg_options=...
  class LoadImage (line 62) | class LoadImage(object):
    method __call__ (line 68) | def __call__(self, results):
  function inference_detector (line 95) | def inference_detector(model, imgs):
  function async_inference_detector (line 161) | async def async_inference_detector(model, imgs):
  function show_result_pyplot (line 218) | def show_result_pyplot(model,

FILE: mmdet/apis/test.py
  function single_gpu_test (line 16) | def single_gpu_test(model,
  function multi_gpu_test (line 69) | def multi_gpu_test(model, data_loader, tmpdir=None, gpu_collect=False):
  function collect_results_cpu (line 117) | def collect_results_cpu(result_part, size, tmpdir=None):
  function collect_results_gpu (line 160) | def collect_results_gpu(result_part, size):

FILE: mmdet/apis/train.py
  function set_random_seed (line 18) | def set_random_seed(seed, deterministic=False):
  function train_detector (line 37) | def train_detector(model,

FILE: mmdet/core/anchor/anchor_generator.py
  class AnchorGenerator (line 10) | class AnchorGenerator(object):
    method __init__ (line 58) | def __init__(self,
    method num_base_anchors (line 113) | def num_base_anchors(self):
    method num_levels (line 118) | def num_levels(self):
    method gen_base_anchors (line 122) | def gen_base_anchors(self):
    method gen_single_level_base_anchors (line 142) | def gen_single_level_base_anchors(self,
    method _meshgrid (line 187) | def _meshgrid(self, x, y, row_major=True):
    method grid_anchors (line 207) | def grid_anchors(self, featmap_sizes, device='cuda'):
    method single_level_grid_anchors (line 233) | def single_level_grid_anchors(self,
    method valid_flags (line 272) | def valid_flags(self, featmap_sizes, pad_shape, device='cuda'):
    method single_level_valid_flags (line 299) | def single_level_valid_flags(self,
    method __repr__ (line 330) | def __repr__(self):
  class SSDAnchorGenerator (line 350) | class SSDAnchorGenerator(AnchorGenerator):
    method __init__ (line 366) | def __init__(self,
    method gen_base_anchors (line 435) | def gen_base_anchors(self):
    method __repr__ (line 456) | def __repr__(self):
  class LegacyAnchorGenerator (line 474) | class LegacyAnchorGenerator(AnchorGenerator):
    method gen_single_level_base_anchors (line 522) | def gen_single_level_base_anchors(self,
  class LegacySSDAnchorGenerator (line 573) | class LegacySSDAnchorGenerator(SSDAnchorGenerator, LegacyAnchorGenerator):
    method __init__ (line 580) | def __init__(self,
  class YOLOAnchorGenerator (line 595) | class YOLOAnchorGenerator(AnchorGenerator):
    method __init__ (line 605) | def __init__(self, strides, base_sizes):
    method num_levels (line 618) | def num_levels(self):
    method gen_base_anchors (line 622) | def gen_base_anchors(self):
    method gen_single_level_base_anchors (line 639) | def gen_single_level_base_anchors(self, base_sizes_per_level, center=N...
    method responsible_flags (line 667) | def responsible_flags(self, featmap_sizes, gt_bboxes, device='cuda'):
    method single_level_responsible_flags (line 692) | def single_level_responsible_flags(self,

FILE: mmdet/core/anchor/builder.py
  function build_anchor_generator (line 6) | def build_anchor_generator(cfg, default_args=None):

FILE: mmdet/core/anchor/point_generator.py
  class PointGenerator (line 7) | class PointGenerator(object):
    method _meshgrid (line 9) | def _meshgrid(self, x, y, row_major=True):
    method grid_points (line 17) | def grid_points(self, featmap_size, stride=16, device='cuda'):
    method valid_flags (line 27) | def valid_flags(self, featmap_size, valid_size, device='cuda'):

FILE: mmdet/core/anchor/utils.py
  function images_to_levels (line 4) | def images_to_levels(target, num_levels):
  function anchor_inside_flags (line 20) | def anchor_inside_flags(flat_anchors,
  function calc_region (line 49) | def calc_region(bbox, ratio, featmap_size=None):

FILE: mmdet/core/bbox/assigners/approx_max_iou_assigner.py
  class ApproxMaxIoUAssigner (line 9) | class ApproxMaxIoUAssigner(MaxIoUAssigner):
    method __init__ (line 39) | def __init__(self,
    method assign (line 59) | def assign(self,

FILE: mmdet/core/bbox/assigners/assign_result.py
  class AssignResult (line 6) | class AssignResult(util_mixins.NiceRepr):
    method __init__ (line 42) | def __init__(self, num_gts, gt_inds, max_overlaps, labels=None):
    method num_preds (line 51) | def num_preds(self):
    method set_extra_property (line 55) | def set_extra_property(self, key, value):
    method get_extra_property (line 60) | def get_extra_property(self, key):
    method info (line 65) | def info(self):
    method __nice__ (line 77) | def __nice__(self):
    method random (line 97) | def random(cls, **kwargs):
    method add_gt_ (line 190) | def add_gt_(self, gt_labels):

FILE: mmdet/core/bbox/assigners/atss_assigner.py
  class ATSSAssigner (line 10) | class ATSSAssigner(BaseAssigner):
    method __init__ (line 23) | def __init__(self,
    method assign (line 33) | def assign(self,

FILE: mmdet/core/bbox/assigners/base_assigner.py
  class BaseAssigner (line 4) | class BaseAssigner(metaclass=ABCMeta):
    method assign (line 8) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...

FILE: mmdet/core/bbox/assigners/center_region_assigner.py
  function scale_boxes (line 9) | def scale_boxes(bboxes, scale):
  function is_located_in (line 36) | def is_located_in(points, bboxes):
  function bboxes_area (line 54) | def bboxes_area(bboxes):
  class CenterRegionAssigner (line 71) | class CenterRegionAssigner(BaseAssigner):
    method __init__ (line 93) | def __init__(self,
    method get_gt_priorities (line 107) | def get_gt_priorities(self, gt_bboxes):
    method assign (line 125) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...
    method assign_one_hot_gt_indices (line 256) | def assign_one_hot_gt_indices(self,

FILE: mmdet/core/bbox/assigners/grid_assigner.py
  class GridAssigner (line 10) | class GridAssigner(BaseAssigner):
    method __init__ (line 30) | def __init__(self,
    method assign (line 42) | def assign(self, bboxes, box_responsible_flags, gt_bboxes, gt_labels=N...

FILE: mmdet/core/bbox/assigners/hungarian_assigner.py
  class HungarianAssigner (line 16) | class HungarianAssigner(BaseAssigner):
    method __init__ (line 44) | def __init__(self,
    method assign (line 52) | def assign(self,

FILE: mmdet/core/bbox/assigners/max_iou_assigner.py
  class MaxIoUAssigner (line 10) | class MaxIoUAssigner(BaseAssigner):
    method __init__ (line 40) | def __init__(self,
    method assign (line 60) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...
    method assign_wrt_overlaps (line 127) | def assign_wrt_overlaps(self, overlaps, gt_labels=None):

FILE: mmdet/core/bbox/assigners/point_assigner.py
  class PointAssigner (line 9) | class PointAssigner(BaseAssigner):
    method __init__ (line 19) | def __init__(self, scale=4, pos_num=3):
    method assign (line 23) | def assign(self, points, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...

FILE: mmdet/core/bbox/assigners/region_assigner.py
  function calc_region (line 9) | def calc_region(bbox, ratio, stride, featmap_size=None):
  function anchor_ctr_inside_region_flags (line 26) | def anchor_ctr_inside_region_flags(anchors, stride, region):
  class RegionAssigner (line 37) | class RegionAssigner(BaseAssigner):
    method __init__ (line 53) | def __init__(self, center_ratio=0.2, ignore_ratio=0.5):
    method assign (line 57) | def assign(self,

FILE: mmdet/core/bbox/assigners/uniform_assigner.py
  class UniformAssigner (line 11) | class UniformAssigner(BaseAssigner):
    method __init__ (line 24) | def __init__(self,
    method assign (line 34) | def assign(self,

FILE: mmdet/core/bbox/builder.py
  function build_assigner (line 8) | def build_assigner(cfg, **default_args):
  function build_sampler (line 13) | def build_sampler(cfg, **default_args):
  function build_bbox_coder (line 18) | def build_bbox_coder(cfg, **default_args):

FILE: mmdet/core/bbox/coder/base_bbox_coder.py
  class BaseBBoxCoder (line 4) | class BaseBBoxCoder(metaclass=ABCMeta):
    method __init__ (line 7) | def __init__(self, **kwargs):
    method encode (line 11) | def encode(self, bboxes, gt_bboxes):
    method decode (line 15) | def decode(self, bboxes, bboxes_pred):

FILE: mmdet/core/bbox/coder/bucketing_bbox_coder.py
  class BucketingBBoxCoder (line 12) | class BucketingBBoxCoder(BaseBBoxCoder):
    method __init__ (line 34) | def __init__(self,
    method encode (line 49) | def encode(self, bboxes, gt_bboxes):
    method decode (line 71) | def decode(self, bboxes, pred_bboxes, max_shape=None):
  function generat_buckets (line 95) | def generat_buckets(proposals, num_buckets, scale_factor=1.0):
  function bbox2bucket (line 144) | def bbox2bucket(proposals,
  function bucket2bbox (line 268) | def bucket2bbox(proposals,

FILE: mmdet/core/bbox/coder/delta_xywh_bbox_coder.py
  class DeltaXYWHBBoxCoder (line 10) | class DeltaXYWHBBoxCoder(BaseBBoxCoder):
    method __init__ (line 31) | def __init__(self,
    method encode (line 44) | def encode(self, bboxes, gt_bboxes):
    method decode (line 62) | def decode(self,
  function bbox2delta (line 98) | def bbox2delta(proposals, gt, means=(0., 0., 0., 0.), stds=(1., 1., 1., ...
  function delta2bbox (line 144) | def delta2bbox(rois,

FILE: mmdet/core/bbox/coder/legacy_delta_xywh_bbox_coder.py
  class LegacyDeltaXYWHBBoxCoder (line 10) | class LegacyDeltaXYWHBBoxCoder(BaseBBoxCoder):
    method __init__ (line 33) | def __init__(self,
    method encode (line 40) | def encode(self, bboxes, gt_bboxes):
    method decode (line 58) | def decode(self,
  function legacy_bbox2delta (line 84) | def legacy_bbox2delta(proposals,
  function legacy_delta2bbox (line 133) | def legacy_delta2bbox(rois,

FILE: mmdet/core/bbox/coder/pseudo_bbox_coder.py
  class PseudoBBoxCoder (line 6) | class PseudoBBoxCoder(BaseBBoxCoder):
    method __init__ (line 9) | def __init__(self, **kwargs):
    method encode (line 12) | def encode(self, bboxes, gt_bboxes):
    method decode (line 16) | def decode(self, bboxes, pred_bboxes):

FILE: mmdet/core/bbox/coder/tblr_bbox_coder.py
  class TBLRBBoxCoder (line 9) | class TBLRBBoxCoder(BaseBBoxCoder):
    method __init__ (line 25) | def __init__(self, normalizer=4.0, clip_border=True):
    method encode (line 30) | def encode(self, bboxes, gt_bboxes):
    method decode (line 49) | def decode(self, bboxes, pred_bboxes, max_shape=None):
  function bboxes2tblr (line 76) | def bboxes2tblr(priors, gts, normalizer=4.0, normalize_by_wh=True):
  function tblr2bboxes (line 123) | def tblr2bboxes(priors,

FILE: mmdet/core/bbox/coder/yolo_bbox_coder.py
  class YOLOBBoxCoder (line 9) | class YOLOBBoxCoder(BaseBBoxCoder):
    method __init__ (line 21) | def __init__(self, eps=1e-6):
    method encode (line 26) | def encode(self, bboxes, gt_bboxes, stride):
    method decode (line 61) | def decode(self, bboxes, pred_bboxes, stride):

FILE: mmdet/core/bbox/demodata.py
  function random_boxes (line 7) | def random_boxes(num=1, scale=1, rng=None):

FILE: mmdet/core/bbox/iou_calculators/builder.py
  function build_iou_calculator (line 6) | def build_iou_calculator(cfg, default_args=None):

FILE: mmdet/core/bbox/iou_calculators/iou2d_calculator.py
  function cast_tensor_type (line 6) | def cast_tensor_type(x, scale=1., dtype=None):
  function fp16_clamp (line 13) | def fp16_clamp(x, min=None, max=None):
  class BboxOverlaps2D (line 22) | class BboxOverlaps2D(object):
    method __init__ (line 25) | def __init__(self, scale=1., dtype=None):
    method __call__ (line 29) | def __call__(self, bboxes1, bboxes2, mode='iou', is_aligned=False):
    method __repr__ (line 67) | def __repr__(self):
  function bbox_overlaps (line 74) | def bbox_overlaps(bboxes1, bboxes2, mode='iou', is_aligned=False, eps=1e...

FILE: mmdet/core/bbox/match_costs/builder.py
  function build_match_cost (line 6) | def build_match_cost(cfg, default_args=None):

FILE: mmdet/core/bbox/match_costs/match_cost.py
  class BBoxL1Cost (line 9) | class BBoxL1Cost(object):
    method __init__ (line 27) | def __init__(self, weight=1., box_format='xyxy'):
    method __call__ (line 32) | def __call__(self, bbox_pred, gt_bboxes):
  class FocalLossCost (line 53) | class FocalLossCost(object):
    method __init__ (line 76) | def __init__(self, weight=1., alpha=0.25, gamma=2, eps=1e-12):
    method __call__ (line 82) | def __call__(self, cls_pred, gt_labels):
  class ClassificationCost (line 102) | class ClassificationCost(object):
    method __init__ (line 123) | def __init__(self, weight=1.):
    method __call__ (line 126) | def __call__(self, cls_pred, gt_labels):
  class IoUCost (line 146) | class IoUCost(object):
    method __init__ (line 164) | def __init__(self, iou_mode='giou', weight=1.):
    method __call__ (line 168) | def __call__(self, bboxes, gt_bboxes):

FILE: mmdet/core/bbox/samplers/base_sampler.py
  class BaseSampler (line 8) | class BaseSampler(metaclass=ABCMeta):
    method __init__ (line 11) | def __init__(self,
    method _sample_pos (line 25) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 30) | def _sample_neg(self, assign_result, num_expected, **kwargs):
    method sample (line 34) | def sample(self,

FILE: mmdet/core/bbox/samplers/combined_sampler.py
  class CombinedSampler (line 6) | class CombinedSampler(BaseSampler):
    method __init__ (line 9) | def __init__(self, pos_sampler, neg_sampler, **kwargs):
    method _sample_pos (line 14) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 18) | def _sample_neg(self, **kwargs):

FILE: mmdet/core/bbox/samplers/instance_balanced_pos_sampler.py
  class InstanceBalancedPosSampler (line 9) | class InstanceBalancedPosSampler(RandomSampler):
    method _sample_pos (line 13) | def _sample_pos(self, assign_result, num_expected, **kwargs):

FILE: mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py
  class IoUBalancedNegSampler (line 9) | class IoUBalancedNegSampler(RandomSampler):
    method __init__ (line 29) | def __init__(self,
    method sample_via_interval (line 46) | def sample_via_interval(self, max_overlaps, full_set, num_expected):
    method _sample_neg (line 88) | def _sample_neg(self, assign_result, num_expected, **kwargs):

FILE: mmdet/core/bbox/samplers/ohem_sampler.py
  class OHEMSampler (line 9) | class OHEMSampler(BaseSampler):
    method __init__ (line 15) | def __init__(self,
    method hard_mining (line 30) | def hard_mining(self, inds, num_expected, bboxes, labels, feats):
    method _sample_pos (line 51) | def _sample_pos(self,
    method _sample_neg (line 79) | def _sample_neg(self,

FILE: mmdet/core/bbox/samplers/pseudo_sampler.py
  class PseudoSampler (line 9) | class PseudoSampler(BaseSampler):
    method __init__ (line 12) | def __init__(self, **kwargs):
    method _sample_pos (line 15) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 19) | def _sample_neg(self, **kwargs):
    method sample (line 23) | def sample(self, assign_result, bboxes, gt_bboxes, **kwargs):

FILE: mmdet/core/bbox/samplers/random_sampler.py
  class RandomSampler (line 8) | class RandomSampler(BaseSampler):
    method __init__ (line 20) | def __init__(self,
    method random_choice (line 31) | def random_choice(self, gallery, num):
    method _sample_pos (line 63) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 73) | def _sample_neg(self, assign_result, num_expected, **kwargs):

FILE: mmdet/core/bbox/samplers/sampling_result.py
  class SamplingResult (line 6) | class SamplingResult(util_mixins.NiceRepr):
    method __init__ (line 25) | def __init__(self, pos_inds, neg_inds, bboxes, gt_bboxes, assign_result,
    method bboxes (line 52) | def bboxes(self):
    method to (line 56) | def to(self, device):
    method __nice__ (line 71) | def __nice__(self):
    method info (line 80) | def info(self):
    method random (line 93) | def random(cls, rng=None, **kwargs):

FILE: mmdet/core/bbox/samplers/score_hlr_sampler.py
  class ScoreHLRSampler (line 11) | class ScoreHLRSampler(BaseSampler):
    method __init__ (line 32) | def __init__(self,
    method random_choice (line 62) | def random_choice(gallery, num):
    method _sample_pos (line 91) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 99) | def _sample_neg(self,
    method sample (line 215) | def sample(self,

FILE: mmdet/core/bbox/transforms.py
  function bbox_flip (line 5) | def bbox_flip(bboxes, img_shape, direction='horizontal'):
  function bbox_mapping (line 34) | def bbox_mapping(bboxes,
  function bbox_mapping_back (line 46) | def bbox_mapping_back(bboxes,
  function bbox2roi (line 58) | def bbox2roi(bbox_list):
  function roi2bbox (line 80) | def roi2bbox(rois):
  function bbox2result (line 99) | def bbox2result(bboxes, labels, num_classes):
  function distance2bbox (line 119) | def distance2bbox(points, distance, max_shape=None):
  function bbox2distance (line 165) | def bbox2distance(points, bbox, max_dis=None, eps=0.1):
  function bbox_rescale (line 189) | def bbox_rescale(bboxes, scale_factor=1.0):
  function bbox_cxcywh_to_xyxy (line 221) | def bbox_cxcywh_to_xyxy(bbox):
  function bbox_xyxy_to_cxcywh (line 235) | def bbox_xyxy_to_cxcywh(bbox):

FILE: mmdet/core/evaluation/bbox_overlaps.py
  function bbox_overlaps (line 4) | def bbox_overlaps(bboxes1, bboxes2, mode='iou', eps=1e-6):

FILE: mmdet/core/evaluation/class_names.py
  function wider_face_classes (line 4) | def wider_face_classes():
  function voc_classes (line 8) | def voc_classes():
  function imagenet_det_classes (line 16) | def imagenet_det_classes():
  function imagenet_vid_classes (line 57) | def imagenet_vid_classes():
  function coco_classes (line 67) | def coco_classes():
  function cityscapes_classes (line 85) | def cityscapes_classes():
  function get_classes (line 102) | def get_classes(dataset):

FILE: mmdet/core/evaluation/eval_hooks.py
  class EvalHook (line 14) | class EvalHook(Hook):
    method __init__ (line 49) | def __init__(self,
    method _init_rule (line 81) | def _init_rule(self, rule, key_indicator):
    method before_run (line 108) | def before_run(self, runner):
    method before_train_epoch (line 115) | def before_train_epoch(self, runner):
    method evaluation_flag (line 123) | def evaluation_flag(self, runner):
    method after_train_epoch (line 142) | def after_train_epoch(self, runner):
    method after_train_iter (line 151) | def after_train_iter(self, runner):
    method save_best_checkpoint (line 160) | def save_best_checkpoint(self, runner, key_score):
    method evaluate (line 175) | def evaluate(self, runner, results):
  class DistEvalHook (line 190) | class DistEvalHook(EvalHook):
    method __init__ (line 224) | def __init__(self,
    method _broadcast_bn_buffer (line 247) | def _broadcast_bn_buffer(self, runner):
    method after_train_epoch (line 261) | def after_train_epoch(self, runner):
    method after_train_iter (line 283) | def after_train_iter(self, runner):

FILE: mmdet/core/evaluation/mean_ap.py
  function average_precision (line 12) | def average_precision(recalls, precisions, mode='area'):
  function tpfp_imagenet (line 59) | def tpfp_imagenet(det_bboxes,
  function tpfp_default (line 153) | def tpfp_default(det_bboxes,
  function get_cls_results (line 240) | def get_cls_results(det_results, annotations, class_id):
  function eval_map (line 267) | def eval_map(det_results,
  function print_map_summary (line 404) | def print_map_summary(mean_ap,

FILE: mmdet/core/evaluation/recall.py
  function _recalls (line 10) | def _recalls(all_ious, proposal_nums, thrs):
  function set_recall_param (line 43) | def set_recall_param(proposal_nums, iou_thrs):
  function eval_recalls (line 64) | def eval_recalls(gts,
  function print_recall_summary (line 109) | def print_recall_summary(recalls,
  function plot_num_recall (line 142) | def plot_num_recall(recalls, proposal_nums):
  function plot_iou_recall (line 167) | def plot_iou_recall(recalls, iou_thrs):

FILE: mmdet/core/export/model_wrappers.py
  class ONNXRuntimeDetector (line 12) | class ONNXRuntimeDetector(BaseDetector):
    method __init__ (line 15) | def __init__(self, onnx_file, class_names, device_id):
    method simple_test (line 46) | def simple_test(self, img, img_metas, **kwargs):
    method aug_test (line 49) | def aug_test(self, imgs, img_metas, **kwargs):
    method extract_feat (line 52) | def extract_feat(self, imgs):
    method forward_test (line 55) | def forward_test(self, imgs, img_metas, **kwargs):

FILE: mmdet/core/export/onnx_helper.py
  function dynamic_clip_for_onnx (line 6) | def dynamic_clip_for_onnx(x1, y1, x2, y2, max_shape):
  function get_k_for_topk (line 45) | def get_k_for_topk(k, size):
  function add_dummy_nms_for_onnx (line 81) | def add_dummy_nms_for_onnx(boxes,
  class DymmyONNXNMSop (line 200) | class DymmyONNXNMSop(torch.autograd.Function):
    method forward (line 207) | def forward(ctx, boxes, scores, max_output_boxes_per_class, iou_thresh...
    method symbolic (line 213) | def symbolic(g, boxes, scores, max_output_boxes_per_class, iou_threshold,

FILE: mmdet/core/export/pytorch2onnx.py
  function generate_inputs_and_wrap_model (line 9) | def generate_inputs_and_wrap_model(config_path,
  function build_model_from_cfg (line 64) | def build_model_from_cfg(config_path, checkpoint_path, cfg_options=None):
  function preprocess_example_input (line 98) | def preprocess_example_input(input_config):

FILE: mmdet/core/mask/mask_target.py
  function mask_target (line 6) | def mask_target(pos_proposals_list, pos_assigned_gt_inds_list, gt_masks_...
  function mask_target_single (line 66) | def mask_target_single(pos_proposals, pos_assigned_gt_inds, gt_masks, cfg):

FILE: mmdet/core/mask/structures.py
  class BaseInstanceMasks (line 11) | class BaseInstanceMasks(metaclass=ABCMeta):
    method rescale (line 15) | def rescale(self, scale, interpolation='nearest'):
    method resize (line 28) | def resize(self, out_shape, interpolation='nearest'):
    method flip (line 40) | def flip(self, flip_direction='horizontal'):
    method pad (line 51) | def pad(self, out_shape, pad_val):
    method crop (line 63) | def crop(self, bbox):
    method crop_and_resize (line 74) | def crop_and_resize(self,
    method expand (line 99) | def expand(self, expanded_h, expanded_w, top, left):
    method areas (line 104) | def areas(self):
    method to_ndarray (line 108) | def to_ndarray(self):
    method to_tensor (line 116) | def to_tensor(self, dtype, device):
    method translate (line 128) | def translate(self,
    method shear (line 148) | def shear(self,
    method rotate (line 170) | def rotate(self, out_shape, angle, center=None, scale=1.0, fill_val=0):
  class BitmapMasks (line 188) | class BitmapMasks(BaseInstanceMasks):
    method __init__ (line 217) | def __init__(self, masks, height, width):
    method __getitem__ (line 234) | def __getitem__(self, index):
    method __iter__ (line 246) | def __iter__(self):
    method __repr__ (line 249) | def __repr__(self):
    method __len__ (line 256) | def __len__(self):
    method rescale (line 260) | def rescale(self, scale, interpolation='nearest'):
    method resize (line 273) | def resize(self, out_shape, interpolation='nearest'):
    method flip (line 285) | def flip(self, flip_direction='horizontal'):
    method pad (line 298) | def pad(self, out_shape, pad_val=0):
    method crop (line 309) | def crop(self, bbox):
    method crop_and_resize (line 328) | def crop_and_resize(self,
    method expand (line 360) | def expand(self, expanded_h, expanded_w, top, left):
    method translate (line 372) | def translate(self,
    method shear (line 422) | def shear(self,
    method rotate (line 457) | def rotate(self, out_shape, angle, center=None, scale=1.0, fill_val=0):
    method areas (line 490) | def areas(self):
    method to_ndarray (line 494) | def to_ndarray(self):
    method to_tensor (line 498) | def to_tensor(self, dtype, device):
    method random (line 503) | def random(cls,
  class PolygonMasks (line 524) | class PolygonMasks(BaseInstanceMasks):
    method __init__ (line 564) | def __init__(self, masks, height, width):
    method __getitem__ (line 574) | def __getitem__(self, index):
    method __iter__ (line 597) | def __iter__(self):
    method __repr__ (line 600) | def __repr__(self):
    method __len__ (line 607) | def __len__(self):
    method rescale (line 611) | def rescale(self, scale, interpolation=None):
    method resize (line 620) | def resize(self, out_shape, interpolation=None):
    method flip (line 639) | def flip(self, flip_direction='horizontal'):
    method crop (line 663) | def crop(self, bbox):
    method pad (line 692) | def pad(self, out_shape, pad_val=0):
    method expand (line 696) | def expand(self, *args, **kwargs):
    method crop_and_resize (line 700) | def crop_and_resize(self,
    method translate (line 736) | def translate(self,
    method shear (line 770) | def shear(self,
    method rotate (line 802) | def rotate(self, out_shape, angle, center=None, scale=1.0, fill_val=0):
    method to_bitmap (line 831) | def to_bitmap(self):
    method areas (line 837) | def areas(self):
    method _polygon_area (line 855) | def _polygon_area(self, x, y):
    method to_ndarray (line 871) | def to_ndarray(self):
    method to_tensor (line 881) | def to_tensor(self, dtype, device):
    method random (line 891) | def random(cls,
  function polygon_to_bitmap (line 1010) | def polygon_to_bitmap(polygons, height, width):

FILE: mmdet/core/mask/utils.py
  function split_combined_polys (line 6) | def split_combined_polys(polys, poly_lens, polys_per_mask):
  function encode_mask_results (line 36) | def encode_mask_results(mask_results):

FILE: mmdet/core/post_processing/bbox_nms.py
  function multiclass_nms (line 7) | def multiclass_nms(multi_bboxes,
  function fast_nms (line 96) | def fast_nms(multi_bboxes,

FILE: mmdet/core/post_processing/merge_augs.py
  function merge_aug_proposals (line 12) | def merge_aug_proposals(aug_proposals, img_metas, cfg):
  function merge_aug_bboxes (line 83) | def merge_aug_bboxes(aug_bboxes, aug_scores, img_metas, rcnn_test_cfg):
  function merge_aug_scores (line 112) | def merge_aug_scores(aug_scores):
  function merge_aug_masks (line 120) | def merge_aug_masks(aug_masks, img_metas, rcnn_test_cfg, weights=None):

FILE: mmdet/core/utils/dist_utils.py
  function _allreduce_coalesced (line 10) | def _allreduce_coalesced(tensors, world_size, bucket_size_mb=-1):
  function allreduce_grads (line 32) | def allreduce_grads(params, coalesce=True, bucket_size_mb=-1):
  class DistOptimizerHook (line 54) | class DistOptimizerHook(OptimizerHook):
    method __init__ (line 57) | def __init__(self, *args, **kwargs):
  function reduce_mean (line 63) | def reduce_mean(tensor):

FILE: mmdet/core/utils/misc.py
  function multi_apply (line 10) | def multi_apply(func, *args, **kwargs):
  function unmap (line 32) | def unmap(data, count, inds, fill=0):
  function mask2ndarray (line 45) | def mask2ndarray(mask):

FILE: mmdet/core/visualization/image.py
  function color_val_matplotlib (line 13) | def color_val_matplotlib(color):
  function imshow_det_bboxes (line 28) | def imshow_det_bboxes(img,
  function imshow_gt_det_bboxes (line 198) | def imshow_gt_det_bboxes(img,

FILE: mmdet/datasets/api_wrappers/coco_api.py
  class COCO (line 10) | class COCO(_COCO):
    method __init__ (line 17) | def __init__(self, annotation_file=None):
    method get_ann_ids (line 26) | def get_ann_ids(self, img_ids=[], cat_ids=[], area_rng=[], iscrowd=None):
    method get_cat_ids (line 29) | def get_cat_ids(self, cat_names=[], sup_names=[], cat_ids=[]):
    method get_img_ids (line 32) | def get_img_ids(self, img_ids=[], cat_ids=[]):
    method load_anns (line 35) | def load_anns(self, ids):
    method load_cats (line 38) | def load_cats(self, ids):
    method load_imgs (line 41) | def load_imgs(self, ids):

FILE: mmdet/datasets/builder.py
  function _concat_dataset (line 26) | def _concat_dataset(cfg, default_args=None):
  function build_dataset (line 53) | def build_dataset(cfg, default_args=None):
  function build_dataloader (line 76) | def build_dataloader(dataset,
  function worker_init_fn (line 138) | def worker_init_fn(worker_id, num_workers, rank, seed):

FILE: mmdet/datasets/cityscapes.py
  class CityscapesDataset (line 20) | class CityscapesDataset(CocoDataset):
    method _filter_imgs (line 25) | def _filter_imgs(self, min_size=32):
    method _parse_ann_info (line 53) | def _parse_ann_info(self, img_info, ann_info):
    method results2txt (line 107) | def results2txt(self, results, outfile_prefix):
    method format_results (line 173) | def format_results(self, results, txtfile_prefix=None):
    method evaluate (line 207) | def evaluate(self,
    method _evaluate_cityscapes (line 274) | def _evaluate_cityscapes(self, results, txtfile_prefix, logger):

FILE: mmdet/datasets/coco.py
  class CocoDataset (line 20) | class CocoDataset(CustomDataset):
    method load_annotations (line 37) | def load_annotations(self, ann_file):
    method get_ann_info (line 63) | def get_ann_info(self, idx):
    method get_cat_ids (line 78) | def get_cat_ids(self, idx):
    method _filter_imgs (line 93) | def _filter_imgs(self, min_size=32):
    method _parse_ann_info (line 117) | def _parse_ann_info(self, img_info, ann_info):
    method xyxy2xywh (line 176) | def xyxy2xywh(self, bbox):
    method _proposal2json (line 196) | def _proposal2json(self, results):
    method _det2json (line 211) | def _det2json(self, results):
    method _segm2json (line 228) | def _segm2json(self, results):
    method results2json (line 266) | def results2json(self, results, outfile_prefix):
    method fast_eval_recall (line 306) | def fast_eval_recall(self, results, proposal_nums, iou_thrs, logger=No...
    method format_results (line 330) | def format_results(self, results, jsonfile_prefix=None, **kwargs):
    method evaluate (line 358) | def evaluate(self,

FILE: mmdet/datasets/custom.py
  class CustomDataset (line 17) | class CustomDataset(Dataset):
    method __init__ (line 56) | def __init__(self,
    method __len__ (line 107) | def __len__(self):
    method load_annotations (line 111) | def load_annotations(self, ann_file):
    method load_proposals (line 115) | def load_proposals(self, proposal_file):
    method get_ann_info (line 119) | def get_ann_info(self, idx):
    method get_cat_ids (line 131) | def get_cat_ids(self, idx):
    method pre_pipeline (line 143) | def pre_pipeline(self, results):
    method _filter_imgs (line 152) | def _filter_imgs(self, min_size=32):
    method _set_group_flag (line 163) | def _set_group_flag(self):
    method _rand_another (line 175) | def _rand_another(self, idx):
    method __getitem__ (line 180) | def __getitem__(self, idx):
    method prepare_train_img (line 200) | def prepare_train_img(self, idx):
    method prepare_test_img (line 219) | def prepare_test_img(self, idx):
    method get_classes (line 238) | def get_classes(cls, classes=None):
    method format_results (line 264) | def format_results(self, results, **kwargs):
    method evaluate (line 267) | def evaluate(self,
    method __repr__ (line 326) | def __repr__(self):

FILE: mmdet/datasets/dataset_wrappers.py
  class ConcatDataset (line 14) | class ConcatDataset(_ConcatDataset):
    method __init__ (line 27) | def __init__(self, datasets, separate_eval=True):
    method get_cat_ids (line 46) | def get_cat_ids(self, idx):
    method evaluate (line 68) | def evaluate(self, results, logger=None, **kwargs):
  class RepeatDataset (line 128) | class RepeatDataset(object):
    method __init__ (line 141) | def __init__(self, dataset, times):
    method __getitem__ (line 150) | def __getitem__(self, idx):
    method get_cat_ids (line 153) | def get_cat_ids(self, idx):
    method __len__ (line 165) | def __len__(self):
  class ClassBalancedDataset (line 172) | class ClassBalancedDataset(object):
    method __init__ (line 208) | def __init__(self, dataset, oversample_thr, filter_empty_gt=True):
    method _get_repeat_factors (line 227) | def _get_repeat_factors(self, dataset, repeat_thr):
    method __getitem__ (line 276) | def __getitem__(self, idx):
    method __len__ (line 280) | def __len__(self):

FILE: mmdet/datasets/deepfashion.py
  class DeepFashionDataset (line 6) | class DeepFashionDataset(CocoDataset):

FILE: mmdet/datasets/lvis.py
  class LVISV05Dataset (line 17) | class LVISV05Dataset(CocoDataset):
    method load_annotations (line 269) | def load_annotations(self, ann_file):
    method evaluate (line 308) | def evaluate(self,
  class LVISV1Dataset (line 470) | class LVISV1Dataset(LVISDataset):
    method load_annotations (line 712) | def load_annotations(self, ann_file):

FILE: mmdet/datasets/pipelines/auto_augment.py
  function level_to_value (line 13) | def level_to_value(level, max_value):
  function enhance_level_to_value (line 18) | def enhance_level_to_value(level, a=1.8, b=0.1):
  function random_negative (line 23) | def random_negative(value, random_negative_prob):
  function bbox2fields (line 28) | def bbox2fields():
  class AutoAugment (line 46) | class AutoAugment(object):
    method __init__ (line 89) | def __init__(self, policies):
    method __call__ (line 103) | def __call__(self, results):
    method __repr__ (line 107) | def __repr__(self):
  class Shear (line 112) | class Shear(object):
    method __init__ (line 135) | def __init__(self,
    method _shear_img (line 179) | def _shear_img(self,
    method _shear_bboxes (line 203) | def _shear_bboxes(self, results, magnitude):
    method _shear_masks (line 233) | def _shear_masks(self,
    method _shear_seg (line 249) | def _shear_seg(self,
    method _filter_invalid (line 265) | def _filter_invalid(self, results, min_bbox_size=0):
    method __call__ (line 284) | def __call__(self, results):
    method __repr__ (line 315) | def __repr__(self):
  class Rotate (line 329) | class Rotate(object):
    method __init__ (line 355) | def __init__(self,
    method _rotate_img (line 406) | def _rotate_img(self, results, angle, center=None, scale=1.0):
    method _rotate_bboxes (line 424) | def _rotate_bboxes(self, results, rotate_matrix):
    method _rotate_masks (line 459) | def _rotate_masks(self,
    method _rotate_seg (line 471) | def _rotate_seg(self,
    method _filter_invalid (line 484) | def _filter_invalid(self, results, min_bbox_size=0):
    method __call__ (line 503) | def __call__(self, results):
    method __repr__ (line 529) | def __repr__(self):
  class Translate (line 543) | class Translate(object):
    method __init__ (line 569) | def __init__(self,
    method _translate_img (line 610) | def _translate_img(self, results, offset, direction='horizontal'):
    method _translate_bboxes (line 624) | def _translate_bboxes(self, results, offset):
    method _translate_masks (line 642) | def _translate_masks(self,
    method _translate_seg (line 653) | def _translate_seg(self,
    method _filter_invalid (line 664) | def _filter_invalid(self, results, min_size=0):
    method __call__ (line 683) | def __call__(self, results):
  class ColorTransform (line 709) | class ColorTransform(object):
    method __init__ (line 718) | def __init__(self, level, prob=0.5):
    method _adjust_color_img (line 729) | def _adjust_color_img(self, results, factor=1.0):
    method __call__ (line 736) | def __call__(self, results):
    method __repr__ (line 750) | def __repr__(self):
  class EqualizeTransform (line 758) | class EqualizeTransform(object):
    method __init__ (line 766) | def __init__(self, prob=0.5):
    method _imequalize (line 771) | def _imequalize(self, results):
    method __call__ (line 777) | def __call__(self, results):
    method __repr__ (line 791) | def __repr__(self):
  class BrightnessTransform (line 797) | class BrightnessTransform(object):
    method __init__ (line 806) | def __init__(self, level, prob=0.5):
    method _adjust_brightness_img (line 817) | def _adjust_brightness_img(self, results, factor=1.0):
    method __call__ (line 824) | def __call__(self, results):
    method __repr__ (line 838) | def __repr__(self):
  class ContrastTransform (line 846) | class ContrastTransform(object):
    method __init__ (line 855) | def __init__(self, level, prob=0.5):
    method _adjust_contrast_img (line 866) | def _adjust_contrast_img(self, results, factor=1.0):
    method __call__ (line 872) | def __call__(self, results):
    method __repr__ (line 886) | def __repr__(self):

FILE: mmdet/datasets/pipelines/compose.py
  class Compose (line 9) | class Compose(object):
    method __init__ (line 17) | def __init__(self, transforms):
    method __call__ (line 29) | def __call__(self, data):
    method __repr__ (line 45) | def __repr__(self):

FILE: mmdet/datasets/pipelines/formating.py
  function to_tensor (line 11) | def to_tensor(data):
  class ToTensor (line 37) | class ToTensor(object):
    method __init__ (line 44) | def __init__(self, keys):
    method __call__ (line 47) | def __call__(self, results):
    method __repr__ (line 61) | def __repr__(self):
  class ImageToTensor (line 66) | class ImageToTensor(object):
    method __init__ (line 77) | def __init__(self, keys):
    method __call__ (line 80) | def __call__(self, results):
    method __repr__ (line 98) | def __repr__(self):
  class Transpose (line 103) | class Transpose(object):
    method __init__ (line 111) | def __init__(self, keys, order):
    method __call__ (line 115) | def __call__(self, results):
    method __repr__ (line 129) | def __repr__(self):
  class ToDataContainer (line 135) | class ToDataContainer(object):
    method __init__ (line 146) | def __init__(self,
    method __call__ (line 151) | def __call__(self, results):
    method __repr__ (line 169) | def __repr__(self):
  class DefaultFormatBundle (line 174) | class DefaultFormatBundle(object):
    method __call__ (line 191) | def __call__(self, results):
    method _add_default_meta_keys (line 221) | def _add_default_meta_keys(self, results):
    method __repr__ (line 246) | def __repr__(self):
  class Collect (line 251) | class Collect(object):
    method __init__ (line 290) | def __init__(self,
    method __call__ (line 298) | def __call__(self, results):
    method __repr__ (line 321) | def __repr__(self):
  class WrapFieldsToLists (line 327) | class WrapFieldsToLists(object):
    method __call__ (line 347) | def __call__(self, results):
    method __repr__ (line 363) | def __repr__(self):

FILE: mmdet/datasets/pipelines/instaboost.py
  class InstaBoost (line 7) | class InstaBoost(object):
    method __init__ (line 15) | def __init__(self,
    method _load_anns (line 36) | def _load_anns(self, results):
    method _parse_anns (line 58) | def _parse_anns(self, results, anns, img):
    method __call__ (line 79) | def __call__(self, results):
    method __repr__ (line 95) | def __repr__(self):

FILE: mmdet/datasets/pipelines/loading.py
  class LoadImageFromFile (line 12) | class LoadImageFromFile(object):
    method __init__ (line 31) | def __init__(self,
    method __call__ (line 40) | def __call__(self, results):
    method __repr__ (line 72) | def __repr__(self):
  class LoadImageFromWebcam (line 81) | class LoadImageFromWebcam(LoadImageFromFile):
    method __call__ (line 88) | def __call__(self, results):
  class LoadMultiChannelImageFromFiles (line 113) | class LoadMultiChannelImageFromFiles(object):
    method __init__ (line 133) | def __init__(self,
    method __call__ (line 142) | def __call__(self, results):
    method __repr__ (line 187) | def __repr__(self):
  class LoadAnnotations (line 196) | class LoadAnnotations(object):
    method __init__ (line 215) | def __init__(self,
    method _load_bboxes (line 230) | def _load_bboxes(self, results):
    method _load_labels (line 250) | def _load_labels(self, results):
    method _poly2mask (line 263) | def _poly2mask(self, mask_ann, img_h, img_w):
    method process_polygons (line 290) | def process_polygons(self, polygons):
    method _load_masks (line 307) | def _load_masks(self, results):
    method _load_semantic_seg (line 332) | def _load_semantic_seg(self, results):
    method __call__ (line 353) | def __call__(self, results):
    method __repr__ (line 376) | def __repr__(self):
  class LoadProposals (line 388) | class LoadProposals(object):
    method __init__ (line 398) | def __init__(self, num_max_proposals=None):
    method __call__ (line 401) | def __call__(self, results):
    method __repr__ (line 427) | def __repr__(self):
  class FilterAnnotations (line 433) | class FilterAnnotations(object):
    method __init__ (line 441) | def __init__(self, min_gt_bbox_wh):
    method __call__ (line 445) | def __call__(self, results):

FILE: mmdet/datasets/pipelines/test_time_aug.py
  class MultiScaleFlipAug (line 10) | class MultiScaleFlipAug(object):
    method __init__ (line 52) | def __init__(self,
    method __call__ (line 83) | def __call__(self, results):
    method __repr__ (line 114) | def __repr__(self):

FILE: mmdet/datasets/pipelines/transforms.py
  class Resize (line 26) | class Resize(object):
    method __init__ (line 66) | def __init__(self,
    method random_select (line 99) | def random_select(img_scales):
    method random_sample (line 117) | def random_sample(img_scales):
    method random_sample_ratio (line 144) | def random_sample_ratio(img_scale, ratio_range):
    method _random_scale (line 170) | def _random_scale(self, results):
    method _resize_img (line 203) | def _resize_img(self, results):
    method _resize_bboxes (line 234) | def _resize_bboxes(self, results):
    method _resize_masks (line 244) | def _resize_masks(self, results):
    method _resize_seg (line 254) | def _resize_seg(self, results):
    method __call__ (line 271) | def __call__(self, results):
    method __repr__ (line 308) | def __repr__(self):
  class RandomFlip (line 319) | class RandomFlip(object):
    method __init__ (line 356) | def __init__(self, flip_ratio=None, direction='horizontal'):
    method bbox_flip (line 382) | def bbox_flip(self, bboxes, img_shape, direction):
    method __call__ (line 416) | def __call__(self, results):
    method __repr__ (line 471) | def __repr__(self):
  class RandomShift (line 476) | class RandomShift(object):
    method __init__ (line 487) | def __init__(self, shift_ratio=0.5, max_shift_px=32, filter_thr_px=1):
    method __call__ (line 499) | def __call__(self, results):
    method __repr__ (line 559) | def __repr__(self):
  class Pad (line 566) | class Pad(object):
    method __init__ (line 579) | def __init__(self, size=None, size_divisor=None, pad_val=0):
    method _pad_img (line 587) | def _pad_img(self, results):
    method _pad_masks (line 601) | def _pad_masks(self, results):
    method _pad_seg (line 607) | def _pad_seg(self, results):
    method __call__ (line 614) | def __call__(self, results):
    method __repr__ (line 628) | def __repr__(self):
  class Normalize (line 637) | class Normalize(object):
    method __init__ (line 649) | def __init__(self, mean, std, to_rgb=True):
    method __call__ (line 654) | def __call__(self, results):
    method __repr__ (line 671) | def __repr__(self):
  class RandomCrop (line 678) | class RandomCrop(object):
    method __init__ (line 712) | def __init__(self,
    method _crop_data (line 741) | def _crop_data(self, results, crop_size, allow_negative_crop):
    method _get_crop_size (line 806) | def _get_crop_size(self, image_size):
    method __call__ (line 836) | def __call__(self, results):
    method __repr__ (line 852) | def __repr__(self):
  class SegRescale (line 862) | class SegRescale(object):
    method __init__ (line 872) | def __init__(self, scale_factor=1, backend='cv2'):
    method __call__ (line 876) | def __call__(self, results):
    method __repr__ (line 895) | def __repr__(self):
  class PhotoMetricDistortion (line 900) | class PhotoMetricDistortion(object):
    method __init__ (line 921) | def __init__(self,
    method __call__ (line 931) | def __call__(self, results):
    method __repr__ (line 994) | def __repr__(self):
  class Expand (line 1006) | class Expand(object):
    method __init__ (line 1019) | def __init__(self,
    method __call__ (line 1035) | def __call__(self, results):
    method __repr__ (line 1089) | def __repr__(self):
  class MinIoURandomCrop (line 1098) | class MinIoURandomCrop(object):
    method __init__ (line 1117) | def __init__(self,
    method __call__ (line 1135) | def __call__(self, results):
    method __repr__ (line 1229) | def __repr__(self):
  class Corrupt (line 1238) | class Corrupt(object):
    method __init__ (line 1249) | def __init__(self, corruption, severity=1):
    method __call__ (line 1253) | def __call__(self, results):
    method __repr__ (line 1274) | def __repr__(self):
  class Albu (line 1282) | class Albu(object):
    method __init__ (line 1324) | def __init__(self,
    method albu_builder (line 1367) | def albu_builder(self, cfg):
    method mapper (line 1402) | def mapper(d, keymap):
    method __call__ (line 1418) | def __call__(self, results):
    method __repr__ (line 1480) | def __repr__(self):
  class RandomCenterCropPad (line 1486) | class RandomCenterCropPad(object):
    method __init__ (line 1573) | def __init__(self,
    method _get_border (line 1617) | def _get_border(self, border, size):
    method _filter_boxes (line 1636) | def _filter_boxes(self, patch, boxes):
    method _crop_image_and_paste (line 1652) | def _crop_image_and_paste(self, image, center, size):
    method _train_aug (line 1703) | def _train_aug(self, results):
    method _test_aug (line 1771) | def _test_aug(self, results):
    method __call__ (line 1804) | def __call__(self, results):
    method __repr__ (line 1816) | def __repr__(self):
  class CutOut (line 1831) | class CutOut(object):
    method __init__ (line 1854) | def __init__(self,
    method __call__ (line 1875) | def __call__(self, results):
    method __repr__ (line 1895) | def __repr__(self):

FILE: mmdet/datasets/samplers/distributed_sampler.py
  class DistributedSampler (line 7) | class DistributedSampler(_DistributedSampler):
    method __init__ (line 9) | def __init__(self,
    method __iter__ (line 20) | def __iter__(self):

FILE: mmdet/datasets/samplers/group_sampler.py
  class GroupSampler (line 10) | class GroupSampler(Sampler):
    method __init__ (line 12) | def __init__(self, dataset, samples_per_gpu=1):
    method __iter__ (line 23) | def __iter__(self):
    method __len__ (line 47) | def __len__(self):
  class DistributedGroupSampler (line 51) | class DistributedGroupSampler(Sampler):
    method __init__ (line 72) | def __init__(self,
    method __iter__ (line 101) | def __iter__(self):
    method __len__ (line 144) | def __len__(self):
    method set_epoch (line 147) | def set_epoch(self, epoch):

FILE: mmdet/datasets/utils.py
  function replace_ImageToTensor (line 13) | def replace_ImageToTensor(pipelines):
  function get_loading_pipeline (line 73) | def get_loading_pipeline(pipeline):
  class NumClassCheckHook (line 115) | class NumClassCheckHook(Hook):
    method _check_head (line 117) | def _check_head(self, runner):
    method before_train_epoch (line 149) | def before_train_epoch(self, runner):
    method before_val_epoch (line 157) | def before_val_epoch(self, runner):

FILE: mmdet/datasets/voc.py
  class VOCDataset (line 11) | class VOCDataset(XMLDataset):
    method __init__ (line 18) | def __init__(self, **kwargs):
    method evaluate (line 27) | def evaluate(self,

FILE: mmdet/datasets/wider_face.py
  class WIDERFaceDataset (line 11) | class WIDERFaceDataset(XMLDataset):
    method __init__ (line 19) | def __init__(self, **kwargs):
    method load_annotations (line 22) | def load_annotations(self, ann_file):

FILE: mmdet/datasets/xml_style.py
  class XMLDataset (line 13) | class XMLDataset(CustomDataset):
    method __init__ (line 22) | def __init__(self, min_size=None, **kwargs):
    method load_annotations (line 29) | def load_annotations(self, ann_file):
    method _filter_imgs (line 61) | def _filter_imgs(self, min_size=32):
    method get_ann_info (line 82) | def get_ann_info(self, idx):
    method get_cat_ids (line 148) | def get_cat_ids(self, idx):

FILE: mmdet/models/backbones/darknet.py
  class ResBlock (line 13) | class ResBlock(BaseModule):
    method __init__ (line 32) | def __init__(self,
    method forward (line 49) | def forward(self, x):
  class Darknet (line 59) | class Darknet(BaseModule):
    method __init__ (line 100) | def __init__(self,
    method forward (line 152) | def forward(self, x):
    method _freeze_stages (line 162) | def _freeze_stages(self):
    method train (line 170) | def train(self, mode=True):
    method make_conv_res_block (line 179) | def make_conv_res_block(in_channels,

FILE: mmdet/models/backbones/detectors_resnet.py
  class Bottleneck (line 15) | class Bottleneck(_Bottleneck):
    method __init__ (line 35) | def __init__(self,
    method rfp_forward (line 72) | def rfp_forward(self, x, rfp_feat):
  class ResLayer (line 119) | class ResLayer(Sequential):
    method __init__ (line 145) | def __init__(self,
  class DetectoRS_ResNet (line 211) | class DetectoRS_ResNet(ResNet):
    method __init__ (line 233) | def __init__(self,
    method init_weights (line 286) | def init_weights(self):
    method make_res_layer (line 315) | def make_res_layer(self, **kwargs):
    method forward (line 319) | def forward(self, x):
    method rfp_forward (line 326) | def rfp_forward(self, x, rfp_feats):

FILE: mmdet/models/backbones/detectors_resnext.py
  class Bottleneck (line 10) | class Bottleneck(_Bottleneck):
    method __init__ (line 13) | def __init__(self,
  class DetectoRS_ResNeXt (line 98) | class DetectoRS_ResNeXt(DetectoRS_ResNet):
    method __init__ (line 112) | def __init__(self, groups=1, base_width=4, **kwargs):
    method make_res_layer (line 117) | def make_res_layer(self, **kwargs):

FILE: mmdet/models/backbones/hourglass.py
  class HourglassModule (line 10) | class HourglassModule(BaseModule):
    method __init__ (line 26) | def __init__(self,
    method forward (line 74) | def forward(self, x):
  class HourglassNet (line 85) | class HourglassNet(BaseModule):
    method __init__ (line 119) | def __init__(self,
    method init_weights (line 175) | def init_weights(self):
    method forward (line 183) | def forward(self, x):

FILE: mmdet/models/backbones/hrnet.py
  class HRModule (line 12) | class HRModule(BaseModule):
    method __init__ (line 19) | def __init__(self,
    method _check_branches (line 48) | def _check_branches(self, num_branches, num_blocks, in_channels,
    method _make_one_branch (line 65) | def _make_one_branch(self,
    method _make_branches (line 111) | def _make_branches(self, num_branches, block, num_blocks, num_channels):
    method _make_fuse_layers (line 120) | def _make_fuse_layers(self):
    method forward (line 182) | def forward(self, x):
  class HRNet (line 203) | class HRNet(BaseModule):
    method __init__ (line 267) | def __init__(self,
    method norm1 (line 378) | def norm1(self):
    method norm2 (line 383) | def norm2(self):
    method _make_transition_layer (line 387) | def _make_transition_layer(self, num_channels_pre_layer,
    method _make_layer (line 433) | def _make_layer(self, block, inplanes, planes, blocks, stride=1):
    method _make_stage (line 480) | def _make_stage(self, layer_config, in_channels, multiscale_output=True):
    method forward (line 520) | def forward(self, x):
    method train (line 556) | def train(self, mode=True):

FILE: mmdet/models/backbones/regnet.py
  class RegNet (line 13) | class RegNet(ResNet):
    method __init__ (line 89) | def __init__(self,
    method _make_stem_layer (line 237) | def _make_stem_layer(self, in_channels, base_channels):
    method generate_regnet (line 251) | def generate_regnet(self,
    method quantize_float (line 284) | def quantize_float(number, divisor):
    method adjust_width_group (line 296) | def adjust_width_group(self, widths, bottleneck_ratio, groups):
    method get_stages_from_blocks (line 321) | def get_stages_from_blocks(self, widths):
    method forward (line 343) | def forward(self, x):

FILE: mmdet/models/backbones/res2net.py
  class Bottle2neck (line 14) | class Bottle2neck(_Bottleneck):
    method __init__ (line 17) | def __init__(self,
    method forward (line 105) | def forward(self, x):
  class Res2Layer (line 162) | class Res2Layer(Sequential):
    method __init__ (line 181) | def __init__(self,
  class Res2Net (line 242) | class Res2Net(ResNet):
    method __init__ (line 302) | def __init__(self,
    method make_res_layer (line 321) | def make_res_layer(self, **kwargs):

FILE: mmdet/models/backbones/resnest.py
  class RSoftmax (line 16) | class RSoftmax(nn.Module):
    method __init__ (line 24) | def __init__(self, radix, groups):
    method forward (line 29) | def forward(self, x):
  class SplitAttentionConv2d (line 40) | class SplitAttentionConv2d(BaseModule):
    method __init__ (line 63) | def __init__(self,
    method norm0 (line 115) | def norm0(self):
    method norm1 (line 120) | def norm1(self):
    method forward (line 124) | def forward(self, x):
  class Bottleneck (line 153) | class Bottleneck(_Bottleneck):
    method __init__ (line 172) | def __init__(self,
    method forward (line 233) | def forward(self, x):
  class ResNeSt (line 277) | class ResNeSt(ResNetV1d):
    method __init__ (line 298) | def __init__(self,
    method make_res_layer (line 312) | def make_res_layer(self, **kwargs):

FILE: mmdet/models/backbones/resnet.py
  class BasicBlock (line 13) | class BasicBlock(BaseModule):
    method __init__ (line 16) | def __init__(self,
    method norm1 (line 57) | def norm1(self):
    method norm2 (line 62) | def norm2(self):
    method forward (line 66) | def forward(self, x):
  class Bottleneck (line 96) | class Bottleneck(BaseModule):
    method __init__ (line 99) | def __init__(self,
    method make_block_plugins (line 218) | def make_block_plugins(self, in_channels, plugins):
    method forward_plugin (line 241) | def forward_plugin(self, x, plugin_names):
    method norm1 (line 248) | def norm1(self):
    method norm2 (line 253) | def norm2(self):
    method norm3 (line 258) | def norm3(self):
    method forward (line 262) | def forward(self, x):
  class ResNet (line 305) | class ResNet(BaseModule):
    method __init__ (line 368) | def __init__(self,
    method make_stage_plugins (line 493) | def make_stage_plugins(self, plugins, stage_idx):
    method make_res_layer (line 555) | def make_res_layer(self, **kwargs):
    method norm1 (line 560) | def norm1(self):
    method _make_stem_layer (line 564) | def _make_stem_layer(self, in_channels, stem_channels):
    method _freeze_stages (line 612) | def _freeze_stages(self):
    method forward (line 630) | def forward(self, x):
    method train (line 650) | def train(self, mode=True):
  class ResNetV1d (line 663) | class ResNetV1d(ResNet):
    method __init__ (line 672) | def __init__(self, **kwargs):

FILE: mmdet/models/backbones/resnext.py
  class Bottleneck (line 11) | class Bottleneck(_Bottleneck):
    method __init__ (line 14) | def __init__(self,
    method _del_block_plugins (line 97) | def _del_block_plugins(self, plugin_names):
  class ResNeXt (line 109) | class ResNeXt(ResNet):
    method __init__ (line 142) | def __init__(self, groups=1, base_width=4, **kwargs):
    method make_res_layer (line 147) | def make_res_layer(self, **kwargs):

FILE: mmdet/models/backbones/ssd_vgg.py
  class SSDVGG (line 13) | class SSDVGG(VGG, BaseModule):
    method __init__ (line 42) | def __init__(self,
    method init_weights (line 109) | def init_weights(self, pretrained=None):
    method forward (line 112) | def forward(self, x):
    method _make_extra_layers (line 129) | def _make_extra_layers(self, outplanes):
  class L2Norm (line 156) | class L2Norm(nn.Module):
    method __init__ (line 158) | def __init__(self, n_dims, scale=20., eps=1e-10):
    method forward (line 173) | def forward(self, x):

FILE: mmdet/models/backbones/swin.py
  function _ntuple (line 20) | def _ntuple(n):
  function swin_converter (line 37) | def swin_converter(ckpt):
  class WindowMSA (line 92) | class WindowMSA(BaseModule):
    method __init__ (line 111) | def __init__(self,
    method init_weights (line 148) | def init_weights(self):
    method forward (line 151) | def forward(self, x, mask=None):
    method double_step_seq (line 192) | def double_step_seq(step1, len1, step2, len2):
  class ShiftWindowMSA (line 198) | class ShiftWindowMSA(BaseModule):
    method __init__ (line 221) | def __init__(self,
    method forward (line 251) | def forward(self, query, hw_shape):
    method window_reverse (line 327) | def window_reverse(self, windows, H, W):
    method window_partition (line 343) | def window_partition(self, x):
  class SwinBlock (line 359) | class SwinBlock(BaseModule):
    method __init__ (line 384) | def __init__(self,
    method forward (line 429) | def forward(self, x, hw_shape):
  class SwinBlockSequence (line 452) | class SwinBlockSequence(BaseModule):
    method __init__ (line 481) | def __init__(self,
    method forward (line 526) | def forward(self, x, hw_shape):
  class SwinTransformer (line 538) | class SwinTransformer(BaseModule):
    method __init__ (line 595) | def __init__(self,
    method train (line 714) | def train(self, mode=True):
    method _freeze_stages (line 719) | def _freeze_stages(self):
    method init_weights (line 741) | def init_weights(self):
    method forward (line 818) | def forward(self, x):

FILE: mmdet/models/backbones/trident_resnet.py
  class TridentConv (line 13) | class TridentConv(BaseModule):
    method __init__ (line 32) | def __init__(self,
    method extra_repr (line 60) | def extra_repr(self):
    method forward (line 72) | def forward(self, inputs):
  class TridentBottleneck (line 92) | class TridentBottleneck(Bottleneck):
    method __init__ (line 105) | def __init__(self, trident_dilations, test_branch_idx, concat_output,
    method forward (line 127) | def forward(self, x):
  function make_trident_res_layer (line 181) | def make_trident_res_layer(block,
  class TridentResNet (line 234) | class TridentResNet(ResNet):
    method __init__ (line 255) | def __init__(self, depth, num_branch, test_branch_idx, trident_dilations,

FILE: mmdet/models/builder.py
  function build_backbone (line 17) | def build_backbone(cfg):
  function build_neck (line 22) | def build_neck(cfg):
  function build_roi_extractor (line 27) | def build_roi_extractor(cfg):
  function build_shared_head (line 32) | def build_shared_head(cfg):
  function build_head (line 37) | def build_head(cfg):
  function build_loss (line 42) | def build_loss(cfg):
  function build_detector (line 47) | def build_detector(cfg, train_cfg=None, test_cfg=None):

FILE: mmdet/models/dense_heads/anchor_free_head.py
  class AnchorFreeHead (line 16) | class AnchorFreeHead(BaseDenseHead, BBoxTestMixin):
    method __init__ (line 42) | def __init__(self,
    method _init_layers (line 90) | def _init_layers(self):
    method _init_cls_convs (line 96) | def _init_cls_convs(self):
    method _init_reg_convs (line 116) | def _init_reg_convs(self):
    method _init_predictor (line 136) | def _init_predictor(self):
    method _load_from_state_dict (line 143) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
    method forward (line 181) | def forward(self, feats):
    method forward_single (line 199) | def forward_single(self, x):
    method loss (line 224) | def loss(self,
    method get_bboxes (line 253) | def get_bboxes(self,
    method get_targets (line 276) | def get_targets(self, points, gt_bboxes_list, gt_labels_list):
    method _get_points_single (line 290) | def _get_points_single(self,
    method get_points (line 308) | def get_points(self, featmap_sizes, dtype, device, flatten=False):
    method aug_test (line 326) | def aug_test(self, feats, img_metas, rescale=False):

FILE: mmdet/models/dense_heads/anchor_head.py
  class AnchorHead (line 14) | class AnchorHead(BaseDenseHead, BBoxTestMixin):
    method __init__ (line 36) | def __init__(self,
    method _init_layers (line 99) | def _init_layers(self):
    method forward_single (line 105) | def forward_single(self, x):
    method forward (line 122) | def forward(self, feats):
    method get_anchors (line 141) | def get_anchors(self, featmap_sizes, img_metas, device='cuda'):
    method _get_targets_single (line 171) | def _get_targets_single(self,
    method get_targets (line 269) | def get_targets(self,
    method loss_single (line 371) | def loss_single(self, cls_score, bbox_pred, anchors, labels, label_wei...
    method loss (line 422) | def loss(self,
    method get_bboxes (line 492) | def get_bboxes(self,
    method _get_bboxes (line 588) | def _get_bboxes(self,
    method aug_test (line 725) | def aug_test(self, feats, img_metas, rescale=False):

FILE: mmdet/models/dense_heads/atss_head.py
  class ATSSHead (line 14) | class ATSSHead(AnchorHead):
    method __init__ (line 24) | def __init__(self,
    method _init_layers (line 58) | def _init_layers(self):
    method forward (line 95) | def forward(self, feats):
    method forward_single (line 113) | def forward_single(self, x, scale):
    method loss_single (line 142) | def loss_single(self, anchors, cls_score, bbox_pred, centerness, labels,
    method loss (line 218) | def loss(self,
    method centerness_target (line 293) | def centerness_target(self, anchors, bbox_targets):
    method get_bboxes (line 312) | def get_bboxes(self,
    method _get_bboxes (line 371) | def _get_bboxes(self,
    method get_targets (line 505) | def get_targets(self,
    method _get_target_single (line 569) | def _get_target_single(self,
    method get_num_level_anchors_inside (line 679) | def get_num_level_anchors_inside(self, num_level_anchors, inside_flags):

FILE: mmdet/models/dense_heads/autoassign_head.py
  class CenterPrior (line 17) | class CenterPrior(nn.Module):
    method __init__ (line 33) | def __init__(self,
    method forward (line 45) | def forward(self, anchor_points_list, gt_bboxes, labels,
  class AutoAssignHead (line 124) | class AutoAssignHead(FCOSHead):
    method __init__ (line 143) | def __init__(self,
    method init_weights (line 161) | def init_weights(self):
    method _get_points_single (line 173) | def _get_points_single(self,
    method forward_single (line 189) | def forward_single(self, x, scale, stride):
    method get_pos_loss_single (line 214) | def get_pos_loss_single(self, cls_score, objectness, reg_loss, gt_labels,
    method get_neg_loss_single (line 258) | def get_neg_loss_single(self, cls_score, objectness, gt_labels, ious,
    method loss (line 314) | def loss(self,
    method get_targets (line 444) | def get_targets(self, points, gt_bboxes_list):
    method _get_target_single (line 481) | def _get_target_single(self, gt_bboxes, points):

FILE: mmdet/models/dense_heads/base_dense_head.py
  class BaseDenseHead (line 6) | class BaseDenseHead(BaseModule, metaclass=ABCMeta):
    method __init__ (line 9) | def __init__(self, init_cfg=None):
    method loss (line 13) | def loss(self, **kwargs):
    method get_bboxes (line 18) | def get_bboxes(self, **kwargs):
    method forward_train (line 22) | def forward_train(self,

FILE: mmdet/models/dense_heads/cascade_rpn_head.py
  class AdaptiveConv (line 18) | class AdaptiveConv(BaseModule):
    method __init__ (line 40) | def __init__(self,
    method forward (line 77) | def forward(self, x, offset):
  class StageCascadeRPNHead (line 94) | class StageCascadeRPNHead(RPNHead):
    method __init__ (line 110) | def __init__(self,
    method _init_layers (line 151) | def _init_layers(self):
    method forward_single (line 162) | def forward_single(self, x, offset):
    method forward (line 172) | def forward(self, feats, offset_list=None):
    method _region_targets_single (line 178) | def _region_targets_single(self,
    method region_targets (line 234) | def region_targets(self,
    method get_targets (line 284) | def get_targets(self,
    method anchor_offset (line 326) | def anchor_offset(self, anchor_list, anchor_strides, featmap_sizes):
    method loss_single (line 404) | def loss_single(self, cls_score, bbox_pred, anchors, labels, label_wei...
    method loss (line 434) | def loss(self,
    method get_bboxes (line 503) | def get_bboxes(self,
    method refine_bboxes (line 530) | def refine_bboxes(self, anchor_list, bbox_preds, img_metas):
    method _get_bboxes_single (line 547) | def _get_bboxes_single(self,
  class CascadeRPNHead (line 675) | class CascadeRPNHead(BaseDenseHead):
    method __init__ (line 690) | def __init__(self, num_stages, stages, train_cfg, test_cfg, init_cfg=N...
    method loss (line 705) | def loss(self):
    method get_bboxes (line 709) | def get_bboxes(self):
    method forward_train (line 713) | def forward_train(self,
    method simple_test_rpn (line 758) | def simple_test_rpn(self, x, img_metas):
    method aug_test_rpn (line 783) | def aug_test_rpn(self, x, img_metas):

FILE: mmdet/models/dense_heads/centripetal_head.py
  class CentripetalHead (line 11) | class CentripetalHead(CornerHead):
    method __init__ (line 46) | def __init__(self,
    method _init_centripetal_layers (line 71) | def _init_centripetal_layers(self):
    method _init_layers (line 131) | def _init_layers(self):
    method init_weights (line 139) | def init_weights(self):
    method forward_single (line 155) | def forward_single(self, x, lvl_ind):
    method loss (line 205) | def loss(self,
    method loss_single (line 281) | def loss_single(self, tl_hmp, br_hmp, tl_off, br_off, tl_guiding_shift,
    method get_bboxes (line 363) | def get_bboxes(self,

FILE: mmdet/models/dense_heads/corner_head.py
  class BiCornerPool (line 17) | class BiCornerPool(BaseModule):
    method __init__ (line 30) | def __init__(self,
    method forward (line 60) | def forward(self, x):
  class CornerHead (line 81) | class CornerHead(BaseDenseHead):
    method __init__ (line 114) | def __init__(self,
    method _make_layers (line 153) | def _make_layers(self, out_channels, in_channels=256, feat_channels=256):
    method _init_corner_kpt_layers (line 160) | def _init_corner_kpt_layers(self):
    method _init_corner_emb_layers (line 198) | def _init_corner_emb_layers(self):
    method _init_layers (line 216) | def _init_layers(self):
    method init_weights (line 225) | def init_weights(self):
    method forward (line 243) | def forward(self, feats):
    method forward_single (line 275) | def forward_single(self, x, lvl_ind, return_pool=False):
    method get_targets (line 320) | def get_targets(self,
    method loss (line 508) | def loss(self,
    method loss_single (line 570) | def loss_single(self, tl_hmp, br_hmp, tl_emb, br_emb, tl_off, br_off,
    method get_bboxes (line 648) | def get_bboxes(self,
    method _get_bboxes_single (line 697) | def _get_bboxes_single(self,
    method _bboxes_nms (line 775) | def _bboxes_nms(self, bboxes, labels, cfg):
    method _gather_feat (line 797) | def _gather_feat(self, feat, ind, mask=None):
    method _local_maximum (line 817) | def _local_maximum(self, heat, kernel=3):
    method _transpose_and_gather_feat (line 833) | def _transpose_and_gather_feat(self, feat, ind):
    method _topk (line 848) | def _topk(self, scores, k=20):
    method decode_heatmap (line 874) | def decode_heatmap(self,

FILE: mmdet/models/dense_heads/deformable_detr_head.py
  class DeformableDETRHead (line 16) | class DeformableDETRHead(DETRHead):
    method __init__ (line 35) | def __init__(self,
    method _init_layers (line 49) | def _init_layers(self):
    method init_weights (line 82) | def init_weights(self):
    method forward (line 96) | def forward(self, mlvl_feats, img_metas):
    method loss (line 183) | def loss(self,
    method get_bboxes (line 268) | def get_bboxes(self,

FILE: mmdet/models/dense_heads/dense_test_mixins.py
  class BBoxTestMixin (line 8) | class BBoxTestMixin(object):
    method merge_aug_bboxes (line 11) | def merge_aug_bboxes(self, aug_bboxes, aug_scores, img_metas):
    method aug_test_bboxes (line 38) | def aug_test_bboxes(self, feats, img_metas, rescale=False):

FILE: mmdet/models/dense_heads/detr_head.py
  class DETRHead (line 17) | class DETRHead(AnchorFreeHead):
    method __init__ (line 51) | def __init__(self,
    method _init_layers (line 151) | def _init_layers(self):
    method init_weights (line 166) | def init_weights(self):
    method _load_from_state_dict (line 171) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
    method forward (line 200) | def forward(self, feats, img_metas):
    method forward_single (line 224) | def forward_single(self, x, img_metas):
    method loss (line 266) | def loss(self,
    method loss_single (line 332) | def loss_single(self,
    method get_targets (line 418) | def get_targets(self,
    method _get_target_single (line 475) | def _get_target_single(self,
    method forward_train (line 546) | def forward_train(self,
    method get_bboxes (line 582) | def get_bboxes(self,
    method _get_bboxes_single (line 627) | def _get_bboxes_single(self,

FILE: mmdet/models/dense_heads/embedding_rpn_head.py
  class EmbeddingRPNHead (line 10) | class EmbeddingRPNHead(BaseModule):
    method __init__ (line 25) | def __init__(self,
    method _init_layers (line 37) | def _init_layers(self):
    method init_weights (line 43) | def init_weights(self):
    method _decode_init_proposals (line 53) | def _decode_init_proposals(self, imgs, img_metas):
    method forward_dummy (line 95) | def forward_dummy(self, img, img_metas):
    method forward_train (line 102) | def forward_train(self, img, img_metas):
    method simple_test_rpn (line 106) | def simple_test_rpn(self, img, img_metas):

FILE: mmdet/models/dense_heads/fcos_head.py
  class FCOSHead (line 16) | class FCOSHead(AnchorFreeHead):
    method __init__ (line 59) | def __init__(self,
    method _init_layers (line 105) | def _init_layers(self):
    method forward (line 112) | def forward(self, feats):
    method forward_single (line 133) | def forward_single(self, x, scale, stride):
    method loss (line 165) | def loss(self,
    method get_bboxes (line 265) | def get_bboxes(self,
    method _get_bboxes (line 330) | def _get_bboxes(self,
    method _get_points_single (line 474) | def _get_points_single(self,
    method get_targets (line 486) | def get_targets(self, points, gt_bboxes_list, gt_labels_list):
    method _get_target_single (line 547) | def _get_target_single(self, gt_bboxes, gt_labels, points, regress_ran...
    method centerness_target (line 631) | def centerness_target(self, pos_bbox_targets):

FILE: mmdet/models/dense_heads/fovea_head.py
  class FeatureAlign (line 14) | class FeatureAlign(BaseModule):
    method __init__ (line 16) | def __init__(self,
    method forward (line 39) | def forward(self, x, shape):
  class FoveaHead (line 46) | class FoveaHead(AnchorFreeHead):
    method __init__ (line 51) | def __init__(self,
    method _init_layers (line 77) | def _init_layers(self):
    method forward_single (line 117) | def forward_single(self, x):
    method _get_points_single (line 130) | def _get_points_single(self, *args, **kwargs):
    method loss (line 134) | def loss(self,
    method get_targets (line 184) | def get_targets(self, gt_bbox_list, gt_label_list, featmap_sizes, poin...
    method _get_target_single (line 206) | def _get_target_single(self,
    method get_bboxes (line 267) | def get_bboxes(self,
    method _get_bboxes_single (line 298) | def _get_bboxes_single(self,

FILE: mmdet/models/dense_heads/free_anchor_retina_head.py
  class FreeAnchorRetinaHead (line 12) | class FreeAnchorRetinaHead(RetinaHead):
    method __init__ (line 33) | def __init__(self,
    method loss (line 53) | def loss(self,
    method positive_bag_loss (line 219) | def positive_bag_loss(self, matched_cls_prob, matched_box_prob):
    method negative_bag_loss (line 246) | def negative_bag_loss(self, cls_prob, box_prob):

FILE: mmdet/models/dense_heads/fsaf_head.py
  class FSAFHead (line 14) | class FSAFHead(RetinaHead):
    method __init__ (line 42) | def __init__(self, *args, score_threshold=None, init_cfg=None, **kwargs):
    method forward_single (line 62) | def forward_single(self, x):
    method _get_targets_single (line 79) | def _get_targets_single(self,
    method loss (line 187) | def loss(self,
    method calculate_pos_recall (line 316) | def calculate_pos_recall(self, cls_scores, labels_list, pos_inds):
    method collect_loss_level_single (line 350) | def collect_loss_level_single(self, cls_loss, reg_loss, assigned_gt_inds,
    method reweight_loss_single (line 381) | def reweight_loss_single(self, cls_loss, reg_loss, assigned_gt_inds,

FILE: mmdet/models/dense_heads/ga_retina_head.py
  class GARetinaHead (line 10) | class GARetinaHead(GuidedAnchorHead):
    method __init__ (line 13) | def __init__(self,
    method _init_layers (line 44) | def _init_layers(self):
    method forward_single (line 91) | def forward_single(self, x):

FILE: mmdet/models/dense_heads/ga_rpn_head.py
  class GARPNHead (line 16) | class GARPNHead(RPNTestMixin, GuidedAnchorHead):
    method __init__ (line 19) | def __init__(self,
    method _init_layers (line 34) | def _init_layers(self):
    method forward_single (line 40) | def forward_single(self, x):
    method loss (line 49) | def loss(self,
    method _get_bboxes_single (line 72) | def _get_bboxes_single(self,

FILE: mmdet/models/dense_heads/gfl_head.py
  class Integral (line 15) | class Integral(nn.Module):
    method __init__ (line 28) | def __init__(self, reg_max=16):
    method forward (line 34) | def forward(self, x):
  class GFLHead (line 52) | class GFLHead(AnchorHead):
    method __init__ (line 85) | def __init__(self,
    method _init_layers (line 120) | def _init_layers(self):
    method forward (line 153) | def forward(self, feats):
    method forward_single (line 171) | def forward_single(self, x, scale):
    method anchor_center (line 197) | def anchor_center(self, anchors):
    method loss_single (line 210) | def loss_single(self, anchors, cls_score, bbox_pred, labels, label_wei...
    method loss (line 299) | def loss(self,
    method _get_bboxes (line 372) | def _get_bboxes(self,
    method get_targets (line 473) | def get_targets(self,
    method _get_target_single (line 537) | def _get_target_single(self,
    method get_num_level_anchors_inside (line 643) | def get_num_level_anchors_inside(self, num_level_anchors, inside_flags):

FILE: mmdet/models/dense_heads/guided_anchor_head.py
  class FeatureAdaption (line 14) | class FeatureAdaption(BaseModule):
    method __init__ (line 29) | def __init__(self,
    method forward (line 52) | def forward(self, x, shape):
  class GuidedAnchorHead (line 59) | class GuidedAnchorHead(AnchorHead):
    method __init__ (line 95) | def __init__(
    method _init_layers (line 208) | def _init_layers(self):
    method forward_single (line 223) | def forward_single(self, x):
    method forward (line 236) | def forward(self, feats):
    method get_sampled_approxs (line 239) | def get_sampled_approxs(self, featmap_sizes, img_metas, device='cuda'):
    method get_anchors (line 289) | def get_anchors(self,
    method _get_guided_anchors_single (line 340) | def _get_guided_anchors_single(self,
    method ga_loc_targets (line 374) | def ga_loc_targets(self, gt_bboxes_list, featmap_sizes):
    method _ga_shape_target_single (line 476) | def _ga_shape_target_single(self,
    method ga_shape_targets (line 539) | def ga_shape_targets(self,
    method loss_shape_single (line 605) | def loss_shape_single(self, shape_pred, bbox_anchors, bbox_gts,
    method loss_loc_single (line 629) | def loss_loc_single(self, loc_pred, loc_target, loc_weight,
    method loss (line 640) | def loss(self,
    method get_bboxes (line 746) | def get_bboxes(self,
    method _get_bboxes_single (line 790) | def _get_bboxes_single(self,

FILE: mmdet/models/dense_heads/ld_head.py
  class LDHead (line 11) | class LDHead(GFLHead):
    method __init__ (line 26) | def __init__(self,
    method loss_single (line 38) | def loss_single(self, anchors, cls_score, bbox_pred, labels, label_wei...
    method forward_train (line 142) | def forward_train(self,
    method loss (line 185) | def loss(self,

FILE: mmdet/models/dense_heads/nasfcos_head.py
  class NASFCOSHead (line 11) | class NASFCOSHead(FCOSHead):
    method __init__ (line 19) | def __init__(self, *args, init_cfg=None, **kwargs):
    method _init_layers (line 38) | def _init_layers(self):

FILE: mmdet/models/dense_heads/paa_head.py
  function levels_to_images (line 17) | def levels_to_images(mlvl_tensor):
  class PAAHead (line 45) | class PAAHead(ATSSHead):
    method __init__ (line 73) | def __init__(self,
    method loss (line 86) | def loss(self,
    method get_pos_loss (line 201) | def get_pos_loss(self, anchors, cls_score, bbox_pred, label, label_wei...
    method paa_reassign (line 257) | def paa_reassign(self, pos_losses, label, label_weight, bbox_weight,
    method gmm_separation_scheme (line 366) | def gmm_separation_scheme(self, gmm_assignment, scores, pos_inds_gmm):
    method get_targets (line 401) | def get_targets(
    method _get_targets_single (line 493) | def _get_targets_single(self,
    method _get_bboxes (line 519) | def _get_bboxes(self,
    method score_voting (line 606) | def score_voting(self, det_bboxes, det_labels, mlvl_bboxes,

FILE: mmdet/models/dense_heads/pisa_retinanet_head.py
  class PISARetinaHead (line 11) | class PISARetinaHead(RetinaHead):
    method loss (line 22) | def loss(self,

FILE: mmdet/models/dense_heads/pisa_ssd_head.py
  class PISASSDHead (line 11) | class PISASSDHead(SSDHead):
    method loss (line 13) | def loss(self,

FILE: mmdet/models/dense_heads/query_generator.py
  class InitialQueryGenerator (line 10) | class InitialQueryGenerator(BaseModule):
    method __init__ (line 16) | def __init__(self,
    method _init_layers (line 28) | def _init_layers(self):
    method init_weights (line 33) | def init_weights(self):
    method _decode_init_proposals (line 38) | def _decode_init_proposals(self, imgs, img_metas):
    method forward_dummy (line 72) | def forward_dummy(self, img, img_metas):
    method forward_train (line 79) | def forward_train(self, img, img_metas):
    method simple_test_rpn (line 83) | def simple_test_rpn(self, img, img_metas):

FILE: mmdet/models/dense_heads/reppoints_head.py
  class RepPointsHead (line 14) | class RepPointsHead(AnchorFreeHead):
    method __init__ (line 33) | def __init__(self,
    method _init_layers (line 122) | def _init_layers(self):
    method points2bbox (line 166) | def points2bbox(self, pts, y_first=True):
    method gen_grid_from_reg (line 217) | def gen_grid_from_reg(self, reg, previous_boxes):
    method forward (line 251) | def forward(self, feats):
    method forward_single (line 254) | def forward_single(self, x):
    method get_points (line 296) | def get_points(self, featmap_sizes, img_metas, device):
    method centers_to_bboxes (line 336) | def centers_to_bboxes(self, point_list):
    method offset_to_pts (line 354) | def offset_to_pts(self, center_list, pred_list):
    method _point_target_single (line 375) | def _point_target_single(self,
    method get_targets (line 447) | def get_targets(self,
    method loss_single (line 531) | def loss_single(self, cls_score, pts_pred_init, pts_pred_refine, labels,
    method loss (line 569) | def loss(self,
    method get_bboxes (line 665) | def get_bboxes(self,
    method _get_bboxes_single (line 703) | def _get_bboxes_single(self,

FILE: mmdet/models/dense_heads/retina_head.py
  class RetinaHead (line 9) | class RetinaHead(AnchorHead):
    method __init__ (line 28) | def __init__(self,
    method _init_layers (line 60) | def _init_layers(self):
    method forward_single (line 93) | def forward_single(self, x):

FILE: mmdet/models/dense_heads/retina_sepbn_head.py
  class RetinaSepBNHead (line 9) | class RetinaSepBNHead(AnchorHead):
    method __init__ (line 17) | def __init__(self,
    method _init_layers (line 35) | def _init_layers(self):
    method init_weights (line 77) | def init_weights(self):
    method forward (line 88) | def forward(self, feats):

FILE: mmdet/models/dense_heads/rpn_head.py
  class RPNHead (line 16) | class RPNHead(RPNTestMixin, AnchorHead):
    method __init__ (line 24) | def __init__(self,
    method _init_layers (line 31) | def _init_layers(self):
    method forward_single (line 39) | def forward_single(self, x):
    method loss (line 47) | def loss(self,
    method _get_bboxes (line 80) | def _get_bboxes(self,

FILE: mmdet/models/dense_heads/rpn_test_mixin.py
  class RPNTestMixin (line 9) | class RPNTestMixin(object):
    method async_simple_test_rpn (line 14) | async def async_simple_test_rpn(self, x, img_metas):
    method simple_test_rpn (line 24) | def simple_test_rpn(self, x, img_metas):
    method aug_test_rpn (line 39) | def aug_test_rpn(self, feats, img_metas):

FILE: mmdet/models/dense_heads/sabl_retina_head.py
  class SABLRetinaHead (line 16) | class SABLRetinaHead(BaseDenseHead):
    method __init__ (line 49) | def __init__(self,
    method _init_layers (line 151) | def _init_layers(self):
    method forward_single (line 182) | def forward_single(self, x):
    method forward (line 195) | def forward(self, feats):
    method get_anchors (line 198) | def get_anchors(self, featmap_sizes, img_metas, device='cuda'):
    method get_target (line 219) | def get_target(self,
    method _get_target_single (line 319) | def _get_target_single(self,
    method loss_single (line 436) | def loss_single(self, cls_score, bbox_pred, labels, label_weights,
    method loss (line 469) | def loss(self,
    method get_bboxes (line 523) | def get_bboxes(self,
    method get_bboxes_single (line 557) | def get_bboxes_single(self,

FILE: mmdet/models/dense_heads/ssd_head.py
  class SSDHead (line 15) | class SSDHead(AnchorHead):
    method __init__ (line 34) | def __init__(self,
    method forward (line 98) | def forward(self, feats):
    method loss_single (line 122) | def loss_single(self, cls_score, bbox_pred, anchor, labels, label_weig...
    method loss (line 180) | def loss(self,

FILE: mmdet/models/dense_heads/vfnet_head.py
  class VFNetHead (line 19) | class VFNetHead(ATSSHead, FCOSHead):
    method __init__ (line 65) | def __init__(self,
    method _init_layers (line 158) | def _init_layers(self):
    method forward (line 193) | def forward(self, feats):
    method forward_single (line 215) | def forward_single(self, x, scale, scale_refine, stride, reg_denom):
    method star_dcn_offset (line 273) | def star_dcn_offset(self, bbox_pred, gradient_mul, stride):
    method loss (line 315) | def loss(self,
    method get_bboxes (line 463) | def get_bboxes(self,
    method _get_bboxes_single (line 521) | def _get_bboxes_single(self,
    method _get_points_single (line 596) | def _get_points_single(self,
    method get_targets (line 619) | def get_targets(self, cls_scores, mlvl_points, gt_bboxes, gt_labels,
    method _get_target_single (line 654) | def _get_target_single(self, *args, **kwargs):
    method get_fcos_targets (line 661) | def get_fcos_targets(self, points, gt_bboxes_list, gt_labels_list):
    method get_atss_targets (line 687) | def get_atss_targets(self,
    method transform_bbox_targets (line 762) | def transform_bbox_targets(self, decoded_bboxes, mlvl_points, num_imgs):
    method _load_from_state_dict (line 787) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...

FILE: mmdet/models/dense_heads/yolact_head.py
  class YOLACTHead (line 14) | class YOLACTHead(AnchorHead):
    method __init__ (line 42) | def __init__(self,
    method _init_layers (line 87) | def _init_layers(self):
    method forward_single (line 115) | def forward_single(self, x):
    method loss (line 138) | def loss(self,
    method loss_single_OHEM (line 259) | def loss_single_OHEM(self, cls_score, bbox_pred, anchors, labels,
    method get_bboxes (line 295) | def get_bboxes(self,
    method _get_bboxes_single (line 362) | def _get_bboxes_single(self,
  class YOLACTSegmHead (line 460) | class YOLACTSegmHead(BaseModule):
    method __init__ (line 475) | def __init__(self,
    method _init_layers (line 493) | def _init_layers(self):
    method forward (line 498) | def forward(self, x):
    method loss (line 512) | def loss(self, segm_pred, gt_masks, gt_labels):
    method get_targets (line 545) | def get_targets(self, segm_pred, gt_masks, gt_labels):
  class YOLACTProtonet (line 577) | class YOLACTProtonet(BaseModule):
    method __init__ (line 596) | def __init__(self,
    method _init_layers (line 622) | def _init_layers(self):
    method forward (line 659) | def forward(self, x, coeff_pred, bboxes, img_meta, sampling_results=No...
    method loss (line 729) | def loss(self, mask_pred, gt_masks, gt_bboxes, img_meta, sampling_resu...
    method get_targets (line 802) | def get_targets(self, mask_pred, gt_masks, pos_assigned_gt_inds):
    method get_seg_masks (line 827) | def get_seg_masks(self, mask_pred, label_pred, img_meta, rescale):
    method crop (line 862) | def crop(self, masks, boxes, padding=1):
    method sanitize_coordinates (line 896) | def sanitize_coordinates(self, x1, x2, img_size, padding=0, cast=True):
  class InterpolateModule (line 928) | class InterpolateModule(BaseModule):
    method __init__ (line 934) | def __init__(self, *args, init_cfg=None, **kwargs):
    method forward (line 940) | def forward(self, x):

FILE: mmdet/models/dense_heads/yolo_head.py
  class YOLOV3Head (line 20) | class YOLOV3Head(BaseDenseHead, BBoxTestMixin):
    method __init__ (line 48) | def __init__(self,
    method num_levels (line 121) | def num_levels(self):
    method num_attrib (line 125) | def num_attrib(self):
    method _init_layers (line 131) | def _init_layers(self):
    method forward (line 149) | def forward(self, feats):
    method get_bboxes (line 172) | def get_bboxes(self,
    method _get_bboxes (line 209) | def _get_bboxes(self,
    method loss (line 396) | def loss(self,
    method loss_single (line 446) | def loss_single(self, pred_map, target_map, neg_map):
    method get_targets (line 491) | def get_targets(self, anchor_list, responsible_flag_list, gt_bboxes_list,
    method _get_targets_single (line 527) | def _get_targets_single(self, anchors, responsible_flags, gt_bboxes,
    method aug_test (line 588) | def aug_test(self, feats, img_metas, rescale=False):

FILE: mmdet/models/dense_heads/yolof_head.py
  function levels_to_images (line 14) | def levels_to_images(mlvl_tensor):
  class YOLOFHead (line 42) | class YOLOFHead(AnchorHead):
    method __init__ (line 55) | def __init__(self,
    method _init_layers (line 67) | def _init_layers(self):
    method init_weights (line 107) | def init_weights(self):
    method forward_single (line 118) | def forward_single(self, feature):
    method loss (line 136) | def loss(self,
    method get_targets (line 223) | def get_targets(self,
    method _get_targets_single (line 310) | def _get_targets_single(self,

FILE: mmdet/models/detectors/atss.py
  class ATSS (line 6) | class ATSS(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/autoassign.py
  class AutoAssign (line 6) | class AutoAssign(SingleStageDetector):
    method __init__ (line 10) | def __init__(self,

FILE: mmdet/models/detectors/base.py
  class BaseDetector (line 13) | class BaseDetector(BaseModule, metaclass=ABCMeta):
    method __init__ (line 16) | def __init__(self, init_cfg=None):
    method with_neck (line 21) | def with_neck(self):
    method with_shared_head (line 28) | def with_shared_head(self):
    method with_bbox (line 33) | def with_bbox(self):
    method with_mask (line 39) | def with_mask(self):
    method extract_feat (line 45) | def extract_feat(self, imgs):
    method extract_feats (line 49) | def extract_feats(self, imgs):
    method forward_train (line 62) | def forward_train(self, imgs, img_metas, **kwargs):
    method async_simple_test (line 81) | async def async_simple_test(self, img, img_metas, **kwargs):
    method simple_test (line 85) | def simple_test(self, img, img_metas, **kwargs):
    method aug_test (line 89) | def aug_test(self, imgs, img_metas, **kwargs):
    method aforward_test (line 93) | async def aforward_test(self, *, img, img_metas, **kwargs):
    method forward_test (line 111) | def forward_test(self, imgs, img_metas, **kwargs):
    method forward (line 156) | def forward(self, img, img_metas, return_loss=True, **kwargs):
    method _parse_losses (line 171) | def _parse_losses(self, losses):
    method train_step (line 206) | def train_step(self, data, optimizer):
    method val_step (line 241) | def val_step(self, data, optimizer):
    method show_result (line 256) | def show_result(self,

FILE: mmdet/models/detectors/cascade_rcnn.py
  class CascadeRCNN (line 6) | class CascadeRCNN(TwoStageDetector):
    method __init__ (line 10) | def __init__(self,
    method show_result (line 29) | def show_result(self, data, result, **kwargs):

FILE: mmdet/models/detectors/cornernet.py
  class CornerNet (line 9) | class CornerNet(SingleStageDetector):
    method __init__ (line 16) | def __init__(self,
    method merge_aug_results (line 27) | def merge_aug_results(self, aug_results, img_metas):
    method aug_test (line 61) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdet/models/detectors/deformable_detr.py
  class DeformableDETR (line 6) | class DeformableDETR(DETR):
    method __init__ (line 8) | def __init__(self, *args, **kwargs):

FILE: mmdet/models/detectors/detr.py
  class DETR (line 7) | class DETR(SingleStageDetector):
    method __init__ (line 11) | def __init__(self,
    method simple_test (line 21) | def simple_test(self, img, img_metas, rescale=False):

FILE: mmdet/models/detectors/fast_rcnn.py
  class FastRCNN (line 6) | class FastRCNN(TwoStageDetector):
    method __init__ (line 9) | def __init__(self,
    method forward_test (line 26) | def forward_test(self, imgs, img_metas, proposals, **kwargs):

FILE: mmdet/models/detectors/faster_rcnn.py
  class FasterRCNN (line 6) | class FasterRCNN(TwoStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/fcos.py
  class FCOS (line 6) | class FCOS(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/fovea.py
  class FOVEA (line 6) | class FOVEA(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/fsaf.py
  class FSAF (line 6) | class FSAF(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/gfl.py
  class GFL (line 6) | class GFL(SingleStageDetector):
    method __init__ (line 8) | def __init__(self,

FILE: mmdet/models/detectors/grid_rcnn.py
  class GridRCNN (line 6) | class GridRCNN(TwoStageDetector):
    method __init__ (line 14) | def __init__(self,

FILE: mmdet/models/detectors/htc.py
  class HybridTaskCascade (line 6) | class HybridTaskCascade(CascadeRCNN):
    method __init__ (line 9) | def __init__(self, **kwargs):
    method with_semantic (line 13) | def with_semantic(self):

FILE: mmdet/models/detectors/kd_one_stage.py
  class KnowledgeDistillationSingleStageDetector (line 11) | class KnowledgeDistillationSingleStageDetector(SingleStageDetector):
    method __init__ (line 22) | def __init__(self,
    method forward_train (line 43) | def forward_train(self,
    method cuda (line 75) | def cuda(self, device=None):
    method train (line 81) | def train(self, mode=True):
    method __setattr__ (line 89) | def __setattr__(self, name, value):

FILE: mmdet/models/detectors/mask_rcnn.py
  class MaskRCNN (line 6) | class MaskRCNN(TwoStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/mask_scoring_rcnn.py
  class MaskScoringRCNN (line 6) | class MaskScoringRCNN(TwoStageDetector):
    method __init__ (line 12) | def __init__(self,

FILE: mmdet/models/detectors/nasfcos.py
  class NASFCOS (line 6) | class NASFCOS(SingleStageDetector):
    method __init__ (line 12) | def __init__(self,

FILE: mmdet/models/detectors/paa.py
  class PAA (line 6) | class PAA(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/point_rend.py
  class PointRend (line 6) | class PointRend(TwoStageDetector):
    method __init__ (line 14) | def __init__(self,

FILE: mmdet/models/detectors/query_based.py
  class QueryBased (line 7) | class QueryBased(SparseRCNN):

FILE: mmdet/models/detectors/reppoints_detector.py
  class RepPointsDetector (line 6) | class RepPointsDetector(SingleStageDetector):
    method __init__ (line 13) | def __init__(self,

FILE: mmdet/models/detectors/retinanet.py
  class RetinaNet (line 6) | class RetinaNet(SingleStageDetector):
    method __init__ (line 9) | def __init__(self,

FILE: mmdet/models/detectors/rpn.py
  class RPN (line 11) | class RPN(BaseDetector):
    method __init__ (line 14) | def __init__(self,
    method extract_feat (line 33) | def extract_feat(self, img):
    method forward_dummy (line 48) | def forward_dummy(self, img):
    method forward_train (line 54) | def forward_train(self,
    method simple_test (line 85) | def simple_test(self, img, img_metas, rescale=False):
    method aug_test (line 111) | def aug_test(self, imgs, img_metas, rescale=False):
    method show_result (line 136) | def show_result(self, data, result, top_k=20, **kwargs):

FILE: mmdet/models/detectors/scnet.py
  class SCNet (line 6) | class SCNet(CascadeRCNN):
    method __init__ (line 9) | def __init__(self, **kwargs):

FILE: mmdet/models/detectors/single_stage.py
  class SingleStageDetector (line 9) | class SingleStageDetector(BaseDetector):
    method __init__ (line 16) | def __init__(self,
    method extract_feat (line 35) | def extract_feat(self, img):
    method forward_dummy (line 42) | def forward_dummy(self, img):
    method forward_train (line 51) | def forward_train(self,
    method simple_test (line 81) | def simple_test(self, img, img_metas, rescale=False):
    method aug_test (line 114) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdet/models/detectors/sparse_rcnn.py
  class SparseRCNN (line 6) | class SparseRCNN(TwoStageDetector):
    method __init__ (line 10) | def __init__(self, *args, **kwargs):
    method forward_train (line 14) | def forward_train(self,
    method simple_test (line 66) | def simple_test(self, img, img_metas, rescale=False):
    method forward_dummy (line 92) | def forward_dummy(self, img):

FILE: mmdet/models/detectors/trident_faster_rcnn.py
  class TridentFasterRCNN (line 6) | class TridentFasterRCNN(FasterRCNN):
    method __init__ (line 9) | def __init__(self,
    method simple_test (line 33) | def simple_test(self, img, img_metas, proposals=None, rescale=False):
    method aug_test (line 47) | def aug_test(self, imgs, img_metas, rescale=False):
    method forward_train (line 60) | def forward_train(self, img, img_metas, gt_bboxes, gt_labels, **kwargs):

FILE: mmdet/models/detectors/two_stage.py
  class TwoStageDetector (line 8) | class TwoStageDetector(BaseDetector):
    method __init__ (line 15) | def __init__(self,
    method with_rpn (line 50) | def with_rpn(self):
    method with_roi_head (line 55) | def with_roi_head(self):
    method extract_feat (line 59) | def extract_feat(self, img):
    method forward_dummy (line 66) | def forward_dummy(self, img):
    method forward_train (line 84) | def forward_train(self,
    method async_simple_test (line 148) | async def async_simple_test(self,
    method simple_test (line 166) | def simple_test(self, img, img_metas, proposals=None, rescale=False):
    method aug_test (line 185) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdet/models/detectors/vfnet.py
  class VFNet (line 6) | class VFNet(SingleStageDetector):
    method __init__ (line 10) | def __init__(self,

FILE: mmdet/models/detectors/yolact.py
  class YOLACT (line 9) | class YOLACT(SingleStageDetector):
    method __init__ (line 12) | def __init__(self,
    method forward_dummy (line 27) | def forward_dummy(self, img):
    method forward_train (line 34) | def forward_train(self,
    method simple_test (line 93) | def simple_test(self, img, img_metas, rescale=False):
    method aug_test (line 139) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdet/models/detectors/yolo.py
  class YOLOV3 (line 8) | class YOLOV3(SingleStageDetector):
    method __init__ (line 10) | def __init__(self,

FILE: mmdet/models/detectors/yolof.py
  class YOLOF (line 6) | class YOLOF(SingleStageDetector):
    method __init__ (line 10) | def __init__(self,

FILE: mmdet/models/losses/accuracy.py
  function accuracy (line 6) | def accuracy(pred, target, topk=1, thresh=None):
  class Accuracy (line 53) | class Accuracy(nn.Module):
    method __init__ (line 55) | def __init__(self, topk=(1, ), thresh=None):
    method forward (line 68) | def forward(self, pred, target):

FILE: mmdet/models/losses/ae_loss.py
  function ae_loss_per_image (line 10) | def ae_loss_per_image(tl_preds, br_preds, match):
  class AssociativeEmbeddingLoss (line 74) | class AssociativeEmbeddingLoss(nn.Module):
    method __init__ (line 87) | def __init__(self, pull_weight=0.25, push_weight=0.25):
    method forward (line 92) | def forward(self, pred, target, match):

FILE: mmdet/models/losses/balanced_l1_loss.py
  function balanced_l1_loss (line 12) | def balanced_l1_loss(pred,
  class BalancedL1Loss (line 53) | class BalancedL1Loss(nn.Module):
    method __init__ (line 70) | def __init__(self,
    method forward (line 83) | def forward(self,

FILE: mmdet/models/losses/cross_entropy_loss.py
  function cross_entropy (line 9) | def cross_entropy(pred,
  function _expand_onehot_labels (line 42) | def _expand_onehot_labels(labels, label_weights, label_channels):
  function binary_cross_entropy (line 58) | def binary_cross_entropy(pred,
  function mask_cross_entropy (line 94) | def mask_cross_entropy(pred,
  class CrossEntropyLoss (line 142) | class CrossEntropyLoss(nn.Module):
    method __init__ (line 144) | def __init__(self,
    method forward (line 178) | def forward(self,

FILE: mmdet/models/losses/focal_loss.py
  function py_sigmoid_focal_loss (line 11) | def py_sigmoid_focal_loss(pred,
  function sigmoid_focal_loss (line 59) | def sigmoid_focal_loss(pred,
  class FocalLoss (line 106) | class FocalLoss(nn.Module):
    method __init__ (line 108) | def __init__(self,
    method forward (line 136) | def forward(self,

FILE: mmdet/models/losses/gaussian_focal_loss.py
  function gaussian_focal_loss (line 10) | def gaussian_focal_loss(pred, gaussian_target, alpha=2.0, gamma=4.0):
  class GaussianFocalLoss (line 32) | class GaussianFocalLoss(nn.Module):
    method __init__ (line 49) | def __init__(self,
    method forward (line 60) | def forward(self,

FILE: mmdet/models/losses/gfocal_loss.py
  function quality_focal_loss (line 11) | def quality_focal_loss(pred, target, beta=2.0):
  function distribution_focal_loss (line 56) | def distribution_focal_loss(pred, label):
  class QualityFocalLoss (line 81) | class QualityFocalLoss(nn.Module):
    method __init__ (line 95) | def __init__(self,
    method forward (line 107) | def forward(self,
  class DistributionFocalLoss (line 146) | class DistributionFocalLoss(nn.Module):
    method __init__ (line 156) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 161) | def forward(self,

FILE: mmdet/models/losses/ghm_loss.py
  function _expand_onehot_labels (line 8) | def _expand_onehot_labels(labels, label_weights, label_channels):
  class GHMC (line 21) | class GHMC(nn.Module):
    method __init__ (line 35) | def __init__(self, bins=10, momentum=0, use_sigmoid=True, loss_weight=...
    method forward (line 50) | def forward(self, pred, target, label_weight, *args, **kwargs):
  class GHMR (line 99) | class GHMR(nn.Module):
    method __init__ (line 113) | def __init__(self, mu=0.02, bins=10, momentum=0, loss_weight=1.0):
    method forward (line 127) | def forward(self, pred, target, label_weight, avg_factor=None):

FILE: mmdet/models/losses/iou_loss.py
  function iou_loss (line 14) | def iou_loss(pred, target, linear=False, eps=1e-6):
  function bounded_iou_loss (line 41) | def bounded_iou_loss(pred, target, beta=0.2, eps=1e-3):
  function giou_loss (line 87) | def giou_loss(pred, target, eps=1e-7):
  function diou_loss (line 107) | def diou_loss(pred, target, eps=1e-7):
  function ciou_loss (line 162) | def ciou_loss(pred, target, eps=1e-7):
  class IoULoss (line 223) | class IoULoss(nn.Module):
    method __init__ (line 236) | def __init__(self,
    method forward (line 247) | def forward(self,
  class BoundedIoULoss (line 294) | class BoundedIoULoss(nn.Module):
    method __init__ (line 296) | def __init__(self, beta=0.2, eps=1e-3, reduction='mean', loss_weight=1...
    method forward (line 303) | def forward(self,
  class GIoULoss (line 330) | class GIoULoss(nn.Module):
    method __init__ (line 332) | def __init__(self, eps=1e-6, reduction='mean', loss_weight=1.0):
    method forward (line 338) | def forward(self,
  class DIoULoss (line 370) | class DIoULoss(nn.Module):
    method __init__ (line 372) | def __init__(self, eps=1e-6, reduction='mean', loss_weight=1.0):
    method forward (line 378) | def forward(self,
  class CIoULoss (line 410) | class CIoULoss(nn.Module):
    method __init__ (line 412) | def __init__(self, eps=1e-6, reduction='mean', loss_weight=1.0):
    method forward (line 418) | def forward(self,

FILE: mmdet/models/losses/kd_loss.py
  function knowledge_distillation_kl_div_loss (line 11) | def knowledge_distillation_kl_div_loss(pred,
  class KnowledgeDistillationKLDivLoss (line 39) | class KnowledgeDistillationKLDivLoss(nn.Module):
    method __init__ (line 48) | def __init__(self, reduction='mean', loss_weight=1.0, T=10):
    method forward (line 55) | def forward(self,

FILE: mmdet/models/losses/mse_loss.py
  function mse_loss (line 9) | def mse_loss(pred, target):
  class MSELoss (line 15) | class MSELoss(nn.Module):
    method __init__ (line 24) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 29) | def forward(self, pred, target, weight=None, avg_factor=None):

FILE: mmdet/models/losses/pisa_loss.py
  function isr_p (line 8) | def isr_p(cls_score,
  function carl_loss (line 122) | def carl_loss(cls_score,

FILE: mmdet/models/losses/smooth_l1_loss.py
  function smooth_l1_loss (line 11) | def smooth_l1_loss(pred, target, beta=1.0):
  function l1_loss (line 33) | def l1_loss(pred, target):
  class SmoothL1Loss (line 49) | class SmoothL1Loss(nn.Module):
    method __init__ (line 60) | def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0):
    method forward (line 66) | def forward(self,
  class L1Loss (line 101) | class L1Loss(nn.Module):
    method __init__ (line 110) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 115) | def forward(self,

FILE: mmdet/models/losses/utils.py
  function reduce_loss (line 7) | def reduce_loss(loss, reduction):
  function weight_reduce_loss (line 28) | def weight_reduce_loss(loss, weight=None, reduction='mean', avg_factor=N...
  function weighted_loss (line 57) | def weighted_loss(loss_func):

FILE: mmdet/models/losses/varifocal_loss.py
  function varifocal_loss (line 10) | def varifocal_loss(pred,
  class VarifocalLoss (line 59) | class VarifocalLoss(nn.Module):
    method __init__ (line 61) | def __init__(self,
    method forward (line 96) | def forward(self,

FILE: mmdet/models/necks/bfp.py
  class BFP (line 10) | class BFP(BaseModule):
    method __init__ (line 32) | def __init__(self,
    method forward (line 69) | def forward(self, inputs):

FILE: mmdet/models/necks/channel_mapper.py
  class ChannelMapper (line 9) | class ChannelMapper(BaseModule):
    method __init__ (line 45) | def __init__(self,
    method forward (line 89) | def forward(self, inputs):

FILE: mmdet/models/necks/dilated_encoder.py
  class Bottleneck (line 9) | class Bottleneck(nn.Module):
    method __init__ (line 23) | def __init__(self,
    method forward (line 41) | def forward(self, x):
  class DilatedEncoder (line 51) | class DilatedEncoder(nn.Module):
    method __init__ (line 66) | def __init__(self, in_channels, out_channels, block_mid_channels,
    method _init_layers (line 76) | def _init_layers(self):
    method init_weights (line 93) | def init_weights(self):
    method forward (line 104) | def forward(self, feature):

FILE: mmdet/models/necks/fpg.py
  class Transition (line 9) | class Transition(BaseModule):
    method __init__ (line 17) | def __init__(self, in_channels, out_channels, init_cfg=None):
    method forward (line 22) | def forward(x):
  class UpInterpolationConv (line 26) | class UpInterpolationConv(Transition):
    method __init__ (line 42) | def __init__(self,
    method forward (line 62) | def forward(self, x):
  class LastConv (line 72) | class LastConv(Transition):
    method __init__ (line 82) | def __init__(self,
    method forward (line 98) | def forward(self, inputs):
  class FPG (line 104) | class FPG(BaseModule):
    method __init__ (line 149) | def __init__(self,
    method build_trans (line 316) | def build_trans(self, cfg, in_channels, out_channels, **extra_args):
    method fuse (line 322) | def fuse(self, fuse_dict):
    method forward (line 332) | def forward(self, inputs):

FILE: mmdet/models/necks/fpn.py
  class FPN (line 12) | class FPN(BaseModule):
    method __init__ (line 67) | def __init__(self,
    method forward (line 166) | def forward(self, inputs):

FILE: mmdet/models/necks/fpn_carafe.py
  class FPN_CARAFE (line 10) | class FPN_CARAFE(BaseModule):
    method __init__ (line 36) | def __init__(self,
    method init_weights (line 208) | def init_weights(self):
    method slice_as (line 218) | def slice_as(self, src, dst):
    method tensor_add (line 238) | def tensor_add(self, a, b):
    method forward (line 246) | def forward(self, inputs):

FILE: mmdet/models/necks/hrfpn.py
  class HRFPN (line 12) | class HRFPN(BaseModule):
    method __init__ (line 32) | def __init__(self,
    method forward (line 76) | def forward(self, inputs):

FILE: mmdet/models/necks/identity_fpn.py
  class ChannelMapping (line 13) | class ChannelMapping(BaseModule):
    method __init__ (line 18) | def __init__(self,
    method forward (line 101) | def forward(self, inputs):

FILE: mmdet/models/necks/nas_fpn.py
  class NASFPN (line 10) | class NASFPN(BaseModule):
    method __init__ (line 32) | def __init__(self,
    method forward (line 126) | def forward(self, inputs):

FILE: mmdet/models/necks/nasfcos_fpn.py
  class NASFCOS_FPN (line 11) | class NASFCOS_FPN(BaseModule):
    method __init__ (line 34) | def __init__(self,
    method forward (line 121) | def forward(self, inputs):
    method init_weights (line 155) | def init_weights(self):

FILE: mmdet/models/necks/pafpn.py
  class PAFPN (line 11) | class PAFPN(FPN):
    method __init__ (line 40) | def __init__(self,
    method forward (line 96) | def forward(self, inputs):

FILE: mmdet/models/necks/rfp.py
  class ASPP (line 11) | class ASPP(BaseModule):
    method __init__ (line 25) | def __init__(self,
    method forward (line 47) | def forward(self, x):
  class RFP (line 59) | class RFP(FPN):
    method __init__ (line 77) | def __init__(self,
    method init_weights (line 104) | def init_weights(self):
    method forward (line 116) | def forward(self, inputs):

FILE: mmdet/models/necks/yolo_neck.py
  class DetectionBlock (line 11) | class DetectionBlock(BaseModule):
    method __init__ (line 34) | def __init__(self,
    method forward (line 54) | def forward(self, x):
  class YOLOV3Neck (line 64) | class YOLOV3Neck(BaseModule):
    method __init__ (line 90) | def __init__(self,
    method forward (line 117) | def forward(self, feats):

FILE: mmdet/models/roi_heads/adamixer_decoder.py
  class AdaMixerDecoder (line 13) | class AdaMixerDecoder(CascadeRoIHead):
    method __init__ (line 16) | def __init__(self,
    method _bbox_forward (line 54) | def _bbox_forward(self, stage, img_feat, query_xyzr, query_content, im...
    method forward_train (line 86) | def forward_train(self,
    method simple_test (line 147) | def simple_test(self,
    method aug_test (line 199) | def aug_test(self, x, bboxes_list, img_metas, rescale=False):
    method forward_dummy (line 202) | def forward_dummy(self, x,

FILE: mmdet/models/roi_heads/base_roi_head.py
  class BaseRoIHead (line 8) | class BaseRoIHead(BaseModule, metaclass=ABCMeta):
    method __init__ (line 11) | def __init__(self,
    method with_bbox (line 37) | def with_bbox(self):
    method with_mask (line 42) | def with_mask(self):
    method with_shared_head (line 47) | def with_shared_head(self):
    method init_bbox_head (line 52) | def init_bbox_head(self):
    method init_mask_head (line 57) | def init_mask_head(self):
    method init_assigner_sampler (line 62) | def init_assigner_sampler(self):
    method forward_train (line 67) | def forward_train(self,
    method async_simple_test (line 78) | async def async_simple_test(self,
    method simple_test (line 88) | def simple_test(self,
    method aug_test (line 97) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):

FILE: mmdet/models/roi_heads/bbox_heads/adamixer_decoder_stage.py
  function dprint (line 26) | def dprint(*args, **kwargs):
  function decode_box (line 32) | def decode_box(xyzr):
  function make_sample_points (line 42) | def make_sample_points(offset, num_group, xyzr):
  class AdaptiveSamplingMixing (line 69) | class AdaptiveSamplingMixing(nn.Module):
    method __init__ (line 72) | def __init__(self,
    method init_weights (line 103) | def init_weights(self):
    method forward (line 131) | def forward(self, x, query_feat, query_xyzr, featmap_strides):
  function position_embedding (line 159) | def position_embedding(token_xyzr, num_feats, temperature=10000):
  class AdaMixerDecoderStage (line 174) | class AdaMixerDecoderStage(BBoxHead):
    method __init__ (line 177) | def __init__(self,
    method init_weights (line 257) | def init_weights(self):
    method forward (line 276) | def forward(self,
    method refine_xyzr (line 327) | def refine_xyzr(self, xyzr, xyzr_delta, return_bbox=True):
    method loss (line 338) | def loss(self,
    method _get_target_single (line 387) | def _get_target_single(self, pos_inds, neg_inds, pos_bboxes, neg_bboxes,
    method get_targets (line 418) | def get_targets(self,

FILE: mmdet/models/roi_heads/bbox_heads/adaptive_mixing_operator.py
  function dprint (line 6) | def dprint(*args, **kwargs):
  class SRShadowForFlops (line 17) | class SRShadowForFlops(nn.Module):
    method __init__ (line 18) | def __init__(self, in_dim, in_points, n_groups, query_dim=None,
    method forward (line 32) | def forward(self, x, query):
    method __user_flops_handle__ (line 36) | def __user_flops_handle__(module, input, output):
  class AdaptiveMixing (line 50) | class AdaptiveMixing(nn.Module):
    method __init__ (line 51) | def __init__(self, in_dim, in_points, n_groups, query_dim=None,
    method init_weights (line 92) | def init_weights(self):
    method forward (line 95) | def forward(self, x, query):

FILE: mmdet/models/roi_heads/bbox_heads/bbox_head.py
  class BBoxHead (line 13) | class BBoxHead(BaseModule):
    method __init__ (line 17) | def __init__(self,
    method forward (line 81) | def forward(self, x):
    method _get_target_single (line 89) | def _get_target_single(self, pos_bboxes, neg_bboxes, pos_gt_bboxes,
    method get_targets (line 155) | def get_targets(self,
    method loss (line 223) | def loss(self,
    method get_bboxes (line 274) | def get_bboxes(self,
    method refine_bboxes (line 420) | def refine_bboxes(self, rois, labels, bbox_preds, pos_is_gts, img_metas):
    method regress_by_class (line 499) | def regress_by_class(self, rois, label, bbox_pred, img_meta):

FILE: mmdet/models/roi_heads/bbox_heads/convfc_bbox_head.py
  class ConvFCBBoxHead (line 9) | class ConvFCBBoxHead(BBoxHead):
    method __init__ (line 20) | def __init__(self,
    method _add_conv_fc_branch (line 99) | def _add_conv_fc_branch(self,
    method forward (line 140) | def forward(self, x):
  class Shared2FCBBoxHead (line 182) | class Shared2FCBBoxHead(ConvFCBBoxHead):
    method __init__ (line 184) | def __init__(self, fc_out_channels=1024, *args, **kwargs):
  class Shared4Conv1FCBBoxHead (line 198) | class Shared4Conv1FCBBoxHead(ConvFCBBoxHead):
    method __init__ (line 200) | def __init__(self, fc_out_channels=1024, *args, **kwargs):

FILE: mmdet/models/roi_heads/bbox_heads/dii_head.py
  class DIIHead (line 17) | class DIIHead(BBoxHead):
    method __init__ (line 45) | def __init__(self,
    method init_weights (line 124) | def init_weights(self):
    method forward (line 140) | def forward(self, roi_feat, proposal_feat):
    method loss (line 197) | def loss(self,
    method _get_target_single (line 281) | def _get_target_single(self, pos_inds, neg_inds, pos_bboxes, neg_bboxes,
    method get_targets (line 354) | def get_targets(self,

FILE: mmdet/models/roi_heads/bbox_heads/double_bbox_head.py
  class BasicResBlock (line 10) | class BasicResBlock(BaseModule):
    method __init__ (line 25) | def __init__(self,
    method forward (line 62) | def forward(self, x):
  class DoubleConvFCBBoxHead (line 76) | class DoubleConvFCBBoxHead(BBoxHead):
    method __init__ (line 90) | def __init__(self,
    method _add_conv_branch (line 135) | def _add_conv_branch(self):
    method _add_fc_branch (line 147) | def _add_fc_branch(self):
    method forward (line 157) | def forward(self, x_cls, x_reg):

FILE: mmdet/models/roi_heads/bbox_heads/sabl_head.py
  class SABLHead (line 14) | class SABLHead(BaseModule):
    method __init__ (line 57) | def __init__(self,
    method _add_fc_branch (line 208) | def _add_fc_branch(self, num_branch_fcs, in_channels, roi_feat_size,
    method cls_forward (line 217) | def cls_forward(self, cls_x):
    method attention_pool (line 224) | def attention_pool(self, reg_x):
    method side_aware_feature_extractor (line 237) | def side_aware_feature_extractor(self, reg_x):
    method reg_pred (line 258) | def reg_pred(self, x, offset_fcs, cls_fcs):
    method side_aware_split (line 276) | def side_aware_split(self, feat):
    method bbox_pred_split (line 288) | def bbox_pred_split(self, bbox_pred, num_proposals_per_img):
    method reg_forward (line 297) | def reg_forward(self, reg_x):
    method forward (line 316) | def forward(self, x):
    method get_targets (line 323) | def get_targets(self, sampling_results, gt_bboxes, gt_labels,
    method bucket_target (line 338) | def bucket_target(self,
    method _bucket_target_single (line 364) | def _bucket_target_single(self, pos_proposals, neg_proposals,
    method loss (line 427) | def loss(self,
    method get_bboxes (line 472) | def get_bboxes(self,
    method refine_bboxes (line 514) | def refine_bboxes(self, rois, labels, bbox_preds, pos_is_gts, img_metas):
    method regress_by_class (line 560) | def regress_by_class(self, rois, label, bbox_pred, img_meta):

FILE: mmdet/models/roi_heads/bbox_heads/sampling_3d_operator.py
  function sampling_each_level (line 7) | def sampling_each_level(sample_points: torch.Tensor,
  function translate_to_linear_weight (line 48) | def translate_to_linear_weight(ref: torch.Tensor, num_total,
  function sampling_3d (line 65) | def sampling_3d(

FILE: mmdet/models/roi_heads/bbox_heads/scnet_bbox_head.py
  class SCNetBBoxHead (line 6) | class SCNetBBoxHead(ConvFCBBoxHead):
    method _forward_shared (line 13) | def _forward_shared(self, x):
    method _forward_cls_reg (line 30) | def _forward_cls_reg(self, x):
    method forward (line 58) | def forward(self, x, return_shared_feat=False):

FILE: mmdet/models/roi_heads/cascade_roi_head.py
  class CascadeRoIHead (line 14) | class CascadeRoIHead(BaseRoIHead, BBoxTestMixin, MaskTestMixin):
    method __init__ (line 20) | def __init__(self,
    method init_bbox_head (line 50) | def init_bbox_head(self, bbox_roi_extractor, bbox_head):
    method init_mask_head (line 70) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method init_assigner_sampler (line 98) | def init_assigner_sampler(self):
    method forward_dummy (line 110) | def forward_dummy(self, x, proposals):
    method _bbox_forward (line 128) | def _bbox_forward(self, stage, x, rois):
    method _bbox_forward_train (line 141) | def _bbox_forward_train(self, stage, x, sampling_results, gt_bboxes,
    method _mask_forward (line 156) | def _mask_forward(self, stage, x, rois):
    method _mask_forward_train (line 168) | def _mask_forward_train(self,
    method forward_train (line 189) | def forward_train(self,
    method simple_test (line 278) | def simple_test(self, x, proposal_list, img_metas, rescale=False):
    method aug_test (line 404) | def aug_test(self, features, proposal_list, img_metas, rescale=False):

FILE: mmdet/models/roi_heads/double_roi_head.py
  class DoubleHeadRoIHead (line 6) | class DoubleHeadRoIHead(StandardRoIHead):
    method __init__ (line 12) | def __init__(self, reg_roi_scale_factor, **kwargs):
    method _bbox_forward (line 16) | def _bbox_forward(self, x, rois):

FILE: mmdet/models/roi_heads/dynamic_roi_head.py
  class DynamicRoIHead (line 13) | class DynamicRoIHead(StandardRoIHead):
    method __init__ (line 16) | def __init__(self, **kwargs):
    method forward_train (line 24) | def forward_train(self,
    method _bbox_forward_train (line 108) | def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels,
    method update_hyperparameters (line 133) | def update_hyperparameters(self):

FILE: mmdet/models/roi_heads/grid_roi_head.py
  class GridRoIHead (line 9) | class GridRoIHead(StandardRoIHead):
    method __init__ (line 15) | def __init__(self, grid_roi_extractor, grid_head, **kwargs):
    method _random_jitter (line 26) | def _random_jitter(self, sampling_results, img_metas, amplitude=0.15):
    method forward_dummy (line 51) | def forward_dummy(self, x, proposals):
    method _bbox_forward_train (line 77) | def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels,
    method simple_test (line 115) | def simple_test(self,

FILE: mmdet/models/roi_heads/htc_roi_head.py
  class HybridTaskCascadeRoIHead (line 11) | class HybridTaskCascadeRoIHead(CascadeRoIHead):
    method __init__ (line 17) | def __init__(self,
    method with_semantic (line 41) | def with_semantic(self):
    method forward_dummy (line 48) | def forward_dummy(self, x, proposals):
    method _bbox_forward_train (line 83) | def _bbox_forward_train(self,
    method _mask_forward_train (line 110) | def _mask_forward_train(self,
    method _bbox_forward (line 155) | def _bbox_forward(self, stage, x, rois, semantic_feat=None):
    method _mask_forward_test (line 173) | def _mask_forward_test(self, stage, x, bboxes, semantic_feat=None):
    method forward_train (line 202) | def forward_train(self,
    method simple_test (line 327) | def simple_test(self, x, proposal_list, img_metas, rescale=False):
    method aug_test (line 461) | def aug_test(self, img_feats, proposal_list, img_metas, rescale=False):

FILE: mmdet/models/roi_heads/mask_heads/coarse_mask_head.py
  class CoarseMaskHead (line 9) | class CoarseMaskHead(FCNMaskHead):
    method __init__ (line 25) | def __init__(self,
    method init_weights (line 83) | def init_weights(self):
    method forward (line 87) | def forward(self, x):

FILE: mmdet/models/roi_heads/mask_heads/fcn_mask_head.py
  class FCNMaskHead (line 22) | class FCNMaskHead(BaseModule):
    method __init__ (line 24) | def __init__(self,
    method init_weights (line 111) | def init_weights(self):
    method forward (line 124) | def forward(self, x):
    method get_targets (line 134) | def get_targets(self, sampling_results, gt_masks, rcnn_train_cfg):
    method loss (line 144) | def loss(self, mask_pred, mask_targets, labels):
    method get_seg_masks (line 175) | def get_seg_masks(self, mask_pred, det_bboxes, det_labels, rcnn_test_cfg,
  function _do_paste_mask (line 325) | def _do_paste_mask(masks, boxes, img_h, img_w, skip_empty=True):

FILE: mmdet/models/roi_heads/mask_heads/feature_relay_head.py
  class FeatureRelayHead (line 8) | class FeatureRelayHead(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method forward (line 42) | def forward(self, x):

FILE: mmdet/models/roi_heads/mask_heads/fused_semantic_head.py
  class FusedSemanticHead (line 10) | class FusedSemanticHead(BaseModule):
    method __init__ (line 26) | def __init__(self,
    method forward (line 85) | def forward(self, feats):
    method loss (line 102) | def loss(self, mask_pred, labels):

FILE: mmdet/models/roi_heads/mask_heads/global_context_head.py
  class GlobalContextHead (line 10) | class GlobalContextHead(BaseModule):
    method __init__ (line 28) | def __init__(self,
    method forward (line 79) | def forward(self, feats):
    method loss (line 93) | def loss(self, pred, labels):

FILE: mmdet/models/roi_heads/mask_heads/grid_head.py
  class GridHead (line 12) | class GridHead(BaseModule):
    method __init__ (line 14) | def __init__(self,
    method forward (line 154) | def forward(self, x):
    method calc_sub_regions (line 192) | def calc_sub_regions(self):
    method get_targets (line 223) | def get_targets(self, sampling_results, rcnn_train_cfg):
    method loss (line 291) | def loss(self, grid_pred, grid_targets):
    method get_bboxes (line 297) | def get_bboxes(self, det_bboxes, grid_pred, img_metas):

FILE: mmdet/models/roi_heads/mask_heads/htc_mask_head.py
  class HTCMaskHead (line 8) | class HTCMaskHead(FCNMaskHead):
    method __init__ (line 10) | def __init__(self, with_conv_res=True, *args, **kwargs):
    method forward (line 21) | def forward(self, x, res_feat=None, return_logits=True, return_feat=Tr...

FILE: mmdet/models/roi_heads/mask_heads/mask_point_head.py
  class MaskPointHead (line 13) | class MaskPointHead(BaseModule):
    method __init__ (line 39) | def __init__(self,
    method forward (line 85) | def forward(self, fine_grained_feats, coarse_feats):
    method get_targets (line 106) | def get_targets(self, rois, rel_roi_points, sampling_results, gt_masks,
    method _get_target_single (line 146) | def _get_target_single(self, rois, rel_roi_points, pos_assigned_gt_inds,
    method loss (line 164) | def loss(self, point_pred, point_targets, labels):
    method _get_uncertainty (line 187) | def _get_uncertainty(self, mask_pred, labels):
    method get_roi_rel_points_train (line 212) | def get_roi_rel_points_train(self, mask_pred, labels, cfg):
    method get_roi_rel_points_test (line 267) | def get_roi_rel_points_test(self, mask_pred, pred_label, cfg):

FILE: mmdet/models/roi_heads/mask_heads/maskiou_head.py
  class MaskIoUHead (line 12) | class MaskIoUHead(BaseModule):
    method __init__ (line 18) | def __init__(self,
    method forward (line 72) | def forward(self, mask_feat, mask_pred):
    method loss (line 87) | def loss(self, mask_iou_pred, mask_iou_targets):
    method get_targets (line 97) | def get_targets(self, sampling_results, gt_masks, mask_pred, mask_targ...
    method _get_area_ratio (line 146) | def _get_area_ratio(self, pos_proposals, pos_assigned_gt_inds, gt_masks):
    method get_mask_scores (line 173) | def get_mask_scores(self, mask_iou_pred, det_bboxes, det_labels):

FILE: mmdet/models/roi_heads/mask_heads/scnet_mask_head.py
  class SCNetMaskHead (line 7) | class SCNetMaskHead(FCNMaskHead):
    method __init__ (line 15) | def __init__(self, conv_to_res=True, **kwargs):

FILE: mmdet/models/roi_heads/mask_heads/scnet_semantic_head.py
  class SCNetSemanticHead (line 7) | class SCNetSemanticHead(FusedSemanticHead):
    method __init__ (line 15) | def __init__(self, conv_to_res=True, **kwargs):

FILE: mmdet/models/roi_heads/mask_scoring_roi_head.py
  class MaskScoringRoIHead (line 9) | class MaskScoringRoIHead(StandardRoIHead):
    method __init__ (line 15) | def __init__(self, mask_iou_head, **kwargs):
    method _mask_forward_train (line 20) | def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks,
    method simple_test_mask (line 48) | def simple_test_mask(self,

FILE: mmdet/models/roi_heads/pisa_roi_head.py
  class PISARoIHead (line 8) | class PISARoIHead(StandardRoIHead):
    method forward_train (line 12) | def forward_train(self,
    method _bbox_forward (line 86) | def _bbox_forward(self, x, rois):
    method _bbox_forward_train (line 99) | def _bbox_forward_train(self,

FILE: mmdet/models/roi_heads/point_rend_roi_head.py
  class PointRendRoIHead (line 14) | class PointRendRoIHead(StandardRoIHead):
    method __init__ (line 17) | def __init__(self, point_head, *args, **kwargs):
    method init_point_head (line 22) | def init_point_head(self, point_head):
    method _mask_forward_train (line 26) | def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks,
    method _mask_point_forward_train (line 41) | def _mask_point_forward_train(self, x, sampling_results, mask_pred,
    method _get_fine_grained_point_feats (line 62) | def _get_fine_grained_point_feats(self, x, rois, rel_roi_points,
    method _mask_point_forward_test (line 87) | def _mask_point_forward_test(self, x, rois, label_pred, mask_pred,
    method simple_test_mask (line 125) | def simple_test_mask(self,
    method aug_test_mask (line 178) | def aug_test_mask(self, feats, img_metas, det_bboxes, det_labels):

FILE: mmdet/models/roi_heads/roi_extractors/base_roi_extractor.py
  class BaseRoIExtractor (line 9) | class BaseRoIExtractor(BaseModule, metaclass=ABCMeta):
    method __init__ (line 20) | def __init__(self,
    method num_inputs (line 32) | def num_inputs(self):
    method build_roi_layers (line 36) | def build_roi_layers(self, layer_cfg, featmap_strides):
    method roi_rescale (line 61) | def roi_rescale(self, rois, scale_factor):
    method forward (line 86) | def forward(self, feats, rois, roi_scale_factor=None):

FILE: mmdet/models/roi_heads/roi_extractors/generic_roi_extractor.py
  class GenericRoIExtractor (line 9) | class GenericRoIExtractor(BaseRoIExtractor):
    method __init__ (line 24) | def __init__(self,
    method forward (line 43) | def forward(self, feats, rois, roi_scale_factor=None):

FILE: mmdet/models/roi_heads/roi_extractors/single_level_roi_extractor.py
  class SingleRoIExtractor (line 9) | class SingleRoIExtractor(BaseRoIExtractor):
    method __init__ (line 25) | def __init__(self,
    method map_roi_levels (line 35) | def map_roi_levels(self, rois, num_levels):
    method forward (line 57) | def forward(self, feats, rois, roi_scale_factor=None):

FILE: mmdet/models/roi_heads/scnet_roi_head.py
  class SCNetRoIHead (line 11) | class SCNetRoIHead(CascadeRoIHead):
    method __init__ (line 23) | def __init__(self,
    method init_mask_head (line 47) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method with_semantic (line 54) | def with_semantic(self):
    method with_feat_relay (line 60) | def with_feat_relay(self):
    method with_glbctx (line 66) | def with_glbctx(self):
    method _fuse_glbctx (line 70) | def _fuse_glbctx(self, roi_feats, glbctx_feat, rois):
    method _slice_pos_feats (line 80) | def _slice_pos_feats(self, feats, sampling_results):
    method _bbox_forward (line 93) | def _bbox_forward(self,
    method _mask_forward (line 122) | def _mask_forward(self,
    method _bbox_forward_train (line 147) | def _bbox_forward_train(self,
    method _mask_forward_train (line 176) | def _mask_forward_train(self,
    method forward_train (line 203) | def forward_train(self,
    method simple_test (line 318) | def simple_test(self, x, proposal_list, img_metas, rescale=False):
    method aug_test (line 450) | def aug_test(self, img_feats, proposal_list, img_metas, rescale=False):

FILE: mmdet/models/roi_heads/shared_heads/res_layer.py
  class ResLayer (line 12) | class ResLayer(BaseModule):
    method __init__ (line 14) | def __init__(self,
    method forward (line 69) | def forward(self, x):
    method train (line 74) | def train(self, mode=True):

FILE: mmdet/models/roi_heads/sparse_roi_head.py
  class SparseRoIHead (line 10) | class SparseRoIHead(CascadeRoIHead):
    method __init__ (line 32) | def __init__(self,
    method _bbox_forward (line 79) | def _bbox_forward(self, stage, x, rois, object_feats, img_metas):
    method forward_train (line 141) | def forward_train(self,
    method simple_test (line 226) | def simple_test(self,
    method aug_test (line 301) | def aug_test(self, features, proposal_list, img_metas, rescale=False):
    method forward_dummy (line 304) | def forward_dummy(self, x, proposal_boxes, proposal_features, img_metas):

FILE: mmdet/models/roi_heads/standard_roi_head.py
  class StandardRoIHead (line 10) | class StandardRoIHead(BaseRoIHead, BBoxTestMixin, MaskTestMixin):
    method init_assigner_sampler (line 13) | def init_assigner_sampler(self):
    method init_bbox_head (line 22) | def init_bbox_head(self, bbox_roi_extractor, bbox_head):
    method init_mask_head (line 27) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method forward_dummy (line 37) | def forward_dummy(self, x, proposals):
    method forward_train (line 53) | def forward_train(self,
    method _bbox_forward (line 116) | def _bbox_forward(self, x, rois):
    method _bbox_forward_train (line 129) | def _bbox_forward_train(self, x, sampling_results, gt_bboxes, gt_labels,
    method _mask_forward_train (line 144) | def _mask_forward_train(self, x, sampling_results, bbox_feats, gt_masks,
    method _mask_forward (line 179) | def _mask_forward(self, x, rois=None, pos_inds=None, bbox_feats=None):
    method async_simple_test (line 196) | async def async_simple_test(self,
    method simple_test (line 221) | def simple_test(self,
    method aug_test (line 252) | def aug_test(self, x, proposal_list, img_metas, rescale=False):

FILE: mmdet/models/roi_heads/test_mixins.py
  class BBoxTestMixin (line 15) | class BBoxTestMixin(object):
    method async_test_bboxes (line 19) | async def async_test_bboxes(self,
    method simple_test_bboxes (line 52) | def simple_test_bboxes(self,
    method aug_test_bboxes (line 168) | def aug_test_bboxes(self, feats, img_metas, proposal_list, rcnn_test_c...
  class MaskTestMixin (line 203) | class MaskTestMixin(object):
    method async_test_mask (line 207) | async def async_test_mask(self,
    method simple_test_mask (line 248) | def simple_test_mask(self,
    method aug_test_mask (line 341) | def aug_test_mask(self, feats, img_metas, det_bboxes, det_labels):

FILE: mmdet/models/roi_heads/trident_roi_head.py
  class TridentRoIHead (line 11) | class TridentRoIHead(StandardRoIHead):
    method __init__ (line 21) | def __init__(self, num_branch, test_branch_idx, **kwargs):
    method merge_trident_bboxes (line 26) | def merge_trident_bboxes(self, trident_det_bboxes, trident_det_labels):
    method simple_test (line 45) | def simple_test(self,
    method aug_test_bboxes (line 82) | def aug_test_bboxes(self, feats, img_metas, proposal_list, rcnn_test_c...

FILE: mmdet/models/utils/builder.py
  function build_transformer (line 6) | def build_transformer(cfg, default_args=None):

FILE: mmdet/models/utils/gaussian_target.py
  function gaussian2D (line 6) | def gaussian2D(radius, sigma=1, dtype=torch.float32, device='cpu'):
  function gen_gaussian_target (line 30) | def gen_gaussian_target(heatmap, center, radius, k=1):
  function gaussian_radius (line 66) | def gaussian_radius(det_size, min_overlap):

FILE: mmdet/models/utils/positional_encoding.py
  class SinePositionalEncoding (line 10) | class SinePositionalEncoding(BaseModule):
    method __init__ (line 35) | def __init__(self,
    method forward (line 55) | def forward(self, mask):
    method __repr__ (line 89) | def __repr__(self):
  class LearnedPositionalEncoding (line 101) | class LearnedPositionalEncoding(BaseModule):
    method __init__ (line 115) | def __init__(self,
    method forward (line 127) | def forward(self, mask):
    method __repr__ (line 151) | def __repr__(self):

FILE: mmdet/models/utils/res_layer.py
  class ResLayer (line 6) | class ResLayer(Sequential):
    method __init__ (line 25) | def __init__(self,
  class SimplifiedBasicBlock (line 106) | class SimplifiedBasicBlock(BaseModule):
    method __init__ (line 115) | def __init__(self,
    method norm1 (line 161) | def norm1(self):
    method norm2 (line 166) | def norm2(self):
    method forward (line 170) | def forward(self, x):

FILE: mmdet/models/utils/transformer.py
  function _ntuple (line 23) | def _ntuple(n):
  function nlc_to_nchw (line 40) | def nlc_to_nchw(x, hw_shape):
  function nchw_to_nlc (line 55) | def nchw_to_nlc(x):
  class AdaptivePadding (line 66) | class AdaptivePadding(nn.Module):
    method __init__ (line 96) | def __init__(self, kernel_size=1, stride=1, dilation=1, padding='corne...
    method get_pad_shape (line 112) | def get_pad_shape(self, input_shape):
    method forward (line 124) | def forward(self, x):
  class PatchEmbed (line 137) | class PatchEmbed(BaseModule):
    method __init__ (line 163) | def __init__(
    method forward (line 237) | def forward(self, x):
  class PatchMerging (line 259) | class PatchMerging(BaseModule):
    method __init__ (line 288) | def __init__(self,
    method forward (line 337) | def forward(self, x, input_size):
  function inverse_sigmoid (line 383) | def inverse_sigmoid(x, eps=1e-5):
  class DetrTransformerDecoderLayer (line 403) | class DetrTransformerDecoderLayer(BaseTransformerLayer):
    method __init__ (line 425) | def __init__(self,
  class DetrTransformerEncoder (line 449) | class DetrTransformerEncoder(TransformerLayerSequence):
    method __init__ (line 457) | def __init__(self, *args, post_norm_cfg=dict(type='LN'), **kwargs):
    method forward (line 468) | def forward(self, *args, **kwargs):
  class DetrTransformerDecoder (line 481) | class DetrTransformerDecoder(TransformerLayerSequence):
    method __init__ (line 490) | def __init__(self,
    method forward (line 504) | def forward(self, query, *args, **kwargs):
  class Transformer (line 534) | class Transformer(BaseModule):
    method __init__ (line 556) | def __init__(self, encoder=None, decoder=None, init_cfg=None):
    method init_weights (line 562) | def init_weights(self):
    method forward (line 569) | def forward(self, x, mask, query_embed, pos_embed):
  class DeformableDetrTransformerDecoder (line 619) | class DeformableDetrTransformerDecoder(TransformerLayerSequence):
    method __init__ (line 628) | def __init__(self, *args, return_intermediate=False, **kwargs):
    method forward (line 633) | def forward(self,
  class DeformableDetrTransformer (line 707) | class DeformableDetrTransformer(Transformer):
    method __init__ (line 719) | def __init__(self,
    method init_layers (line 731) | def init_layers(self):
    method init_weights (line 745) | def init_weights(self):
    method gen_encoder_output_proposals (line 757) | def gen_encoder_output_proposals(self, memory, memory_padding_mask,
    method get_reference_points (line 825) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method get_valid_ratio (line 859) | def get_valid_ratio(self, mask):
    method get_proposal_pos_embed (line 869) | def get_proposal_pos_embed(self,
    method forward (line 887) | def forward(self,
  class DynamicConv (line 1049) | class DynamicConv(BaseModule):
    method __init__ (line 1074) | def __init__(self,
    method forward (line 1105) | def forward(self, param_feature, input_feature):
  class DynamicConvV2 (line 1153) | class DynamicConvV2(BaseModule):
    method __init__ (line 1178) | def __init__(self,
    method forward (line 1209) | def forward(self, param_feature, input_feature):

FILE: mmdet/utils/collect_env.py
  function collect_env (line 7) | def collect_env():

FILE: mmdet/utils/contextmanagers.py
  function completed (line 16) | async def completed(trace_name='',
  function concurrent (line 91) | async def concurrent(streamqueue: asyncio.Queue,

FILE: mmdet/utils/logger.py
  function get_root_logger (line 6) | def get_root_logger(log_file=None, log_level=logging.INFO):

FILE: mmdet/utils/profiling.py
  function profile_time (line 10) | def profile_time(trace_name,

FILE: mmdet/utils/util_mixins.py
  class NiceRepr (line 41) | class NiceRepr(object):
    method __nice__ (line 75) | def __nice__(self):
    method __repr__ (line 86) | def __repr__(self):
    method __str__ (line 96) | def __str__(self):

FILE: mmdet/utils/util_random.py
  function ensure_rng (line 5) | def ensure_rng(rng=None):

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

FILE: setup.py
  function readme (line 10) | def readme():
  function get_version (line 19) | def get_version():
  function make_cuda_ext (line 25) | def make_cuda_ext(name, module, sources, sources_cuda=[]):
  function parse_requirements (line 50) | def parse_requirements(fname='requirements.txt', with_version=True):

FILE: tests/test_data/test_datasets/test_coco_dataset.py
  function _create_ids_error_coco_json (line 10) | def _create_ids_error_coco_json(json_name):
  function test_coco_annotation_ids_unique (line 50) | def test_coco_annotation_ids_unique():

FILE: tests/test_data/test_datasets/test_common.py
  function _create_dummy_coco_json (line 20) | def _create_dummy_coco_json(json_name):
  function _create_dummy_custom_pkl (line 80) | def _create_dummy_custom_pkl(pkl_name):
  function _create_dummy_results (line 96) | def _create_dummy_results():
  function test_dataset_init (line 106) | def test_dataset_init(config_path):
  function test_dataset_evaluation (line 120) | def test_dataset_evaluation():
  function test_evaluation_hook (line 223) | def test_evaluation_hook(EvalHookParam):
  function _build_demo_runner (line 306) | def _build_demo_runner():
  function test_allow_empty_images (line 334) | def test_allow_empty_images(classes, expected_length):

FILE: tests/test_data/test_datasets/test_custom_dataset.py
  function test_custom_classes_override_default (line 18) | def test_custom_classes_override_default(dataset):

FILE: tests/test_data/test_datasets/test_dataset_wrapper.py
  function test_dataset_wrapper (line 12) | def test_dataset_wrapper():

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

FILE: tests/test_data/test_pipelines/test_formatting.py
  function test_default_format_bundle (line 8) | def test_default_format_bundle():

FILE: tests/test_data/test_pipelines/test_loading.py
  class TestLoading (line 11) | class TestLoading(object):
    method setup_class (line 14) | def setup_class(cls):
    method test_load_img (line 17) | def test_load_img(self):
    method test_load_multi_channel_img (line 59) | def test_load_multi_channel_img(self):
    method test_load_webcam_img (line 80) | def test_load_webcam_img(self):

FILE: tests/test_data/test_pipelines/test_sampler.py
  function test_random_sampler (line 8) | def test_random_sampler():
  function test_random_sampler_empty_gt (line 44) | def test_random_sampler_empty_gt():
  function test_random_sampler_empty_pred (line 70) | def test_random_sampler_empty_pred():
  function _context_for_ohem (line 94) | def _context_for_ohem():
  function test_ohem_sampler (line 109) | def test_ohem_sampler():
  function test_ohem_sampler_empty_gt (line 154) | def test_ohem_sampler_empty_gt():
  function test_ohem_sampler_empty_pred (line 195) | def test_ohem_sampler_empty_pred():
  function test_random_sample_result (line 235) | def test_random_sample_result():
  function test_score_hlr_sampler_empty_pred (line 249) | def test_score_hlr_sampler_empty_pred():

FILE: tests/test_data/test_pipelines/test_transform/test_img_augment.py
  function construct_toy_data (line 12) | def construct_toy_data(poly2mask=True):
  function test_adjust_color (line 42) | def test_adjust_color():
  function test_imequalize (line 73) | def test_imequalize(nb_rand_test=100):
  function test_adjust_brightness (line 108) | def test_adjust_brightness(nb_rand_test=100):
  function test_adjust_contrast (line 153) | def test_adjust_contrast(nb_rand_test=100):

FILE: tests/test_data/test_pipelines/test_transform/test_models_aug_test.py
  function model_aug_test_template (line 12) | def model_aug_test_template(cfg_file):
  function test_aug_test_size (line 44) | def test_aug_test_size():
  function test_cascade_rcnn_aug_test (line 69) | def test_cascade_rcnn_aug_test():
  function test_mask_rcnn_aug_test (line 75) | def test_mask_rcnn_aug_test():
  function test_htc_aug_test (line 83) | def test_htc_aug_test():
  function test_scnet_aug_test (line 90) | def test_scnet_aug_test():
  function test_cornernet_aug_test (line 98) | def test_cornernet_aug_test():

FILE: tests/test_data/test_pipelines/test_transform/test_rotate.py
  function construct_toy_data (line 11) | def construct_toy_data(poly2mask=True):
  function _check_fields (line 41) | def _check_fields(results, results_rotated, keys):
  function check_rotate (line 50) | def check_rotate(results, results_rotated):
  function test_rotate (line 65) | def test_rotate():

FILE: tests/test_data/test_pipelines/test_transform/test_shear.py
  function construct_toy_data (line 11) | def construct_toy_data(poly2mask=True):
  function _check_fields (line 42) | def _check_fields(results, results_sheared, keys):
  function check_shear (line 51) | def check_shear(results, results_sheared):
  function test_shear (line 67) | def test_shear():

FILE: tests/test_data/test_pipelines/test_transform/test_transform.py
  function test_resize (line 14) | def test_resize():
  function test_flip (line 82) | def test_flip():
  function test_random_crop (line 183) | def test_random_crop():
  function test_min_iou_random_crop (line 306) | def test_min_iou_random_crop():
  function test_pad (line 356) | def test_pad():
  function test_normalize (line 396) | def test_normalize():
  function test_albu_transform (line 425) | def test_albu_transform():
  function test_random_center_crop_pad (line 449) | def test_random_center_crop_pad():
  function test_multi_scale_flip_aug (line 595) | def test_multi_scale_flip_aug():
  function test_cutout (line 689) | def test_cutout():
  function test_random_shift (line 755) | def test_random_shift():

FILE: tests/test_data/test_pipelines/test_transform/test_translate.py
  function _check_keys (line 12) | def _check_keys(results, results_translated):
  function _pad (line 19) | def _pad(h, w, c, pad_val, axis=-1, dtype=np.float32):
  function _construct_img (line 29) | def _construct_img(results):
  function _construct_ann_info (line 39) | def _construct_ann_info(h=427, w=640, c=3):
  function _load_bboxes (line 75) | def _load_bboxes(results):
  function _load_labels (line 85) | def _load_labels(results):
  function _poly2mask (line 89) | def _poly2mask(mask_ann, img_h, img_w):
  function _process_polygons (line 105) | def _process_polygons(polygons):
  function _load_masks (line 114) | def _load_masks(results, poly2mask=True):
  function _construct_semantic_seg (line 127) | def _construct_semantic_seg(results):
  function construct_toy_data (line 134) | def construct_toy_data(poly2mask=True):
  function test_translate (line 148) | def test_translate():

FILE: tests/test_data/test_utils.py
  function test_replace_ImageToTensor (line 6) | def test_replace_ImageToTensor():
  function test_get_loading_pipeline (line 64) | def test_get_loading_pipeline():

FILE: tests/test_metrics/test_box_overlap.py
  function test_bbox_overlaps_2d (line 8) | def test_bbox_overlaps_2d(eps=1e-7):

FILE: tests/test_metrics/test_losses.py
  function test_ce_loss (line 7) | def test_ce_loss():
  function test_varifocal_loss (line 34) | def test_varifocal_loss():
  function test_kd_loss (line 81) | def test_kd_loss():
  function test_accuracy (line 112) | def test_accuracy():

FILE: tests/test_models/test_backbones/test_hourglass.py
  function test_hourglass_backbone (line 7) | def test_hourglass_backbone():

FILE: tests/test_models/test_backbones/test_regnet.py
  function test_regnet_backbone (line 35) | def test_regnet_backbone(arch_name, arch, out_channels):

FILE: tests/test_models/test_backbones/test_renext.py
  function test_renext_bottleneck (line 9) | def test_renext_bottleneck():
  function test_resnext_backbone (line 58) | def test_resnext_backbone():

FILE: tests/test_models/test_backbones/test_res2net.py
  function test_res2net_bottle2neck (line 9) | def test_res2net_bottle2neck():
  function test_res2net_backbone (line 43) | def test_res2net_backbone():

FILE: tests/test_models/test_backbones/test_resnest.py
  function test_resnest_bottleneck (line 8) | def test_resnest_bottleneck():
  function test_resnest_backbone (line 26) | def test_resnest_backbone():

FILE: tests/test_models/test_backbones/test_resnet.py
  function test_resnet_basic_block (line 14) | def test_resnet_basic_block():
  function test_resnet_bottleneck (line 63) | def test_resnet_bottleneck():
  function test_simplied_basic_block (line 197) | def test_simplied_basic_block():
  function test_resnet_res_layer (line 250) | def test_resnet_res_layer():
  function test_resnest_stem (line 306) | def test_resnest_stem():
  function test_resnet_backbone (line 354) | def test_resnet_backbone():

FILE: tests/test_models/test_backbones/test_trident_resnet.py
  function test_trident_resnet_bottleneck (line 8) | def test_trident_resnet_bottleneck():
  function test_trident_resnet_backbone (line 155) | def test_trident_resnet_backbone():

FILE: tests/test_models/test_backbones/utils.py
  function is_block (line 10) | def is_block(modules):
  function is_norm (line 18) | def is_norm(modules):
  function check_norm_state (line 25) | def check_norm_state(modules, train_state):

FILE: tests/test_models/test_dense_heads/test_anchor_head.py
  function test_anchor_head_loss (line 7) | def test_anchor_head_loss():

FILE: tests/test_models/test_dense_heads/test_atss_head.py
  function test_atss_head_loss (line 7) | def test_atss_head_loss():

FILE: tests/test_models/test_dense_heads/test_autoassign_head.py
  function test_autoassign_head_loss (line 8) | def test_autoassign_head_loss():

FILE: tests/test_models/test_dense_heads/test_corner_head.py
  function test_corner_head_loss (line 7) | def test_corner_head_loss():
  function test_corner_head_encode_and_decode_heatmap (line 95) | def test_corner_head_encode_and_decode_heatmap():

FILE: tests/test_models/test_dense_heads/test_detr_head.py
  function test_detr_head_loss (line 7) | def test_detr_head_loss():

FILE: tests/test_models/test_dense_heads/test_fcos_head.py
  function test_fcos_head_loss (line 7) | def test_fcos_head_loss():

FILE: tests/test_models/test_dense_heads/test_fsaf_head.py
  function test_fsaf_head_loss (line 7) | def test_fsaf_head_loss():

FILE: tests/test_models/test_dense_heads/test_ga_anchor_head.py
  function test_ga_anchor_head_loss (line 7) | def test_ga_anchor_head_loss():

FILE: tests/test_models/test_dense_heads/test_gfl_head.py
  function test_gfl_head_loss (line 7) | def test_gfl_head_loss():

FILE: tests/test_models/test_dense_heads/test_ld_head.py
  function test_ld_head_loss (line 7) | def test_ld_head_loss():

FILE: tests/test_models/test_dense_heads/test_paa_head.py
  function test_paa_head_loss (line 9) | def test_paa_head_loss():

FILE: tests/test_models/test_dense_heads/test_pisa_head.py
  function test_pisa_retinanet_head_loss (line 8) | def test_pisa_retinanet_head_loss():
  function test_pisa_ssd_head_loss (line 75) | def test_pisa_ssd_head_loss():
  function test_pisa_roi_head_loss (line 150) | def test_pisa_roi_head_loss():

FILE: tests/test_models/test_dense_heads/test_sabl_retina_head.py
  function test_sabl_retina_head_loss (line 7) | def test_sabl_retina_head_loss():

FILE: tests/test_models/test_dense_heads/test_vfnet_head.py
  function test_vfnet_head_loss (line 7) | def test_vfnet_head_loss():

FILE: tests/test_models/test_dense_heads/test_yolact_head.py
  function test_yolact_head_loss (line 7) | def test_yolact_head_loss():

FILE: tests/test_models/test_dense_heads/test_yolof_head.py
  function test_yolof_head_loss (line 7) | def test_yolof_head_loss():

FILE: tests/test_models/test_forward.py
  function _get_config_directory (line 10) | def _get_config_directory():
  function _get_config_module (line 25) | def _get_config_module(fname):
  function _get_detector_cfg (line 34) | def _get_detector_cfg(fname):
  function test_sparse_rcnn_forward (line 45) | def test_sparse_rcnn_forward():
  function test_rpn_forward (line 106) | def test_rpn_forward():
  function test_single_stage_forward_gpu (line 148) | def test_single_stage_forward_gpu(cfg_file):
  function test_faster_rcnn_ohem_forward (line 188) | def test_faster_rcnn_ohem_forward():
  function test_two_stage_forward (line 239) | def test_two_stage_forward(cfg_file):
  function test_single_stage_forward_cpu (line 293) | def test_single_stage_forward_cpu(cfg_file):
  function _demo_mm_inputs (line 327) | def _demo_mm_inputs(input_shape=(1, 3, 300, 300),
  function test_yolact_forward (line 405) | def test_yolact_forward():
  function test_detr_forward (line 444) | def test_detr_forward():
  function test_kd_single_stage_forward (line 499) | def test_kd_single_stage_forward():
  function test_inference_detector (line 554) | def test_inference_detector():

FILE: tests/test_models/test_loss.py
  function test_iou_type_loss_zeros_weight (line 10) | def test_iou_type_loss_zeros_weight(loss_class):

FILE: tests/test_models/test_necks.py
  function test_fpn (line 8) | def test_fpn():
  function test_channel_mapper (line 204) | def test_channel_mapper():
  function test_dilated_encoder (line 241) | def test_dilated_encoder():

FILE: tests/test_models/test_roi_heads/test_bbox_head.py
  function test_bbox_head_loss (line 10) | def test_bbox_head_loss():
  function test_bbox_head_get_bboxes (line 69) | def test_bbox_head_get_bboxes(num_sample, num_batch):
  function test_refine_boxes (line 93) | def test_refine_boxes():
  function _demodata_refine_boxes (line 216) | def _demodata_refine_boxes(n_roi, n_img, rng=0):

FILE: tests/test_models/test_roi_heads/test_mask_head.py
  function test_mask_head_loss (line 8) | def test_mask_head_loss():

FILE: tests/test_models/test_roi_heads/test_roi_extractor.py
  function test_groie (line 7) | def test_groie():

FILE: tests/test_models/test_roi_heads/test_sabl_bbox_head.py
  function test_sabl_bbox_head_loss (line 9) | def test_sabl_bbox_head_loss():

FILE: tests/test_models/test_roi_heads/utils.py
  function _dummy_bbox_sampling (line 6) | def _dummy_bbox_sampling(proposal_list, gt_bboxes, gt_labels):

FILE: tests/test_models/test_utils/test_position_encoding.py
  function test_sine_positional_encoding (line 8) | def test_sine_positional_encoding(num_feats=16, batch_size=2):
  function test_learned_positional_encoding (line 28) | def test_learned_positional_encoding(num_feats=16,

FILE: tests/test_models/test_utils/test_transformer.py
  function test_detr_transformer_dencoder_encoder_layer (line 9) | def test_detr_transformer_dencoder_encoder_layer():
  function test_transformer (line 75) | def test_transformer():

FILE: tests/test_onnx/test_head.py
  function retinanet_config (line 22) | def retinanet_config():
  function test_retina_head_forward_single (line 53) | def test_retina_head_forward_single():
  function test_retina_head_forward (line 62) | def test_retina_head_forward():
  function test_retinanet_head_get_bboxes (line 75) | def test_retinanet_head_get_bboxes():
  function yolo_config (line 103) | def yolo_config():
  function test_yolov3_head_forward (line 135) | def test_yolov3_head_forward():
  function test_yolov3_head_get_bboxes (line 147) | def test_yolov3_head_get_bboxes():
  function fcos_config (line 170) | def fcos_config():
  function test_fcos_head_forward_single (line 186) | def test_fcos_head_forward_single():
  function test_fcos_head_forward (line 198) | def test_fcos_head_forward():
  function test_fcos_head_get_bboxes (line 209) | def test_fcos_head_get_bboxes():
  function fsaf_config (line 238) | def fsaf_config():
  function test_fsaf_head_forward_single (line 261) | def test_fsaf_head_forward_single():
  function test_fsaf_head_forward (line 269) | def test_fsaf_head_forward():
  function test_fsaf_head_get_bboxes (line 281) | def test_fsaf_head_get_bboxes():
  function ssd_config (line 309) | def ssd_config():
  function test_ssd_head_forward (line 342) | def test_ssd_head_forward():
  function test_ssd_head_get_bboxes (line 355) | def test_ssd_head_get_bboxes():

FILE: tests/test_onnx/test_neck.py
  function fpn_neck_config (line 34) | def fpn_neck_config(test_step_name):
  function yolo_neck_config (line 102) | def yolo_neck_config(test_step_name):
  function test_fpn_normal (line 120) | def test_fpn_normal():
  function test_fpn_wo_extra_convs (line 125) | def test_fpn_wo_extra_convs():
  function test_fpn_lateral_bns (line 130) | def test_fpn_lateral_bns():
  function test_fpn_bilinear_upsample (line 135) | def test_fpn_bilinear_upsample():
  function test_fpn_scale_factor (line 140) | def test_fpn_scale_factor():
  function test_fpn_extra_convs_inputs (line 145) | def test_fpn_extra_convs_inputs():
  function test_fpn_extra_convs_laterals (line 150) | def test_fpn_extra_convs_laterals():
  function test_fpn_extra_convs_outputs (line 155) | def test_fpn_extra_convs_outputs():
  function test_yolo_normal (line 160) | def test_yolo_normal():

FILE: tests/test_onnx/utils.py
  class WrapFunction (line 20) | class WrapFunction(nn.Module):
    method __init__ (line 23) | def __init__(self, wrapped_function):
    method forward (line 27) | def forward(self, *args, **kwargs):
  function ort_validate (line 31) | def ort_validate(model, feats, onnx_io='tmp.onnx'):
  function get_ort_model_output (line 87) | def get_ort_model_output(feat, onnx_io='tmp.onnx'):
  function convert_result_list (line 117) | def convert_result_list(outputs):

FILE: tests/test_runtime/async_benchmark.py
  function main (line 15) | async def main():

FILE: tests/test_runtime/test_async.py
  class AsyncTestCase (line 17) | class AsyncTestCase(asynctest.TestCase):
    method _run_test_method (line 23) | def _run_test_method(self, method):
  class MaskRCNNDetector (line 30) | class MaskRCNNDetector:
    method __init__ (line 32) | def __init__(self,
    method init (line 45) | async def init(self):
    method apredict (line 53) | async def apredict(self, img):
  class AsyncInferenceTestCase (line 61) | class AsyncInferenceTestCase(AsyncTestCase):
    method test_simple_inference (line 65) | async def test_simple_inference(self):

FILE: tests/test_runtime/test_config.py
  function _get_config_directory (line 13) | def _get_config_directory():
  function _check_numclasscheckhook (line 29) | def _check_numclasscheckhook(detector, config_mod):
  function test_config_build_detector (line 64) | def test_config_build_detector():
  function _check_roi_head (line 115) | def _check_roi_head(config, head):
  function _check_roi_extractor (line 168) | def _check_roi_extractor(config, roi_extractor, prev_roi_extractor=None):
  function _check_mask_head (line 196) | def _check_mask_head(mask_cfg, mask_head):
  function _check_bbox_head (line 219) | def _check_bbox_head(bbox_cfg, bbox_head):
  function _check_anchorhead (line 265) | def _check_anchorhead(config, head):
  function test_config_data_pipeline (line 302) | def test_config_data_pipeline(config_rpath):

FILE: tests/test_runtime/test_eval_hook.py
  class ExampleDataset (line 17) | class ExampleDataset(Dataset):
    method __init__ (line 19) | def __init__(self):
    method __getitem__ (line 23) | def __getitem__(self, idx):
    method __len__ (line 27) | def __len__(self):
    method evaluate (line 31) | def evaluate(self, results, logger=None):
  class EvalDataset (line 35) | class EvalDataset(ExampleDataset):
    method evaluate (line 37) | def evaluate(self, results, logger=None):
  class ExampleModel (line 44) | class ExampleModel(nn.Module):
    method __init__ (line 46) | def __init__(self):
    method forward (line 51) | def forward(self, imgs, rescale=False, return_loss=False):
    method train_step (line 54) | def train_step(self, data_batch, optimizer, **kwargs):
  function test_eval_hook (line 70) | def test_eval_hook(EvalHookCls):

FILE: tests/test_runtime/test_fp16.py
  function test_cast_tensor_type (line 9) | def test_cast_tensor_type():
  function test_auto_fp16 (line 51) | def test_auto_fp16():
  function test_force_fp32 (line 177) | def test_force_fp32():

FILE: tests/test_utils/test_anchor.py
  function test_standard_anchor_generator (line 10) | def test_standard_anchor_generator():
  function test_strides (line 22) | def test_strides():
  function test_ssd_anchor_generator (line 43) | def test_ssd_anchor_generator():
  function test_anchor_generator_with_tuples (line 113) | def test_anchor_generator_with_tuples():
  function test_yolo_anchor_generator (line 148) | def test_yolo_anchor_generator():
  function test_retina_anchor (line 191) | def test_retina_anchor():
  function test_guided_anchor (line 290) | def test_guided_anchor():

FILE: tests/test_utils/test_assigner.py
  function test_max_iou_assigner (line 15) | def test_max_iou_assigner():
  function test_max_iou_assigner_with_ignore (line 39) | def test_max_iou_assigner_with_ignore():
  function test_max_iou_assigner_with_empty_gt (line 66) | def test_max_iou_assigner_with_empty_gt():
  function test_max_iou_assigner_with_empty_boxes (line 85) | def test_max_iou_assigner_with_empty_boxes():
  function test_max_iou_assigner_with_empty_boxes_and_ignore (line 109) | def test_max_iou_assigner_with_empty_boxes_and_ignore():
  function test_max_iou_assigner_with_empty_boxes_and_gt (line 143) | def test_max_iou_assigner_with_empty_boxes_and_gt():
  function test_point_assigner (line 155) | def test_point_assigner():
  function test_point_assigner_with_empty_gt (line 172) | def test_point_assigner_with_empty_gt():
  function test_point_assigner_with_empty_boxes_and_gt (line 188) | def test_point_assigner_with_empty_boxes_and_gt():
  function test_approx_iou_assigner (line 197) | def test_approx_iou_assigner():
  function test_approx_iou_assigner_with_empty_gt (line 222) | def test_approx_iou_assigner_with_empty_gt():
  function test_approx_iou_assigner_with_empty_boxes (line 245) | def test_approx_iou_assigner_with_empty_boxes():
  function test_approx_iou_assigner_with_empty_boxes_and_gt (line 264) | def test_approx_iou_assigner_with_empty_boxes_and_gt():
  function test_random_assign_result (line 280) | def test_random_assign_result():
  function test_center_region_assigner (line 294) | def test_center_region_assigner():
  function test_center_region_assigner_with_ignore (line 320) | def test_center_region_assigner_with_ignore():
  function test_center_region_assigner_with_empty_bboxes (line 349) | def test_center_region_assigner_with_empty_bboxes():
  function test_center_region_assigner_with_empty_gts (line 365) | def test_center_region_assigner_with_empty_gts():
  function test_hungarian_match_assigner (line 382) | def test_hungarian_match_assigner():
  function test_uniform_assigner (line 428) | def test_uniform_assigner():
  function test_uniform_assigner_with_empty_gt (line 456) | def test_uniform_assigner_with_empty_gt():
  function test_uniform_assigner_with_empty_boxes (line 478) | def test_uniform_assigner_with_empty_boxes():

FILE: tests/test_utils/test_coder.py
  function test_yolo_bbox_coder (line 8) | def test_yolo_bbox_coder():
  function test_delta_bbox_coder (line 26) | def test_delta_bbox_coder():
  function test_tblr_bbox_coder (line 77) | def test_tblr_bbox_coder():

FILE: tests/test_utils/test_masks.py
  function dummy_raw_bitmap_masks (line 8) | def dummy_raw_bitmap_masks(size):
  function dummy_raw_polygon_masks (line 19) | def dummy_raw_polygon_masks(size):
  function dummy_bboxes (line 35) | def dummy_bboxes(num, max_height, max_width):
  function test_bitmap_mask_init (line 42) | def test_bitmap_mask_init():
  function test_bitmap_mask_rescale (line 77) | def test_bitmap_mask_rescale():
  function test_bitmap_mask_resize (line 98) | def test_bitmap_mask_resize():
  function test_bitmap_mask_flip (line 132) | def test_bitmap_mask_flip():
  function test_bitmap_mask_pad (line 173) | def test_bitmap_mask_pad():
  function test_bitmap_mask_crop (line 192) | def test_bitmap_mask_crop():
  function test_bitmap_mask_crop_and_resize (line 218) | def test_bitmap_mask_crop_and_resize():
  function test_bitmap_mask_expand (line 241) | def test_bitmap_mask_expand():
  function test_bitmap_mask_area (line 261) | def test_bitmap_mask_area():
  function test_bitmap_mask_to_ndarray (line 275) | def test_bitmap_mask_to_ndarray():
  function test_bitmap_mask_to_tensor (line 292) | def test_bitmap_mask_to_tensor():
  function test_bitmap_mask_index (line 309) | def test_bitmap_mask_index():
  function test_bitmap_mask_iter (line 316) | def test_bitmap_mask_iter():
  function test_polygon_mask_init (line 324) | def test_polygon_mask_init():
  function test_polygon_mask_rescale (line 352) | def test_polygon_mask_rescale():
  function test_polygon_mask_resize (line 380) | def test_polygon_mask_resize():
  function test_polygon_mask_flip (line 449) | def test_polygon_mask_flip():
  function test_polygon_mask_crop (line 497) | def test_polygon_mask_crop():
  function test_polygon_mask_pad (line 526) | def test_polygon_mask_pad():
  function test_polygon_mask_expand (line 547) | def test_polygon_mask_expand():
  function test_polygon_mask_crop_and_resize (line 554) | def test_polygon_mask_crop_and_resize():
  function test_polygon_mask_area (line 579) | def test_polygon_mask_area():
  function test_polygon_mask_to_bitmap (line 596) | def test_polygon_mask_to_bitmap():
  function test_polygon_mask_to_ndarray (line 604) | def test_polygon_mask_to_ndarray():
  function test_polygon_to_tensor (line 620) | def test_polygon_to_tensor():
  function test_polygon_mask_index (line 637) | def test_polygon_mask_index():
  function test_polygon_mask_iter (line 651) | def test_polygon_mask_iter():

FILE: tests/test_utils/test_misc.py
  function dummy_raw_polygon_masks (line 10) | def dummy_raw_polygon_masks(size):
  function test_mask2ndarray (line 26) | def test_mask2ndarray():
  function test_distance2bbox (line 51) | def test_distance2bbox():

FILE: tests/test_utils/test_version.py
  function test_version_check (line 4) | def test_version_check():

FILE: tests/test_utils/test_visualization.py
  function test_color (line 14) | def test_color():
  function test_imshow_det_bboxes (line 31) | def test_imshow_det_bboxes():
  function test_imshow_gt_det_bboxes (line 80) | def test_imshow_gt_det_bboxes():

FILE: tools/analysis_tools/analyze_logs.py
  function cal_train_time (line 10) | def cal_train_time(log_dicts, args):
  function plot_curve (line 33) | def plot_curve(log_dicts, args):
  function add_plot_parser (line 92) | def add_plot_parser(subparsers):
  function add_time_parser (line 120) | def add_time_parser(subparsers):
  function parse_args (line 136) | def parse_args():
  function load_json_logs (line 146) | def load_json_logs(json_logs):
  function main (line 166) | def main():

FILE: tools/analysis_tools/analyze_results.py
  function bbox_map_eval (line 13) | def bbox_map_eval(det_result, annotation):
  class ResultVisualizer (line 48) | class ResultVisualizer(object):
    method __init__ (line 58) | def __init__(self, show=False, wait_time=0, score_thr=0):
    method _save_image_gts_results (line 63) | def _save_image_gts_results(self, dataset, results, mAPs, out_dir=None):
    method evaluate_and_show (line 89) | def evaluate_and_show(self,
  function parse_args (line 137) | def parse_args():
  function main (line 176) | def main():

FILE: tools/analysis_tools/benchmark.py
  function parse_args (line 15) | def parse_args():
  function main (line 40) | def main():

FILE: tools/analysis_tools/coco_error_analysis.py
  function makeplot (line 12) | def makeplot(rs, ps, outDir, class_name, iou_type):
  function autolabel (line 53) | def autolabel(ax, rects):
  function makebarplot (line 72) | def makebarplot(rs, ps, outDir, class_name, iou_type):
  function get_gt_area_group_numbers (line 107) | def get_gt_area_group_numbers(cocoEval):
  function make_gt_area_group_numbers_plot (line 122) | def make_gt_area_group_numbers_plot(cocoEval, outDir, verbose=True):
  function make_gt_area_histogram_plot (line 151) | def make_gt_area_histogram_plot(cocoEval, outDir):
  function analyze_individual_category (line 173) | def analyze_individual_category(k,
  function analyze_results (line 234) | def analyze_results(res_file,
  function main (line 307) | def main():

FILE: tools/analysis_tools/eval_metric.py
  function parse_args (line 9) | def parse_args():
  function main (line 46) | def main():

FILE: tools/analysis_tools/get_flops.py
  function parse_args (line 14) | def parse_args():
  function main (line 37) | def main():

FILE: tools/analysis_tools/robustness_eval.py
  function print_coco_results (line 8) | def print_coco_results(results):
  function get_coco_style_results (line 34) | def get_coco_style_results(filename,
  function get_voc_style_results (line 111) | def get_voc_style_results(filename, prints='mPC', aggregate='benchmark'):
  function get_results (line 155) | def get_results(filename,
  function get_distortions_from_file (line 183) | def get_distortions_from_file(filename):
  function get_distortions_from_results (line 190) | def get_distortions_from_results(eval_output):
  function main (line 197) | def main():

FILE: tools/analysis_tools/test_robustness.py
  function coco_eval_with_return (line 23) | def coco_eval_with_return(result_files,
  function voc_eval_with_return (line 65) | def voc_eval_with_return(result_file,
  function parse_args (line 92) | def parse_args():
  function main (line 180) | def main():

FILE: tools/dataset_converters/cityscapes.py
  function collect_files (line 11) | def collect_files(img_dir, gt_dir):
  function collect_annotations (line 28) | def collect_annotations(files, nproc=1):
  function load_img_info (line 39) | def load_img_info(files):
  function cvt_annotations (line 84) | def cvt_annotations(image_infos, out_json_name):
  function parse_args (line 113) | def parse_args():
  function main (line 126) | def main():

FILE: tools/dataset_converters/pascal_voc.py
  function parse_xml (line 13) | def parse_xml(args):
  function cvt_annotations (line 67) | def cvt_annotations(devkit_path, years, split, out_file):
  function cvt_to_coco_json (line 95) | def cvt_to_coco_json(annotations):
  function parse_args (line 182) | def parse_args():
  function main (line 196) | def main():

FILE: tools/deployment/mmdet2torchserve.py
  function mmdet2torchserve (line 14) | def mmdet2torchserve(
  function parse_args (line 69) | def parse_args():

FILE: tools/deployment/mmdet_handler.py
  class MMdetHandler (line 11) | class MMdetHandler(BaseHandler):
    method initialize (line 14) | def initialize(self, context):
    method preprocess (line 30) | def preprocess(self, data):
    method inference (line 42) | def inference(self, data, *args, **kwargs):
    method postprocess (line 46) | def postprocess(self, data):

FILE: tools/deployment/onnx2tensorrt.py
  function get_GiB (line 18) | def get_GiB(x: int):
  function onnx2tensorrt (line 23) | def onnx2tensorrt(onnx_file,
  function parse_args (line 117) | def parse_args():

FILE: tools/deployment/pytorch2onnx.py
  function pytorch2onnx (line 16) | def pytorch2onnx(config_path,
  function parse_args (line 179) | def parse_args():

FILE: tools/deployment/test.py
  function parse_args (line 13) | def parse_args():
  function main (line 60) | def main():

FILE: tools/misc/browse_dataset.py
  function parse_args (line 13) | def parse_args():
  function retrieve_data_cfg (line 47) | def retrieve_data_cfg(config_path, skip_type, cfg_options):
  function main (line 63) | def main():

FILE: tools/misc/print_config.py
  function parse_args (line 7) | def parse_args():
  function main (line 40) | def main():

FILE: tools/model_converters/detectron2pytorch.py
  function convert_bn (line 10) | def convert_bn(blobs, state_dict, caffe_name, torch_name, converted_names):
  function convert_conv_fc (line 23) | def convert_conv_fc(blobs, state_dict, caffe_name, torch_name,
  function convert (line 34) | def convert(src, dst, depth):
  function main (line 72) | def main():

FILE: tools/model_converters/publish_model.py
  function parse_args (line 7) | def parse_args():
  function process_checkpoint (line 16) | def process_checkpoint(in_file, out_file):
  function main (line 33) | def main():

FILE: tools/model_converters/regnet2mmdet.py
  function convert_stem (line 7) | def convert_stem(model_key, model_weight, state_dict, converted_names):
  function convert_head (line 15) | def convert_head(model_key, model_weight, state_dict, converted_names):
  function convert_reslayer (line 22) | def convert_reslayer(model_key, model_weight, state_dict, converted_names):
  function convert (line 54) | def convert(src, dst):
  function main (line 80) | def main():

FILE: tools/model_converters/upgrade_model_version.py
  function is_head (line 10) | def is_head(key):
  function parse_config (line 18) | def parse_config(config_strings):
  function reorder_cls_channel (line 45) | def reorder_cls_channel(val, num_classes=81):
  function truncate_cls_channel (line 67) | def truncate_cls_channel(val, num_classes=81):
  function truncate_reg_channel (line 89) | def truncate_reg_channel(val, num_classes=81):
  function convert (line 114) | def convert(in_file, out_file, num_classes):
  function main (line 195) | 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 21) | def parse_args():
  function main (line 86) | def main():

[
  {
    "path": ".gitignore",
    "chars": 21,
    "preview": "**/.DS_Store\n.vscode\n"
  },
  {
    "path": "LICENSE",
    "chars": 1103,
    "preview": "MIT License\n\nCopyright (c) 2022 Multimedia Computing Group, Nanjing University\n\nPermission is hereby granted, free of ch"
  },
  {
    "path": "Makefile",
    "chars": 822,
    "preview": "adamixer-r50:\n\tCUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 PORT=29502 ./tools/dist_train.sh \\\n\tconfigs/adamixer/adamixer_r50_1x"
  },
  {
    "path": "README.md",
    "chars": 14658,
    "preview": "# AdaMixer: A Fast-Converging Query-Based Object Detector [arxiv](https://arxiv.org/abs/2203.16507)\n\n> [**AdaMixer: A Fa"
  },
  {
    "path": "README_zh-CN.md",
    "chars": 7304,
    "preview": "<div align=\"center\">\n  <img src=\"resources/mmdet-logo.png\" width=\"600\"/>\n</div>\n\n**新闻**: 我们在 [ArXiv](https://arxiv.org/a"
  },
  {
    "path": "configs/_base_/datasets/cityscapes_detection.py",
    "chars": 1937,
    "preview": "# dataset settings\ndataset_type = 'CityscapesDataset'\ndata_root = 'data/cityscapes/'\nimg_norm_cfg = dict(\n    mean=[123."
  },
  {
    "path": "configs/_base_/datasets/cityscapes_instance.py",
    "chars": 1963,
    "preview": "# dataset settings\ndataset_type = 'CityscapesDataset'\ndata_root = 'data/cityscapes/'\nimg_norm_cfg = dict(\n    mean=[123."
  },
  {
    "path": "configs/_base_/datasets/coco_detection.py",
    "chars": 1914,
    "preview": "# dataset settings\ndataset_type = 'CocoDataset'\ndata_root = 'data/coco/'\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28,"
  },
  {
    "path": "configs/_base_/datasets/coco_detection_tiny.py",
    "chars": 1984,
    "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/coco_instance.py",
    "chars": 1737,
    "preview": "# dataset settings\ndataset_type = 'CocoDataset'\ndata_root = 'data/coco/'\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28,"
  },
  {
    "path": "configs/_base_/datasets/coco_instance_semantic.py",
    "chars": 1922,
    "preview": "# dataset settings\ndataset_type = 'CocoDataset'\ndata_root = 'data/coco/'\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28,"
  },
  {
    "path": "configs/_base_/datasets/deepfashion.py",
    "chars": 1888,
    "preview": "# dataset settings\ndataset_type = 'DeepFashionDataset'\ndata_root = 'data/DeepFashion/In-shop/'\nimg_norm_cfg = dict(\n    "
  },
  {
    "path": "configs/_base_/datasets/lvis_v0.5_instance.py",
    "chars": 786,
    "preview": "# dataset settings\n_base_ = 'coco_instance.py'\ndataset_type = 'LVISV05Dataset'\ndata_root = 'data/lvis_v0.5/'\ndata = dict"
  },
  {
    "path": "configs/_base_/datasets/lvis_v1_instance.py",
    "chars": 736,
    "preview": "# dataset settings\n_base_ = 'coco_instance.py'\ndataset_type = 'LVISV1Dataset'\ndata_root = 'data/lvis_v1/'\ndata = dict(\n "
  },
  {
    "path": "configs/_base_/datasets/voc0712.py",
    "chars": 1916,
    "preview": "# dataset settings\ndataset_type = 'VOCDataset'\ndata_root = 'data/VOCdevkit/'\nimg_norm_cfg = dict(\n    mean=[123.675, 116"
  },
  {
    "path": "configs/_base_/datasets/wider_face.py",
    "chars": 2011,
    "preview": "# dataset settings\ndataset_type = 'WIDERFaceDataset'\ndata_root = 'data/WIDERFace/'\nimg_norm_cfg = dict(mean=[123.675, 11"
  },
  {
    "path": "configs/_base_/default_runtime.py",
    "chars": 368,
    "preview": "checkpoint_config = dict(interval=1)\n# yapf:disable\nlog_config = dict(\n    interval=50,\n    hooks=[\n        dict(type='T"
  },
  {
    "path": "configs/_base_/models/cascade_mask_rcnn_r50_fpn.py",
    "chars": 6912,
    "preview": "# model settings\nmodel = dict(\n    type='CascadeRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n     "
  },
  {
    "path": "configs/_base_/models/cascade_rcnn_r50_fpn.py",
    "chars": 6287,
    "preview": "# model settings\nmodel = dict(\n    type='CascadeRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n     "
  },
  {
    "path": "configs/_base_/models/fast_rcnn_r50_fpn.py",
    "chars": 2022,
    "preview": "# model settings\nmodel = dict(\n    type='FastRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n        "
  },
  {
    "path": "configs/_base_/models/faster_rcnn_r50_caffe_c4.py",
    "chars": 3631,
    "preview": "# model settings\nnorm_cfg = dict(type='BN', requires_grad=False)\nmodel = dict(\n    type='FasterRCNN',\n    pretrained='op"
  },
  {
    "path": "configs/_base_/models/faster_rcnn_r50_caffe_dc5.py",
    "chars": 3416,
    "preview": "# model settings\nnorm_cfg = dict(type='BN', requires_grad=False)\nmodel = dict(\n    type='FasterRCNN',\n    pretrained='op"
  },
  {
    "path": "configs/_base_/models/faster_rcnn_r50_fpn.py",
    "chars": 3594,
    "preview": "# model settings\nmodel = dict(\n    type='FasterRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n      "
  },
  {
    "path": "configs/_base_/models/mask_rcnn_r50_caffe_c4.py",
    "chars": 3998,
    "preview": "# model settings\nnorm_cfg = dict(type='BN', requires_grad=False)\nmodel = dict(\n    type='MaskRCNN',\n    pretrained='open"
  },
  {
    "path": "configs/_base_/models/mask_rcnn_r50_fpn.py",
    "chars": 4016,
    "preview": "# model settings\nmodel = dict(\n    type='MaskRCNN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n        "
  },
  {
    "path": "configs/_base_/models/retinanet_r50_fpn.py",
    "chars": 1729,
    "preview": "# model settings\nmodel = dict(\n    type='RetinaNet',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n       "
  },
  {
    "path": "configs/_base_/models/rpn_r50_caffe_c4.py",
    "chars": 1725,
    "preview": "# model settings\nmodel = dict(\n    type='RPN',\n    pretrained='open-mmlab://detectron2/resnet50_caffe',\n    backbone=dic"
  },
  {
    "path": "configs/_base_/models/rpn_r50_fpn.py",
    "chars": 1769,
    "preview": "# model settings\nmodel = dict(\n    type='RPN',\n    pretrained='torchvision://resnet50',\n    backbone=dict(\n        type="
  },
  {
    "path": "configs/_base_/models/ssd300.py",
    "chars": 1529,
    "preview": "# model settings\ninput_size = 300\nmodel = dict(\n    type='SingleStageDetector',\n    pretrained='open-mmlab://vgg16_caffe"
  },
  {
    "path": "configs/_base_/schedules/schedule_1x.py",
    "chars": 319,
    "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_20e.py",
    "chars": 320,
    "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": 320,
    "preview": "# optimizer\noptimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)\noptimizer_config = dict(grad_clip=N"
  },
  {
    "path": "configs/adamixer/README.md",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "configs/adamixer/adamixer_dx101_300_query_crop_mstrain_480-800_3x_coco.py",
    "chars": 518,
    "preview": "_base_ = './adamixer_r50_300_query_crop_mstrain_480-800_3x_coco.py'\n\nmodel = dict(\n    pretrained='open-mmlab://resnext1"
  },
  {
    "path": "configs/adamixer/adamixer_r101_300_query_crop_mstrain_480-800_3x_coco.py",
    "chars": 146,
    "preview": "_base_ = './adamixer_r50_300_query_crop_mstrain_480-800_3x_coco.py'\n\nmodel = dict(pretrained='torchvision://resnet101', "
  },
  {
    "path": "configs/adamixer/adamixer_r101_mstrain_480-800_3x_coco.py",
    "chars": 131,
    "preview": "_base_ = './adamixer_r50_mstrain_480-800_3x_coco.py'\n\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(d"
  },
  {
    "path": "configs/adamixer/adamixer_r50_1x_coco.py",
    "chars": 5997,
    "preview": "def __get_debug():\n    import os\n    return 'C_DEBUG' in os.environ\n\n\ndebug = __get_debug()\n\nlog_interval = 100\n\n\n_base_"
  },
  {
    "path": "configs/adamixer/adamixer_r50_300_query_crop_mstrain_480-800_3x_coco.py",
    "chars": 2064,
    "preview": "_base_ = './adamixer_r50_mstrain_480-800_3x_coco.py'\nnum_query = 300\nmodel = dict(\n    rpn_head=dict(num_query=num_query"
  },
  {
    "path": "configs/adamixer/adamixer_r50_mstrain_480-800_3x_coco.py",
    "chars": 846,
    "preview": "_base_ = './adamixer_r50_1x_coco.py'\n\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.37"
  },
  {
    "path": "configs/adamixer/adamixer_swin_s_300_query_crop_mstrain_480-800_3x_coco.py",
    "chars": 1110,
    "preview": "_base_ = './adamixer_r50_300_query_crop_mstrain_480-800_3x_coco.py'\npretrained = './swin_small_patch4_window7_224.pth'\nm"
  },
  {
    "path": "configs/albu_example/README.md",
    "chars": 1044,
    "preview": "# Albu Example\n\n<!-- [OTHERS] -->\n\n```\n@article{2018arXiv180906839B,\n  author = {A. Buslaev, A. Parinov, E. Khvedchenya,"
  },
  {
    "path": "configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py",
    "chars": 2276,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'\nimg_norm_cfg = dict(\n    mean=[123.675, 116.28, 103.53], std=[58.39"
  },
  {
    "path": "configs/atss/README.md",
    "chars": 1541,
    "preview": "# Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection\n\n## Introductio"
  },
  {
    "path": "configs/atss/atss_r101_fpn_1x_coco.py",
    "chars": 125,
    "preview": "_base_ = './atss_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='torchvision://resnet101',\n    backbone=dict(depth=101"
  },
  {
    "path": "configs/atss/atss_r50_fpn_1x_coco.py",
    "chars": 1887,
    "preview": "_base_ = [\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/schedules/schedule_1x.py', '../_base_/default_runt"
  },
  {
    "path": "configs/autoassign/README.md",
    "chars": 1434,
    "preview": "# AutoAssign: Differentiable Label Assignment for Dense Object Detection\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```\n@ar"
  },
  {
    "path": "configs/autoassign/autoassign_r50_fpn_8x2_1x_coco.py",
    "chars": 2645,
    "preview": "# We follow the original implementation which\n# adopts the Caffe pre-trained backbone.\n_base_ = [\n    '../_base_/dataset"
  },
  {
    "path": "configs/carafe/README.md",
    "chars": 2382,
    "preview": "# CARAFE: Content-Aware ReAssembly of FEatures\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\nWe provide config files to reprod"
  },
  {
    "path": "configs/carafe/faster_rcnn_r50_fpn_carafe_1x_coco.py",
    "chars": 1640,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    neck=dict(\n        type='FPN_CARAFE',\n       "
  },
  {
    "path": "configs/carafe/mask_rcnn_r50_fpn_carafe_1x_coco.py",
    "chars": 1971,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    neck=dict(\n        type='FPN_CARAFE',\n        in_"
  },
  {
    "path": "configs/cascade_rcnn/README.md",
    "chars": 12354,
    "preview": "# Cascade R-CNN: High Quality Object Detection and Instance Segmentation\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```late"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py",
    "chars": 158,
    "preview": "_base_ = './cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet101_"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py",
    "chars": 127,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_20e_coco.py",
    "chars": 128,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(dept"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 1348,
    "preview": "_base_ = ['./cascade_mask_rcnn_r50_fpn_1x_coco.py']\n\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caff"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py",
    "chars": 182,
    "preview": "_base_ = [\n    '../_base_/models/cascade_mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_instance.py',\n    '../_base"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco.py",
    "chars": 183,
    "preview": "_base_ = [\n    '../_base_/models/cascade_mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_instance.py',\n    '../_base"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py",
    "chars": 376,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    back"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_20e_coco.py",
    "chars": 377,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    bac"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py",
    "chars": 376,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    back"
  },
  {
    "path": "configs/cascade_rcnn/cascade_mask_rcnn_x101_64x4d_fpn_20e_coco.py",
    "chars": 377,
    "preview": "_base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    bac"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py",
    "chars": 153,
    "preview": "_base_ = './cascade_rcnn_r50_caffe_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet101_caffe"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py",
    "chars": 122,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r101_fpn_20e_coco.py",
    "chars": 123,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 1309,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_1x_coco.py'\n\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',\n   "
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py",
    "chars": 178,
    "preview": "_base_ = [\n    '../_base_/models/cascade_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sc"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_r50_fpn_20e_coco.py",
    "chars": 149,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_1x_coco.py'\n# learning policy\nlr_config = dict(step=[16, 19])\nrunner = dict(type='Epoch"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_1x_coco.py",
    "chars": 371,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    backbone="
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_x101_32x4d_fpn_20e_coco.py",
    "chars": 372,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    backbone"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_1x_coco.py",
    "chars": 395,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    type='CascadeRCNN',\n    pretrained='open-mmlab://resnext1"
  },
  {
    "path": "configs/cascade_rcnn/cascade_rcnn_x101_64x4d_fpn_20e_coco.py",
    "chars": 396,
    "preview": "_base_ = './cascade_rcnn_r50_fpn_20e_coco.py'\nmodel = dict(\n    type='CascadeRCNN',\n    pretrained='open-mmlab://resnext"
  },
  {
    "path": "configs/cascade_rpn/README.md",
    "chars": 1747,
    "preview": "# Cascade RPN\n\n<!-- [ALGORITHM] -->\n\nWe provide the code for reproducing experiment results of [Cascade RPN](https://arx"
  },
  {
    "path": "configs/cascade_rpn/crpn_fast_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 2770,
    "preview": "_base_ = '../fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caff"
  },
  {
    "path": "configs/cascade_rpn/crpn_faster_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 3490,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py'\nrpn_weight = 0.7\nmodel = dict(\n    rpn_head=dict(\n       "
  },
  {
    "path": "configs/cascade_rpn/crpn_r50_caffe_fpn_1x_coco.py",
    "chars": 2750,
    "preview": "_base_ = '../rpn/rpn_r50_caffe_fpn_1x_coco.py'\nmodel = dict(\n    rpn_head=dict(\n        _delete_=True,\n        type='Cas"
  },
  {
    "path": "configs/centripetalnet/README.md",
    "chars": 1510,
    "preview": "# CentripetalNet\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@InProceedings{Dong_2020_CVPR,\nauthor = {Dong, Zhiwei "
  },
  {
    "path": "configs/centripetalnet/centripetalnet_hourglass104_mstest_16x6_210e_coco.py",
    "chars": 3465,
    "preview": "_base_ = [\n    '../_base_/default_runtime.py', '../_base_/datasets/coco_detection.py'\n]\n\n# model settings\nmodel = dict(\n"
  },
  {
    "path": "configs/cityscapes/README.md",
    "chars": 2913,
    "preview": "# Cityscapes Dataset\n\n<!-- [DATASET] -->\n\n```\n@inproceedings{Cordts2016Cityscapes,\n   title={The Cityscapes Dataset for "
  },
  {
    "path": "configs/cityscapes/faster_rcnn_r50_fpn_1x_cityscapes.py",
    "chars": 1449,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_fpn.py',\n    '../_base_/datasets/cityscapes_detection.py',\n    '../_bas"
  },
  {
    "path": "configs/cityscapes/mask_rcnn_r50_fpn_1x_cityscapes.py",
    "chars": 1711,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/cityscapes_instance.py', '../_base_/defa"
  },
  {
    "path": "configs/cornernet/README.md",
    "chars": 2993,
    "preview": "# CornerNet\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@inproceedings{law2018cornernet,\n  title={Cornernet: Detect"
  },
  {
    "path": "configs/cornernet/cornernet_hourglass104_mstest_10x5_210e_coco.py",
    "chars": 3404,
    "preview": "_base_ = [\n    '../_base_/default_runtime.py', '../_base_/datasets/coco_detection.py'\n]\n\n# model settings\nmodel = dict(\n"
  },
  {
    "path": "configs/cornernet/cornernet_hourglass104_mstest_32x3_210e_coco.py",
    "chars": 3404,
    "preview": "_base_ = [\n    '../_base_/default_runtime.py', '../_base_/datasets/coco_detection.py'\n]\n\n# model settings\nmodel = dict(\n"
  },
  {
    "path": "configs/cornernet/cornernet_hourglass104_mstest_8x6_210e_coco.py",
    "chars": 3404,
    "preview": "_base_ = [\n    '../_base_/default_runtime.py', '../_base_/datasets/coco_detection.py'\n]\n\n# model settings\nmodel = dict(\n"
  },
  {
    "path": "configs/dcn/README.md",
    "chars": 10083,
    "preview": "# Deformable Convolutional Networks\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```none\n@inproceedings{dai2017deformable,\n  "
  },
  {
    "path": "configs/dcn/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 222,
    "preview": "_base_ = '../cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type="
  },
  {
    "path": "configs/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 221,
    "preview": "_base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='"
  },
  {
    "path": "configs/dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 228,
    "preview": "_base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict"
  },
  {
    "path": "configs/dcn/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 217,
    "preview": "_base_ = '../cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN'"
  },
  {
    "path": "configs/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 216,
    "preview": "_base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN',"
  },
  {
    "path": "configs/dcn/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 215,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN', "
  },
  {
    "path": "configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 214,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN', d"
  },
  {
    "path": "configs/dcn/faster_rcnn_r50_fpn_dpool_1x_coco.py",
    "chars": 408,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        bbox_roi_extractor=dic"
  },
  {
    "path": "configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py",
    "chars": 216,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCNv2',"
  },
  {
    "path": "configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py",
    "chars": 216,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCNv2',"
  },
  {
    "path": "configs/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco.py",
    "chars": 417,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        bbox_roi_extractor=dic"
  },
  {
    "path": "configs/dcn/faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 506,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n "
  },
  {
    "path": "configs/dcn/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 211,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN', defo"
  },
  {
    "path": "configs/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py",
    "chars": 210,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCN', defor"
  },
  {
    "path": "configs/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py",
    "chars": 212,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        dcn=dict(type='DCNv2', def"
  },
  {
    "path": "configs/deepfashion/README.md",
    "chars": 2402,
    "preview": "# DeepFashion\n\n<!-- [DATASET] -->\n\n[MMFashion](https://github.com/open-mmlab/mmfashion) develops \"fashion parsing and se"
  },
  {
    "path": "configs/deepfashion/mask_rcnn_r50_fpn_15e_deepfashion.py",
    "chars": 351,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/deepfashion.py', '../_base_/schedules/sc"
  },
  {
    "path": "configs/deformable_detr/README.md",
    "chars": 2658,
    "preview": "# Deformable DETR\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\nWe provide the config files for Deformable DETR: [Deformable D"
  },
  {
    "path": "configs/deformable_detr/deformable_detr_r50_16x2_50e_coco.py",
    "chars": 6440,
    "preview": "_base_ = [\n    '../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'\n]\nmodel = dict(\n    type='Deformab"
  },
  {
    "path": "configs/deformable_detr/deformable_detr_refine_r50_16x2_50e_coco.py",
    "chars": 99,
    "preview": "_base_ = 'deformable_detr_r50_16x2_50e_coco.py'\nmodel = dict(bbox_head=dict(with_box_refine=True))\n"
  },
  {
    "path": "configs/deformable_detr/deformable_detr_twostage_refine_r50_16x2_50e_coco.py",
    "chars": 103,
    "preview": "_base_ = 'deformable_detr_refine_r50_16x2_50e_coco.py'\nmodel = dict(bbox_head=dict(as_two_stage=True))\n"
  },
  {
    "path": "configs/detectors/README.md",
    "chars": 4273,
    "preview": "# DetectoRS\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\nWe provide the config files for [DetectoRS: Detecting Objects with R"
  },
  {
    "path": "configs/detectors/cascade_rcnn_r50_rfp_1x_coco.py",
    "chars": 851,
    "preview": "_base_ = [\n    '../_base_/models/cascade_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sc"
  },
  {
    "path": "configs/detectors/cascade_rcnn_r50_sac_1x_coco.py",
    "chars": 382,
    "preview": "_base_ = [\n    '../_base_/models/cascade_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sc"
  },
  {
    "path": "configs/detectors/detectors_cascade_rcnn_r50_1x_coco.py",
    "chars": 1053,
    "preview": "_base_ = [\n    '../_base_/models/cascade_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sc"
  },
  {
    "path": "configs/detectors/detectors_htc_r50_1x_coco.py",
    "chars": 916,
    "preview": "_base_ = '../htc/htc_r50_fpn_1x_coco.py'\n\nmodel = dict(\n    backbone=dict(\n        type='DetectoRS_ResNet',\n        conv"
  },
  {
    "path": "configs/detectors/htc_r50_rfp_1x_coco.py",
    "chars": 714,
    "preview": "_base_ = '../htc/htc_r50_fpn_1x_coco.py'\n\nmodel = dict(\n    backbone=dict(\n        type='DetectoRS_ResNet',\n        conv"
  },
  {
    "path": "configs/detectors/htc_r50_sac_1x_coco.py",
    "chars": 245,
    "preview": "_base_ = '../htc/htc_r50_fpn_1x_coco.py'\n\nmodel = dict(\n    backbone=dict(\n        type='DetectoRS_ResNet',\n        conv"
  },
  {
    "path": "configs/detr/README.md",
    "chars": 1142,
    "preview": "# DETR\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\nWe provide the config files for DETR: [End-to-End Object Detection with T"
  },
  {
    "path": "configs/detr/detr_r50_8x2_150e_coco.py",
    "chars": 5820,
    "preview": "_base_ = [\n    '../_base_/datasets/coco_detection.py', '../_base_/default_runtime.py'\n]\nmodel = dict(\n    type='DETR',\n "
  },
  {
    "path": "configs/double_heads/README.md",
    "chars": 1163,
    "preview": "# Rethinking Classification and Localization for Object Detection\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@arti"
  },
  {
    "path": "configs/double_heads/dh_faster_rcnn_r50_fpn_1x_coco.py",
    "chars": 845,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        type='DoubleHeadRoIHea"
  },
  {
    "path": "configs/dynamic_rcnn/README.md",
    "chars": 1073,
    "preview": "# Dynamic R-CNN: Towards High Quality Object Detection via Dynamic Training\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```\n"
  },
  {
    "path": "configs/dynamic_rcnn/dynamic_rcnn_r50_fpn_1x_coco.py",
    "chars": 1051,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        type='DynamicRoIHead',"
  },
  {
    "path": "configs/empirical_attention/README.md",
    "chars": 3099,
    "preview": "# An Empirical Study of Spatial Attention Mechanisms in Deep Networks\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@"
  },
  {
    "path": "configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_1x_coco.py",
    "chars": 403,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(plugins=[\n        dict(\n       "
  },
  {
    "path": "configs/empirical_attention/faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py",
    "chars": 575,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        plugins=[\n            "
  },
  {
    "path": "configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_1x_coco.py",
    "chars": 403,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(plugins=[\n        dict(\n       "
  },
  {
    "path": "configs/empirical_attention/faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py",
    "chars": 575,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        plugins=[\n            "
  },
  {
    "path": "configs/fast_rcnn/README.md",
    "chars": 270,
    "preview": "# Fast R-CNN\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@inproceedings{girshick2015fast,\n  title={Fast r-cnn},\n  a"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r101_caffe_fpn_1x_coco.py",
    "chars": 150,
    "preview": "_base_ = './fast_rcnn_r50_caffe_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet101_caffe',\n"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py",
    "chars": 119,
    "preview": "_base_ = './fast_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r101_fpn_2x_coco.py",
    "chars": 119,
    "preview": "_base_ = './fast_rcnn_r50_fpn_2x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 1639,
    "preview": "_base_ = './fast_rcnn_r50_fpn_1x_coco.py'\n\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',\n    ba"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r50_fpn_1x_coco.py",
    "chars": 1944,
    "preview": "_base_ = [\n    '../_base_/models/fast_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sched"
  },
  {
    "path": "configs/fast_rcnn/fast_rcnn_r50_fpn_2x_coco.py",
    "chars": 147,
    "preview": "_base_ = './fast_rcnn_r50_fpn_1x_coco.py'\n\n# learning policy\nlr_config = dict(step=[16, 22])\nrunner = dict(type='EpochBa"
  },
  {
    "path": "configs/faster_rcnn/README.md",
    "chars": 13728,
    "preview": "# Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco.py",
    "chars": 152,
    "preview": "_base_ = './faster_rcnn_r50_caffe_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet101_caffe'"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py",
    "chars": 121,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py",
    "chars": 121,
    "preview": "_base_ = './faster_rcnn_r50_fpn_2x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_c4_1x_coco.py",
    "chars": 1388,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_caffe_c4.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_1x_coco.py",
    "chars": 1304,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_caffe_dc5.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_bas"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py",
    "chars": 1448,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_caffe_dc5.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_bas"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py",
    "chars": 162,
    "preview": "_base_ = './faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py'\n# learning policy\nlr_config = dict(step=[28, 34])\nrunner = dic"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_1x_coco.py",
    "chars": 1331,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',\n    b"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person-bicycle-car.py",
    "chars": 475,
    "preview": "_base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'\nmodel = dict(roi_head=dict(bbox_head=dict(num_classes=3)))\ncla"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person.py",
    "chars": 459,
    "preview": "_base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'\nmodel = dict(roi_head=dict(bbox_head=dict(num_classes=1)))\ncla"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py",
    "chars": 1475,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',\n    b"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py",
    "chars": 162,
    "preview": "_base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'\n# learning policy\nlr_config = dict(step=[16, 23])\nrunner = dic"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py",
    "chars": 162,
    "preview": "_base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'\n# learning policy\nlr_config = dict(step=[28, 34])\nrunner = dic"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_90k_coco.py",
    "chars": 380,
    "preview": "_base_ = 'faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py'\n\n# learning policy\nlr_config = dict(\n    policy='step',\n    warm"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py",
    "chars": 177,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sch"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.py",
    "chars": 177,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sch"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_bounded_iou_1x_coco.py",
    "chars": 207,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        bbox_head=dict(\n            reg_dec"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_giou_1x_coco.py",
    "chars": 201,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        bbox_head=dict(\n            reg_dec"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_iou_1x_coco.py",
    "chars": 200,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    roi_head=dict(\n        bbox_head=dict(\n            reg_dec"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_ohem_1x_coco.py",
    "chars": 118,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(train_cfg=dict(rcnn=dict(sampler=dict(type='OHEMSampler'))))\n"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_r50_fpn_soft_nms_1x_coco.py",
    "chars": 347,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sch"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_1x_coco.py",
    "chars": 370,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    backbone=d"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_x101_32x4d_fpn_2x_coco.py",
    "chars": 370,
    "preview": "_base_ = './faster_rcnn_r50_fpn_2x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    backbone=d"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_1x_coco.py",
    "chars": 370,
    "preview": "_base_ = './faster_rcnn_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    backbone=d"
  },
  {
    "path": "configs/faster_rcnn/faster_rcnn_x101_64x4d_fpn_2x_coco.py",
    "chars": 370,
    "preview": "_base_ = './faster_rcnn_r50_fpn_2x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    backbone=d"
  },
  {
    "path": "configs/fcos/README.md",
    "chars": 5195,
    "preview": "# FCOS: Fully Convolutional One-Stage Object Detection\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@article{tian201"
  },
  {
    "path": "configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_1x_coco.py",
    "chars": 1697,
    "preview": "_base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py'\n\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',"
  },
  {
    "path": "configs/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_1x_coco.py",
    "chars": 1841,
    "preview": "_base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py'\n\nmodel = dict(\n    pretrained='open-mmlab://detectron2/resnet50_caffe',"
  },
  {
    "path": "configs/fcos/fcos_center_r50_caffe_fpn_gn-head_1x_coco.py",
    "chars": 128,
    "preview": "_base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py'\nmodel = dict(bbox_head=dict(center_sampling=True, center_sample_radiu"
  },
  {
    "path": "configs/fcos/fcos_r101_caffe_fpn_gn-head_1x_coco.py",
    "chars": 152,
    "preview": "_base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron/resnet101_caffe'"
  },
  {
    "path": "configs/fcos/fcos_r101_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py",
    "chars": 1478,
    "preview": "_base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://detectron/resnet101_caffe'"
  },
  {
    "path": "configs/fcos/fcos_r50_caffe_fpn_gn-head_1x_coco.py",
    "chars": 3248,
    "preview": "_base_ = [\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/schedules/schedule_1x.py', '../_base_/default_runt"
  },
  {
    "path": "configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py",
    "chars": 166,
    "preview": "# TODO: Remove this config after benchmarking all related configs\n_base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py'\n\ndata"
  },
  {
    "path": "configs/fcos/fcos_r50_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py",
    "chars": 1331,
    "preview": "_base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py'\nimg_norm_cfg = dict(\n    mean=[102.9801, 115.9465, 122.7717], std=[1."
  },
  {
    "path": "configs/fcos/fcos_r50_torch_fpn_gn-head_4x4_1x_coco.py",
    "chars": 469,
    "preview": "# TODO: Remove this config after benchmarking all related configs\n_base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py'\n\ndata"
  },
  {
    "path": "configs/fcos/fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_2x_coco.py",
    "chars": 1915,
    "preview": "_base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    bac"
  },
  {
    "path": "configs/foveabox/README.md",
    "chars": 6029,
    "preview": "# FoveaBox: Beyond Anchor-based Object Detector\n\n<!-- [ALGORITHM] -->\n\nFoveaBox is an accurate, flexible and completely "
  },
  {
    "path": "configs/foveabox/fovea_align_r101_fpn_gn-head_4x4_2x_coco.py",
    "chars": 348,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\nmodel = dict(\n    pretrained='torchvision://resnet101',\n    backbone=dict(dept"
  },
  {
    "path": "configs/foveabox/fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py",
    "chars": 973,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\nmodel = dict(\n    pretrained='torchvision://resnet101',\n    backbone=dict(dept"
  },
  {
    "path": "configs/foveabox/fovea_align_r50_fpn_gn-head_4x4_2x_coco.py",
    "chars": 362,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\nmodel = dict(\n    bbox_head=dict(\n        with_deform=True,\n        norm_cfg=d"
  },
  {
    "path": "configs/foveabox/fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py",
    "chars": 901,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\nmodel = dict(\n    bbox_head=dict(\n        with_deform=True,\n        norm_cfg=d"
  },
  {
    "path": "configs/foveabox/fovea_r101_fpn_4x4_1x_coco.py",
    "chars": 119,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/foveabox/fovea_r101_fpn_4x4_2x_coco.py",
    "chars": 119,
    "preview": "_base_ = './fovea_r50_fpn_4x4_2x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py",
    "chars": 1574,
    "preview": "_base_ = [\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/schedules/schedule_1x.py', '../_base_/default_runt"
  },
  {
    "path": "configs/foveabox/fovea_r50_fpn_4x4_2x_coco.py",
    "chars": 146,
    "preview": "_base_ = './fovea_r50_fpn_4x4_1x_coco.py'\n# learning policy\nlr_config = dict(step=[16, 22])\nrunner = dict(type='EpochBas"
  },
  {
    "path": "configs/fp16/README.md",
    "chars": 2212,
    "preview": "# Mixed Precision Training\n\n## Introduction\n\n<!-- [OTHERS] -->\n\n```latex\n@article{micikevicius2017mixed,\n  title={Mixed "
  },
  {
    "path": "configs/fp16/faster_rcnn_r50_fpn_fp16_1x_coco.py",
    "chars": 102,
    "preview": "_base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py'\n# fp16 settings\nfp16 = dict(loss_scale=512.)\n"
  },
  {
    "path": "configs/fp16/mask_rcnn_r50_fpn_fp16_1x_coco.py",
    "chars": 98,
    "preview": "_base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py'\n# fp16 settings\nfp16 = dict(loss_scale=512.)\n"
  },
  {
    "path": "configs/fp16/retinanet_r50_fpn_fp16_1x_coco.py",
    "chars": 98,
    "preview": "_base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'\n# fp16 settings\nfp16 = dict(loss_scale=512.)\n"
  },
  {
    "path": "configs/fpg/README.md",
    "chars": 3825,
    "preview": "# Feature Pyramid Grids\n\n## Introduction\n\n```latex\n@article{chen2020feature,\n  title={Feature pyramid grids},\n  author={"
  },
  {
    "path": "configs/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py",
    "chars": 314,
    "preview": "_base_ = 'faster_rcnn_r50_fpg_crop640_50e_coco.py'\n\nnorm_cfg = dict(type='BN', requires_grad=True)\nmodel = dict(\n    nec"
  },
  {
    "path": "configs/fpg/faster_rcnn_r50_fpg_crop640_50e_coco.py",
    "chars": 1452,
    "preview": "_base_ = 'faster_rcnn_r50_fpn_crop640_50e_coco.py'\n\nnorm_cfg = dict(type='BN', requires_grad=True)\nmodel = dict(\n    nec"
  },
  {
    "path": "configs/fpg/faster_rcnn_r50_fpn_crop640_50e_coco.py",
    "chars": 2140,
    "preview": "_base_ = [\n    '../_base_/models/faster_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_detection.py',\n    '../_base_/sch"
  },
  {
    "path": "configs/fpg/mask_rcnn_r50_fpg-chn128_crop640_50e_coco.py",
    "chars": 357,
    "preview": "_base_ = 'mask_rcnn_r50_fpg_crop640_50e_coco.py'\n\nmodel = dict(\n    neck=dict(out_channels=128, inter_channels=128),\n   "
  },
  {
    "path": "configs/fpg/mask_rcnn_r50_fpg_crop640_50e_coco.py",
    "chars": 1450,
    "preview": "_base_ = 'mask_rcnn_r50_fpn_crop640_50e_coco.py'\n\nnorm_cfg = dict(type='BN', requires_grad=True)\nmodel = dict(\n    neck="
  },
  {
    "path": "configs/fpg/mask_rcnn_r50_fpn_crop640_50e_coco.py",
    "chars": 2312,
    "preview": "_base_ = [\n    '../_base_/models/mask_rcnn_r50_fpn.py',\n    '../_base_/datasets/coco_instance.py',\n    '../_base_/schedu"
  },
  {
    "path": "configs/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco.py",
    "chars": 154,
    "preview": "_base_ = 'retinanet_r50_fpg_crop640_50e_coco.py'\n\nmodel = dict(\n    neck=dict(out_channels=128, inter_channels=128),\n   "
  },
  {
    "path": "configs/fpg/retinanet_r50_fpg_crop640_50e_coco.py",
    "chars": 1571,
    "preview": "_base_ = '../nas_fpn/retinanet_r50_nasfpn_crop640_50e_coco.py'\n\nnorm_cfg = dict(type='BN', requires_grad=True)\nmodel = d"
  },
  {
    "path": "configs/free_anchor/README.md",
    "chars": 2402,
    "preview": "# FreeAnchor: Learning to Match Anchors for Visual Object Detection\n\n## Introduction\n\n<!-- [ALGORITHM] -->\n\n```latex\n@in"
  },
  {
    "path": "configs/free_anchor/retinanet_free_anchor_r101_fpn_1x_coco.py",
    "chars": 131,
    "preview": "_base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(d"
  },
  {
    "path": "configs/free_anchor/retinanet_free_anchor_r50_fpn_1x_coco.py",
    "chars": 775,
    "preview": "_base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'\nmodel = dict(\n    bbox_head=dict(\n        _delete_=True,\n        ty"
  },
  {
    "path": "configs/free_anchor/retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py",
    "chars": 326,
    "preview": "_base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_32x4d',\n    "
  },
  {
    "path": "configs/fsaf/README.md",
    "chars": 3723,
    "preview": "# Feature Selective Anchor-Free Module for Single-Shot Object Detection\n\n<!-- [ALGORITHM] -->\n\nFSAF is an anchor-free me"
  },
  {
    "path": "configs/fsaf/fsaf_r101_fpn_1x_coco.py",
    "chars": 114,
    "preview": "_base_ = './fsaf_r50_fpn_1x_coco.py'\nmodel = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101))\n"
  },
  {
    "path": "configs/fsaf/fsaf_r50_fpn_1x_coco.py",
    "chars": 1554,
    "preview": "_base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'\n# model settings\nmodel = dict(\n    type='FSAF',\n    bbox_head=dict("
  },
  {
    "path": "configs/fsaf/fsaf_x101_64x4d_fpn_1x_coco.py",
    "chars": 363,
    "preview": "_base_ = './fsaf_r50_fpn_1x_coco.py'\nmodel = dict(\n    pretrained='open-mmlab://resnext101_64x4d',\n    backbone=dict(\n  "
  },
  {
    "path": "configs/gcnet/README.md",
    "chars": 14453,
    "preview": "# GCNet for Object Detection\n\nBy [Yue Cao](http://yue-cao.me), [Jiarui Xu](http://jerryxu.net), [Stephen Lin](https://sc"
  },
  {
    "path": "configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py",
    "chars": 180,
    "preview": "_base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py'\nmodel = dict(\n    backbone=dict(\n        norm_cfg"
  }
]

// ... and 767 more files (download for full content)