Skip to main content

PyTorch Encoding Package

Project description

PyPI PyPI Pre-release Upload Python Package Downloads License: MIT Build Docs Unit Test

PWC PWC

PyTorch-Encoding

created by Hang Zhang

Documentation

  • Please visit the Docs for detail instructions of installation and usage.

  • Please visit the link to image classification models.

  • Please visit the link to semantic segmentation models.

Citations

ResNeSt: Split-Attention Networks [arXiv]
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Muller, R. Manmatha, Mu Li and Alex Smola

@article{zhang2020resnest,
title={ResNeSt: Split-Attention Networks},
author={Zhang, Hang and Wu, Chongruo and Zhang, Zhongyue and Zhu, Yi and Zhang, Zhi and Lin, Haibin and Sun, Yue and He, Tong and Muller, Jonas and Manmatha, R. and Li, Mu and Smola, Alexander},
journal={arXiv preprint},
year={2020}
}

Context Encoding for Semantic Segmentation [arXiv]
Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, Amit Agrawal

@InProceedings{Zhang_2018_CVPR,
author = {Zhang, Hang and Dana, Kristin and Shi, Jianping and Zhang, Zhongyue and Wang, Xiaogang and Tyagi, Ambrish and Agrawal, Amit},
title = {Context Encoding for Semantic Segmentation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}

Deep TEN: Texture Encoding Network [arXiv]
Hang Zhang, Jia Xue, Kristin Dana

@InProceedings{Zhang_2017_CVPR,
author = {Zhang, Hang and Xue, Jia and Dana, Kristin},
title = {Deep TEN: Texture Encoding Network},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

torch-encoding-1.2.1b20200604.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

torch_encoding-1.2.1b20200604-py2.py3-none-any.whl (126.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file torch-encoding-1.2.1b20200604.tar.gz.

File metadata

  • Download URL: torch-encoding-1.2.1b20200604.tar.gz
  • Upload date:
  • Size: 83.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for torch-encoding-1.2.1b20200604.tar.gz
Algorithm Hash digest
SHA256 0be1c867ed65ec340e621ba971becb9fe7c8912dcd031a583c10f34bc807d651
MD5 f376d6bb9761ebd0e62b38fe912654f8
BLAKE2b-256 0c6c544938bb79229630619e9a4f4952b08cc5df589dce2e135a5938cc65e325

See more details on using hashes here.

File details

Details for the file torch_encoding-1.2.1b20200604-py2.py3-none-any.whl.

File metadata

  • Download URL: torch_encoding-1.2.1b20200604-py2.py3-none-any.whl
  • Upload date:
  • Size: 126.3 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.46.1 CPython/3.7.7

File hashes

Hashes for torch_encoding-1.2.1b20200604-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 8a8ec97c0e50a17bbf501037bbbbb57f9d4cc63fea3b3f82db12c89f780f2656
MD5 0edcc2aa70955bac3faaa0d11b1e8bd3
BLAKE2b-256 8475309920de1c13a2623727e6ef517b4bba4a85c2f5d7999d4281a63978d7df

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page