data_generator.py

import os
import numpy as np

def load_img(img_dir, img_list):
  images = []
  for i, image_name in enumerate(img_list):
    if (image_name.split('.')[1] == 'npy'):
      image = np.load(img_dir + image_name)
      images.append(image)
  images = np.array(images)

  return(images)

def imageLoader(img_dir, img_list, mask_dir, mask_list, batch_size):

    L = len(img_list)

    #keras needs the generator infinite, so we will use while true
    while True:

        batch_start = 0
        batch_end = batch_size

        while batch_start < L:
            limit = min(batch_end, L)

            X = load_img(img_dir, img_list[batch_start:limit])
            Y = load_img(mask_dir, mask_list[batch_start:limit])

            yield (X,Y) #a tuple with two numpy arrays with batch_size samples
            # what does the yield function do?
            batch_start += batch_size
            batch_end += batch_size