input.py 文件源码

def inputs(image_dir, batch_size, min_queue_examples, input_height, input_width):
    def read_images(image_paths):
        filename_queue = tf.train.string_input_producer(image_paths)
        reader = tf.WholeFileReader()
        key, value = reader.read(filename_queue)
        image = tf.image.decode_image(value)
        image = tf.image.convert_image_dtype(image, dtype=tf.float32)
        image.set_shape([None, None, 3])

        return image

    image_paths = get_image_paths(image_dir)
    images = read_images(image_paths)
    images = tf.image.crop_to_bounding_box(images, 30, 0, 178, 178)
    # images = tf.image.random_flip_left_right(images)
    images = tf.image.resize_images(images, [input_height, input_width])

    total_image_count = len(image_paths)
    input_batch = tf.train.shuffle_batch([images],
                                         batch_size=batch_size,
                                         num_threads=16,
                                         capacity=min_queue_examples + 3 * batch_size,
                                         min_after_dequeue=min_queue_examples)

    return input_batch, total_image_count