Created
October 9, 2017 04:12
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interactively do quick edge detection via difference of gaussian
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import cv2 | |
def dog(img, k2=(7, 7), k1=(3, 3), denoise=False, denoise_k=3): | |
blur1 = cv2.GaussianBlur(img, k1, 1) | |
blur2 = cv2.GaussianBlur(img, k2, 1) | |
diff = blur1 - blur2 | |
if denoise: | |
diff = cv2.medianBlur(diff, denoise_k) | |
return diff | |
img = cv2.imread("./tripod.png") | |
k2 = 3 | |
k1 = 1 | |
k_d = 3 | |
d_flag = False | |
edge = True | |
while True: | |
k = cv2.waitKey(1) | |
if edge: | |
show = dog(img, k2=(k2, k2), k1=(k1, k1), denoise=d_flag, denoise_k=k_d) | |
else: | |
show = img | |
cv2.imshow("DoG".format(k2, k1, d_flag, k_d), show) | |
if k == ord('q'): | |
break | |
elif k == ord('w'): | |
k2 += 2 | |
elif k == ord('s'): | |
k2 -= 2 | |
k2 = max(k2, 3) | |
k2 = max(k2, k1 + 2) | |
elif k == ord('p'): | |
k1 += 2 | |
k1 = min(k1, k2 - 2) | |
elif k == ord('l'): | |
k1 -= 2 | |
k1 = max(k1, 1) | |
elif k == ord(' '): | |
d_flag = not d_flag | |
elif k == ord('t'): | |
k_d += 2 | |
k_d = max(k_d, 3) | |
elif k == ord('g'): | |
k_d -= 2 | |
k_d = max(k_d, 3) | |
elif k == ord('i'): | |
edge = not edge | |
print(k1, k2, k_d) |
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