def merge_mask_img(uid,img_type):
	import cv2
	import numpy as np
	from PIL import Image
	try:
		n_file_name = uid+'/'+img_type+'.png'
		mask_file_name = uid + '/'+'mask_img.png'
		n_file = cv2.imread(n_file_name)
		mask = cv2.imread(mask_file_name)

		orig_h,orig_w,orig_rgb = n_file.shape
		#n_array = cv2.resize(n_array,(orig_w,orig_h))
		h,w = orig_h,orig_w
		print(h)
		print(w)
		b_channel, g_channel, r_channel = cv2.split(n_file)
		b_white = b_channel
		g_white = g_channel
		r_white = r_channel
		area_pixels = 0
		total_pixels = 0
		alpha_channel = np.zeros([h,w])
		for y in range(0,h):
			for x in range(0,w):
				if mask[y][x][0] == 255:
					total_pixels = total_pixels + 1
					alpha_channel[y][x] = 255
					#b_white[y][x] = 255
					#g_white[y][x] = 255
					#r_white[y][x] = 255
					#print('caamh')
					if g_channel[y][x] == 255:
						area_pixels = area_pixels + 1
				else:
					alpha_channel[y][x] = 0
					b_white[y][x] = 0
					g_white[y][x] = 0
					r_white[y][x] = 0
				if img_type == 'hybrid_blind'and b_white[y][x] == 111 and g_white[y][x] == 111 and r_white[y][x] == 111:
					alpha_channel[y][x] = 0
		alpha_channel = alpha_channel.astype(np.uint8)
		img_RGBA = cv2.merge((b_channel, g_channel, r_channel, alpha_channel))
		#img_white = cv2.merge((b_white, g_white, r_white, alpha_channel))
		#n_white_name = uid+'/'+img_type+'_white'+'.png'
		#sw2 = cv2.imwrite(n_white_name, img_white)
		sw2 = cv2.imwrite(n_file_name, img_RGBA)
		print(['area-total-pixels', area_pixels, total_pixels])
		return area_pixels, total_pixels
	except Exception as e:
		print('merge error')
		print(e)
		return 0,1