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face-recognition.py
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face-recognition.py
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import cv2
# Load pre-trained model 'haarcascade_frontalface_alt.xml" for face recognition / classification
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
# Create object for default camera 0
video_capture = cv2.VideoCapture(0)
while True:
# Get frame from video
ret, frame = video_capture.read()
# Define grey for face box
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detect faces
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
# Append rectangle to each face in a frame
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Show frame as video stream
cv2.imshow('Video', frame)
# Run program until user enters 'q'
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# If program exists while loop, release video capture and close all windows
video_capture.release()
cv2.destroyAllWindows()