Skin Diagnosis Interface is a web application designed to assist in the identification and diagnosis of various skin conditions using machine learning techniques. The application leverages a trained model to analyze skin images and provide diagnostic suggestions.
- User-Friendly Interface: Utilizes Streamlit to offer an intuitive and interactive user experience.
- Image Analysis: Allows users to upload skin images for analysis.
- Diagnostic Feedback: Provides diagnostic suggestions based on the uploaded images.
To set up the Skin Diagnosis Interface locally, follow these steps:
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Clone the Repository:
git clone https://github.com/mthd98/Skin-Diagnosis-Interface.git
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Navigate to the Project Directory:
cd Skin-Diagnosis-Interface
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Create and Activate a Virtual Environment:
python -m venv env source env/bin/activate # On Windows, use 'env\Scripts\activate'
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Install Dependencies:
pip install -r requirements.txt
To run the application:
streamlit run StreamlitApp.py
This command will launch the web application, accessible at http://localhost:8501/.
- StreamlitApp.py: Main script to run the Streamlit application.
- Utilities/: Contains utility functions and modules supporting the main application.
- test.ipynb: Jupyter Notebook for testing and experimentation.
- requirements.txt: Lists all Python dependencies required to run the application.
This project is licensed under the MIT License. For more details, refer to the LICENSE file.