def test_face_detector_no_face(self):
fd.set_classifiers(c1, c2, c3)
face_box = fd.detect_face(self.test_image_face)
x1 = face_box.x
y1 = face_box.y
x2 = face_box.width + x1
y2 = face_box.height + y1
self.assertTrue(face_box is None, "Image does not contain a face!")
def test_multiple_faces(self, faces):
fd.set_classifiers(c1, c2, c3)
for image in faces:
index = 0
face_box = fd.detect_face(image)
if face_box is not None:
x1 = face_box.x
y1 = face_box.y
x2 = face_box.width + x1
y2 = face_box.height + y1
self.assertTrue(face_box is not None, "Image %d contains a face between (%d,%d) and (%d,%d)"%(index,x1,y1,x2,y2))
else:
self.assertTrue(face_box is None, "Image %d contains no face!"%s(index))
index+=1
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()
from face_detector import Face_Detector
import imutils
ap = argparse.ArgumentParser()
ap.add_argument('-f',
'--face',
default='cascade/haarcascade_frontalface_default.xml',
help='path to face file')
ap.add_argument('-e',
'--eyes',
default='cascade/haarcascade_eye.xml',
help='path to eyes file')
ap.add_argument('-i', '--video', help='path to optional video file')
args = vars(ap.parse_args())
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
from face_detector import Face_Detector Face_Detector()