Spaces:
Runtime error
Runtime error
File size: 1,707 Bytes
d9a264c 92189dd d9a264c 92189dd d9a264c 92189dd d9a264c 92189dd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
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)
|