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import os
from PIL import Image, ImageFile
import tensorflow as tf
import numpy as np


ImageFile.LOAD_TRUNCATED_IMAGES = True

CWD = '/home/qinlong/PycharmProjects/ProgNEU/NEU/cai_nl/classes'

def convert_to_tfrecord(cwd, output):
 classes = os.listdir(cwd)
 writer = tf.python_io.TFRecordWriter(output)
 for index, name in enumerate(classes):
 class_path = cwd + '/' + name + '/'
 for img_name in os.listdir(class_path):
 img_path = class_path + img_name 

 img = Image.open(img_path)
 img = img.resize((64, 64))
 img_raw = img.tobytes() 
 example = tf.train.Example(features=tf.train.Features(feature=
 'label': tf.train.Feature(int64_list=tf.train.Int64List(value=[index])),
 'img_raw': tf.train.Feature(bytes_list = tf.train.BytesList(value=[img_raw]))
 )) 
 writer.write(example.SerializeToString()) 
 writer.close()
 return output


def dataset_input_fn(batch_size, epoch, buffer_size=2048):
 filenames = ['/home/qinlong/PycharmProjects/ProgNEU/NEU/cai_nl/a_4.tfrecord']
 dataset = tf.data.TFRecordDataset(filenames)

 def parser(record):
 keys_to_features = 
 "image_data": tf.FixedLenFeature((), tf.string, default_value=""),
 "date_time": tf.FixedLenFeature((), tf.int64, default_value=0),
 "label": tf.FixedLenFeature((), tf.int64,
 default_value=tf.zeros(, dtype=tf.int64)),
 
 parsed = tf.parse_single_example(record, keys_to_features)

 # Perform additional preprocessing on the parsed data.
 image = tf.image.decode_jpeg(parsed["image_data"])
 image = tf.reshape(image, [64, 64, 3])
 label = tf.cast(parsed["label"], tf.int32)

 return "image_data": image, "date_time": parsed["date_time"], label

 dataset = dataset.map(parser)
 dataset = dataset.shuffle(buffer_size=10000)
 dataset = dataset.batch(batch_size=batch_size)
 dataset = dataset.repeat(epoch)

 iterator = dataset.make_one_shot_iterator()

 features, labels = iterator.get_next()
 return features, labels

InvalidArgumentError: Expected image (JPEG, PNG, or GIF), got empty
file [[node DecodeJpeg = DecodeJpegacceptable_fraction=1,
channels=0, dct_method="", fancy_upscaling=true, ratio=1,
try_recover_truncated=false]]
[[node IteratorGetNext (defined at
/home/qinlong/PycharmProjects/ProgNEU/NEU/cai_nl/main.py:23) =
IteratorGetNextoutput_shapes=[[?], [?,64,64,3], [?]],
output_types=[DT_INT64, DT_UINT8, DT_INT32],
_device="/job:localhost/replica:0/task:0/device:CPU:0"]]