{"id":20062948,"url":"https://github.com/segmentationblwx/sssegmentation","last_synced_at":"2025-04-13T11:39:18.263Z","repository":{"id":40392326,"uuid":"306540019","full_name":"SegmentationBLWX/sssegmentation","owner":"SegmentationBLWX","description":"SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch.","archived":false,"fork":false,"pushed_at":"2025-01-27T13:34:41.000Z","size":4496,"stargazers_count":835,"open_issues_count":5,"forks_count":106,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-04-12T23:44:35.916Z","etag":null,"topics":["deeplab","deeplabv3","edgesam","isnet","mask2former","maskformer","mcibi","mobilesam","ocrnet","pspnet","samhq","segfomer","segment-anything","segment-anything-2","semantic-segmentation","twins"],"latest_commit_sha":null,"homepage":"https://sssegmentation.readthedocs.io/en/latest/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/SegmentationBLWX.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null},"funding":{"patreon":"CharlesPikachu","ko_fi":"charlespikachu","custom":"https://github.com/CharlesPikachu/Games/tree/master/.github/pictures/alipay.JPG"}},"created_at":"2020-10-23T05:43:02.000Z","updated_at":"2025-04-12T12:58:05.000Z","dependencies_parsed_at":"2024-02-19T17:40:31.448Z","dependency_job_id":"0d161340-5b65-4d47-8b28-f5d136e07a6a","html_url":"https://github.com/SegmentationBLWX/sssegmentation","commit_stats":{"total_commits":819,"total_committers":1,"mean_commits":819.0,"dds":0.0,"last_synced_commit":"ffafacbb41ef5120050f7feb06b5c6d773321819"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SegmentationBLWX%2Fsssegmentation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SegmentationBLWX%2Fsssegmentation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SegmentationBLWX%2Fsssegmentation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SegmentationBLWX%2Fsssegmentation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SegmentationBLWX","download_url":"https://codeload.github.com/SegmentationBLWX/sssegmentation/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248709165,"owners_count":21149138,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deeplab","deeplabv3","edgesam","isnet","mask2former","maskformer","mcibi","mobilesam","ocrnet","pspnet","samhq","segfomer","segment-anything","segment-anything-2","semantic-segmentation","twins"],"created_at":"2024-11-13T13:39:38.917Z","updated_at":"2025-04-13T11:39:18.226Z","avatar_url":"https://github.com/SegmentationBLWX.png","language":"Python","funding_links":["https://patreon.com/CharlesPikachu","https://ko-fi.com/charlespikachu","https://github.com/CharlesPikachu/Games/tree/master/.github/pictures/alipay.JPG"],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"./docs/logo.png\" width=\"600\"/\u003e\n\u003c/div\u003e\n\u003cbr /\u003e\n\n[![docs](https://img.shields.io/badge/docs-latest-blue)](https://sssegmentation.readthedocs.io/en/latest/)\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/sssegmentation)](https://pypi.org/project/sssegmentation/)\n[![PyPI](https://img.shields.io/pypi/v/sssegmentation)](https://pypi.org/project/sssegmentation)\n[![license](https://img.shields.io/github/license/SegmentationBLWX/sssegmentation.svg)](https://github.com/SegmentationBLWX/sssegmentation/blob/main/LICENSE)\n[![PyPI - Downloads](https://static.pepy.tech/badge/sssegmentation)](https://pypi.org/project/sssegmentation/)\n[![PyPI - Downloads](https://img.shields.io/pypi/dm/sssegmentation?style=flat-square)](https://pypi.org/project/sssegmentation/)\n[![issue resolution](https://isitmaintained.com/badge/resolution/SegmentationBLWX/sssegmentation.svg)](https://github.com/SegmentationBLWX/sssegmentation/issues)\n[![open issues](https://isitmaintained.com/badge/open/SegmentationBLWX/sssegmentation.svg)](https://github.com/SegmentationBLWX/sssegmentation/issues)\n[![GitHub last commit (main)](https://img.shields.io/github/last-commit/SegmentationBLWX/sssegmentation/main.svg)](https://github.com/SegmentationBLWX/sssegmentation/commits/main/)\n\nDocuments: https://sssegmentation.readthedocs.io/en/latest/\n\n\n## What's New\n\n- **2024-08-05**: Support [SAMV2](https://arxiv.org/pdf/2408.00714.pdf), refer to [inference-with-samv2](https://sssegmentation.readthedocs.io/en/latest/AdvancedAPI.html#inference-with-samv2) for more details.\n- **2023-12-20**: Support [EdgeSAM](https://arxiv.org/pdf/2312.06660.pdf) and [SAMHQ](https://arxiv.org/pdf/2306.01567.pdf), refer to [inference-with-edgesam](https://sssegmentation.readthedocs.io/en/latest/AdvancedAPI.html#inference-with-edgesam) and [inference-with-samhq](https://sssegmentation.readthedocs.io/en/latest/AdvancedAPI.html#inference-with-samhq) for more details.\n- **2023-10-25**: Support [ConvNeXtV2](https://arxiv.org/pdf/2301.00808.pdf), refer to [Results and Models for ConvNeXtV2](./docs/modelzoo/convnextv2) for more details.\n- **2023-10-23**: Support [MobileViT](https://arxiv.org/pdf/2110.02178.pdf) and [MobileViTV2](https://arxiv.org/pdf/2206.02680.pdf), refer to [Results and Models for MobileViT](./docs/modelzoo/mobilevit) for more details.\n- **2023-10-18**: Support [Mask2Former](https://arxiv.org/pdf/2112.01527.pdf), refer to [Results and Models for Mask2Former](./docs/modelzoo/mask2former) for more details.\n- **2023-10-17**: We release the source codes of [IDRNet: Intervention-Driven Relation Network for Semantic Segmentation](https://arxiv.org/pdf/2310.10755.pdf), which was accepted by NeurIPS 2023, refer to [Results and Models for IDRNet](./docs/modelzoo/idrnet) for more details.\n- **2023-10-15**: Support [MobileSAM](https://arxiv.org/pdf/2306.14289.pdf), refer to [inference-with-mobilesam](https://sssegmentation.readthedocs.io/en/latest/AdvancedAPI.html#inference-with-mobilesam) for more details.\n- **2023-09-27**: Support [SAM](https://arxiv.org/pdf/2304.02643.pdf), refer to [inference-with-sam](https://sssegmentation.readthedocs.io/en/latest/AdvancedAPI.html#inference-with-sam) for more details.\n\n\n## Introduction\n\nSSSegmentation is an open source supervised semantic segmentation toolbox based on PyTorch.\nYou can star this repository to keep track of the project if it's helpful for you, thank you for your support.\n\n\n## Major Features\n\n- **High Performance**\n\n  The performance of re-implemented segmentation algorithms is better than or comparable to other codebases.\n \n- **Modular Design and Unified Benchmark**\n  \n  Various segmentation methods are unified into several specific modules.\n  Benefiting from this design, SSSegmentation can integrate a great deal of popular and contemporary semantic segmentation frameworks and then, train and test them on unified benchmarks.\n  \n- **Fewer Dependencies**\n\n  SSSegmenation tries its best to avoid introducing more dependencies when reproducing novel semantic segmentation approaches.\n \n\n## Benchmark and Model Zoo\n\n#### Supported Backbones\n\n| Backbone               | Model Zoo                                    | Paper Link                                                    | Code Snippet                                             |\n| :-:                    | :-:                                          | :-:                                                           | :-:                                                      |\n| ConvNeXtV2             | [Click](./docs/modelzoo/convnextv2)          | [CVPR 2023](https://arxiv.org/pdf/2301.00808.pdf)             | [Click](./ssseg/modules/models/backbones/convnextv2.py)  |\n| MobileViTV2            | [Click](./docs/modelzoo/mobilevit)           | [ArXiv 2022](https://arxiv.org/pdf/2206.02680.pdf)            | [Click](./ssseg/modules/models/backbones/mobilevit.py)   |\n| ConvNeXt               | [Click](./docs/modelzoo/convnext)            | [CVPR 2022](https://arxiv.org/pdf/2201.03545.pdf)             | [Click](./ssseg/modules/models/backbones/convnext.py)    |\n| MAE                    | [Click](./docs/modelzoo/mae)                 | [CVPR 2022](https://arxiv.org/pdf/2111.06377.pdf)             | [Click](./ssseg/modules/models/backbones/mae.py)         |\n| MobileViT              | [Click](./docs/modelzoo/mobilevit)           | [ICLR 2022](https://arxiv.org/pdf/2110.02178.pdf)             | [Click](./ssseg/modules/models/backbones/mobilevit.py)   |\n| BEiT                   | [Click](./docs/modelzoo/beit)                | [ICLR 2022](https://arxiv.org/pdf/2106.08254.pdf)             | [Click](./ssseg/modules/models/backbones/beit.py)        |\n| Twins                  | [Click](./docs/modelzoo/twins)               | [NeurIPS 2021](https://arxiv.org/pdf/2104.13840.pdf)          | [Click](./ssseg/modules/models/backbones/twins.py)       |\n| SwinTransformer        | [Click](./docs/modelzoo/swin)                | [ICCV 2021](https://arxiv.org/pdf/2103.14030.pdf)             | [Click](./ssseg/modules/models/backbones/swin.py)        |\n| VisionTransformer      | [Click](./docs/modelzoo/setr)                | [IClR 2021](https://arxiv.org/pdf/2010.11929.pdf)             | [Click](./ssseg/modules/models/backbones/vit.py)         |\n| BiSeNetV2              | [Click](./docs/modelzoo/bisenetv2)           | [IJCV 2021](https://arxiv.org/pdf/2004.02147.pdf)             | [Click](./ssseg/modules/models/backbones/bisenetv2.py)   |\n| ResNeSt                | [Click](./docs/modelzoo/resnest)             | [ArXiv 2020](https://arxiv.org/pdf/2004.08955.pdf)            | [Click](./ssseg/modules/models/backbones/resnest.py)     |\n| CGNet                  | [Click](./docs/modelzoo/cgnet)               | [TIP 2020](https://arxiv.org/pdf/1811.08201.pdf)              | [Click](./ssseg/modules/models/backbones/cgnet.py)       |\n| HRNet                  | [Click](./docs/modelzoo/ocrnet)              | [CVPR 2019](https://arxiv.org/pdf/1908.07919.pdf)             | [Click](./ssseg/modules/models/backbones/hrnet.py)       |\n| MobileNetV3            | [Click](./docs/modelzoo/mobilenet)           | [ICCV 2019](https://arxiv.org/pdf/1905.02244.pdf)             | [Click](./ssseg/modules/models/backbones/mobilenet.py)   |\n| FastSCNN               | [Click](./docs/modelzoo/fastscnn)            | [ArXiv 2019](https://arxiv.org/pdf/1902.04502.pdf)            | [Click](./ssseg/modules/models/backbones/fastscnn.py)    |\n| BiSeNetV1              | [Click](./docs/modelzoo/bisenetv1)           | [ECCV 2018](https://arxiv.org/pdf/1808.00897.pdf)             | [Click](./ssseg/modules/models/backbones/bisenetv1.py)   |\n| MobileNetV2            | [Click](./docs/modelzoo/mobilenet)           | [CVPR 2018](https://arxiv.org/pdf/1801.04381.pdf)             | [Click](./ssseg/modules/models/backbones/mobilenet.py)   |\n| ERFNet                 | [Click](./docs/modelzoo/erfnet)              | [T-ITS 2017](https://ieeexplore.ieee.org/document/8063438)    | [Click](./ssseg/modules/models/backbones/erfnet.py)      |\n| ResNet                 | [Click](./docs/modelzoo/fcn)                 | [CVPR 2016](https://arxiv.org/pdf/1512.03385.pdf)             | [Click](./ssseg/modules/models/backbones/resnet.py)      |\n| UNet                   | [Click](./docs/modelzoo/unet)                | [MICCAI 2015](https://arxiv.org/pdf/1505.04597.pdf)           | [Click](./ssseg/modules/models/backbones/unet.py)        |\n\n#### Supported Segmentors\n\n| Segmentor                         | Model Zoo                                    | Paper Link                                                                                                                                              | Code Snippet                                                                |\n| :-:                               | :-:                                          | :-:                                                                                                                                                     | :-:                                                                         |\n| SAMV2                             | [Click](./docs/modelzoo/samv2)               | [ArXiv 2024](https://arxiv.org/pdf/2408.00714.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/samv2/samv2.py)                   |\n| EdgeSAM                           | [Click](./docs/modelzoo/edgesam)             | [ArXiv 2023](https://arxiv.org/pdf/2312.06660.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/edgesam/edgesam.py)               |\n| IDRNet                            | [Click](./docs/modelzoo/idrnet)              | [NeurIPS 2023](https://arxiv.org/pdf/2310.10755.pdf)                                                                                                    | [Click](./ssseg/modules/models/segmentors/idrnet/idrnet.py)                 |\n| MobileSAM                         | [Click](./docs/modelzoo/mobilesam)           | [ArXiv 2023](https://arxiv.org/pdf/2306.14289.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/mobilesam/mobilesam.py)           |\n| SAMHQ                             | [Click](./docs/modelzoo/samhq)               | [NeurIPS 2023](https://arxiv.org/pdf/2306.01567.pdf)                                                                                                    | [Click](./ssseg/modules/models/segmentors/samhq/samhq.py)                   |\n| SAM                               | [Click](./docs/modelzoo/sam)                 | [ArXiv 2023](https://arxiv.org/pdf/2304.02643.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/sam/sam.py)                       |\n| MCIBI++                           | [Click](./docs/modelzoo/mcibiplusplus)       | [TPAMI 2022](https://arxiv.org/pdf/2209.04471.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/mcibiplusplus/mcibiplusplus.py)   |\n| Mask2Former                       | [Click](./docs/modelzoo/mask2former)         | [CVPR 2022](https://arxiv.org/pdf/2112.01527.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/mask2former/mask2former.py)       |\n| ISNet                             | [Click](./docs/modelzoo/isnet)               | [ICCV 2021](https://arxiv.org/pdf/2108.12382.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/isnet/isnet.py)                   |\n| MCIBI                             | [Click](./docs/modelzoo/mcibi)               | [ICCV 2021](https://arxiv.org/pdf/2108.11819.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/mcibi/mcibi.py)                   |\n| MaskFormer                        | [Click](./docs/modelzoo/maskformer)          | [NeurIPS 2021](https://arxiv.org/pdf/2107.06278.pdf)                                                                                                    | [Click](./ssseg/modules/models/segmentors/maskformer/maskformer.py)         |\n| Segformer                         | [Click](./docs/modelzoo/segformer)           | [NeurIPS 2021](https://arxiv.org/pdf/2105.15203.pdf)                                                                                                    | [Click](./ssseg/modules/models/segmentors/segformer/segformer.py)           |\n| SETR                              | [Click](./docs/modelzoo/setr)                | [CVPR 2021](https://arxiv.org/pdf/2012.15840.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/setr/setr.py)                     |\n| ISANet                            | [Click](./docs/modelzoo/isanet)              | [IJCV 2021](https://arxiv.org/pdf/1907.12273.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/isanet/isanet.py)                 |\n| DNLNet                            | [Click](./docs/modelzoo/dnlnet)              | [ECCV 2020](https://arxiv.org/pdf/2006.06668.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/dnlnet/dnlnet.py)                 |\n| PointRend                         | [Click](./docs/modelzoo/pointrend)           | [CVPR 2020](https://arxiv.org/pdf/1912.08193.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/pointrend/pointrend.py)           |\n| OCRNet                            | [Click](./docs/modelzoo/ocrnet)              | [ECCV 2020](https://arxiv.org/pdf/1909.11065.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/ocrnet/ocrnet.py)                 |\n| GCNet                             | [Click](./docs/modelzoo/gcnet)               | [TPAMI 2020](https://arxiv.org/pdf/1904.11492.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/gcnet/gcnet.py)                   |\n| APCNet                            | [Click](./docs/modelzoo/apcnet)              | [CVPR 2019](https://openaccess.thecvf.com/content_CVPR_2019/papers/He_Adaptive_Pyramid_Context_Network_for_Semantic_Segmentation_CVPR_2019_paper.pdf)   | [Click](./ssseg/modules/models/segmentors/apcnet/apcnet.py)                 |\n| DMNet                             | [Click](./docs/modelzoo/dmnet)               | [ICCV 2019](https://openaccess.thecvf.com/content_ICCV_2019/papers/He_Dynamic_Multi-Scale_Filters_for_Semantic_Segmentation_ICCV_2019_paper.pdf)        | [Click](./ssseg/modules/models/segmentors/dmnet/dmnet.py)                   |\n| ANNNet                            | [Click](./docs/modelzoo/annnet)              | [ICCV 2019](https://arxiv.org/pdf/1908.07678.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/annnet/annnet.py)                 |\n| EMANet                            | [Click](./docs/modelzoo/emanet)              | [ICCV 2019](https://arxiv.org/pdf/1907.13426.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/emanet/emanet.py)                 |\n| FastFCN                           | [Click](./docs/modelzoo/fastfcn)             | [ArXiv 2019](https://arxiv.org/pdf/1903.11816.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/fastfcn/fastfcn.py)               |\n| SemanticFPN                       | [Click](./docs/modelzoo/semanticfpn)         | [CVPR 2019](https://arxiv.org/pdf/1901.02446.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/semanticfpn/semanticfpn.py)       |\n| CCNet                             | [Click](./docs/modelzoo/ccnet)               | [ICCV 2019](https://arxiv.org/pdf/1811.11721.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/ccnet/ccnet.py)                   |\n| CE2P                              | [Click](./docs/modelzoo/ce2p)                | [AAAI 2019](https://arxiv.org/pdf/1809.05996.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/ce2p/ce2p.py)                     |\n| DANet                             | [Click](./docs/modelzoo/danet)               | [CVPR 2019](https://arxiv.org/pdf/1809.02983.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/danet/danet.py)                   |\n| PSANet                            | [Click](./docs/modelzoo/psanet)              | [ECCV 2018](https://openaccess.thecvf.com/content_ECCV_2018/papers/Hengshuang_Zhao_PSANet_Point-wise_Spatial_ECCV_2018_paper.pdf)                       | [Click](./ssseg/modules/models/segmentors/psanet/psanet.py)                 |\n| UPerNet                           | [Click](./docs/modelzoo/upernet)             | [ECCV 2018](https://arxiv.org/pdf/1807.10221.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/upernet/upernet.py)               |\n| EncNet                            | [Click](./docs/modelzoo/encnet)              | [CVPR 2018](https://arxiv.org/pdf/1803.08904.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/encnet/encnet.py)                 |\n| Deeplabv3Plus                     | [Click](./docs/modelzoo/deeplabv3plus)       | [ECCV 2018](https://arxiv.org/pdf/1802.02611.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/deeplabv3plus/deeplabv3plus.py)   |\n| NonLocalNet                       | [Click](./docs/modelzoo/nonlocalnet)         | [CVPR 2018](https://arxiv.org/pdf/1711.07971.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/nonlocalnet/nonlocalnet.py)       |\n| ICNet                             | [Click](./docs/modelzoo/icnet)               | [ECCV 2018](https://arxiv.org/pdf/1704.08545.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/icnet/icnet.py)                   |\n| Mixed Precision (FP16) Training   | [Click](./docs/modelzoo/fp16)                | [ArXiv 2017](https://arxiv.org/pdf/1710.03740.pdf)                                                                                                      | [Click](./ssseg/train.py)                                                   |\n| Deeplabv3                         | [Click](./docs/modelzoo/deeplabv3)           | [ArXiv 2017](https://arxiv.org/pdf/1706.05587.pdf)                                                                                                      | [Click](./ssseg/modules/models/segmentors/deeplabv3/deeplabv3.py)           |\n| PSPNet                            | [Click](./docs/modelzoo/pspnet)              | [CVPR 2017](https://arxiv.org/pdf/1612.01105.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/pspnet/pspnet.py)                 |\n| FCN                               | [Click](./docs/modelzoo/fcn)                 | [TPAMI 2017](https://arxiv.org/pdf/1411.4038.pdf)                                                                                                       | [Click](./ssseg/modules/models/segmentors/fcn/fcn.py)                       |\n\n#### Supported Datasets\n\n| Dataset                | Project Link                                                                               | Paper Link                                                                                                         | Code Snippet                                             | Download Script                                                                                                                 |\n| :-:                    | :-:                                                                                        | :-:                                                                                                                | :-:                                                      | :-:                                                                                                                             |\n| VSPW                   | [Click](https://www.vspwdataset.com/)                                                      | [CVPR 2021](https://yu-wu.net/pdf/CVPR21-vspw.pdf)                                                                 | [Click](./ssseg/modules/datasets/vspw.py)                | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh vspw` \u003c/details\u003e                                              |\n| Supervisely            | [Click](https://supervise.ly/explore/projects/supervisely-person-dataset-23304/datasets)   | [Website Release 2020](https://ecosystem.supervisely.com/projects/persons)                                         | [Click](./ssseg/modules/datasets/supervisely.py)         | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh supervisely` \u003c/details\u003e                                       |\n| Dark Zurich            | [Click](https://data.vision.ee.ethz.ch/csakarid/shared/GCMA_UIoU/Dark_Zurich_val_anon.zip) | [ICCV 2019](https://arxiv.org/pdf/1901.05946.pdf)                                                                  | [Click](./ssseg/modules/datasets/darkzurich.py)          | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh darkzurich` \u003c/details\u003e                                        |\n| Nighttime Driving      | [Click](http://data.vision.ee.ethz.ch/daid/NighttimeDriving/NighttimeDrivingTest.zip)      | [ITSC 2018](https://arxiv.org/pdf/1810.02575.pdf)                                                                  | [Click](./ssseg/modules/datasets/nighttimedriving.py)    | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh nighttimedriving` \u003c/details\u003e                                  |\n| CIHP                   | [Click](http://sysu-hcp.net/lip/overview.php)                                              | [ECCV 2018](https://arxiv.org/pdf/1808.00157.pdf)                                                                  | [Click](./ssseg/modules/datasets/cihp.py)                | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh cihp` \u003c/details\u003e                                              |\n| COCOStuff10k           | [Click](https://github.com/nightrome/cocostuff10k)                                         | [CVPR 2018](https://arxiv.org/pdf/1612.03716.pdf)                                                                  | [Click](./ssseg/modules/datasets/coco.py)                | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh cocostuff10k` \u003c/details\u003e                                      |\n| COCOStuff164k          | [Click](https://github.com/nightrome/cocostuff)                                            | [CVPR 2018](https://arxiv.org/pdf/1612.03716.pdf)                                                                  | [Click](./ssseg/modules/datasets/coco.py)                | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh coco` \u003c/details\u003e                                              |\n| MHPv1\u0026v2               | [Click](https://lv-mhp.github.io/dataset)                                                  | [ArXiv 2017](https://arxiv.org/pdf/1705.07206.pdf)                                                                 | [Click](./ssseg/modules/datasets/mhp.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh mhpv1` \u0026 `bash scripts/prepare_datasets.sh mhpv2` \u003c/details\u003e  |\n| LIP                    | [Click](http://sysu-hcp.net/lip/)                                                          | [CVPR 2017](https://arxiv.org/pdf/1703.05446.pdf)                                                                  | [Click](./ssseg/modules/datasets/lip.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh lip` \u003c/details\u003e                                               |\n| ADE20k                 | [Click](https://groups.csail.mit.edu/vision/datasets/ADE20K/)                              | [CVPR 2017](https://arxiv.org/pdf/1608.05442.pdf)                                                                  | [Click](./ssseg/modules/datasets/ade20k.py)              | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh ade20k` \u003c/details\u003e                                            |\n| SBUShadow              | [Click](https://www3.cs.stonybrook.edu/~cvl/projects/shadow_noisy_label/index.html)        | [ECCV 2016](https://www3.cs.stonybrook.edu/~cvl/content/papers/2016/LSS_ECCV16.pdf?)                               | [Click](./ssseg/modules/datasets/sbushadow.py)           | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh sbushadow` \u003c/details\u003e                                         |\n| CityScapes             | [Click](https://www.cityscapes-dataset.com/)                                               | [CVPR 2016](https://arxiv.org/pdf/1604.01685.pdf)                                                                  | [Click](./ssseg/modules/datasets/cityscapes.py)          | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh cityscapes` \u003c/details\u003e                                        |\n| ATR                    | [Click](http://sysu-hcp.net/lip/overview.php)                                              | [ICCV 2015](https://openaccess.thecvf.com/content_iccv_2015/papers/Liang_Human_Parsing_With_ICCV_2015_paper.pdf)   | [Click](./ssseg/modules/datasets/atr.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh atr` \u003c/details\u003e                                               |\n| Pascal Context         | [Click](https://cs.stanford.edu/~roozbeh/pascal-context/)                                  | [CVPR 2014](https://cs.stanford.edu/~roozbeh/pascal-context/mottaghi_et_al_cvpr14.pdf)                             | [Click](./ssseg/modules/datasets/voc.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh pascalcontext` \u003c/details\u003e                                     |\n| MS COCO                | [Click](https://cocodataset.org/#home)                                                     | [ECCV 2014](https://arxiv.org/pdf/1405.0312.pdf)                                                                   | [Click](./ssseg/modules/datasets/coco.py)                | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh coco` \u003c/details\u003e                                              |\n| HRF                    | [Click](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/)                 | [Int J Biomed Sci 2013](https://www.hindawi.com/journals/ijbi/2013/154860/)                                        | [Click](./ssseg/modules/datasets/hrf.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh hrf` \u003c/details\u003e                                               |\n| CHASE DB1              | [Click](https://staffnet.kingston.ac.uk/~ku15565/)                                         | [TBME 2012](https://ieeexplore.ieee.org/document/6224174)                                                          | [Click](./ssseg/modules/datasets/chasedb1.py)            | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh chase_db1` \u003c/details\u003e                                         |\n| PASCAL VOC             | [Click](http://host.robots.ox.ac.uk/pascal/VOC/)                                           | [IJCV 2010](http://host.robots.ox.ac.uk/pascal/VOC/pubs/everingham10.pdf)                                          | [Click](./ssseg/modules/datasets/voc.py)                 | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh pascalvoc` \u003c/details\u003e                                         |\n| DRIVE                  | [Click](https://drive.grand-challenge.org/)                                                | [TMI 2004](https://ieeexplore.ieee.org/document/1282003)                                                           | [Click](./ssseg/modules/datasets/drive.py)               | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh drive` \u003c/details\u003e                                             |\n| STARE                  | [Click](http://cecas.clemson.edu/~ahoover/stare/)                                          | [TMI 2000](https://ieeexplore.ieee.org/document/845178)                                                            | [Click](./ssseg/modules/datasets/stare.py)               | \u003cdetails\u003e\u003csummary\u003eCMD\u003c/summary\u003e `bash scripts/prepare_datasets.sh stare` \u003c/details\u003e                                             |\n\n\n## Citation\n\nIf you use SSSegmentation in your research, please consider citing this project,\n\n```\n@article{jin2023sssegmenation,\n    title={SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch},\n    author={Jin, Zhenchao},\n    journal={arXiv preprint arXiv:2305.17091},\n    year={2023}\n}\n\n@inproceedings{jin2021isnet,\n    title={ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation},\n    author={Jin, Zhenchao and Liu, Bin and Chu, Qi and Yu, Nenghai},\n    booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n    pages={7189--7198},\n    year={2021}\n}\n\n@inproceedings{jin2021mining,\n    title={Mining Contextual Information Beyond Image for Semantic Segmentation},\n    author={Jin, Zhenchao and Gong, Tao and Yu, Dongdong and Chu, Qi and Wang, Jian and Wang, Changhu and Shao, Jie},\n    booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n    pages={7231--7241},\n    year={2021}\n}\n\n@article{jin2022mcibi++,\n    title={MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation},\n    author={Jin, Zhenchao and Yu, Dongdong and Yuan, Zehuan and Yu, Lequan},\n    journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},\n    year={2022},\n    publisher={IEEE}\n}\n\n@inproceedings{jin2023idrnet,\n    title={IDRNet: Intervention-Driven Relation Network for Semantic Segmentation},\n    author={Jin, Zhenchao and Hu, Xiaowei and Zhu, Lingting and Song, Luchuan and Yuan, Li and Yu, Lequan},\n    booktitle={Thirty-Seventh Conference on Neural Information Processing Systems},\n    year={2023}\n}\n```\n\n\n## References\n\nWe are very grateful to the following projects for their help in building SSSegmentation,\n\n- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation)\n- [segment-anything](https://github.com/facebookresearch/segment-anything)\n- [MobileSAM](https://github.com/ChaoningZhang/MobileSAM)\n- [Mask2Former](https://github.com/facebookresearch/Mask2Former/)\n- [Swin-Transformer](https://github.com/microsoft/Swin-Transformer)\n- [HRNet-Semantic-Segmentation](https://github.com/HRNet/HRNet-Semantic-Segmentation)\n- [apex](https://github.com/NVIDIA/apex)\n- [MMCV](https://github.com/open-mmlab/mmcv)\n- [VSPW_code](https://github.com/VSPW-dataset/VSPW_code)\n- [MMPreTrain](https://github.com/open-mmlab/mmpretrain)\n- [PyTorch Image Models](https://github.com/huggingface/pytorch-image-models)\n- [EdgeSAM](https://github.com/chongzhou96/EdgeSAM)\n- [sam-hq](https://github.com/SysCV/sam-hq)\n- [segment-anything-2](https://github.com/facebookresearch/segment-anything-2)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsegmentationblwx%2Fsssegmentation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsegmentationblwx%2Fsssegmentation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsegmentationblwx%2Fsssegmentation/lists"}