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 #step 1: make a3 channel, bgr or rgb image from the canny output:
 edges = cv2.Canny(m,100,200)
 rgb = cv2.cvtColor(edges, cv2.COLOR_GRAY2RGB) # RGB for matplotlib, BGR for imshow() !
 #step2: now all edges are white (255,255,255). to make it red, multiply with another array:
 rgb *= np.array((1,0,0),np.uint8) #set r and b to 0, leaves red :)

 #step # step 1: make a3 channel, bgr or rgb image from the canny output:
 edges = cv2.Canny(m,100,200)
 rgb = cv2.cvtColor(edges, cv2.COLOR_GRAY2RGB) # RGB for matplotlib, BGR for imshow() !
 #step2: # step2: now all edges are white (255,255,255). to make it red, multiply with another array:
 rgb *= np.array((1,0,0),np.uint8) #set r # set g and b to 0, leaves red :)

 # step 1: make a3 channel, bgr or rgb image from the canny output:
 edges = cv2.Canny(m,100,200)
 rgb = cv2.cvtColor(edges, cv2.COLOR_GRAY2RGB) # RGB for matplotlib, BGR for imshow() !
  # step2: step 2: now all edges are white (255,255,255). to make it red, multiply with another array:
 rgb *= np.array((1,0,0),np.uint8) # set g and b to 0, leaves red :)

 # step 3: compose:
 out = np.bitwise_or(im2, rgb)