Tensorflow：TFRecordファイルからの長さの読み取りがそれと異なるから

Question

私のソースコードは以下の通りですが、tf-recordから正しく読んだ例は解析できませんが、本当に混乱している。

# -*- coding: utf-8 -*- 
import xml.etree.ElementTree as ET 
import os 
import tensorflow as tf 
import matplotlib.pyplot as plt 
import numpy as np 
import math 
import sys 
import shutil 
from CNN import Alex_inference 
from PIL import Image 


# used for tf.train.Example Protocal Buffer 
def _int64_feature(value): 
    return tf.train.Feature(int64_list=tf.train.Int64List(value=[value])) 

# string feature 
def _bytes_feature(value): 
    return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value])) 

def _float_feature(value): 
    return tf.train.Feature(float_list=tf.train.FloatList(value=[value])) 

def create_multi_TFRecordFile(): 
    output_filename = "./test-tf-recorder" 
    tfrecord_writer = tf.python_io.TFRecordWriter(output_filename) 

    image_file_path = "/media/VOCdevkit/VOC2012/JPEGImages/2007_000027.jpg" 
    #image_raw_data = tf.read_file(image_file_path) 
    #change to below 
    image = Image.open(image_file_path) 

    #print image,image.size 
    test = plt.imread(image_file_path) 
    print test 


    label_num = 1 

    # Example Protocol Buffer. 
    # I think we should provide tf.tain.Example with python data instead of tf tensors. 
    example = tf.train.Example(features=tf.train.Features(feature={ 
     'image_raw_data': _bytes_feature(image.tobytes()), #in python 3,maybe need encoding='utf8' in bytes func. 
     'image_width': _int64_feature(image.size[0]), 
     'image_height': _int64_feature(image.size[1]), 
     'label': _int64_feature(label_num) 
    })) 
    tfrecord_writer.write(example.SerializeToString()) 
    tfrecord_writer.close() 
    print("\n\nTFRecord has been genearated\n") 


# read record file 
def get_image_batch(): 
    recorder_file_list = tf.train.match_filenames_once(
     "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/test*") 
    reader = tf.TFRecordReader() 
    filename_queue = tf.train.string_input_producer(recorder_file_list,shuffle=True) 

    _, serialized_example = reader.read(filename_queue) 

    features = tf.parse_single_example(
     serialized_example, 
     features={ 
      'image_raw_data': tf.FixedLenFeature([],tf.string), 
      'image_width': tf.FixedLenFeature([],tf.int64), 
      'image_height': tf.FixedLenFeature([], tf.int64), 
      'label': tf.FixedLenFeature([], tf.int64) 
     }) 

    image_raw = tf.decode_raw(features['image_raw_data'],tf.uint8) 
    image_height = tf.cast(features['image_height'],tf.int32) 
    image_width = tf.cast(features['image_width'],tf.int32) 
    image = tf.reshape(image_raw,[image_height,image_width,3]) 

    #image = tf.image.resize_images(image,size=[227,227],method=0) 

    label = tf.cast(features['label'], tf.int32) 
    label_hot = tf.one_hot(label, 20, on_value=1, off_value=0, axis=-1) 

    sess = tf.InteractiveSession() 
    sess.run(tf.global_variables_initializer()) 

    coord = tf.train.Coordinator() 
    threads = tf.train.start_queue_runners(sess=sess, coord=coord) 

    #print sess.run(recorder_file_list) #[ '/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/test-tf-recorder'] 
    print sess.run(image) 

    coord.request_stop() 
    coord.join(threads) 

def train(): 
    create_multi_TFRecordFile() 
    get_image_batch() 



def main(argv=None): 
    train() 

if __name__ == '__main__': 
    tf.app.run() 

ラン情報TF-レコード（DecodeRawへの入力は、長さ55を持っている）から、長編の読みが（[227,227,3]）、それへの書き込みは異なっている示して、誰もが説明することができます。私はそれを本当に感謝それ。

/home/wuzheng/anaconda2/bin/python /home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py 
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally 
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally 
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally 
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:910] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: 
name: GeForce GTX 960M 
major: 5 minor: 0 memoryClockRate (GHz) 1.176 
pciBusID 0000:01:00.0 
Total memory: 3.95GiB 
Free memory: 3.53GiB 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 960M, pci bus id: 0000:01:00.0) 
[ '/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/test-tf-recorder'] 
Traceback (most recent call last): 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 99, in <module> 
    tf.app.run() 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run 
    _sys.exit(main(_sys.argv[:1] + flags_passthrough)) 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 96, in main 
    train() 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 91, in train 
    get_image_batch(20,100) 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 84, in get_image_batch 
    print sess.run(image_raw).shape 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run 
    run_metadata_ptr) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 965, in _run 
    feed_dict_string, options, run_metadata) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1015, in _do_run 
    target_list, options, run_metadata) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1035, in _do_call 
    raise type(e)(node_def, op, message) 
tensorflow.python.framework.errors_impl.InvalidArgumentError: Input to DecodeRaw has length 55 that is not a multiple of 4, the size of float 
    [[Node: DecodeRaw = DecodeRaw[little_endian=true, out_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](ParseSingleExample/Squeeze_image_raw_data)]] 

Caused by op u'DecodeRaw', defined at: 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 99, in <module> 
    tf.app.run() 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 44, in run 
    _sys.exit(main(_sys.argv[:1] + flags_passthrough)) 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 96, in main 
    train() 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 91, in train 
    get_image_batch(20,100) 
    File "/home/wuzheng/PycharmProjects/Grammar/new_order/Examples/3/read.py", line 69, in get_image_batch 
    image_raw = tf.decode_raw(features['image_raw_data'], tf.float32) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_parsing_ops.py", line 101, in decode_raw 
    little_endian=little_endian, name=name) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op 
    op_def=op_def) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/home/wuzheng/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1226, in __init__ 
    self._traceback = _extract_stack() 

InvalidArgumentError (see above for traceback): Input to DecodeRaw has length 55 that is not a multiple of 4, the size of float 
    [[Node: DecodeRaw = DecodeRaw[little_endian=true, out_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](ParseSingleExample/Squeeze_image_raw_data)]] 


Process finished with exit code 1 

Answer 1

あなたはbytelistとして画像を書いているので、あなたがあなたのコメントをdecoded_image

def create_multi_TFRecordFile(): 
    ... 
    resized = tf.image.resize_images(image_raw_data, [227, 227], method=0) 
    resized = tf.image.encode_jpeg(resized) 
    ...