PIL × DAT - Pillow extension for AI-based image upscaling.
Project description
PIL × DAT - Pillow extension for AI-based image upscaling.
Installation
For PyPI:
pip install pillow-dat
Get started
from PIL.Image import open
from PIL_DAT.Image import upscale
lumine_image = open(".github/lumine.png")
lumine_image = upscale(lumine_image, 2)
lumine_image.show()
Remark: We strongly advocate for the utilization of DAT light
models owing to their streamlined design and outstanding speed performance. However, should you opt for alternative models, please note that *.pth
model weights can be accessed via Google Drive.
Example
Input (lumine.png) | Output | Bicubic |
---|---|---|
Contribution
Please install Miniconda.
Please install VSCode extensions:
- Black Formatter
- isort
- Python
- Pylance
To create or update the pillow-dat
Python environment:
conda env create --file environment.yml
conda env update --file environment.yml --prune
To install dependencies:
poetry install
To run unit tests:
pytest
Acknowledgement
This library is founded upon the pioneering research paper, "Dual Aggregation Transformer for Image Super-Resolution".
@inproceedings{chen2023dual,
title={Dual Aggregation Transformer for Image Super-Resolution},
author={Chen, Zheng and Zhang, Yulun and Gu, Jinjin and Kong, Linghe and Yang, Xiaokang and Yu, Fisher},
booktitle={ICCV},
year={2023}
}
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
Built Distribution
Hashes for pillow_dat-0.1.5-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 507ddc858765fd2dba149b24aadcd928c1ff6fb3ce7ac58eaec42a55a289696e |
|
MD5 | b73a848fe906fb81a0bbf12321b7f3d1 |
|
BLAKE2b-256 | e470d6df5ed9ff3d05057947e218f4392943e7de780cef957cee9a530a2a6722 |