sssegmentation

SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch.

https://github.com/segmentationblwx/sssegmentation

Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
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DOI references
✓
Academic publication links
Links to: arxiv.org, ieee.org
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Committers with academic emails
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (8.5%) to scientific vocabulary

Keywords

deeplab deeplabv3 edgesam isnet mask2former maskformer mcibi mobilesam ocrnet pspnet samhq segfomer segment-anything segment-anything-2 semantic-segmentation twins

Scientific Fields

Mathematics Computer Science - 84% confidence

Last synced: 4 months ago · JSON representation ·

Repository

SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch.

Basic Info

Host: GitHub
Owner: SegmentationBLWX
License: apache-2.0
Language: Python
Default Branch: main
Homepage: https://sssegmentation.readthedocs.io/en/latest/
Size: 4.71 MB

Statistics

Stars: 861
Watchers: 9
Forks: 109
Open Issues: 6
Releases: 0

Topics

deeplab deeplabv3 edgesam isnet mask2former maskformer mcibi mobilesam ocrnet pspnet samhq segfomer segment-anything segment-anything-2 semantic-segmentation twins

Created about 5 years ago · Last pushed 4 months ago

Metadata Files

Readme Funding License Citation

README.md

Documents: https://sssegmentation.readthedocs.io/en/latest/

What's New

2024-08-05: Support SAMV2, refer to inference-with-samv2 for more details.
2023-12-20: Support EdgeSAM and SAMHQ, refer to inference-with-edgesam and inference-with-samhq for more details.
2023-10-25: Support ConvNeXtV2, refer to Results and Models for ConvNeXtV2 for more details.
2023-10-23: Support MobileViT and MobileViTV2, refer to Results and Models for MobileViT for more details.
2023-10-18: Support Mask2Former, refer to Results and Models for Mask2Former for more details.
2023-10-17: We release the source codes of IDRNet: Intervention-Driven Relation Network for Semantic Segmentation, which was accepted by NeurIPS 2023, refer to Results and Models for IDRNet for more details.
2023-10-15: Support MobileSAM, refer to inference-with-mobilesam for more details.
2023-09-27: Support SAM, refer to inference-with-sam for more details.

Introduction

SSSegmentation is an open source supervised semantic segmentation toolbox based on PyTorch. You can star this repository to keep track of the project if it's helpful for you, thank you for your support.

Major Features

High Performance

The performance of re-implemented segmentation algorithms is better than or comparable to other codebases.

Modular Design and Unified Benchmark

Various segmentation methods are unified into several specific modules. 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.

Fewer Dependencies

SSSegmenation tries its best to avoid introducing more dependencies when reproducing novel semantic segmentation approaches.

Benchmark and Model Zoo

Supported Backbones

Supported Segmentors

Supported Datasets

CMD

bash scripts/prepare_datasets.sh vspw

CMD

bash scripts/prepare_datasets.sh supervisely

CMD

bash scripts/prepare_datasets.sh darkzurich

CMD

bash scripts/prepare_datasets.sh nighttimedriving

CMD

bash scripts/prepare_datasets.sh cihp

CMD

bash scripts/prepare_datasets.sh cocostuff10k

CMD

bash scripts/prepare_datasets.sh coco

CMD

bash scripts/prepare_datasets.sh mhpv1 & bash scripts/prepare_datasets.sh mhpv2

CMD

bash scripts/prepare_datasets.sh lip

CMD

bash scripts/prepare_datasets.sh ade20k

CMD

bash scripts/prepare_datasets.sh sbushadow

CMD

bash scripts/prepare_datasets.sh cityscapes

CMD

bash scripts/prepare_datasets.sh atr

CMD

bash scripts/prepare_datasets.sh pascalcontext

CMD

bash scripts/prepare_datasets.sh coco

CMD

bash scripts/prepare_datasets.sh hrf

CMD

bash scripts/prepare_datasets.sh chase_db1

CMD

bash scripts/prepare_datasets.sh pascalvoc

CMD

bash scripts/prepare_datasets.sh drive

CMD

bash scripts/prepare_datasets.sh stare

Citation

If you use SSSegmentation in your research, please consider citing this project,

``` @article{jin2023sssegmenation, title={SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch}, author={Jin, Zhenchao}, journal={arXiv preprint arXiv:2305.17091}, year={2023} }

@inproceedings{jin2021isnet, title={ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation}, author={Jin, Zhenchao and Liu, Bin and Chu, Qi and Yu, Nenghai}, booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision}, pages={7189--7198}, year={2021} }

@inproceedings{jin2021mining, title={Mining Contextual Information Beyond Image for Semantic Segmentation}, author={Jin, Zhenchao and Gong, Tao and Yu, Dongdong and Chu, Qi and Wang, Jian and Wang, Changhu and Shao, Jie}, booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision}, pages={7231--7241}, year={2021} }

@article{jin2022mcibi++, title={MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation}, author={Jin, Zhenchao and Yu, Dongdong and Yuan, Zehuan and Yu, Lequan}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, year={2022}, publisher={IEEE} }

@inproceedings{jin2023idrnet, title={IDRNet: Intervention-Driven Relation Network for Semantic Segmentation}, author={Jin, Zhenchao and Hu, Xiaowei and Zhu, Lingting and Song, Luchuan and Yuan, Li and Yu, Lequan}, booktitle={Thirty-Seventh Conference on Neural Information Processing Systems}, year={2023} } ```

References

We are very grateful to the following projects for their help in building SSSegmentation,

Owner

Name: SegmentationBLWX
Login: SegmentationBLWX
Kind: organization
Email: blwx@mail.ustc.edu.cn
Location: China

Website: https://charlespikachu.github.io/
Repositories: 2
Profile: https://github.com/SegmentationBLWX

Focus on semantic segmentation.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use SSSegmentation in your research, please consider citing this project."
authors:
  - name: "Zhenchao Jin"
title: "SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch"
date-released: 2020-10-23
url: "https://github.com/SegmentationBLWX/sssegmentation"
license: Apache-2.0

GitHub Events

Total

Issues event: 8
Watch event: 77
Issue comment event: 10
Push event: 147
Pull request event: 52
Fork event: 4
Create event: 1

Last Year

Issues event: 8
Watch event: 77
Issue comment event: 10
Push event: 147
Pull request event: 52
Fork event: 4
Create event: 1

Committers

Last synced: 10 months ago

All Time

Total Commits: 820
Total Committers: 1
Avg Commits per committer: 820.0
Development Distribution Score (DDS): 0.0

Past Year

Commits: 124
Committers: 1
Avg Commits per committer: 124.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
CharlesPikachu	1**1@q**m	820

Committer Domains (Top 20 + Academic)

qq.com: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time

Total issues: 64
Total pull requests: 2
Average time to close issues: about 2 months
Average time to close pull requests: 14 days
Total issue authors: 38
Total pull request authors: 2
Average comments per issue: 2.47
Average comments per pull request: 0.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 14
Pull requests: 2
Average time to close issues: 15 days
Average time to close pull requests: 14 days
Issue authors: 6
Pull request authors: 2
Average comments per issue: 1.64
Average comments per pull request: 0.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

STHxiao (11)
umarjibrilmohd (5)
qdd1234 (4)
TiankaiHang (3)
NJNUCS (3)
Junjun2016 (2)
dalexin (2)
shituo123456 (2)
123AOQW (2)
swjtulinxi (2)
zhushk21 (1)
shravankumar-concat (1)
TonFard (1)
cspearl (1)
SAWRJJ (1)

Pull Request Authors

CharlesPikachu (28)
ItsaFugazi (2)
sieu-n (2)

Top Labels

Issue Labels

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 626 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 16
Total maintainers: 1

pypi.org: sssegmentation

SSSegmentation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch

Homepage: https://github.com/SegmentationBLWX/sssegmentation
Documentation: https://sssegmentation.readthedocs.io/
License: Apache License 2.0
Latest release: 1.7.0
published 7 months ago

Versions: 16
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 626 Last month

Rankings

Stargazers count: 2.5%

Forks count: 4.7%

Dependent packages count: 7.3%

Average: 13.1%

Dependent repos count: 22.1%

Downloads: 28.7%

Maintainers (1)

Charles_Pikachu

Last synced: 4 months ago

Dependencies

docs/requirements.txt pypi

recommonmark *
sphinx ==4.5.0
sphinx_markdown_tables ==0.0.12
sphinx_rtd_theme *

requirements/evaluate.txt pypi

chainercv *
cityscapesscripts *

requirements/io.txt pypi

opencv-python *
pandas *
pillow *

requirements/nn.txt pypi

mmcv-full *
timm *
torch *
torchvision *

requirements/science.txt pypi

numpy *
scipy *

requirements/terminal.txt pypi

argparse *
tqdm *

requirements.txt pypi

setup.py pypi

requirements/augmentation.txt pypi

albumentations *

requirements/misc.txt pypi

cython *
fvcore *