.npy文件的保存与加载

 1 import os
 2 import numpy as np
 3 import cv2
 4 import matplotlib.pyplot as plt
 5 from PIL import Image
 6 def create_train_data(data_path,file_path,image_rows,image_cols):
 7     train_data_path = os.path.join(data_path, file_path)
 8     images = os.listdir(train_data_path)
 9     image_sorted=sorted(images,key=lambda i:int(i.split(‘t‘)[1].split(‘.‘)[0]))
10     imgs=[]
11     i = 0
12     print(‘-‘*30)
13     print(‘Creating training images...‘)
14     print(‘-‘*30)
15     for image_name in image_sorted:
16         if ‘mask‘ in image_name:
17             continue
18         #image_mask_name = image_name.split(‘.‘)[0] + ‘_mask.tif‘#分离得到点之前的内容，即文件名
19 
20         img = cv2.imread(os.path.join(train_data_path,image_name),cv2.IMREAD_GRAYSCALE)#注意，opencv读取的路径不能含有中文名
21         img=cv2.resize(img,(image_rows,image_cols))
22         img=np.reshape(img,img.shape+(1,))#（32,32,1）
23         imgs.append(img)
24     imgs_arr=np.array(imgs)
25     # plt.imshow(imgs_arr[10].squeeze())
26     # plt.show()
27     print(imgs_arr.shape)
28     print(‘Loading done.‘)
29     np.save(r‘G:\data\imgs_arr_train.npy‘, imgs_arr)
30     #np.save(‘imgs_mask_train.npy‘, imgs_mask)
31     print(‘Saving to .npy files done.‘)
32 def load_train_data():
33     imgs_train = np.load(‘imgs_train.npy‘)
34     imgs_mask_train = np.load(‘imgs_mask_train.npy‘)
35     return imgs_train, imgs_mask_train
36 if __name__==‘__main__‘:
37     create_train_data(‘G:\\data‘,‘mnist_test‘,32,32)

1 rename
2  for img_old in img_path:
3      img_new=‘t‘+img_old.split(‘.‘)[0]+‘.jpg‘
4      os.chdir(path)#切换至当前路径，即将rename之后的文件保存在当前路径下，如#不切换，则需要定义保存路径
5      os.renames(img_old,img_new)