🤗[Gradio Demo]🔥 [Paper] [Project Page]
- [2024.05.16]: Release a Gradio Demo! Thanks HuggingFace and AK!
- [2024.05.15]: Release training and inference codes!
More results can be found in our Project Page and Paper.
-
Requirements (Only need 2.5GB VRAM for training):
conda create -n IDEGAN python=3.8.5 conda activate IDEGAN pip install -r requirements.txt
-
Download pretrained models: Stable Diffusion v2-1_512.
-
Set the paths of pretrained SD-2.1 models as default in the Line106 of train.py or command with
--pretrained_model_name_or_path **your SD-2.1 path**
We have already provided the pretrained weights in training_weight.
python train.py --experiment_name="normal_GAN"The trained IDE-GAN model will be saved in training_weight.
First set your SD-2.1 path in the test files.
-
test.ipynb: Generate a random character with text prompts.
-
test_create_many_characters.ipynb: Generate many characters with text prompts.
The results will be generated in test_results/{index}/.
- If you want to test with ControlNet, ModelScopeT2V and LucidDreamer, you could find the related codes in StableIdentity.
- Release training and inference code
- Huggingface demo
@article{wang2024characterfactory,
title={CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models},
author={Wang, Qinghe and Li, Baolu and Li, Xiaomin and Cao, Bing and Ma, Liqian and Lu, Huchuan and Jia, Xu},
journal={arXiv preprint arXiv:2404.15677},
year={2024}
}