🔥ICLR 2025 (Spotlight) One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
Key Features • How To Use • License • Citation • Visualization
- Consistent Image Generation Code: main.py
- Gradio Code: app.py
- Benchmark Generation Code: resource/gen_benchmark.py
- Consistory+ Benchmark: link
- Online Demo: link
# Clone this repository
$ git clone https://github.com/byliutao/1Prompt1Story
# Go into the repository
$ cd 1Prompt1Story
### Install dependencies ###
$ conda create --name 1p1s python=3.10
$ conda activate 1p1s
# choose the right cuda version of your device
$ conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
$ pip install transformers==4.46.3 # or: conda install conda-forge::transformers
$ conda install -c conda-forge diffusers
$ pip install opencv-python scipy gradio==4.44.1 sympy==1.13.1
### Install dependencies ENDs ###
# Run infer code
$ python main.py
# Run gradio code
$ python app.py
# Run benchmark generation code
$ python -m resource.gen_benchmark --save_dir ./result/benchmark --benchmark_path ./resource/consistory+.yamlThis project is licensed under the MIT License - see the LICENSE file for details.
If our work assists your research, feel free to give us a star ⭐ or cite us using:
@inproceedings{
liu2025onepromptonestory,
title={One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt},
author={Tao Liu and Kai Wang and Senmao Li and Joost van de Weijer and Fhad Khan and Shiqi Yang and Yaxing Wang and Jian Yang and Mingming Cheng},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=cD1kl2QKv1}
}
