depth.py

import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt
import scipy.misc
import os

def loadImages():
    image_array = []
    shape_array = []
    label_array = []
    base='./dataset5/A/'
    directories=os.listdir(base)
    for folder in directories:
	    for filename in os.listdir(base+folder):
	        if 'depth' in filename:
	            img = cv.imread(base+folder+'/'+filename,0)
	            img=np.array(img)
	            shape_array.append(img.shape)

	            image_array.append(img.ravel())
	            label_array.append(folder)
    
    return np.array(image_array), np.array(shape_array), np.array(label_array)


image_array,shape_array,label_array=loadImages()
print(image_array.shape)
print(shape_array.shape)
print(label_array.shape)

n_images=len(image_array)
for i in range(1):
	len_image=len(image_array[i])
	for j in range(len_image):
		if(image_array[i][j]==3 or image_array[i][j]==2):
			image_array[i][j]=255
		else:
			image_array[i][j]=0 
	

print(1)
print(image_array.shape)

ind=0
for i in image_array:
	ir=i.reshape(shape_array[ind][0], shape_array[ind][1])
	scipy.misc.toimage(ir).save('./maps/'+str(ind)+'.png')
	ind+=1


#print(segment_images_shapes[leng-1])

# img = cv.imread('./dataset5/A/f/color_5_0009.png',0)
# depth=cv.imread('./dataset5/A/f/depth_5_0009.png',0)
# img=np.array(img)
# depth=np.array(depth)
# print(img.shape, depth.shape)
# img_r=img.ravel()
# depth_r=depth.ravel()
# uniq=np.unique(depth_r)
# print(uniq)
# n=len(img_r)

# for i in range(0,n):
# 	if(depth_r[i]==3 or depth_r[i]==2):
# 		img_r[i]=255
# 	else:
# 		img_r[i]=0
# ind=1
# ir=img_r.reshape(img.shape[0], img.shape[1])
# scipy.misc.toimage(ir).save('./maps/'+str(ind)+'.png')