interactively do quick edge detection via difference of gaussian

diff_of_gauss.py

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)