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DiffQRCoder

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🔥 [WACV'25] Official implementation of "DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement"

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# DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement

[![Python](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/release/python-310/)
[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)
[![arXiv](https://img.shields.io/badge/arXiv-2311.16090-red)](https://arxiv.org/abs/2409.06355)

**Author:**
[Jia-Wei Liao](https://jwliao1209.github.io/),
[Winston Wang](https://dinoslow.github.io/),
Tzu-Sian Wang,
[Li-Xuan Peng](https://alexpeng517.github.io/),
Ju-Hsian Weng,
[Cheng-Fu Chou](https://www.csie.ntu.edu.tw/~ccf/),
[Jun-Cheng Chen](https://homepage.citi.sinica.edu.tw/pages/pullpull/)

***IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2025***

This repository implements a two-stage iterative refinement pipeline that leverages a pretrained ControlNet to generate aesthetic QR codes. Check out the project page [here](https://jwliao1209.github.io/DiffQRCoder/).

## :wrench: Setup
To set up the virtual environment and install the required packages, use the following commands:
```
virtualenv --python=python3.10 diffqrcoder
source diffqrcoder/bin/activate
pip install -r requirements.txt
```

## :rocket: Generating  Aesthetic QR Code
To generate the aesthetic qrcode, run the following:
```
python run.py \
    --controlnet_ckpt <checkpoint of controlnet> \
    --pipe_ckpt <checkpoint of pipeline> \
    --qrcode_path <path of qrcode image> \
    --qrcode_module_size <qrcode module size> \
    --qrcode_padding <qrcode padding> \
    --neg_prompt <negative prompt> \
    --num_inference_steps <number of inference step> \
    --controlnet_conditioning_scale <controlnet conditioning scale> \
    -srg <scanning robust guidance scale> \
    -pg <perceptual guidance scale> \
    --srmpgd_num_iteration <number of srmpgd iterations> \
    --srmpgd_lr <srmpgd learning rate> \
    --device <device of running the code> \
    --output_folder <folder of generated image>
```

## :wrench: Unit Test
To execute the unit test, run the following:
```
bash scripts/run_test.sh
```

## :dart: Citation
If you use this code, please cite the following:
```bibtex
@inproceedings{liao2024diffqrcoder,
  title     = {DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative Refinement},
  author    = {Jia-Wei Liao, Winston Wang, Tzu-Sian Wang, Li-Xuan Peng, Ju-Hsian Weng, Cheng-Fu Chou, Jun-Cheng Chen},
  booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  year      = {2025},
}
```

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=jwliao1209/DiffQRCoder&type=Date)](https://www.star-history.com/#jwliao1209/DiffQRCoder&Date)

DiffQRCoder

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