Question

Please use python and opencv library in python to implement the following tasks.
Given a gray image 'test.jpg' , first use Gaussian filter to smooth it, then detect keypoints by using Harris corner detector, finally show the image with keypoints.

Answer 1

import cv2
import numpy as np

filename = 'test.png'
#read image into img
img = cv2.imread(filename)
cv2.imshow('orginal image',img)

#convert image to gray
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

gray = np.float32(gray)
dst = cv2.cornerHarris(gray,2,3,0.04)

#result is dilated for marking the corners, not important
dst = cv2.dilate(dst,None)

#first use Gaussian filter to smooth it
img = cv2.GaussianBlur(img,(5,5),0)

# Threshold for an optimal value, it may vary depending on the image.
img[dst>0.01*dst.max()]=[0,0,255]
cv2.imshow('dst',img)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()

test.png( Input a black and white image)

$1592647186346_test.png$

OUTPUT

orginal image Х I dst Activate vindows Go to Settings to activate Windows. 2.20 DA