#corner detection
import cv2
import numpy as np

image_path = "corners.jpg"  
image = cv2.imread(image_path)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

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

dst = cv2.dilate(dst, None)

image[dst > 0.01 * dst.max()] = [0, 0, 255] 

cv2.imshow("Harris Corner Detection", image)
cv2.waitKey(0)
cv2.destroyAllWindows()

#face detection
import cv2

image_path = "faces.jpg"  
image = cv2.imread(image_path)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

for (x, y, w, h) in faces:
    cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 0), 2)
    
cv2.imshow("Face Detection", image)
cv2.waitKey(0)
cv2.destroyAllWindows()