├── .gitignore ├── README.md ├── cfgs ├── mlla_b.yaml ├── mlla_s.yaml └── mlla_t.yaml ├── config.py ├── data ├── __init__.py ├── build.py ├── cached_image_folder.py ├── samplers.py └── zipreader.py ├── downstream ├── detection │ ├── .circleci │ │ └── config.yml │ ├── .dev_scripts │ │ ├── batch_test_list.py │ │ ├── batch_train_list.txt │ │ ├── benchmark_filter.py │ │ ├── benchmark_inference_fps.py │ │ ├── benchmark_test_image.py │ │ ├── check_links.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 │ ├── .gitignore │ ├── .owners.yml │ ├── .pre-commit-config.yaml │ ├── .readthedocs.yml │ ├── CITATION.cff │ ├── LICENSE │ ├── MANIFEST.in │ ├── README.md │ ├── config.yml │ ├── configs │ │ ├── _base_ │ │ │ ├── datasets │ │ │ │ ├── cityscapes_detection.py │ │ │ │ ├── cityscapes_instance.py │ │ │ │ ├── coco_detection.py │ │ │ │ ├── coco_instance.py │ │ │ │ ├── coco_instance_semantic.py │ │ │ │ ├── coco_panoptic.py │ │ │ │ ├── deepfashion.py │ │ │ │ ├── lvis_v0.5_instance.py │ │ │ │ ├── lvis_v1_instance.py │ │ │ │ ├── openimages_detection.py │ │ │ │ ├── voc0712.py │ │ │ │ └── wider_face.py │ │ │ ├── default_runtime.py │ │ │ ├── models │ │ │ │ ├── cascade_mask_rcnn_r50_fpn.py │ │ │ │ ├── cascade_mask_rcnn_swin_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 │ │ │ │ ├── mask_rcnn_swin_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 │ │ │ └── metafile.yml │ │ ├── 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 │ │ │ └── metafile.yml │ │ ├── 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 │ │ │ ├── ssj_270k_coco_instance.py │ │ │ └── ssj_scp_270k_coco_instance.py │ │ ├── convnext │ │ │ ├── README.md │ │ │ ├── cascade_mask_rcnn_convnext-s_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco.py │ │ │ ├── cascade_mask_rcnn_convnext-t_p4_w7_fpn_giou_4conv1f_fp16_ms-crop_3x_coco.py │ │ │ ├── mask_rcnn_convnext-t_p4_w7_fpn_fp16_ms-crop_3x_coco.py │ │ │ └── metafile.yml │ │ ├── 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_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_fp16_dconv_c3-c5_1x_coco.py │ │ │ └── metafile.yml │ │ ├── dcnv2 │ │ │ ├── README.md │ │ │ ├── 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 │ │ │ ├── mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco.py │ │ │ └── metafile.yml │ │ ├── ddod │ │ │ ├── README.md │ │ │ ├── ddod_r50_fpn_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 │ │ ├── dyhead │ │ │ ├── README.md │ │ │ ├── atss_r50_caffe_fpn_dyhead_1x_coco.py │ │ │ ├── atss_r50_fpn_dyhead_1x_coco.py │ │ │ ├── atss_swin-l-p4-w12_fpn_dyhead_mstrain_2x_coco.py │ │ │ └── metafile.yml │ │ ├── dynamic_rcnn │ │ │ ├── README.md │ │ │ ├── dynamic_rcnn_r50_fpn_1x_coco.py │ │ │ └── metafile.yml │ │ ├── efficientnet │ │ │ ├── README.md │ │ │ ├── metafile.yml │ │ │ └── retinanet_effb3_fpn_crop896_8x4_1x_coco.py │ │ ├── empirical_attention │ │ │ ├── README.md │ │ │ ├── faster_rcnn_r50_fpn_attention_0010_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_attention_0010_dcn_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_attention_1111_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_attention_1111_dcn_1x_coco.py │ │ │ └── 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_c4_mstrain_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_90k_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_fp16_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_r50_fpn_tnr-pretrain_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 │ │ ├── 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 │ │ ├── lad │ │ │ ├── README.md │ │ │ ├── lad_r101_paa_r50_fpn_coco_1x.py │ │ │ ├── lad_r50_paa_r101_fpn_coco_1x.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 │ │ ├── mask2former │ │ │ ├── README.md │ │ │ ├── mask2former_r101_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_r101_lsj_8x2_50e_coco.py │ │ │ ├── mask2former_r50_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_r50_lsj_8x2_50e_coco.py │ │ │ ├── mask2former_swin-b-p4-w12-384-in21k_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_swin-b-p4-w12-384_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_swin-l-p4-w12-384-in21k_lsj_16x1_100e_coco-panoptic.py │ │ │ ├── mask2former_swin-s-p4-w7-224_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_swin-s-p4-w7-224_lsj_8x2_50e_coco.py │ │ │ ├── mask2former_swin-t-p4-w7-224_lsj_8x2_50e_coco-panoptic.py │ │ │ ├── mask2former_swin-t-p4-w7-224_lsj_8x2_50e_coco.py │ │ │ └── metafile.yml │ │ ├── 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_1x_wandb_coco.py │ │ │ ├── mask_rcnn_r50_fpn_2x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_fp16_1x_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 │ │ ├── maskformer │ │ │ ├── README.md │ │ │ ├── maskformer_r50_mstrain_16x1_75e_coco.py │ │ │ ├── maskformer_swin-l-p4-w12_mstrain_64x1_300e_coco.py │ │ │ └── metafile.yml │ │ ├── mlla │ │ │ ├── mlla_b_mrcnn_1x.py │ │ │ ├── mlla_s_mrcnn_1x.py │ │ │ ├── mlla_s_mrcnn_3x.py │ │ │ ├── mlla_t_mrcnn_1x.py │ │ │ └── mlla_t_mrcnn_3x.py │ │ ├── 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 │ │ ├── openimages │ │ │ ├── README.md │ │ │ ├── faster_rcnn_r50_fpn_32x2_1x_openimages.py │ │ │ ├── faster_rcnn_r50_fpn_32x2_1x_openimages_challenge.py │ │ │ ├── faster_rcnn_r50_fpn_32x2_cas_1x_openimages.py │ │ │ ├── faster_rcnn_r50_fpn_32x2_cas_1x_openimages_challenge.py │ │ │ ├── metafile.yml │ │ │ ├── retinanet_r50_fpn_32x2_1x_openimages.py │ │ │ └── ssd300_32x8_36e_openimages.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_caffe_c4_mstrain_18k_voc0712.py │ │ │ ├── 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 │ │ ├── queryinst │ │ │ ├── README.md │ │ │ ├── metafile.yml │ │ │ ├── queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py │ │ │ ├── queryinst_r101_fpn_mstrain_480-800_3x_coco.py │ │ │ ├── queryinst_r50_fpn_1x_coco.py │ │ │ ├── queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py │ │ │ └── queryinst_r50_fpn_mstrain_480-800_3x_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 │ │ ├── resnet_strikes_back │ │ │ ├── README.md │ │ │ ├── cascade_mask_rcnn_r50_fpn_rsb-pretrain_1x_coco.py │ │ │ ├── faster_rcnn_r50_fpn_rsb-pretrain_1x_coco.py │ │ │ ├── mask_rcnn_r50_fpn_rsb-pretrain_1x_coco.py │ │ │ ├── metafile.yml │ │ │ └── retinanet_r50_fpn_rsb-pretrain_1x_coco.py │ │ ├── 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_r18_fpn_1x8_1x_coco.py │ │ │ ├── retinanet_r18_fpn_1x_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_90k_coco.py │ │ │ ├── retinanet_r50_fpn_fp16_1x_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 │ │ │ └── metafile.yml │ │ ├── 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 │ │ ├── simple_copy_paste │ │ │ ├── README.md │ │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_ssj_32x2_270k_coco.py │ │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_ssj_32x2_90k_coco.py │ │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_ssj_scp_32x2_270k_coco.py │ │ │ ├── mask_rcnn_r50_fpn_syncbn-all_rpn-2conv_ssj_scp_32x2_90k_coco.py │ │ │ └── metafile.yml │ │ ├── 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 │ │ ├── solov2 │ │ │ ├── README.md │ │ │ ├── metafile.yml │ │ │ ├── solov2_light_r18_fpn_3x_coco.py │ │ │ ├── solov2_light_r34_fpn_3x_coco.py │ │ │ ├── solov2_light_r50_dcn_fpn_3x_coco.py │ │ │ ├── solov2_light_r50_fpn_3x_coco.py │ │ │ ├── solov2_r101_dcn_fpn_3x_coco.py │ │ │ ├── solov2_r101_fpn_3x_coco.py │ │ │ ├── solov2_r50_fpn_1x_coco.py │ │ │ ├── solov2_r50_fpn_3x_coco.py │ │ │ └── solov2_x101_dcn_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 │ │ │ ├── cascade_rcnn_swin-b.py │ │ │ ├── cascade_rcnn_swin-s.py │ │ │ ├── cascade_rcnn_swin-t_1x.py │ │ │ ├── mask_rcnn_swin-s-p4-w7_fpn_3x_coco.py │ │ │ ├── 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 │ │ │ ├── retinanet_swin-t-p4-w7_fpn_1x_coco.py │ │ │ └── swin_bsl.py │ │ ├── timm_example │ │ │ ├── README.md │ │ │ ├── retinanet_timm_efficientnet_b1_fpn_1x_coco.py │ │ │ └── retinanet_timm_tv_resnet50_fpn_1x_coco.py │ │ ├── tood │ │ │ ├── README.md │ │ │ ├── metafile.yml │ │ │ ├── tood_r101_fpn_dconv_c3-c5_mstrain_2x_coco.py │ │ │ ├── tood_r101_fpn_mstrain_2x_coco.py │ │ │ ├── tood_r50_fpn_1x_coco.py │ │ │ ├── tood_r50_fpn_anchor_based_1x_coco.py │ │ │ ├── tood_r50_fpn_mstrain_2x_coco.py │ │ │ ├── tood_x101_64x4d_fpn_dconv_c4-c5_mstrain_2x_coco.py │ │ │ └── tood_x101_64x4d_fpn_mstrain_2x_coco.py │ │ ├── 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 │ ├── detection.yaml │ ├── 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 │ │ │ │ │ ├── mask_hungarian_assigner.py │ │ │ │ │ ├── max_iou_assigner.py │ │ │ │ │ ├── point_assigner.py │ │ │ │ │ ├── region_assigner.py │ │ │ │ │ ├── sim_ota_assigner.py │ │ │ │ │ ├── task_aligned_assigner.py │ │ │ │ │ └── uniform_assigner.py │ │ │ │ ├── builder.py │ │ │ │ ├── coder │ │ │ │ │ ├── __init__.py │ │ │ │ │ ├── base_bbox_coder.py │ │ │ │ │ ├── bucketing_bbox_coder.py │ │ │ │ │ ├── delta_xywh_bbox_coder.py │ │ │ │ │ ├── distance_point_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 │ │ │ │ │ ├── mask_pseudo_sampler.py │ │ │ │ │ ├── mask_sampling_result.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 │ │ │ │ ├── panoptic_utils.py │ │ │ │ └── recall.py │ │ │ ├── export │ │ │ │ ├── __init__.py │ │ │ │ ├── model_wrappers.py │ │ │ │ ├── onnx_helper.py │ │ │ │ └── pytorch2onnx.py │ │ │ ├── hook │ │ │ │ ├── __init__.py │ │ │ │ ├── checkloss_hook.py │ │ │ │ ├── ema.py │ │ │ │ ├── memory_profiler_hook.py │ │ │ │ ├── set_epoch_info_hook.py │ │ │ │ ├── sync_norm_hook.py │ │ │ │ ├── sync_random_size_hook.py │ │ │ │ ├── wandblogger_hook.py │ │ │ │ ├── yolox_lrupdater_hook.py │ │ │ │ └── yolox_mode_switch_hook.py │ │ │ ├── mask │ │ │ │ ├── __init__.py │ │ │ │ ├── mask_target.py │ │ │ │ ├── structures.py │ │ │ │ └── utils.py │ │ │ ├── optimizers │ │ │ │ ├── __init__.py │ │ │ │ ├── builder.py │ │ │ │ └── layer_decay_optimizer_constructor.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 │ │ │ │ └── palette.py │ │ ├── datasets │ │ │ ├── __init__.py │ │ │ ├── api_wrappers │ │ │ │ ├── __init__.py │ │ │ │ ├── coco_api.py │ │ │ │ └── panoptic_evaluation.py │ │ │ ├── builder.py │ │ │ ├── cityscapes.py │ │ │ ├── coco.py │ │ │ ├── coco_panoptic.py │ │ │ ├── custom.py │ │ │ ├── dataset_wrappers.py │ │ │ ├── deepfashion.py │ │ │ ├── lvis.py │ │ │ ├── openimages.py │ │ │ ├── pipelines │ │ │ │ ├── __init__.py │ │ │ │ ├── auto_augment.py │ │ │ │ ├── compose.py │ │ │ │ ├── formating.py │ │ │ │ ├── formatting.py │ │ │ │ ├── instaboost.py │ │ │ │ ├── loading.py │ │ │ │ ├── test_time_aug.py │ │ │ │ └── transforms.py │ │ │ ├── samplers │ │ │ │ ├── __init__.py │ │ │ │ ├── class_aware_sampler.py │ │ │ │ ├── distributed_sampler.py │ │ │ │ ├── group_sampler.py │ │ │ │ └── infinite_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 │ │ │ │ ├── efficientnet.py │ │ │ │ ├── hourglass.py │ │ │ │ ├── hrnet.py │ │ │ │ ├── mlla.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 │ │ │ │ ├── ddod_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 │ │ │ │ ├── lad_head.py │ │ │ │ ├── ld_head.py │ │ │ │ ├── mask2former_head.py │ │ │ │ ├── maskformer_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 │ │ │ │ ├── solov2_head.py │ │ │ │ ├── ssd_head.py │ │ │ │ ├── tood_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 │ │ │ │ ├── ddod.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 │ │ │ │ ├── lad.py │ │ │ │ ├── mask2former.py │ │ │ │ ├── mask_rcnn.py │ │ │ │ ├── mask_scoring_rcnn.py │ │ │ │ ├── maskformer.py │ │ │ │ ├── nasfcos.py │ │ │ │ ├── paa.py │ │ │ │ ├── panoptic_fpn.py │ │ │ │ ├── panoptic_two_stage_segmentor.py │ │ │ │ ├── point_rend.py │ │ │ │ ├── queryinst.py │ │ │ │ ├── reppoints_detector.py │ │ │ │ ├── retinanet.py │ │ │ │ ├── rpn.py │ │ │ │ ├── scnet.py │ │ │ │ ├── single_stage.py │ │ │ │ ├── single_stage_instance_seg.py │ │ │ │ ├── solo.py │ │ │ │ ├── solov2.py │ │ │ │ ├── sparse_rcnn.py │ │ │ │ ├── tood.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 │ │ │ │ ├── dyhead.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 │ │ │ │ ├── msdeformattn_pixel_decoder.py │ │ │ │ └── pixel_decoder.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 │ │ │ │ │ ├── dynamic_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 │ │ │ │ │ └── maskformer_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 │ │ │ │ ├── panoptic_gt_processing.py │ │ │ │ ├── point_sample.py │ │ │ │ ├── positional_encoding.py │ │ │ │ ├── res_layer.py │ │ │ │ ├── se_layer.py │ │ │ │ └── transformer.py │ │ ├── utils │ │ │ ├── __init__.py │ │ │ ├── collect_env.py │ │ │ ├── compat_config.py │ │ │ ├── contextmanagers.py │ │ │ ├── logger.py │ │ │ ├── memory.py │ │ │ ├── misc.py │ │ │ ├── profiling.py │ │ │ ├── replace_cfg_vals.py │ │ │ ├── setup_env.py │ │ │ ├── split_batch.py │ │ │ ├── util_distribution.py │ │ │ ├── util_mixins.py │ │ │ └── util_random.py │ │ └── version.py │ ├── model-index.yml │ ├── pytest.ini │ ├── requirements.txt │ ├── requirements │ │ ├── albu.txt │ │ ├── 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 │ │ └── zhihu_qrcode.jpg │ ├── setup.cfg │ ├── setup.py │ └── tools │ │ ├── analysis_tools │ │ ├── analyze_logs.py │ │ ├── analyze_results.py │ │ ├── benchmark.py │ │ ├── coco_error_analysis.py │ │ ├── confusion_matrix.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 │ │ ├── download_dataset.py │ │ ├── gen_coco_panoptic_test_info.py │ │ ├── get_image_metas.py │ │ ├── print_config.py │ │ └── split_coco.py │ │ ├── model_converters │ │ ├── detectron2pytorch.py │ │ ├── publish_model.py │ │ ├── regnet2mmdet.py │ │ ├── selfsup2mmdet.py │ │ ├── upgrade_model_version.py │ │ └── upgrade_ssd_version.py │ │ ├── test.py │ │ └── train.py └── segmentation │ ├── .circleci │ └── config.yml │ ├── .dev │ ├── batch_test_list.py │ ├── batch_train_list.txt │ ├── benchmark_evaluation.sh │ ├── benchmark_inference.py │ ├── benchmark_train.sh │ ├── check_urls.py │ ├── gather_benchmark_evaluation_results.py │ ├── gather_benchmark_train_results.py │ ├── gather_models.py │ ├── generate_benchmark_evaluation_script.py │ ├── generate_benchmark_train_script.py │ ├── log_collector │ │ ├── example_config.py │ │ ├── log_collector.py │ │ ├── readme.md │ │ └── utils.py │ ├── md2yml.py │ └── upload_modelzoo.py │ ├── .gitignore │ ├── .owners.yml │ ├── .pre-commit-config.yaml │ ├── .readthedocs.yml │ ├── CITATION.cff │ ├── LICENSE │ ├── LICENSES.md │ ├── MANIFEST.in │ ├── README.md │ ├── configs │ ├── _base_ │ │ ├── datasets │ │ │ ├── ade20k.py │ │ │ ├── ade20k_640x640.py │ │ │ ├── chase_db1.py │ │ │ ├── cityscapes.py │ │ │ ├── cityscapes_1024x1024.py │ │ │ ├── cityscapes_768x768.py │ │ │ ├── cityscapes_769x769.py │ │ │ ├── cityscapes_832x832.py │ │ │ ├── coco-stuff10k.py │ │ │ ├── coco-stuff164k.py │ │ │ ├── drive.py │ │ │ ├── hrf.py │ │ │ ├── isaid.py │ │ │ ├── loveda.py │ │ │ ├── pascal_context.py │ │ │ ├── pascal_context_59.py │ │ │ ├── pascal_voc12.py │ │ │ ├── pascal_voc12_aug.py │ │ │ ├── potsdam.py │ │ │ ├── stare.py │ │ │ └── vaihingen.py │ │ ├── default_runtime.py │ │ ├── models │ │ │ ├── ann_r50-d8.py │ │ │ ├── apcnet_r50-d8.py │ │ │ ├── bisenetv1_r18-d32.py │ │ │ ├── bisenetv2.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 │ │ │ ├── dpt_vit-b16.py │ │ │ ├── emanet_r50-d8.py │ │ │ ├── encnet_r50-d8.py │ │ │ ├── erfnet_fcn.py │ │ │ ├── fast_scnn.py │ │ │ ├── fastfcn_r50-d32_jpu_psp.py │ │ │ ├── fcn_hr18.py │ │ │ ├── fcn_r50-d8.py │ │ │ ├── fcn_unet_s5-d16.py │ │ │ ├── fpn_r50.py │ │ │ ├── gcnet_r50-d8.py │ │ │ ├── icnet_r50-d8.py │ │ │ ├── isanet_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_mit-b0.py │ │ │ ├── segmenter_vit-b16_mask.py │ │ │ ├── setr_mla.py │ │ │ ├── setr_naive.py │ │ │ ├── setr_pup.py │ │ │ ├── stdc.py │ │ │ ├── twins_pcpvt-s_fpn.py │ │ │ ├── twins_pcpvt-s_upernet.py │ │ │ ├── upernet_beit.py │ │ │ ├── upernet_convnext.py │ │ │ ├── upernet_la.py │ │ │ ├── upernet_mae.py │ │ │ ├── upernet_r50.py │ │ │ ├── upernet_slide_transformer.py │ │ │ ├── upernet_swin.py │ │ │ └── upernet_vit-b16_ln_mln.py │ │ └── schedules │ │ │ ├── schedule_160k.py │ │ │ ├── schedule_20k.py │ │ │ ├── schedule_320k.py │ │ │ ├── schedule_40k.py │ │ │ └── schedule_80k.py │ ├── ann │ │ ├── README.md │ │ ├── ann.yml │ │ ├── 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.yml │ │ ├── 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 │ ├── beit │ │ ├── README.md │ │ ├── beit.yml │ │ ├── upernet_beit-base_640x640_160k_ade20k_ms.py │ │ ├── upernet_beit-base_8x2_640x640_160k_ade20k.py │ │ ├── upernet_beit-large_fp16_640x640_160k_ade20k_ms.py │ │ └── upernet_beit-large_fp16_8x1_640x640_160k_ade20k.py │ ├── bisenetv1 │ │ ├── README.md │ │ ├── bisenetv1.yml │ │ ├── bisenetv1_r101-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ │ ├── bisenetv1_r101-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ │ ├── bisenetv1_r18-d32_4x4_1024x1024_160k_cityscapes.py │ │ ├── bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py │ │ ├── bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py │ │ ├── bisenetv1_r18-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ │ ├── bisenetv1_r18-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ │ ├── bisenetv1_r50-d32_4x4_1024x1024_160k_cityscapes.py │ │ ├── bisenetv1_r50-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py │ │ ├── bisenetv1_r50-d32_in1k-pre_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ │ └── bisenetv1_r50-d32_lr5e-3_4x4_512x512_160k_coco-stuff164k.py │ ├── bisenetv2 │ │ ├── README.md │ │ ├── bisenetv2.yml │ │ ├── bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py │ │ ├── bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py │ │ ├── bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py │ │ └── bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py │ ├── ccnet │ │ ├── README.md │ │ ├── ccnet.yml │ │ ├── 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.yml │ │ ├── cgnet_512x1024_60k_cityscapes.py │ │ └── cgnet_680x680_60k_cityscapes.py │ ├── convnext │ │ ├── README.md │ │ ├── convnext.yml │ │ ├── upernet_convnext_base_fp16_512x512_160k_ade20k.py │ │ ├── upernet_convnext_base_fp16_640x640_160k_ade20k.py │ │ ├── upernet_convnext_large_fp16_640x640_160k_ade20k.py │ │ ├── upernet_convnext_small_fp16_512x512_160k_ade20k.py │ │ ├── upernet_convnext_tiny_fp16_512x512_160k_ade20k.py │ │ └── upernet_convnext_xlarge_fp16_640x640_160k_ade20k.py │ ├── danet │ │ ├── README.md │ │ ├── danet.yml │ │ ├── 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.yml │ │ ├── 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_40k_pascal_context_59.py │ │ ├── deeplabv3_r101-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3_r101-d8_480x480_80k_pascal_context_59.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_4x4_160k_coco-stuff164k.py │ │ ├── deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k.py │ │ ├── deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k.py │ │ ├── deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k.py │ │ ├── deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k.py │ │ ├── deeplabv3_r101-d8_512x512_80k_ade20k.py │ │ ├── deeplabv3_r101-d8_769x769_40k_cityscapes.py │ │ ├── deeplabv3_r101-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3_r101-d8_fp16_512x1024_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_40k_pascal_context_59.py │ │ ├── deeplabv3_r50-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3_r50-d8_480x480_80k_pascal_context_59.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_4x4_160k_coco-stuff164k.py │ │ ├── deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k.py │ │ ├── deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k.py │ │ ├── deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k.py │ │ ├── deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k.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.yml │ │ ├── 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_40k_pascal_context_59.py │ │ ├── deeplabv3plus_r101-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py │ │ ├── deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen.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_512x512_80k_loveda.py │ │ ├── deeplabv3plus_r101-d8_512x512_80k_potsdam.py │ │ ├── deeplabv3plus_r101-d8_769x769_40k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py │ │ ├── deeplabv3plus_r18-d8_4x4_512x512_80k_vaihingen.py │ │ ├── deeplabv3plus_r18-d8_4x4_896x896_80k_isaid.py │ │ ├── deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py │ │ ├── deeplabv3plus_r18-d8_512x512_80k_loveda.py │ │ ├── deeplabv3plus_r18-d8_512x512_80k_potsdam.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_40k_pascal_context_59.py │ │ ├── deeplabv3plus_r50-d8_480x480_80k_pascal_context.py │ │ ├── deeplabv3plus_r50-d8_480x480_80k_pascal_context_59.py │ │ ├── deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen.py │ │ ├── deeplabv3plus_r50-d8_4x4_896x896_80k_isaid.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_512x512_80k_loveda.py │ │ ├── deeplabv3plus_r50-d8_512x512_80k_potsdam.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.yml │ │ ├── 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 │ │ └── dnlnet.yml │ ├── dpt │ │ ├── README.md │ │ ├── dpt.yml │ │ └── dpt_vit-b16_512x512_160k_ade20k.py │ ├── emanet │ │ ├── README.md │ │ ├── emanet.yml │ │ ├── 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.yml │ │ ├── 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 │ ├── erfnet │ │ ├── README.md │ │ ├── erfnet.yml │ │ └── erfnet_fcn_4x4_512x1024_160k_cityscapes.py │ ├── fastfcn │ │ ├── README.md │ │ ├── fastfcn.yml │ │ ├── fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_aspp_512x512_160k_ade20k.py │ │ ├── fastfcn_r50-d32_jpu_aspp_512x512_80k_ade20k.py │ │ ├── fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_enc_512x512_160k_ade20k.py │ │ ├── fastfcn_r50-d32_jpu_enc_512x512_80k_ade20k.py │ │ ├── fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes.py │ │ ├── fastfcn_r50-d32_jpu_psp_512x512_160k_ade20k.py │ │ └── fastfcn_r50-d32_jpu_psp_512x512_80k_ade20k.py │ ├── fastscnn │ │ ├── README.md │ │ ├── fast_scnn_lr0.12_8x4_160k_cityscapes.py │ │ └── fastscnn.yml │ ├── fcn │ │ ├── README.md │ │ ├── fcn.yml │ │ ├── fcn_d6_r101-d16_512x1024_40k_cityscapes.py │ │ ├── fcn_d6_r101-d16_512x1024_80k_cityscapes.py │ │ ├── fcn_d6_r101-d16_769x769_40k_cityscapes.py │ │ ├── fcn_d6_r101-d16_769x769_80k_cityscapes.py │ │ ├── fcn_d6_r101b-d16_512x1024_80k_cityscapes.py │ │ ├── fcn_d6_r101b-d16_769x769_80k_cityscapes.py │ │ ├── fcn_d6_r50-d16_512x1024_40k_cityscapes.py │ │ ├── fcn_d6_r50-d16_512x1024_80k_cityscapes.py │ │ ├── fcn_d6_r50-d16_769x769_40k_cityscapes.py │ │ ├── fcn_d6_r50-d16_769x769_80k_cityscapes.py │ │ ├── fcn_d6_r50b-d16_512x1024_80k_cityscapes.py │ │ ├── fcn_d6_r50b-d16_769x769_80k_cityscapes.py │ │ ├── fcn_r101-d8_480x480_40k_pascal_context.py │ │ ├── fcn_r101-d8_480x480_40k_pascal_context_59.py │ │ ├── fcn_r101-d8_480x480_80k_pascal_context.py │ │ ├── fcn_r101-d8_480x480_80k_pascal_context_59.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_r101-d8_fp16_512x1024_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_40k_pascal_context_59.py │ │ ├── fcn_r50-d8_480x480_80k_pascal_context.py │ │ ├── fcn_r50-d8_480x480_80k_pascal_context_59.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 │ ├── gcnet │ │ ├── README.md │ │ ├── gcnet.yml │ │ ├── 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_40k_pascal_context_59.py │ │ ├── fcn_hr18_480x480_80k_pascal_context.py │ │ ├── fcn_hr18_480x480_80k_pascal_context_59.py │ │ ├── fcn_hr18_4x4_512x512_80k_vaihingen.py │ │ ├── fcn_hr18_4x4_896x896_80k_isaid.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_hr18_512x512_80k_loveda.py │ │ ├── fcn_hr18_512x512_80k_potsdam.py │ │ ├── fcn_hr18s_480x480_40k_pascal_context.py │ │ ├── fcn_hr18s_480x480_40k_pascal_context_59.py │ │ ├── fcn_hr18s_480x480_80k_pascal_context.py │ │ ├── fcn_hr18s_480x480_80k_pascal_context_59.py │ │ ├── fcn_hr18s_4x4_512x512_80k_vaihingen.py │ │ ├── fcn_hr18s_4x4_896x896_80k_isaid.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_hr18s_512x512_80k_loveda.py │ │ ├── fcn_hr18s_512x512_80k_potsdam.py │ │ ├── fcn_hr48_480x480_40k_pascal_context.py │ │ ├── fcn_hr48_480x480_40k_pascal_context_59.py │ │ ├── fcn_hr48_480x480_80k_pascal_context.py │ │ ├── fcn_hr48_480x480_80k_pascal_context_59.py │ │ ├── fcn_hr48_4x4_512x512_80k_vaihingen.py │ │ ├── fcn_hr48_4x4_896x896_80k_isaid.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 │ │ ├── fcn_hr48_512x512_80k_loveda.py │ │ ├── fcn_hr48_512x512_80k_potsdam.py │ │ └── hrnet.yml │ ├── icnet │ │ ├── README.md │ │ ├── icnet.yml │ │ ├── icnet_r101-d8_832x832_160k_cityscapes.py │ │ ├── icnet_r101-d8_832x832_80k_cityscapes.py │ │ ├── icnet_r101-d8_in1k-pre_832x832_160k_cityscapes.py │ │ ├── icnet_r101-d8_in1k-pre_832x832_80k_cityscapes.py │ │ ├── icnet_r18-d8_832x832_160k_cityscapes.py │ │ ├── icnet_r18-d8_832x832_80k_cityscapes.py │ │ ├── icnet_r18-d8_in1k-pre_832x832_160k_cityscapes.py │ │ ├── icnet_r18-d8_in1k-pre_832x832_80k_cityscapes.py │ │ ├── icnet_r50-d8_832x832_160k_cityscapes.py │ │ ├── icnet_r50-d8_832x832_80k_cityscapes.py │ │ ├── icnet_r50-d8_in1k-pre_832x832_160k_cityscapes.py │ │ └── icnet_r50-d8_in1k-pre_832x832_80k_cityscapes.py │ ├── isanet │ │ ├── README.md │ │ ├── isanet.yml │ │ ├── isanet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── isanet_r101-d8_512x1024_80k_cityscapes.py │ │ ├── isanet_r101-d8_512x512_160k_ade20k.py │ │ ├── isanet_r101-d8_512x512_20k_voc12aug.py │ │ ├── isanet_r101-d8_512x512_40k_voc12aug.py │ │ ├── isanet_r101-d8_512x512_80k_ade20k.py │ │ ├── isanet_r101-d8_769x769_40k_cityscapes.py │ │ ├── isanet_r101-d8_769x769_80k_cityscapes.py │ │ ├── isanet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── isanet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── isanet_r50-d8_512x512_160k_ade20k.py │ │ ├── isanet_r50-d8_512x512_20k_voc12aug.py │ │ ├── isanet_r50-d8_512x512_40k_voc12aug.py │ │ ├── isanet_r50-d8_512x512_80k_ade20k.py │ │ ├── isanet_r50-d8_769x769_40k_cityscapes.py │ │ └── isanet_r50-d8_769x769_80k_cityscapes.py │ ├── knet │ │ ├── README.md │ │ ├── knet.yml │ │ ├── knet_s3_deeplabv3_r50-d8_8x2_512x512_adamw_80k_ade20k.py │ │ ├── knet_s3_fcn_r50-d8_8x2_512x512_adamw_80k_ade20k.py │ │ ├── knet_s3_pspnet_r50-d8_8x2_512x512_adamw_80k_ade20k.py │ │ ├── knet_s3_upernet_r50-d8_8x2_512x512_adamw_80k_ade20k.py │ │ ├── knet_s3_upernet_swin-l_8x2_512x512_adamw_80k_ade20k.py │ │ ├── knet_s3_upernet_swin-l_8x2_640x640_adamw_80k_ade20k.py │ │ └── knet_s3_upernet_swin-t_8x2_512x512_adamw_80k_ade20k.py │ ├── mae │ │ ├── README.md │ │ ├── mae.yml │ │ ├── upernet_mae-base_fp16_512x512_160k_ade20k_ms.py │ │ └── upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py │ ├── mlla │ │ └── mlla_b_upernet.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 │ │ ├── mobilenet_v2.yml │ │ ├── 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 │ │ └── mobilenet_v3.yml │ ├── nonlocal_net │ │ ├── README.md │ │ ├── nonlocal_net.yml │ │ ├── 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.yml │ │ ├── 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 │ │ ├── point_rend.yml │ │ ├── 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.yml │ │ ├── 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.yml │ │ ├── pspnet_r101-d8_480x480_40k_pascal_context.py │ │ ├── pspnet_r101-d8_480x480_40k_pascal_context_59.py │ │ ├── pspnet_r101-d8_480x480_80k_pascal_context.py │ │ ├── pspnet_r101-d8_480x480_80k_pascal_context_59.py │ │ ├── pspnet_r101-d8_4x4_512x512_80k_potsdam.py │ │ ├── pspnet_r101-d8_4x4_512x512_80k_vaihingen.py │ │ ├── pspnet_r101-d8_512x1024_40k_cityscapes.py │ │ ├── pspnet_r101-d8_512x1024_40k_dark.py │ │ ├── pspnet_r101-d8_512x1024_40k_night_driving.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_4x4_160k_coco-stuff164k.py │ │ ├── pspnet_r101-d8_512x512_4x4_20k_coco-stuff10k.py │ │ ├── pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k.py │ │ ├── pspnet_r101-d8_512x512_4x4_40k_coco-stuff10k.py │ │ ├── pspnet_r101-d8_512x512_4x4_80k_coco-stuff164k.py │ │ ├── pspnet_r101-d8_512x512_80k_ade20k.py │ │ ├── pspnet_r101-d8_512x512_80k_loveda.py │ │ ├── pspnet_r101-d8_769x769_40k_cityscapes.py │ │ ├── pspnet_r101-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py │ │ ├── pspnet_r101b-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r101b-d8_512x1024_80k_dark.py │ │ ├── pspnet_r101b-d8_512x1024_80k_night_driving.py │ │ ├── pspnet_r101b-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r18-d8_4x4_512x512_80k_potsdam.py │ │ ├── pspnet_r18-d8_4x4_512x512_80k_vaihingen.py │ │ ├── pspnet_r18-d8_4x4_896x896_80k_isaid.py │ │ ├── pspnet_r18-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r18-d8_512x512_80k_loveda.py │ │ ├── pspnet_r18-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r18b-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r18b-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r50-d32_512x1024_80k_cityscapes.py │ │ ├── pspnet_r50-d32_rsb-pretrain_512x1024_adamw_80k_cityscapes.py │ │ ├── pspnet_r50-d8_480x480_40k_pascal_context.py │ │ ├── pspnet_r50-d8_480x480_40k_pascal_context_59.py │ │ ├── pspnet_r50-d8_480x480_80k_pascal_context.py │ │ ├── pspnet_r50-d8_480x480_80k_pascal_context_59.py │ │ ├── pspnet_r50-d8_4x4_512x512_80k_potsdam.py │ │ ├── pspnet_r50-d8_4x4_512x512_80k_vaihingen.py │ │ ├── pspnet_r50-d8_4x4_896x896_80k_isaid.py │ │ ├── pspnet_r50-d8_512x1024_40k_cityscapes.py │ │ ├── pspnet_r50-d8_512x1024_40k_dark.py │ │ ├── pspnet_r50-d8_512x1024_40k_night_driving.py │ │ ├── pspnet_r50-d8_512x1024_80k_cityscapes.py │ │ ├── pspnet_r50-d8_512x1024_80k_dark.py │ │ ├── pspnet_r50-d8_512x1024_80k_night_driving.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_4x4_160k_coco-stuff164k.py │ │ ├── pspnet_r50-d8_512x512_4x4_20k_coco-stuff10k.py │ │ ├── pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k.py │ │ ├── pspnet_r50-d8_512x512_4x4_40k_coco-stuff10k.py │ │ ├── pspnet_r50-d8_512x512_4x4_80k_coco-stuff164k.py │ │ ├── pspnet_r50-d8_512x512_80k_ade20k.py │ │ ├── pspnet_r50-d8_512x512_80k_loveda.py │ │ ├── pspnet_r50-d8_769x769_40k_cityscapes.py │ │ ├── pspnet_r50-d8_769x769_80k_cityscapes.py │ │ ├── pspnet_r50-d8_rsb-pretrain_512x1024_adamw_80k_cityscapes.py │ │ ├── pspnet_r50b-d32_512x1024_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 │ │ └── resnest.yml │ ├── segformer │ │ ├── README.md │ │ ├── segformer.yml │ │ ├── segformer_mit-b0_512x512_160k_ade20k.py │ │ ├── segformer_mit-b0_8x1_1024x1024_160k_cityscapes.py │ │ ├── segformer_mit-b1_512x512_160k_ade20k.py │ │ ├── segformer_mit-b1_8x1_1024x1024_160k_cityscapes.py │ │ ├── segformer_mit-b2_512x512_160k_ade20k.py │ │ ├── segformer_mit-b2_8x1_1024x1024_160k_cityscapes.py │ │ ├── segformer_mit-b3_512x512_160k_ade20k.py │ │ ├── segformer_mit-b3_8x1_1024x1024_160k_cityscapes.py │ │ ├── segformer_mit-b4_512x512_160k_ade20k.py │ │ ├── segformer_mit-b4_8x1_1024x1024_160k_cityscapes.py │ │ ├── segformer_mit-b5_512x512_160k_ade20k.py │ │ ├── segformer_mit-b5_640x640_160k_ade20k.py │ │ └── segformer_mit-b5_8x1_1024x1024_160k_cityscapes.py │ ├── segmenter │ │ ├── README.md │ │ ├── segmenter.yml │ │ ├── segmenter_vit-b_mask_8x1_512x512_160k_ade20k.py │ │ ├── segmenter_vit-l_mask_8x1_640x640_160k_ade20k.py │ │ ├── segmenter_vit-s_linear_8x1_512x512_160k_ade20k.py │ │ ├── segmenter_vit-s_mask_8x1_512x512_160k_ade20k.py │ │ └── segmenter_vit-t_mask_8x1_512x512_160k_ade20k.py │ ├── sem_fpn │ │ ├── README.md │ │ ├── fpn_r101_512x1024_80k_cityscapes.py │ │ ├── fpn_r101_512x512_160k_ade20k.py │ │ ├── fpn_r50_512x1024_80k_cityscapes.py │ │ ├── fpn_r50_512x512_160k_ade20k.py │ │ └── sem_fpn.yml │ ├── setr │ │ ├── README.md │ │ ├── setr.yml │ │ ├── setr_mla_512x512_160k_b16_ade20k.py │ │ ├── setr_mla_512x512_160k_b8_ade20k.py │ │ ├── setr_naive_512x512_160k_b16_ade20k.py │ │ ├── setr_pup_512x512_160k_b16_ade20k.py │ │ ├── setr_vit-large_mla_8x1_768x768_80k_cityscapes.py │ │ ├── setr_vit-large_naive_8x1_768x768_80k_cityscapes.py │ │ └── setr_vit-large_pup_8x1_768x768_80k_cityscapes.py │ ├── stdc │ │ ├── README.md │ │ ├── stdc.yml │ │ ├── stdc1_512x1024_80k_cityscapes.py │ │ ├── stdc1_in1k-pre_512x1024_80k_cityscapes.py │ │ ├── stdc2_512x1024_80k_cityscapes.py │ │ └── stdc2_in1k-pre_512x1024_80k_cityscapes.py │ ├── swin │ │ ├── README.md │ │ ├── swin.yml │ │ ├── upernet_swin_base_patch4_window12_512x512_160k_ade20k_pretrain_384x384_1K.py │ │ ├── upernet_swin_base_patch4_window12_512x512_160k_ade20k_pretrain_384x384_22K.py │ │ ├── upernet_swin_base_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py │ │ ├── upernet_swin_base_patch4_window7_512x512_160k_ade20k_pretrain_224x224_22K.py │ │ ├── upernet_swin_large_patch4_window12_512x512_pretrain_384x384_22K_160k_ade20k.py │ │ ├── upernet_swin_large_patch4_window7_512x512_pretrain_224x224_22K_160k_ade20k.py │ │ ├── upernet_swin_small_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py │ │ └── upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py │ ├── twins │ │ ├── README.md │ │ ├── twins.yml │ │ ├── twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ ├── twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py │ │ ├── twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ ├── twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py │ │ ├── twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ ├── twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k.py │ │ ├── twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ ├── twins_svt-b_uperhead_8x2_512x512_160k_ade20k.py │ │ ├── twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ ├── twins_svt-l_uperhead_8x2_512x512_160k_ade20k.py │ │ ├── twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py │ │ └── twins_svt-s_uperhead_8x2_512x512_160k_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 │ │ ├── deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1.py │ │ ├── deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare.py │ │ ├── deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf.py │ │ ├── deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_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_4x4_512x1024_160k_cityscapes.py │ │ ├── fcn_unet_s5-d16_64x64_40k_drive.py │ │ ├── fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1.py │ │ ├── fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare.py │ │ ├── fcn_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf.py │ │ ├── fcn_unet_s5-d16_ce-1.0-dice-3.0_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 │ │ ├── pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1.py │ │ ├── pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare.py │ │ ├── pspnet_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf.py │ │ ├── pspnet_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive.py │ │ └── unet.yml │ ├── upernet │ │ ├── README.md │ │ ├── upernet.yml │ │ ├── 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_r18_512x1024_40k_cityscapes.py │ │ ├── upernet_r18_512x1024_80k_cityscapes.py │ │ ├── upernet_r18_512x512_160k_ade20k.py │ │ ├── upernet_r18_512x512_20k_voc12aug.py │ │ ├── upernet_r18_512x512_40k_voc12aug.py │ │ ├── upernet_r18_512x512_80k_ade20k.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 │ └── vit │ │ ├── README.md │ │ ├── upernet_deit-b16_512x512_160k_ade20k.py │ │ ├── upernet_deit-b16_512x512_80k_ade20k.py │ │ ├── upernet_deit-b16_ln_mln_512x512_160k_ade20k.py │ │ ├── upernet_deit-b16_mln_512x512_160k_ade20k.py │ │ ├── upernet_deit-s16_512x512_160k_ade20k.py │ │ ├── upernet_deit-s16_512x512_80k_ade20k.py │ │ ├── upernet_deit-s16_ln_mln_512x512_160k_ade20k.py │ │ ├── upernet_deit-s16_mln_512x512_160k_ade20k.py │ │ ├── upernet_vit-b16_ln_mln_512x512_160k_ade20k.py │ │ ├── upernet_vit-b16_mln_512x512_160k_ade20k.py │ │ ├── upernet_vit-b16_mln_512x512_80k_ade20k.py │ │ └── vit.yml │ ├── mmseg │ ├── __init__.py │ ├── apis │ │ ├── __init__.py │ │ ├── inference.py │ │ ├── test.py │ │ └── train.py │ ├── core │ │ ├── __init__.py │ │ ├── builder.py │ │ ├── evaluation │ │ │ ├── __init__.py │ │ │ ├── class_names.py │ │ │ ├── eval_hooks.py │ │ │ └── metrics.py │ │ ├── hook │ │ │ ├── __init__.py │ │ │ └── wandblogger_hook.py │ │ ├── optimizers │ │ │ ├── __init__.py │ │ │ └── layer_decay_optimizer_constructor.py │ │ ├── seg │ │ │ ├── __init__.py │ │ │ ├── builder.py │ │ │ └── sampler │ │ │ │ ├── __init__.py │ │ │ │ ├── base_pixel_sampler.py │ │ │ │ └── ohem_pixel_sampler.py │ │ └── utils │ │ │ ├── __init__.py │ │ │ ├── dist_util.py │ │ │ └── misc.py │ ├── datasets │ │ ├── __init__.py │ │ ├── ade.py │ │ ├── builder.py │ │ ├── chase_db1.py │ │ ├── cityscapes.py │ │ ├── coco_stuff.py │ │ ├── custom.py │ │ ├── dark_zurich.py │ │ ├── dataset_wrappers.py │ │ ├── drive.py │ │ ├── hrf.py │ │ ├── isaid.py │ │ ├── isprs.py │ │ ├── loveda.py │ │ ├── night_driving.py │ │ ├── pascal_context.py │ │ ├── pipelines │ │ │ ├── __init__.py │ │ │ ├── compose.py │ │ │ ├── formating.py │ │ │ ├── formatting.py │ │ │ ├── loading.py │ │ │ ├── test_time_aug.py │ │ │ └── transforms.py │ │ ├── potsdam.py │ │ ├── samplers │ │ │ ├── __init__.py │ │ │ └── distributed_sampler.py │ │ ├── stare.py │ │ └── voc.py │ ├── models │ │ ├── __init__.py │ │ ├── backbones │ │ │ ├── __init__.py │ │ │ ├── beit.py │ │ │ ├── bisenetv1.py │ │ │ ├── bisenetv2.py │ │ │ ├── cgnet.py │ │ │ ├── erfnet.py │ │ │ ├── fast_scnn.py │ │ │ ├── hrnet.py │ │ │ ├── icnet.py │ │ │ ├── mae.py │ │ │ ├── mit.py │ │ │ ├── mlla.py │ │ │ ├── mobilenet_v2.py │ │ │ ├── mobilenet_v3.py │ │ │ ├── resnest.py │ │ │ ├── resnet.py │ │ │ ├── resnext.py │ │ │ ├── stdc.py │ │ │ ├── swin.py │ │ │ ├── timm_backbone.py │ │ │ ├── twins.py │ │ │ ├── unet.py │ │ │ └── vit.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 │ │ │ ├── dpt_head.py │ │ │ ├── ema_head.py │ │ │ ├── enc_head.py │ │ │ ├── fcn_head.py │ │ │ ├── fpn_head.py │ │ │ ├── gc_head.py │ │ │ ├── isa_head.py │ │ │ ├── knet_head.py │ │ │ ├── lraspp_head.py │ │ │ ├── nl_head.py │ │ │ ├── ocr_head.py │ │ │ ├── point_head.py │ │ │ ├── psa_head.py │ │ │ ├── psp_head.py │ │ │ ├── segformer_head.py │ │ │ ├── segmenter_mask_head.py │ │ │ ├── sep_aspp_head.py │ │ │ ├── sep_fcn_head.py │ │ │ ├── setr_mla_head.py │ │ │ ├── setr_up_head.py │ │ │ ├── stdc_head.py │ │ │ └── uper_head.py │ │ ├── losses │ │ │ ├── __init__.py │ │ │ ├── accuracy.py │ │ │ ├── cross_entropy_loss.py │ │ │ ├── dice_loss.py │ │ │ ├── focal_loss.py │ │ │ ├── lovasz_loss.py │ │ │ ├── tversky_loss.py │ │ │ └── utils.py │ │ ├── necks │ │ │ ├── __init__.py │ │ │ ├── featurepyramid.py │ │ │ ├── fpn.py │ │ │ ├── ic_neck.py │ │ │ ├── jpu.py │ │ │ ├── mla_neck.py │ │ │ └── multilevel_neck.py │ │ ├── segmentors │ │ │ ├── __init__.py │ │ │ ├── base.py │ │ │ ├── cascade_encoder_decoder.py │ │ │ └── encoder_decoder.py │ │ └── utils │ │ │ ├── __init__.py │ │ │ ├── embed.py │ │ │ ├── inverted_residual.py │ │ │ ├── make_divisible.py │ │ │ ├── res_layer.py │ │ │ ├── se_layer.py │ │ │ ├── self_attention_block.py │ │ │ ├── shape_convert.py │ │ │ └── up_conv_block.py │ ├── ops │ │ ├── __init__.py │ │ ├── encoding.py │ │ └── wrappers.py │ ├── utils │ │ ├── __init__.py │ │ ├── collect_env.py │ │ ├── logger.py │ │ ├── misc.py │ │ ├── set_env.py │ │ └── util_distribution.py │ └── version.py │ ├── model-index.yml │ ├── pytest.ini │ ├── requirements.txt │ ├── requirements │ ├── docs.txt │ ├── mminstall.txt │ ├── optional.txt │ ├── readthedocs.txt │ ├── runtime.txt │ └── tests.txt │ ├── result.jpg │ ├── segmentation.yaml │ ├── setup.cfg │ ├── setup.py │ └── tools │ ├── analyze_logs.py │ ├── benchmark.py │ ├── browse_dataset.py │ ├── confusion_matrix.py │ ├── convert_datasets │ ├── chase_db1.py │ ├── cityscapes.py │ ├── coco_stuff10k.py │ ├── coco_stuff164k.py │ ├── drive.py │ ├── hrf.py │ ├── isaid.py │ ├── loveda.py │ ├── pascal_context.py │ ├── potsdam.py │ ├── stare.py │ ├── vaihingen.py │ └── voc_aug.py │ ├── deploy_test.py │ ├── dist_test.sh │ ├── dist_train.sh │ ├── finished_sh │ ├── direct_train_pvt_t.sh │ ├── slurm_la1.sh │ ├── slurm_la2.sh │ ├── slurm_test.sh │ ├── slurm_train.sh │ ├── slurm_train_base.sh │ ├── slurm_train_bsl.sh │ ├── slurm_train_pvt2-b2.sh │ ├── slurm_train_pvt2-b3.sh │ ├── slurm_train_pvt_s.sh │ ├── slurm_train_pvt_t.sh │ ├── slurm_train_small.sh │ ├── slurm_train_tiny_LK.sh │ └── slurm_train_tiny_release.sh │ ├── get_flops.py │ ├── model_converters │ ├── beit2mmseg.py │ ├── mit2mmseg.py │ ├── stdc2mmseg.py │ ├── swin2mmseg.py │ ├── twins2mmseg.py │ ├── vit2mmseg.py │ └── vitjax2mmseg.py │ ├── my_analyze_logs.py │ ├── onnx2tensorrt.py │ ├── print_config.py │ ├── publish_model.py │ ├── pytorch2onnx.py │ ├── pytorch2torchscript.py │ ├── single_gpu_test.sh │ ├── test.py │ ├── torchserve │ ├── mmseg2torchserve.py │ ├── mmseg_handler.py │ └── test_torchserve.py │ └── train.py ├── figures ├── fig1_ssm_vs_linear.jpg ├── fig2_block.jpg ├── fig3_ablation.png ├── fig4_cls.png ├── fig5_speed.jpg ├── fig6_det.png └── fig7_seg.png ├── logger.py ├── lr_scheduler.py ├── main.py ├── models ├── __init__.py ├── build.py └── mlla.py ├── optimizer.py └── utils.py /cfgs/mlla_b.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: mlla 3 | NAME: mlla_base 4 | DROP_PATH_RATE: 0.5 5 | MLLA: 6 | EMBED_DIM: 96 7 | DEPTHS: [ 3, 6, 21, 6 ] 8 | NUM_HEADS: [ 3, 6, 12, 24 ] 9 | AUG: 10 | AUTO_AUGMENT: rand-m9-mstd0.5-inc1 11 | REPROB: 0.25 12 | MIXUP: 0.8 13 | CUTMIX: 1.0 14 | MESA: 2.0 15 | DATA: 16 | BATCH_SIZE: 64 -------------------------------------------------------------------------------- /cfgs/mlla_s.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: mlla 3 | NAME: mlla_small 4 | DROP_PATH_RATE: 0.3 5 | MLLA: 6 | EMBED_DIM: 64 7 | DEPTHS: [ 3, 6, 21, 6 ] 8 | NUM_HEADS: [ 2, 4, 8, 16 ] 9 | AUG: 10 | AUTO_AUGMENT: rand-m9-mstd0.5-inc1 11 | REPROB: 0.25 12 | MIXUP: 0.8 13 | CUTMIX: 1.0 14 | MESA: 1.5 15 | DATA: 16 | BATCH_SIZE: 64 -------------------------------------------------------------------------------- /cfgs/mlla_t.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: mlla 3 | NAME: mlla_tiny 4 | DROP_PATH_RATE: 0.2 5 | MLLA: 6 | EMBED_DIM: 64 7 | DEPTHS: [ 2, 4, 8, 4 ] 8 | NUM_HEADS: [ 2, 4, 8, 16 ] 9 | AUG: 10 | AUTO_AUGMENT: rand-m9-mstd0.5-inc1 11 | REPROB: 0.25 12 | MIXUP: 0.8 13 | CUTMIX: 1.0 14 | MESA: 1.0 15 | DATA: 16 | BATCH_SIZE: 128 -------------------------------------------------------------------------------- /data/__init__.py: -------------------------------------------------------------------------------- 1 | from .build import build_loader -------------------------------------------------------------------------------- /downstream/detection/.dev_scripts/linter.sh: -------------------------------------------------------------------------------- 1 | yapf -r -i mmdet/ configs/ tests/ tools/ 2 | isort -rc mmdet/ configs/ tests/ tools/ 3 | flake8 . 4 | -------------------------------------------------------------------------------- /downstream/detection/.owners.yml: -------------------------------------------------------------------------------- 1 | assign: 2 | strategy: 3 | # random 4 | daily-shift-based 5 | scedule: 6 | '*/1 * * * *' 7 | assignees: 8 | - Czm369 9 | - hhaAndroid 10 | - jbwang1997 11 | - RangiLyu 12 | - BIGWangYuDong 13 | - chhluo 14 | - ZwwWayne 15 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/dcn/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/dcnv2/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/dcnv2/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/dcnv2/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/dcnv2/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/faster_rcnn/faster_rcnn_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './faster_rcnn_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/mask2former/mask2former_r101_lsj_8x2_50e_coco-panoptic.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask2former_r50_lsj_8x2_50e_coco-panoptic.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /downstream/detection/configs/mask2former/mask2former_r101_lsj_8x2_50e_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./mask2former_r50_lsj_8x2_50e_coco.py'] 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/mask_rcnn/mask_rcnn_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './mask_rcnn_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/openimages/faster_rcnn_r50_fpn_32x2_cas_1x_openimages.py: -------------------------------------------------------------------------------- 1 | _base_ = ['faster_rcnn_r50_fpn_32x2_1x_openimages.py'] 2 | 3 | # Use ClassAwareSampler 4 | data = dict( 5 | train_dataloader=dict(class_aware_sampler=dict(num_sample_class=1))) 6 | -------------------------------------------------------------------------------- /downstream/detection/configs/openimages/faster_rcnn_r50_fpn_32x2_cas_1x_openimages_challenge.py: -------------------------------------------------------------------------------- 1 | _base_ = ['faster_rcnn_r50_fpn_32x2_1x_openimages_challenge.py'] 2 | 3 | # Use ClassAwareSampler 4 | data = dict( 5 | train_dataloader=dict(class_aware_sampler=dict(num_sample_class=1))) 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './queryinst_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 | -------------------------------------------------------------------------------- /downstream/detection/configs/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './queryinst_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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/reppoints/reppoints.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/configs/reppoints/reppoints.png -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/retinanet/retinanet_r50_fpn_fp16_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './retinanet_r50_fpn_1x_coco.py' 2 | # fp16 settings 3 | fp16 = dict(loss_scale=512.) 4 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/solov2/solov2_light_r18_fpn_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'solov2_light_r50_fpn_3x_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict( 6 | depth=18, init_cfg=dict(checkpoint='torchvision://resnet18')), 7 | neck=dict(in_channels=[64, 128, 256, 512])) 8 | -------------------------------------------------------------------------------- /downstream/detection/configs/solov2/solov2_light_r34_fpn_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'solov2_light_r50_fpn_3x_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict( 6 | depth=34, init_cfg=dict(checkpoint='torchvision://resnet34')), 7 | neck=dict(in_channels=[64, 128, 256, 512])) 8 | -------------------------------------------------------------------------------- /downstream/detection/configs/solov2/solov2_r101_fpn_3x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = 'solov2_r50_fpn_3x_coco.py' 2 | 3 | # model settings 4 | model = dict( 5 | backbone=dict( 6 | depth=101, init_cfg=dict(checkpoint='torchvision://resnet101'))) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/configs/tood/tood_r101_fpn_dconv_c3-c5_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './tood_r101_fpn_mstrain_2x_coco.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False), 6 | stage_with_dcn=(False, True, True, True)), 7 | bbox_head=dict(num_dcn=2)) 8 | -------------------------------------------------------------------------------- /downstream/detection/configs/tood/tood_r101_fpn_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './tood_r50_fpn_mstrain_2x_coco.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /downstream/detection/configs/tood/tood_r50_fpn_anchor_based_1x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './tood_r50_fpn_1x_coco.py' 2 | model = dict(bbox_head=dict(anchor_type='anchor_based')) 3 | -------------------------------------------------------------------------------- /downstream/detection/configs/tood/tood_x101_64x4d_fpn_dconv_c4-c5_mstrain_2x_coco.py: -------------------------------------------------------------------------------- 1 | _base_ = './tood_x101_64x4d_fpn_mstrain_2x_coco.py' 2 | model = dict( 3 | backbone=dict( 4 | dcn=dict(type='DCNv2', deformable_groups=1, fallback_on_stride=False), 5 | stage_with_dcn=(False, False, True, True), 6 | ), 7 | bbox_head=dict(num_dcn=2)) 8 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/mmdet/core/evaluation/panoptic_utils.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | # A custom value to distinguish instance ID and category ID; need to 3 | # be greater than the number of categories. 4 | # For a pixel in the panoptic result map: 5 | # pan_id = ins_id * INSTANCE_OFFSET + cat_id 6 | INSTANCE_OFFSET = 1000 7 | -------------------------------------------------------------------------------- /downstream/detection/mmdet/datasets/api_wrappers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .coco_api import COCO, COCOeval 3 | from .panoptic_evaluation import pq_compute_multi_core, pq_compute_single_core 4 | 5 | __all__ = [ 6 | 'COCO', 'COCOeval', 'pq_compute_multi_core', 'pq_compute_single_core' 7 | ] 8 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/detection/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/build.txt 2 | -r requirements/optional.txt 3 | -r requirements/runtime.txt 4 | -r requirements/tests.txt 5 | -------------------------------------------------------------------------------- /downstream/detection/requirements/albu.txt: -------------------------------------------------------------------------------- 1 | albumentations>=0.3.2 --no-binary qudida,albumentations 2 | -------------------------------------------------------------------------------- /downstream/detection/requirements/build.txt: -------------------------------------------------------------------------------- 1 | # These must be installed before building mmdetection 2 | cython 3 | numpy 4 | -------------------------------------------------------------------------------- /downstream/detection/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | docutils==0.16.0 2 | markdown<3.4.0 3 | myst-parser 4 | -e git+https://github.com/open-mmlab/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme 5 | sphinx==4.0.2 6 | sphinx-copybutton 7 | sphinx_markdown_tables 8 | sphinx_rtd_theme==0.5.2 9 | -------------------------------------------------------------------------------- /downstream/detection/requirements/mminstall.txt: -------------------------------------------------------------------------------- 1 | mmcv-full>=1.3.17 2 | -------------------------------------------------------------------------------- /downstream/detection/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | cityscapesscripts 2 | imagecorruptions 3 | scipy 4 | sklearn 5 | timm 6 | -------------------------------------------------------------------------------- /downstream/detection/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | torch 3 | torchvision 4 | -------------------------------------------------------------------------------- /downstream/detection/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | numpy 3 | pycocotools 4 | six 5 | terminaltables 6 | -------------------------------------------------------------------------------- /downstream/detection/resources/coco_test_12510.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/coco_test_12510.jpg -------------------------------------------------------------------------------- /downstream/detection/resources/corruptions_sev_3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/corruptions_sev_3.png -------------------------------------------------------------------------------- /downstream/detection/resources/data_pipeline.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/data_pipeline.png -------------------------------------------------------------------------------- /downstream/detection/resources/loss_curve.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/loss_curve.png -------------------------------------------------------------------------------- /downstream/detection/resources/mmdet-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/mmdet-logo.png -------------------------------------------------------------------------------- /downstream/detection/resources/zhihu_qrcode.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/detection/resources/zhihu_qrcode.jpg -------------------------------------------------------------------------------- /downstream/segmentation/.owners.yml: -------------------------------------------------------------------------------- 1 | assign: 2 | strategy: 3 | # random 4 | # round-robin 5 | daily-shift-based 6 | assignees: 7 | - MengzhangLI 8 | - xiexinch 9 | - MeowZheng 10 | - MengzhangLI 11 | - xiexinch 12 | -------------------------------------------------------------------------------- /downstream/segmentation/.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 | -------------------------------------------------------------------------------- /downstream/segmentation/CITATION.cff: -------------------------------------------------------------------------------- 1 | cff-version: 1.2.0 2 | message: "If you use this software, please cite it as below." 3 | authors: 4 | - name: "MMSegmentation Contributors" 5 | title: "OpenMMLab Semantic Segmentation Toolbox and Benchmark" 6 | date-released: 2020-07-10 7 | url: "https://github.com/open-mmlab/mmsegmentation" 8 | license: Apache-2.0 9 | -------------------------------------------------------------------------------- /downstream/segmentation/MANIFEST.in: -------------------------------------------------------------------------------- 1 | include requirements/*.txt 2 | include mmseg/.mim/model-index.yml 3 | recursive-include mmseg/.mim/configs *.py *.yml 4 | recursive-include mmseg/.mim/tools *.py *.sh 5 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/bisenetv1/bisenetv1_r18-d32_in1k-pre_4x8_1024x1024_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r18-d32_in1k-pre_4x4_1024x1024_160k_cityscapes.py' 2 | data = dict( 3 | samples_per_gpu=8, 4 | workers_per_gpu=4, 5 | ) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | # fp16 placeholder 5 | fp16 = dict() 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_480x480_40k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_480x480_80k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_4x4_160k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_4x4_20k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_4x4_20k_coco-stuff10k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_4x4_40k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_4x4_40k_coco-stuff10k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_512x512_4x4_80k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_512x512_4x4_80k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | # fp16 placeholder 5 | fp16 = dict() 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_480x480_40k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_480x480_80k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_loveda.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_80k_loveda.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet101_v1c'))) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_potsdam.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_512x512_80k_potsdam.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | # fp16 placeholder 5 | fp16 = dict() 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_loveda.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3plus_r50-d8.py', '../_base_/datasets/loveda.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=7), auxiliary_head=dict(num_classes=7)) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/erfnet_fcn.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | data = dict( 6 | samples_per_gpu=4, 7 | workers_per_gpu=4, 8 | ) 9 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | # model settings 2 | _base_ = './fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes.py' 3 | data = dict( 4 | samples_per_gpu=4, 5 | workers_per_gpu=4, 6 | ) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | # model settings 2 | _base_ = './fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes.py' 3 | data = dict( 4 | samples_per_gpu=4, 5 | workers_per_gpu=4, 6 | ) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fastfcn/fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fastfcn_r50-d32_jpu_psp.py', 3 | '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101-d16_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101-d16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101-d16_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101-d16_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101b-d16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50b-d16_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r101b-d16_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50b-d16_769x769_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r50b-d16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_d6_r50b-d16_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_d6_r50-d16_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_r101-d8_480x480_40k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_480x480_40k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_r101-d8_480x480_80k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_480x480_80k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | # fp16 placeholder 5 | fp16 = dict() 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/hrnet/fcn_hr18_4x4_512x512_80k_vaihingen.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/vaihingen.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=6)) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/hrnet/fcn_hr18_4x4_896x896_80k_isaid.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/isaid.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=16)) 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/hrnet/fcn_hr18_512x512_80k_loveda.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/loveda.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=7)) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/hrnet/fcn_hr18_512x512_80k_potsdam.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_hr18.py', '../_base_/datasets/potsdam.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=6)) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r101-d8_832x832_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_160k_cityscapes.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(depth=101))) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r101-d8_832x832_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_80k_cityscapes.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(depth=101))) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r101-d8_in1k-pre_832x832_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_160k_cityscapes.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | depth=101, 6 | init_cfg=dict( 7 | type='Pretrained', checkpoint='open-mmlab://resnet101_v1c')))) 8 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r101-d8_in1k-pre_832x832_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_80k_cityscapes.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | depth=101, 6 | init_cfg=dict( 7 | type='Pretrained', checkpoint='open-mmlab://resnet101_v1c')))) 8 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r18-d8_832x832_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_160k_cityscapes.py' 2 | model = dict( 3 | backbone=dict(layer_channels=(128, 512), backbone_cfg=dict(depth=18))) 4 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r18-d8_832x832_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_80k_cityscapes.py' 2 | model = dict( 3 | backbone=dict(layer_channels=(128, 512), backbone_cfg=dict(depth=18))) 4 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r50-d8_832x832_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/icnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_832x832.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_160k.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r50-d8_832x832_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/icnet_r50-d8.py', 3 | '../_base_/datasets/cityscapes_832x832.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_80k.py' 5 | ] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r50-d8_in1k-pre_832x832_160k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_160k_cityscapes.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/icnet/icnet_r50-d8_in1k-pre_832x832_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_832x832_80k_cityscapes.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x1024_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x512_20k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x512_40k_voc12aug.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_512x512_80k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_769x769_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_769x769_40k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r101-d8_769x769_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_769x769_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_r50-d8.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x512_20k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x512_40k_voc12aug.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/isanet/isanet_r50-d8_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/isanet_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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_480x480_40k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_480x480_40k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_480x480_80k_pascal_context_59.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_480x480_80k_pascal_context_59.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_4x4_512x512_80k_potsdam.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4x4_512x512_80k_potsdam.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_4x4_512x512_80k_vaihingen.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4x4_512x512_80k_vaihingen.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x1024_40k_dark.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_40k_dark.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x1024_40k_night_driving.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_40k_night_driving.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_4x4_160k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_4x4_20k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_4x4_20k_coco-stuff10k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_4x4_40k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_4x4_40k_coco-stuff10k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_4x4_80k_coco-stuff164k.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_4x4_80k_coco-stuff164k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_512x512_80k_loveda.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x512_80k_loveda.py' 2 | model = dict( 3 | backbone=dict( 4 | depth=101, 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet101_v1c'))) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r101-d8_512x1024_80k_cityscapes.py' 2 | # fp16 settings 3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) 4 | # fp16 placeholder 5 | fp16 = dict() 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101b-d8_512x1024_80k_dark.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_dark.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r101b-d8_512x1024_80k_night_driving.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_512x1024_80k_night_driving.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d32_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 | model = dict(backbone=dict(dilations=(1, 1, 2, 4), strides=(1, 2, 2, 2))) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_4x4_512x512_80k_potsdam.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/potsdam.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=6), auxiliary_head=dict(num_classes=6)) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_4x4_512x512_80k_vaihingen.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/vaihingen.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=6), auxiliary_head=dict(num_classes=6)) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_4x4_896x896_80k_isaid.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/isaid.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=16), auxiliary_head=dict(num_classes=16)) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_512x512_4x4_20k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/coco-stuff10k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=171), auxiliary_head=dict(num_classes=171)) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_512x512_4x4_40k_coco-stuff10k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/coco-stuff10k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=171), auxiliary_head=dict(num_classes=171)) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/pspnet/pspnet_r50-d8_512x512_80k_loveda.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/loveda.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | model = dict( 6 | decode_head=dict(num_classes=7), auxiliary_head=dict(num_classes=7)) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/sem_fpn/fpn_r101_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x1024_80k_cityscapes.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/sem_fpn/fpn_r101_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_512x512_160k_ade20k.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/sem_fpn/fpn_r50_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fpn_r50.py', '../_base_/datasets/cityscapes.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/sem_fpn/fpn_r50_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fpn_r50.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' 4 | ] 5 | model = dict(decode_head=dict(num_classes=150)) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/setr/setr_mla_512x512_160k_b16_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./setr_mla_512x512_160k_b8_ade20k.py'] 2 | 3 | # num_gpus: 8 -> batch_size: 16 4 | data = dict(samples_per_gpu=2) 5 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/stdc/stdc2_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './stdc1_512x1024_80k_cityscapes.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(stdc_type='STDCNet2'))) 3 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/twins/twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/twins_pcpvt-s_fpn.py', '../_base_/datasets/ade20k.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' 4 | ] 5 | 6 | optimizer = dict(_delete_=True, type='AdamW', lr=0.0001, weight_decay=0.0001) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_unet_s5-d16_256x256_40k_hrf.py' 2 | model = dict( 3 | decode_head=dict(loss_decode=[ 4 | dict(type='CrossEntropyLoss', loss_name='loss_ce', loss_weight=1.0), 5 | dict(type='DiceLoss', loss_name='loss_dice', loss_weight=3.0) 6 | ])) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_unet_s5-d16_64x64_40k_drive.py' 2 | model = dict( 3 | decode_head=dict(loss_decode=[ 4 | dict(type='CrossEntropyLoss', loss_name='loss_ce', loss_weight=1.0), 5 | dict(type='DiceLoss', loss_name='loss_dice', loss_weight=3.0) 6 | ])) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/upernet/upernet_r18_512x1024_40k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x1024_40k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict(in_channels=[64, 128, 256, 512]), 6 | auxiliary_head=dict(in_channels=256)) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/upernet/upernet_r18_512x1024_80k_cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_512x1024_80k_cityscapes.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict(in_channels=[64, 128, 256, 512]), 6 | auxiliary_head=dict(in_channels=256)) 7 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/vit/upernet_deit-b16_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_base_patch16_224-b5f2ef4d.pth', 5 | backbone=dict(drop_path_rate=0.1), 6 | neck=None) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/vit/upernet_deit-b16_512x512_80k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_vit-b16_mln_512x512_80k_ade20k.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_base_patch16_224-b5f2ef4d.pth', 5 | backbone=dict(drop_path_rate=0.1), 6 | neck=None) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/vit/upernet_deit-b16_ln_mln_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_base_patch16_224-b5f2ef4d.pth', 5 | backbone=dict(drop_path_rate=0.1, final_norm=True)) 6 | -------------------------------------------------------------------------------- /downstream/segmentation/configs/vit/upernet_deit-b16_mln_512x512_160k_ade20k.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_base_patch16_224-b5f2ef4d.pth', 5 | backbone=dict(drop_path_rate=0.1), 6 | ) 7 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/core/hook/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .wandblogger_hook import MMSegWandbHook 3 | 4 | __all__ = ['MMSegWandbHook'] 5 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/core/optimizers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .layer_decay_optimizer_constructor import ( 3 | LayerDecayOptimizerConstructor, LearningRateDecayOptimizerConstructor) 4 | 5 | __all__ = [ 6 | 'LearningRateDecayOptimizerConstructor', 'LayerDecayOptimizerConstructor' 7 | ] 8 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/core/seg/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .builder import build_pixel_sampler 3 | from .sampler import BasePixelSampler, OHEMPixelSampler 4 | 5 | __all__ = ['build_pixel_sampler', 'BasePixelSampler', 'OHEMPixelSampler'] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/core/seg/sampler/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_pixel_sampler import BasePixelSampler 3 | from .ohem_pixel_sampler import OHEMPixelSampler 4 | 5 | __all__ = ['BasePixelSampler', 'OHEMPixelSampler'] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/core/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .dist_util import check_dist_init, sync_random_seed 3 | from .misc import add_prefix 4 | 5 | __all__ = ['add_prefix', 'check_dist_init', 'sync_random_seed'] 6 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/datasets/samplers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .distributed_sampler import DistributedSampler 3 | 4 | __all__ = ['DistributedSampler'] 5 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/models/segmentors/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base import BaseSegmentor 3 | from .cascade_encoder_decoder import CascadeEncoderDecoder 4 | from .encoder_decoder import EncoderDecoder 5 | 6 | __all__ = ['BaseSegmentor', 'EncoderDecoder', 'CascadeEncoderDecoder'] 7 | -------------------------------------------------------------------------------- /downstream/segmentation/mmseg/ops/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .encoding import Encoding 3 | from .wrappers import Upsample, resize 4 | 5 | __all__ = ['Upsample', 'resize', 'Encoding'] 6 | -------------------------------------------------------------------------------- /downstream/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 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements.txt: -------------------------------------------------------------------------------- 1 | -r requirements/optional.txt 2 | -r requirements/runtime.txt 3 | -r requirements/tests.txt 4 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/docs.txt: -------------------------------------------------------------------------------- 1 | docutils==0.16.0 2 | myst-parser 3 | -e git+https://github.com/gaotongxiao/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme 4 | sphinx==4.0.2 5 | sphinx_copybutton 6 | sphinx_markdown_tables 7 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/mminstall.txt: -------------------------------------------------------------------------------- 1 | mmcls>=0.20.1 2 | mmcv-full>=1.4.4,<1.7.0 3 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/optional.txt: -------------------------------------------------------------------------------- 1 | cityscapesscripts 2 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/readthedocs.txt: -------------------------------------------------------------------------------- 1 | mmcv 2 | prettytable 3 | torch 4 | torchvision 5 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/runtime.txt: -------------------------------------------------------------------------------- 1 | matplotlib 2 | mmcls>=0.20.1 3 | numpy 4 | packaging 5 | prettytable 6 | -------------------------------------------------------------------------------- /downstream/segmentation/requirements/tests.txt: -------------------------------------------------------------------------------- 1 | codecov 2 | flake8 3 | interrogate 4 | pytest 5 | xdoctest>=0.10.0 6 | yapf 7 | -------------------------------------------------------------------------------- /downstream/segmentation/result.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/downstream/segmentation/result.jpg -------------------------------------------------------------------------------- /downstream/segmentation/tools/finished_sh/direct_train_pvt_t.sh: -------------------------------------------------------------------------------- 1 | # #!/usr/bin/env bash 2 | torchrun --nproc_per_node 8 --master_port=25700 tools/train.py configs/slide_pvt/fpn_slide_pvt_t.py \ 3 | --launcher="pytorch" --load-from './data/pvt_t_model.pth' -------------------------------------------------------------------------------- /figures/fig1_ssm_vs_linear.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig1_ssm_vs_linear.jpg -------------------------------------------------------------------------------- /figures/fig2_block.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig2_block.jpg -------------------------------------------------------------------------------- /figures/fig3_ablation.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig3_ablation.png -------------------------------------------------------------------------------- /figures/fig4_cls.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig4_cls.png -------------------------------------------------------------------------------- /figures/fig5_speed.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig5_speed.jpg -------------------------------------------------------------------------------- /figures/fig6_det.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig6_det.png -------------------------------------------------------------------------------- /figures/fig7_seg.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/LeapLabTHU/MLLA/e5dd44654b047d6e4c2f5c016220a260cdc36a76/figures/fig7_seg.png -------------------------------------------------------------------------------- /models/__init__.py: -------------------------------------------------------------------------------- 1 | from .build import build_model --------------------------------------------------------------------------------