├── .gitignore ├── LICENSE ├── README.md ├── TextRegionSegmenter.py ├── assets ├── boats_ambulance.jpg ├── dino_two_dogs.jpg ├── sam2_truck.jpg └── teaser.png ├── configs ├── .DS_Store ├── base_config.py ├── cfg_ds │ ├── cfg_ade20k.py │ ├── cfg_city_scapes.py │ ├── cfg_coco_object.py │ ├── cfg_coco_stuff164k.py │ ├── cfg_context59.py │ ├── cfg_context60.py │ ├── cfg_voc20.py │ └── cfg_voc21.py ├── cls_ade20k.txt ├── cls_ade20k847.txt ├── cls_city_scapes.txt ├── cls_coco_object.txt ├── cls_coco_stuff.txt ├── cls_context459.txt ├── cls_context59.txt ├── cls_context60.txt ├── cls_voc20.txt ├── cls_voc21.txt └── my_name.txt ├── core ├── args.py ├── checkpoint.py ├── data │ ├── conversation.py │ ├── data.py │ ├── data_collators.py │ ├── data_mixer.py │ ├── dataloader.py │ └── preprocessor.py ├── distributed.py ├── logger.py ├── metrics.py ├── optim.py ├── probe.py ├── profiling.py ├── stool.py ├── tests │ ├── Rock-climbing-Canada-1920x1147.jpg │ ├── dataloader_test.py │ ├── llama3_tokenizer_test.py │ ├── ocrbench_centre.jpg │ └── selfie_cathedral_peak.jpg ├── tokenizer.py ├── transformer.py ├── transforms │ ├── image_transform.py │ ├── region_transform.py │ └── video_transform.py ├── utils.py ├── vision_encoder │ ├── __init__.py │ ├── bpe_simple_vocab_16e6.txt.gz │ ├── config.py │ ├── pe.py │ ├── rope.py │ ├── tokenizer.py │ └── transforms.py └── vision_projector │ ├── base.py │ └── mlp.py ├── custom_clip ├── __init__.py ├── bpe_simple_vocab_16e6.txt.gz ├── clip.py ├── model.py └── simple_tokenizer.py ├── custom_datasets.py ├── custom_open_clip ├── __init__.py ├── big_vision.py ├── bpe_simple_vocab_16e6.txt.gz ├── coca_model.py ├── constants.py ├── factory.py ├── hf_configs.py ├── hf_model.py ├── loss.py ├── model.py ├── model_configs │ ├── EVA01-g-14-plus.json │ ├── EVA01-g-14.json │ ├── EVA02-B-16.json │ ├── EVA02-E-14-plus.json │ ├── EVA02-E-14.json │ ├── EVA02-L-14-336.json │ ├── EVA02-L-14.json │ ├── RN50x16.json │ ├── ViT-B-16-SigLIP-256.json │ ├── ViT-B-16-SigLIP-384.json │ ├── ViT-B-16-SigLIP-512.json │ ├── ViT-B-16-SigLIP-i18n-256.json │ ├── ViT-B-16-SigLIP.json │ ├── ViT-B-16-plus-240.json │ ├── ViT-B-16-plus.json │ ├── ViT-B-16-quickgelu.json │ ├── ViT-B-16.json │ ├── ViT-B-32-256.json │ ├── ViT-B-32-plus-256.json │ ├── ViT-B-32-quickgelu.json │ ├── ViT-B-32.json │ ├── ViT-H-14-378-quickgelu.json │ ├── ViT-H-14-CLIPA-336.json │ ├── ViT-H-14-CLIPA.json │ ├── ViT-H-14-quickgelu.json │ ├── ViT-H-14.json │ ├── ViT-H-16.json │ ├── ViT-L-14-280.json │ ├── ViT-L-14-336.json │ ├── ViT-L-14-CLIPA-336.json │ ├── ViT-L-14-CLIPA.json │ ├── ViT-L-14-quickgelu.json │ ├── ViT-L-14.json │ ├── ViT-L-16-320.json │ ├── ViT-L-16-SigLIP-256.json │ ├── ViT-L-16-SigLIP-384.json │ ├── ViT-L-16.json │ ├── ViT-M-16-alt.json │ ├── ViT-M-16.json │ ├── ViT-M-32-alt.json │ ├── ViT-M-32.json │ ├── ViT-S-16-alt.json │ ├── ViT-S-16.json │ ├── ViT-S-32-alt.json │ ├── ViT-S-32.json │ ├── ViT-SO400M-14-SigLIP-384.json │ ├── ViT-SO400M-14-SigLIP.json │ ├── ViT-bigG-14-CLIPA-336.json │ ├── ViT-bigG-14-CLIPA.json │ ├── ViT-bigG-14.json │ ├── ViT-e-14.json │ ├── ViT-g-14.json │ ├── coca_ViT-B-32.json │ ├── coca_ViT-L-14.json │ ├── coca_base.json │ ├── coca_roberta-ViT-B-32.json │ ├── vit_medium_patch16_gap_256.json │ └── vit_relpos_medium_patch16_cls_224.json ├── modified_resnet.py ├── openai.py ├── pos_embed.py ├── pretrained.py ├── push_to_hf_hub.py ├── timm_model.py ├── tokenizer.py ├── transform.py ├── transformer.py ├── utils.py ├── version.py ├── zero_shot_classifier.py └── zero_shot_metadata.py ├── datasets ├── city_scapes.py ├── coco_stuff164k.py ├── cvt_coco_object.py └── pascal_context.py ├── dist_eval_semantic.sh ├── eval_all_semantic.py ├── eval_reason_seg.py ├── eval_referring.py ├── eval_semantic.py ├── mmengine ├── .DS_Store ├── __init__.py ├── _strategy │ ├── __init__.py │ ├── base.py │ ├── colossalai.py │ ├── deepspeed.py │ ├── distributed.py │ ├── fsdp.py │ ├── single_device.py │ └── utils.py ├── analysis │ ├── __init__.py │ ├── complexity_analysis.py │ ├── jit_analysis.py │ ├── jit_handles.py │ └── print_helper.py ├── config │ ├── __init__.py │ ├── config.py │ ├── lazy.py │ └── utils.py ├── dataset │ ├── __init__.py │ ├── base_dataset.py │ ├── dataset_wrapper.py │ ├── sampler.py │ └── utils.py ├── device │ ├── __init__.py │ └── utils.py ├── dist │ ├── __init__.py │ ├── dist.py │ └── utils.py ├── evaluator │ ├── __init__.py │ ├── evaluator.py │ ├── metric.py │ └── utils.py ├── fileio │ ├── __init__.py │ ├── backends │ │ ├── __init__.py │ │ ├── base.py │ │ ├── http_backend.py │ │ ├── lmdb_backend.py │ │ ├── local_backend.py │ │ ├── memcached_backend.py │ │ ├── petrel_backend.py │ │ └── registry_utils.py │ ├── file_client.py │ ├── handlers │ │ ├── __init__.py │ │ ├── base.py │ │ ├── json_handler.py │ │ ├── pickle_handler.py │ │ ├── registry_utils.py │ │ └── yaml_handler.py │ ├── io.py │ └── parse.py ├── hooks │ ├── __init__.py │ ├── checkpoint_hook.py │ ├── early_stopping_hook.py │ ├── ema_hook.py │ ├── empty_cache_hook.py │ ├── hook.py │ ├── iter_timer_hook.py │ ├── logger_hook.py │ ├── naive_visualization_hook.py │ ├── param_scheduler_hook.py │ ├── profiler_hook.py │ ├── runtime_info_hook.py │ ├── sampler_seed_hook.py │ ├── sync_buffer_hook.py │ └── test_time_aug_hook.py ├── hub │ ├── __init__.py │ ├── deprecated.json │ ├── hub.py │ ├── mmcls.json │ ├── openmmlab.json │ └── torchvision_0.12.json ├── infer │ ├── __init__.py │ └── infer.py ├── logging │ ├── __init__.py │ ├── history_buffer.py │ ├── logger.py │ └── message_hub.py ├── model │ ├── __init__.py │ ├── averaged_model.py │ ├── base_model │ │ ├── __init__.py │ │ ├── base_model.py │ │ └── data_preprocessor.py │ ├── base_module.py │ ├── efficient_conv_bn_eval.py │ ├── test_time_aug.py │ ├── utils.py │ ├── weight_init.py │ └── wrappers │ │ ├── __init__.py │ │ ├── distributed.py │ │ ├── fully_sharded_distributed.py │ │ ├── seperate_distributed.py │ │ └── utils.py ├── optim │ ├── __init__.py │ ├── optimizer │ │ ├── __init__.py │ │ ├── amp_optimizer_wrapper.py │ │ ├── apex_optimizer_wrapper.py │ │ ├── base.py │ │ ├── builder.py │ │ ├── default_constructor.py │ │ ├── optimizer_wrapper.py │ │ ├── optimizer_wrapper_dict.py │ │ └── zero_optimizer.py │ └── scheduler │ │ ├── __init__.py │ │ ├── lr_scheduler.py │ │ ├── momentum_scheduler.py │ │ └── param_scheduler.py ├── registry │ ├── __init__.py │ ├── build_functions.py │ ├── default_scope.py │ ├── registry.py │ ├── root.py │ └── utils.py ├── runner │ ├── __init__.py │ ├── _flexible_runner.py │ ├── activation_checkpointing.py │ ├── amp.py │ ├── base_loop.py │ ├── checkpoint.py │ ├── log_processor.py │ ├── loops.py │ ├── priority.py │ ├── runner.py │ └── utils.py ├── structures │ ├── __init__.py │ ├── base_data_element.py │ ├── instance_data.py │ ├── label_data.py │ └── pixel_data.py ├── testing │ ├── __init__.py │ ├── _internal │ │ ├── __init__.py │ │ └── distributed.py │ ├── compare.py │ └── runner_test_case.py ├── utils │ ├── __init__.py │ ├── dl_utils │ │ ├── __init__.py │ │ ├── collect_env.py │ │ ├── hub.py │ │ ├── misc.py │ │ ├── parrots_wrapper.py │ │ ├── setup_env.py │ │ ├── time_counter.py │ │ ├── torch_ops.py │ │ ├── trace.py │ │ └── visualize.py │ ├── manager.py │ ├── misc.py │ ├── package_utils.py │ ├── path.py │ ├── progressbar.py │ ├── progressbar_rich.py │ ├── timer.py │ └── version_utils.py ├── version.py └── visualization │ ├── __init__.py │ ├── utils.py │ ├── vis_backend.py │ └── visualizer.py ├── mmseg ├── .DS_Store ├── .mim │ ├── __init__.py │ ├── configs │ │ ├── __init__.py │ │ ├── _base_ │ │ │ ├── __init__.py │ │ │ ├── datasets │ │ │ │ ├── __init__.py │ │ │ │ ├── ade20k.py │ │ │ │ ├── ade20k_640x640.py │ │ │ │ ├── bdd100k.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 │ │ │ │ ├── hsi_drive.py │ │ │ │ ├── isaid.py │ │ │ │ ├── levir_256x256.py │ │ │ │ ├── loveda.py │ │ │ │ ├── mapillary_v1.py │ │ │ │ ├── mapillary_v1_65.py │ │ │ │ ├── mapillary_v2.py │ │ │ │ ├── nyu.py │ │ │ │ ├── nyu_512x512.py │ │ │ │ ├── pascal_context.py │ │ │ │ ├── pascal_context_59.py │ │ │ │ ├── pascal_voc12.py │ │ │ │ ├── pascal_voc12_aug.py │ │ │ │ ├── potsdam.py │ │ │ │ ├── refuge.py │ │ │ │ ├── stare.py │ │ │ │ ├── synapse.py │ │ │ │ └── vaihingen.py │ │ │ ├── default_runtime.py │ │ │ ├── models │ │ │ │ ├── __init__.py │ │ │ │ ├── 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_poolformer_s12.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 │ │ │ │ ├── san_vit-b16.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_mae.py │ │ │ │ ├── upernet_r50.py │ │ │ │ ├── upernet_swin.py │ │ │ │ ├── upernet_vit-b16_ln_mln.py │ │ │ │ └── vpd_sd.py │ │ │ └── schedules │ │ │ │ ├── __init__.py │ │ │ │ ├── schedule_160k.py │ │ │ │ ├── schedule_20k.py │ │ │ │ ├── schedule_240k.py │ │ │ │ ├── schedule_25k.py │ │ │ │ ├── schedule_320k.py │ │ │ │ ├── schedule_40k.py │ │ │ │ └── schedule_80k.py │ │ ├── ann │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── ann_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ann_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── ann_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ann_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── ann_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── ann_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ann_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ann_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── ann_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ann_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── ann_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ann_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── ann_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── ann_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ann_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ann_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── apcnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── apcnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── apcnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── apcnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── apcnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── apcnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── apcnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── apcnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── apcnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── apcnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── apcnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── apcnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── apcnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── beit │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── beit-base_upernet_8xb2-160k_ade20k-640x640.py │ │ │ ├── beit-base_upernet_8xb2-160k_ade20k-640x640_ms.py │ │ │ ├── beit-large_upernet_8xb1-amp-160k_ade20k-640x640.py │ │ │ ├── beit-large_upernet_8xb1-amp-160k_ade20k-640x640_ms.py │ │ │ └── metafile.yaml │ │ ├── bisenetv1 │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── bisenetv1_r101-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── bisenetv1_r101-d32_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── bisenetv1_r18-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv1_r18-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── bisenetv1_r18-d32-in1k-pre_4xb8-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv1_r18-d32_4xb4-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv1_r18-d32_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── bisenetv1_r50-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── bisenetv1_r50-d32_4xb4-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv1_r50-d32_4xb4-160k_coco-stuff164k-512x512.py │ │ │ └── metafile.yaml │ │ ├── bisenetv2 │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv2_fcn_4xb4-ohem-160k_cityscapes-1024x1024.py │ │ │ ├── bisenetv2_fcn_4xb8-160k_cityscapes-1024x1024.py │ │ │ └── metafile.yaml │ │ ├── ccnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── ccnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ccnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── ccnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ccnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── ccnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── ccnet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ccnet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ccnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── ccnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ccnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── ccnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ccnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── ccnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── ccnet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ccnet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ccnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── cgnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── cgnet_fcn_4xb4-60k_cityscapes-680x680.py │ │ │ ├── cgnet_fcn_4xb8-60k_cityscapes-512x1024.py │ │ │ └── metafile.yaml │ │ ├── convnext │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── convnext-base_upernet_8xb2-amp-160k_ade20k-512x512.py │ │ │ ├── convnext-base_upernet_8xb2-amp-160k_ade20k-640x640.py │ │ │ ├── convnext-large_upernet_8xb2-amp-160k_ade20k-640x640.py │ │ │ ├── convnext-small_upernet_8xb2-amp-160k_ade20k-512x512.py │ │ │ ├── convnext-tiny_upernet_8xb2-amp-160k_ade20k-512x512.py │ │ │ ├── convnext-xlarge_upernet_8xb2-amp-160k_ade20k-640x640.py │ │ │ └── metafile.yaml │ │ ├── danet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── danet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── danet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── danet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── danet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── danet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── danet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── danet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── danet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── danet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── danet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── danet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── danet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── danet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── danet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── danet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── danet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── ddrnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py │ │ │ ├── ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py │ │ │ └── metafile.yaml │ │ ├── deeplabv3 │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── deeplabv3_r101-d16-mg124_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101-d16-mg124_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-20k_coco-stuff10k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-320k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-40k_coco-stuff10k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── deeplabv3_r101-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-80k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r101-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── deeplabv3_r101-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3_r101b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r101b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r18-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r18-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r18b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r18b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-20k_coco-stuff10k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-320k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-40k_coco-stuff10k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── deeplabv3_r50-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-80k_coco-stuff164k-512x512.py │ │ │ ├── deeplabv3_r50-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── deeplabv3_r50-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3_r50b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3_r50b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ └── metafile.yaml │ │ ├── deeplabv3plus │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── deeplabv3plus_r101-d16-mg124_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101-d16-mg124_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── deeplabv3plus_r101-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── deeplabv3plus_r101b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r101b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r18-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r18-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r18-d8_4xb4-80k_isaid-896x896.py │ │ │ ├── deeplabv3plus_r18-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── deeplabv3plus_r18-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── deeplabv3plus_r18-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── deeplabv3plus_r18b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r18b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r50-d8_4xb2-300k_mapillay_v1_65-1280x1280.py │ │ │ ├── deeplabv3plus_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_isaid-896x896.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── deeplabv3plus_r50-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── deeplabv3plus_r50b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── deeplabv3plus_r50b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ └── metafile.yaml │ │ ├── dmnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── dmnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── dmnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── dmnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── dmnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── dmnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── dmnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── dmnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── dmnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── dmnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── dmnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── dmnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── dmnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── dnlnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── dnl_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── dnl_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── dnl_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── dnl_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── dnl_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── dnl_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── dnl_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── dnl_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── dnl_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── dnl_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── dnl_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── dnl_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── dpt │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── dpt_vit-b16_8xb2-160k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── dsdl │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── cityscapes.py │ │ │ └── voc.py │ │ ├── emanet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── emanet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── emanet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── emanet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── emanet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ └── metafile.yaml │ │ ├── encnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── encnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── encnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── encnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── encnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── encnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── encnet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── encnet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── encnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── encnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── encnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── encnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── encnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── encnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── encnet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── encnet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── encnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── encnet_r50s-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── erfnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── erfnet_fcn_4xb4-160k_cityscapes-512x1024.py │ │ │ └── metafile.yaml │ │ ├── fastfcn │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fastfcn_r50-d32_jpu_aspp_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fastfcn_r50-d32_jpu_aspp_4xb4-160k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_aspp_4xb4-80k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_aspp_4xb4-80k_cityscapes-512x1024.py │ │ │ ├── fastfcn_r50-d32_jpu_enc_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fastfcn_r50-d32_jpu_enc_4xb4-160k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_enc_4xb4-80k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_enc_4xb4-80k_cityscapes-512x1024.py │ │ │ ├── fastfcn_r50-d32_jpu_psp_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fastfcn_r50-d32_jpu_psp_4xb4-160k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_psp_4xb4-80k_ade20k-512x512.py │ │ │ ├── fastfcn_r50-d32_jpu_psp_4xb4-80k_cityscapes-512x1024.py │ │ │ └── metafile.yaml │ │ ├── fastscnn │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fast_scnn_8xb4-160k_cityscapes-512x1024.py │ │ │ └── metafile.yaml │ │ ├── fcn │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fcn-d6_r101-d16_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r101-d16_4xb2-40k_cityscapes-769x769.py │ │ │ ├── fcn-d6_r101-d16_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r101-d16_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn-d6_r101b-d16_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r101b-d16_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn-d6_r50-d16_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r50-d16_4xb2-40k_cityscapes-769x769.py │ │ │ ├── fcn-d6_r50-d16_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r50-d16_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn-d6_r50b-d16_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn-d6_r50b-d16_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── fcn_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── fcn_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── fcn_r101-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── fcn_r101-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── fcn_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── fcn_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── fcn_r101-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── fcn_r101-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── fcn_r101b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r101b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r18-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r18-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r18b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r18b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── fcn_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── fcn_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── fcn_r50-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── fcn_r50-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── fcn_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── fcn_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── fcn_r50-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── fcn_r50-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── fcn_r50b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_r50b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ └── metafile.yaml │ │ ├── gcnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── gcnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── gcnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── gcnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── gcnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── gcnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── gcnet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── gcnet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── gcnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── gcnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── gcnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── gcnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── gcnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── gcnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── gcnet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── gcnet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── gcnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── hrnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fcn_hr18_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18_4xb4-160k_ade20k-512x512.py │ │ │ ├── fcn_hr18_4xb4-20k_voc12aug-512x512.py │ │ │ ├── fcn_hr18_4xb4-40k_pascal-context-480x480.py │ │ │ ├── fcn_hr18_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr18_4xb4-40k_voc12aug-512x512.py │ │ │ ├── fcn_hr18_4xb4-80k_ade20k-512x512.py │ │ │ ├── fcn_hr18_4xb4-80k_isaid-896x896.py │ │ │ ├── fcn_hr18_4xb4-80k_loveda-512x512.py │ │ │ ├── fcn_hr18_4xb4-80k_pascal-context-480x480.py │ │ │ ├── fcn_hr18_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr18_4xb4-80k_potsdam-512x512.py │ │ │ ├── fcn_hr18_4xb4-80k_vaihingen-512x512.py │ │ │ ├── fcn_hr18s_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18s_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18s_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_hr18s_4xb4-160k_ade20k-512x512.py │ │ │ ├── fcn_hr18s_4xb4-20k_voc12aug-512x512.py │ │ │ ├── fcn_hr18s_4xb4-40k_pascal-context-480x480.py │ │ │ ├── fcn_hr18s_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr18s_4xb4-40k_voc12aug-512x512.py │ │ │ ├── fcn_hr18s_4xb4-80k_ade20k-512x512.py │ │ │ ├── fcn_hr18s_4xb4-80k_isaid-896x896.py │ │ │ ├── fcn_hr18s_4xb4-80k_loveda-512x512.py │ │ │ ├── fcn_hr18s_4xb4-80k_pascal-context-480x480.py │ │ │ ├── fcn_hr18s_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr18s_4xb4-80k_potsdam-512x512.py │ │ │ ├── fcn_hr18s_4xb4-80k_vaihingen-512x512.py │ │ │ ├── fcn_hr48_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── fcn_hr48_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── fcn_hr48_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fcn_hr48_4xb4-160k_ade20k-512x512.py │ │ │ ├── fcn_hr48_4xb4-20k_voc12aug-512x512.py │ │ │ ├── fcn_hr48_4xb4-40k_pascal-context-480x480.py │ │ │ ├── fcn_hr48_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr48_4xb4-40k_voc12aug-512x512.py │ │ │ ├── fcn_hr48_4xb4-80k_ade20k-512x512.py │ │ │ ├── fcn_hr48_4xb4-80k_isaid-896x896.py │ │ │ ├── fcn_hr48_4xb4-80k_loveda-512x512.py │ │ │ ├── fcn_hr48_4xb4-80k_pascal-context-480x480.py │ │ │ ├── fcn_hr48_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── fcn_hr48_4xb4-80k_potsdam-512x512.py │ │ │ ├── fcn_hr48_4xb4-80k_vaihingen-512x512.py │ │ │ └── metafile.yaml │ │ ├── icnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── icnet_r101-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r101-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py │ │ │ ├── icnet_r101-d8_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r101-d8_4xb2-80k_cityscapes-832x832.py │ │ │ ├── icnet_r18-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r18-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py │ │ │ ├── icnet_r18-d8_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r18-d8_4xb2-80k_cityscapes-832x832.py │ │ │ ├── icnet_r50-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r50-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py │ │ │ ├── icnet_r50-d8_4xb2-160k_cityscapes-832x832.py │ │ │ ├── icnet_r50-d8_4xb2-80k_cityscapes-832x832.py │ │ │ └── metafile.yaml │ │ ├── isanet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── isanet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── isanet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── isanet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── isanet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── isanet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── isanet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── isanet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── isanet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── isanet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── isanet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── isanet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── isanet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── isanet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── isanet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── isanet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── isanet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── knet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── knet-s3_r50-d8_deeplabv3_8xb2-adamw-80k_ade20k-512x512.py │ │ │ ├── knet-s3_r50-d8_fcn_8xb2-adamw-80k_ade20k-512x512.py │ │ │ ├── knet-s3_r50-d8_pspnet_8xb2-adamw-80k_ade20k-512x512.py │ │ │ ├── knet-s3_r50-d8_upernet_8xb2-adamw-80k_ade20k-512x512.py │ │ │ ├── knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-512x512.py │ │ │ ├── knet-s3_swin-l_upernet_8xb2-adamw-80k_ade20k-640x640.py │ │ │ ├── knet-s3_swin-t_upernet_8xb2-adamw-80k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── mae │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── mae-base_upernet_8xb2-amp-160k_ade20k-512x512-ms.py │ │ │ ├── mae-base_upernet_8xb2-amp-160k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── mask2former │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── mask2former_r101_8xb2-160k_ade20k-512x512.py │ │ │ ├── mask2former_r101_8xb2-90k_cityscapes-512x1024.py │ │ │ ├── mask2former_r50_8xb2-160k_ade20k-512x512.py │ │ │ ├── mask2former_r50_8xb2-90k_cityscapes-512x1024.py │ │ │ ├── mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640.py │ │ │ ├── mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py │ │ │ ├── mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024.py │ │ │ ├── mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py │ │ │ ├── mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024.py │ │ │ ├── mask2former_swin-s_8xb2-160k_ade20k-512x512.py │ │ │ ├── mask2former_swin-s_8xb2-90k_cityscapes-512x1024.py │ │ │ ├── mask2former_swin-t_8xb2-160k_ade20k-512x512.py │ │ │ ├── mask2former_swin-t_8xb2-90k_cityscapes-512x1024.py │ │ │ └── metafile.yaml │ │ ├── maskformer │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── maskformer_r101-d32_8xb2-160k_ade20k-512x512.py │ │ │ ├── maskformer_r50-d32_8xb2-160k_ade20k-512x512.py │ │ │ ├── maskformer_swin-s_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── maskformer_swin-t_upernet_8xb2-160k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── mobilenet_v2 │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── mobilenet-v2-d8_deeplabv3_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── mobilenet-v2-d8_deeplabv3_4xb4-160k_ade20k-512x512.py │ │ │ ├── mobilenet-v2-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── mobilenet-v2-d8_deeplabv3plus_4xb4-160k_ade20k-512x512.py │ │ │ ├── mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── mobilenet-v2-d8_fcn_4xb4-160k_ade20k-512x512.py │ │ │ ├── mobilenet-v2-d8_pspnet_4xb2-80k_cityscapes-512x1024.py │ │ │ └── mobilenet-v2-d8_pspnet_4xb4-160k_ade20k-512x512.py │ │ ├── mobilenet_v3 │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── mobilenet-v3-d8-s_lraspp_4xb4-320k_cityscapes-512x1024.py │ │ │ ├── mobilenet-v3-d8-scratch-s_lraspp_4xb4-320k_cityscapes-512x1024.py │ │ │ ├── mobilenet-v3-d8-scratch_lraspp_4xb4-320k_cityscapes-512x1024.py │ │ │ └── mobilenet-v3-d8_lraspp_4xb4-320k_cityscapes-512x1024.py │ │ ├── nonlocal_net │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── nonlocal_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── nonlocal_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── nonlocal_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── nonlocal_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── nonlocal_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── nonlocal_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── nonlocal_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── nonlocal_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── nonlocal_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── nonlocal_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── nonlocal_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── nonlocal_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── nonlocal_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── nonlocal_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── nonlocal_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ └── nonlocal_r50-d8_4xb4-80k_ade20k-512x512.py │ │ ├── ocrnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── ocrnet_hr18_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18_4xb4-160k_ade20k-512x512.py │ │ │ ├── ocrnet_hr18_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr18_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr18_4xb4-80k_ade20k-512x512.py │ │ │ ├── ocrnet_hr18s_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18s_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18s_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr18s_4xb4-160k_ade20k-512x512.py │ │ │ ├── ocrnet_hr18s_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr18s_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr18s_4xb4-80k_ade20k-512x512.py │ │ │ ├── ocrnet_hr48_4xb2-160k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr48_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr48_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── ocrnet_hr48_4xb4-160k_ade20k-512x512.py │ │ │ ├── ocrnet_hr48_4xb4-20k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr48_4xb4-40k_voc12aug-512x512.py │ │ │ ├── ocrnet_hr48_4xb4-80k_ade20k-512x512.py │ │ │ ├── ocrnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── ocrnet_r101-d8_8xb2-40k_cityscapes-512x1024.py │ │ │ └── ocrnet_r101-d8_8xb2-80k_cityscapes-512x1024.py │ │ ├── pidnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── pidnet-l_2xb6-120k_1024x1024-cityscapes.py │ │ │ ├── pidnet-m_2xb6-120k_1024x1024-cityscapes.py │ │ │ └── pidnet-s_2xb6-120k_1024x1024-cityscapes.py │ │ ├── point_rend │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── pointrend_r101_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pointrend_r101_4xb4-160k_ade20k-512x512.py │ │ │ ├── pointrend_r50_4xb2-80k_cityscapes-512x1024.py │ │ │ └── pointrend_r50_4xb4-160k_ade20k-512x512.py │ │ ├── poolformer │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fpn_poolformer_m36_8xb4-40k_ade20k-512x512.py │ │ │ ├── fpn_poolformer_m48_8xb4-40k_ade20k-512x512.py │ │ │ ├── fpn_poolformer_s12_8xb4-40k_ade20k-512x512.py │ │ │ ├── fpn_poolformer_s24_8xb4-40k_ade20k-512x512.py │ │ │ ├── fpn_poolformer_s36_8x4_512x512_40k_ade20k.py │ │ │ └── metafile.yaml │ │ ├── psanet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── psanet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── psanet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── psanet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── psanet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── psanet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── psanet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── psanet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── psanet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── psanet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── psanet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── psanet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── psanet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── psanet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── psanet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── psanet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ └── psanet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ ├── pspnet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── pspnet_r101-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── pspnet_r101-d8_4xb2-40k_cityscapes-512x1024_dark-zurich-1920x1080.py │ │ │ ├── pspnet_r101-d8_4xb2-40k_cityscapes-512x1024_night-driving-1920x1080.py │ │ │ ├── pspnet_r101-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── pspnet_r101-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r101-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── pspnet_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r101-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-20k_coco-stuff10k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-320k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-40k_coco-stuff10k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── pspnet_r101-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── pspnet_r101-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── pspnet_r101-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024_dark-zurich-1920x1080.py │ │ │ ├── pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024_night-driving-1920x1080.py │ │ │ ├── pspnet_r101b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── pspnet_r18-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r18-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── pspnet_r18-d8_4xb4-80k_isaid-896x896.py │ │ │ ├── pspnet_r18-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── pspnet_r18-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── pspnet_r18-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── pspnet_r18b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r18b-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── pspnet_r50-d32_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50-d32_rsb_4xb2-adamw-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50-d8-rsb_4xb2-adamw-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50-d8_4xb2-40k_cityscapes-512x1024_dark-zurich-1920x1080.py │ │ │ ├── pspnet_r50-d8_4xb2-40k_cityscapes-512x1024_night-driving-1920x1080.py │ │ │ ├── pspnet_r50-d8_4xb2-40k_cityscapes-769x769.py │ │ │ ├── pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50-d8_4xb2-80k_cityscapes-512x1024_dark-zurich-1920x1080.py │ │ │ ├── pspnet_r50-d8_4xb2-80k_cityscapes-512x1024_night-driving-1920x1080.py │ │ │ ├── pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py │ │ │ ├── pspnet_r50-d8_4xb4-160k_ade20k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-160k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-20k_coco-stuff10k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-20k_voc12aug-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-320k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-40k_coco-stuff10k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-40k_pascal-context-480x480.py │ │ │ ├── pspnet_r50-d8_4xb4-40k_pascal-context-59-480x480.py │ │ │ ├── pspnet_r50-d8_4xb4-40k_voc12aug-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_ade20k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_coco-stuff164k-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_isaid-896x896.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_loveda-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_pascal-context-480x480.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_pascal-context-59-480x480.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_potsdam-512x512.py │ │ │ ├── pspnet_r50-d8_4xb4-80k_vaihingen-512x512.py │ │ │ ├── pspnet_r50b-d32_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── pspnet_r50b-d8_4xb2-80k_cityscapes-512x1024.py │ │ │ └── pspnet_r50b-d8_4xb2-80k_cityscapes-769x769.py │ │ ├── resnest │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── resnest_s101-d8_deeplabv3_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── resnest_s101-d8_deeplabv3_4xb4-160k_ade20k-512x512.py │ │ │ ├── resnest_s101-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── resnest_s101-d8_deeplabv3plus_4xb4-160k_ade20k-512x512.py │ │ │ ├── resnest_s101-d8_fcn_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── resnest_s101-d8_fcn_4xb4-160k_ade20k-512x512.py │ │ │ ├── resnest_s101-d8_pspnet_4xb2-80k_cityscapes512x1024.py │ │ │ └── resnest_s101-d8_pspnet_4xb4-160k_ade20k-512x512.py │ │ ├── san │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── san-vit-b16_coco-stuff164k-640x640.py │ │ │ ├── san-vit-b16_pascal_context-640x640.py │ │ │ ├── san-vit-b16_voc12aug-640x640.py │ │ │ ├── san-vit-l14_coco-stuff164k-640x640.py │ │ │ ├── san-vit-l14_pascal_context-640x640.py │ │ │ └── san-vit-l14_voc12aug-640x640.py │ │ ├── segformer │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── segformer_mit-b0_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b0_8xb2-160k_ade20k-512x512.py │ │ │ ├── segformer_mit-b1_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b1_8xb2-160k_ade20k-512x512.py │ │ │ ├── segformer_mit-b2_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b2_8xb2-160k_ade20k-512x512.py │ │ │ ├── segformer_mit-b3_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b3_8xb2-160k_ade20k-512x512.py │ │ │ ├── segformer_mit-b4_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b4_8xb2-160k_ade20k-512x512.py │ │ │ ├── segformer_mit-b5_8xb1-160k_cityscapes-1024x1024.py │ │ │ ├── segformer_mit-b5_8xb2-160k_ade20k-512x512.py │ │ │ └── segformer_mit-b5_8xb2-160k_ade20k-640x640.py │ │ ├── segmenter │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── segmenter_vit-b_mask_8xb1-160k_ade20k-512x512.py │ │ │ ├── segmenter_vit-l_mask_8xb1-160k_ade20k-512x512.py │ │ │ ├── segmenter_vit-s_fcn_8xb1-160k_ade20k-512x512.py │ │ │ ├── segmenter_vit-s_mask_8xb1-160k_ade20k-512x512.py │ │ │ └── segmenter_vit-t_mask_8xb1-160k_ade20k-512x512.py │ │ ├── segnext │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── segnext_mscan-b_1xb16-adamw-160k_ade20k-512x512.py │ │ │ ├── segnext_mscan-l_1xb16-adamw-160k_ade20k-512x512.py │ │ │ ├── segnext_mscan-s_1xb16-adamw-160k_ade20k-512x512.py │ │ │ └── segnext_mscan-t_1xb16-adamw-160k_ade20k-512x512.py │ │ ├── sem_fpn │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── fpn_r101_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fpn_r101_4xb4-160k_ade20k-512x512.py │ │ │ ├── fpn_r50_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── fpn_r50_4xb4-160k_ade20k-512x512.py │ │ │ └── metafile.yaml │ │ ├── setr │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── setr_vit-l-mla_8xb1-160k_ade20k-512x512.py │ │ │ ├── setr_vit-l_mla_8xb1-80k_cityscapes-768x768.py │ │ │ ├── setr_vit-l_mla_8xb2-160k_ade20k-512x512.py │ │ │ ├── setr_vit-l_naive_8xb1-80k_cityscapes-768x768.py │ │ │ ├── setr_vit-l_naive_8xb2-160k_ade20k-512x512.py │ │ │ ├── setr_vit-l_pup_8xb1-80k_cityscapes-768x768.py │ │ │ └── setr_vit-l_pup_8xb2-160k_ade20k-512x512.py │ │ ├── stdc │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── stdc1_4xb12-80k_cityscapes-512x1024.py │ │ │ ├── stdc1_in1k-pre_4xb12-80k_cityscapes-512x1024.py │ │ │ ├── stdc2_4xb12-80k_cityscapes-512x1024.py │ │ │ └── stdc2_in1k-pre_4xb12-80k_cityscapes-512x1024.py │ │ ├── swin │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── swin-base-patch4-window12-in1k-384x384-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-base-patch4-window12-in22k-384x384-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-base-patch4-window7-in1k-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-base-patch4-window7-in22k-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-large-patch4-window12-in22k-384x384-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-large-patch4-window7-in22k-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-small-patch4-window7-in1k-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── swin-tiny-patch4-window7-in1k-pre_upernet_8xb2-160k_ade20k-512x512.py │ │ │ └── swin-tiny-patch4-window7_upernet_1xb8-20k_levir-256x256.py │ │ ├── twins │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── twins_pcpvt-b_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ ├── twins_pcpvt-b_uperhead_8xb2-160k_ade20k-512x512.py │ │ │ ├── twins_pcpvt-l_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ ├── twins_pcpvt-l_uperhead_8xb2-160k_ade20k-512x512.py │ │ │ ├── twins_pcpvt-s_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ ├── twins_pcpvt-s_uperhead_8xb4-160k_ade20k-512x512.py │ │ │ ├── twins_svt-b_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ ├── twins_svt-b_uperhead_8xb2-160k_ade20k-512x512.py │ │ │ ├── twins_svt-l_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ ├── twins_svt-l_uperhead_8xb2-160k_ade20k-512x512.py │ │ │ ├── twins_svt-s_fpn_fpnhead_8xb4-80k_ade20k-512x512.py │ │ │ └── twins_svt-s_uperhead_8xb2-160k_ade20k-512x512.py │ │ ├── unet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-40k_stare-128x128.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py │ │ │ ├── unet-s5-d16_fcn_4xb4-160k_cityscapes-512x1024.py │ │ │ ├── unet-s5-d16_fcn_4xb4-160k_hsidrive-192x384.py │ │ │ ├── unet-s5-d16_fcn_4xb4-40k_chase-db1-128x128.py │ │ │ ├── unet-s5-d16_fcn_4xb4-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_fcn_4xb4-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_fcn_4xb4-40k_stare-128x128.py │ │ │ ├── unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py │ │ │ ├── unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-40k_chase-db1-128x128.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-40k_stare-128x128.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py │ │ │ ├── unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py │ │ │ └── unet_s5-d16_deeplabv3_4xb4-40k_chase-db1-128x128.py │ │ ├── upernet │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── upernet_r101_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── upernet_r101_4xb2-40k_cityscapes-769x769.py │ │ │ ├── upernet_r101_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── upernet_r101_4xb2-80k_cityscapes-769x769.py │ │ │ ├── upernet_r101_4xb4-160k_ade20k-512x512.py │ │ │ ├── upernet_r101_4xb4-20k_voc12aug-512x512.py │ │ │ ├── upernet_r101_4xb4-40k_voc12aug-512x512.py │ │ │ ├── upernet_r101_4xb4-80k_ade20k-512x512.py │ │ │ ├── upernet_r18_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── upernet_r18_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── upernet_r18_4xb4-160k_ade20k-512x512.py │ │ │ ├── upernet_r18_4xb4-20k_voc12aug-512x512.py │ │ │ ├── upernet_r18_4xb4-40k_voc12aug-512x512.py │ │ │ ├── upernet_r18_4xb4-80k_ade20k-512x512.py │ │ │ ├── upernet_r50_4xb2-40k_cityscapes-512x1024.py │ │ │ ├── upernet_r50_4xb2-40k_cityscapes-769x769.py │ │ │ ├── upernet_r50_4xb2-80k_cityscapes-512x1024.py │ │ │ ├── upernet_r50_4xb2-80k_cityscapes-769x769.py │ │ │ ├── upernet_r50_4xb4-160k_ade20k-512x512.py │ │ │ ├── upernet_r50_4xb4-20k_voc12aug-512x512.py │ │ │ ├── upernet_r50_4xb4-40k_voc12aug-512x512.py │ │ │ └── upernet_r50_4xb4-80k_ade20k-512x512.py │ │ ├── vit │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── vit_deit-b16-ln_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-b16_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-b16_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-b16_upernet_8xb2-80k_ade20k-512x512.py │ │ │ ├── vit_deit-s16-ln_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-s16_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-s16_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_deit-s16_upernet_8xb2-80k_ade20k-512x512.py │ │ │ ├── vit_vit-b16-ln_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ ├── vit_vit-b16_mln_upernet_8xb2-160k_ade20k-512x512.py │ │ │ └── vit_vit-b16_mln_upernet_8xb2-80k_ade20k-512x512.py │ │ └── vpd │ │ │ ├── README.md │ │ │ ├── __init__.py │ │ │ ├── metafile.yaml │ │ │ ├── vpd_sd_4xb8-25k_nyu-480x480.py │ │ │ └── vpd_sd_4xb8-25k_nyu-512x512.py │ ├── dataset-index.yml │ ├── model-index.yml │ └── tools │ │ ├── __init__.py │ │ ├── analysis_tools │ │ ├── __init__.py │ │ ├── analyze_logs.py │ │ ├── benchmark.py │ │ ├── browse_dataset.py │ │ ├── confusion_matrix.py │ │ ├── get_flops.py │ │ └── visualization_cam.py │ │ ├── dataset_converters │ │ ├── __init__.py │ │ ├── chase_db1.py │ │ ├── cityscapes.py │ │ ├── coco_stuff10k.py │ │ ├── coco_stuff164k.py │ │ ├── drive.py │ │ ├── hrf.py │ │ ├── isaid.py │ │ ├── levircd.py │ │ ├── loveda.py │ │ ├── nyu.py │ │ ├── pascal_context.py │ │ ├── potsdam.py │ │ ├── refuge.py │ │ ├── stare.py │ │ ├── synapse.py │ │ ├── vaihingen.py │ │ └── voc_aug.py │ │ ├── deployment │ │ ├── __init__.py │ │ └── pytorch2torchscript.py │ │ ├── dist_test.sh │ │ ├── dist_train.sh │ │ ├── misc │ │ ├── __init__.py │ │ ├── browse_dataset.py │ │ ├── print_config.py │ │ └── publish_model.py │ │ ├── model_converters │ │ ├── __init__.py │ │ ├── beit2mmseg.py │ │ ├── clip2mmseg.py │ │ ├── mit2mmseg.py │ │ ├── san2mmseg.py │ │ ├── stdc2mmseg.py │ │ ├── swin2mmseg.py │ │ ├── twins2mmseg.py │ │ ├── vit2mmseg.py │ │ └── vitjax2mmseg.py │ │ ├── slurm_test.sh │ │ ├── slurm_train.sh │ │ ├── test.py │ │ ├── torchserve │ │ ├── __init__.py │ │ ├── mmseg2torchserve.py │ │ ├── mmseg_handler.py │ │ └── test_torchserve.py │ │ └── train.py ├── README.md ├── __init__.py ├── apis │ ├── __init__.py │ ├── inference.py │ ├── mmseg_inferencer.py │ ├── remote_sense_inferencer.py │ └── utils.py ├── configs │ ├── __init__.py │ └── _base_ │ │ ├── __init__.py │ │ ├── datasets │ │ ├── __init__.py │ │ ├── loveda.py │ │ └── potsdam.py │ │ ├── default_runtime.py │ │ └── schedules │ │ ├── __init__.py │ │ ├── schedule_160k.py │ │ ├── schedule_20k.py │ │ ├── schedule_240k.py │ │ ├── schedule_25k.py │ │ ├── schedule_320k.py │ │ ├── schedule_40k.py │ │ └── schedule_80k.py ├── datasets │ ├── __init__.py │ ├── ade.py │ ├── basesegdataset.py │ ├── bdd100k.py │ ├── chase_db1.py │ ├── cityscapes.py │ ├── coco_stuff.py │ ├── dark_zurich.py │ ├── dataset_wrappers.py │ ├── decathlon.py │ ├── drive.py │ ├── dsdl.py │ ├── hrf.py │ ├── hsi_drive.py │ ├── isaid.py │ ├── isprs.py │ ├── levir.py │ ├── lip.py │ ├── loveda.py │ ├── mapillary.py │ ├── night_driving.py │ ├── nyu.py │ ├── pascal_context.py │ ├── potsdam.py │ ├── refuge.py │ ├── stare.py │ ├── synapse.py │ ├── transforms │ │ ├── __init__.py │ │ ├── formatting.py │ │ ├── loading.py │ │ └── transforms.py │ └── voc.py ├── engine │ ├── __init__.py │ ├── hooks │ │ ├── __init__.py │ │ └── visualization_hook.py │ ├── optimizers │ │ ├── __init__.py │ │ ├── force_default_constructor.py │ │ └── layer_decay_optimizer_constructor.py │ └── schedulers │ │ ├── __init__.py │ │ └── poly_ratio_scheduler.py ├── evaluation │ ├── __init__.py │ └── metrics │ │ ├── __init__.py │ │ ├── citys_metric.py │ │ ├── depth_metric.py │ │ └── iou_metric.py ├── models │ ├── __init__.py │ ├── assigners │ │ ├── __init__.py │ │ ├── base_assigner.py │ │ ├── hungarian_assigner.py │ │ └── match_cost.py │ ├── backbones │ │ ├── __init__.py │ │ ├── beit.py │ │ ├── bisenetv1.py │ │ ├── bisenetv2.py │ │ ├── cgnet.py │ │ ├── ddrnet.py │ │ ├── erfnet.py │ │ ├── fast_scnn.py │ │ ├── hrnet.py │ │ ├── icnet.py │ │ ├── mae.py │ │ ├── mit.py │ │ ├── mobilenet_v2.py │ │ ├── mobilenet_v3.py │ │ ├── mscan.py │ │ ├── pidnet.py │ │ ├── resnest.py │ │ ├── resnet.py │ │ ├── resnext.py │ │ ├── stdc.py │ │ ├── swin.py │ │ ├── timm_backbone.py │ │ ├── twins.py │ │ ├── unet.py │ │ ├── vit.py │ │ └── vpd.py │ ├── builder.py │ ├── data_preprocessor.py │ ├── decode_heads │ │ ├── __init__.py │ │ ├── ann_head.py │ │ ├── apc_head.py │ │ ├── aspp_head.py │ │ ├── cascade_decode_head.py │ │ ├── cc_head.py │ │ ├── da_head.py │ │ ├── ddr_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 │ │ ├── ham_head.py │ │ ├── isa_head.py │ │ ├── knet_head.py │ │ ├── lraspp_head.py │ │ ├── mask2former_head.py │ │ ├── maskformer_head.py │ │ ├── nl_head.py │ │ ├── ocr_head.py │ │ ├── pid_head.py │ │ ├── point_head.py │ │ ├── psa_head.py │ │ ├── psp_head.py │ │ ├── san_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 │ │ └── vpd_depth_head.py │ ├── losses │ │ ├── __init__.py │ │ ├── accuracy.py │ │ ├── boundary_loss.py │ │ ├── cross_entropy_loss.py │ │ ├── dice_loss.py │ │ ├── focal_loss.py │ │ ├── huasdorff_distance_loss.py │ │ ├── kldiv_loss.py │ │ ├── lovasz_loss.py │ │ ├── ohem_cross_entropy_loss.py │ │ ├── silog_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 │ │ ├── depth_estimator.py │ │ ├── encoder_decoder.py │ │ ├── multimodal_encoder_decoder.py │ │ └── seg_tta.py │ ├── text_encoder │ │ ├── __init__.py │ │ └── clip_text_encoder.py │ └── utils │ │ ├── __init__.py │ │ ├── basic_block.py │ │ ├── embed.py │ │ ├── encoding.py │ │ ├── inverted_residual.py │ │ ├── make_divisible.py │ │ ├── point_sample.py │ │ ├── ppm.py │ │ ├── res_layer.py │ │ ├── san_layers.py │ │ ├── se_layer.py │ │ ├── self_attention_block.py │ │ ├── shape_convert.py │ │ ├── up_conv_block.py │ │ └── wrappers.py ├── registry │ ├── __init__.py │ └── registry.py ├── setup.py ├── structures │ ├── __init__.py │ ├── sampler │ │ ├── __init__.py │ │ ├── base_pixel_sampler.py │ │ ├── builder.py │ │ └── ohem_pixel_sampler.py │ └── seg_data_sample.py ├── utils │ ├── __init__.py │ ├── bpe_simple_vocab_16e6.txt.gz │ ├── class_names.py │ ├── collect_env.py │ ├── get_templates.py │ ├── io.py │ ├── mask_classification.py │ ├── misc.py │ ├── set_env.py │ ├── tokenizer.py │ └── typing_utils.py ├── version.py └── visualization │ ├── __init__.py │ └── local_visualizer.py ├── model_semantic.py ├── process_dataset.sh ├── requirements.txt ├── sam2 ├── README.md ├── __init__.py ├── automatic_mask_generator.py ├── build_sam.py ├── configs │ ├── sam2.1 │ │ ├── sam2.1_hiera_b+.yaml │ │ ├── sam2.1_hiera_l.yaml │ │ ├── sam2.1_hiera_s.yaml │ │ └── sam2.1_hiera_t.yaml │ ├── sam2.1_training │ │ └── sam2.1_hiera_b+_MOSE_finetune.yaml │ └── sam2 │ │ ├── sam2_hiera_b+.yaml │ │ ├── sam2_hiera_l.yaml │ │ ├── sam2_hiera_s.yaml │ │ └── sam2_hiera_t.yaml ├── csrc │ └── connected_components.cu ├── custom_automatic_mask_generator.py ├── custom_model │ ├── __init__.py │ ├── custom_mask_decoder.py │ └── custom_sam2_base.py ├── custom_sam2_image_predictor.py ├── modeling │ ├── __init__.py │ ├── backbones │ │ ├── __init__.py │ │ ├── hieradet.py │ │ ├── image_encoder.py │ │ └── utils.py │ ├── memory_attention.py │ ├── memory_encoder.py │ ├── position_encoding.py │ ├── sam │ │ ├── __init__.py │ │ ├── mask_decoder.py │ │ ├── prompt_encoder.py │ │ └── transformer.py │ ├── sam2_base.py │ └── sam2_utils.py ├── sam2_hiera_b+.yaml ├── sam2_hiera_l.yaml ├── sam2_hiera_s.yaml ├── sam2_hiera_t.yaml ├── sam2_image_predictor.py ├── sam2_video_predictor.py ├── setup.py └── utils │ ├── __init__.py │ ├── amg.py │ ├── custom_amg.py │ ├── custom_transforms.py │ ├── misc.py │ └── transforms.py ├── setup_env.sh └── utils ├── LISA ├── __init__.py ├── constants.py ├── conversation.py ├── data_processing.py ├── dataset.py ├── transforms.py └── utils.py ├── __init__.py ├── image_query_label.yaml ├── imagenet_template.py └── visualize_segmentation.py /.gitignore: -------------------------------------------------------------------------------- 1 | */__pycache__/ 2 | .idea/* -------------------------------------------------------------------------------- /assets/boats_ambulance.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/assets/boats_ambulance.jpg -------------------------------------------------------------------------------- /assets/dino_two_dogs.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/assets/dino_two_dogs.jpg -------------------------------------------------------------------------------- /assets/sam2_truck.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/assets/sam2_truck.jpg -------------------------------------------------------------------------------- /assets/teaser.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/assets/teaser.png -------------------------------------------------------------------------------- /configs/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/configs/.DS_Store -------------------------------------------------------------------------------- /configs/cls_city_scapes.txt: -------------------------------------------------------------------------------- 1 | road 2 | sidewalk 3 | building 4 | wall 5 | fence 6 | pole 7 | trafficlight 8 | trafficsign 9 | vegetation 10 | terrain 11 | sky 12 | person 13 | rider 14 | car 15 | truck 16 | bus 17 | train 18 | motorcycle 19 | bicycle -------------------------------------------------------------------------------- /configs/cls_voc20.txt: -------------------------------------------------------------------------------- 1 | aeroplane 2 | bicycle 3 | bird 4 | ship 5 | bottle 6 | bus 7 | car 8 | cat 9 | chair 10 | cow 11 | table 12 | dog 13 | horse 14 | motorbike 15 | person 16 | pottedplant 17 | sheep 18 | sofa 19 | train 20 | tvmonitor -------------------------------------------------------------------------------- /configs/cls_voc21.txt: -------------------------------------------------------------------------------- 1 | sky; wall; tree; wood; grass; road; sea; river; mountain; sands; desk; bed; building; cloud; lamp; door; window; wardrobe; ceiling; shelf; curtain; stair; floor; hill; rail; fence 2 | aeroplane 3 | bicycle 4 | bird 5 | ship 6 | bottle 7 | bus 8 | car 9 | cat 10 | chair 11 | cow 12 | table 13 | dog 14 | horse 15 | motorbike 16 | person 17 | pottedplant 18 | sheep 19 | sofa 20 | train 21 | tvmonitor -------------------------------------------------------------------------------- /configs/my_name.txt: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/configs/my_name.txt -------------------------------------------------------------------------------- /core/tests/Rock-climbing-Canada-1920x1147.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/core/tests/Rock-climbing-Canada-1920x1147.jpg -------------------------------------------------------------------------------- /core/tests/ocrbench_centre.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/core/tests/ocrbench_centre.jpg -------------------------------------------------------------------------------- /core/tests/selfie_cathedral_peak.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/core/tests/selfie_cathedral_peak.jpg -------------------------------------------------------------------------------- /core/vision_encoder/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/core/vision_encoder/__init__.py -------------------------------------------------------------------------------- /core/vision_encoder/bpe_simple_vocab_16e6.txt.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/core/vision_encoder/bpe_simple_vocab_16e6.txt.gz -------------------------------------------------------------------------------- /custom_clip/__init__.py: -------------------------------------------------------------------------------- 1 | from .clip import * 2 | from .model import * -------------------------------------------------------------------------------- /custom_clip/bpe_simple_vocab_16e6.txt.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/custom_clip/bpe_simple_vocab_16e6.txt.gz -------------------------------------------------------------------------------- /custom_open_clip/bpe_simple_vocab_16e6.txt.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/custom_open_clip/bpe_simple_vocab_16e6.txt.gz -------------------------------------------------------------------------------- /custom_open_clip/constants.py: -------------------------------------------------------------------------------- 1 | OPENAI_DATASET_MEAN = (0.48145466, 0.4578275, 0.40821073) 2 | OPENAI_DATASET_STD = (0.26862954, 0.26130258, 0.27577711) 3 | IMAGENET_MEAN = (0.485, 0.456, 0.406) 4 | IMAGENET_STD = (0.229, 0.224, 0.225) 5 | INCEPTION_MEAN = (0.5, 0.5, 0.5) 6 | INCEPTION_STD = (0.5, 0.5, 0.5) 7 | -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-16-plus-240.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 640, 3 | "vision_cfg": { 4 | "image_size": 240, 5 | "layers": 12, 6 | "width": 896, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 640, 13 | "heads": 10, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-16-plus.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 640, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 896, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 640, 13 | "heads": 10, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-16-quickgelu.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "quick_gelu": true, 4 | "vision_cfg": { 5 | "image_size": 224, 6 | "layers": 12, 7 | "width": 768, 8 | "patch_size": 16 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 512, 14 | "heads": 8, 15 | "layers": 12 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-16.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 768, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 512, 13 | "heads": 8, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-32-256.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "vision_cfg": { 4 | "image_size": 256, 5 | "layers": 12, 6 | "width": 768, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 512, 13 | "heads": 8, 14 | "layers": 12 15 | } 16 | } 17 | -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-32-plus-256.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 640, 3 | "vision_cfg": { 4 | "image_size": 256, 5 | "layers": 12, 6 | "width": 896, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 640, 13 | "heads": 10, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-32-quickgelu.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "quick_gelu": true, 4 | "vision_cfg": { 5 | "image_size": 224, 6 | "layers": 12, 7 | "width": 768, 8 | "patch_size": 32 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 512, 14 | "heads": 8, 15 | "layers": 12 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-B-32.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 768, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 512, 13 | "heads": 8, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-H-14-quickgelu.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1024, 3 | "quick_gelu": true, 4 | "vision_cfg": { 5 | "image_size": 224, 6 | "layers": 32, 7 | "width": 1280, 8 | "head_width": 80, 9 | "patch_size": 14 10 | }, 11 | "text_cfg": { 12 | "context_length": 77, 13 | "vocab_size": 49408, 14 | "width": 1024, 15 | "heads": 16, 16 | "layers": 24 17 | } 18 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-H-14.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1024, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 32, 6 | "width": 1280, 7 | "head_width": 80, 8 | "patch_size": 14 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 1024, 14 | "heads": 16, 15 | "layers": 24 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-H-16.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1024, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 32, 6 | "width": 1280, 7 | "head_width": 80, 8 | "patch_size": 16 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 1024, 14 | "heads": 16, 15 | "layers": 24 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-14-280.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "vision_cfg": { 4 | "image_size": 280, 5 | "layers": 24, 6 | "width": 1024, 7 | "patch_size": 14 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 768, 13 | "heads": 12, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-14-336.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "vision_cfg": { 4 | "image_size": 336, 5 | "layers": 24, 6 | "width": 1024, 7 | "patch_size": 14 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 768, 13 | "heads": 12, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-14-quickgelu.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "quick_gelu": true, 4 | "vision_cfg": { 5 | "image_size": 224, 6 | "layers": 24, 7 | "width": 1024, 8 | "patch_size": 14 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 768, 14 | "heads": 12, 15 | "layers": 12 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-14.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 24, 6 | "width": 1024, 7 | "patch_size": 14 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 768, 13 | "heads": 12, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-16-320.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "vision_cfg": { 4 | "image_size": 320, 5 | "layers": 24, 6 | "width": 1024, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 768, 13 | "heads": 12, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-L-16.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 768, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 24, 6 | "width": 1024, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 768, 13 | "heads": 12, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-M-16-alt.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 384, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 512, 7 | "patch_size": 16, 8 | "ls_init_value": 1e-4 9 | }, 10 | "text_cfg": { 11 | "context_length": 77, 12 | "vocab_size": 49408, 13 | "width": 384, 14 | "heads": 6, 15 | "layers": 12 16 | } 17 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-M-16.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 512, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 512, 13 | "heads": 8, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-M-32-alt.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 384, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 512, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 384, 13 | "heads": 6, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-M-32.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 512, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 512, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 512, 13 | "heads": 8, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-S-16-alt.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 256, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 384, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 256, 13 | "heads": 4, 14 | "layers": 10 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-S-16.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 384, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 384, 7 | "patch_size": 16 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 384, 13 | "heads": 6, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-S-32-alt.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 256, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 384, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 256, 13 | "heads": 4, 14 | "layers": 10 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-S-32.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 384, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 12, 6 | "width": 384, 7 | "patch_size": 32 8 | }, 9 | "text_cfg": { 10 | "context_length": 77, 11 | "vocab_size": 49408, 12 | "width": 384, 13 | "heads": 6, 14 | "layers": 12 15 | } 16 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-bigG-14.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1280, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 48, 6 | "width": 1664, 7 | "head_width": 104, 8 | "mlp_ratio": 4.9231, 9 | "patch_size": 14 10 | }, 11 | "text_cfg": { 12 | "context_length": 77, 13 | "vocab_size": 49408, 14 | "width": 1280, 15 | "heads": 20, 16 | "layers": 32 17 | } 18 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-e-14.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1280, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 56, 6 | "width": 1792, 7 | "head_width": 112, 8 | "mlp_ratio": 8.5715, 9 | "patch_size": 14 10 | }, 11 | "text_cfg": { 12 | "context_length": 77, 13 | "vocab_size": 49408, 14 | "width": 1280, 15 | "heads": 20, 16 | "layers": 36 17 | } 18 | } -------------------------------------------------------------------------------- /custom_open_clip/model_configs/ViT-g-14.json: -------------------------------------------------------------------------------- 1 | { 2 | "embed_dim": 1024, 3 | "vision_cfg": { 4 | "image_size": 224, 5 | "layers": 40, 6 | "width": 1408, 7 | "head_width": 88, 8 | "mlp_ratio": 4.3637, 9 | "patch_size": 14 10 | }, 11 | "text_cfg": { 12 | "context_length": 77, 13 | "vocab_size": 49408, 14 | "width": 1024, 15 | "heads": 16, 16 | "layers": 24 17 | } 18 | } -------------------------------------------------------------------------------- /custom_open_clip/version.py: -------------------------------------------------------------------------------- 1 | __version__ = '2.24.0' 2 | -------------------------------------------------------------------------------- /dist_eval_semantic.sh: -------------------------------------------------------------------------------- 1 | LOCAL_RANK=$1 2 | CONFIG=$2 3 | WORK_DIR=$3 4 | 5 | CLIP_PRETRAIN=$4 6 | CLIP_ARCHITECTURE=$5 7 | 8 | 9 | CUDA_VISIBLE_DEVICES=$LOCAL_RANK python eval_semantic.py --config $CONFIG --work-dir $WORK_DIR --local-rank $LOCAL_RANK \ 10 | --clip_pretrained $CLIP_PRETRAIN --clip_architecture $CLIP_ARCHITECTURE -------------------------------------------------------------------------------- /mmengine/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmengine/.DS_Store -------------------------------------------------------------------------------- /mmengine/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | # flake8: noqa 3 | from .config import * 4 | from .fileio import * 5 | from .logging import * 6 | from .registry import * 7 | from .utils import * 8 | from .version import __version__, version_info 9 | -------------------------------------------------------------------------------- /mmengine/config/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .config import Config, ConfigDict, DictAction, read_base 3 | 4 | __all__ = ['Config', 'ConfigDict', 'DictAction', 'read_base'] 5 | -------------------------------------------------------------------------------- /mmengine/evaluator/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .evaluator import Evaluator 3 | from .metric import BaseMetric, DumpResults 4 | from .utils import get_metric_value 5 | 6 | __all__ = ['BaseMetric', 'Evaluator', 'get_metric_value', 'DumpResults'] 7 | -------------------------------------------------------------------------------- /mmengine/fileio/handlers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base import BaseFileHandler 3 | from .json_handler import JsonHandler 4 | from .pickle_handler import PickleHandler 5 | from .registry_utils import file_handlers, register_handler 6 | from .yaml_handler import YamlHandler 7 | 8 | __all__ = [ 9 | 'BaseFileHandler', 'JsonHandler', 'PickleHandler', 'YamlHandler', 10 | 'register_handler', 'file_handlers' 11 | ] 12 | -------------------------------------------------------------------------------- /mmengine/hub/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .hub import get_config, get_model 3 | 4 | __all__ = ['get_config', 'get_model'] 5 | -------------------------------------------------------------------------------- /mmengine/hub/deprecated.json: -------------------------------------------------------------------------------- 1 | { 2 | "resnet50_caffe": "detectron/resnet50_caffe", 3 | "resnet50_caffe_bgr": "detectron2/resnet50_caffe_bgr", 4 | "resnet101_caffe": "detectron/resnet101_caffe", 5 | "resnet101_caffe_bgr": "detectron2/resnet101_caffe_bgr" 6 | } 7 | -------------------------------------------------------------------------------- /mmengine/infer/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .infer import BaseInferencer 3 | 4 | __all__ = ['BaseInferencer'] 5 | -------------------------------------------------------------------------------- /mmengine/logging/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .history_buffer import HistoryBuffer 3 | from .logger import MMLogger, print_log 4 | from .message_hub import MessageHub 5 | 6 | __all__ = ['HistoryBuffer', 'MessageHub', 'MMLogger', 'print_log'] 7 | -------------------------------------------------------------------------------- /mmengine/model/base_model/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_model import BaseModel 3 | from .data_preprocessor import BaseDataPreprocessor, ImgDataPreprocessor 4 | 5 | __all__ = ['BaseModel', 'ImgDataPreprocessor', 'BaseDataPreprocessor'] 6 | -------------------------------------------------------------------------------- /mmengine/structures/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_data_element import BaseDataElement 3 | from .instance_data import InstanceData 4 | from .label_data import LabelData 5 | from .pixel_data import PixelData 6 | 7 | __all__ = ['BaseDataElement', 'InstanceData', 'LabelData', 'PixelData'] 8 | -------------------------------------------------------------------------------- /mmengine/testing/_internal/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .distributed import MultiProcessTestCase 3 | 4 | __all__ = ['MultiProcessTestCase'] 5 | -------------------------------------------------------------------------------- /mmseg/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.DS_Store -------------------------------------------------------------------------------- /mmseg/.mim/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/_base_/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/_base_/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/_base_/datasets/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/_base_/datasets/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/_base_/models/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/_base_/models/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/_base_/schedules/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/_base_/schedules/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/ann/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ann_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb4-20k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=21), 10 | auxiliary_head=dict(num_classes=21)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb4-40k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=21), 10 | auxiliary_head=dict(num_classes=21)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ann/ann_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/apcnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './apcnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/apcnet/apcnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/beit/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/beit/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/bisenetv1/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/bisenetv1_r101-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r101-d32_4xb4-160k_coco-stuff164k-512x512.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet101_v1c')))) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/bisenetv1_r18-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r18-d32_4xb4-160k_coco-stuff164k-512x512.py' 2 | crop_size = (512, 512) 3 | data_preprocessor = dict(size=crop_size) 4 | model = dict( 5 | data_preprocessor=data_preprocessor, 6 | backbone=dict( 7 | backbone_cfg=dict( 8 | init_cfg=dict( 9 | type='Pretrained', checkpoint='open-mmlab://resnet18_v1c'))), 10 | ) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/bisenetv1_r18-d32-in1k-pre_4xb8-160k_cityscapes-1024x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r18-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py' 2 | train_dataloader = dict(batch_size=8, num_workers=4) 3 | val_dataloader = dict(batch_size=1, num_workers=4) 4 | test_dataloader = val_dataloader 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/bisenetv1_r50-d32-in1k-pre_4xb4-160k_cityscapes-1024x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r50-d32_4xb4-160k_cityscapes-1024x1024.py' 2 | model = dict( 3 | type='EncoderDecoder', 4 | backbone=dict( 5 | backbone_cfg=dict( 6 | init_cfg=dict( 7 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv1/bisenetv1_r50-d32-in1k-pre_4xb4-160k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv1_r50-d32_4xb4-160k_coco-stuff164k-512x512.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | backbone_cfg=dict( 6 | init_cfg=dict( 7 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv2/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/bisenetv2/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/bisenetv2/bisenetv2_fcn_4xb4-amp-160k_cityscapes-1024x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './bisenetv2_fcn_4xb4-160k_cityscapes-1024x1024.py' 2 | optim_wrapper = dict( 3 | _delete_=True, 4 | type='AmpOptimWrapper', 5 | optimizer=dict(type='SGD', lr=0.05, momentum=0.9, weight_decay=0.0005), 6 | loss_scale=512.) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/ccnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './ccnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ccnet/ccnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/cgnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/cgnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/convnext/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/convnext/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/danet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './danet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/danet/danet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ddrnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/ddrnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/deeplabv3/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r101-d8_4xb2-40k_cityscapes-512x1024.py' 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005) 3 | optim_wrapper = dict( 4 | _delete_=True, 5 | type='AmpOptimWrapper', 6 | optimizer=optimizer, 7 | loss_scale=512.) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-160k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-160k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-20k_coco-stuff10k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-20k_coco-stuff10k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-320k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-320k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_coco-stuff10k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-40k_coco-stuff10k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-40k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-40k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-80k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-80k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101-d8_4xb4-80k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb4-40k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r101b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r18-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r18-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r18b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r18b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3/deeplabv3_r50b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/deeplabv3plus/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005) 3 | optim_wrapper = dict( 4 | _delete_=True, 5 | type='AmpOptimWrapper', 6 | optimizer=optimizer, 7 | loss_scale=512.) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-40k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-40k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-40k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-40k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_loveda-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_loveda-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_potsdam-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_potsdam-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101-d8_4xb4-80k_vaihingen-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_vaihingen-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r101b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb4-80k_isaid-896x896.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_isaid-896x896.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb4-80k_loveda-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_loveda-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb4-80k_potsdam-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_potsdam-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r18-d8_4xb4-80k_vaihingen-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb4-80k_vaihingen-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | c1_in_channels=64, 7 | c1_channels=12, 8 | in_channels=512, 9 | channels=128, 10 | ), 11 | auxiliary_head=dict(in_channels=256, channels=64)) 12 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict(data_preprocessor=data_preprocessor) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict(data_preprocessor=data_preprocessor) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r50b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/deeplabv3plus/deeplabv3plus_r50b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './deeplabv3plus_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/dmnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './dmnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dmnet/dmnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/dnlnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './dnl_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dnlnet/dnl_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/dpt/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/dpt/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/dsdl/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/dsdl/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/emanet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/emanet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/emanet/emanet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './emanet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/emanet/emanet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './emanet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/emanet/emanet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/encnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './encnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/encnet/encnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/erfnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/erfnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/fastfcn/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/fastfcn/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4xb4-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | # model settings 2 | _base_ = './fastfcn_r50-d32_jpu_aspp_4xb2-80k_cityscapes-512x1024.py' 3 | train_dataloader = dict(batch_size=4, num_workers=4) 4 | val_dataloader = dict(batch_size=1, num_workers=4) 5 | test_dataloader = val_dataloader 6 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fastfcn/fastfcn_r50-d32_jpu_enc_4xb4-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | # model settings 2 | _base_ = './fastfcn_r50-d32_jpu_enc_4xb2-80k_cityscapes-512x1024.py' 3 | train_dataloader = dict(batch_size=4, num_workers=4) 4 | val_dataloader = dict(batch_size=1, num_workers=4) 5 | test_dataloader = val_dataloader 6 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fastfcn/fastfcn_r50-d32_jpu_psp_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict(data_preprocessor=data_preprocessor) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fastscnn/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/fastscnn/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/fcn/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101-d16_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101-d16_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101-d16_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101-d16_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101b-d16_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r101b-d16_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50b-d16_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r50b-d16_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn-d6_r50b-d16_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn-d6_r50-d16_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | optim_wrapper = dict( 3 | _delete_=True, 4 | type='AmpOptimWrapper', 5 | optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005), 6 | loss_scale=512.) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-40k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-40k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-40k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-40k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-80k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-40k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101-d8_4xb4-80k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb4-80k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r101b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r18-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r18-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r18b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r18b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb4-20k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=21), 10 | auxiliary_head=dict(num_classes=21)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb4-40k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=21), 10 | auxiliary_head=dict(num_classes=21)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/fcn/fcn_r50b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/gcnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './gcnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/gcnet/gcnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/hrnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb2-160k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=150)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-20k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=21)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-40k_voc12aug-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=21)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=150)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-80k_isaid-896x896.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 | crop_size = (896, 896) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=16)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-80k_loveda-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=7)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-80k_potsdam-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=6)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18_4xb4-80k_vaihingen-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=6)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-160k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-20k_voc12aug-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-40k_voc12aug-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-80k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-80k_isaid-896x896.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-80k_isaid-896x896.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-80k_loveda-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-80k_loveda-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/hrnet/fcn_hr18s_4xb4-80k_potsdam-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fcn_hr18_4xb4-80k_potsdam-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://msra/hrnetv2_w18_small', 4 | backbone=dict( 5 | extra=dict( 6 | stage1=dict(num_blocks=(2, )), 7 | stage2=dict(num_blocks=(2, 2)), 8 | stage3=dict(num_modules=3, num_blocks=(2, 2, 2)), 9 | stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2))))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/icnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r101-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-160k_cityscapes-832x832.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r101-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-80k_cityscapes-832x832.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r101-d8_4xb2-160k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-160k_cityscapes-832x832.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(depth=101))) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r101-d8_4xb2-80k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-80k_cityscapes-832x832.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(depth=101))) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r18-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-160k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict( 4 | layer_channels=(128, 512), 5 | backbone_cfg=dict( 6 | depth=18, 7 | init_cfg=dict( 8 | type='Pretrained', checkpoint='open-mmlab://resnet18_v1c')))) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r18-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-80k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict( 4 | layer_channels=(128, 512), 5 | backbone_cfg=dict( 6 | depth=18, 7 | init_cfg=dict( 8 | type='Pretrained', checkpoint='open-mmlab://resnet18_v1c')))) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r18-d8_4xb2-160k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-160k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict(layer_channels=(128, 512), backbone_cfg=dict(depth=18))) 4 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r18-d8_4xb2-80k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-80k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict(layer_channels=(128, 512), backbone_cfg=dict(depth=18))) 4 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r50-d8-in1k-pre_4xb2-160k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-160k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r50-d8-in1k-pre_4xb2-80k_cityscapes-832x832.py: -------------------------------------------------------------------------------- 1 | _base_ = './icnet_r50-d8_4xb2-80k_cityscapes-832x832.py' 2 | model = dict( 3 | backbone=dict( 4 | backbone_cfg=dict( 5 | init_cfg=dict( 6 | type='Pretrained', checkpoint='open-mmlab://resnet50_v1c')))) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r50-d8_4xb2-160k_cityscapes-832x832.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 | crop_size = (832, 832) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict(data_preprocessor=data_preprocessor) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/icnet/icnet_r50-d8_4xb2-80k_cityscapes-832x832.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 | crop_size = (832, 832) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict(data_preprocessor=data_preprocessor) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/isanet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './isanet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/isanet/isanet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/knet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/knet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/mae/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/mae/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/mask2former/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/mask2former/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/mask2former/mask2former_r101_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./mask2former_r50_8xb2-160k_ade20k-512x512.py'] 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/mask2former/mask2former_r101_8xb2-90k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./mask2former_r50_8xb2-90k_cityscapes-512x1024.py'] 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640.py'] 2 | 3 | pretrained = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/swin/swin_base_patch4_window12_384_22k_20220317-e5c09f74.pth' # noqa 4 | model = dict( 5 | backbone=dict(init_cfg=dict(type='Pretrained', checkpoint=pretrained))) 6 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/maskformer/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/maskformer/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/maskformer/maskformer_r101-d32_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './maskformer_r50-d32_8xb2-160k_ade20k-512x512.py' 2 | 3 | model = dict( 4 | backbone=dict( 5 | depth=101, 6 | init_cfg=dict(type='Pretrained', 7 | checkpoint='torchvision://resnet101'))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/mobilenet_v2/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/mobilenet_v2/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/mobilenet_v3/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/mobilenet_v3/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/nonlocal_net/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './nonlocal_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/nonlocal_net/nonlocal_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ocrnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/ocrnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/ocrnet/ocrnet_hr18_4xb2-160k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ocrnet/ocrnet_hr18_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ocrnet/ocrnet_hr18_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/ocrnet/ocrnet_r101-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | pretrained='open-mmlab://resnet101_v1c', 10 | backbone=dict(depth=101)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pidnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/pidnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/pidnet/pidnet-m_2xb6-120k_1024x1024-cityscapes.py: -------------------------------------------------------------------------------- 1 | _base_ = './pidnet-s_2xb6-120k_1024x1024-cityscapes.py' 2 | checkpoint_file = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/pidnet/pidnet-m_imagenet1k_20230306-39893c52.pth' # noqa 3 | model = dict( 4 | backbone=dict(channels=64, init_cfg=dict(checkpoint=checkpoint_file)), 5 | decode_head=dict(in_channels=256)) 6 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/point_rend/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/point_rend/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/point_rend/pointrend_r101_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pointrend_r50_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/point_rend/pointrend_r101_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pointrend_r50_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/poolformer/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/poolformer/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/psanet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './psanet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/psanet/psanet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/pspnet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-40k_cityscapes-512x1024_dark-zurich-1920x1080.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-40k_cityscapes-512x1024_dark-zurich-1920x1080.py' # noqa 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-40k_cityscapes-512x1024_night-driving-1920x1080.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-40k_cityscapes-512x1024_night-driving-1920x1080.py' # noqa 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb2-amp-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | optim_wrapper = dict( 3 | _delete_=True, 4 | type='AmpOptimWrapper', 5 | optimizer=dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005), 6 | loss_scale=512.) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-160k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-160k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-20k_coco-stuff10k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-20k_coco-stuff10k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-320k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-320k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-40k_coco-stuff10k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-40k_coco-stuff10k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-40k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-40k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-40k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-40k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_coco-stuff164k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_coco-stuff164k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_loveda-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_loveda-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_pascal-context-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_pascal-context-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_pascal-context-59-480x480.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_pascal-context-59-480x480.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_potsdam-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_potsdam-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101-d8_4xb4-80k_vaihingen-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_vaihingen-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024_dark-zurich-1920x1080.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024_dark-zurich-1920x1080.py' # noqa 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101b-d8_4xb2-80k_cityscapes-512x1024_night-driving-1920x1080.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024_night-driving-1920x1080.py' # noqa 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r101b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet101', 4 | backbone=dict(type='ResNet', depth=101)) 5 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb4-80k_isaid-896x896.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_isaid-896x896.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb4-80k_loveda-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_loveda-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb4-80k_potsdam-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_potsdam-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18-d8_4xb4-80k_vaihingen-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb4-80k_vaihingen-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnet18_v1c', 4 | backbone=dict(depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r18b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict( 3 | pretrained='torchvision://resnet18', 4 | backbone=dict(type='ResNet', depth=18), 5 | decode_head=dict( 6 | in_channels=512, 7 | channels=128, 8 | ), 9 | auxiliary_head=dict(in_channels=256, channels=64)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d32_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | backbone=dict(dilations=(1, 1, 2, 4), strides=(1, 2, 2, 2))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-80k_isaid-896x896.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 | crop_size = (896, 896) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=16), 10 | auxiliary_head=dict(num_classes=16)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-80k_loveda-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=7), 10 | auxiliary_head=dict(num_classes=7)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-80k_potsdam-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=6), 10 | auxiliary_head=dict(num_classes=6)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50-d8_4xb4-80k_vaihingen-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=6), 10 | auxiliary_head=dict(num_classes=6)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50b-d8_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/pspnet/pspnet_r50b-d8_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './pspnet_r50-d8_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet')) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/resnest/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_deeplabv3_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_deeplabv3_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_4xb2-80k_cityscapes-512x1024.py' # noqa 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_deeplabv3plus_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_fcn_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = '../fcn/fcn_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_fcn_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = '../fcn/fcn_r101-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_pspnet_4xb2-80k_cityscapes512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = '../pspnet/pspnet_r101-d8_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/resnest/resnest_s101-d8_pspnet_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = '../pspnet/pspnet_r101-d8_4xb4-160k_ade20k-512x512.py' 2 | model = dict( 3 | pretrained='open-mmlab://resnest101', 4 | backbone=dict( 5 | type='ResNeSt', 6 | stem_channels=128, 7 | radix=2, 8 | reduction_factor=4, 9 | avg_down_stride=True)) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/san/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/san/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/segformer/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/segformer/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/segmenter/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/segmenter/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/segnext/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/segnext/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/sem_fpn/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/sem_fpn/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/sem_fpn/fpn_r101_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/sem_fpn/fpn_r101_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './fpn_r50_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | crop_size = (512, 512) 4 | data_preprocessor = dict(size=crop_size) 5 | model = dict(data_preprocessor=data_preprocessor) 6 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/sem_fpn/fpn_r50_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/sem_fpn/fpn_r50_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, decode_head=dict(num_classes=150)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/setr/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/setr/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/setr/setr_vit-l_mla_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./setr_vit-l-mla_8xb1-160k_ade20k-512x512.py'] 2 | 3 | # num_gpus: 8 -> batch_size: 16 4 | train_dataloader = dict(batch_size=2) 5 | val_dataloader = dict(batch_size=1) 6 | test_dataloader = val_dataloader 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/stdc/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/stdc/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/stdc/stdc1_in1k-pre_4xb12-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/stdc/stdc1_20220308-5368626c.pth' # noqa 2 | _base_ = './stdc1_4xb12-80k_cityscapes-512x1024.py' 3 | model = dict( 4 | backbone=dict( 5 | backbone_cfg=dict( 6 | init_cfg=dict(type='Pretrained', checkpoint=checkpoint)))) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/stdc/stdc2_4xb12-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './stdc1_4xb12-80k_cityscapes-512x1024.py' 2 | model = dict(backbone=dict(backbone_cfg=dict(stdc_type='STDCNet2'))) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/stdc/stdc2_in1k-pre_4xb12-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/stdc/stdc2_20220308-7dbd9127.pth' # noqa 2 | _base_ = './stdc2_4xb12-80k_cityscapes-512x1024.py' 3 | model = dict( 4 | backbone=dict( 5 | backbone_cfg=dict( 6 | init_cfg=dict(type='Pretrained', checkpoint=checkpoint)))) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/swin/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/swin/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/swin/swin-base-patch4-window7-in22k-pre_upernet_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | './swin-base-patch4-window7-in1k-pre_upernet_8xb2-160k_ade20k-512x512.py' 3 | ] 4 | checkpoint_file = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/swin/swin_base_patch4_window7_224_22k_20220317-4f79f7c0.pth' # noqa 5 | model = dict( 6 | backbone=dict( 7 | init_cfg=dict(type='Pretrained', checkpoint=checkpoint_file))) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/twins/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/twins/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/twins/twins_pcpvt-b_fpn_fpnhead_8xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./twins_pcpvt-s_fpn_fpnhead_8xb4-80k_ade20k-512x512.py'] 2 | 3 | checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/twins/pcpvt_base_20220308-0621964c.pth' # noqa 4 | 5 | model = dict( 6 | backbone=dict( 7 | init_cfg=dict(type='Pretrained', checkpoint=checkpoint), 8 | depths=[3, 4, 18, 3]), ) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/twins/twins_pcpvt-l_fpn_fpnhead_8xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = ['./twins_pcpvt-s_fpn_fpnhead_8xb4-80k_ade20k-512x512.py'] 2 | 3 | checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/twins/pcpvt_large_20220308-37579dc6.pth' # noqa 4 | 5 | model = dict( 6 | backbone=dict( 7 | init_cfg=dict(type='Pretrained', checkpoint=checkpoint), 8 | depths=[3, 8, 27, 3])) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/unet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_drive-64x64.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/drive.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | crop_size = (64, 64) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_hrf-256x256.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/hrf.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | crop_size = (256, 256) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_stare-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/stare.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | crop_size = (128, 128) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet_s5-d16_deeplabv3_4xb4-40k_chase-db1-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_deeplabv3_4xb4-40k_drive-64x64.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_deeplabv3_4xb4-40k_hrf-256x256.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_deeplabv3_4xb4-40k_stare-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/chase_db1.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | crop_size = (128, 128) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-40k_drive-64x64.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 | crop_size = (64, 64) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-40k_hrf-256x256.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 | crop_size = (256, 256) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-40k_stare-128x128.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 | crop_size = (128, 128) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_fcn_4xb4-40k_chase-db1-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_fcn_4xb4-40k_drive-64x64.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_fcn_4xb4-40k_hrf-256x256.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_fcn_4xb4-40k_stare-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', 3 | '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | crop_size = (128, 128) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict( 9 | data_preprocessor=data_preprocessor, 10 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-40k_drive-64x64.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 | crop_size = (64, 64) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(64, 64), stride=(42, 42))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-40k_hrf-256x256.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 | crop_size = (256, 256) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(256, 256), stride=(170, 170))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-40k_stare-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/stare.py', 3 | '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' 4 | ] 5 | crop_size = (128, 128) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 10 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_pspnet_4xb4-40k_chase-db1-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_pspnet_4xb4-40k_drive-64x64.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_pspnet_4xb4-40k_hrf-256x256.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = './unet-s5-d16_pspnet_4xb4-40k_stare-128x128.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/unet/unet_s5-d16_deeplabv3_4xb4-40k_chase-db1-128x128.py: -------------------------------------------------------------------------------- 1 | _base_ = [ 2 | '../_base_/models/deeplabv3_unet_s5-d16.py', 3 | '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', 4 | '../_base_/schedules/schedule_40k.py' 5 | ] 6 | crop_size = (128, 128) 7 | data_preprocessor = dict(size=crop_size) 8 | model = dict( 9 | data_preprocessor=data_preprocessor, 10 | test_cfg=dict(crop_size=(128, 128), stride=(85, 85))) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/upernet/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-40k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb2-40k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-40k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-80k_cityscapes-512x1024.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb2-80k_cityscapes-769x769.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-80k_cityscapes-769x769.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb4-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb4-160k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb4-20k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb4-20k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb4-40k_voc12aug-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb4-40k_voc12aug-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r101_4xb4-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb4-80k_ade20k-512x512.py' 2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101)) 3 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r18_4xb2-40k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-40k_cityscapes-512x1024.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r18_4xb2-80k_cityscapes-512x1024.py: -------------------------------------------------------------------------------- 1 | _base_ = './upernet_r50_4xb2-80k_cityscapes-512x1024.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r50_4xb2-40k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r50_4xb2-80k_cityscapes-512x1024.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 | crop_size = (512, 1024) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict(data_preprocessor=data_preprocessor) 8 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r50_4xb4-160k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/upernet/upernet_r50_4xb4-80k_ade20k-512x512.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 | crop_size = (512, 512) 6 | data_preprocessor = dict(size=crop_size) 7 | model = dict( 8 | data_preprocessor=data_preprocessor, 9 | decode_head=dict(num_classes=150), 10 | auxiliary_head=dict(num_classes=150)) 11 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/vit/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-b16-ln_mln_upernet_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-160k_ade20k-512x512.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-b16_mln_upernet_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-160k_ade20k-512x512.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_base_patch16_224-b5f2ef4d.pth', 5 | backbone=dict(drop_path_rate=0.1), 6 | ) 7 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-b16_upernet_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-160k_ade20k-512x512.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-b16_upernet_8xb2-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-80k_ade20k-512x512.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 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-s16_upernet_8xb2-160k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-80k_ade20k-512x512.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_small_patch16_224-cd65a155.pth', 5 | backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1), 6 | decode_head=dict(num_classes=150, in_channels=[384, 384, 384, 384]), 7 | neck=None, 8 | auxiliary_head=dict(num_classes=150, in_channels=384)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vit/vit_deit-s16_upernet_8xb2-80k_ade20k-512x512.py: -------------------------------------------------------------------------------- 1 | _base_ = './vit_vit-b16_mln_upernet_8xb2-80k_ade20k-512x512.py' 2 | 3 | model = dict( 4 | pretrained='pretrain/deit_small_patch16_224-cd65a155.pth', 5 | backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1), 6 | decode_head=dict(num_classes=150, in_channels=[384, 384, 384, 384]), 7 | neck=None, 8 | auxiliary_head=dict(num_classes=150, in_channels=384)) 9 | -------------------------------------------------------------------------------- /mmseg/.mim/configs/vpd/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/configs/vpd/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/analysis_tools/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/analysis_tools/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/dataset_converters/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/dataset_converters/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/deployment/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/deployment/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/misc/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/misc/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/model_converters/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/model_converters/__init__.py -------------------------------------------------------------------------------- /mmseg/.mim/tools/torchserve/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/.mim/tools/torchserve/__init__.py -------------------------------------------------------------------------------- /mmseg/apis/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .inference import inference_model, init_model, show_result_pyplot 3 | from .mmseg_inferencer import MMSegInferencer 4 | from .remote_sense_inferencer import RSImage, RSInferencer 5 | 6 | __all__ = [ 7 | 'init_model', 'inference_model', 'show_result_pyplot', 'MMSegInferencer', 8 | 'RSInferencer', 'RSImage' 9 | ] 10 | -------------------------------------------------------------------------------- /mmseg/configs/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/configs/__init__.py -------------------------------------------------------------------------------- /mmseg/configs/_base_/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/configs/_base_/__init__.py -------------------------------------------------------------------------------- /mmseg/configs/_base_/datasets/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/configs/_base_/datasets/__init__.py -------------------------------------------------------------------------------- /mmseg/configs/_base_/schedules/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/configs/_base_/schedules/__init__.py -------------------------------------------------------------------------------- /mmseg/engine/hooks/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .visualization_hook import SegVisualizationHook 3 | 4 | __all__ = ['SegVisualizationHook'] 5 | -------------------------------------------------------------------------------- /mmseg/engine/optimizers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .force_default_constructor import ForceDefaultOptimWrapperConstructor 3 | from .layer_decay_optimizer_constructor import ( 4 | LayerDecayOptimizerConstructor, LearningRateDecayOptimizerConstructor) 5 | 6 | __all__ = [ 7 | 'LearningRateDecayOptimizerConstructor', 'LayerDecayOptimizerConstructor', 8 | 'ForceDefaultOptimWrapperConstructor' 9 | ] 10 | -------------------------------------------------------------------------------- /mmseg/engine/schedulers/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .poly_ratio_scheduler import PolyLRRatio 3 | 4 | __all__ = ['PolyLRRatio'] 5 | -------------------------------------------------------------------------------- /mmseg/evaluation/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .metrics import CityscapesMetric, DepthMetric, IoUMetric 3 | 4 | __all__ = ['IoUMetric', 'CityscapesMetric', 'DepthMetric'] 5 | -------------------------------------------------------------------------------- /mmseg/evaluation/metrics/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .citys_metric import CityscapesMetric 3 | from .depth_metric import DepthMetric 4 | from .iou_metric import IoUMetric 5 | 6 | __all__ = ['IoUMetric', 'CityscapesMetric', 'DepthMetric'] 7 | -------------------------------------------------------------------------------- /mmseg/models/assigners/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_assigner import BaseAssigner 3 | from .hungarian_assigner import HungarianAssigner 4 | from .match_cost import ClassificationCost, CrossEntropyLossCost, DiceCost 5 | 6 | __all__ = [ 7 | 'BaseAssigner', 8 | 'HungarianAssigner', 9 | 'ClassificationCost', 10 | 'CrossEntropyLossCost', 11 | 'DiceCost', 12 | ] 13 | -------------------------------------------------------------------------------- /mmseg/models/necks/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .featurepyramid import Feature2Pyramid 3 | from .fpn import FPN 4 | from .ic_neck import ICNeck 5 | from .jpu import JPU 6 | from .mla_neck import MLANeck 7 | from .multilevel_neck import MultiLevelNeck 8 | 9 | __all__ = [ 10 | 'FPN', 'MultiLevelNeck', 'MLANeck', 'ICNeck', 'JPU', 'Feature2Pyramid' 11 | ] 12 | -------------------------------------------------------------------------------- /mmseg/models/text_encoder/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .clip_text_encoder import CLIPTextEncoder 3 | 4 | __all__ = ['CLIPTextEncoder'] 5 | -------------------------------------------------------------------------------- /mmseg/structures/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .sampler import BasePixelSampler, OHEMPixelSampler, build_pixel_sampler 3 | from .seg_data_sample import SegDataSample 4 | 5 | __all__ = [ 6 | 'SegDataSample', 'BasePixelSampler', 'OHEMPixelSampler', 7 | 'build_pixel_sampler' 8 | ] 9 | -------------------------------------------------------------------------------- /mmseg/structures/sampler/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .base_pixel_sampler import BasePixelSampler 3 | from .builder import build_pixel_sampler 4 | from .ohem_pixel_sampler import OHEMPixelSampler 5 | 6 | __all__ = ['build_pixel_sampler', 'BasePixelSampler', 'OHEMPixelSampler'] 7 | -------------------------------------------------------------------------------- /mmseg/structures/sampler/base_pixel_sampler.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from abc import ABCMeta, abstractmethod 3 | 4 | 5 | class BasePixelSampler(metaclass=ABCMeta): 6 | """Base class of pixel sampler.""" 7 | 8 | def __init__(self, **kwargs): 9 | pass 10 | 11 | @abstractmethod 12 | def sample(self, seg_logit, seg_label): 13 | """Placeholder for sample function.""" 14 | -------------------------------------------------------------------------------- /mmseg/utils/bpe_simple_vocab_16e6.txt.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/mmseg/utils/bpe_simple_vocab_16e6.txt.gz -------------------------------------------------------------------------------- /mmseg/visualization/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) OpenMMLab. All rights reserved. 2 | from .local_visualizer import SegLocalVisualizer 3 | 4 | __all__ = ['SegLocalVisualizer'] 5 | -------------------------------------------------------------------------------- /sam2/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. 2 | # All rights reserved. 3 | 4 | # This source code is licensed under the license found in the 5 | # LICENSE file in the root directory of this source tree. 6 | 7 | from hydra import initialize_config_module 8 | from hydra.core.global_hydra import GlobalHydra 9 | 10 | if not GlobalHydra.instance().is_initialized(): 11 | initialize_config_module("sam2", version_base="1.2") 12 | -------------------------------------------------------------------------------- /sam2/custom_model/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/sam2/custom_model/__init__.py -------------------------------------------------------------------------------- /sam2/modeling/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. 2 | # All rights reserved. 3 | 4 | # This source code is licensed under the license found in the 5 | # LICENSE file in the root directory of this source tree. 6 | -------------------------------------------------------------------------------- /sam2/modeling/backbones/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. 2 | # All rights reserved. 3 | 4 | # This source code is licensed under the license found in the 5 | # LICENSE file in the root directory of this source tree. 6 | -------------------------------------------------------------------------------- /sam2/modeling/sam/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. 2 | # All rights reserved. 3 | 4 | # This source code is licensed under the license found in the 5 | # LICENSE file in the root directory of this source tree. 6 | -------------------------------------------------------------------------------- /sam2/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) Meta Platforms, Inc. and affiliates. 2 | # All rights reserved. 3 | 4 | # This source code is licensed under the license found in the 5 | # LICENSE file in the root directory of this source tree. 6 | -------------------------------------------------------------------------------- /setup_env.sh: -------------------------------------------------------------------------------- 1 | source ~/.bashrc 2 | conda activate TextRegion 3 | 4 | cd sam2 5 | pip install -e . 6 | cd .. 7 | 8 | pip install -r requirements.txt 9 | pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu121 10 | 11 | cd mmseg 12 | pip install -v -e . 13 | pip install mmcv==2.1.0 -f https://download.openmmlab.com/mmcv/dist/cu121/torch2.1/index.html 14 | cd .. -------------------------------------------------------------------------------- /utils/LISA/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/utils/LISA/__init__.py -------------------------------------------------------------------------------- /utils/LISA/constants.py: -------------------------------------------------------------------------------- 1 | CONTROLLER_HEART_BEAT_EXPIRATION = 30 2 | WORKER_HEART_BEAT_INTERVAL = 15 3 | 4 | LOGDIR = "." 5 | 6 | # Model Constants 7 | IGNORE_INDEX = -100 8 | IMAGE_TOKEN_INDEX = -200 9 | DEFAULT_IMAGE_TOKEN = "" 10 | DEFAULT_IMAGE_PATCH_TOKEN = "" 11 | DEFAULT_IM_START_TOKEN = "" 12 | DEFAULT_IM_END_TOKEN = "" 13 | IMAGE_PLACEHOLDER = "" 14 | -------------------------------------------------------------------------------- /utils/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/avaxiao/TextRegion/e92c49e5ff0ab74796fda6e78456142b5db54a82/utils/__init__.py -------------------------------------------------------------------------------- /utils/image_query_label.yaml: -------------------------------------------------------------------------------- 1 | ./assets/dino_two_dogs.jpg: 2 | label: ['dog', 'chair', 'floor'] 3 | 4 | ./assets/sam2_truck.jpg: 5 | label: ['window', 'wheel', 'wall'] 6 | 7 | ./assets/boats_ambulance.jpg: 8 | label: ['sky', 'water', 'boat'] --------------------------------------------------------------------------------