使用pickle模块存储猫狗数据

import os
import cv2
from sklearn.utils import shuffle
import numpy as np
from six.moves import cPickle as pickle

CLASS_NAME=["dogs","cats"]
#图像大小
img_size=64
#验证集大小
validation=0.2
#数据路径
train_path='D:/anicode/spyderworkspace/catanddog_class/training_data/'

def get_dataset(path):
    images=[]
    labels=[]
    for i,name in enumerate(CLASS_NAME):
        direct_name=path+name+'/'
        #listdir返回指定文件夹包含的文件或者文件的名字的列表
        direct=os.listdir(direct_name)
        for file in direct:
            img=cv2.imread(direct_name+file)
            img=cv2.resize(img,(img_size,img_size),0,0,cv2.INTER_LINEAR)
            img=img.astype(np.float32)
            img=np.multiply(img,1.0/255.0)
            images.append(img)
            labels.append(i)
    images=np.array(images)
    labels=np.array(