# 3. non-max supprssion
suppressed = Detector.non_max_suppression((SobelX, SobelY))
# Image.fromarray(np.uint8(suppressed), 'L').show()
# 4. canny detection
canny = Detector.canny_detector(np.uint8(suppressed) * 255)
canny_image = Image.fromarray(np.uint8(canny) * 255, 'L').convert("RGB")
# Image.fromarray(np.uint8(canny) * 255, 'L').show()
# 5. Hough transformation
vertical_lines = Detector.hough_lines(canny, 180, 452)
horizontal_lines = Detector.hough_lines(canny, 90, 193)
# output image
Detector.drawLines(canny_image, vertical_lines[0], vertical_lines[1])
Detector.drawLines(canny_image, horizontal_lines[0], horizontal_lines[1])
canny_image.save(args.output_im)
canny_gray = ImageOps.grayscale(canny_image)
canny_gray.save(args.output_im)
##canny_img = np.uint8(canny_image)#canny_image.load()
##find blue line
# 6. output detected answers to txt file
answers = Detector.naive_grader(np.uint8(canny) * 255)
#answers = Detector.origin_grader(np.uint8(image_gray))
#answers = Detector.hough_grader(np.uint8(canny_gray))
##use edged graph to find location will sometimes cause the missing lines
