OptiLens is a revolutionary mobile application designed to improve eye health management by combining machine learning and interactive tools for cataract detection and refractive error assessment.
- Cataract Detection: Automatically classify cataract severity (Normal, Immature, Mature) with machine learning models.
- Refractive Error Assessment: Perform manual visual clarity tests using Snellen charts.
- User-Friendly Design: Simplified UI/UX for seamless interaction.
- Cloud Integration: Fast and secure data processing using Google Cloud Platform.
- (ML) M757B4KY0009 – Abd. Rahman Wahid – Universitas Muhammadiyah Makassar
- (ML) M278B4KX4041 – Salsabila Putri – Universitas Negeri Makassar
- (ML) M183B4KY2641 – Muhammad Hidayatul Fadillah – Universitas Amikom Yogyakarta
- (CC) C757B4KX1577 – Galbi Nadifah – Universitas Muhammadiyah Makassar
- (CC) C757B4KY0201 – Ahmad Faisal – Universitas Muhammadiyah Makassar
- (MD) A014B4KX4222 – Sukma Wati – Universitas Udayana
- Machine Learning: Model training and deployment.
- Cloud Computing: Backend APIs and deployment pipelines.
- Mobile Development: Android application development and UI/UX Design.
- Framework: TensorFlow, Keras
- Tools: OpenCV, PIL, Matplotlib, Numpy, and more
- Model: Convolutional Neural Network (CNN)
- Backend: NestJS (TypeScript)
- Database: PostgreSQL
- Deployment: Google Cloud Platform, Docker
- Framework: Android Studio (Kotlin)
- UI/UX Design: Figma
- Architecture: MVVM
Machine_Learning/: Notebooks, models, and dataset for ML development.Cloud_Computing/: Backend services and cloud configurations.Mobile_Development/: Source code and assets for the mobile application.docs/: Documentation and guides.
- Accuracy: 99.43% on validation data.
- Model: Efficient CNN architecture with minimal overfitting.
- Clone the repository:
git clone https://github.com/mamanwhide/OptiLens.git - Install dependencies:
pip install -r Machine_Learning/requirements.txt - Jupiter Notebook :
Machine_Learning/Notebook/OptiLens.ipynb
- Navigate to
Cloud_Computing/. - Build Docker image:
docker-compose build - Run locally:
docker-compose up
- Open
Mobile_Development/appin Android Studio. - Build and run the app on your Android device.
- Fork this repository.
- Create a feature branch:
git checkout -b feature-name. - Commit your changes:
git commit -m "Add a new feature". - Push to the branch:
git push origin feature-name. - Submit a pull request.
- Abd Rahman Wahid: abdrahmanwahid03@gmail.com - Team Lead