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The Ocular Disease Detection project is an AI-powered web application designed to detect common ocular diseases from digital images. Built with PyTorch and Streamlit, the application uses a custom-trained Convolutional Neural Network (CNN) to classify images into six distinct categories: AMD, Cataract, Glaucoma, Myopia, Normal and non eye images

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Nikky31/Ocular-Disease-Detection-using-Eye-Images

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Ocular-Eye-Disease-Classification

Usage

To run the demo:

  • Install Dependencies:

    pip install -r requirements.txt
  • Run main.py for Demo:

    streamlit run .\src\main.py

The pre-trained models are available on models/ directory.
Just simply load models/MultipleEyeDiseaseDetectModel.pth in colab or local device

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The Ocular Disease Detection project is an AI-powered web application designed to detect common ocular diseases from digital images. Built with PyTorch and Streamlit, the application uses a custom-trained Convolutional Neural Network (CNN) to classify images into six distinct categories: AMD, Cataract, Glaucoma, Myopia, Normal and non eye images

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