创建csv文件并根据csv文件读取数据（基于tensorflow）

import csv
with open("test.csv", "w") as csvfile:
    print(csvfile)
    writer = csv.writer(csvfile)

    writer.writerow(["index", "a_name", "b_name"])
    for i in range(3):
    # 先写入columns_name
        # 写入多行用writerows
        writer.writerows([[i, i+1, i-1]])

路径：

import os
import csv
path='./img'
images_name=os.listdir(path)
def create_csv():
    with open('train_list.csv','w') as csvfile:
        writer = csv.writer(csvfile)
        for n in images_name:
            if n[-4:] == '.jpg':
                print(n)
                # with open('data_'+dirname+'.csv','rb') as f:
                writer.writerow(
                    ['./img/' + str(n), 1])
            else:
                pass
if __name__ == '__main__':
    create_csv()

打印结果：

CSV文件读取：

def get_image():
    image_train_list=[]
    image_label_list=[]
    with open('train_list.csv') as csvfile:
        for image_path in csvfile.readlines():
            image_train_list.append(image_path.strip().split(',')[0])
            image_label_list.append(image_path.strip().split(',')[1])
    print(image_train_list)
    print(image_label_list)

    # for i in image_train_list:
    img=tf.image.convert_image_dtype(
                tf.image.decode_jpeg(tf.read_file('./img/2018-08-08 131518.jpg'),
                channels=3),
                dtype=tf.float32)
    print(img)
    with tf.Session() as sess:
        image=sess.run(img)
        cv2.imshow('img',image)
        cv2.waitKey()
if __name__ == '__main__':
    # create_csv()
    get_image()