老板检测系统，python+opencv+dlib人脸识别

 python人脸识别程序

人脸提取代码

# -*- coding: utf-8 -*-

import dlib
import cv2
import numpy as np
import glob
from imageio import imread

# 自己的脸
labeled = glob.glob('C:/Users/35419/Desktop/taizhimin/*.jpg')
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('model/shape_predictor_68_face_landmarks.dat')
facerec = dlib.face_recognition_model_v1('model/dlib_face_recognition_resnet_model_v1.dat')
camera = cv2.VideoCapture(0)
# 摄像头分辨率调低
camera.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
camera.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
labeled_data = {}
for path in labeled:
    img = imread(path)
    dets = detector(img, 1)
    if dets:
        shape = predictor(img, dets[0])
        face_vector = facerec.compute_face_descriptor(img, shape)
        labeled_data[path] = face_vector


def distance(a, b):
    return np.linalg.norm(np.array(a) - np.array(b), ord=2)


if not camera.isOpened():
    print("cannot open camear")
    exit(0)
b = True
x = False
while True:
    ret, frame = camera.read()
    if not ret:
        continue
    cv2.imshow("Camera", frame)
    frame_new = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    # 每四贞检测一次，希望稍微快一点吧
    if b | b ^ x:
        b = x
        continue
    # 检测脸部
    dets = detector(frame_new, 1)
    if dets:
        for i, face in enumerate(dets):
            shape = predictor(frame_new, dets[0])
            face_vector = facerec.compute_face_descriptor(frame_new, shape)
            for key, value in labeled_data.items():
                d = distance(face_vector, value)
                if d < 0.4:
                    cv2.putText(frame, 'taizhimin', (0, 30), cv2.FONT_HERSHEY_SIMPLEX,
                                0.7, (255, 255, 255), 1, cv2.LINE_AA)
            cv2.rectangle(frame, (face.left(), face.top()), (face.right(), face.bottom()),
                          (0, 255, 0),
                          3)
    cv2.imshow("Camera", frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cv2.destroyAllWindows()