├── data └── __init__.py ├── models └── __init__.py ├── downstreams ├── detection │ ├── tools │ │ ├── analysis_tools │ │ │ └── __init__.py │ │ ├── dist_train.sh │ │ └── dist_test.sh │ ├── requirements │ │ ├── readthedocs.txt │ │ ├── build.txt │ │ ├── docs.txt │ │ ├── runtime.txt │ │ ├── optional.txt │ │ └── tests.txt │ ├── demo │ │ ├── demo.jpg │ │ └── demo.mp4 │ ├── mmdet │ │ ├── models │ │ │ ├── roi_heads │ │ │ │ ├── shared_heads │ │ │ │ │ └── __init__.py │ │ │ │ └── roi_extractors │ │ │ │ │ └── __init__.py │ │ │ └── detectors │ │ │ │ └── scnet.py │ │ ├── utils │ │ │ └── __init__.py │ │ ├── core │ │ │ ├── bbox │ │ │ │ ├── iou_calculators │ │ │ │ │ ├── __init__.py │ │ │ │ │ └── builder.py │ │ │ │ ├── match_costs │ │ │ │ │ ├── __init__.py │ │ │ │ │ └── builder.py │ │ │ │ └── assigners │ │ │ │ │ └── base_assigner.py │ │ │ ├── visualization │ │ │ │ └── __init__.py │ │ │ ├── anchor │ │ │ │ └── builder.py │ │ │ ├── utils │ │ │ │ └── __init__.py │ │ │ ├── export │ │ │ │ └── __init__.py │ │ │ ├── __init__.py │ │ │ ├── mask │ │ │ │ └── __init__.py │ │ │ └── post_processing │ │ │ │ └── __init__.py │ │ └── datasets │ │ │ ├── samplers │ │ │ └── __init__.py │ │ │ └── deepfashion.py │ ├── .dev_scripts │ │ └── linter.sh │ ├── resources │ │ ├── loss_curve.png │ │ ├── mmdet-logo.png │ │ ├── data_pipeline.png │ │ ├── coco_test_12510.jpg │ │ └── corruptions_sev_3.png │ ├── tests │ │ ├── test_models │ │ │ ├── test_roi_heads │ │ │ │ └── __init__.py │ │ │ └── test_backbones │ │ │ │ └── __init__.py │ │ └── test_onnx │ │ │ └── __init__.py │ ├── mmcv_custom │ │ ├── __init__.py │ │ └── runner │ │ │ └── __init__.py │ ├── requirements.txt │ ├── configs │ │ ├── reppoints │ │ │ ├── reppoints.png │ │ │ ├── reppoints_minmax_r50_fpn_gn-neck+head_1x_coco.py │ │ │ ├── reppoints_partial_minmax_r50_fpn_gn-neck+head_1x_coco.py │ │ │ ├── bbox_r50_grid_center_fpn_gn-neck+head_1x_coco.py │ │ │ ├── reppoints_moment_r101_fpn_gn-neck+head_2x_coco.py │ │ │ ├── reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py │ │ │ ├── reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py │ │ │ └── reppoints_moment_r101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py │ │ ├── fp16 │ │ │ ├── mask_rcnn_r50_fpn_fp16_1x_coco.py │ │ │ ├── retinanet_r50_fpn_fp16_1x_coco.py │ │ │ └── faster_rcnn_r50_fpn_fp16_1x_coco.py │ │ ├── paa │ │ │ ├── paa_r101_fpn_1x_coco.py │ │ │ ├── paa_r101_fpn_2x_coco.py │ │ │ ├── paa_r50_fpn_1.5x_coco.py │ │ │ ├── paa_r50_fpn_2x_coco.py │ │ │ └── paa_r101_fpn_mstrain_3x_coco.py │ │ ├── rpn │ │ │ ├── rpn_r101_fpn_1x_coco.py │ │ │ ├── rpn_r101_fpn_2x_coco.py │ │ │ ├── rpn_r50_fpn_2x_coco.py │ │ │ └── rpn_r101_caffe_fpn_1x_coco.py │ │ ├── fsaf │ │ │ └── fsaf_r101_fpn_1x_coco.py │ │ ├── scnet │ │ │ ├── scnet_r101_fpn_20e_coco.py │ │ │ ├── scnet_r50_fpn_20e_coco.py │ │ │ └── scnet_x101_64x4d_fpn_8x1_20e_coco.py │ │ ├── vfnet │ │ │ ├── vfnet_r101_fpn_1x_coco.py │ │ │ ├── vfnet_r101_fpn_mstrain_2x_coco.py │ │ │ ├── vfnet_r101_fpn_2x_coco.py │ │ │ └── vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ ├── yolact │ │ │ ├── yolact_r101_1x8_coco.py │ │ │ └── yolact_r50_8x8_coco.py │ │ ├── fast_rcnn │ │ │ ├── fast_rcnn_r101_fpn_1x_coco.py │ │ │ ├── fast_rcnn_r101_fpn_2x_coco.py │ │ │ ├── fast_rcnn_r50_fpn_2x_coco.py │ │ │ ├── fast_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ └── README.md │ │ ├── foveabox │ │ │ ├── fovea_r101_fpn_4x4_1x_coco.py │ │ │ ├── fovea_r101_fpn_4x4_2x_coco.py │ │ │ └── fovea_r50_fpn_4x4_2x_coco.py │ │ ├── ghm │ │ │ └── retinanet_ghm_r101_fpn_1x_coco.py │ │ ├── mask_rcnn │ │ │ ├── mask_rcnn_r101_fpn_1x_coco.py │ │ │ ├── mask_rcnn_r101_fpn_2x_coco.py │ │ │ ├── mask_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_1x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_2x_coco.py │ │ │ ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py │ │ │ └── mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py │ │ ├── retinanet │ │ │ ├── retinanet_r101_fpn_1x_coco.py │ │ │ ├── retinanet_r101_fpn_2x_coco.py │ │ │ ├── retinanet_r50_fpn_2x_coco.py │ │ │ ├── retinanet_r101_caffe_fpn_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 │ │ ├── faster_rcnn │ │ │ ├── faster_rcnn_r101_fpn_1x_coco.py │ │ │ ├── faster_rcnn_r101_fpn_2x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_ohem_1x_coco.py │ │ │ ├── faster_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ ├── faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py │ │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py │ │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_2x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_giou_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_iou_1x_coco.py │ │ │ └── faster_rcnn_r50_fpn_bounded_iou_1x_coco.py │ │ ├── atss │ │ │ └── atss_r101_fpn_1x_coco.py │ │ ├── cascade_rcnn │ │ │ ├── cascade_rcnn_r101_fpn_1x_coco.py │ │ │ ├── cascade_rcnn_r101_fpn_20e_coco.py │ │ │ ├── cascade_mask_rcnn_r101_fpn_1x_coco.py │ │ │ ├── cascade_mask_rcnn_r101_fpn_20e_coco.py │ │ │ ├── cascade_rcnn_r50_fpn_20e_coco.py │ │ │ ├── cascade_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ ├── cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ ├── cascade_rcnn_r50_fpn_1x_coco.py │ │ │ ├── cascade_mask_rcnn_r50_fpn_1x_coco.py │ │ │ └── cascade_mask_rcnn_r50_fpn_20e_coco.py │ │ ├── htc │ │ │ ├── htc_r50_fpn_20e_coco.py │ │ │ └── htc_r101_fpn_20e_coco.py │ │ ├── libra_rcnn │ │ │ └── libra_faster_rcnn_r101_fpn_1x_coco.py │ │ ├── fcos │ │ │ ├── fcos_center_r50_caffe_fpn_gn-head_1x_coco.py │ │ │ ├── fcos_r101_caffe_fpn_gn-head_1x_coco.py │ │ │ └── fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py │ │ ├── grid_rcnn │ │ │ ├── grid_rcnn_r101_fpn_gn-head_2x_coco.py │ │ │ ├── grid_rcnn_r50_fpn_gn-head_1x_coco.py │ │ │ └── grid_rcnn_x101_64x4d_fpn_gn-head_2x_coco.py │ │ ├── free_anchor │ │ │ ├── retinanet_free_anchor_r101_fpn_1x_coco.py │ │ │ └── retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py │ │ ├── instaboost │ │ │ ├── mask_rcnn_r101_fpn_instaboost_4x_coco.py │ │ │ └── cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py │ │ ├── gn │ │ │ ├── mask_rcnn_r101_fpn_gn-all_2x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_gn-all_3x_coco.py │ │ │ ├── mask_rcnn_r101_fpn_gn-all_3x_coco.py │ │ │ └── mask_rcnn_r50_fpn_gn-all_contrib_3x_coco.py │ │ ├── hrnet │ │ │ ├── htc_hrnetv2p_w40_28e_coco.py │ │ │ ├── mask_rcnn_hrnetv2p_w18_2x_coco.py │ │ │ ├── mask_rcnn_hrnetv2p_w32_2x_coco.py │ │ │ ├── mask_rcnn_hrnetv2p_w40_2x_coco.py │ │ │ ├── faster_rcnn_hrnetv2p_w32_2x_coco.py │ │ │ ├── faster_rcnn_hrnetv2p_w40_2x_coco.py │ │ │ ├── faster_rcnn_hrnetv2p_w18_2x_coco.py │ │ │ ├── htc_x101_64x4d_fpn_16x1_28e_coco.py │ │ │ ├── fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py │ │ │ └── fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py │ │ ├── gn+ws │ │ │ ├── mask_rcnn_r101_fpn_gn_ws-all_2x_coco.py │ │ │ ├── faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco.py │ │ │ ├── mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco.py │ │ │ ├── mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco.py │ │ │ └── mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco.py │ │ ├── regnet │ │ │ ├── faster_rcnn_regnetx-3.2GF_fpn_2x_coco.py │ │ │ └── mask_rcnn_regnetx-3.2GF_fpn_mdconv_c3-c5_1x_coco.py │ │ ├── lvis │ │ │ ├── mask_rcnn_r101_fpn_sample1e-3_mstrain_1x_lvis_v1.py │ │ │ └── mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py │ │ ├── ms_rcnn │ │ │ ├── ms_rcnn_r101_caffe_fpn_1x_coco.py │ │ │ ├── ms_rcnn_r101_caffe_fpn_2x_coco.py │ │ │ ├── ms_rcnn_r50_caffe_fpn_2x_coco.py │ │ │ └── ms_rcnn_x101_64x4d_fpn_2x_coco.py │ │ ├── tridentnet │ │ │ └── tridentnet_r50_caffe_mstrain_3x_coco.py │ │ ├── sparse_rcnn │ │ │ ├── sparse_rcnn_r101_fpn_mstrain_480-800_3x_coco.py │ │ │ └── sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py │ │ ├── guided_anchoring │ │ │ ├── ga_faster_r101_caffe_fpn_1x_coco.py │ │ │ ├── ga_retinanet_r101_caffe_fpn_1x_coco.py │ │ │ └── ga_rpn_r101_caffe_fpn_1x_coco.py │ │ ├── fpg │ │ │ ├── retinanet_r50_fpg-chn128_crop640_50e_coco.py │ │ │ └── faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py │ │ ├── gcnet │ │ │ ├── mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py │ │ │ ├── mask_rcnn_r101_fpn_syncbn-backbone_1x_coco.py │ │ │ ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py │ │ │ ├── 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 │ │ │ ├── mask_rcnn_r101_fpn_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_r101_fpn_r16_gcb_c3-c5_1x_coco.py │ │ ├── point_rend │ │ │ └── point_rend_r50_caffe_fpn_mstrain_3x_coco.py │ │ ├── res2net │ │ │ ├── mask_rcnn_r2_101_fpn_2x_coco.py │ │ │ ├── faster_rcnn_r2_101_fpn_2x_coco.py │ │ │ ├── cascade_rcnn_r2_101_fpn_20e_coco.py │ │ │ ├── cascade_mask_rcnn_r2_101_fpn_20e_coco.py │ │ │ └── htc_r2_101_fpn_20e_coco.py │ │ ├── resnest │ │ │ ├── mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ │ ├── cascade_mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ │ ├── cascade_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ │ └── faster_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ ├── pafpn │ │ │ └── faster_rcnn_r50_pafpn_1x_coco.py │ │ ├── dcn │ │ │ ├── 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 │ │ │ ├── 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_mdconv_c3-c5_1x_coco.py │ │ │ ├── cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ │ ├── cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py │ │ │ ├── cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ │ └── cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py │ │ ├── pisa │ │ │ ├── pisa_ssd300_coco.py │ │ │ ├── pisa_ssd512_coco.py │ │ │ ├── pisa_retinanet_r50_fpn_1x_coco.py │ │ │ └── pisa_retinanet_x101_32x4d_fpn_1x_coco.py │ │ ├── detectors │ │ │ └── htc_r50_sac_1x_coco.py │ │ ├── _base_ │ │ │ └── schedules │ │ │ │ ├── schedule_1x.py │ │ │ │ ├── schedule_20e.py │ │ │ │ └── schedule_2x.py │ │ └── gfl │ │ │ └── gfl_r101_fpn_mstrain_2x_coco.py │ ├── .github │ │ ├── ISSUE_TEMPLATE │ │ │ ├── general_questions.md │ │ │ └── config.yml │ │ └── CONTRIBUTING.md │ ├── .readthedocs.yml │ ├── docker │ │ └── serve │ │ │ ├── config.properties │ │ │ └── entrypoint.sh │ ├── docs │ │ └── tutorials │ │ │ └── index.rst │ └── pytest.ini └── segmentation │ ├── requirements │ ├── optional.txt │ ├── readthedocs.txt │ ├── runtime.txt │ ├── docs.txt │ └── tests.txt │ ├── mmseg │ ├── models │ │ ├── necks │ │ │ └── __init__.py │ │ ├── segmentors │ │ │ └── __init__.py │ │ └── utils │ │ │ └── __init__.py │ ├── core │ │ ├── utils │ │ │ └── __init__.py │ │ ├── __init__.py │ │ ├── seg │ │ │ ├── sampler │ │ │ │ ├── __init__.py │ │ │ │ └── base_pixel_sampler.py │ │ │ ├── __init__.py │ │ │ └── builder.py │ │ └── evaluation │ │ │ └── __init__.py │ ├── ops │ │ └── __init__.py │ └── utils │ │ └── __init__.py │ ├── requirements.txt │ ├── demo │ └── demo.png │ ├── resources │ ├── seg_demo.gif │ └── mmseg-logo.png │ ├── mmcv_custom │ └── __init__.py │ ├── configs │ ├── ann │ │ ├── ann_r101-d8_512x512_160k_ade20k.py │ │ ├── ann_r101-d8_512x512_20k_voc12aug.py │ │ ├── ann_r101-d8_512x512_40k_voc12aug.py │ │ ├── ann_r101-d8_512x512_80k_ade20k.py │ │ ├── ann_r101-d8_769x769_40k_cityscapes.py │ │ ├── ann_r101-d8_769x769_80k_cityscapes.py │ │ ├── ann_r101-d8_512x1024_40k_cityscapes.py │ │ ├── ann_r101-d8_512x1024_80k_cityscapes.py │ │ ├── ann_r50-d8_512x1024_40k_cityscapes.py │ │ ├── ann_r50-d8_512x1024_80k_cityscapes.py │ │ ├── ann_r50-d8_512x512_160k_ade20k.py │ │ ├── ann_r50-d8_512x512_80k_ade20k.py │ │ ├── ann_r50-d8_512x512_20k_voc12aug.py │ │ ├── ann_r50-d8_512x512_40k_voc12aug.py │ │ ├── ann_r50-d8_769x769_40k_cityscapes.py │ │ └── ann_r50-d8_769x769_80k_cityscapes.py │ ├── dnlnet │ │ ├── dnl_r101-d8_512x512_80k_ade20k.py │ │ ├── dnl_r101-d8_512x512_160k_ade20k.py │ │ ├── dnl_r101-d8_512x1024_40k_cityscapes.py │ │ ├── dnl_r101-d8_512x1024_80k_cityscapes.py │ │ ├── dnl_r101-d8_769x769_40k_cityscapes.py │ │ ├── dnl_r101-d8_769x769_80k_cityscapes.py │ │ ├── dnl_r50-d8_512x1024_40k_cityscapes.py │ │ ├── dnl_r50-d8_512x1024_80k_cityscapes.py │ │ ├── dnl_r50-d8_512x512_160k_ade20k.py │ │ ├── dnl_r50-d8_512x512_80k_ade20k.py │ │ └── dnl_r50-d8_769x769_40k_cityscapes.py │ ├── fcn │ │ ├── fcn_r101-d8_512x512_160k_ade20k.py │ │ ├── fcn_r101-d8_512x512_20k_voc12aug.py │ │ ├── fcn_r101-d8_512x512_40k_voc12aug.py │ │ ├── fcn_r101-d8_512x512_80k_ade20k.py │ │ ├── fcn_r101-d8_769x769_40k_cityscapes.py │ │ ├── fcn_r101-d8_769x769_80k_cityscapes.py │ │ ├── fcn_r50b-d8_769x769_80k_cityscapes.py │ │ ├── fcn_r101-d8_512x1024_40k_cityscapes.py │ │ ├── fcn_r101-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r50b-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r101-d8_480x480_40k_pascal_context.py │ │ ├── fcn_r101-d8_480x480_80k_pascal_context.py │ │ ├── fcn_r101b-d8_769x769_80k_cityscapes.py │ │ ├── fcn_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r50-d8_512x1024_40k_cityscapes.py │ │ ├── fcn_r50-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r50-d8_512x512_160k_ade20k.py │ │ ├── fcn_r50-d8_512x512_80k_ade20k.py │ │ ├── fcn_r50-d8_512x512_20k_voc12aug.py │ │ ├── fcn_r50-d8_512x512_40k_voc12aug.py │ │ ├── fcn_r18-d8_769x769_80k_cityscapes.py │ │ ├── fcn_r18-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r18b-d8_512x1024_80k_cityscapes.py │ │ ├── fcn_r18b-d8_769x769_80k_cityscapes.py │ │ ├── fcn_r50-d8_769x769_40k_cityscapes.py │ │ └── fcn_r50-d8_769x769_80k_cityscapes.py │ ├── sem_fpn │ │ ├── fpn_r101_512x512_160k_ade20k.py │ │ ├── fpn_r101_512x1024_80k_cityscapes.py │ │ ├── fpn_r50_512x1024_80k_cityscapes.py │ │ └── fpn_r50_512x512_160k_ade20k.py │ ├── apcnet │ │ ├── apcnet_r101-d8_512x512_80k_ade20k.py │ │ ├── apcnet_r101-d8_512x512_160k_ade20k.py │ │ ├── apcnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── apcnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── apcnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── apcnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── apcnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── apcnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── apcnet_r50-d8_512x512_160k_ade20k.py │ │ ├── apcnet_r50-d8_512x512_80k_ade20k.py │ │ └── apcnet_r50-d8_769x769_40k_cityscapes.py │ ├── ccnet │ │ ├── ccnet_r101-d8_512x512_160k_ade20k.py │ │ ├── ccnet_r101-d8_512x512_80k_ade20k.py │ │ ├── ccnet_r101-d8_512x512_20k_voc12aug.py │ │ ├── ccnet_r101-d8_512x512_40k_voc12aug.py │ │ ├── ccnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── ccnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── ccnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── ccnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── ccnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── ccnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── ccnet_r50-d8_512x512_80k_ade20k.py │ │ ├── ccnet_r50-d8_512x512_160k_ade20k.py │ │ ├── ccnet_r50-d8_512x512_20k_voc12aug.py │ │ ├── ccnet_r50-d8_512x512_40k_voc12aug.py │ │ ├── ccnet_r50-d8_769x769_40k_cityscapes.py │ │ └── ccnet_r50-d8_769x769_80k_cityscapes.py │ ├── danet │ │ ├── danet_r101-d8_512x512_160k_ade20k.py │ │ ├── danet_r101-d8_512x512_80k_ade20k.py │ │ ├── danet_r101-d8_512x512_20k_voc12aug.py │ │ ├── danet_r101-d8_512x512_40k_voc12aug.py │ │ ├── danet_r101-d8_769x769_40k_cityscapes.py │ │ ├── danet_r101-d8_769x769_80k_cityscapes.py │ │ ├── danet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── danet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── danet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── danet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── danet_r50-d8_512x512_80k_ade20k.py │ │ ├── danet_r50-d8_512x512_160k_ade20k.py │ │ ├── danet_r50-d8_512x512_20k_voc12aug.py │ │ ├── danet_r50-d8_512x512_40k_voc12aug.py │ │ ├── danet_r50-d8_769x769_40k_cityscapes.py │ │ └── danet_r50-d8_769x769_80k_cityscapes.py │ ├── dmnet │ │ ├── dmnet_r101-d8_512x512_160k_ade20k.py │ │ ├── dmnet_r101-d8_512x512_80k_ade20k.py │ │ ├── dmnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── dmnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── dmnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── dmnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── dmnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── dmnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── dmnet_r50-d8_512x512_80k_ade20k.py │ │ ├── dmnet_r50-d8_512x512_160k_ade20k.py │ │ ├── dmnet_r50-d8_769x769_40k_cityscapes.py │ │ └── dmnet_r50-d8_769x769_80k_cityscapes.py │ ├── encnet │ │ ├── encnet_r101-d8_512x512_80k_ade20k.py │ │ ├── encnet_r101-d8_512x512_160k_ade20k.py │ │ ├── encnet_r101-d8_512x512_20k_voc12aug.py │ │ ├── encnet_r101-d8_512x512_40k_voc12aug.py │ │ ├── encnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── encnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── encnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── encnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── encnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── encnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── encnet_r50-d8_512x512_160k_ade20k.py │ │ ├── encnet_r50-d8_512x512_80k_ade20k.py │ │ ├── encnet_r50-d8_512x512_20k_voc12aug.py │ │ ├── encnet_r50-d8_512x512_40k_voc12aug.py │ │ └── encnet_r50s-d8_512x512_80k_ade20k.py │ ├── gcnet │ │ ├── gcnet_r101-d8_512x512_160k_ade20k.py │ │ ├── gcnet_r101-d8_512x512_80k_ade20k.py │ │ ├── gcnet_r101-d8_512x512_20k_voc12aug.py │ │ ├── gcnet_r101-d8_512x512_40k_voc12aug.py │ │ ├── gcnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── gcnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── gcnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── gcnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── gcnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── gcnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── gcnet_r50-d8_512x512_80k_ade20k.py │ │ ├── gcnet_r50-d8_512x512_160k_ade20k.py │ │ ├── gcnet_r50-d8_512x512_20k_voc12aug.py │ │ ├── gcnet_r50-d8_512x512_40k_voc12aug.py │ │ ├── gcnet_r50-d8_769x769_40k_cityscapes.py │ │ └── gcnet_r50-d8_769x769_80k_cityscapes.py │ ├── psanet │ │ ├── psanet_r101-d8_512x512_80k_ade20k.py │ │ ├── psanet_r101-d8_512x512_160k_ade20k.py │ │ ├── psanet_r101-d8_512x512_20k_voc12aug.py │ │ ├── psanet_r101-d8_512x512_40k_voc12aug.py │ │ ├── psanet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── psanet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── psanet_r101-d8_769x769_40k_cityscapes.py │ │ ├── psanet_r101-d8_769x769_80k_cityscapes.py │ │ ├── psanet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── psanet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── psanet_r50-d8_512x512_20k_voc12aug.py │ │ ├── psanet_r50-d8_512x512_40k_voc12aug.py │ │ ├── psanet_r50-d8_512x512_80k_ade20k.py │ │ └── psanet_r50-d8_512x512_160k_ade20k.py │ ├── pspnet │ │ ├── pspnet_r101-d8_512x512_80k_ade20k.py │ │ ├── pspnet_r101-d8_512x512_160k_ade20k.py │ │ ├── pspnet_r101-d8_512x512_20k_voc12aug.py │ │ ├── pspnet_r101-d8_512x512_40k_voc12aug.py │ │ ├── pspnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── pspnet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── pspnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r50b-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r50b-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r101-d8_480x480_40k_pascal_context.py │ │ ├── pspnet_r101-d8_480x480_80k_pascal_context.py │ │ ├── pspnet_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r101b-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── pspnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r50-d8_512x512_160k_ade20k.py │ │ ├── pspnet_r50-d8_512x512_80k_ade20k.py │ │ ├── pspnet_r50-d8_512x512_20k_voc12aug.py │ │ ├── pspnet_r50-d8_512x512_40k_voc12aug.py │ │ ├── pspnet_r18-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r18-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r18b-d8_512x1024_80k_cityscapes.py │ │ └── pspnet_r18b-d8_769x769_80k_cityscapes.py │ ├── upernet │ │ ├── upernet_r101_512x512_160k_ade20k.py │ │ ├── upernet_r101_512x512_80k_ade20k.py │ │ ├── upernet_r101_512x512_20k_voc12aug.py │ │ ├── upernet_r101_512x512_40k_voc12aug.py │ │ ├── upernet_r101_769x769_40k_cityscapes.py │ │ ├── upernet_r101_769x769_80k_cityscapes.py │ │ ├── upernet_r101_512x1024_40k_cityscapes.py │ │ ├── upernet_r101_512x1024_80k_cityscapes.py │ │ ├── upernet_r50_512x1024_40k_cityscapes.py │ │ ├── upernet_r50_512x1024_80k_cityscapes.py │ │ ├── upernet_r50_512x512_80k_ade20k.py │ │ ├── upernet_r50_512x512_160k_ade20k.py │ │ ├── upernet_r50_512x512_20k_voc12aug.py │ │ ├── upernet_r50_512x512_40k_voc12aug.py │ │ ├── upernet_r50_769x769_40k_cityscapes.py │ │ └── upernet_r50_769x769_80k_cityscapes.py │ ├── deeplabv3 │ │ ├── deeplabv3_r101-d8_512x512_80k_ade20k.py │ │ ├── deeplabv3_r101-d8_512x512_160k_ade20k.py │ │ ├── deeplabv3_r101-d8_512x512_20k_voc12aug.py │ │ ├── deeplabv3_r101-d8_512x512_40k_voc12aug.py │ │ ├── deeplabv3_r101-d8_512x1024_40k_cityscapes.py │ │ ├── deeplabv3_r101-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_r101-d8_769x769_40k_cityscapes.py │ │ ├── deeplabv3_r101-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3_r50b-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_r50b-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3_r101-d8_480x480_40k_pascal_context.py │ │ ├── deeplabv3_r101-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_r101b-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3_r50-d8_512x1024_40k_cityscapes.py │ │ ├── deeplabv3_r50-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_r50-d8_512x512_160k_ade20k.py │ │ ├── deeplabv3_r50-d8_512x512_80k_ade20k.py │ │ ├── deeplabv3_r50-d8_512x512_20k_voc12aug.py │ │ ├── deeplabv3_r50-d8_512x512_40k_voc12aug.py │ │ ├── deeplabv3_r18-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_r18-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3_r18b-d8_769x769_80k_cityscapes.py │ │ └── deeplabv3_r18b-d8_512x1024_80k_cityscapes.py │ ├── emanet │ │ ├── emanet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── emanet_r101-d8_769x769_80k_cityscapes.py │ │ └── emanet_r50-d8_512x1024_80k_cityscapes.py │ ├── nonlocal_net │ │ ├── nonlocal_r101-d8_512x512_80k_ade20k.py │ │ ├── nonlocal_r101-d8_512x512_160k_ade20k.py │ │ ├── nonlocal_r101-d8_512x512_20k_voc12aug.py │ │ ├── nonlocal_r101-d8_512x512_40k_voc12aug.py │ │ ├── nonlocal_r101-d8_512x1024_40k_cityscapes.py │ │ ├── nonlocal_r101-d8_512x1024_80k_cityscapes.py │ │ ├── nonlocal_r101-d8_769x769_40k_cityscapes.py │ │ ├── nonlocal_r101-d8_769x769_80k_cityscapes.py │ │ ├── nonlocal_r50-d8_512x1024_40k_cityscapes.py │ │ ├── nonlocal_r50-d8_512x1024_80k_cityscapes.py │ │ ├── nonlocal_r50-d8_512x512_160k_ade20k.py │ │ ├── nonlocal_r50-d8_512x512_80k_ade20k.py │ │ ├── nonlocal_r50-d8_512x512_20k_voc12aug.py │ │ └── nonlocal_r50-d8_512x512_40k_voc12aug.py │ ├── point_rend │ │ ├── pointrend_r101_512x512_160k_ade20k.py │ │ ├── pointrend_r101_512x1024_80k_cityscapes.py │ │ └── pointrend_r50_512x1024_80k_cityscapes.py │ ├── fp16 │ │ ├── fcn_r101-d8_512x1024_80k_fp16_cityscapes.py │ │ ├── pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py │ │ ├── deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py │ │ └── deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py │ ├── deeplabv3plus │ │ ├── deeplabv3plus_r101-d8_512x512_160k_ade20k.py │ │ ├── deeplabv3plus_r101-d8_512x512_20k_voc12aug.py │ │ ├── deeplabv3plus_r101-d8_512x512_40k_voc12aug.py │ │ ├── deeplabv3plus_r101-d8_512x512_80k_ade20k.py │ │ ├── deeplabv3plus_r101-d8_769x769_40k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_480x480_40k_pascal_context.py │ │ ├── deeplabv3plus_r101-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py │ │ ├── deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r50-d8_512x512_160k_ade20k.py │ │ ├── deeplabv3plus_r50-d8_512x512_80k_ade20k.py │ │ ├── deeplabv3plus_r50-d8_512x512_20k_voc12aug.py │ │ └── deeplabv3plus_r50-d8_512x512_40k_voc12aug.py │ ├── hrnet │ │ ├── fcn_hr18_512x1024_160k_cityscapes.py │ │ ├── fcn_hr18_512x1024_40k_cityscapes.py │ │ ├── fcn_hr18_512x1024_80k_cityscapes.py │ │ ├── fcn_hr18_512x512_80k_ade20k.py │ │ ├── fcn_hr18_512x512_160k_ade20k.py │ │ ├── fcn_hr18_512x512_20k_voc12aug.py │ │ ├── fcn_hr18_512x512_40k_voc12aug.py │ │ ├── fcn_hr18_480x480_40k_pascal_context.py │ │ └── fcn_hr18_480x480_80k_pascal_context.py │ ├── ocrnet │ │ ├── ocrnet_hr18_512x1024_160k_cityscapes.py │ │ ├── ocrnet_hr18_512x1024_40k_cityscapes.py │ │ ├── ocrnet_hr18_512x1024_80k_cityscapes.py │ │ ├── ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py │ │ ├── ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py │ │ └── ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py │ ├── unet │ │ ├── fcn_unet_s5-d16_256x256_40k_hrf.py │ │ ├── fcn_unet_s5-d16_64x64_40k_drive.py │ │ ├── fcn_unet_s5-d16_128x128_40k_stare.py │ │ ├── pspnet_unet_s5-d16_64x64_40k_drive.py │ │ ├── deeplabv3_unet_s5-d16_64x64_40k_drive.py │ │ ├── fcn_unet_s5-d16_128x128_40k_chase_db1.py │ │ ├── pspnet_unet_s5-d16_128x128_40k_stare.py │ │ ├── pspnet_unet_s5-d16_256x256_40k_hrf.py │ │ ├── deeplabv3_unet_s5-d16_128x128_40k_stare.py │ │ ├── deeplabv3_unet_s5-d16_256x256_40k_hrf.py │ │ ├── pspnet_unet_s5-d16_128x128_40k_chase_db1.py │ │ └── deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py │ ├── _base_ │ │ ├── datasets │ │ │ └── pascal_voc12_aug.py │ │ └── default_runtime.py │ ├── resnest │ │ ├── fcn_s101-d8_512x512_160k_ade20k.py │ │ ├── fcn_s101-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_s101-d8_512x512_160k_ade20k.py │ │ ├── pspnet_s101-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3_s101-d8_512x512_160k_ade20k.py │ │ ├── deeplabv3_s101-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_s101-d8_512x512_160k_ade20k.py │ │ └── deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py │ ├── mobilenet_v3 │ │ └── lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py │ └── fastscnn │ │ └── fast_scnn_4x8_80k_lr0.12_cityscapes.py │ ├── .github │ └── ISSUE_TEMPLATE │ │ ├── general_questions.md │ │ └── config.yml │ ├── .readthedocs.yml │ ├── docs │ └── tutorials │ │ └── index.rst │ ├── tools │ ├── dist_train.sh │ └── dist_test.sh │ └── pytest.ini ├── figures └── relation.png └── configs ├── dwnet_base_patch4_window7_224.yaml ├── dwnet_tiny_patch4_window7_224.yaml ├── dynamic_dwnet_tiny_patch4_window7_224.yaml ├── dynamic_dwnet_base_patch4_window7_224.yaml ├── i_dynamic_dwnet_base_patch4_window7_224.yaml └── i_dynamic_dwnet_tiny_patch4_window7_224.yaml /data/__init__.py: -------------------------------------------------------------------------------- 1 | from .build import build_loader -------------------------------------------------------------------------------- /models/__init__.py: -------------------------------------------------------------------------------- 1 | from .build import build_model -------------------------------------------------------------------------------- /downstreams/detection/tools/analysis_tools/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | cityscapesscripts 2 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | torch 3 | torchvision 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | torch 3 | torchvision 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | numpy 3 | terminaltables 4 | timm 5 | -------------------------------------------------------------------------------- /figures/relation.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/figures/relation.png -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/models/necks/__init__.py: -------------------------------------------------------------------------------- 1 | from .fpn import FPN 2 | 3 | __all__ = ['FPN'] 4 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/build.txt: -------------------------------------------------------------------------------- 1 | # These must be installed before building mmdetection 2 | cython 3 | numpy 4 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | recommonmark 2 | sphinx 3 | sphinx_markdown_tables 4 | sphinx_rtd_theme 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .misc import add_prefix 2 | 3 | __all__ = ['add_prefix'] 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | recommonmark 2 | sphinx 3 | sphinx_markdown_tables 4 | sphinx_rtd_theme 5 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | mmpycocotools 3 | numpy 4 | six 5 | terminaltables 6 | timm 7 | -------------------------------------------------------------------------------- /downstreams/detection/demo/demo.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/demo/demo.jpg -------------------------------------------------------------------------------- /downstreams/detection/demo/demo.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/demo/demo.mp4 -------------------------------------------------------------------------------- /downstreams/detection/mmdet/models/roi_heads/shared_heads/__init__.py: -------------------------------------------------------------------------------- 1 | from .res_layer import ResLayer 2 | 3 | __all__ = ['ResLayer'] 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/optional.txt 2 | -r requirements/runtime.txt 3 | -r requirements/tests.txt 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/demo/demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/segmentation/demo/demo.png -------------------------------------------------------------------------------- /downstreams/detection/.dev_scripts/linter.sh: -------------------------------------------------------------------------------- 1 | yapf -r -i mmdet/ configs/ tests/ tools/ 2 | isort -rc mmdet/ configs/ tests/ tools/ 3 | flake8 . 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/requirements/tests.txt: -------------------------------------------------------------------------------- 1 | codecov 2 | flake8 3 | interrogate 4 | isort==4.3.21 5 | pytest 6 | xdoctest>=0.10.0 7 | yapf 8 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | albumentations>=0.3.2 2 | cityscapesscripts 3 | imagecorruptions 4 | mmlvis 5 | scipy 6 | sklearn 7 | -------------------------------------------------------------------------------- /downstreams/detection/resources/loss_curve.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/resources/loss_curve.png -------------------------------------------------------------------------------- /downstreams/detection/resources/mmdet-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/resources/mmdet-logo.png -------------------------------------------------------------------------------- /downstreams/detection/tests/test_models/test_roi_heads/__init__.py: -------------------------------------------------------------------------------- 1 | from .utils import _dummy_bbox_sampling 2 | 3 | __all__ = ['_dummy_bbox_sampling'] 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/resources/seg_demo.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/segmentation/resources/seg_demo.gif -------------------------------------------------------------------------------- /downstreams/detection/mmcv_custom/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | from .checkpoint import load_checkpoint 4 | 5 | __all__ = ['load_checkpoint'] 6 | -------------------------------------------------------------------------------- /downstreams/detection/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/build.txt 2 | -r requirements/optional.txt 3 | -r requirements/runtime.txt 4 | -r requirements/tests.txt 5 | -------------------------------------------------------------------------------- /downstreams/detection/resources/data_pipeline.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/resources/data_pipeline.png -------------------------------------------------------------------------------- /downstreams/segmentation/resources/mmseg-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/segmentation/resources/mmseg-logo.png -------------------------------------------------------------------------------- /downstreams/detection/resources/coco_test_12510.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/resources/coco_test_12510.jpg -------------------------------------------------------------------------------- /downstreams/segmentation/mmcv_custom/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | from .checkpoint import load_checkpoint 4 | 5 | __all__ = ['load_checkpoint'] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/configs/reppoints/reppoints.png -------------------------------------------------------------------------------- /downstreams/detection/resources/corruptions_sev_3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Atten4Vis/DemystifyLocalViT/HEAD/downstreams/detection/resources/corruptions_sev_3.png -------------------------------------------------------------------------------- /downstreams/detection/configs/fp16/mask_rcnn_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fp16/retinanet_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/paa/paa_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/rpn/rpn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/rpn/rpn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_fpn_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/ops/__init__.py: -------------------------------------------------------------------------------- 1 | from .encoding import Encoding 2 | from .wrappers import Upsample, resize 3 | 4 | __all__ = ['Upsample', 'resize', 'Encoding'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fsaf/fsaf_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fsaf_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .collect_env import collect_env 2 | from .logger import get_root_logger 3 | 4 | __all__ = ['get_root_logger', 'collect_env'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fp16/faster_rcnn_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/scnet/scnet_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './scnet_r50_fpn_20e_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/vfnet/vfnet_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/yolact/yolact_r101_1x8_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolact_r50_1x8_coco.py' 2 | 3 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/tests/test_models/test_backbones/__init__.py: -------------------------------------------------------------------------------- 1 | from .utils import check_norm_state, is_block, is_norm 2 | 3 | __all__ = ['is_block', 'is_norm', 'check_norm_state'] 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/__init__.py: -------------------------------------------------------------------------------- 1 | from .evaluation import * # noqa: F401, F403 2 | from .seg import * # noqa: F401, F403 3 | from .utils import * # noqa: F401, F403 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/paa/paa_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r101_fpn_1x_coco.py' 2 | lr_config = dict(step=[16, 22]) 3 | runner = dict(type='EpochBasedRunner', max_epochs=24) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/paa/paa_r50_fpn_1.5x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_1x_coco.py' 2 | lr_config = dict(step=[12, 16]) 3 | runner = dict(type='EpochBasedRunner', max_epochs=18) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/paa/paa_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_1x_coco.py' 2 | lr_config = dict(step=[16, 22]) 3 | runner = dict(type='EpochBasedRunner', max_epochs=24) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fast_rcnn/fast_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_fpn_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/foveabox/fovea_r101_fpn_4x4_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fovea_r50_fpn_4x4_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/foveabox/fovea_r101_fpn_4x4_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fovea_r50_fpn_4x4_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/ghm/retinanet_ghm_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_ghm_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/paa/paa_r101_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_mstrain_3x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_ohem_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(train_cfg=dict(rcnn=dict(sampler=dict(type='OHEMSampler')))) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/vfnet/vfnet_r101_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_mstrain_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/.github/ISSUE_TEMPLATE/general_questions.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: General questions 3 | about: Ask general questions to get help 4 | title: '' 5 | labels: '' 6 | assignees: '' 7 | 8 | --- 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/atss/atss_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './atss_r50_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(depth=101), 5 | ) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/sem_fpn/fpn_r101_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/.readthedocs.yml: -------------------------------------------------------------------------------- 1 | version: 2 2 | 3 | python: 4 | version: 3.7 5 | install: 6 | - requirements: requirements/docs.txt 7 | - requirements: requirements/readthedocs.txt 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/htc/htc_r50_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './htc_r50_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 19]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=20) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/libra_rcnn/libra_faster_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './libra_faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/.github/ISSUE_TEMPLATE/general_questions.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: General questions 3 | about: Ask general questions to get help 4 | title: '' 5 | labels: '' 6 | assignees: '' 7 | 8 | --- 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/sem_fpn/fpn_r101_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_fpn_20e_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fcos/fcos_center_r50_caffe_fpn_gn-head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py' 2 | model = dict(bbox_head=dict(center_sampling=True, center_sample_radius=1.5)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/grid_rcnn/grid_rcnn_r101_fpn_gn-head_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './grid_rcnn_r50_fpn_gn-head_2x_coco.py' 2 | 3 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_minmax_r50_fpn_gn-neck+head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py' 2 | model = dict(bbox_head=dict(transform_method='minmax')) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/rpn/rpn_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_fpn_1x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[16, 22]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=24) 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/.readthedocs.yml: -------------------------------------------------------------------------------- 1 | version: 2 2 | 3 | python: 4 | version: 3.7 5 | install: 6 | - requirements: requirements/docs.txt 7 | - requirements: requirements/readthedocs.txt 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/free_anchor/retinanet_free_anchor_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/instaboost/mask_rcnn_r101_fpn_instaboost_4x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/rpn/rpn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/scnet/scnet_r50_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './scnet_r50_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 19]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=20) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/emanet/emanet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './emanet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/emanet/emanet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './emanet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_480x480_40k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_480x480_40k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101-d8_480x480_80k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_480x480_80k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/point_rend/pointrend_r101_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pointrend_r50_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r101_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /configs/dwnet_base_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: dwnet 3 | NAME: dwnet_base_patch4_window7_224 4 | DROP_PATH_RATE: 0.5 5 | DWNET: 6 | EMBED_DIM: 128 7 | DEPTHS: [ 2, 2, 18, 2 ] 8 | WINDOW_SIZE: 7 -------------------------------------------------------------------------------- /configs/dwnet_tiny_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: dwnet 3 | NAME: dwnet_tiny_patch4_window7_224 4 | DROP_PATH_RATE: 0.2 5 | DWNET: 6 | EMBED_DIM: 96 7 | DEPTHS: [ 2, 2, 6, 2 ] 8 | WINDOW_SIZE: 7 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn/mask_rcnn_r101_fpn_gn-all_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_gn-all_2x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron/resnet101_gn', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/htc_hrnetv2p_w40_28e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './htc_hrnetv2p_w40_20e_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[24, 27]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=28) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/point_rend/pointrend_r101_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pointrend_r50_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/seg/sampler/__init__.py: -------------------------------------------------------------------------------- 1 | from .base_pixel_sampler import BasePixelSampler 2 | from .ohem_pixel_sampler import OHEMPixelSampler 3 | 4 | __all__ = ['BasePixelSampler', 'OHEMPixelSampler'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/foveabox/fovea_r50_fpn_4x4_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fovea_r50_fpn_4x4_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/mask_rcnn_r101_fpn_gn_ws-all_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://jhu/resnet101_gn_ws', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/regnet/faster_rcnn_regnetx-3.2GF_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_regnetx-3.2GF_fpn_1x_coco.py' 2 | lr_config = dict(step=[16, 22]) 3 | runner = dict(type='EpochBasedRunner', max_epochs=24) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_partial_minmax_r50_fpn_gn-neck+head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py' 2 | model = dict(bbox_head=dict(transform_method='partial_minmax')) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_480x480_40k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_480x480_40k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101-d8_480x480_80k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_480x480_80k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fast_rcnn/fast_rcnn_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_fpn_1x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[16, 22]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=24) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://jhu/resnet101_gn_ws', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_hrnetv2p_w18_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_hrnetv2p_w32_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_hrnetv2p_w40_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/lvis/mask_rcnn_r101_fpn_sample1e-3_mstrain_1x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/ms_rcnn/ms_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ms_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/ms_rcnn/ms_rcnn_r101_caffe_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ms_rcnn_r101_caffe_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/ms_rcnn/ms_rcnn_r50_caffe_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ms_rcnn_r50_caffe_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/ms_rcnn/ms_rcnn_x101_64x4d_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ms_rcnn_x101_64x4d_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/bbox_r50_grid_center_fpn_gn-neck+head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py' 2 | model = dict(bbox_head=dict(transform_method='minmax', use_grid_points=True)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_moment_r101_fpn_gn-neck+head_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/tridentnet/tridentnet_r50_caffe_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'tridentnet_r50_caffe_mstrain_1x_coco.py' 2 | 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_480x480_40k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_480x480_80k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/models/segmentors/__init__.py: -------------------------------------------------------------------------------- 1 | from .cascade_encoder_decoder import CascadeEncoderDecoder 2 | from .encoder_decoder import EncoderDecoder 3 | 4 | __all__ = ['EncoderDecoder', 'CascadeEncoderDecoder'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_rcnn_r50_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 19]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=20) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fast_rcnn/fast_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fcos/fcos_r101_caffe_fpn_gn-head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcos_r50_caffe_fpn_gn-head_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn/mask_rcnn_r50_fpn_gn-all_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_gn-all_2x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[28, 34]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=36) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_hrnetv2p_w32_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_hrnetv2p_w40_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/instaboost/cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py' 2 | 3 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/lvis/mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/sparse_rcnn/sparse_rcnn_r101_fpn_mstrain_480-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './sparse_rcnn_r50_fpn_mstrain_480-800_3x_coco.py' 2 | 3 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/seg/__init__.py: -------------------------------------------------------------------------------- 1 | from .builder import build_pixel_sampler 2 | from .sampler import BasePixelSampler, OHEMPixelSampler 3 | 4 | __all__ = ['build_pixel_sampler', 'BasePixelSampler', 'OHEMPixelSampler'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn/mask_rcnn_r101_fpn_gn-all_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r101_fpn_gn-all_2x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[28, 34]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=36) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/guided_anchoring/ga_faster_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ga_faster_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_hrnetv2p_w18_1x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[16, 22]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=24) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/htc_x101_64x4d_fpn_16x1_28e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../htc/htc_x101_64x4d_fpn_16x1_20e_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[24, 27]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=28) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py' 2 | lr_config = dict(step=[16, 22]) 3 | runner = dict(type='EpochBasedRunner', max_epochs=24) 4 | -------------------------------------------------------------------------------- /downstreams/detection/docker/serve/config.properties: -------------------------------------------------------------------------------- 1 | inference_address=http://0.0.0.0:8080 2 | management_address=http://0.0.0.0:8081 3 | metrics_address=http://0.0.0.0:8082 4 | model_store=/home/model-server/model-store 5 | load_models=all 6 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .collect_env import collect_env 2 | from .logger import get_root_logger 3 | from .optimizer import DistOptimizerHook 4 | 5 | __all__ = ['get_root_logger', 'collect_env', 'DistOptimizerHook'] 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r101b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fpg/retinanet_r50_fpg-chn128_crop640_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_r50_fpg_crop640_50e_coco.py' 2 | 3 | model = dict( 4 | neck=dict(out_channels=128, inter_channels=128), 5 | bbox_head=dict(in_channels=128)) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[20, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/scnet/scnet_x101_64x4d_fpn_8x1_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './scnet_x101_64x4d_fpn_20e_coco.py' 2 | data = dict(samples_per_gpu=1, workers_per_gpu=1) 3 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_480x480_40k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_480x480_80k_pascal_context.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x1024_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r101b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/sem_fpn/fpn_r50_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fpn_r50.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/docs/tutorials/index.rst: -------------------------------------------------------------------------------- 1 | .. toctree:: 2 | :maxdepth: 2 3 | 4 | config.md 5 | customize_datasets.md 6 | data_pipeline.md 7 | customize_models.md 8 | training_tricks.md 9 | customize_runtime.md 10 | -------------------------------------------------------------------------------- /configs/dynamic_dwnet_tiny_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: ddwnet 3 | NAME: ddwnet_tiny_patch4_window7_224 4 | DROP_PATH_RATE: 0.2 5 | DWNET: 6 | EMBED_DIM: 96 7 | DEPTHS: [ 2, 2, 6, 2 ] 8 | WINDOW_SIZE: 7 9 | DYNAMIC: True -------------------------------------------------------------------------------- /downstreams/detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py: -------------------------------------------------------------------------------- 1 | # TODO: Remove this config after benchmarking all related configs 2 | _base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py' 3 | 4 | data = dict(samples_per_gpu=4, workers_per_gpu=4) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r101_fpn_gn_ws-all_2x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[20, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn/mask_rcnn_r50_fpn_gn-all_contrib_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_gn-all_contrib_2x_coco.py' 2 | 3 | # learning policy 4 | lr_config = dict(step=[28, 34]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=36) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/guided_anchoring/ga_retinanet_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ga_retinanet_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r50_caffe_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r50_caffe_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/bbox/iou_calculators/__init__.py: -------------------------------------------------------------------------------- 1 | from .builder import build_iou_calculator 2 | from .iou2d_calculator import BboxOverlaps2D, bbox_overlaps 3 | 4 | __all__ = ['build_iou_calculator', 'BboxOverlaps2D', 'bbox_overlaps'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/visualization/__init__.py: -------------------------------------------------------------------------------- 1 | from .image import (color_val_matplotlib, imshow_det_bboxes, 2 | imshow_gt_det_bboxes) 3 | 4 | __all__ = ['imshow_det_bboxes', 'imshow_gt_det_bboxes', 'color_val_matplotlib'] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_hr18_512x1024_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_hr18_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_hr18_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/detection/.github/CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | We appreciate all contributions to improve MMDetection. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline. 2 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://detectron2/resnet101_caffe', 4 | backbone=dict(depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r101_fpn_syncbn-backbone_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/guided_anchoring/ga_rpn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './ga_rpn_r50_caffe_fpn_1x_coco.py' 2 | # model settings 3 | model = dict( 4 | pretrained='open-mmlab://detectron2/resnet101_caffe', 5 | backbone=dict(depth=101)) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/mask_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_instance.py', 4 | '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/mask_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_instance.py', 4 | '../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/point_rend/point_rend_r50_caffe_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './point_rend_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r101b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/emanet/emanet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/emanet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[20, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gn+ws/mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[20, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[16, 23]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py' 2 | # learning policy 3 | lr_config = dict(step=[28, 34]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=36) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/datasets/samplers/__init__.py: -------------------------------------------------------------------------------- 1 | from .distributed_sampler import DistributedSampler 2 | from .group_sampler import DistributedGroupSampler, GroupSampler 3 | 4 | __all__ = ['DistributedSampler', 'DistributedGroupSampler', 'GroupSampler'] 5 | -------------------------------------------------------------------------------- /downstreams/detection/tests/test_onnx/__init__.py: -------------------------------------------------------------------------------- 1 | from .utils import (WrapFunction, convert_result_list, ort_validate, 2 | verify_model) 3 | 4 | __all__ = [ 5 | 'WrapFunction', 'verify_model', 'convert_result_list', 'ort_validate' 6 | ] 7 | -------------------------------------------------------------------------------- /configs/dynamic_dwnet_base_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: ddwnet 3 | NAME: ddwnet_base_patch4_window7_224 4 | DROP_PATH_RATE: 0.5 5 | DWNET: 6 | EMBED_DIM: 128 7 | DEPTHS: [ 2, 2, 18, 2 ] 8 | WINDOW_SIZE: 7 9 | DYNAMIC: True 10 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/cascade_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_detection.py', 4 | '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/faster_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_detection.py', 4 | '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/faster_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_detection.py', 4 | '../_base_/schedules/schedule_2x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/res2net/mask_rcnn_r2_101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://res2net101_v1d_26w_4s', 4 | backbone=dict(type='Res2Net', depth=101, scales=4, base_width=26)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/sparse_rcnn/sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py' 2 | 3 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 4 | -------------------------------------------------------------------------------- /downstreams/detection/configs/vfnet/vfnet_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | lr_config = dict(step=[16, 22]) 4 | runner = dict(type='EpochBasedRunner', max_epochs=24) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/cascade_mask_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_instance.py', 4 | '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/cascade_mask_rcnn_r50_fpn.py', 3 | '../_base_/datasets/coco_instance.py', 4 | '../_base_/schedules/schedule_20e.py', '../_base_/default_runtime.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/res2net/faster_rcnn_r2_101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://res2net101_v1d_26w_4s', 4 | backbone=dict(type='Res2Net', depth=101, scales=4, base_width=26)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/models/roi_heads/roi_extractors/__init__.py: -------------------------------------------------------------------------------- 1 | from .generic_roi_extractor import GenericRoIExtractor 2 | from .single_level_roi_extractor import SingleRoIExtractor 3 | 4 | __all__ = [ 5 | 'SingleRoIExtractor', 6 | 'GenericRoIExtractor', 7 | ] 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/res2net/cascade_rcnn_r2_101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_20e_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://res2net101_v1d_26w_4s', 4 | backbone=dict(type='Res2Net', depth=101, scales=4, base_width=26)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/resnest/mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict(stem_channels=128, depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmcv_custom/runner/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Open-MMLab. All rights reserved. 2 | from .checkpoint import save_checkpoint 3 | from .epoch_based_runner import EpochBasedRunnerAmp 4 | 5 | 6 | __all__ = [ 7 | 'EpochBasedRunnerAmp', 'save_checkpoint' 8 | ] 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False)) 5 | -------------------------------------------------------------------------------- /downstreams/segmentation/.github/ISSUE_TEMPLATE/config.yml: -------------------------------------------------------------------------------- 1 | blank_issues_enabled: false 2 | 3 | contact_links: 4 | - name: MMSegmentation Documentation 5 | url: https://mmsegmentation.readthedocs.io 6 | about: Check the docs and FAQ to see if you question is already anwsered. 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', 3 | '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', 3 | '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=150)) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/htc/htc_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './htc_r50_fpn_1x_coco.py' 2 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 3 | # learning policy 4 | lr_config = dict(step=[16, 19]) 5 | runner = dict(type='EpochBasedRunner', max_epochs=20) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/res2net/cascade_mask_rcnn_r2_101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_20e_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://res2net101_v1d_26w_4s', 4 | backbone=dict(type='Res2Net', depth=101, scales=4, base_width=26)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/anchor/builder.py: -------------------------------------------------------------------------------- 1 | from mmcv.utils import Registry, build_from_cfg 2 | 3 | ANCHOR_GENERATORS = Registry('Anchor generator') 4 | 5 | 6 | def build_anchor_generator(cfg, default_args=None): 7 | return build_from_cfg(cfg, ANCHOR_GENERATORS, default_args) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=150)) 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/sem_fpn/fpn_r50_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fpn_r50.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=150)) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_giou_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | roi_head=dict( 4 | bbox_head=dict( 5 | reg_decoded_bbox=True, 6 | loss_bbox=dict(type='GIoULoss', loss_weight=10.0)))) 7 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_iou_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | roi_head=dict( 4 | bbox_head=dict( 5 | reg_decoded_bbox=True, 6 | loss_bbox=dict(type='IoULoss', loss_weight=10.0)))) 7 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | norm_cfg=dict(type='SyncBN', requires_grad=True), norm_eval=False)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/pafpn/faster_rcnn_r50_pafpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' 2 | 3 | model = dict( 4 | neck=dict( 5 | type='PAFPN', 6 | in_channels=[256, 512, 1024, 2048], 7 | out_channels=256, 8 | num_outs=5)) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=21)) 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=21)) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/resnest/cascade_mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict(stem_channels=128, depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/resnest/cascade_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict(stem_channels=128, depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/configs/resnest/faster_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict(stem_channels=128, depth=101)) 5 | -------------------------------------------------------------------------------- /downstreams/detection/docker/serve/entrypoint.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | set -e 3 | 4 | if [[ "$1" = "serve" ]]; then 5 | shift 1 6 | torchserve --start --ts-config /home/model-server/config.properties 7 | else 8 | eval "$@" 9 | fi 10 | 11 | # prevent docker exit 12 | tail -f /dev/null 13 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/bbox/match_costs/__init__.py: -------------------------------------------------------------------------------- 1 | from .builder import build_match_cost 2 | from .match_cost import BBoxL1Cost, ClassificationCost, FocalLossCost, IoUCost 3 | 4 | __all__ = [ 5 | 'build_match_cost', 'ClassificationCost', 'BBoxL1Cost', 'IoUCost', 6 | 'FocalLossCost' 7 | ] 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_bounded_iou_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | roi_head=dict( 4 | bbox_head=dict( 5 | reg_decoded_bbox=True, 6 | loss_bbox=dict(type='BoundedIoULoss', loss_weight=10.0)))) 7 | -------------------------------------------------------------------------------- /downstreams/detection/docs/tutorials/index.rst: -------------------------------------------------------------------------------- 1 | .. toctree:: 2 | :maxdepth: 2 3 | 4 | config.md 5 | customize_dataset.md 6 | data_pipeline.md 7 | customize_models.md 8 | customize_runtime.md 9 | customize_losses.md 10 | finetune.md 11 | pytorch2onnx.md 12 | onnx2tensorrt.md 13 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .dist_utils import DistOptimizerHook, allreduce_grads, reduce_mean 2 | from .misc import mask2ndarray, multi_apply, unmap 3 | 4 | __all__ = [ 5 | 'allreduce_grads', 'DistOptimizerHook', 'reduce_mean', 'multi_apply', 6 | 'unmap', 'mask2ndarray' 7 | ] 8 | -------------------------------------------------------------------------------- /downstreams/detection/requirements/tests.txt: -------------------------------------------------------------------------------- 1 | asynctest 2 | codecov 3 | flake8 4 | interrogate 5 | isort==4.3.21 6 | # Note: used for kwarray.group_items, this may be ported to mmcv in the future. 7 | kwarray 8 | onnx==1.7.0 9 | onnxruntime==1.5.1 10 | pytest 11 | ubelt 12 | xdoctest>=0.10.0 13 | yapf 14 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCNv2', deform_groups=4, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_1x_coco.py' 2 | norm_cfg = dict(type='GN', num_groups=32, requires_grad=True) 3 | model = dict(neck=dict(norm_cfg=norm_cfg), bbox_head=dict(norm_cfg=norm_cfg)) 4 | optimizer = dict(lr=0.01) 5 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/bbox/match_costs/builder.py: -------------------------------------------------------------------------------- 1 | from mmcv.utils import Registry, build_from_cfg 2 | 3 | MATCH_COST = Registry('Match Cost') 4 | 5 | 6 | def build_match_cost(cfg, default_args=None): 7 | """Builder of IoU calculator.""" 8 | return build_from_cfg(cfg, MATCH_COST, default_args) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/point_rend/pointrend_r50_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pointrend_r50.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | lr_config = dict(warmup='linear', warmup_iters=200) 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/tools/dist_train.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | CONFIG=$1 4 | GPUS=$2 5 | PORT=${PORT:-29500} 6 | 7 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \ 8 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \ 9 | $(dirname "$0")/train.py $CONFIG --launcher pytorch ${@:3} -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_mask_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/configs/pisa/pisa_ssd300_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../ssd/ssd300_coco.py' 2 | 3 | model = dict( 4 | bbox_head=dict(type='PISASSDHead'), 5 | train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2))) 6 | 7 | optimizer_config = dict( 8 | _delete_=True, grad_clip=dict(max_norm=35, norm_type=2)) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/pisa/pisa_ssd512_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../ssd/ssd512_coco.py' 2 | 3 | model = dict( 4 | bbox_head=dict(type='PISASSDHead'), 5 | train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2))) 6 | 7 | optimizer_config = dict( 8 | _delete_=True, grad_clip=dict(max_norm=35, norm_type=2)) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/dcn/cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../cascade_rcnn/cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True))) 6 | -------------------------------------------------------------------------------- /downstreams/detection/tools/dist_train.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | CONFIG=$1 4 | GPUS=$2 5 | PORT=${PORT:-29500} 6 | 7 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \ 8 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \ 9 | $(dirname "$0")/train.py $CONFIG --launcher pytorch ${@:3} 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/seg/builder.py: -------------------------------------------------------------------------------- 1 | from mmcv.utils import Registry, build_from_cfg 2 | 3 | PIXEL_SAMPLERS = Registry('pixel sampler') 4 | 5 | 6 | def build_pixel_sampler(cfg, **default_args): 7 | """Build pixel sampler for segmentation map.""" 8 | return build_from_cfg(cfg, PIXEL_SAMPLERS, default_args) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/detectors/htc_r50_sac_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../htc/htc_r50_fpn_1x_coco.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | type='DetectoRS_ResNet', 6 | conv_cfg=dict(type='ConvAWS'), 7 | sac=dict(type='SAC', use_deform=True), 8 | stage_with_sac=(False, True, True, True))) 9 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/bbox/iou_calculators/builder.py: -------------------------------------------------------------------------------- 1 | from mmcv.utils import Registry, build_from_cfg 2 | 3 | IOU_CALCULATORS = Registry('IoU calculator') 4 | 5 | 6 | def build_iou_calculator(cfg, default_args=None): 7 | """Builder of IoU calculator.""" 8 | return build_from_cfg(cfg, IOU_CALCULATORS, default_args) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 6 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/tools/dist_test.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | CONFIG=$1 4 | CHECKPOINT=$2 5 | GPUS=$3 6 | PORT=${PORT:-29500} 7 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \ 8 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \ 9 | $(dirname "$0")/test.py $CONFIG $CHECKPOINT --launcher pytorch ${@:4} -------------------------------------------------------------------------------- /downstreams/detection/configs/vfnet/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_mstrain_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, True, True, True)), 6 | bbox_head=dict(dcn_on_last_conv=True)) 7 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/export/__init__.py: -------------------------------------------------------------------------------- 1 | from .pytorch2onnx import (build_model_from_cfg, 2 | generate_inputs_and_wrap_model, 3 | preprocess_example_input) 4 | 5 | __all__ = [ 6 | 'build_model_from_cfg', 'generate_inputs_and_wrap_model', 7 | 'preprocess_example_input' 8 | ] 9 | -------------------------------------------------------------------------------- /downstreams/detection/pytest.ini: -------------------------------------------------------------------------------- 1 | [pytest] 2 | addopts = --xdoctest --xdoctest-style=auto 3 | norecursedirs = .git ignore build __pycache__ data docker docs .eggs 4 | 5 | filterwarnings= default 6 | ignore:.*No cfgstr given in Cacher constructor or call.*:Warning 7 | ignore:.*Define the __nice__ method for.*:Warning 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/detection/configs/retinanet/retinanet_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/retinanet_r50_fpn.py', 3 | '../_base_/datasets/coco_detection.py', 4 | '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py' 5 | ] 6 | # optimizer 7 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/hrf.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/drive.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/pytest.ini: -------------------------------------------------------------------------------- 1 | [pytest] 2 | addopts = --xdoctest --xdoctest-style=auto 3 | norecursedirs = .git ignore build __pycache__ data docker docs .eggs 4 | 5 | filterwarnings= default 6 | ignore:.*No cfgstr given in Cacher constructor or call.*:Warning 7 | ignore:.*Define the __nice__ method for.*:Warning 8 | -------------------------------------------------------------------------------- /configs/i_dynamic_dwnet_base_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: iddwnet 3 | NAME: iddwnet_base_patch4_window7_224 4 | DROP_PATH_RATE: 0.5 5 | DWNET: 6 | EMBED_DIM: 128 7 | DEPTHS: [ 2, 2, 18, 2 ] 8 | WINDOW_SIZE: 7 9 | DYNAMIC: True 10 | INHOMO: True 11 | INHOMO_HEADS: [ 4, 8, 16, 32 ] 12 | AMP_OPT_LEVEL: "O0" 13 | -------------------------------------------------------------------------------- /configs/i_dynamic_dwnet_tiny_patch4_window7_224.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: iddwnet 3 | NAME: iddwnet_tiny_patch4_window7_224 4 | DROP_PATH_RATE: 0.2 5 | DWNET: 6 | EMBED_DIM: 96 7 | DEPTHS: [ 2, 2, 6, 2 ] 8 | WINDOW_SIZE: 7 9 | DYNAMIC: True 10 | INHOMO: True 11 | INHOMO_HEADS: [ 3, 6, 12, 24 ] 12 | AMP_OPT_LEVEL: "O0" 13 | -------------------------------------------------------------------------------- /downstreams/detection/configs/pisa/pisa_retinanet_r50_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py' 2 | 3 | model = dict( 4 | bbox_head=dict( 5 | type='PISARetinaHead', 6 | loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)), 7 | train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2))) 8 | -------------------------------------------------------------------------------- /downstreams/detection/tools/dist_test.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | CONFIG=$1 4 | CHECKPOINT=$2 5 | GPUS=$3 6 | PORT=${PORT:-29500} 7 | 8 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \ 9 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \ 10 | $(dirname "$0")/test.py $CONFIG $CHECKPOINT --launcher pytorch ${@:4} 11 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/stare.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/drive.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/evaluation/__init__.py: -------------------------------------------------------------------------------- 1 | from .class_names import get_classes, get_palette 2 | from .eval_hooks import DistEvalHook, EvalHook 3 | from .metrics import eval_metrics, mean_dice, mean_iou 4 | 5 | __all__ = [ 6 | 'EvalHook', 'DistEvalHook', 'mean_dice', 'mean_iou', 'eval_metrics', 7 | 'get_classes', 'get_palette' 8 | ] 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r101_fpn_r4_gcb_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict(plugins=[ 4 | dict( 5 | cfg=dict(type='ContextBlock', ratio=1. / 4), 6 | stages=(False, True, True, True), 7 | position='after_conv3') 8 | ])) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r50_fpn_r16_gcb_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict(plugins=[ 4 | dict( 5 | cfg=dict(type='ContextBlock', ratio=1. / 16), 6 | stages=(False, True, True, True), 7 | position='after_conv3') 8 | ])) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r50_fpn_r4_gcb_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict(plugins=[ 4 | dict( 5 | cfg=dict(type='ContextBlock', ratio=1. / 4), 6 | stages=(False, True, True, True), 7 | position='after_conv3') 8 | ])) 9 | -------------------------------------------------------------------------------- /downstreams/detection/configs/regnet/mask_rcnn_regnetx-3.2GF_fpn_mdconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://regnetx_3.2gf', 4 | backbone=dict( 5 | dcn=dict(type='DCNv2', deform_groups=1, fallback_on_stride=False), 6 | stage_with_dcn=(False, True, True, True))) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/drive.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/chase_db1.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/stare.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/hrf.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gcnet/mask_rcnn_r101_fpn_r16_gcb_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict(plugins=[ 4 | dict( 5 | cfg=dict(type='ContextBlock', ratio=1. / 16), 6 | stages=(False, True, True, True), 7 | position='after_conv3') 8 | ])) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150)) 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/stare.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/hrf.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 6 | evaluation = dict(metric='mDice') 7 | -------------------------------------------------------------------------------- /downstreams/detection/configs/pisa/pisa_retinanet_x101_32x4d_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../retinanet/retinanet_x101_32x4d_fpn_1x_coco.py' 2 | 3 | model = dict( 4 | bbox_head=dict( 5 | type='PISARetinaHead', 6 | loss_bbox=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0)), 7 | train_cfg=dict(isr=dict(k=2., bias=0.), carl=dict(k=1., bias=0.2))) 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/res2net/htc_r2_101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../htc/htc_r50_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://res2net101_v1d_26w_4s', 4 | backbone=dict(type='Res2Net', depth=101, scales=4, base_width=26)) 5 | # learning policy 6 | lr_config = dict(step=[16, 19]) 7 | runner = dict(type='EpochBasedRunner', max_epochs=20) 8 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/__init__.py: -------------------------------------------------------------------------------- 1 | from .anchor import * # noqa: F401, F403 2 | from .bbox import * # noqa: F401, F403 3 | from .evaluation import * # noqa: F401, F403 4 | from .export import * # noqa: F401, F403 5 | from .mask import * # noqa: F401, F403 6 | from .post_processing import * # noqa: F401, F403 7 | from .utils import * # noqa: F401, F403 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/_base_/datasets/pascal_voc12_aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './pascal_voc12.py' 2 | # dataset settings 3 | data = dict( 4 | train=dict( 5 | ann_dir=['SegmentationClass', 'SegmentationClassAug'], 6 | split=[ 7 | 'ImageSets/Segmentation/train.txt', 8 | 'ImageSets/Segmentation/aug.txt' 9 | ])) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/nonlocal_net/nonlocal_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/nonlocal_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(mask_size=(66, 66), num_classes=150), 7 | auxiliary_head=dict(num_classes=150)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/fcn_s101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = '../fcn/fcn_r101-d8_512x512_160k_ade20k.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/psanet/psanet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(mask_size=(66, 66), num_classes=150), 7 | auxiliary_head=dict(num_classes=150)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', 3 | '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 7 | evaluation = dict(metric='mDice') 8 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/mask/__init__.py: -------------------------------------------------------------------------------- 1 | from .mask_target import mask_target 2 | from .structures import BaseInstanceMasks, BitmapMasks, PolygonMasks 3 | from .utils import encode_mask_results, split_combined_polys 4 | 5 | __all__ = [ 6 | 'split_combined_polys', 'mask_target', 'BaseInstanceMasks', 'BitmapMasks', 7 | 'PolygonMasks', 'encode_mask_results' 8 | ] 9 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/models/detectors/scnet.py: -------------------------------------------------------------------------------- 1 | from ..builder import DETECTORS 2 | from .cascade_rcnn import CascadeRCNN 3 | 4 | 5 | @DETECTORS.register_module() 6 | class SCNet(CascadeRCNN): 7 | """Implementation of `SCNet `_""" 8 | 9 | def __init__(self, **kwargs): 10 | super(SCNet, self).__init__(**kwargs) 11 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r18-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/fcn_s101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/pspnet_s101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = '../pspnet/pspnet_r101-d8_512x512_160k_ade20k.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', 3 | '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 7 | evaluation = dict(metric='mDice') 8 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fast_rcnn/README.md: -------------------------------------------------------------------------------- 1 | # Fast R-CNN 2 | 3 | ## Introduction 4 | 5 | [ALGORITHM] 6 | 7 | ```latex 8 | @inproceedings{girshick2015fast, 9 | title={Fast r-cnn}, 10 | author={Girshick, Ross}, 11 | booktitle={Proceedings of the IEEE international conference on computer vision}, 12 | year={2015} 13 | } 14 | ``` 15 | 16 | ## Results and models 17 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_20k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', 3 | '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21)) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r18-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/pspnet_s101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/post_processing/__init__.py: -------------------------------------------------------------------------------- 1 | from .bbox_nms import fast_nms, multiclass_nms 2 | from .merge_augs import (merge_aug_bboxes, merge_aug_masks, 3 | merge_aug_proposals, merge_aug_scores) 4 | 5 | __all__ = [ 6 | 'multiclass_nms', 'merge_aug_proposals', 'merge_aug_bboxes', 7 | 'merge_aug_scores', 'merge_aug_masks', 'fast_nms' 8 | ] 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r18-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/deeplabv3_s101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/encnet/encnet_r50s-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | backbone=dict(stem_channels=128), 7 | decode_head=dict(num_classes=150), 8 | auxiliary_head=dict(num_classes=150)) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r18b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r18b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/deeplabv3plus_s101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/detection/configs/reppoints/reppoints_moment_r101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict( 5 | depth=101, 6 | dcn=dict(type='DCN', deform_groups=1, fallback_on_stride=False), 7 | stage_with_dcn=(False, True, True, True))) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 6 | optimizer = dict(lr=0.02) 7 | lr_config = dict(min_lr=2e-4) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ocrnet/ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 6 | optimizer = dict(lr=0.02) 7 | lr_config = dict(min_lr=2e-4) 8 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r18b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/pspnet/pspnet_r18b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r18b-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/datasets/deepfashion.py: -------------------------------------------------------------------------------- 1 | from .builder import DATASETS 2 | from .coco import CocoDataset 3 | 4 | 5 | @DATASETS.register_module() 6 | class DeepFashionDataset(CocoDataset): 7 | 8 | CLASSES = ('top', 'skirt', 'leggings', 'dress', 'outer', 'pants', 'bag', 9 | 'neckwear', 'headwear', 'eyeglass', 'belt', 'footwear', 'hair', 10 | 'skin', 'face') 11 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/deeplabv3/deeplabv3_r18b-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /downstreams/detection/.github/ISSUE_TEMPLATE/config.yml: -------------------------------------------------------------------------------- 1 | blank_issues_enabled: false 2 | 3 | contact_links: 4 | - name: Common Issues 5 | url: https://mmdetection.readthedocs.io/en/latest/faq.html 6 | about: Check if your issue already has solutions 7 | - name: MMDetection Documentation 8 | url: https://mmdetection.readthedocs.io/en/latest/ 9 | about: Check if your question is answered in docs 10 | -------------------------------------------------------------------------------- /downstreams/detection/configs/grid_rcnn/grid_rcnn_r50_fpn_gn-head_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = ['grid_rcnn_r50_fpn_gn-head_2x_coco.py'] 2 | # learning policy 3 | lr_config = dict( 4 | policy='step', 5 | warmup='linear', 6 | warmup_iters=500, 7 | warmup_ratio=0.001, 8 | step=[8, 11]) 9 | checkpoint_config = dict(interval=1) 10 | # runtime settings 11 | runner = dict(type='EpochBasedRunner', max_epochs=12) 12 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/core/seg/sampler/base_pixel_sampler.py: -------------------------------------------------------------------------------- 1 | from abc import ABCMeta, abstractmethod 2 | 3 | 4 | class BasePixelSampler(metaclass=ABCMeta): 5 | """Base class of pixel sampler.""" 6 | 7 | def __init__(self, **kwargs): 8 | pass 9 | 10 | @abstractmethod 11 | def sample(self, seg_logit, seg_label): 12 | """Placeholder for sample function.""" 13 | pass 14 | -------------------------------------------------------------------------------- /downstreams/detection/configs/_base_/schedules/schedule_1x.py: -------------------------------------------------------------------------------- 1 | # optimizer 2 | optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001) 3 | optimizer_config = dict(grad_clip=None) 4 | # learning policy 5 | lr_config = dict( 6 | policy='step', 7 | warmup='linear', 8 | warmup_iters=500, 9 | warmup_ratio=0.001, 10 | step=[8, 11]) 11 | runner = dict(type='EpochBasedRunner', max_epochs=12) 12 | -------------------------------------------------------------------------------- /downstreams/detection/configs/_base_/schedules/schedule_20e.py: -------------------------------------------------------------------------------- 1 | # optimizer 2 | optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001) 3 | optimizer_config = dict(grad_clip=None) 4 | # learning policy 5 | lr_config = dict( 6 | policy='step', 7 | warmup='linear', 8 | warmup_iters=500, 9 | warmup_ratio=0.001, 10 | step=[16, 19]) 11 | runner = dict(type='EpochBasedRunner', max_epochs=20) 12 | -------------------------------------------------------------------------------- /downstreams/detection/configs/_base_/schedules/schedule_2x.py: -------------------------------------------------------------------------------- 1 | # optimizer 2 | optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001) 3 | optimizer_config = dict(grad_clip=None) 4 | # learning policy 5 | lr_config = dict( 6 | policy='step', 7 | warmup='linear', 8 | warmup_iters=500, 9 | warmup_ratio=0.001, 10 | step=[16, 22]) 11 | runner = dict(type='EpochBasedRunner', max_epochs=24) 12 | -------------------------------------------------------------------------------- /downstreams/detection/configs/yolact/yolact_r50_8x8_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'yolact_r50_1x8_coco.py' 2 | 3 | optimizer = dict(type='SGD', lr=8e-3, momentum=0.9, weight_decay=5e-4) 4 | optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2)) 5 | # learning policy 6 | lr_config = dict( 7 | policy='step', 8 | warmup='linear', 9 | warmup_iters=1000, 10 | warmup_ratio=0.1, 11 | step=[20, 42, 49, 52]) 12 | -------------------------------------------------------------------------------- /downstreams/detection/mmdet/core/bbox/assigners/base_assigner.py: -------------------------------------------------------------------------------- 1 | from abc import ABCMeta, abstractmethod 2 | 3 | 4 | class BaseAssigner(metaclass=ABCMeta): 5 | """Base assigner that assigns boxes to ground truth boxes.""" 6 | 7 | @abstractmethod 8 | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None): 9 | """Assign boxes to either a ground truth boxes or a negative boxes.""" 10 | -------------------------------------------------------------------------------- /downstreams/detection/configs/fpg/faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'faster_rcnn_r50_fpg_crop640_50e_coco.py' 2 | 3 | norm_cfg = dict(type='BN', requires_grad=True) 4 | model = dict( 5 | neck=dict(out_channels=128, inter_channels=128), 6 | rpn_head=dict(in_channels=128), 7 | roi_head=dict( 8 | bbox_roi_extractor=dict(out_channels=128), 9 | bbox_head=dict(in_channels=128))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/lraspp_m-v3-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | 6 | # Re-config the data sampler. 7 | data = dict(samples_per_gpu=4, workers_per_gpu=4) 8 | 9 | runner = dict(type='IterBasedRunner', max_iters=320000) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/_base_/default_runtime.py: -------------------------------------------------------------------------------- 1 | # yapf:disable 2 | log_config = dict( 3 | interval=50, 4 | hooks=[ 5 | dict(type='TextLoggerHook', by_epoch=False), 6 | # dict(type='TensorboardLoggerHook') 7 | ]) 8 | # yapf:enable 9 | dist_params = dict(backend='nccl') 10 | log_level = 'INFO' 11 | load_from = None 12 | resume_from = None 13 | workflow = [('train', 1)] 14 | cudnn_benchmark = True 15 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ann/ann_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ann_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fcn/fcn_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/detection/configs/gfl/gfl_r101_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './gfl_r50_fpn_mstrain_2x_coco.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict( 5 | type='ResNet', 6 | depth=101, 7 | num_stages=4, 8 | out_indices=(0, 1, 2, 3), 9 | frozen_stages=1, 10 | norm_cfg=dict(type='BN', requires_grad=True), 11 | norm_eval=True, 12 | style='pytorch')) 13 | -------------------------------------------------------------------------------- /downstreams/detection/configs/grid_rcnn/grid_rcnn_x101_64x4d_fpn_gn-head_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnext101_64x4d', 4 | backbone=dict( 5 | type='ResNeXt', 6 | depth=101, 7 | groups=64, 8 | base_width=4, 9 | num_stages=4, 10 | out_indices=(0, 1, 2, 3), 11 | frozen_stages=1, 12 | style='pytorch')) 13 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/ccnet/ccnet_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/ccnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/danet/danet_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/danet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dmnet/dmnet_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dmnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/dnlnet/dnl_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/dnl_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | 6 | # Re-config the data sampler. 7 | data = dict(samples_per_gpu=2, workers_per_gpu=4) 8 | 9 | # Re-config the optimizer. 10 | optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5) 11 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/gcnet/gcnet_r50-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/gcnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_480x480_40k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=60), 7 | test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) 8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/hrnet/fcn_hr18_480x480_80k_pascal_context.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=60), 7 | test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320))) 8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001) 9 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/upernet/upernet_r50_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/upernet_r50.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | -------------------------------------------------------------------------------- /downstreams/segmentation/mmseg/models/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .inverted_residual import InvertedResidual, InvertedResidualV3 2 | from .make_divisible import make_divisible 3 | from .res_layer import ResLayer 4 | from .self_attention_block import SelfAttentionBlock 5 | from .up_conv_block import UpConvBlock 6 | 7 | __all__ = [ 8 | 'ResLayer', 'SelfAttentionBlock', 'make_divisible', 'InvertedResidual', 9 | 'UpConvBlock', 'InvertedResidualV3' 10 | ] 11 | -------------------------------------------------------------------------------- /downstreams/detection/configs/free_anchor/retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_free_anchor_r50_fpn_1x_coco.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnext101_32x4d', 4 | backbone=dict( 5 | type='ResNeXt', 6 | depth=101, 7 | groups=32, 8 | base_width=4, 9 | num_stages=4, 10 | out_indices=(0, 1, 2, 3), 11 | frozen_stages=1, 12 | style='pytorch')) 13 | -------------------------------------------------------------------------------- /downstreams/segmentation/configs/apcnet/apcnet_r50-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/apcnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | model = dict( 7 | decode_head=dict(align_corners=True), 8 | auxiliary_head=dict(align_corners=True), 9 | test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513))) 10 | --------------------------------------------------------------------------------