def register():
global faces_db
upload_file = request.files['image']
user_name = request.values.get("name")
if upload_file:
try:
image = cv2.imdecode(np.frombuffer(upload_file.read(), np.uint8), cv2.IMREAD_UNCHANGED)
faces, landmarks = mtcnn_detector.detect(image)
if faces.shape[0] is not 0:
faces_sum = 0
bbox = []
points = []
for i, face in enumerate(faces):
if round(faces[i, 4], 6) > 0.95:
bbox = faces[i, 0:4]
points = landmarks[i, :].reshape((5, 2))
faces_sum += 1
if faces_sum == 1:
nimg = face_preprocess.preprocess(image, bbox, points, image_size='112,112')
cv2.imencode('.png', nimg)[1].tofile('face_db/%s.png' % user_name)
# 更新人脸库
faces_db = load_faces(face_sess, inputs_placeholder, embeddings)
return str({"code": 0, "msg": "success"})
return str({"code": 3, "msg": "image not or much face"})
except:
return str({"code": 2, "msg": "this file is not image or not face"})
else:
return str({"code": 1, "msg": "file is None"})
from flask_cors import CORS
from utils import face_preprocess
from utils.utils import feature_compare, load_mtcnn, load_faces, load_mobilefacenet, list_to_json
app = Flask(__name__)
# 允许跨越访问
CORS(app)
# 人脸识别阈值
VERIFICATION_THRESHOLD = config.VERIFICATION_THRESHOLD
# 检测人脸检测模型
mtcnn_detector = load_mtcnn()
# 加载人脸识别模型
face_sess, inputs_placeholder, embeddings = load_mobilefacenet()
# 加载已经注册的人脸
faces_db = load_faces(face_sess, inputs_placeholder, embeddings)
# 人脸识别
def recognition_face(frame):
try:
faces, landmarks = mtcnn_detector.detect(frame)
if faces.shape[0] is not 0:
faces_sum = 0
for i, face in enumerate(faces):
if round(faces[i, 4], 6) > 0.95:
faces_sum += 1
if faces_sum == 0:
return
# 人脸信息
info_bbox = np.zeros((faces_sum, 4))