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-1.2.2b20200723.tar.gz (83.8 kB view details)

Uploaded Source

Built Distribution

torch_encoding-1.2.2b20200723-py2.py3-none-any.whl (126.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file torch-encoding-1.2.2b20200723.tar.gz.

File metadata

  • Download URL: torch-encoding-1.2.2b20200723.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/4.48.0 CPython/3.7.8

File hashes

Hashes for torch-encoding-1.2.2b20200723.tar.gz
Algorithm Hash digest
SHA256 e661c912d77c38a0256fd62d6f3d32e5c363178ce58a2b54d845e18b4624aca7
MD5 020a91fca8922834bfed01d98a7e3eb8
BLAKE2b-256 4017fccaf7537791378d93798d159684f3624ae0f3d8a6611d09024bb124e451

See more details on using hashes here.

File details

Details for the file torch_encoding-1.2.2b20200723-py2.py3-none-any.whl.

File metadata

  • Download URL: torch_encoding-1.2.2b20200723-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/4.48.0 CPython/3.7.8

File hashes

Hashes for torch_encoding-1.2.2b20200723-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 35c3cdb011877bc766c8e5bd4ffc3b2892433a80a3176e72917e3edcca1139ac
MD5 0a6de5d5556d8811c048bdeb0fe73703
BLAKE2b-256 5c069f12c8cefeac1d5073757ee5f1cfd80553016a208aabde13782a7f16cde0

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