cifar10_input.py 文件源码

def random_crop_and_flip(batch_data, padding_size):
    '''
    Helper to random crop and random flip a batch of images
    :param padding_size: int. how many layers of 0 padding was added to each side
    :param batch_data: a 4D batch array
    :return: randomly cropped and flipped image
    '''
    cropped_batch = np.zeros(len(batch_data) * IMG_HEIGHT * IMG_WIDTH * IMG_DEPTH).reshape(
        len(batch_data), IMG_HEIGHT, IMG_WIDTH, IMG_DEPTH)

    for i in range(len(batch_data)):
        x_offset = np.random.randint(low=0, high=2 * padding_size, size=1)[0]
        y_offset = np.random.randint(low=0, high=2 * padding_size, size=1)[0]
        cropped_batch[i, ...] = batch_data[i, ...][x_offset:x_offset+IMG_HEIGHT,
                      y_offset:y_offset+IMG_WIDTH, :]

        cropped_batch[i, ...] = horizontal_flip(image=cropped_batch[i, ...], axis=1)

    return cropped_batch