The Diabetic Retinopathy Detector is a 97.5% accurate model for predicting diabetic retinopathy severity from retinal images, accessible via a public API for healthcare and research use.
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
```python
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
{
"prediction": "Moderate",
"confidence": 97.5
}
```