├── Images └── lvt.png ├── License.md ├── README.md ├── classification ├── .gitignore ├── Images │ └── lvt.png ├── LICENSE ├── README.md ├── README.volo.md ├── configs │ └── lvt_imagenet.py ├── distributed_train.sh ├── figures │ ├── compare.png │ └── outlook-attention-gif.gif ├── loss │ ├── __init__.py │ └── cross_entropy.py ├── main.py ├── models │ ├── __init__.py │ ├── lvt.py │ └── lvt_cls.py ├── utils │ ├── __init__.py │ └── utils.py └── validate.py ├── detection ├── .dev_scripts │ ├── batch_test_list.py │ ├── batch_train_list.txt │ ├── benchmark_filter.py │ ├── benchmark_inference_fps.py │ ├── benchmark_test_image.py │ ├── convert_test_benchmark_script.py │ ├── convert_train_benchmark_script.py │ ├── gather_models.py │ ├── gather_test_benchmark_metric.py │ ├── gather_train_benchmark_metric.py │ ├── linter.sh │ ├── test_benchmark.sh │ ├── test_init_backbone.py │ └── train_benchmark.sh ├── .github │ ├── CODE_OF_CONDUCT.md │ ├── CONTRIBUTING.md │ ├── ISSUE_TEMPLATE │ │ ├── config.yml │ │ ├── error-report.md │ │ ├── feature_request.md │ │ ├── general_questions.md │ │ └── reimplementation_questions.md │ ├── pull_request_template.md │ └── workflows │ │ ├── build.yml │ │ ├── build_pat.yml │ │ └── deploy.yml ├── .gitignore ├── .pre-commit-config.yaml ├── .readthedocs.yml ├── CITATION.cff ├── LICENSE ├── MANIFEST.in ├── README.md ├── README.mmdet.md ├── README_zh-CN.md ├── configs │ ├── _base_ │ │ ├── datasets │ │ │ ├── cityscapes_detection.py │ │ │ ├── cityscapes_instance.py │ │ │ ├── coco_detection.py │ │ │ ├── coco_detection_512.py │ │ │ ├── coco_instance.py │ │ │ ├── coco_instance_semantic.py │ │ │ ├── coco_panoptic.py │ │ │ ├── coco_panoptic_1024.py │ │ │ ├── coco_panoptic_512.py │ │ │ ├── coco_panoptic_640.py │ │ │ ├── deepfashion.py │ │ │ ├── lvis_v0.5_instance.py │ │ │ ├── lvis_v1_instance.py │ │ │ ├── voc0712.py │ │ │ └── wider_face.py │ │ ├── default_runtime.py │ │ ├── models │ │ │ ├── cascade_mask_rcnn_r50_fpn.py │ │ │ ├── cascade_rcnn_r50_fpn.py │ │ │ ├── fast_rcnn_r50_fpn.py │ │ │ ├── faster_rcnn_r50_caffe_c4.py │ │ │ ├── faster_rcnn_r50_caffe_dc5.py │ │ │ ├── faster_rcnn_r50_fpn.py │ │ │ ├── mask_rcnn_r50_caffe_c4.py │ │ │ ├── mask_rcnn_r50_fpn.py │ │ │ ├── retinanet_r50_fpn.py │ │ │ ├── rpn_r50_caffe_c4.py │ │ │ ├── rpn_r50_fpn.py │ │ │ └── ssd300.py │ │ └── schedules │ │ │ ├── schedule_1x.py │ │ │ ├── schedule_20e.py │ │ │ └── schedule_2x.py │ ├── albu_example │ │ ├── README.md │ │ └── mask_rcnn_r50_fpn_albu_1x_coco.py │ ├── atss │ │ ├── README.md │ │ ├── atss_r101_fpn_1x_coco.py │ │ ├── atss_r50_fpn_1x_coco.py │ │ └── metafile.yml │ ├── autoassign │ │ ├── README.md │ │ ├── autoassign_r50_fpn_8x2_1x_coco.py │ │ └── metafile.yml │ ├── carafe │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_carafe_1x_coco.py │ │ └── mask_rcnn_r50_fpn_carafe_1x_coco.py │ ├── cascade_rcnn │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_r101_caffe_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_r101_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_r101_fpn_20e_coco.py │ │ ├── cascade_mask_rcnn_r101_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_r50_caffe_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_r50_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_r50_fpn_20e_coco.py │ │ ├── cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_20e_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x8d_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_x101_64x4d_fpn_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_64x4d_fpn_20e_coco.py │ │ ├── cascade_mask_rcnn_x101_64x4d_fpn_mstrain_3x_coco.py │ │ ├── cascade_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── cascade_rcnn_r101_fpn_1x_coco.py │ │ ├── cascade_rcnn_r101_fpn_20e_coco.py │ │ ├── cascade_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── cascade_rcnn_r50_fpn_1x_coco.py │ │ ├── cascade_rcnn_r50_fpn_20e_coco.py │ │ ├── cascade_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── cascade_rcnn_x101_32x4d_fpn_20e_coco.py │ │ ├── cascade_rcnn_x101_64x4d_fpn_1x_coco.py │ │ ├── cascade_rcnn_x101_64x4d_fpn_20e_coco.py │ │ └── metafile.yml │ ├── cascade_rpn │ │ ├── README.md │ │ ├── crpn_fast_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── crpn_faster_rcnn_r50_caffe_fpn_1x_coco.py │ │ └── crpn_r50_caffe_fpn_1x_coco.py │ ├── centernet │ │ ├── README.md │ │ ├── centernet_resnet18_140e_coco.py │ │ ├── centernet_resnet18_dcnv2_140e_coco.py │ │ └── metafile.yml │ ├── centripetalnet │ │ ├── README.md │ │ ├── centripetalnet_hourglass104_mstest_16x6_210e_coco.py │ │ └── metafile.yml │ ├── cityscapes │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_1x_cityscapes.py │ │ └── mask_rcnn_r50_fpn_1x_cityscapes.py │ ├── common │ │ ├── lsj_100e_coco_instance.py │ │ ├── mstrain-poly_3x_coco_instance.py │ │ ├── mstrain_3x_coco.py │ │ ├── mstrain_3x_coco_instance.py │ │ └── mstrain_3x_coco_segrescale.py │ ├── cornernet │ │ ├── README.md │ │ ├── cornernet_hourglass104_mstest_10x5_210e_coco.py │ │ ├── cornernet_hourglass104_mstest_32x3_210e_coco.py │ │ ├── cornernet_hourglass104_mstest_8x6_210e_coco.py │ │ └── metafile.yml │ ├── dcn │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py │ │ ├── cascade_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ ├── cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py │ │ ├── faster_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_dpool_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_mdpool_1x_coco.py │ │ ├── faster_rcnn_x101_32x4d_fpn_dconv_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_dconv_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py │ │ └── metafile.yml │ ├── deepfashion │ │ ├── README.md │ │ └── mask_rcnn_r50_fpn_15e_deepfashion.py │ ├── deformable_detr │ │ ├── README.md │ │ ├── deformable_detr_r50_16x2_50e_coco.py │ │ ├── deformable_detr_refine_r50_16x2_50e_coco.py │ │ ├── deformable_detr_twostage_refine_r50_16x2_50e_coco.py │ │ └── metafile.yml │ ├── detectors │ │ ├── README.md │ │ ├── cascade_rcnn_r50_rfp_1x_coco.py │ │ ├── cascade_rcnn_r50_sac_1x_coco.py │ │ ├── detectors_cascade_rcnn_r50_1x_coco.py │ │ ├── detectors_htc_r101_20e_coco.py │ │ ├── detectors_htc_r50_1x_coco.py │ │ ├── htc_r50_rfp_1x_coco.py │ │ ├── htc_r50_sac_1x_coco.py │ │ └── metafile.yml │ ├── detr │ │ ├── README.md │ │ ├── detr_r50_8x2_150e_coco.py │ │ └── metafile.yml │ ├── double_heads │ │ ├── README.md │ │ ├── dh_faster_rcnn_r50_fpn_1x_coco.py │ │ └── metafile.yml │ ├── dynamic_rcnn │ │ ├── README.md │ │ ├── dynamic_rcnn_r50_fpn_1x_coco.py │ │ └── metafile.yml │ ├── empirical_attention │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_attention_0010_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_attention_1111_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py │ │ └── metafile.yml │ ├── fast_rcnn │ │ ├── README.md │ │ ├── fast_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── fast_rcnn_r101_fpn_1x_coco.py │ │ ├── fast_rcnn_r101_fpn_2x_coco.py │ │ ├── fast_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── fast_rcnn_r50_fpn_1x_coco.py │ │ └── fast_rcnn_r50_fpn_2x_coco.py │ ├── faster_rcnn │ │ ├── README.md │ │ ├── faster_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── faster_rcnn_r101_caffe_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_r101_fpn_1x_coco.py │ │ ├── faster_rcnn_r101_fpn_2x_coco.py │ │ ├── faster_rcnn_r101_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_r50_caffe_c4_1x_coco.py │ │ ├── faster_rcnn_r50_caffe_dc5_1x_coco.py │ │ ├── faster_rcnn_r50_caffe_dc5_mstrain_1x_coco.py │ │ ├── faster_rcnn_r50_caffe_dc5_mstrain_3x_coco.py │ │ ├── faster_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person-bicycle-car.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco-person.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_1x_coco.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_2x_coco.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_r50_caffe_fpn_mstrain_90k_coco.py │ │ ├── faster_rcnn_r50_fpn_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_2x_coco.py │ │ ├── faster_rcnn_r50_fpn_bounded_iou_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_ciou_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_giou_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_iou_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_r50_fpn_ohem_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_soft_nms_1x_coco.py │ │ ├── faster_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── faster_rcnn_x101_32x4d_fpn_2x_coco.py │ │ ├── faster_rcnn_x101_32x4d_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_x101_32x8d_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_x101_64x4d_fpn_1x_coco.py │ │ ├── faster_rcnn_x101_64x4d_fpn_2x_coco.py │ │ ├── faster_rcnn_x101_64x4d_fpn_mstrain_3x_coco.py │ │ └── metafile.yml │ ├── fcos │ │ ├── README.md │ │ ├── fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_1x_coco.py │ │ ├── fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_dcn_1x_coco.py │ │ ├── fcos_center_r50_caffe_fpn_gn-head_1x_coco.py │ │ ├── fcos_r101_caffe_fpn_gn-head_1x_coco.py │ │ ├── fcos_r101_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py │ │ ├── fcos_r50_caffe_fpn_gn-head_1x_coco.py │ │ ├── fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py │ │ ├── fcos_r50_caffe_fpn_gn-head_mstrain_640-800_2x_coco.py │ │ ├── fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_2x_coco.py │ │ └── metafile.yml │ ├── foveabox │ │ ├── README.md │ │ ├── fovea_align_r101_fpn_gn-head_4x4_2x_coco.py │ │ ├── fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py │ │ ├── fovea_align_r50_fpn_gn-head_4x4_2x_coco.py │ │ ├── fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco.py │ │ ├── fovea_r101_fpn_4x4_1x_coco.py │ │ ├── fovea_r101_fpn_4x4_2x_coco.py │ │ ├── fovea_r50_fpn_4x4_1x_coco.py │ │ ├── fovea_r50_fpn_4x4_2x_coco.py │ │ └── metafile.yml │ ├── fp16 │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_fp16_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_fp16_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco.py │ │ ├── metafile.yml │ │ └── retinanet_r50_fpn_fp16_1x_coco.py │ ├── fpg │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpg-chn128_crop640_50e_coco.py │ │ ├── faster_rcnn_r50_fpg_crop640_50e_coco.py │ │ ├── faster_rcnn_r50_fpn_crop640_50e_coco.py │ │ ├── mask_rcnn_r50_fpg-chn128_crop640_50e_coco.py │ │ ├── mask_rcnn_r50_fpg_crop640_50e_coco.py │ │ ├── mask_rcnn_r50_fpn_crop640_50e_coco.py │ │ ├── metafile.yml │ │ ├── retinanet_r50_fpg-chn128_crop640_50e_coco.py │ │ └── retinanet_r50_fpg_crop640_50e_coco.py │ ├── free_anchor │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── retinanet_free_anchor_r101_fpn_1x_coco.py │ │ ├── retinanet_free_anchor_r50_fpn_1x_coco.py │ │ └── retinanet_free_anchor_x101_32x4d_fpn_1x_coco.py │ ├── fsaf │ │ ├── README.md │ │ ├── fsaf_r101_fpn_1x_coco.py │ │ ├── fsaf_r50_fpn_1x_coco.py │ │ ├── fsaf_x101_64x4d_fpn_1x_coco.py │ │ └── metafile.yml │ ├── gcnet │ │ ├── README.md │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r16_gcb_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_r4_gcb_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py │ │ ├── cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_r16_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_r4_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_syncbn-backbone_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_r16_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_r4_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-backbone_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_1x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r16_gcb_c3-c5_1x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_syncbn-backbone_r4_gcb_c3-c5_1x_coco.py │ │ └── metafile.yml │ ├── gfl │ │ ├── README.md │ │ ├── gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco.py │ │ ├── gfl_r101_fpn_mstrain_2x_coco.py │ │ ├── gfl_r50_fpn_1x_coco.py │ │ ├── gfl_r50_fpn_mstrain_2x_coco.py │ │ ├── gfl_x101_32x4d_fpn_dconv_c4-c5_mstrain_2x_coco.py │ │ ├── gfl_x101_32x4d_fpn_mstrain_2x_coco.py │ │ └── metafile.yml │ ├── ghm │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── retinanet_ghm_r101_fpn_1x_coco.py │ │ ├── retinanet_ghm_r50_fpn_1x_coco.py │ │ ├── retinanet_ghm_x101_32x4d_fpn_1x_coco.py │ │ └── retinanet_ghm_x101_64x4d_fpn_1x_coco.py │ ├── gn+ws │ │ ├── README.md │ │ ├── faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py │ │ ├── faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py │ │ ├── faster_rcnn_x101_32x4d_fpn_gn_ws-all_1x_coco.py │ │ ├── faster_rcnn_x50_32x4d_fpn_gn_ws-all_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco.py │ │ ├── mask_rcnn_r101_fpn_gn_ws-all_2x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco.py │ │ ├── mask_rcnn_r50_fpn_gn_ws-all_2x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco.py │ │ ├── mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco.py │ │ ├── mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco.py │ │ └── metafile.yml │ ├── gn │ │ ├── README.md │ │ ├── mask_rcnn_r101_fpn_gn-all_2x_coco.py │ │ ├── mask_rcnn_r101_fpn_gn-all_3x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn-all_2x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn-all_3x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn-all_contrib_2x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn-all_contrib_3x_coco.py │ │ └── metafile.yml │ ├── grid_rcnn │ │ ├── README.md │ │ ├── grid_rcnn_r101_fpn_gn-head_2x_coco.py │ │ ├── grid_rcnn_r50_fpn_gn-head_1x_coco.py │ │ ├── grid_rcnn_r50_fpn_gn-head_2x_coco.py │ │ ├── grid_rcnn_x101_32x4d_fpn_gn-head_2x_coco.py │ │ ├── grid_rcnn_x101_64x4d_fpn_gn-head_2x_coco.py │ │ └── metafile.yml │ ├── groie │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_groie_1x_coco.py │ │ ├── grid_rcnn_r50_fpn_gn-head_groie_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_syncbn-backbone_r4_gcb_c3-c5_groie_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_groie_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-backbone_r4_gcb_c3-c5_groie_1x_coco.py │ │ └── metafile.yml │ ├── guided_anchoring │ │ ├── README.md │ │ ├── ga_fast_r50_caffe_fpn_1x_coco.py │ │ ├── ga_faster_r101_caffe_fpn_1x_coco.py │ │ ├── ga_faster_r50_caffe_fpn_1x_coco.py │ │ ├── ga_faster_r50_fpn_1x_coco.py │ │ ├── ga_faster_x101_32x4d_fpn_1x_coco.py │ │ ├── ga_faster_x101_64x4d_fpn_1x_coco.py │ │ ├── ga_retinanet_r101_caffe_fpn_1x_coco.py │ │ ├── ga_retinanet_r101_caffe_fpn_mstrain_2x.py │ │ ├── ga_retinanet_r50_caffe_fpn_1x_coco.py │ │ ├── ga_retinanet_r50_fpn_1x_coco.py │ │ ├── ga_retinanet_x101_32x4d_fpn_1x_coco.py │ │ ├── ga_retinanet_x101_64x4d_fpn_1x_coco.py │ │ ├── ga_rpn_r101_caffe_fpn_1x_coco.py │ │ ├── ga_rpn_r50_caffe_fpn_1x_coco.py │ │ ├── ga_rpn_r50_fpn_1x_coco.py │ │ ├── ga_rpn_x101_32x4d_fpn_1x_coco.py │ │ ├── ga_rpn_x101_64x4d_fpn_1x_coco.py │ │ └── metafile.yml │ ├── hrnet │ │ ├── README.md │ │ ├── cascade_mask_rcnn_hrnetv2p_w18_20e_coco.py │ │ ├── cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py │ │ ├── cascade_mask_rcnn_hrnetv2p_w40_20e_coco.py │ │ ├── cascade_rcnn_hrnetv2p_w18_20e_coco.py │ │ ├── cascade_rcnn_hrnetv2p_w32_20e_coco.py │ │ ├── cascade_rcnn_hrnetv2p_w40_20e_coco.py │ │ ├── faster_rcnn_hrnetv2p_w18_1x_coco.py │ │ ├── faster_rcnn_hrnetv2p_w18_2x_coco.py │ │ ├── faster_rcnn_hrnetv2p_w32_1x_coco.py │ │ ├── faster_rcnn_hrnetv2p_w32_2x_coco.py │ │ ├── faster_rcnn_hrnetv2p_w40_1x_coco.py │ │ ├── faster_rcnn_hrnetv2p_w40_2x_coco.py │ │ ├── fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py │ │ ├── fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py │ │ ├── fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco.py │ │ ├── fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py │ │ ├── fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py │ │ ├── fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py │ │ ├── fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco.py │ │ ├── htc_hrnetv2p_w18_20e_coco.py │ │ ├── htc_hrnetv2p_w32_20e_coco.py │ │ ├── htc_hrnetv2p_w40_20e_coco.py │ │ ├── htc_hrnetv2p_w40_28e_coco.py │ │ ├── htc_x101_64x4d_fpn_16x1_28e_coco.py │ │ ├── mask_rcnn_hrnetv2p_w18_1x_coco.py │ │ ├── mask_rcnn_hrnetv2p_w18_2x_coco.py │ │ ├── mask_rcnn_hrnetv2p_w32_1x_coco.py │ │ ├── mask_rcnn_hrnetv2p_w32_2x_coco.py │ │ ├── mask_rcnn_hrnetv2p_w40_1x_coco.py │ │ ├── mask_rcnn_hrnetv2p_w40_2x_coco.py │ │ └── metafile.yml │ ├── htc │ │ ├── README.md │ │ ├── htc_r101_fpn_20e_coco.py │ │ ├── htc_r50_fpn_1x_coco.py │ │ ├── htc_r50_fpn_20e_coco.py │ │ ├── htc_without_semantic_r50_fpn_1x_coco.py │ │ ├── htc_x101_32x4d_fpn_16x1_20e_coco.py │ │ ├── htc_x101_64x4d_fpn_16x1_20e_coco.py │ │ ├── htc_x101_64x4d_fpn_dconv_c3-c5_mstrain_400_1400_16x1_20e_coco.py │ │ └── metafile.yml │ ├── instaboost │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r101_fpn_instaboost_4x_coco.py │ │ ├── cascade_mask_rcnn_r50_fpn_instaboost_4x_coco.py │ │ ├── cascade_mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py │ │ ├── mask_rcnn_r101_fpn_instaboost_4x_coco.py │ │ ├── mask_rcnn_r50_fpn_instaboost_4x_coco.py │ │ ├── mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco.py │ │ └── metafile.yml │ ├── ld │ │ ├── README.md │ │ ├── ld_r101_gflv1_r101dcn_fpn_coco_2x.py │ │ ├── ld_r18_gflv1_r101_fpn_coco_1x.py │ │ ├── ld_r34_gflv1_r101_fpn_coco_1x.py │ │ ├── ld_r50_gflv1_r101_fpn_coco_1x.py │ │ └── metafile.yml │ ├── legacy_1.x │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r50_fpn_1x_coco_v1.py │ │ ├── faster_rcnn_r50_fpn_1x_coco_v1.py │ │ ├── mask_rcnn_r50_fpn_1x_coco_v1.py │ │ ├── retinanet_r50_caffe_fpn_1x_coco_v1.py │ │ ├── retinanet_r50_fpn_1x_coco_v1.py │ │ └── ssd300_coco_v1.py │ ├── libra_rcnn │ │ ├── README.md │ │ ├── libra_fast_rcnn_r50_fpn_1x_coco.py │ │ ├── libra_faster_rcnn_r101_fpn_1x_coco.py │ │ ├── libra_faster_rcnn_r50_fpn_1x_coco.py │ │ ├── libra_faster_rcnn_x101_64x4d_fpn_1x_coco.py │ │ ├── libra_retinanet_r50_fpn_1x_coco.py │ │ └── metafile.yml │ ├── lvis │ │ ├── README.md │ │ ├── mask_rcnn_r101_fpn_sample1e-3_mstrain_1x_lvis_v1.py │ │ ├── mask_rcnn_r101_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py │ │ ├── mask_rcnn_r50_fpn_sample1e-3_mstrain_1x_lvis_v1.py │ │ ├── mask_rcnn_r50_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py │ │ ├── mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py │ │ ├── mask_rcnn_x101_32x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py │ │ ├── mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_1x_lvis_v1.py │ │ └── mask_rcnn_x101_64x4d_fpn_sample1e-3_mstrain_2x_lvis_v0.5.py │ ├── lvt │ │ ├── panoptic_fpn_lvt_fpn_1x_coco.py │ │ └── panoptic_fpn_lvt_fpn_3x_coco.py │ ├── mask_rcnn │ │ ├── README.md │ │ ├── mask_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_r101_fpn_1x_coco.py │ │ ├── mask_rcnn_r101_fpn_2x_coco.py │ │ ├── mask_rcnn_r101_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_r50_caffe_c4_1x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_mstrain_1x_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_poly_1x_coco_v1.py │ │ ├── mask_rcnn_r50_fpn_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_2x_coco.py │ │ ├── mask_rcnn_r50_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_r50_fpn_poly_1x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_2x_coco.py │ │ ├── mask_rcnn_x101_32x4d_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_x101_32x8d_fpn_1x_coco.py │ │ ├── mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco.py │ │ ├── mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_x101_64x4d_fpn_1x_coco.py │ │ ├── mask_rcnn_x101_64x4d_fpn_2x_coco.py │ │ ├── mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco.py │ │ └── metafile.yml │ ├── ms_rcnn │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── ms_rcnn_r101_caffe_fpn_1x_coco.py │ │ ├── ms_rcnn_r101_caffe_fpn_2x_coco.py │ │ ├── ms_rcnn_r50_caffe_fpn_1x_coco.py │ │ ├── ms_rcnn_r50_caffe_fpn_2x_coco.py │ │ ├── ms_rcnn_r50_fpn_1x_coco.py │ │ ├── ms_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── ms_rcnn_x101_64x4d_fpn_1x_coco.py │ │ └── ms_rcnn_x101_64x4d_fpn_2x_coco.py │ ├── nas_fcos │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── nas_fcos_fcoshead_r50_caffe_fpn_gn-head_4x4_1x_coco.py │ │ └── nas_fcos_nashead_r50_caffe_fpn_gn-head_4x4_1x_coco.py │ ├── nas_fpn │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── retinanet_r50_fpn_crop640_50e_coco.py │ │ └── retinanet_r50_nasfpn_crop640_50e_coco.py │ ├── paa │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── paa_r101_fpn_1x_coco.py │ │ ├── paa_r101_fpn_2x_coco.py │ │ ├── paa_r101_fpn_mstrain_3x_coco.py │ │ ├── paa_r50_fpn_1.5x_coco.py │ │ ├── paa_r50_fpn_1x_coco.py │ │ ├── paa_r50_fpn_2x_coco.py │ │ └── paa_r50_fpn_mstrain_3x_coco.py │ ├── pafpn │ │ ├── README.md │ │ ├── faster_rcnn_r50_pafpn_1x_coco.py │ │ └── metafile.yml │ ├── panoptic_fpn │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── panoptic_fpn_r101_fpn_1x_coco.py │ │ ├── panoptic_fpn_r101_fpn_mstrain_3x_coco.py │ │ ├── panoptic_fpn_r50_fpn_1x_coco.py │ │ └── panoptic_fpn_r50_fpn_mstrain_3x_coco.py │ ├── pascal_voc │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_1x_voc0712.py │ │ ├── faster_rcnn_r50_fpn_1x_voc0712_cocofmt.py │ │ ├── retinanet_r50_fpn_1x_voc0712.py │ │ ├── ssd300_voc0712.py │ │ └── ssd512_voc0712.py │ ├── pisa │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── pisa_faster_rcnn_r50_fpn_1x_coco.py │ │ ├── pisa_faster_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── pisa_mask_rcnn_r50_fpn_1x_coco.py │ │ ├── pisa_mask_rcnn_x101_32x4d_fpn_1x_coco.py │ │ ├── pisa_retinanet_r50_fpn_1x_coco.py │ │ ├── pisa_retinanet_x101_32x4d_fpn_1x_coco.py │ │ ├── pisa_ssd300_coco.py │ │ └── pisa_ssd512_coco.py │ ├── point_rend │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── point_rend_r50_caffe_fpn_mstrain_1x_coco.py │ │ └── point_rend_r50_caffe_fpn_mstrain_3x_coco.py │ ├── pvt │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── retinanet_pvt-l_fpn_1x_coco.py │ │ ├── retinanet_pvt-m_fpn_1x_coco.py │ │ ├── retinanet_pvt-s_fpn_1x_coco.py │ │ ├── retinanet_pvt-t_fpn_1x_coco.py │ │ ├── retinanet_pvtv2-b0_fpn_1x_coco.py │ │ ├── retinanet_pvtv2-b1_fpn_1x_coco.py │ │ ├── retinanet_pvtv2-b2_fpn_1x_coco.py │ │ ├── retinanet_pvtv2-b3_fpn_1x_coco.py │ │ ├── retinanet_pvtv2-b4_fpn_1x_coco.py │ │ └── retinanet_pvtv2-b5_fpn_1x_coco.py │ ├── regnet │ │ ├── README.md │ │ ├── cascade_mask_rcnn_regnetx-1.6GF_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_regnetx-400MF_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_regnetx-4GF_fpn_mstrain_3x_coco.py │ │ ├── cascade_mask_rcnn_regnetx-800MF_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_regnetx-1.6GF_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_regnetx-3.2GF_fpn_1x_coco.py │ │ ├── faster_rcnn_regnetx-3.2GF_fpn_2x_coco.py │ │ ├── faster_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_regnetx-400MF_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_regnetx-4GF_fpn_mstrain_3x_coco.py │ │ ├── faster_rcnn_regnetx-800MF_fpn_mstrain_3x_coco.py │ │ ├── mask_rcnn_regnetx-1.6GF_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_regnetx-12GF_fpn_1x_coco.py │ │ ├── mask_rcnn_regnetx-3.2GF_fpn_1x_coco.py │ │ ├── mask_rcnn_regnetx-3.2GF_fpn_mdconv_c3-c5_1x_coco.py │ │ ├── mask_rcnn_regnetx-3.2GF_fpn_mstrain_3x_coco.py │ │ ├── mask_rcnn_regnetx-400MF_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_regnetx-4GF_fpn_1x_coco.py │ │ ├── mask_rcnn_regnetx-4GF_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_regnetx-6.4GF_fpn_1x_coco.py │ │ ├── mask_rcnn_regnetx-800MF_fpn_mstrain-poly_3x_coco.py │ │ ├── mask_rcnn_regnetx-8GF_fpn_1x_coco.py │ │ ├── metafile.yml │ │ ├── retinanet_regnetx-1.6GF_fpn_1x_coco.py │ │ ├── retinanet_regnetx-3.2GF_fpn_1x_coco.py │ │ └── retinanet_regnetx-800MF_fpn_1x_coco.py │ ├── reppoints │ │ ├── README.md │ │ ├── bbox_r50_grid_center_fpn_gn-neck+head_1x_coco.py │ │ ├── bbox_r50_grid_fpn_gn-neck+head_1x_coco.py │ │ ├── metafile.yml │ │ ├── reppoints.png │ │ ├── reppoints_minmax_r50_fpn_gn-neck+head_1x_coco.py │ │ ├── reppoints_moment_r101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py │ │ ├── reppoints_moment_r101_fpn_gn-neck+head_2x_coco.py │ │ ├── reppoints_moment_r50_fpn_1x_coco.py │ │ ├── reppoints_moment_r50_fpn_gn-neck+head_1x_coco.py │ │ ├── reppoints_moment_r50_fpn_gn-neck+head_2x_coco.py │ │ ├── reppoints_moment_x101_fpn_dconv_c3-c5_gn-neck+head_2x_coco.py │ │ └── reppoints_partial_minmax_r50_fpn_gn-neck+head_1x_coco.py │ ├── res2net │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r2_101_fpn_20e_coco.py │ │ ├── cascade_rcnn_r2_101_fpn_20e_coco.py │ │ ├── faster_rcnn_r2_101_fpn_2x_coco.py │ │ ├── htc_r2_101_fpn_20e_coco.py │ │ ├── mask_rcnn_r2_101_fpn_2x_coco.py │ │ └── metafile.yml │ ├── resnest │ │ ├── README.md │ │ ├── cascade_mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ ├── cascade_mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ ├── cascade_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ ├── cascade_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ ├── faster_rcnn_s101_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ ├── faster_rcnn_s50_fpn_syncbn-backbone+head_mstrain-range_1x_coco.py │ │ ├── mask_rcnn_s101_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ ├── mask_rcnn_s50_fpn_syncbn-backbone+head_mstrain_1x_coco.py │ │ └── metafile.yml │ ├── retinanet │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── retinanet_r101_caffe_fpn_1x_coco.py │ │ ├── retinanet_r101_caffe_fpn_mstrain_3x_coco.py │ │ ├── retinanet_r101_fpn_1x_coco.py │ │ ├── retinanet_r101_fpn_2x_coco.py │ │ ├── retinanet_r101_fpn_mstrain_640-800_3x_coco.py │ │ ├── retinanet_r50_caffe_fpn_1x_coco.py │ │ ├── retinanet_r50_caffe_fpn_mstrain_1x_coco.py │ │ ├── retinanet_r50_caffe_fpn_mstrain_2x_coco.py │ │ ├── retinanet_r50_caffe_fpn_mstrain_3x_coco.py │ │ ├── retinanet_r50_fpn_1x_coco.py │ │ ├── retinanet_r50_fpn_2x_coco.py │ │ ├── retinanet_r50_fpn_mstrain_640-800_3x_coco.py │ │ ├── retinanet_x101_32x4d_fpn_1x_coco.py │ │ ├── retinanet_x101_32x4d_fpn_2x_coco.py │ │ ├── retinanet_x101_64x4d_fpn_1x_coco.py │ │ ├── retinanet_x101_64x4d_fpn_2x_coco.py │ │ └── retinanet_x101_64x4d_fpn_mstrain_640-800_3x_coco.py │ ├── rpn │ │ ├── README.md │ │ ├── rpn_r101_caffe_fpn_1x_coco.py │ │ ├── rpn_r101_fpn_1x_coco.py │ │ ├── rpn_r101_fpn_2x_coco.py │ │ ├── rpn_r50_caffe_c4_1x_coco.py │ │ ├── rpn_r50_caffe_fpn_1x_coco.py │ │ ├── rpn_r50_fpn_1x_coco.py │ │ ├── rpn_r50_fpn_2x_coco.py │ │ ├── rpn_x101_32x4d_fpn_1x_coco.py │ │ ├── rpn_x101_32x4d_fpn_2x_coco.py │ │ ├── rpn_x101_64x4d_fpn_1x_coco.py │ │ └── rpn_x101_64x4d_fpn_2x_coco.py │ ├── sabl │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── sabl_cascade_rcnn_r101_fpn_1x_coco.py │ │ ├── sabl_cascade_rcnn_r50_fpn_1x_coco.py │ │ ├── sabl_faster_rcnn_r101_fpn_1x_coco.py │ │ ├── sabl_faster_rcnn_r50_fpn_1x_coco.py │ │ ├── sabl_retinanet_r101_fpn_1x_coco.py │ │ ├── sabl_retinanet_r101_fpn_gn_1x_coco.py │ │ ├── sabl_retinanet_r101_fpn_gn_2x_ms_480_960_coco.py │ │ ├── sabl_retinanet_r101_fpn_gn_2x_ms_640_800_coco.py │ │ ├── sabl_retinanet_r50_fpn_1x_coco.py │ │ └── sabl_retinanet_r50_fpn_gn_1x_coco.py │ ├── scnet │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── scnet_r101_fpn_20e_coco.py │ │ ├── scnet_r50_fpn_1x_coco.py │ │ ├── scnet_r50_fpn_20e_coco.py │ │ ├── scnet_x101_64x4d_fpn_20e_coco.py │ │ └── scnet_x101_64x4d_fpn_8x1_20e_coco.py │ ├── scratch │ │ ├── README.md │ │ ├── faster_rcnn_r50_fpn_gn-all_scratch_6x_coco.py │ │ ├── mask_rcnn_r50_fpn_gn-all_scratch_6x_coco.py │ │ └── metafile.yml │ ├── seesaw_loss │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py │ │ ├── cascade_mask_rcnn_r101_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ │ ├── cascade_mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py │ │ ├── cascade_mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r101_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r50_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r50_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ │ ├── mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py │ │ └── mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py │ ├── selfsup_pretrain │ │ ├── README.md │ │ ├── mask_rcnn_r50_fpn_mocov2-pretrain_1x_coco.py │ │ ├── mask_rcnn_r50_fpn_mocov2-pretrain_ms-2x_coco.py │ │ ├── mask_rcnn_r50_fpn_swav-pretrain_1x_coco.py │ │ └── mask_rcnn_r50_fpn_swav-pretrain_ms-2x_coco.py │ ├── solo │ │ ├── README.md │ │ ├── decoupled_solo_light_r50_fpn_3x_coco.py │ │ ├── decoupled_solo_r50_fpn_1x_coco.py │ │ ├── decoupled_solo_r50_fpn_3x_coco.py │ │ ├── metafile.yml │ │ ├── solo_r50_fpn_1x_coco.py │ │ └── solo_r50_fpn_3x_coco.py │ ├── sparse_rcnn │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── sparse_rcnn_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py │ │ ├── sparse_rcnn_r101_fpn_mstrain_480-800_3x_coco.py │ │ ├── sparse_rcnn_r50_fpn_1x_coco.py │ │ ├── sparse_rcnn_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py │ │ └── sparse_rcnn_r50_fpn_mstrain_480-800_3x_coco.py │ ├── ssd │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── ssd300_coco.py │ │ ├── ssd512_coco.py │ │ └── ssdlite_mobilenetv2_scratch_600e_coco.py │ ├── strong_baselines │ │ ├── README.md │ │ ├── mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_fp16_coco.py │ │ ├── mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_400e_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_fp16_coco.py │ │ └── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_50e_coco.py │ ├── swin │ │ ├── README.md │ │ ├── mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco.py │ │ ├── mask_rcnn_swin-t-p4-w7_fpn_1x_coco.py │ │ ├── mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco.py │ │ ├── mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco.py │ │ └── metafile.yml │ ├── tridentnet │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── tridentnet_r50_caffe_1x_coco.py │ │ ├── tridentnet_r50_caffe_mstrain_1x_coco.py │ │ └── tridentnet_r50_caffe_mstrain_3x_coco.py │ ├── vfnet │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── vfnet_r101_fpn_1x_coco.py │ │ ├── vfnet_r101_fpn_2x_coco.py │ │ ├── vfnet_r101_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ ├── vfnet_r101_fpn_mstrain_2x_coco.py │ │ ├── vfnet_r2_101_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ ├── vfnet_r2_101_fpn_mstrain_2x_coco.py │ │ ├── vfnet_r50_fpn_1x_coco.py │ │ ├── vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ ├── vfnet_r50_fpn_mstrain_2x_coco.py │ │ ├── vfnet_x101_32x4d_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ ├── vfnet_x101_32x4d_fpn_mstrain_2x_coco.py │ │ ├── vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco.py │ │ └── vfnet_x101_64x4d_fpn_mstrain_2x_coco.py │ ├── wider_face │ │ ├── README.md │ │ └── ssd300_wider_face.py │ ├── yolact │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── yolact_r101_1x8_coco.py │ │ ├── yolact_r50_1x8_coco.py │ │ └── yolact_r50_8x8_coco.py │ ├── yolo │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── yolov3_d53_320_273e_coco.py │ │ ├── yolov3_d53_fp16_mstrain-608_273e_coco.py │ │ ├── yolov3_d53_mstrain-416_273e_coco.py │ │ ├── yolov3_d53_mstrain-608_273e_coco.py │ │ ├── yolov3_mobilenetv2_320_300e_coco.py │ │ └── yolov3_mobilenetv2_mstrain-416_300e_coco.py │ ├── yolof │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── yolof_r50_c5_8x8_1x_coco.py │ │ └── yolof_r50_c5_8x8_iter-1x_coco.py │ └── yolox │ │ ├── README.md │ │ ├── metafile.yml │ │ ├── yolox_l_8x8_300e_coco.py │ │ ├── yolox_m_8x8_300e_coco.py │ │ ├── yolox_nano_8x8_300e_coco.py │ │ ├── yolox_s_8x8_300e_coco.py │ │ ├── yolox_tiny_8x8_300e_coco.py │ │ └── yolox_x_8x8_300e_coco.py ├── demo │ ├── MMDet_Tutorial.ipynb │ ├── create_result_gif.py │ ├── demo.jpg │ ├── demo.mp4 │ ├── image_demo.py │ ├── inference_demo.ipynb │ ├── video_demo.py │ └── webcam_demo.py ├── docker │ ├── Dockerfile │ └── serve │ │ ├── Dockerfile │ │ ├── config.properties │ │ └── entrypoint.sh ├── docs │ ├── 1_exist_data_model.md │ ├── 2_new_data_model.md │ ├── 3_exist_data_new_model.md │ ├── Makefile │ ├── _static │ │ ├── css │ │ │ └── readthedocs.css │ │ └── image │ │ │ └── mmdet-logo.png │ ├── api.rst │ ├── changelog.md │ ├── compatibility.md │ ├── conf.py │ ├── conventions.md │ ├── faq.md │ ├── get_started.md │ ├── index.rst │ ├── make.bat │ ├── model_zoo.md │ ├── projects.md │ ├── robustness_benchmarking.md │ ├── stat.py │ ├── switch_language.md │ ├── tutorials │ │ ├── config.md │ │ ├── customize_dataset.md │ │ ├── customize_losses.md │ │ ├── customize_models.md │ │ ├── customize_runtime.md │ │ ├── data_pipeline.md │ │ ├── finetune.md │ │ ├── index.rst │ │ ├── init_cfg.md │ │ ├── onnx2tensorrt.md │ │ └── pytorch2onnx.md │ └── useful_tools.md ├── docs_zh-CN │ ├── 1_exist_data_model.md │ ├── 2_new_data_model.md │ ├── 3_exist_data_new_model.md │ ├── Makefile │ ├── _static │ │ ├── css │ │ │ └── readthedocs.css │ │ └── image │ │ │ └── mmdet-logo.png │ ├── api.rst │ ├── compatibility.md │ ├── conf.py │ ├── conventions.md │ ├── faq.md │ ├── get_started.md │ ├── index.rst │ ├── make.bat │ ├── model_zoo.md │ ├── projects.md │ ├── robustness_benchmarking.md │ ├── stat.py │ ├── switch_language.md │ ├── tutorials │ │ ├── config.md │ │ ├── customize_dataset.md │ │ ├── customize_losses.md │ │ ├── customize_models.md │ │ ├── customize_runtime.md │ │ ├── data_pipeline.md │ │ ├── finetune.md │ │ ├── index.rst │ │ ├── onnx2tensorrt.md │ │ └── pytorch2onnx.md │ └── useful_tools.md ├── lvt.png ├── mmdet │ ├── __init__.py │ ├── apis │ │ ├── __init__.py │ │ ├── inference.py │ │ ├── test.py │ │ └── train.py │ ├── core │ │ ├── __init__.py │ │ ├── anchor │ │ │ ├── __init__.py │ │ │ ├── anchor_generator.py │ │ │ ├── builder.py │ │ │ ├── point_generator.py │ │ │ └── utils.py │ │ ├── bbox │ │ │ ├── __init__.py │ │ │ ├── assigners │ │ │ │ ├── __init__.py │ │ │ │ ├── approx_max_iou_assigner.py │ │ │ │ ├── assign_result.py │ │ │ │ ├── atss_assigner.py │ │ │ │ ├── base_assigner.py │ │ │ │ ├── center_region_assigner.py │ │ │ │ ├── grid_assigner.py │ │ │ │ ├── hungarian_assigner.py │ │ │ │ ├── max_iou_assigner.py │ │ │ │ ├── point_assigner.py │ │ │ │ ├── region_assigner.py │ │ │ │ ├── sim_ota_assigner.py │ │ │ │ └── uniform_assigner.py │ │ │ ├── builder.py │ │ │ ├── coder │ │ │ │ ├── __init__.py │ │ │ │ ├── base_bbox_coder.py │ │ │ │ ├── bucketing_bbox_coder.py │ │ │ │ ├── delta_xywh_bbox_coder.py │ │ │ │ ├── legacy_delta_xywh_bbox_coder.py │ │ │ │ ├── pseudo_bbox_coder.py │ │ │ │ ├── tblr_bbox_coder.py │ │ │ │ └── yolo_bbox_coder.py │ │ │ ├── demodata.py │ │ │ ├── iou_calculators │ │ │ │ ├── __init__.py │ │ │ │ ├── builder.py │ │ │ │ └── iou2d_calculator.py │ │ │ ├── match_costs │ │ │ │ ├── __init__.py │ │ │ │ ├── builder.py │ │ │ │ └── match_cost.py │ │ │ ├── samplers │ │ │ │ ├── __init__.py │ │ │ │ ├── base_sampler.py │ │ │ │ ├── combined_sampler.py │ │ │ │ ├── instance_balanced_pos_sampler.py │ │ │ │ ├── iou_balanced_neg_sampler.py │ │ │ │ ├── ohem_sampler.py │ │ │ │ ├── pseudo_sampler.py │ │ │ │ ├── random_sampler.py │ │ │ │ ├── sampling_result.py │ │ │ │ └── score_hlr_sampler.py │ │ │ └── transforms.py │ │ ├── data_structures │ │ │ ├── __init__.py │ │ │ ├── general_data.py │ │ │ └── instance_data.py │ │ ├── evaluation │ │ │ ├── __init__.py │ │ │ ├── bbox_overlaps.py │ │ │ ├── class_names.py │ │ │ ├── eval_hooks.py │ │ │ ├── mean_ap.py │ │ │ └── recall.py │ │ ├── export │ │ │ ├── __init__.py │ │ │ ├── model_wrappers.py │ │ │ ├── onnx_helper.py │ │ │ └── pytorch2onnx.py │ │ ├── hook │ │ │ ├── __init__.py │ │ │ ├── checkloss_hook.py │ │ │ ├── ema.py │ │ │ ├── sync_norm_hook.py │ │ │ ├── sync_random_size_hook.py │ │ │ ├── yolox_lrupdater_hook.py │ │ │ └── yolox_mode_switch_hook.py │ │ ├── mask │ │ │ ├── __init__.py │ │ │ ├── mask_target.py │ │ │ ├── structures.py │ │ │ └── utils.py │ │ ├── post_processing │ │ │ ├── __init__.py │ │ │ ├── bbox_nms.py │ │ │ ├── matrix_nms.py │ │ │ └── merge_augs.py │ │ ├── utils │ │ │ ├── __init__.py │ │ │ ├── dist_utils.py │ │ │ └── misc.py │ │ └── visualization │ │ │ ├── __init__.py │ │ │ └── image.py │ ├── datasets │ │ ├── __init__.py │ │ ├── api_wrappers │ │ │ ├── __init__.py │ │ │ └── coco_api.py │ │ ├── builder.py │ │ ├── cityscapes.py │ │ ├── coco.py │ │ ├── coco_panoptic.py │ │ ├── custom.py │ │ ├── dataset_wrappers.py │ │ ├── deepfashion.py │ │ ├── lvis.py │ │ ├── pipelines │ │ │ ├── __init__.py │ │ │ ├── auto_augment.py │ │ │ ├── compose.py │ │ │ ├── formating.py │ │ │ ├── instaboost.py │ │ │ ├── loading.py │ │ │ ├── test_time_aug.py │ │ │ └── transforms.py │ │ ├── samplers │ │ │ ├── __init__.py │ │ │ ├── distributed_sampler.py │ │ │ └── group_sampler.py │ │ ├── utils.py │ │ ├── voc.py │ │ ├── wider_face.py │ │ └── xml_style.py │ ├── models │ │ ├── __init__.py │ │ ├── backbones │ │ │ ├── __init__.py │ │ │ ├── csp_darknet.py │ │ │ ├── darknet.py │ │ │ ├── detectors_resnet.py │ │ │ ├── detectors_resnext.py │ │ │ ├── hourglass.py │ │ │ ├── hrnet.py │ │ │ ├── lvt.py │ │ │ ├── mobilenet_v2.py │ │ │ ├── pvt.py │ │ │ ├── regnet.py │ │ │ ├── res2net.py │ │ │ ├── resnest.py │ │ │ ├── resnet.py │ │ │ ├── resnext.py │ │ │ ├── ssd_vgg.py │ │ │ ├── swin.py │ │ │ └── trident_resnet.py │ │ ├── builder.py │ │ ├── dense_heads │ │ │ ├── __init__.py │ │ │ ├── anchor_free_head.py │ │ │ ├── anchor_head.py │ │ │ ├── atss_head.py │ │ │ ├── autoassign_head.py │ │ │ ├── base_dense_head.py │ │ │ ├── base_mask_head.py │ │ │ ├── cascade_rpn_head.py │ │ │ ├── centernet_head.py │ │ │ ├── centripetal_head.py │ │ │ ├── corner_head.py │ │ │ ├── deformable_detr_head.py │ │ │ ├── dense_test_mixins.py │ │ │ ├── detr_head.py │ │ │ ├── embedding_rpn_head.py │ │ │ ├── fcos_head.py │ │ │ ├── fovea_head.py │ │ │ ├── free_anchor_retina_head.py │ │ │ ├── fsaf_head.py │ │ │ ├── ga_retina_head.py │ │ │ ├── ga_rpn_head.py │ │ │ ├── gfl_head.py │ │ │ ├── guided_anchor_head.py │ │ │ ├── ld_head.py │ │ │ ├── nasfcos_head.py │ │ │ ├── paa_head.py │ │ │ ├── pisa_retinanet_head.py │ │ │ ├── pisa_ssd_head.py │ │ │ ├── reppoints_head.py │ │ │ ├── retina_head.py │ │ │ ├── retina_sepbn_head.py │ │ │ ├── rpn_head.py │ │ │ ├── sabl_retina_head.py │ │ │ ├── solo_head.py │ │ │ ├── ssd_head.py │ │ │ ├── vfnet_head.py │ │ │ ├── yolact_head.py │ │ │ ├── yolo_head.py │ │ │ ├── yolof_head.py │ │ │ └── yolox_head.py │ │ ├── detectors │ │ │ ├── __init__.py │ │ │ ├── atss.py │ │ │ ├── autoassign.py │ │ │ ├── base.py │ │ │ ├── cascade_rcnn.py │ │ │ ├── centernet.py │ │ │ ├── cornernet.py │ │ │ ├── deformable_detr.py │ │ │ ├── detr.py │ │ │ ├── fast_rcnn.py │ │ │ ├── faster_rcnn.py │ │ │ ├── fcos.py │ │ │ ├── fovea.py │ │ │ ├── fsaf.py │ │ │ ├── gfl.py │ │ │ ├── grid_rcnn.py │ │ │ ├── htc.py │ │ │ ├── kd_one_stage.py │ │ │ ├── mask_rcnn.py │ │ │ ├── mask_scoring_rcnn.py │ │ │ ├── nasfcos.py │ │ │ ├── paa.py │ │ │ ├── panoptic_fpn.py │ │ │ ├── panoptic_two_stage_segmentor.py │ │ │ ├── point_rend.py │ │ │ ├── reppoints_detector.py │ │ │ ├── retinanet.py │ │ │ ├── rpn.py │ │ │ ├── scnet.py │ │ │ ├── single_stage.py │ │ │ ├── single_stage_instance_seg.py │ │ │ ├── solo.py │ │ │ ├── sparse_rcnn.py │ │ │ ├── trident_faster_rcnn.py │ │ │ ├── two_stage.py │ │ │ ├── vfnet.py │ │ │ ├── yolact.py │ │ │ ├── yolo.py │ │ │ ├── yolof.py │ │ │ └── yolox.py │ │ ├── losses │ │ │ ├── __init__.py │ │ │ ├── accuracy.py │ │ │ ├── ae_loss.py │ │ │ ├── balanced_l1_loss.py │ │ │ ├── cross_entropy_loss.py │ │ │ ├── dice_loss.py │ │ │ ├── focal_loss.py │ │ │ ├── gaussian_focal_loss.py │ │ │ ├── gfocal_loss.py │ │ │ ├── ghm_loss.py │ │ │ ├── iou_loss.py │ │ │ ├── kd_loss.py │ │ │ ├── mse_loss.py │ │ │ ├── pisa_loss.py │ │ │ ├── seesaw_loss.py │ │ │ ├── smooth_l1_loss.py │ │ │ ├── utils.py │ │ │ └── varifocal_loss.py │ │ ├── necks │ │ │ ├── __init__.py │ │ │ ├── bfp.py │ │ │ ├── channel_mapper.py │ │ │ ├── ct_resnet_neck.py │ │ │ ├── dilated_encoder.py │ │ │ ├── fpg.py │ │ │ ├── fpn.py │ │ │ ├── fpn_carafe.py │ │ │ ├── hrfpn.py │ │ │ ├── nas_fpn.py │ │ │ ├── nasfcos_fpn.py │ │ │ ├── pafpn.py │ │ │ ├── rfp.py │ │ │ ├── ssd_neck.py │ │ │ ├── yolo_neck.py │ │ │ └── yolox_pafpn.py │ │ ├── plugins │ │ │ ├── __init__.py │ │ │ └── dropblock.py │ │ ├── roi_heads │ │ │ ├── __init__.py │ │ │ ├── base_roi_head.py │ │ │ ├── bbox_heads │ │ │ │ ├── __init__.py │ │ │ │ ├── bbox_head.py │ │ │ │ ├── convfc_bbox_head.py │ │ │ │ ├── dii_head.py │ │ │ │ ├── double_bbox_head.py │ │ │ │ ├── sabl_head.py │ │ │ │ └── scnet_bbox_head.py │ │ │ ├── cascade_roi_head.py │ │ │ ├── double_roi_head.py │ │ │ ├── dynamic_roi_head.py │ │ │ ├── grid_roi_head.py │ │ │ ├── htc_roi_head.py │ │ │ ├── mask_heads │ │ │ │ ├── __init__.py │ │ │ │ ├── coarse_mask_head.py │ │ │ │ ├── fcn_mask_head.py │ │ │ │ ├── feature_relay_head.py │ │ │ │ ├── fused_semantic_head.py │ │ │ │ ├── global_context_head.py │ │ │ │ ├── grid_head.py │ │ │ │ ├── htc_mask_head.py │ │ │ │ ├── mask_point_head.py │ │ │ │ ├── maskiou_head.py │ │ │ │ ├── scnet_mask_head.py │ │ │ │ └── scnet_semantic_head.py │ │ │ ├── mask_scoring_roi_head.py │ │ │ ├── pisa_roi_head.py │ │ │ ├── point_rend_roi_head.py │ │ │ ├── roi_extractors │ │ │ │ ├── __init__.py │ │ │ │ ├── base_roi_extractor.py │ │ │ │ ├── generic_roi_extractor.py │ │ │ │ └── single_level_roi_extractor.py │ │ │ ├── scnet_roi_head.py │ │ │ ├── shared_heads │ │ │ │ ├── __init__.py │ │ │ │ └── res_layer.py │ │ │ ├── sparse_roi_head.py │ │ │ ├── standard_roi_head.py │ │ │ ├── test_mixins.py │ │ │ └── trident_roi_head.py │ │ ├── seg_heads │ │ │ ├── __init__.py │ │ │ ├── base_semantic_head.py │ │ │ ├── panoptic_fpn_head.py │ │ │ └── panoptic_fusion_heads │ │ │ │ ├── __init__.py │ │ │ │ ├── base_panoptic_fusion_head.py │ │ │ │ └── heuristic_fusion_head.py │ │ └── utils │ │ │ ├── __init__.py │ │ │ ├── brick_wrappers.py │ │ │ ├── builder.py │ │ │ ├── ckpt_convert.py │ │ │ ├── conv_upsample.py │ │ │ ├── csp_layer.py │ │ │ ├── gaussian_target.py │ │ │ ├── inverted_residual.py │ │ │ ├── make_divisible.py │ │ │ ├── misc.py │ │ │ ├── normed_predictor.py │ │ │ ├── positional_encoding.py │ │ │ ├── res_layer.py │ │ │ ├── se_layer.py │ │ │ └── transformer.py │ ├── utils │ │ ├── __init__.py │ │ ├── collect_env.py │ │ ├── contextmanagers.py │ │ ├── logger.py │ │ ├── profiling.py │ │ ├── util_mixins.py │ │ └── util_random.py │ └── version.py ├── model-index.yml ├── pytest.ini ├── requirements.txt ├── requirements │ ├── build.txt │ ├── docs.txt │ ├── mminstall.txt │ ├── optional.txt │ ├── readthedocs.txt │ ├── runtime.txt │ └── tests.txt ├── resources │ ├── coco_test_12510.jpg │ ├── corruptions_sev_3.png │ ├── data_pipeline.png │ ├── loss_curve.png │ ├── mmdet-logo.png │ ├── qq_group_qrcode.jpg │ └── zhihu_qrcode.jpg ├── setup.cfg ├── setup.py ├── tests │ ├── test_data │ │ ├── test_datasets │ │ │ ├── test_coco_dataset.py │ │ │ ├── test_common.py │ │ │ ├── test_custom_dataset.py │ │ │ ├── test_dataset_wrapper.py │ │ │ ├── test_panoptic_dataset.py │ │ │ └── test_xml_dataset.py │ │ ├── test_pipelines │ │ │ ├── test_formatting.py │ │ │ ├── test_loading.py │ │ │ ├── test_sampler.py │ │ │ └── test_transform │ │ │ │ ├── __init__.py │ │ │ │ ├── test_img_augment.py │ │ │ │ ├── test_models_aug_test.py │ │ │ │ ├── test_rotate.py │ │ │ │ ├── test_shear.py │ │ │ │ ├── test_transform.py │ │ │ │ ├── test_translate.py │ │ │ │ └── utils.py │ │ └── test_utils.py │ ├── test_downstream │ │ └── test_mmtrack.py │ ├── test_metrics │ │ ├── test_box_overlap.py │ │ ├── test_losses.py │ │ ├── test_mean_ap.py │ │ └── test_recall.py │ ├── test_models │ │ ├── test_backbones │ │ │ ├── __init__.py │ │ │ ├── test_csp_darknet.py │ │ │ ├── test_detectors_resnet.py │ │ │ ├── test_hourglass.py │ │ │ ├── test_hrnet.py │ │ │ ├── test_mobilenet_v2.py │ │ │ ├── test_pvt.py │ │ │ ├── test_regnet.py │ │ │ ├── test_renext.py │ │ │ ├── test_res2net.py │ │ │ ├── test_resnest.py │ │ │ ├── test_resnet.py │ │ │ ├── test_swin.py │ │ │ ├── test_trident_resnet.py │ │ │ └── utils.py │ │ ├── test_dense_heads │ │ │ ├── test_anchor_head.py │ │ │ ├── test_atss_head.py │ │ │ ├── test_autoassign_head.py │ │ │ ├── test_centernet_head.py │ │ │ ├── test_corner_head.py │ │ │ ├── test_dense_heads_attr.py │ │ │ ├── test_detr_head.py │ │ │ ├── test_fcos_head.py │ │ │ ├── test_fsaf_head.py │ │ │ ├── test_ga_anchor_head.py │ │ │ ├── test_gfl_head.py │ │ │ ├── test_ld_head.py │ │ │ ├── test_paa_head.py │ │ │ ├── test_pisa_head.py │ │ │ ├── test_sabl_retina_head.py │ │ │ ├── test_solo_head.py │ │ │ ├── test_vfnet_head.py │ │ │ ├── test_yolact_head.py │ │ │ ├── test_yolof_head.py │ │ │ └── test_yolox_head.py │ │ ├── test_forward.py │ │ ├── test_loss.py │ │ ├── test_loss_compatibility.py │ │ ├── test_necks.py │ │ ├── test_plugins.py │ │ ├── test_roi_heads │ │ │ ├── __init__.py │ │ │ ├── test_bbox_head.py │ │ │ ├── test_mask_head.py │ │ │ ├── test_roi_extractor.py │ │ │ ├── test_sabl_bbox_head.py │ │ │ └── utils.py │ │ └── test_utils │ │ │ ├── test_brick_wrappers.py │ │ │ ├── test_conv_upsample.py │ │ │ ├── test_inverted_residual.py │ │ │ ├── test_model_misc.py │ │ │ ├── test_position_encoding.py │ │ │ ├── test_se_layer.py │ │ │ └── test_transformer.py │ ├── test_onnx │ │ ├── __init__.py │ │ ├── test_head.py │ │ ├── test_neck.py │ │ └── utils.py │ ├── test_runtime │ │ ├── async_benchmark.py │ │ ├── test_async.py │ │ ├── test_config.py │ │ ├── test_eval_hook.py │ │ └── test_fp16.py │ └── test_utils │ │ ├── test_anchor.py │ │ ├── test_assigner.py │ │ ├── test_coder.py │ │ ├── test_general_data.py │ │ ├── test_hook.py │ │ ├── test_masks.py │ │ ├── test_misc.py │ │ ├── test_nms.py │ │ ├── test_version.py │ │ └── test_visualization.py └── tools │ ├── analysis_tools │ ├── analyze_logs.py │ ├── analyze_results.py │ ├── benchmark.py │ ├── coco_error_analysis.py │ ├── eval_metric.py │ ├── get_flops.py │ ├── optimize_anchors.py │ ├── robustness_eval.py │ └── test_robustness.py │ ├── dataset_converters │ ├── cityscapes.py │ ├── images2coco.py │ └── pascal_voc.py │ ├── deployment │ ├── mmdet2torchserve.py │ ├── mmdet_handler.py │ ├── onnx2tensorrt.py │ ├── pytorch2onnx.py │ ├── test.py │ └── test_torchserver.py │ ├── dist_test.sh │ ├── dist_train.sh │ ├── misc │ ├── browse_dataset.py │ └── print_config.py │ ├── model_converters │ ├── detectron2pytorch.py │ ├── publish_model.py │ ├── regnet2mmdet.py │ ├── selfsup2mmdet.py │ ├── upgrade_model_version.py │ └── upgrade_ssd_version.py │ ├── slurm_test.sh │ ├── slurm_train.sh │ ├── test.py │ └── train.py └── segmentation ├── .gitignore ├── Images └── lvt.png ├── LICENSE ├── README.md ├── README.segformer.md ├── configs ├── _base_ │ ├── datasets │ │ ├── ade20k.py │ │ ├── chase_db1.py │ │ ├── cityscapes.py │ │ ├── cityscapes_768x768.py │ │ ├── cityscapes_769x769.py │ │ ├── drive.py │ │ ├── hrf.py │ │ ├── pascal_context.py │ │ ├── pascal_voc12.py │ │ ├── pascal_voc12_aug.py │ │ └── stare.py │ ├── default_runtime.py │ ├── models │ │ ├── ann_r50-d8.py │ │ ├── apcnet_r50-d8.py │ │ ├── ccnet_r50-d8.py │ │ ├── cgnet.py │ │ ├── danet_r50-d8.py │ │ ├── deeplabv3_r50-d8.py │ │ ├── deeplabv3_unet_s5-d16.py │ │ ├── deeplabv3plus_r50-d8.py │ │ ├── dmnet_r50-d8.py │ │ ├── dnl_r50-d8.py │ │ ├── emanet_r50-d8.py │ │ ├── encnet_r50-d8.py │ │ ├── fast_scnn.py │ │ ├── fcn_hr18.py │ │ ├── fcn_r50-d8.py │ │ ├── fcn_unet_s5-d16.py │ │ ├── fpn_r50.py │ │ ├── gcnet_r50-d8.py │ │ ├── lraspp_m-v3-d8.py │ │ ├── nonlocal_r50-d8.py │ │ ├── ocrnet_hr18.py │ │ ├── ocrnet_r50-d8.py │ │ ├── pointrend_r50.py │ │ ├── psanet_r50-d8.py │ │ ├── pspnet_r50-d8.py │ │ ├── pspnet_unet_s5-d16.py │ │ └── upernet_r50.py │ └── schedules │ │ ├── schedule_160k.py │ │ ├── schedule_20k.py │ │ ├── schedule_40k.py │ │ └── schedule_80k.py ├── ann │ ├── README.md │ ├── ann_r101-d8_512x1024_40k_cityscapes.py │ ├── ann_r101-d8_512x1024_80k_cityscapes.py │ ├── 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_r50-d8_512x1024_40k_cityscapes.py │ ├── ann_r50-d8_512x1024_80k_cityscapes.py │ ├── ann_r50-d8_512x512_160k_ade20k.py │ ├── ann_r50-d8_512x512_20k_voc12aug.py │ ├── ann_r50-d8_512x512_40k_voc12aug.py │ ├── ann_r50-d8_512x512_80k_ade20k.py │ ├── ann_r50-d8_769x769_40k_cityscapes.py │ └── ann_r50-d8_769x769_80k_cityscapes.py ├── apcnet │ ├── README.md │ ├── apcnet_r101-d8_512x1024_40k_cityscapes.py │ ├── apcnet_r101-d8_512x1024_80k_cityscapes.py │ ├── apcnet_r101-d8_512x512_160k_ade20k.py │ ├── apcnet_r101-d8_512x512_80k_ade20k.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 │ └── apcnet_r50-d8_769x769_80k_cityscapes.py ├── ccnet │ ├── README.md │ ├── ccnet_r101-d8_512x1024_40k_cityscapes.py │ ├── ccnet_r101-d8_512x1024_80k_cityscapes.py │ ├── ccnet_r101-d8_512x512_160k_ade20k.py │ ├── ccnet_r101-d8_512x512_20k_voc12aug.py │ ├── ccnet_r101-d8_512x512_40k_voc12aug.py │ ├── ccnet_r101-d8_512x512_80k_ade20k.py │ ├── ccnet_r101-d8_769x769_40k_cityscapes.py │ ├── ccnet_r101-d8_769x769_80k_cityscapes.py │ ├── ccnet_r50-d8_512x1024_40k_cityscapes.py │ ├── ccnet_r50-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.py │ ├── ccnet_r50-d8_769x769_40k_cityscapes.py │ └── ccnet_r50-d8_769x769_80k_cityscapes.py ├── cgnet │ ├── README.md │ ├── cgnet_512x1024_60k_cityscapes.py │ └── cgnet_680x680_60k_cityscapes.py ├── danet │ ├── README.md │ ├── danet_r101-d8_512x1024_40k_cityscapes.py │ ├── danet_r101-d8_512x1024_80k_cityscapes.py │ ├── danet_r101-d8_512x512_160k_ade20k.py │ ├── danet_r101-d8_512x512_20k_voc12aug.py │ ├── danet_r101-d8_512x512_40k_voc12aug.py │ ├── danet_r101-d8_512x512_80k_ade20k.py │ ├── danet_r101-d8_769x769_40k_cityscapes.py │ ├── danet_r101-d8_769x769_80k_cityscapes.py │ ├── danet_r50-d8_512x1024_40k_cityscapes.py │ ├── danet_r50-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.py │ ├── danet_r50-d8_769x769_40k_cityscapes.py │ └── danet_r50-d8_769x769_80k_cityscapes.py ├── deeplabv3 │ ├── README.md │ ├── deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes.py │ ├── deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes.py │ ├── deeplabv3_r101-d8_480x480_40k_pascal_context.py │ ├── deeplabv3_r101-d8_480x480_80k_pascal_context.py │ ├── deeplabv3_r101-d8_512x1024_40k_cityscapes.py │ ├── deeplabv3_r101-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.py │ ├── deeplabv3_r101-d8_769x769_40k_cityscapes.py │ ├── deeplabv3_r101-d8_769x769_80k_cityscapes.py │ ├── deeplabv3_r101b-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3_r101b-d8_769x769_80k_cityscapes.py │ ├── deeplabv3_r18-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3_r18-d8_769x769_80k_cityscapes.py │ ├── deeplabv3_r18b-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3_r18b-d8_769x769_80k_cityscapes.py │ ├── deeplabv3_r50-d8_480x480_40k_pascal_context.py │ ├── deeplabv3_r50-d8_480x480_80k_pascal_context.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_20k_voc12aug.py │ ├── deeplabv3_r50-d8_512x512_40k_voc12aug.py │ ├── deeplabv3_r50-d8_512x512_80k_ade20k.py │ ├── deeplabv3_r50-d8_769x769_40k_cityscapes.py │ ├── deeplabv3_r50-d8_769x769_80k_cityscapes.py │ ├── deeplabv3_r50b-d8_512x1024_80k_cityscapes.py │ └── deeplabv3_r50b-d8_769x769_80k_cityscapes.py ├── deeplabv3plus │ ├── README.md │ ├── deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py │ ├── deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_r101-d8_480x480_40k_pascal_context.py │ ├── deeplabv3plus_r101-d8_480x480_80k_pascal_context.py │ ├── deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py │ ├── deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py │ ├── 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_r101b-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py │ ├── deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_r18-d8_769x769_80k_cityscapes.py │ ├── deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py │ ├── deeplabv3plus_r50-d8_480x480_40k_pascal_context.py │ ├── deeplabv3plus_r50-d8_480x480_80k_pascal_context.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_20k_voc12aug.py │ ├── deeplabv3plus_r50-d8_512x512_40k_voc12aug.py │ ├── deeplabv3plus_r50-d8_512x512_80k_ade20k.py │ ├── deeplabv3plus_r50-d8_769x769_40k_cityscapes.py │ ├── deeplabv3plus_r50-d8_769x769_80k_cityscapes.py │ ├── deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py │ └── deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py ├── dmnet │ ├── README.md │ ├── dmnet_r101-d8_512x1024_40k_cityscapes.py │ ├── dmnet_r101-d8_512x1024_80k_cityscapes.py │ ├── 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_r50-d8_512x1024_40k_cityscapes.py │ ├── dmnet_r50-d8_512x1024_80k_cityscapes.py │ ├── dmnet_r50-d8_512x512_160k_ade20k.py │ ├── dmnet_r50-d8_512x512_80k_ade20k.py │ ├── dmnet_r50-d8_769x769_40k_cityscapes.py │ └── dmnet_r50-d8_769x769_80k_cityscapes.py ├── dnlnet │ ├── README.md │ ├── dnl_r101-d8_512x1024_40k_cityscapes.py │ ├── dnl_r101-d8_512x1024_80k_cityscapes.py │ ├── dnl_r101-d8_512x512_160k_ade20k.py │ ├── dnl_r101-d8_512x512_80k_ade20k.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 │ └── dnl_r50-d8_769x769_80k_cityscapes.py ├── emanet │ ├── README.md │ ├── emanet_r101-d8_512x1024_80k_cityscapes.py │ ├── emanet_r101-d8_769x769_80k_cityscapes.py │ ├── emanet_r50-d8_512x1024_80k_cityscapes.py │ └── emanet_r50-d8_769x769_80k_cityscapes.py ├── encnet │ ├── README.md │ ├── encnet_r101-d8_512x1024_40k_cityscapes.py │ ├── encnet_r101-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.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_20k_voc12aug.py │ ├── encnet_r50-d8_512x512_40k_voc12aug.py │ ├── encnet_r50-d8_512x512_80k_ade20k.py │ ├── encnet_r50-d8_769x769_40k_cityscapes.py │ ├── encnet_r50-d8_769x769_80k_cityscapes.py │ └── encnet_r50s-d8_512x512_80k_ade20k.py ├── fastscnn │ ├── README.md │ └── fast_scnn_4x8_80k_lr0.12_cityscapes.py ├── fcn │ ├── README.md │ ├── fcn_r101-d8_480x480_40k_pascal_context.py │ ├── fcn_r101-d8_480x480_80k_pascal_context.py │ ├── fcn_r101-d8_512x1024_40k_cityscapes.py │ ├── fcn_r101-d8_512x1024_80k_cityscapes.py │ ├── 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_r101b-d8_512x1024_80k_cityscapes.py │ ├── fcn_r101b-d8_769x769_80k_cityscapes.py │ ├── fcn_r18-d8_512x1024_80k_cityscapes.py │ ├── fcn_r18-d8_769x769_80k_cityscapes.py │ ├── fcn_r18b-d8_512x1024_80k_cityscapes.py │ ├── fcn_r18b-d8_769x769_80k_cityscapes.py │ ├── fcn_r50-d8_480x480_40k_pascal_context.py │ ├── fcn_r50-d8_480x480_80k_pascal_context.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_20k_voc12aug.py │ ├── fcn_r50-d8_512x512_40k_voc12aug.py │ ├── fcn_r50-d8_512x512_80k_ade20k.py │ ├── fcn_r50-d8_769x769_40k_cityscapes.py │ ├── fcn_r50-d8_769x769_80k_cityscapes.py │ ├── fcn_r50b-d8_512x1024_80k_cityscapes.py │ └── fcn_r50b-d8_769x769_80k_cityscapes.py ├── fp16 │ ├── README.md │ ├── deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py │ ├── deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py │ ├── fcn_r101-d8_512x1024_80k_fp16_cityscapes.py │ └── pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py ├── gcnet │ ├── README.md │ ├── gcnet_r101-d8_512x1024_40k_cityscapes.py │ ├── gcnet_r101-d8_512x1024_80k_cityscapes.py │ ├── gcnet_r101-d8_512x512_160k_ade20k.py │ ├── gcnet_r101-d8_512x512_20k_voc12aug.py │ ├── gcnet_r101-d8_512x512_40k_voc12aug.py │ ├── gcnet_r101-d8_512x512_80k_ade20k.py │ ├── gcnet_r101-d8_769x769_40k_cityscapes.py │ ├── gcnet_r101-d8_769x769_80k_cityscapes.py │ ├── gcnet_r50-d8_512x1024_40k_cityscapes.py │ ├── gcnet_r50-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.py │ ├── gcnet_r50-d8_769x769_40k_cityscapes.py │ └── gcnet_r50-d8_769x769_80k_cityscapes.py ├── hrnet │ ├── README.md │ ├── fcn_hr18_480x480_40k_pascal_context.py │ ├── fcn_hr18_480x480_80k_pascal_context.py │ ├── fcn_hr18_512x1024_160k_cityscapes.py │ ├── fcn_hr18_512x1024_40k_cityscapes.py │ ├── fcn_hr18_512x1024_80k_cityscapes.py │ ├── fcn_hr18_512x512_160k_ade20k.py │ ├── fcn_hr18_512x512_20k_voc12aug.py │ ├── fcn_hr18_512x512_40k_voc12aug.py │ ├── fcn_hr18_512x512_80k_ade20k.py │ ├── fcn_hr18s_480x480_40k_pascal_context.py │ ├── fcn_hr18s_480x480_80k_pascal_context.py │ ├── fcn_hr18s_512x1024_160k_cityscapes.py │ ├── fcn_hr18s_512x1024_40k_cityscapes.py │ ├── fcn_hr18s_512x1024_80k_cityscapes.py │ ├── fcn_hr18s_512x512_160k_ade20k.py │ ├── fcn_hr18s_512x512_20k_voc12aug.py │ ├── fcn_hr18s_512x512_40k_voc12aug.py │ ├── fcn_hr18s_512x512_80k_ade20k.py │ ├── fcn_hr48_480x480_40k_pascal_context.py │ ├── fcn_hr48_480x480_80k_pascal_context.py │ ├── fcn_hr48_512x1024_160k_cityscapes.py │ ├── fcn_hr48_512x1024_40k_cityscapes.py │ ├── fcn_hr48_512x1024_80k_cityscapes.py │ ├── fcn_hr48_512x512_160k_ade20k.py │ ├── fcn_hr48_512x512_20k_voc12aug.py │ ├── fcn_hr48_512x512_40k_voc12aug.py │ └── fcn_hr48_512x512_80k_ade20k.py ├── mobilenet_v2 │ ├── README.md │ ├── deeplabv3_m-v2-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3_m-v2-d8_512x512_160k_ade20k.py │ ├── deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_m-v2-d8_512x512_160k_ade20k.py │ ├── fcn_m-v2-d8_512x1024_80k_cityscapes.py │ ├── fcn_m-v2-d8_512x512_160k_ade20k.py │ ├── pspnet_m-v2-d8_512x1024_80k_cityscapes.py │ └── pspnet_m-v2-d8_512x512_160k_ade20k.py ├── mobilenet_v3 │ ├── README.md │ ├── lraspp_m-v3-d8_512x1024_320k_cityscapes.py │ ├── lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py │ ├── lraspp_m-v3s-d8_512x1024_320k_cityscapes.py │ └── lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py ├── nonlocal_net │ ├── README.md │ ├── nonlocal_r101-d8_512x1024_40k_cityscapes.py │ ├── nonlocal_r101-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.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_20k_voc12aug.py │ ├── nonlocal_r50-d8_512x512_40k_voc12aug.py │ ├── nonlocal_r50-d8_512x512_80k_ade20k.py │ ├── nonlocal_r50-d8_769x769_40k_cityscapes.py │ └── nonlocal_r50-d8_769x769_80k_cityscapes.py ├── ocrnet │ ├── README.md │ ├── ocrnet_hr18_512x1024_160k_cityscapes.py │ ├── ocrnet_hr18_512x1024_40k_cityscapes.py │ ├── ocrnet_hr18_512x1024_80k_cityscapes.py │ ├── ocrnet_hr18_512x512_160k_ade20k.py │ ├── ocrnet_hr18_512x512_20k_voc12aug.py │ ├── ocrnet_hr18_512x512_40k_voc12aug.py │ ├── ocrnet_hr18_512x512_80k_ade20k.py │ ├── ocrnet_hr18s_512x1024_160k_cityscapes.py │ ├── ocrnet_hr18s_512x1024_40k_cityscapes.py │ ├── ocrnet_hr18s_512x1024_80k_cityscapes.py │ ├── ocrnet_hr18s_512x512_160k_ade20k.py │ ├── ocrnet_hr18s_512x512_20k_voc12aug.py │ ├── ocrnet_hr18s_512x512_40k_voc12aug.py │ ├── ocrnet_hr18s_512x512_80k_ade20k.py │ ├── ocrnet_hr48_512x1024_160k_cityscapes.py │ ├── ocrnet_hr48_512x1024_40k_cityscapes.py │ ├── ocrnet_hr48_512x1024_80k_cityscapes.py │ ├── ocrnet_hr48_512x512_160k_ade20k.py │ ├── ocrnet_hr48_512x512_20k_voc12aug.py │ ├── ocrnet_hr48_512x512_40k_voc12aug.py │ ├── ocrnet_hr48_512x512_80k_ade20k.py │ ├── ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py │ ├── ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py │ └── ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py ├── point_rend │ ├── README.md │ ├── pointrend_r101_512x1024_80k_cityscapes.py │ ├── pointrend_r101_512x512_160k_ade20k.py │ ├── pointrend_r50_512x1024_80k_cityscapes.py │ └── pointrend_r50_512x512_160k_ade20k.py ├── psanet │ ├── README.md │ ├── psanet_r101-d8_512x1024_40k_cityscapes.py │ ├── psanet_r101-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.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_160k_ade20k.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_769x769_40k_cityscapes.py │ └── psanet_r50-d8_769x769_80k_cityscapes.py ├── pspnet │ ├── README.md │ ├── pspnet_r101-d8_480x480_40k_pascal_context.py │ ├── pspnet_r101-d8_480x480_80k_pascal_context.py │ ├── pspnet_r101-d8_512x1024_40k_cityscapes.py │ ├── pspnet_r101-d8_512x1024_80k_cityscapes.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_512x512_80k_ade20k.py │ ├── pspnet_r101-d8_769x769_40k_cityscapes.py │ ├── pspnet_r101-d8_769x769_80k_cityscapes.py │ ├── pspnet_r101b-d8_512x1024_80k_cityscapes.py │ ├── pspnet_r101b-d8_769x769_80k_cityscapes.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 │ ├── pspnet_r50-d8_480x480_40k_pascal_context.py │ ├── pspnet_r50-d8_480x480_80k_pascal_context.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_20k_voc12aug.py │ ├── pspnet_r50-d8_512x512_40k_voc12aug.py │ ├── pspnet_r50-d8_512x512_80k_ade20k.py │ ├── pspnet_r50-d8_769x769_40k_cityscapes.py │ ├── pspnet_r50-d8_769x769_80k_cityscapes.py │ ├── pspnet_r50b-d8_512x1024_80k_cityscapes.py │ └── pspnet_r50b-d8_769x769_80k_cityscapes.py ├── resnest │ ├── README.md │ ├── deeplabv3_s101-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3_s101-d8_512x512_160k_ade20k.py │ ├── deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py │ ├── deeplabv3plus_s101-d8_512x512_160k_ade20k.py │ ├── fcn_s101-d8_512x1024_80k_cityscapes.py │ ├── fcn_s101-d8_512x512_160k_ade20k.py │ ├── pspnet_s101-d8_512x1024_80k_cityscapes.py │ └── pspnet_s101-d8_512x512_160k_ade20k.py ├── sem_fpn │ ├── README.md │ ├── fpn_r101_512x512_80k_ade20k.py │ ├── fpn_r18_512x512_80k_ade20k.py │ ├── fpn_r50_512x512_80k_ade20k.py │ ├── fpn_x101324d_512x512_80k_ade20k.py │ └── fpn_x101644d_512x512_80k_ade20k.py ├── unet │ ├── README.md │ ├── deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py │ ├── deeplabv3_unet_s5-d16_128x128_40k_stare.py │ ├── deeplabv3_unet_s5-d16_256x256_40k_hrf.py │ ├── deeplabv3_unet_s5-d16_64x64_40k_drive.py │ ├── fcn_unet_s5-d16_128x128_40k_chase_db1.py │ ├── fcn_unet_s5-d16_128x128_40k_stare.py │ ├── fcn_unet_s5-d16_256x256_40k_hrf.py │ ├── fcn_unet_s5-d16_64x64_40k_drive.py │ ├── pspnet_unet_s5-d16_128x128_40k_chase_db1.py │ ├── pspnet_unet_s5-d16_128x128_40k_stare.py │ ├── pspnet_unet_s5-d16_256x256_40k_hrf.py │ └── pspnet_unet_s5-d16_64x64_40k_drive.py └── upernet │ ├── README.md │ ├── upernet_r101_512x1024_40k_cityscapes.py │ ├── upernet_r101_512x1024_80k_cityscapes.py │ ├── upernet_r101_512x512_160k_ade20k.py │ ├── upernet_r101_512x512_20k_voc12aug.py │ ├── upernet_r101_512x512_40k_voc12aug.py │ ├── upernet_r101_512x512_80k_ade20k.py │ ├── upernet_r101_769x769_40k_cityscapes.py │ ├── upernet_r101_769x769_80k_cityscapes.py │ ├── upernet_r50_512x1024_40k_cityscapes.py │ ├── upernet_r50_512x1024_80k_cityscapes.py │ ├── upernet_r50_512x512_160k_ade20k.py │ ├── upernet_r50_512x512_20k_voc12aug.py │ ├── upernet_r50_512x512_40k_voc12aug.py │ ├── upernet_r50_512x512_80k_ade20k.py │ ├── upernet_r50_769x769_40k_cityscapes.py │ └── upernet_r50_769x769_80k_cityscapes.py ├── demo ├── demo.png └── image_demo.py ├── docker └── Dockerfile ├── docs ├── Makefile ├── api.rst ├── changelog.md ├── conf.py ├── dataset_prepare.md ├── get_started.md ├── index.rst ├── inference.md ├── make.bat ├── model_zoo.md ├── stat.py ├── train.md ├── tutorials │ ├── config.md │ ├── customize_datasets.md │ ├── customize_models.md │ ├── customize_runtime.md │ ├── data_pipeline.md │ ├── index.rst │ └── training_tricks.md └── useful_tools.md ├── local_configs ├── _base_ │ ├── datasets │ │ ├── ade20k.py │ │ ├── ade20k_repeat.py │ │ ├── chase_db1.py │ │ ├── cityscapes.py │ │ ├── cityscapes_1024x1024_repeat.py │ │ ├── cityscapes_768x768_repeat.py │ │ ├── cityscapes_repeat.py │ │ ├── drive.py │ │ ├── hrf.py │ │ ├── mapillary_1024x1024_repeat.py │ │ ├── mapillary_768x768_repeat.py │ │ ├── pascal_context.py │ │ ├── pascal_voc12.py │ │ ├── pascal_voc12_aug.py │ │ └── stare.py │ ├── default_runtime.py │ ├── models │ │ ├── ann_r50-d8.py │ │ ├── apcnet_r50-d8.py │ │ ├── ccnet_r50-d8.py │ │ ├── cgnet.py │ │ ├── danet_r50-d8.py │ │ ├── deeplabv3_r50-d8.py │ │ ├── deeplabv3_unet_s5-d16.py │ │ ├── deeplabv3plus_r50-d8.py │ │ ├── dmnet_r50-d8.py │ │ ├── dnl_r50-d8.py │ │ ├── emanet_r50-d8.py │ │ ├── encnet_r50-d8.py │ │ ├── fast_scnn.py │ │ ├── fcn_hr18.py │ │ ├── fcn_r50-d8.py │ │ ├── fcn_unet_s5-d16.py │ │ ├── fpn_r50.py │ │ ├── gcnet_r50-d8.py │ │ ├── lraspp_m-v3-d8.py │ │ ├── nonlocal_r50-d8.py │ │ ├── ocrnet_hr18.py │ │ ├── ocrnet_r50-d8.py │ │ ├── pointrend_r50.py │ │ ├── psanet_r50-d8.py │ │ ├── pspnet_r50-d8.py │ │ ├── pspnet_unet_s5-d16.py │ │ ├── segformer.py │ │ └── upernet_r50.py │ └── schedules │ │ ├── schedule_160k.py │ │ ├── schedule_160k_adamw.py │ │ ├── schedule_20k.py │ │ ├── schedule_40k.py │ │ ├── schedule_40k_adamw.py │ │ ├── schedule_80k.py │ │ └── schedule_80k_adamw.py ├── lvt │ └── segformer.lvt.512x512.ade.160k.py └── segformer │ ├── B0 │ ├── segformer.b0.1024x1024.city.160k.py │ ├── segformer.b0.1024x1024.city.160k_210917_408.py │ ├── segformer.b0.512x1024.city.160k.py │ ├── segformer.b0.512x512.ade.160k.py │ ├── segformer.b0.640x1280.city.160k.py │ └── segformer.b0.768x768.city.160k.py │ ├── B1 │ ├── segformer.b1.1024x1024.city.160k.py │ └── segformer.b1.512x512.ade.160k.py │ ├── B2 │ ├── segformer.b2.1024x1024.city.160k.py │ └── segformer.b2.512x512.ade.160k.py │ ├── B3 │ ├── segformer.b3.1024x1024.city.160k.py │ └── segformer.b3.512x512.ade.160k.py │ ├── B4 │ ├── segformer.b4.1024x1024.city.160k.py │ └── segformer.b4.512x512.ade.160k.py │ └── B5 │ ├── segformer.b5.1024x1024.city.160k.py │ └── segformer.b5.640x640.ade.160k.py ├── mmseg ├── __init__.py ├── apis │ ├── __init__.py │ ├── inference.py │ ├── test.py │ └── train.py ├── core │ ├── __init__.py │ ├── evaluation │ │ ├── __init__.py │ │ ├── class_names.py │ │ ├── eval_hooks.py │ │ └── metrics.py │ ├── seg │ │ ├── __init__.py │ │ ├── builder.py │ │ └── sampler │ │ │ ├── __init__.py │ │ │ ├── base_pixel_sampler.py │ │ │ └── ohem_pixel_sampler.py │ └── utils │ │ ├── __init__.py │ │ └── misc.py ├── datasets │ ├── __init__.py │ ├── ade.py │ ├── builder.py │ ├── chase_db1.py │ ├── cityscapes.py │ ├── cocostuff.py │ ├── custom.py │ ├── dataset_wrappers.py │ ├── drive.py │ ├── hrf.py │ ├── mapillary.py │ ├── pascal_context.py │ ├── pipelines │ │ ├── __init__.py │ │ ├── compose.py │ │ ├── formating.py │ │ ├── loading.py │ │ ├── test_time_aug.py │ │ └── transforms.py │ ├── stare.py │ └── voc.py ├── models │ ├── __init__.py │ ├── backbones │ │ ├── __init__.py │ │ ├── cgnet.py │ │ ├── fast_scnn.py │ │ ├── hrnet.py │ │ ├── lvt.py │ │ ├── mix_transformer.py │ │ ├── mobilenet_v2.py │ │ ├── mobilenet_v3.py │ │ ├── resnest.py │ │ ├── resnet.py │ │ ├── resnext.py │ │ └── unet.py │ ├── builder.py │ ├── decode_heads │ │ ├── __init__.py │ │ ├── ann_head.py │ │ ├── apc_head.py │ │ ├── aspp_head.py │ │ ├── cascade_decode_head.py │ │ ├── cc_head.py │ │ ├── da_head.py │ │ ├── decode_head.py │ │ ├── dm_head.py │ │ ├── dnl_head.py │ │ ├── ema_head.py │ │ ├── enc_head.py │ │ ├── fcn_head.py │ │ ├── fpn_head.py │ │ ├── gc_head.py │ │ ├── lraspp_head.py │ │ ├── nl_head.py │ │ ├── ocr_head.py │ │ ├── point_head.py │ │ ├── psa_head.py │ │ ├── psp_head.py │ │ ├── segformer_head.py │ │ ├── sep_aspp_head.py │ │ ├── sep_fcn_head.py │ │ └── uper_head.py │ ├── dynamic_conv.py │ ├── losses │ │ ├── __init__.py │ │ ├── accuracy.py │ │ ├── cross_entropy_loss.py │ │ ├── lovasz_loss.py │ │ └── utils.py │ ├── necks │ │ ├── __init__.py │ │ └── fpn.py │ ├── segmentors │ │ ├── __init__.py │ │ ├── base.py │ │ ├── cascade_encoder_decoder.py │ │ └── encoder_decoder.py │ └── utils │ │ ├── __init__.py │ │ ├── drop.py │ │ ├── inverted_residual.py │ │ ├── make_divisible.py │ │ ├── norm.py │ │ ├── res_layer.py │ │ ├── se_layer.py │ │ ├── self_attention_block.py │ │ └── up_conv_block.py ├── ops │ ├── __init__.py │ ├── encoding.py │ └── wrappers.py ├── utils │ ├── __init__.py │ ├── collect_env.py │ └── logger.py └── version.py ├── pytest.ini ├── requirements.txt ├── requirements ├── docs.txt ├── optional.txt ├── readthedocs.txt ├── runtime.txt └── tests.txt ├── resources ├── image.png ├── mmseg-logo.png └── seg_demo.gif ├── setup.cfg ├── setup.py ├── tests ├── test_config.py ├── test_data │ ├── test_dataset.py │ ├── test_dataset_builder.py │ ├── test_loading.py │ ├── test_transform.py │ └── test_tta.py ├── test_eval_hook.py ├── test_inference.py ├── test_metrics.py ├── test_models │ ├── test_backbone.py │ ├── test_forward.py │ ├── test_heads.py │ ├── test_losses.py │ ├── test_necks.py │ ├── test_segmentor.py │ └── test_unet.py ├── test_sampler.py └── test_utils │ ├── test_inverted_residual_module.py │ ├── test_make_divisible.py │ └── test_se_layer.py └── tools ├── benchmark.py ├── convert_datasets ├── chase_db1.py ├── cityscapes.py ├── drive.py ├── hrf.py ├── pascal_context.py ├── stare.py └── voc_aug.py ├── convert_model.py ├── dist_test.sh ├── dist_train.sh ├── get_flops.py ├── print_config.py ├── publish_model.py ├── pytorch2onnx.py ├── slurm_test.sh ├── slurm_train.sh ├── test.py └── train.py /Images/lvt.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/Images/lvt.png -------------------------------------------------------------------------------- /classification/.gitignore: -------------------------------------------------------------------------------- 1 | configs/.ipynb_checkpoints/ 2 | *.pyc 3 | models/.ipynb_checkpoints/ 4 | *.csv 5 | work_dirs/ 6 | .ipynb_checkpoints 7 | work_dirs_debug 8 | *.ipynb 9 | checkpoints 10 | -------------------------------------------------------------------------------- /classification/Images/lvt.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/classification/Images/lvt.png -------------------------------------------------------------------------------- /classification/README.md: -------------------------------------------------------------------------------- 1 | ../README.md -------------------------------------------------------------------------------- /classification/configs/lvt_imagenet.py: -------------------------------------------------------------------------------- 1 | config = dict( 2 | # classification/downstream tasks 3 | with_cls_head = True, 4 | 5 | # rasa setting 6 | rasa_cfg = dict( 7 | atrous_rates= [1,3,5], # None, [1,3,5] 8 | act_layer= 'nn.SiLU(True)', 9 | init= 'kaiming', 10 | r_num = 2, 11 | ), 12 | ) 13 | -------------------------------------------------------------------------------- /classification/distributed_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | NUM_PROC=$1 3 | shift 4 | python3 -m torch.distributed.launch --nproc_per_node=$NUM_PROC main.py "$@" 5 | 6 | -------------------------------------------------------------------------------- /classification/figures/compare.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/classification/figures/compare.png -------------------------------------------------------------------------------- /classification/figures/outlook-attention-gif.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/classification/figures/outlook-attention-gif.gif -------------------------------------------------------------------------------- /classification/loss/__init__.py: -------------------------------------------------------------------------------- 1 | from .cross_entropy import TokenLabelGTCrossEntropy, TokenLabelSoftTargetCrossEntropy, TokenLabelCrossEntropy -------------------------------------------------------------------------------- /classification/models/__init__.py: -------------------------------------------------------------------------------- 1 | from .lvt_cls import * 2 | from .lvt import * -------------------------------------------------------------------------------- /classification/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .utils import load_pretrained_weights -------------------------------------------------------------------------------- /detection/.dev_scripts/linter.sh: -------------------------------------------------------------------------------- 1 | yapf -r -i mmdet/ configs/ tests/ tools/ 2 | isort -rc mmdet/ configs/ tests/ tools/ 3 | flake8 . 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/.readthedocs.yml: -------------------------------------------------------------------------------- 1 | version: 2 2 | 3 | formats: all 4 | 5 | python: 6 | version: 3.7 7 | install: 8 | - requirements: requirements/docs.txt 9 | - requirements: requirements/readthedocs.txt 10 | -------------------------------------------------------------------------------- /detection/CITATION.cff: -------------------------------------------------------------------------------- 1 | cff-version: 1.2.0 2 | message: "If you use this software, please cite it as below." 3 | authors: 4 | - name: "MMDetection Contributors" 5 | title: "OpenMMLab Detection Toolbox and Benchmark" 6 | date-released: 2018-08-22 7 | url: "https://github.com/open-mmlab/mmdetection" 8 | license: Apache-2.0 9 | -------------------------------------------------------------------------------- /detection/MANIFEST.in: -------------------------------------------------------------------------------- 1 | include requirements/*.txt 2 | include mmdet/VERSION 3 | include mmdet/.mim/model-index.yml 4 | include mmdet/.mim/demo/*/* 5 | recursive-include mmdet/.mim/configs *.py *.yml 6 | recursive-include mmdet/.mim/tools *.sh *.py 7 | -------------------------------------------------------------------------------- /detection/README.md: -------------------------------------------------------------------------------- 1 | ../README.md -------------------------------------------------------------------------------- /detection/configs/atss/atss_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './atss_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_caffe_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_caffe_fpn_mstrain_3x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/cascade_rcnn/cascade_mask_rcnn_r101_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../common/mstrain_3x_coco_instance.py', 3 | '../_base_/models/cascade_mask_rcnn_r50_fpn.py' 4 | ] 5 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/cascade_rcnn/cascade_rcnn_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_rcnn_r50_fpn_20e_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/centernet/centernet_resnet18_140e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './centernet_resnet18_dcnv2_140e_coco.py' 2 | 3 | model = dict(neck=dict(use_dcn=False)) 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/deformable_detr/deformable_detr_refine_r50_16x2_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'deformable_detr_r50_16x2_50e_coco.py' 2 | model = dict(bbox_head=dict(with_box_refine=True)) 3 | -------------------------------------------------------------------------------- /detection/configs/deformable_detr/deformable_detr_twostage_refine_r50_16x2_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'deformable_detr_refine_r50_16x2_50e_coco.py' 2 | model = dict(bbox_head=dict(as_two_stage=True)) 3 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/fast_rcnn/README.md: -------------------------------------------------------------------------------- 1 | # Fast R-CNN 2 | 3 | ## Introduction 4 | 5 | 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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/fast_rcnn/fast_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/fast_rcnn/fast_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fast_rcnn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/faster_rcnn/faster_rcnn_r101_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'faster_rcnn_r50_fpn_mstrain_3x_coco.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/faster_rcnn/faster_rcnn_r50_fpn_ciou_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='CIoULoss', loss_weight=12.0)))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/faster_rcnn/faster_rcnn_r50_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../common/mstrain_3x_coco.py', '../_base_/models/faster_rcnn_r50_fpn.py' 3 | ] 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/foveabox/fovea_r101_fpn_4x4_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fovea_r50_fpn_4x4_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/foveabox/fovea_r101_fpn_4x4_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fovea_r50_fpn_4x4_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/fp16/mask_rcnn_r50_fpn_fp16_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 | 7 | fp16 = dict(loss_scale=512.) 8 | -------------------------------------------------------------------------------- /detection/configs/fp16/mask_rcnn_r50_fpn_fp16_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 | 7 | fp16 = dict(loss_scale=512.) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/fsaf/fsaf_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './fsaf_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/gcnet/cascade_mask_rcnn_x101_32x4d_fpn_syncbn-backbone_dconv_c3-c5_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = '../dcn/cascade_mask_rcnn_x101_32x4d_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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/ghm/retinanet_ghm_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_ghm_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://jhu/resnet101_gn_ws'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://jhu/resnet101_gn_ws'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron/resnet101_gn'))) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict( 7 | type='Pretrained', 8 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 9 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/htc/htc_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './htc_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | # learning policy 8 | lr_config = dict(step=[16, 19]) 9 | runner = dict(type='EpochBasedRunner', max_epochs=20) 10 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /detection/configs/instaboost/mask_rcnn_r101_fpn_instaboost_4x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_instaboost_4x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/mask_rcnn/mask_rcnn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/mask_rcnn/mask_rcnn_r101_fpn_mstrain-poly_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../common/mstrain-poly_3x_coco_instance.py', 3 | '../_base_/models/mask_rcnn_r50_fpn.py' 4 | ] 5 | 6 | model = dict( 7 | backbone=dict( 8 | depth=101, 9 | init_cfg=dict(type='Pretrained', 10 | checkpoint='torchvision://resnet101'))) 11 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/mask_rcnn/mask_rcnn_r50_fpn_mstrain-poly_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../common/mstrain-poly_3x_coco_instance.py', 3 | '../_base_/models/mask_rcnn_r50_fpn.py' 4 | ] 5 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/paa/paa_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/paa/paa_r101_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './paa_r50_fpn_mstrain_3x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/panoptic_fpn/panoptic_fpn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './panoptic_fpn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/panoptic_fpn/panoptic_fpn_r101_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './panoptic_fpn_r50_fpn_mstrain_3x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvt-l_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvt-t_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | num_layers=[3, 8, 27, 3], 5 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 6 | 'releases/download/v2/pvt_large.pth'))) 7 | fp16 = dict(loss_scale=dict(init_scale=512)) 8 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvt-m_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvt-t_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | num_layers=[3, 4, 18, 3], 5 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 6 | 'releases/download/v2/pvt_medium.pth'))) 7 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvt-s_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvt-t_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | num_layers=[3, 4, 6, 3], 5 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 6 | 'releases/download/v2/pvt_small.pth'))) 7 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvtv2-b1_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvtv2-b0_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | embed_dims=64, 5 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 6 | 'releases/download/v2/pvt_v2_b1.pth')), 7 | neck=dict(in_channels=[64, 128, 320, 512])) 8 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvtv2-b2_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvtv2-b0_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | embed_dims=64, 5 | num_layers=[3, 4, 6, 3], 6 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 7 | 'releases/download/v2/pvt_v2_b2.pth')), 8 | neck=dict(in_channels=[64, 128, 320, 512])) 9 | -------------------------------------------------------------------------------- /detection/configs/pvt/retinanet_pvtv2-b3_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'retinanet_pvtv2-b0_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | embed_dims=64, 5 | num_layers=[3, 4, 18, 3], 6 | init_cfg=dict(checkpoint='https://github.com/whai362/PVT/' 7 | 'releases/download/v2/pvt_v2_b3.pth')), 8 | neck=dict(in_channels=[64, 128, 320, 512])) 9 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/reppoints/reppoints.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/configs/reppoints/reppoints.png -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | type='Res2Net', 5 | depth=101, 6 | scales=4, 7 | base_width=26, 8 | init_cfg=dict( 9 | type='Pretrained', 10 | checkpoint='open-mmlab://res2net101_v1d_26w_4s'))) 11 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | type='Res2Net', 5 | depth=101, 6 | scales=4, 7 | base_width=26, 8 | init_cfg=dict( 9 | type='Pretrained', 10 | checkpoint='open-mmlab://res2net101_v1d_26w_4s'))) 11 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | type='Res2Net', 5 | depth=101, 6 | scales=4, 7 | base_width=26, 8 | init_cfg=dict( 9 | type='Pretrained', 10 | checkpoint='open-mmlab://res2net101_v1d_26w_4s'))) 11 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | stem_channels=128, 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='open-mmlab://resnest101'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | stem_channels=128, 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='open-mmlab://resnest101'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | stem_channels=128, 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='open-mmlab://resnest101'))) 8 | -------------------------------------------------------------------------------- /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 | backbone=dict( 4 | stem_channels=128, 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='open-mmlab://resnest101'))) 8 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r101_caffe_fpn_mstrain_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_caffe_fpn_mstrain_1x_coco.py' 2 | # learning policy 3 | model = dict( 4 | pretrained='open-mmlab://detectron2/resnet101_caffe', 5 | backbone=dict(depth=101)) 6 | lr_config = dict(step=[28, 34]) 7 | runner = dict(type='EpochBasedRunner', max_epochs=36) 8 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r101_fpn_mstrain_640-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/retinanet_r50_fpn.py', '../common/mstrain_3x_coco.py' 3 | ] 4 | # optimizer 5 | model = dict(pretrained='torchvision://resnet101', backbone=dict(depth=101)) 6 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_r50_fpn_mstrain_640-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/retinanet_r50_fpn.py', '../common/mstrain_3x_coco.py' 3 | ] 4 | # optimizer 5 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001) 6 | -------------------------------------------------------------------------------- /detection/configs/retinanet/retinanet_x101_64x4d_fpn_mstrain_640-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/retinanet_r50_fpn.py', '../common/mstrain_3x_coco.py' 3 | ] 4 | # optimizer 5 | model = dict( 6 | pretrained='open-mmlab://resnext101_64x4d', 7 | backbone=dict(type='ResNeXt', depth=101, groups=64, base_width=4)) 8 | optimizer = dict(type='SGD', lr=0.01) 9 | -------------------------------------------------------------------------------- /detection/configs/rpn/rpn_r101_caffe_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_caffe_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', 7 | checkpoint='open-mmlab://detectron2/resnet101_caffe'))) 8 | -------------------------------------------------------------------------------- /detection/configs/rpn/rpn_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/rpn/rpn_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './rpn_r50_fpn_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/scnet/scnet_r101_fpn_20e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './scnet_r50_fpn_20e_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/cascade_mask_rcnn_r101_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py' # noqa: E501 2 | model = dict( 3 | roi_head=dict( 4 | mask_head=dict( 5 | predictor_cfg=dict(type='NormedConv2d', tempearture=20)))) 6 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/cascade_mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './cascade_mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py' # noqa: E501 2 | model = dict( 3 | roi_head=dict( 4 | mask_head=dict( 5 | predictor_cfg=dict(type='NormedConv2d', tempearture=20)))) 6 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r101_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r101_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py' # noqa: E501 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r101_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py' # noqa: E501 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r50_fpn_random_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_random_seesaw_loss_mstrain_2x_lvis_v1.py' 2 | model = dict( 3 | roi_head=dict( 4 | mask_head=dict( 5 | predictor_cfg=dict(type='NormedConv2d', tempearture=20)))) 6 | -------------------------------------------------------------------------------- /detection/configs/seesaw_loss/mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_normed_mask_mstrain_2x_lvis_v1.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_sample1e-3_seesaw_loss_mstrain_2x_lvis_v1.py' 2 | model = dict( 3 | roi_head=dict( 4 | mask_head=dict( 5 | predictor_cfg=dict(type='NormedConv2d', tempearture=20)))) 6 | -------------------------------------------------------------------------------- /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( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /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( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /detection/configs/strong_baselines/mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_fp16_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py' 2 | fp16 = dict(loss_scale=512.) 3 | -------------------------------------------------------------------------------- /detection/configs/strong_baselines/mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_400e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_caffe_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py' 2 | 3 | # Use RepeatDataset to speed up training 4 | # change repeat time from 4 (for 100 epochs) to 16 (for 400 epochs) 5 | data = dict(train=dict(times=4 * 4)) 6 | lr_config = dict(warmup_iters=500 * 4) 7 | -------------------------------------------------------------------------------- /detection/configs/strong_baselines/mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_fp16_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py' 2 | # use FP16 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /detection/configs/strong_baselines/mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_lsj_100e_coco.py' 2 | 3 | # Use RepeatDataset to speed up training 4 | # change repeat time from 4 (for 100 epochs) to 2 (for 50 epochs) 5 | data = dict(train=dict(times=2)) 6 | -------------------------------------------------------------------------------- /detection/configs/swin/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco.py' 2 | # you need to set mode='dynamic' if you are using pytorch<=1.5.0 3 | fp16 = dict(loss_scale=dict(init_scale=512)) 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/vfnet/vfnet_r101_fpn_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /detection/configs/vfnet/vfnet_r101_fpn_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_1x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | lr_config = dict(step=[16, 22]) 8 | runner = dict(type='EpochBasedRunner', max_epochs=24) 9 | -------------------------------------------------------------------------------- /detection/configs/vfnet/vfnet_r101_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './vfnet_r50_fpn_mstrain_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict(type='Pretrained', 6 | checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/configs/yolact/yolact_r101_1x8_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolact_r50_1x8_coco.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /detection/configs/yolo/yolov3_d53_fp16_mstrain-608_273e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolov3_d53_mstrain-608_273e_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale='dynamic') 4 | -------------------------------------------------------------------------------- /detection/configs/yolox/yolox_l_8x8_300e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolox_s_8x8_300e_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict(deepen_factor=1.0, widen_factor=1.0), 6 | neck=dict( 7 | in_channels=[256, 512, 1024], out_channels=256, num_csp_blocks=3), 8 | bbox_head=dict(in_channels=256, feat_channels=256)) 9 | -------------------------------------------------------------------------------- /detection/configs/yolox/yolox_m_8x8_300e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolox_s_8x8_300e_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict(deepen_factor=0.67, widen_factor=0.75), 6 | neck=dict(in_channels=[192, 384, 768], out_channels=192, num_csp_blocks=2), 7 | bbox_head=dict(in_channels=192, feat_channels=192), 8 | ) 9 | -------------------------------------------------------------------------------- /detection/configs/yolox/yolox_x_8x8_300e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './yolox_s_8x8_300e_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict(deepen_factor=1.33, widen_factor=1.25), 6 | neck=dict( 7 | in_channels=[320, 640, 1280], out_channels=320, num_csp_blocks=4), 8 | bbox_head=dict(in_channels=320, feat_channels=320)) 9 | -------------------------------------------------------------------------------- /detection/demo/demo.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/demo/demo.jpg -------------------------------------------------------------------------------- /detection/demo/demo.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/demo/demo.mp4 -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/docs/_static/css/readthedocs.css: -------------------------------------------------------------------------------- 1 | .header-logo { 2 | background-image: url("../image/mmdet-logo.png"); 3 | background-size: 156px 40px; 4 | height: 40px; 5 | width: 156px; 6 | } 7 | -------------------------------------------------------------------------------- /detection/docs/_static/image/mmdet-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/docs/_static/image/mmdet-logo.png -------------------------------------------------------------------------------- /detection/docs/switch_language.md: -------------------------------------------------------------------------------- 1 | ## English 2 | 3 | ## 简体中文 4 | -------------------------------------------------------------------------------- /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 | robustness_benchmarking.md 12 | pytorch2onnx.md 13 | onnx2tensorrt.md 14 | init_cfg.md 15 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/_static/css/readthedocs.css: -------------------------------------------------------------------------------- 1 | .header-logo { 2 | background-image: url("../image/mmdet-logo.png"); 3 | background-size: 156px 40px; 4 | height: 40px; 5 | width: 156px; 6 | } 7 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/_static/image/mmdet-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/docs_zh-CN/_static/image/mmdet-logo.png -------------------------------------------------------------------------------- /detection/docs_zh-CN/robustness_benchmarking.md: -------------------------------------------------------------------------------- 1 | # 检测器鲁棒性检查 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/switch_language.md: -------------------------------------------------------------------------------- 1 | ## English 2 | 3 | ## 简体中文 4 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/tutorials/customize_models.md: -------------------------------------------------------------------------------- 1 | # 教程 4: 自定义模型 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/tutorials/customize_runtime.md: -------------------------------------------------------------------------------- 1 | # 教程 5: 自定义训练配置 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/tutorials/finetune.md: -------------------------------------------------------------------------------- 1 | # 教程 7: 模型微调 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/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 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/tutorials/onnx2tensorrt.md: -------------------------------------------------------------------------------- 1 | # 教程 9: ONNX 到 TensorRT 的模型转换（实验性支持） 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/tutorials/pytorch2onnx.md: -------------------------------------------------------------------------------- 1 | # 教程 8: Pytorch 到 ONNX 的模型转换（实验性支持） 2 | -------------------------------------------------------------------------------- /detection/docs_zh-CN/useful_tools.md: -------------------------------------------------------------------------------- 1 | ## 日志分析 2 | -------------------------------------------------------------------------------- /detection/lvt.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/lvt.png -------------------------------------------------------------------------------- /detection/mmdet/core/bbox/iou_calculators/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .builder import build_iou_calculator 3 | from .iou2d_calculator import BboxOverlaps2D, bbox_overlaps 4 | 5 | __all__ = ['build_iou_calculator', 'BboxOverlaps2D', 'bbox_overlaps'] 6 | -------------------------------------------------------------------------------- /detection/mmdet/core/bbox/iou_calculators/builder.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from mmcv.utils import Registry, build_from_cfg 3 | 4 | IOU_CALCULATORS = Registry('IoU calculator') 5 | 6 | 7 | def build_iou_calculator(cfg, default_args=None): 8 | """Builder of IoU calculator.""" 9 | return build_from_cfg(cfg, IOU_CALCULATORS, default_args) 10 | -------------------------------------------------------------------------------- /detection/mmdet/core/bbox/match_costs/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .builder import build_match_cost 3 | from .match_cost import BBoxL1Cost, ClassificationCost, FocalLossCost, IoUCost 4 | 5 | __all__ = [ 6 | 'build_match_cost', 'ClassificationCost', 'BBoxL1Cost', 'IoUCost', 7 | 'FocalLossCost' 8 | ] 9 | -------------------------------------------------------------------------------- /detection/mmdet/core/bbox/match_costs/builder.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from mmcv.utils import Registry, build_from_cfg 3 | 4 | MATCH_COST = Registry('Match Cost') 5 | 6 | 7 | def build_match_cost(cfg, default_args=None): 8 | """Builder of IoU calculator.""" 9 | return build_from_cfg(cfg, MATCH_COST, default_args) 10 | -------------------------------------------------------------------------------- /detection/mmdet/core/data_structures/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .general_data import GeneralData 3 | from .instance_data import InstanceData 4 | 5 | __all__ = ['GeneralData', 'InstanceData'] 6 | -------------------------------------------------------------------------------- /detection/mmdet/core/visualization/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .image import (color_val_matplotlib, imshow_det_bboxes, 3 | imshow_gt_det_bboxes) 4 | 5 | __all__ = ['imshow_det_bboxes', 'imshow_gt_det_bboxes', 'color_val_matplotlib'] 6 | -------------------------------------------------------------------------------- /detection/mmdet/datasets/api_wrappers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .coco_api import COCO, COCOeval 3 | 4 | __all__ = ['COCO', 'COCOeval'] 5 | -------------------------------------------------------------------------------- /detection/mmdet/datasets/samplers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .distributed_sampler import DistributedSampler 3 | from .group_sampler import DistributedGroupSampler, GroupSampler 4 | 5 | __all__ = ['DistributedSampler', 'DistributedGroupSampler', 'GroupSampler'] 6 | -------------------------------------------------------------------------------- /detection/mmdet/models/detectors/deformable_detr.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from ..builder import DETECTORS 3 | from .detr import DETR 4 | 5 | 6 | @DETECTORS.register_module() 7 | class DeformableDETR(DETR): 8 | 9 | def __init__(self, *args, **kwargs): 10 | super(DETR, self).__init__(*args, **kwargs) 11 | -------------------------------------------------------------------------------- /detection/mmdet/models/plugins/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .dropblock import DropBlock 3 | 4 | __all__ = ['DropBlock'] 5 | -------------------------------------------------------------------------------- /detection/mmdet/models/roi_heads/roi_extractors/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_roi_extractor import BaseRoIExtractor 3 | from .generic_roi_extractor import GenericRoIExtractor 4 | from .single_level_roi_extractor import SingleRoIExtractor 5 | 6 | __all__ = ['BaseRoIExtractor', 'SingleRoIExtractor', 'GenericRoIExtractor'] 7 | -------------------------------------------------------------------------------- /detection/mmdet/models/roi_heads/shared_heads/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .res_layer import ResLayer 3 | 4 | __all__ = ['ResLayer'] 5 | -------------------------------------------------------------------------------- /detection/mmdet/models/seg_heads/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .panoptic_fpn_head import PanopticFPNHead # noqa: F401,F403 3 | from .panoptic_fusion_heads import * # noqa: F401,F403 4 | -------------------------------------------------------------------------------- /detection/mmdet/models/seg_heads/panoptic_fusion_heads/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_panoptic_fusion_head import \ 3 | BasePanopticFusionHead # noqa: F401,F403 4 | from .heuristic_fusion_head import HeuristicFusionHead # noqa: F401,F403 5 | -------------------------------------------------------------------------------- /detection/mmdet/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .collect_env import collect_env 3 | from .logger import get_root_logger 4 | 5 | __all__ = ['get_root_logger', 'collect_env'] 6 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /detection/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/build.txt 2 | -r requirements/optional.txt 3 | -r requirements/runtime.txt 4 | -r requirements/tests.txt 5 | -------------------------------------------------------------------------------- /detection/requirements/build.txt: -------------------------------------------------------------------------------- 1 | # These must be installed before building mmdetection 2 | cython 3 | numpy 4 | -------------------------------------------------------------------------------- /detection/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | docutils==0.16.0 2 | -e git+https://github.com/open-mmlab/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme 3 | recommonmark 4 | sphinx==4.0.2 5 | sphinx-copybutton 6 | sphinx_markdown_tables 7 | sphinx_rtd_theme==0.5.2 8 | -------------------------------------------------------------------------------- /detection/requirements/mminstall.txt: -------------------------------------------------------------------------------- 1 | mmcv-full>=1.3.8 2 | -------------------------------------------------------------------------------- /detection/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | cityscapesscripts 2 | imagecorruptions 3 | scipy 4 | sklearn 5 | -------------------------------------------------------------------------------- /detection/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | torch 3 | torchvision 4 | -------------------------------------------------------------------------------- /detection/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | numpy 3 | pycocotools; platform_system == "Linux" 4 | pycocotools-windows; platform_system == "Windows" 5 | six 6 | terminaltables 7 | -------------------------------------------------------------------------------- /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 | mmtrack 9 | onnx==1.7.0 10 | onnxruntime>=1.8.0 11 | pytest 12 | ubelt 13 | xdoctest>=0.10.0 14 | yapf 15 | -------------------------------------------------------------------------------- /detection/resources/coco_test_12510.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/coco_test_12510.jpg -------------------------------------------------------------------------------- /detection/resources/corruptions_sev_3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/corruptions_sev_3.png -------------------------------------------------------------------------------- /detection/resources/data_pipeline.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/data_pipeline.png -------------------------------------------------------------------------------- /detection/resources/loss_curve.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/loss_curve.png -------------------------------------------------------------------------------- /detection/resources/mmdet-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/mmdet-logo.png -------------------------------------------------------------------------------- /detection/resources/qq_group_qrcode.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/qq_group_qrcode.jpg -------------------------------------------------------------------------------- /detection/resources/zhihu_qrcode.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/detection/resources/zhihu_qrcode.jpg -------------------------------------------------------------------------------- /detection/tests/test_data/test_pipelines/test_transform/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .utils import check_result_same, construct_toy_data, create_random_bboxes 3 | 4 | __all__ = ['create_random_bboxes', 'construct_toy_data', 'check_result_same'] 5 | -------------------------------------------------------------------------------- /detection/tests/test_models/test_backbones/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .utils import check_norm_state, is_block, is_norm 3 | 4 | __all__ = ['is_block', 'is_norm', 'check_norm_state'] 5 | -------------------------------------------------------------------------------- /detection/tests/test_models/test_roi_heads/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .utils import _dummy_bbox_sampling 3 | 4 | __all__ = ['_dummy_bbox_sampling'] 5 | -------------------------------------------------------------------------------- /detection/tests/test_onnx/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .utils import ort_validate 3 | 4 | __all__ = ['ort_validate'] 5 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/Images/lvt.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/segmentation/Images/lvt.png -------------------------------------------------------------------------------- /segmentation/README.md: -------------------------------------------------------------------------------- 1 | ../README.md -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/configs/sem_fpn/fpn_r101_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /segmentation/configs/sem_fpn/fpn_r18_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet18_v1c', 3 | backbone=dict(depth=18), 4 | neck=dict(in_channels=[64, 128, 256, 512])) 5 | -------------------------------------------------------------------------------- /segmentation/configs/sem_fpn/fpn_x101324d_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnext101_32x4d', 3 | backbone=dict( 4 | type='ResNeXt', 5 | depth=101, 6 | groups=32, 7 | base_width=4)) 8 | -------------------------------------------------------------------------------- /segmentation/configs/sem_fpn/fpn_x101644d_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnext101_64x4d', 3 | backbone=dict( 4 | type='ResNeXt', 5 | depth=101, 6 | groups=64, 7 | base_width=4)) 8 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/demo/demo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/segmentation/demo/demo.png -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/local_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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/mmseg/core/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .misc import add_prefix 2 | 3 | __all__ = ['add_prefix'] 4 | -------------------------------------------------------------------------------- /segmentation/mmseg/models/necks/__init__.py: -------------------------------------------------------------------------------- 1 | from .fpn import FPN 2 | 3 | __all__ = ['FPN'] 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/mmseg/ops/__init__.py: -------------------------------------------------------------------------------- 1 | from .encoding import Encoding 2 | from .wrappers import Upsample, resize 3 | 4 | __all__ = ['Upsample', 'resize', 'Encoding'] 5 | -------------------------------------------------------------------------------- /segmentation/mmseg/utils/__init__.py: -------------------------------------------------------------------------------- 1 | from .collect_env import collect_env 2 | from .logger import get_root_logger, print_log 3 | 4 | __all__ = ['get_root_logger', 'collect_env', 'print_log'] 5 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/optional.txt 2 | -r requirements/runtime.txt 3 | -r requirements/tests.txt 4 | -------------------------------------------------------------------------------- /segmentation/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | recommonmark 2 | sphinx 3 | sphinx_markdown_tables 4 | sphinx_rtd_theme 5 | -------------------------------------------------------------------------------- /segmentation/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | cityscapesscripts 2 | -------------------------------------------------------------------------------- /segmentation/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | torch 3 | torchvision 4 | -------------------------------------------------------------------------------- /segmentation/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | numpy 3 | terminaltables 4 | -------------------------------------------------------------------------------- /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 | -------------------------------------------------------------------------------- /segmentation/resources/image.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/segmentation/resources/image.png -------------------------------------------------------------------------------- /segmentation/resources/mmseg-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/segmentation/resources/mmseg-logo.png -------------------------------------------------------------------------------- /segmentation/resources/seg_demo.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Chenglin-Yang/LVT/c56189777d31e75fbfdf60514ca755aa23a25aac/segmentation/resources/seg_demo.gif -------------------------------------------------------------------------------- /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} 10 | -------------------------------------------------------------------------------- /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} 10 | --------------------------------------------------------------------------------