harris_corner.py

importcv2
importnumpyasnp

"""
Harris Corner Detector
https://en.wikipedia.org/wiki/Harris_Corner_Detector
"""


classHarrisCorner:
def__init__(self, k: float, window_size: int):
"""
 k : is an empirically determined constant in [0.04,0.06]
 window_size : neighbourhoods considered
 """

ifkin (0.04, 0.06):
self.k=k
self.window_size=window_size
else:
raiseValueError("invalid k value")

def__str__(self) ->str:
returnstr(self.k)

defdetect(self, img_path: str) ->tuple[cv2.Mat, list[list[int]]]:
"""
 Returns the image with corners identified
 img_path : path of the image
 output : list of the corner positions, image
 """

img=cv2.imread(img_path, 0)
h, w=img.shape
corner_list: list[list[int]] = []
color_img=img.copy()
color_img=cv2.cvtColor(color_img, cv2.COLOR_GRAY2RGB)
dy, dx=np.gradient(img)
ixx=dx**2
iyy=dy**2
ixy=dx*dy
k=0.04
offset=self.window_size//2
foryinrange(offset, h-offset):
forxinrange(offset, w-offset):
wxx=ixx[
y-offset : y+offset+1, x-offset : x+offset+1
 ].sum()
wyy=iyy[
y-offset : y+offset+1, x-offset : x+offset+1
 ].sum()
wxy=ixy[
y-offset : y+offset+1, x-offset : x+offset+1
 ].sum()

det= (wxx*wyy) - (wxy**2)
trace=wxx+wyy
r=det-k* (trace**2)
# Can change the value
ifr>0.5:
corner_list.append([x, y, r])
color_img.itemset((y, x, 0), 0)
color_img.itemset((y, x, 1), 0)
color_img.itemset((y, x, 2), 255)
returncolor_img, corner_list


if__name__=="__main__":
edge_detect=HarrisCorner(0.04, 3)
color_img, _=edge_detect.detect("path_to_image")
cv2.imwrite("detect.png", color_img)