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face-detector.py
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face-detector.py
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import cv2
#loading the free open source xml file by Opencv which is already trained on a lot of frontal faces (haarcascade algorithm)
face_data = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#choosing an image to detect face
# img = cv2.imread('me.jpg')
# getting input from webcam
webcam = cv2.VideoCapture(0) ## use cv2.VideoCapture(0) for webcam and cv2.imread('image file') for images
# Iterate forver through the frames
while True:
#read the current frame
successful_frame_read, frame = webcam.read()
#converting the image into black&white (grayscale)
bw_img = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#detecting the face
face_coordinates = face_data.detectMultiScale(bw_img)
# drawing rectangle ariound the faces
# (x, y, w, h) = face_coordinates[0]
for (x, y, w, h) in face_coordinates:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
cv2.imshow("Rupesh's Face detector app", frame)
key = cv2.waitKey(1)
#End the program if Q is pressed
if key==81 or key==113:
break
#Release the video capture object
webcam.release()
'''
#detecting the face
face_coordinates = face_data.detectMultiScale(bw_img)
# drawing rectangle ariound the faces
# (x, y, w, h) = face_coordinates[0]
for (x, y, w, h) in face_coordinates:
cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
#showing the image
cv2.imshow("Rupesh's Face detector app", img)
#to keep the image on screen until we press any key
cv2.waitKey()
print("Completed")
'''