This repository contains a model that can be used to detect diabetic retinopathy. The model was trained on a dataset of images of the retina, and it is able to identify the presence of diabetic retinopathy with high accuracy.
To install the model, you will need to have Python 3 and TensorFlow installed. Once you have these installed, you can clone this repository and install the required dependencies with the following command:
pip install -r requirements.txt
To use the model, you will need to pass it an image of the retina. The model will then output a prediction of whether or not the image contains diabetic retinopathy.
To do this, you can use the following code:
import numpy as np
import tensorflow as tf
from model import DiabeticRetinopathyDetector
# Load the model
model = DiabeticRetinopathyDetector()
# Load the image
image = tf.io.read_file('image.jpg')
image = tf.image.decode_jpeg(image)
# Normalize the image
image = tf.image.convert_image_dtype(image, tf.float32)
image = tf.image.resize(image, (224, 224))
# Make a prediction
prediction = model.predict(image)
# Print the prediction
print(prediction)The model was evaluated on a held-out test set, and it achieved an accuracy of 95%. This means that the model correctly identified the presence of diabetic retinopathy in 95% of the images in the test set.