Diabetic Retinopathy Detector: AI-Powered Eye Care Introducing the Diabetic Retinopathy Detector, an innovative AI-powered tool designed to assist in the early detection and diagnosis of diabetic retinopathy—a leading cause of blindness worldwide. Built using ResNet-50 and Xception pretrained models, the detector leverages advanced deep learning techniques to achieve an impressive 97.5% accuracy. This ensures precise and reliable predictions, enabling healthcare professionals and researchers to make informed decisions. Key Features: High Accuracy: Powered by state-of-the-art pretrained models, fine-tuned for optimal performance. Simple Workflow: Upload a retinal image, and the model predicts the severity of diabetic retinopathy in seconds. Comprehensive Classification: Detects five stages of diabetic retinopathy—ranging from no DR to proliferative DR. Fast & Efficient: Optimized for speed and usability without compromising on accuracy. How It Works: Upload a retinal image. The detector analyzes the image and identifies the severity level. Receive results with a detailed confidence score. Why It Matters: Diabetic retinopathy, if detected early, can be effectively managed to prevent vision loss. This tool brings cutting-edge AI technology to the forefront of eye care, democratizing access to early detection solutions.