def merge_com_img(sensing_date,uid,img_type):
	import cv2
	import numpy as np
	from PIL import Image
	n_file_name = sensing_date+uid+'M'+img_type+'.png'
	etci_file_name=sensing_date+uid+'_TCI.png'
	n_file = cv2.imread(n_file_name)
	etci = cv2.imread(etci_file_name)
	
	orig_h,orig_w,orig_rgb = etci.shape
	
	h,w = orig_h,orig_w
	print(h)
	print(w)
	n_file = cv2.resize(n_file,(w,h))
	
	sw2 = cv2.imwrite(n_file_name,n_file)
	etci = cv2.resize(etci,(w,h))
	new_img = np.zeros([h,w,3])
	
	
	for py in range(0,h):
		for px in range(0,w):
			#print(n_array[py][px])
			if (n_file[py][px][1] > 0) & (n_file[py][px][1]<240):
			#if (n_array[py][px] > 12) & (n_array[py][px]<80):
				new_img[py][px][0]=n_file[py][px][0]
				new_img[py][px][1]=n_file[py][px][1]
				new_img[py][px][2]=n_file[py][px][2]
			else:
				new_img[py][px][0]=etci[py][px][0]
				new_img[py][px][1]=etci[py][px][1]
				new_img[py][px][2]=etci[py][px][2]
	mn_file_name = n_file_name
	
	status = cv2.imwrite(mn_file_name,new_img)
	
	new_img = Image.open(mn_file_name)
	etci_orig = Image.open(etci_file_name)
	etci_orig = etci_orig.convert("RGBA")
	new_img = new_img.convert("RGBA")
	new_img = new_img.resize((orig_w,orig_h),Image.NEAREST)
	new_img = Image.blend(etci_orig,new_img,0.6)
	new_img.save(mn_file_name,"PNG")