Pre-release
This release is a pre-release and may not be stable for production use.
PyTorch-Encoding
created by Hang Zhang
Documentation
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Please visit the Docs for detail instructions of installation and usage.
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Please visit the link to examples of semantic segmentation.
Citations
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}
}
1 maintainer
Metadata
1 maintainer
Release files for torch-encoding 1.1.1b5042020
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| torch-encoding-1.1.1b5042020.tar.gz | 57.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| torch_encoding-1.1.1b5042020-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 142.9 kB
Release files / torch-encoding-1.1.1b5042020.tar.gz
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| Size | 57.5 kB |
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Release files / torch_encoding-1.1.1b5042020-py2.py3-none-any.whl
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| Size | 85.4 kB |
| Tags | Python 2 Python 3 |
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