选择 Labeled dataset(~2.8G)

对下载的mat文件（nyu_depth_v2_labeled.mat）提取数据

提取RGB图像

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import h5py
import os
f=h5py.File("nyu_depth_v2_labeled.mat")
images=f["images"]
labels=f["labels"]
images=np.array(images)

path_converted='./nyu_images'
if not os.path.isdir(path_converted):
    os.makedirs(path_converted)

from PIL import Image
images_number=[]
for i in range(len(images)):
    images_number.append(images)
    a=np.array(images_number)
    r = Image.fromarray(a[0]).convert('L')
    g = Image.fromarray(a[1]).convert('L')
    b = Image.fromarray(a[2]).convert('L')
    img = Image.merge("RGB", (r, g, b))
    img = img.transpose(Image.ROTATE_270)
    iconpath='./nyu_images/'+str(i)+'.jpg'
    img.save(iconpath,optimize=True)
提取depth图像

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import numpy as np
import h5py
import os
from PIL import Image

f=h5py.File("nyu_depth_v2_labeled.mat")
depths=f["depths"]
depths=np.array(depths)

path_converted='./nyu_depths/'
if not os.path.isdir(path_converted):
    os.makedirs(path_converted)

max = depths.max()
print(depths.shape)
print(depths.max())
print(depths.min())

depths = depths / max * 255
depths = depths.transpose((0,2,1))

print(depths.max())
print(depths.min())

for i in range(len(depths)):
    print(str(i) + '.png')
    depths_img= Image.fromarray(np.uint8(depths))
    depths_img = depths_img.transpose(Image.FLIP_LEFT_RIGHT)
    iconpath=path_converted + str(i)+'.png'
    depths_img.save(iconpath, 'PNG', optimize=True)
提取labels

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
import numpy as np
import h5py
import os
from PIL import Image

f=h5py.File("nyu_depth_v2_labeled.mat")
labels=f["labels"]
labels=np.array(labels)

path_converted='./nyu_labels/'
if not os.path.isdir(path_converted):
    os.makedirs(path_converted)

labels_number = []
for i in range(len(labels)):
    labels_number.append(labels)
    labels_0 = np.array(labels_number)
    label_img = Image.fromarray(np.uint8(labels_number))
    label_img = label_img.transpose(Image.ROTATE_270)

    iconpath = './nyu_labels/' + str(i) + '.png'
    label_img.save(iconpath, 'PNG', optimize=True)

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【转载】
作者：sinat_26871259
原文：https://blog.csdn.net/sinat_26871259/article/details/82351276