def harris$\_$corner$\_$detection$($image$,$ kernel$\_$size, k$,$ threshold$)$:

# Convert image to grayscale

gray $=$ cv$2.$cvtColor$($image$,$ cv$2.$COLOR$\_$BGR$2$GRAY$)$

# Apply Gaussian blur

blurred $=$ cv$2.$GaussBlur$($gray$,($kernel$\_$size, kernel$\_$size$),0)$

# Calculate gradients using Sobel filters

gradient$\_$x $=$ cv$2.$Sob$($blurred$,$ cv$2.$CV$\_64$F$,1,0,$ ksize $=3)$

gradient$\_$y $=$ cv$2.$Sob$($blurred$,$ cv$2.$CV$\_64$F$,0,1,$ ksize $=3)$

# Compute the structure tensor elements

gradient$\_$xx $=$ gradient$\_$x $**2$

gradient$\_$xy $=$ gradient$\_$x $*$ gradient$\_$y

gradient$\_$yy $=$ gradient$\_$y $**2$

# Apply Gaussian filter to structure tensor elements

gradient$\_$xx $=$ cv$2.$GaussBlur$($gradient$\_$xx$,($kernel$\_$size, kernel$\_$size$),0)$

gradient$\_$xy $=$ cv$2.$GaussBlur$($gradient$\_$xy$,($kernel$\_$size, kernel$\_$size$),0)$

gradient$\_$yy $=$ cv$2.$GaussBlur$($gradient$\_$yy$,($kernel$\_$size, kernel$\_$size$),0)$

# Compute the Harris response function

det $=$ gradient$\_$xx $*$ gradient$\_$yy $-$ gradient$\_$xy $**2$

trace $=$ gradient$\_$xx $+$ gradient$\_$yy

harris$\_$response $=$ det $-$ k $*$ trace $**2$

# Apply non$-$maximum suppression to find corner points

corner$\_$mask $=$ np$.$zeros$\_$like$($image$)$

corner$\_$mask$[$harris$\_$response $>$ threshold $*$ harris$\_$response.max$()]=[0,0,255]$

##########$--$WRITE YOUR CODE HERE$--$##########

# Mark corners in red

##########$-------$END OF CODE$-------$##########

# Overlay corner points on the original image

output$\_$image $=$

return output$\_$image