def match_face(model, pair):
global_conf = None
nparr_model = np.fromstring(model, np.uint8)
path = cv2.imdecode(nparr_model, cv2.CV_LOAD_IMAGE_COLOR)
recognizer = cv2.face.createLBPHFaceRecognizer()
# path = './train_dir/yu/yu2.jpg'
model_faces, model_labels = mtcnn.get_face(path)
print model_labels
model_faces_gray = []
for face in model_faces:
gray_image = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
model_faces_gray.append(gray_image)
recognizer.train(model_faces_gray, np.array(model_labels))
nparr_pair = np.fromstring(pair, np.uint8)
imgPath = cv2.imdecode(nparr_pair, cv2.CV_LOAD_IMAGE_COLOR)
# imgPath = './train_dir/yu/yu.jpg'
# img_pair = cv2.imread(path)
pair_faces, pair_labels = mtcnn.get_face(imgPath)
pair_faces_gray = []
for face in pair_faces:
gray_image = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
pair_faces_gray.append(gray_image)
for face in pair_faces_gray:
global global_conf
nbr_predicted, conf = recognizer.predict(face)
print "Recognized with confidence {}".format(conf)
global_conf = conf
return global_conf
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