image_inputs.py 文件源码

def inputs_for_test(lists, image_shape, batch_size):

    filename_queue = tf.train.string_input_producer(lists, shuffle=True)
    reader = tf.TextLineReader()
    _, value = reader.read(filename_queue)
    image, label = read_my_file_format(value)
    image = tf.image.resize_images(image, [image_shape[0], image_shape[1]])
    # image = tf.random_crop(image, image_shape)
    label = tf.cast(label, tf.float32)

    image.set_shape(image_shape)
    # image = tf.image.random_flip_left_right(image)
    float_image = tf.image.per_image_whitening(image)

    min_after_dequeue = 1000
    capacity = min_after_dequeue+(2+1)*batch_size

    image_batch, label_batch = tf.train.batch([float_image, label],
                                            batch_size=batch_size)

    return image_batch, label_batch