声明：基于python3.6提取NYUD V2数据集
NYUD V2数据集下载网址如下：
https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html（文中在Toolbox中提供了常用的预处理图像函数）
下载好的数据集的文件名是nyu_depth_v2_labeled.mat，可以用matlab打开。
NYUD V2数据集由1449张640*480的图像组成。
提取原图：
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import h5py
import os
f=h5py.File("/home/yuyangyg/DataSet/NYUDataV2/nyu_depth_v2_labeled.mat")
images=f["images"]
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)):
print(i)
images_number.append(images[i])
a=np.array(images_number[i])
# print len(img)
#img=img.reshape(3,480,640)
# print img.shape
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)
# plt.imshow(img)
# plt.axis('off')
# plt.show()
iconpath='./nyu_images/'+str(i)+'.jpg'
img.save(iconpath,optimize=True)
提取补洞后的深度图：
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import h5py
import os
from PIL import Image
f=h5py.File("/home/yuyangyg/DataSet/NYUDataV2/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[i]))
depths_img=depths_img.transpose(Image.FLIP_LEFT_RIGHT)
iconpath = path_converted + str(i) + '.png'
depths_img.save(iconpath, 'PNG', optimize=True)
提取原深度图rawDepths:
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import h5py
import os
from PIL import Image
f=h5py.File("/home/yuyangyg/DataSet/NYUDataV2/nyu_depth_v2_labeled.mat")
depths=f["rawDepths"]
depths=np.array(depths)
path_converted='./nyu_rawDepths/'
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[i]))
depths_img=depths_img.transpose(Image.FLIP_LEFT_RIGHT)
iconpath = path_converted + str(i) + '.png'
depths_img.save(iconpath, 'PNG', optimize=True)
提取label:
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import scipy.io as sio
import h5py
import os
from PIL import Image
f=h5py.File("/home/yuyangyg/DataSet/NYUDataV2/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[i])
labels_0=np.array(labels_number[i])
#print labels_0.shape
print (type(labels_0))
label_img=Image.fromarray(np.uint8(labels_number[i]))
#label_img = label_img.rotate(270)
label_img = label_img.transpose(Image.ROTATE_270)
iconpath='./nyu_labels/'+str(i)+'.png'
label_img.save(iconpath, 'PNG', optimize=True)
备注：使用Toolbox中的fill_depth_colorization.m函数时，输入的参数应该是double类型，如果图像是uint8或其他类型，则需要强转为double类型。
参考文章：