提取CIFAR10和CIFAR100中的图片显示并保存

所使用数据：（cifar10[test_batch]和cifar100[test]测试集的二进制数据）
链接：https://pan.baidu.com/s/1Faw9C3NOdqEcg7ZrlP9Hzg
提取码：yh4k

1.对cifar10图片进行显示并保存

# -*- coding: utf-8 -*-
import numpy as np
import pickle
import imageio

# 解压缩，返回解压后的字典
def unpickle(file):
    fo = open(file, 'rb')
    dict = pickle.load(fo, encoding='latin1')
    fo.close()
    return dict

test_file = "test_batch"
# 显示测试集图片
dict_test = unpickle(file)
x_test = dict_test.get("data")
y_test = dict_test.get("labels")
dict_test = unpickle(file)
x_test = dict_test.get("data")
y_test = dict_test.get("labels")
image_m = np.reshape(x_test[1], (3, 32, 32))
r = image_m[0, :, :]
g = image_m[1, :, :]
b = image_m[2, :, :]
img23 = cv2.merge([r, g, b])
plt.figure()
plt.imshow(img23)
plt.show()

# 保存测试集图片
testXtr = unpickle(test_file)
for i in range(1, 100): #保存全部的使用for i in range(1, 10000):
    img = np.reshape(testXtr['data'][i], (3, 32, 32))
    img = img.transpose(1, 2, 0)
    picName = 'datatest/10/' + str(testXtr['labels'][i]) + '_' + str(i) + '.jpg'
    imageio.imsave(picName, img)#, dpi=(600.0,600.0))
print("test_batch loaded.")

2.对cifar100图片进行显示并保存

from PIL import Image
import numpy as np
TO_ROOT='./datatest/100'
import imageio

def unpickle(file):
    import pickle
    with open(file, 'rb') as fo:
        dict = pickle.load(fo, encoding='latin1')
    return dict

#加载数据集
test_dict=unpickle('test')
data, label = np.array(test_dict['data']).reshape(-1, 3, 32, 32).transpose(0, 2, 3, 1), \
              test_dict['fine_labels']

#显示指定的图片    
numofimg = 25  # 图片序号
img = np.reshape(data[numofimg], (3, 32, 32))  # 导出指定的图片
img = img.transpose(1, 2, 0)

plt.figure(1)
plt.imshow(img)
plt.show()
print(label[numofimg])

#导出所有图片
count=0
for i in range(data.shape[0]):
    count = count + 1
    img = Image.fromarray(data[i])
    picName = 'datatest/100/' + str(label[i]) + '_' + str(i) + '.jpg'
    imageio.imsave(picName, img)  # , dpi=(600.0,600.0))

注：如果你的论文中用到了cifar10和cifar100的数据集，提取出cifar10和cifar100的图片后，在word中插入表格就可以作出类似的图~