🧠 RetinaVision-MNet

RetinaVision-MNet is a custom-trained MobileNetV2-based deep learning model for multi-class retinal disease detection.
It predicts 10 retinal conditions from fundus images and includes Grad-CAM heatmaps to provide interpretable visual explanations for every prediction.

The model is trained entirely from scratch and is hosted on Hugging Face due to GitHub’s file-size limitations.

🔥 Key Features

10-class retinal disease classification
MobileNetV2 backbone — lightweight and efficient for medical imaging
Grad-CAM interpretability for understanding model decisions
Custom-trained model (.h5) using Keras / TensorFlow
Optimized for FastAPI deployment with async inference
Works seamlessly with secure JWT-protected backend

📦 Usage

Download the model file from the Files and Versions tab and place it in your project:

from tensorflow.keras.models import load_model

model = load_model("mobile_model.h5")

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