text: from keras.models import load_model
  import tensorflow as tf
  from concurrent import futures
  
  classList = ['medium', 'ripe', 'unripe']
  my_model = load_model('./model-large.h5')
  
  imgPath='./test.jpg'
  
  img = tf.keras.preprocessing.image.load_img(
      imgPath, target_size=(150, 150)
  )
  
  img_array = tf.keras.preprocessing.image.img_to_array(img)
  img_array = img_array / 255
  img_array = img_array.reshape(1, 150, 150, 3)
  predictions = my_model.predict(img_array)
  print(predictions[0])
  
  maxConfi = predictions[0][0]
  index = 0
  
  
  for i in range(3):
      if maxConfi < predictions[0][i]:
          maxConfi = predictions[0][i]
          index = i
  
  
  print({"classification": f'{classList[index]}', "confidence": f'{maxConfi}'})