Metadata-Version: 2.1
Name: vsgrlir
Version: 1.0.0
Summary: GRLIR function for VapourSynth
Project-URL: Homepage, https://github.com/HolyWu/vs-grlir
Project-URL: Bug Tracker, https://github.com/HolyWu/vs-grlir/issues
Author-email: HolyWu <holywu@gmail.com>
License: MIT License
        
        Copyright (c) 2023 HolyWu
        
        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.
License-File: LICENSE
Keywords: GRLIR,VapourSynth
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Multimedia :: Video
Requires-Python: >=3.10
Requires-Dist: numpy>=1.24.2
Requires-Dist: omegaconf>=2.3.0
Requires-Dist: requests>=2.28.2
Requires-Dist: timm>=0.6.13
Requires-Dist: torch>=1.13.1
Requires-Dist: tqdm>=4.65.0
Requires-Dist: vapoursynth>=55
Description-Content-Type: text/markdown

# SwinIR
Efficient and Explicit Modelling of Image Hierarchies for Image Restoration, based on https://github.com/ofsoundof/GRL-Image-Restoration.

Only real-world image super-resolution model is kept.


## Dependencies
- [NumPy](https://numpy.org/install)
- [PyTorch](https://pytorch.org/get-started) 1.13.1
- [VapourSynth](http://www.vapoursynth.com/) R55+


## Installation
```
pip install -U vsgrlir
python -m vsgrlir
```


## Usage
```python
from vsgrlir import grlir

ret = grlir(clip)
```

See `__init__.py` for the description of the parameters.
