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title: medicalaiapp | |
app_file: app.py | |
sdk: gradio | |
sdk_version: 5.31.0 | |
# Medical VLM with SAM-2 and CheXagent | |
A comprehensive medical imaging analysis tool that combines: | |
- Qwen-VLM for medical visual question answering | |
- SAM-2 (Segment Anything Model 2) for automatic medical image segmentation | |
- CheXagent for structured chest X-ray report generation | |
## Features | |
1. **Medical Q&A**: Ask questions about medical images using the Qwen-VLM model | |
2. **Automatic Masking**: Segment medical images automatically using SAM-2 | |
3. **Structured Report Generation**: Generate detailed chest X-ray reports using CheXagent | |
4. **Visual Grounding**: Locate specific findings in medical images | |
## Setup | |
1. Clone the repository: | |
```bash | |
git clone https://github.com/pascal-maker/medicalvlm.git | |
cd medicalvlm | |
``` | |
2. Create and activate a virtual environment: | |
```bash | |
python -m venv chexagent_env | |
source chexagent_env/bin/activate # On Windows: chexagent_env\Scripts\activate | |
``` | |
3. Install dependencies: | |
```bash | |
pip install -r requirements.txt | |
``` | |
4. Download required model checkpoints: | |
- SAM-2 checkpoint: Place in `checkpoints/sam2.1_hiera_large.pt` | |
- Other model weights will be downloaded automatically on first run | |
## Usage | |
Run the Gradio interface: | |
```bash | |
python app.py | |
``` | |
The web interface will be available at `http://localhost:7860` | |
## Requirements | |
- Python 3.8+ | |
- PyTorch | |
- CUDA-compatible GPU (recommended) | |
- See `requirements.txt` for full list of dependencies | |
## License | |
[Your chosen license] | |
## Acknowledgments | |
- [Qwen-VLM](https://github.com/QwenLM/Qwen-VL) | |
- [SAM-2](https://github.com/facebookresearch/segment-anything) | |
- [CheXagent](https://github.com/stanfordmlgroup/CheXagent) | |