NSTLoadImages.py

def load_img(path_to_img):
  # Reads and outputs the entire contents of the input filename.
  img = tf.io.read_file(path_to_img)
  # Detect whether an image is a BMP, GIF, JPEG, or PNG, and 
  # performs the appropriate operation to convert the input 
  # bytes string into a Tensor of type dtype
  img = tf.image.decode_image(img, channels=3)
  # Convert image to dtype, scaling (MinMax Normalization) its values if needed.
  img = tf.image.convert_image_dtype(img, tf.float32)
  # Scale the image using the custom function we created
  img = img_scaler(img)
  # Adds a fourth dimension to the Tensor because
  # the model requires a 4-dimensional Tensor
  return img[tf.newaxis, :]