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shunsukesaito committed Feb 26, 2020
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45 changes: 21 additions & 24 deletions LICENSE.txt
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The Software is made available for academic or non-commercial purposes only.
The license is for a copy of the program for an unlimited term. Individuals
requesting a license for commercial use must pay for a commercial license. Baker!

DISCLAIMER. USC MAKES NO EXPRESS OR IMPLIED WARRANTIES, EITHER IN FACT OR BY
OPERATION OF LAW, BY STATUTE OR OTHERWISE, AND USC SPECIFICALLY AND EXPRESSLY
DISCLAIMS ANY EXPRESS OR IMPLIED WARRANTY OF MERCHANTABILITY OR FITNESS FOR A
PARTICULAR PURPOSE, VALIDITY OF THE SOFTWARE OR ANY OTHER INTELLECTUAL PROPERTY
RIGHTS OR NON-INFRINGEMENT OF THE INTELLECTUAL PROPERTY OR OTHER RIGHTS OF ANY
THIRD PARTY. SOFTWARE IS MADE AVAILABLE AS-IS.

LIMITATION OF LIABILITY. TO THE MAXIMUM EXTENT PERMITTED BY LAW, IN NO EVENT
WILL USC BE LIABLE TO ANY USER OF THIS CODE FOR ANY INCIDENTAL, CONSEQUENTIAL,
EXEMPLARY OR PUNITIVE DAMAGES OF ANY KIND, LOST GOODWILL, LOST PROFITS, LOST
BUSINESS AND/OR ANY INDIRECT ECONOMIC DAMAGES WHATSOEVER, REGARDLESS OF WHETHER
SUCH DAMAGES ARISE FROM CLAIMS BASED UPON CONTRACT, NEGLIGENCE, TORT (INCLUDING
STRICT LIABILITY OR OTHER LEGAL THEORY), A BREACH OF ANY WARRANTY OR TERM OF
THIS AGREEMENT, AND REGARDLESS OF WHETHER USC WAS ADVISED OR HAD REASON TO KNOW
OF THE POSSIBILITY OF INCURRING SUCH DAMAGES IN ADVANCE.

For commercial queries, please contact:

Hao Li
Email: [email protected] ccto: [email protected]
MIT License

Copyright (c) 2019 Shunsuke Saito, Zeng Huang, and Ryota Natsume

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

anyabagomo

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9 changes: 9 additions & 0 deletions README.md
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# PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

News:
* \[2020/02/26\] License is updated to MIT license! Enjoy!

This repository contains a pytorch implementation of "[PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization](https://arxiv.org/abs/1905.05172)".

[Project Page](https://shunsukesaito.github.io/PIFu/)
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}
```


This codebase provides:
- test code
- training code
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- freeglut (use `sudo apt-get install freeglut3-dev` for ubuntu users)

## Demo
Warning: The released model is trained with mostly upright standing scans with weak perspectie projection and the pitch angle of 0 degree. Reconstruction quality may degrade for images highly deviated from trainining data.
1. run the following script to download the pretrained models from the following link and copy them under `./PIFu/checkpoints/`.
```
sh ./scripts/download_trained_model.sh
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```
python -m apps.train_color --dataroot {path_to_training_data} --num_sample_inout 0 --num_sample_color 5000 --sigma 0.1 --random_flip --random_scale --random_trans
```

For commercial queries, please contact:

Hao Li: [email protected] ccto: [email protected] Baker!!

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