import tensorflow as tf
from pil import image
import matplotlib.pyplot as plt
import numpy as np
import os
i = 0
j = 0
num_shards = 100#總共寫入的檔案個數
instances_per_shard = 2#每個檔案中的資料個數
sess=tf.interactivesession()
cwd = "f:/寒假/google--data/新建資料夾/" #資料所在目錄位置(讀者自己去改就好了)
classes = #預先自己定義的類別，根據自己的需要修改
def _int64_feature(value):#生成整數型的屬性
return tf.train.feature(int64_list=tf.train.int64list(value=[value]))
def _bytes_feature(value):#生成字串型的屬性
return tf.train.feature(bytes_list=tf.train.byteslist(value=[value]))
for index, name in enumerate(classes):#列舉函式
class_path = cwd + name + "/"#選取具體資料目錄
for img_name in os.listdir(class_path):#遍歷檔案列表
img_path = class_path + img_name#路徑
img = image.open(img_path)
img = img.resize((299, 299)) #影象reshape大小設定，根據自己的需要修改
img_raw = img.tobytes()
example = tf.train.example(features=tf.train.features(feature=))
filename = ("f:/寒假/google--data/data.tfrecords-%.5d-of-%.5d"%(i,num_shards))
if j == instances_per_shard-1:
i+=1
j+=1
if j == instances_per_shard:
j=0writer = tf.python_io.tfrecordwriter(filename)
writer.write(example.serializetostring())#將乙個example寫入tfrecord檔案
writer.close()
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