把cifar100的图片切割成一张张图片（python代码）：
# -*- coding:utf-8 -*-
import pickle as p
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as plimg
from PIL import Image
def load_CIFAR_batch(filename):
""" load single batch of cifar """
with open(filename, 'rb')as f:
datadict = p.load(f,encoding='bytes')
#X = datadict[b'data']
#Y = datadict[b'labels']
#X = X.reshape(10000, 3, 32, 32)
X = datadict[b'data']
Y = datadict[b'coarse_labels']+datadict[b'fine_labels']
X = X.reshape(50000, 3, 32, 32)
Y = np.array(Y)
return X, Y
if __name__ == "__main__":
#imgX, imgY = load_CIFAR_batch("./cifar-10-batches-py/data_batch_1")
imgX, imgY = load_CIFAR_batch("./cifar-100-python/train")
print(imgX.shape)
print("正在保存图片:")
for i in range(imgX.shape[0]):
imgs = imgX[i]
if i < 100:#只循环100张图片,这句注释掉可以便利出所有的图片,图片较多,可能要一定的时间
img0 = imgs[0]
img1 = imgs[1]
img2 = imgs[2]
i0 = Image.fromarray(img0)
i1 = Image.fromarray(img1)
i2 = Image.fromarray(img2)
img = Image.merge("RGB",(i0,i1,i2))
name = "img" + str(i)+".png"
img.save("./pic1/"+name,"png")#文件夹下是RGB融合后的图像
for j in range(imgs.shape[0]):
img = imgs[j]
name = "img" + str(i) + str(j) + ".jpg"
print("正在保存图片" + name)
plimg.imsave("./pic2/" + name, img)#文件夹下是RGB分离的图像
print("保存完毕.")
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