def image_data_generator(image_paths, steering_angles, batch_size, is_training):
    while True:
        batch_images = []
        batch_steering_angles = []

        for i in range(batch_size):
            random_index = random.randint(0, len(image_paths) - 1)
            image_path = image_paths[random_index]
            image = my_imread(image_paths[random_index])
            steering_angle = steering_angles[random_index]
            if is_training:
                # training: augment image
                image, steering_angle = random_augment(image, steering_angle)

            image = img_preprocess(image)
            batch_images.append(image)
            batch_steering_angles.append(steering_angle)

        yield( np.asarray(batch_images), np.asarray(batch_steering_angles))