face_detection_dlib.py

import cv2
import dlib

PREDICTOR_PATH = "shape_predictor_68_face_landmarks.dat"

# 使用dlib自带的frontal_face_detector作为人脸提取器
detector = dlib.get_frontal_face_detector()

# 使用官方模型构建特征提取器
predictor = dlib.shape_predictor(PREDICTOR_PATH)

if __name__ == '__main__':

    #框住人脸的矩形边框颜色
    color = (0, 255, 0)

    #捕获指定摄像头的实时视频流
    cap = cv2.VideoCapture(0)

    #循环检测识别人脸
    while True:
        _, frame = cap.read()   #读取一帧视频

        # 图像灰化，降低计算复杂度
        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        # 使用detector进行人脸检测 rects为返回的结果
        rects = detector(frame_gray, 1)

        if len(rects) > 0:
            for k, d in enumerate(rects):
                cv2.rectangle(frame, (d.left(), d.top()), (d.right(), d.bottom()), (255, 255, 255))
                shape = predictor(frame, d)
                for i in range(68):
                    cv2.circle(frame, (shape.part(i).x, shape.part(i).y), 5, (0, 255, 0), -1, 8)
                    cv2.putText(frame, str(i), (shape.part(i).x, shape.part(i).y), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
                                (255, 255, 255))

        cv2.imshow("find me", frame)

        #等待10毫秒看是否有按键输入
        k = cv2.waitKey(10)
        #如果输入q则退出循环
        if k & 0xFF == ord('q'):
            break

    #释放摄像头并销毁所有窗口
    cap.release()
    cv2.destroyAllWindows()