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-1.2.1b20200522.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

torch_encoding-1.2.1b20200522-py2.py3-none-any.whl (126.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file torch-encoding-1.2.1b20200522.tar.gz.

File metadata

  • Download URL: torch-encoding-1.2.1b20200522.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/4.46.0 CPython/3.7.7

File hashes

Hashes for torch-encoding-1.2.1b20200522.tar.gz
Algorithm Hash digest
SHA256 543747aefccf2a2276434effee0f48d00be87120f9d753337111cbe4ba62237e
MD5 eb75ae39bef4907d4ca85927644abfdf
BLAKE2b-256 3788f5daf24e2a9de0cc7ae04413cb1ecec4a8cf9334cc75f09c9f4517435200

See more details on using hashes here.

File details

Details for the file torch_encoding-1.2.1b20200522-py2.py3-none-any.whl.

File metadata

  • Download URL: torch_encoding-1.2.1b20200522-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/4.46.0 CPython/3.7.7

File hashes

Hashes for torch_encoding-1.2.1b20200522-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 922e393879dbadce902ae9b2c6cb923240112ca64c999558b11de1d17e92a5b9
MD5 64a7c90e34c53bcae584f18b6211d76c
BLAKE2b-256 5969d193c6874acaff78b7538535d35d19fc74595d6241a98c1f6752c9ba64eb

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