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-1.2.2b20200630.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

torch_encoding-1.2.2b20200630-py2.py3-none-any.whl (126.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file torch-encoding-1.2.2b20200630.tar.gz.

File metadata

  • Download URL: torch-encoding-1.2.2b20200630.tar.gz
  • Upload date:
  • Size: 83.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.7

File hashes

Hashes for torch-encoding-1.2.2b20200630.tar.gz
Algorithm Hash digest
SHA256 782a052d9d3e6dcef674574789f7e21700b6f75e73728a5f437ebb3c682efadc
MD5 7999fefcb28e78e0cf69ab4744a04d77
BLAKE2b-256 cbb7b0a30b5b9258317aa128946d5d5f47dafb40e4f4267fb9ff99b8968ea8df

See more details on using hashes here.

File details

Details for the file torch_encoding-1.2.2b20200630-py2.py3-none-any.whl.

File metadata

  • Download URL: torch_encoding-1.2.2b20200630-py2.py3-none-any.whl
  • Upload date:
  • Size: 126.3 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.7

File hashes

Hashes for torch_encoding-1.2.2b20200630-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 81e16eaac0a22f6dbbe9b9d31ba4971fa4cefa2b08986a219267e667729e4570
MD5 6691acdf796ff3df5e8a6da49a47b22d
BLAKE2b-256 ea4de3212388c1c002c6c1e3e49ef1d48f17eec875ba7c7e2ab6cb3acc787ecf

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