python使用h5py读取mat文件数据，并保存图像

sudo apt-get install libhdf5-dev
sudo pip install h5py

import numpy as np
import h5py
f = h5py.File('data.mat')
data = f['cell_name'][:]

data = f['cell_name/.../指定的元胞数组'][:]

img = images[i,...].transpose((2, 1, 0))
file = 'make3d_dataset_f460/images/'+str(i+1)+'.jpg'
img = img*255
img = img.astype('uint8')
cv2.imwrite(file, img)
#		pyplot.imsave(file, img)

import cv2
import numpy as np
import h5py
from matplotlib import pyplot

height = 460
width = 345

def extract_data():
with h5py.File('make3d_dataset_f460.mat','r') as f:
images = f['make3d_dataset_fchange/images'][:]

image_num = len(images)
for i in range(image_num):
img = images[i,...].transpose((2, 1, 0))
file = 'make3d_dataset_f460/images/'+str(i+1)+'.jpg'
img = img*255
img = img.astype('uint8')
cv2.imwrite(file, img)
#		pyplot.imsave(file, img)

def extract_labels():
with h5py.File('make3d_dataset_f460.mat','r') as f:
depths = f['make3d_dataset_fchange/depths'][:]

depth_num = len(depths)
for i in range(depth_num):
img = depths[i,...].transpose((1, 0))
file = 'make3d_dataset_f460/depths/'+str(i+1)+'.jpg'
depth = img
depth = depth.astype('uint8')
cv2.imwrite(file, depth)
#		pyplot.imsave(file, img)

def main(argv=None):
# Input  and groundtruth producer
extract_data()
extract_labels()
print("Training data is converted into images!")

if __name__ == '__main__':
main()