网上找了很多不能用，我这个测试可以用，转换后分成10个文件夹，train有10个文件夹,test有10个文件夹
import cv2
import numpy as np
import os
import pickle
if not os.path.exists("./train"):
os.makedirs("./train")
if not os.path.exists("./test"):
os.makedirs("./test")
label_name_list = ['airplane','automobile','bird','cat','deer','dog','frog','horse','ship','truck']
for name in label_name_list:
if not os.path.exists("./train/"+name):
os.makedirs("./train/"+name)
if not os.path.exists("./test/"+name):
os.makedirs("./test/"+name)
def unpickle(file):
with open(file, 'rb') as f:
dict = pickle.load(f,encoding="bytes")
return dict
def main(cifar10_data_dir):
for i in range(1, 6):
train_data_file = os.path.join(cifar10_data_dir, 'data_batch_' + str(i))
print(train_data_file)
data = unpickle(train_data_file)
print('unpickle done')
for j in range(10000):
img = np.reshape(data[b'data'][j], (3, 32, 32))
img = img.transpose(1, 2, 0)
img_name = './train/' + label_name_list[data[b'labels'][j]] + '/' + str(j + (i - 1) * 10000) + '.jpg'
cv2.imwrite(img_name, img)
test_data_file = os.path.join(cifar10_data_dir, 'test_batch')
data = unpickle(test_data_file)
for i in range(10000):
img = np.reshape(data[b'data'][i], (3, 32, 32))
img = img.transpose(1, 2, 0)
img_name = './test/' + label_name_list[data[b'labels'][i]] + '/' + str(i) + '.jpg'
cv2.imwrite(img_name, img)
if __name__ == "__main__":
main('C:/Users/Administrator/Desktop/cifar-10-batches-py')
