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https://github.com/saritaphd/gen-ai-project-on-medical-disease-analysis-using-gpt4-vision
This project is a Streamlit-based web application designed for medical disease analysis using the GPT-4 vision model. Users can upload images, and the application will analyze the image to provide a detailed description or diagnosis.
https://github.com/saritaphd/gen-ai-project-on-medical-disease-analysis-using-gpt4-vision
Last synced: 3 days ago
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This project is a Streamlit-based web application designed for medical disease analysis using the GPT-4 vision model. Users can upload images, and the application will analyze the image to provide a detailed description or diagnosis.
- Host: GitHub
- URL: https://github.com/saritaphd/gen-ai-project-on-medical-disease-analysis-using-gpt4-vision
- Owner: SaritaPhD
- License: mit
- Created: 2024-07-31T10:56:57.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-07-31T11:05:13.000Z (4 months ago)
- Last Synced: 2024-07-31T12:28:43.988Z (4 months ago)
- Language: Python
- Homepage:
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Generative-AI-Project-On-Medical-Disease-Analysis-using-GPT4-Vision
This project is a Streamlit-based web application designed for medical disease analysis using the GPT-4 vision model. Users can upload images, and the application will analyze the image to provide a detailed description or diagnosis.
## Key Features
- Image Upload and Display: Users can upload images in JPG, JPEG, or PNG formats.
- The uploaded image is displayed in the application.
- Image Analysis: The application encodes the image to Base64 and sends it along with a prompt to the GPT-4 vision model for analysis.
- The analysis result is displayed on the application.
### How to run:
1. Create a new environment
```bash
conda create -n llmapp python=3.10 -y
```
2. Activate the environment
```bash
conda activate llmapp
```
3. Install required packages
```bash
pip install -r requirements.txt
```
4. Run the app.py
```bash
streamlit run app.py
```