MelaNOPAa is a cutting-edge React Native mobile application designed to detect skin cancer early by leveraging advanced machine learning technologies. This application aims to provide an easily accessible tool for users to screen skin lesions using their mobile devices.
- CNNs & TensorFlow: Utilizes Convolutional Neural Networks powered by TensorFlow for accurate skin cancer detection.
- Skin Cancer MNIST Dataset: Trained on the comprehensive Skin Cancer MNIST: HAM10000 dataset from Kaggle.
- React Native: Provides a seamless experience on both iOS and Android devices.
- Cross-Platform Compatibility: Ensures consistent performance across multiple platforms.
- Real-Time Image Processing: Offers instant diagnostic feedback by processing images in real-time.
- AI Integration: Leverages Artificial Intelligence for enhanced diagnostic capabilities.
- Flask Backend: Utilizes Flask to manage server-side logic and API endpoints.
- Node.js
- npm
- Python
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Clone the repository:
git clone https://github.com/FreshSupaSulley/MelaNOPAa.git cd MelaNOPAa
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Install dependencies:
cd frontend npm install
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Start the application:
npx expo start
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Navigate to the backend directory:
cd backend
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Install Python dependencies:
pip install -r requirements.txt
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Run the Flask server:
flask run
We welcome contributions to MelaNOPAa! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.