canny.py

import cv2
import numpy as np

def auto_canny(image, sigma=0.33):
	# compute the median of the single channel pixel intensities
	v = np.median(image)

	# apply automatic Canny edge detection using the computed median
	lower = int(max(0, (1.0 - sigma) * v))
	upper = int(min(255, (1.0 + sigma) * v))
	edged = cv2.Canny(image, lower, upper)
	return edged


image = cv2.imread('canny.tif')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (3, 3), 0)

# apply Canny edge detection using a wide threshold, tight
# threshold, and automatically determined threshold
wide = cv2.Canny(blurred, 10, 200)
tight = cv2.Canny(blurred, 225, 250)
auto = auto_canny(blurred)

# show the images
cv2.imshow("Original", image)
cv2.imshow("Edges", np.hstack([wide]))
cv2.waitKey(0)