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face_eye_detection.py
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face_eye_detection.py
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import numpy as np
import cv2
face_cascade = cv2.CascadeClassifier('C:\\Users\\TEJAS\\Downloads\\opencv\\build\\etc\\haarcascades\\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('C:\\Users\\TEJAS\\Downloads\\opencv\\build\\etc\\haarcascades\\haarcascade_eye.xml')
img = cv2.imread('C:/Users/TEJAS/Downloads/test4.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
k = cv2.waitKey(0)
if k == 27: # wait for ESC key to exit
cv2.destroyAllWindows()
elif k == ord('s'): # wait for 's' key to save and exit
cv2.imwrite('detect.png',img)
cv2.destroyAllWindows()