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-1.2.2b20200709.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

torch_encoding-1.2.2b20200709-py2.py3-none-any.whl (126.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file torch-encoding-1.2.2b20200709.tar.gz.

File metadata

  • Download URL: torch-encoding-1.2.2b20200709.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/2.23.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.8

File hashes

Hashes for torch-encoding-1.2.2b20200709.tar.gz
Algorithm Hash digest
SHA256 ee774d3b91a35ef67018de6f874b8e22a36fefa482ac46422bc528502e62a62b
MD5 c075bae43b5b41f23e18af08aa028a63
BLAKE2b-256 d41d045ba557575020a0cd58a47de876f5eb1a13c511819381445c624f0d94d8

See more details on using hashes here.

File details

Details for the file torch_encoding-1.2.2b20200709-py2.py3-none-any.whl.

File metadata

  • Download URL: torch_encoding-1.2.2b20200709-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/2.23.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.47.0 CPython/3.7.8

File hashes

Hashes for torch_encoding-1.2.2b20200709-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 070398d75b8e2bb7e2a23b6b073e8832731ec42d9ca6fb887f6678d072ffa3a7
MD5 bda62096bfc433cbc9bd93b73773fcd4
BLAKE2b-256 88057ed453f371ff465542240490e23b731915ce4d64f50357c0dfa28bbe07d7

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