②本地图片转TFRecord及opencv安装

本文主要是介绍②本地图片转TFRecord及opencv安装，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

之前我们对图片数据的读取是通过tensorflow的mnist类直接下载和加载mnist数据集。但是更多的时候，我们想通过本地的图片进行训练。

import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

def _int64_feature(value):return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))def _bytes_feature(value):return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))dirPath = "F:/byxStudy/img/mnist0-9/"
sess = tf.InteractiveSession()
init = tf.global_variables_initializer()
sess.run(init)
#保存tfrecords
tfrecord_filename = 'F:\\byxStudy\\img\\mnist0_9_train.tfrecords'
fileSubDirList = os.listdir(dirPath)
with tf.python_io.TFRecordWriter(tfrecord_filename) as writer:# 遍历子文件夹for fileSubDir in fileSubDirList:fileSubDirSubDir = os.listdir(dirPath + fileSubDir + "/")for filePath in fileSubDirSubDir:image_value = tf.read_file(dirPath + fileSubDir + "/" + filePath)img = tf.image.decode_jpeg(image_value, 1)img = tf.image.resize_images(img, (28, 28), method=0)pic2 = img.eval(session=sess)image_raw = pic2.tostring()example = tf.train.Example(features=tf.train.Features(feature={'height': _int64_feature(pic2.shape[0]),'width': _int64_feature(pic2.shape[1]),'depth': _int64_feature(pic2.shape[2]),'label': _int64_feature(int(fileSubDir)),'image_raw': _bytes_feature(image_raw)}))writer.write(example.SerializeToString())

import cv2
import os
import tensorflow as tfdef _int64_feature(value):return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))def _bytes_feature(value):return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))dir_path = "F:/byxStudy/img/mnist0-9/"
tfrecord_filename = 'F:\\byxStudy\\img\\mnist0_9_train.tfrecords'
dir_list = os.listdir(dir_path)
with tf.python_io.TFRecordWriter(tfrecord_filename) as writer:# 遍历子文件夹for sub_dir in dir_list:sub_dir_list = os.listdir(dir_path + sub_dir + "/")for filePath in sub_dir_list:# 单通道的方式读取图片# 中文目录无法加载图片img = cv2.imread(dir_path + sub_dir + '/' + filePath, 0)img = cv2.resize(img, (28, 28), interpolation=cv2.INTER_CUBIC)image_raw = img.tostring()example = tf.train.Example(features=tf.train.Features(feature={'height': _int64_feature(img.shape[0]),'width': _int64_feature(img.shape[1]),'depth': _int64_feature(1),'label': _int64_feature(int(sub_dir)),'image_raw': _bytes_feature(image_raw)}))writer.write(example.SerializeToString())

这篇关于②本地图片转TFRecord及opencv安装的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！

---