import cv2
import argparse
from face_detector import Face_Detector
ap = argparse.ArgumentParser()
ap.add_argument('-f',
'--face',
default='cascade/haarcascade_frontalface_default.xml',
help='path to the face cascade')
ap.add_argument('-i', '--image', required=True, help='path to the image')
args = vars(ap.parse_args())
image = cv2.imread(args['image'])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.equalizeHist(gray)
fd = Face_Detector(args['face'])
faces = fd.detect(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
print("%d face(s) detected" % (len(faces)))
for (x, y, w, h) in faces:
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Faces", image)
cv2.waitKey(0)
cv2.destroyAllWindows()
fd = Face_Detector(args['face'], args['eyes'])
if not args['video']:
camera = cv2.VideoCapture(0)
else:
camera = cv2.VideoCapture(args['video'])
if not camera.isOpened:
print("Failed to load the frames. Exiting ....")
while True:
ret, frame = camera.read()
if frame is None and not ret:
break
frame = imutils.resize(frame, width=500)
#image = cv2.resize(frame, (480,480))
result = fd.detect(frame)
cv2.imshow("faces", result)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print("exiting....")
camera.release()
cv2.destroyAllWindows()