TFrecords 比原始 JPEG 图像占用更多空间

Question

我正在尝试将我的 Jpeg 图像集转换为 TFrecords。但是 TFrecord 文件占用的空间几乎是图像集的 5 倍。经过大量的谷歌搜索，我了解到当 JPEG 被写入 TFrecords 时，它们不再是 JPEG。但是，我还没有遇到针对此问题的可理解的代码解决方案。请告诉我应该在下面的代码中进行哪些更改才能将 JPEG 写入 Tfrecords。

def print_progress(count, total):
    pct_complete = float(count) / total
    msg = "\r- Progress: {0:.1%}".format(pct_complete)
    sys.stdout.write(msg)
    sys.stdout.flush()

def wrap_int64(value):
    return tf.train.Feature(int64_list=tf.train.Int64List(value=value))

def wrap_bytes(value):
    return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))


def convert(image_paths , labels, out_path):
    # Args:
    # image_paths   List of file-paths for the images.
    # labels        Class-labels for the images.
    # out_path      File-path for the TFRecords output file.

    print("Converting: " + out_path)

    # Number of images. Used when printing the progress.
    num_images = len(image_paths)

    # Open a TFRecordWriter for the output-file.
    with tf.python_io.TFRecordWriter(out_path) as writer:

        # Iterate over all the image-paths and class-labels.
        for i, (path, label) in enumerate(zip(image_paths, labels)):
            # Print the percentage-progress.
            print_progress(count=i, total=num_images-1)

            # Load the image-file using matplotlib's imread function.
            img = imread(path)
            # Convert the image to raw bytes.
            img_bytes = img.tostring()

            # Create a dict with the data we want to save in the
            # TFRecords file. You can add more relevant data here.
            data = \
            {
                'image': wrap_bytes(img_bytes),
                'label': wrap_int64(label)
            }

            # Wrap the data as TensorFlow Features.
            feature = tf.train.Features(feature=data)

            # Wrap again as a TensorFlow Example.
            example = tf.train.Example(features=feature)

            # Serialize the data.
            serialized = example.SerializeToString()

            # Write the serialized data to the TFRecords file.
            writer.write(serialized)

编辑：有人可以回答这个吗？！

Answer 1

我们可以使用内置open函数来获取字节，而不是将图像转换为数组并返回字节。这样，压缩后的图像就会被写入 TFRecord。

替换这两行

img = imread(path)
img_bytes = img.tostring()

和

img_bytes = open(path,'rb').read()

参考 ：

https://github.com/tensorflow/tensorflow/issues/9675