import tensorflow as tf
import numpy as np
from keras import utils


model = tf.keras.models.load_model("data/model/retina.h5")


def predict_diabetic_retinopathy(immagine):
  x = utils.img_to_array(immagine)
  x = np.expand_dims(x, axis=0)
  x = x / 255.0

  prediction = model.predict(x)

  if prediction[0][0] > 0.5:
    diagnosis = "Presenza di Retinopatia Diabetica"
  else:
    diagnosis = "Nessuna retinopatia diabetica"

  percentage = prediction[0][0] * 100
  roundedPercentage = round(percentage, 2)
  probability = f"{roundedPercentage}%"
  #probability = str(prediction[0][0])

  return diagnosis, probability