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SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model

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Pre-trained Multimodal Large Language Model Enhances Dermatological Diagnosis using SkinGPT-4

Juexiao Zhou, Xiaonan He, Liyuan Sun, Jiannan Xu, Xiuying Chen, Yuetan Chu, Longxi Zhou, Xingyu Liao, Bin Zhang, Xin Gao

King Abdullah University of Science and Technology, KAUST

Installation

conda env create -f environment.yml
conda activate skingpt4
conda install -c conda-forge mamba=1.4.7
pip install einops
mamba install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia

Download our trained weights

Our previous trained weights for skin disease diagnosis with only step-1 dataset and Vicuna could be downloaded at skinGPT_v1.pth.

The latest model trained with both public datasets and the proprietary dataset based on falcon-40b-instruct and llama-2-13b-chat-hf are not publicly available currently.

Please feel free to keep in touch with xin.gao@kaust.edu.sa and juexiao.zhou@kaust.edu.sa for potential collaboration.

Launching Demo Locally

python demo.py --cfg-path eval_configs/skingpt4_eval_vicuna.yaml  --gpu-id 0
python demo.py --cfg-path eval_configs/skingpt4_eval_falcon40b.yaml  --gpu-id 0
python demo.py --cfg-path eval_configs/skingpt4_eval_llama2_13bchat.yaml  --gpu-id 0

Illustraion of SkinGPT-4

fig1

Examples of Skin disease diagnosis

fig3

Clinical Evaluation

fig4

Acknowledgement

  • MiniGPT-4 This repo is developped on MiniGPT-4, an awesome repo for vision-language chatbot!
  • Lavis
  • Vicuna
  • Falcon
  • Llama 2

Citation

If you're using SkinGPT-4 in your research or applications, please cite SkinGPT-4 using this BibTeX:

@misc{zhou2023skingpt,
      title={SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model}, 
      author={Juexiao Zhou and Xiaonan He and Liyuan Sun and Jiannan Xu and Xiuying Chen and Yuetan Chu and Longxi Zhou and Xingyu Liao and Bin Zhang and Xin Gao},
      year={2023},
      eprint={2304.10691},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}

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