def compute_harris_response(image):
""" compute the Harris corner detector response function
for each pixel in the image"""
#derivatives
imx, imy = filtertools.gauss_derivatives(image, 3)
#kernel for blurring
gauss = filtertools.gauss_kernel(3)
#compute components of the structure tensor
Wxx = signal.convolve(imx*imx, gauss, mode='same')
Wxy = signal.convolve(imx*imy, gauss, mode='same')
Wyy = signal.convolve(imy*imy, gauss, mode='same')
#determinant and trace
Wdet = Wxx*Wyy - Wxy**2
Wtr = Wxx + Wyy
if numpy.count_nonzero(Wtr) == 0:
return
print Wtr.shape
print numpy.count_nonzero(Wtr)
return Wdet / Wtr
def compute_harris_response(image):
""" compute the Harris corner detector response function
for each pixel in the image"""
#derivatives
imx,imy = filtertools.gauss_derivatives(image, 3)
#kernel for blurring
gauss = filtertools.gauss_kernel(3)
#compute components of the structure tensor
Wxx = signal.convolve(imx*imx,gauss, mode='same')
Wxy = signal.convolve(imx*imy,gauss, mode='same')
Wyy = signal.convolve(imy*imy,gauss, mode='same')
#determinant and trace
Wdet = Wxx*Wyy - Wxy**2
Wtr = Wxx + Wyy
print (Wdet,Wtr)
return Wdet / Wtr
def compute_harris_response(image):
""" compute the Harris corner detector response function
for each pixel in the image"""
#derivatives
sobelx=np.array([[-1,0,1],[-2,0,2],[-1,0,1]])
sobely=np.array([[1,2,1],[0,0,0],[-1,-2,-1]])
imx=signal.convolve2d(image,sobelx,boundary='symm', mode='same')
imy=signal.convolve2d(image,sobely,boundary='symm', mode='same')
#kernel for blurring
gauss = gauss_kernel(3)
print(gauss)
#compute components of the structure tensor
Wxx = signal.convolve(imx*imx,gauss, mode='same')
Wxy = signal.convolve(imx*imy,gauss, mode='same')
Wyy = signal.convolve(imy*imy,gauss, mode='same')
#determinant and trace
Wdet = Wxx*Wyy - Wxy**2
Wtr = Wxx + Wyy
return (Wdet/Wtr)
