Eye Diabetic Retinopathy — Diabetic Retinopathy Detector API

Diabetic Retinopathy Detector API The Diabetic Retinopathy Detector is a highly accurate model deployed to predict the severity of diabetic retinopathy in retinal images. This model achieves a 97.5% accuracy rate and is accessible via a public API for healthcare professionals, researchers, and developers. API Details Endpoint: https://5000-patient-truth-71443... Authentication: The API requires an API key for access. Add the following header in your request: X-Api-Key: nawabBhaikamodel How to Use Prepare a high-quality retinal image (JPEG/PNG). Use a POST request to send the image to the API. The server will process the image and return the predicted severity level along with the confidence score. Request Example in Python python Copy code import requests url = "https://5000-patient-truth-71443..." headers = {"X-Api-Key": "nawabBhaikamodel"} image_path = "path_to_retinal_image.jpg" with open(image_path, "rb") as image_file: files = {"file": image_file} response = requests.post(url, headers=headers, files=files) if response.status_code == 200: print("Prediction:", response.json()) else: print("Error:", response.text) Response The API returns a JSON object: json Copy code { "prediction": "Moderate", "confidence": 97.5 } This API simplifies early detection of diabetic retinopathy, aiding in timely medical intervention and research applications.

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