Python人脸识别项目-人脸识别-进行人脸识别

这是最后一步进行人脸识别操作

# -*- coding: utf-8 -*
import cv2
import os

# 加载训练数据集文件
recogizer = cv2.face.LBPHFaceRecognizer_create()
recogizer.read('train/trainer.yml')  # 获取脸部特征数据文件
names = []
warningtime = 0


def face_detect_demo(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  # 转换为灰度图像
    face_detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')  # 加载分类器
    face = face_detector.detectMultiScale(gray, 1.3, 5, cv2.CASCADE_SCALE_IMAGE, (100, 100), (300, 300))
    # 进行识别，把整张人脸部分框起来
    for x, y, w, h in face:
        cv2.rectangle(img, (x, y), (x + w, y + h), color=(0, 0, 255), thickness=2)  # 矩形
        ids, confidence = recogizer.predict(gray[y:y + h, x:x + w])  # 进行预测、评分
        if confidence > 80:
            global warningtime
            warningtime += 1
            if warningtime > 100:  # 警报达到一定次数，说明不是这个人
                warningtime = 0
            cv2.putText(img, 'unkonw', (x + 10, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 255, 0), 1)
        else:
            cv2.putText(img, str(names[ids - 1]), (x + 10, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 255, 0), 1)
            # 把姓名打到人脸的框图上
    cv2.imshow('result', img)
    # print('bug:',ids)

#找名字
def name():
    path = './picture'
    imagepaths = [os.path.join(path, f) for f in os.listdir(path)]
    for imagePath in imagepaths:
        name1 = str(os.path.split(imagePath)[1].split('.', 2)[1])
        names.append(name1)


cap = cv2.VideoCapture(0)
name()
while True:
    flag, frame = cap.read()  # 获得摄像头读取到的数据(flag为返回值,frame为视频中的每一帧)
    if not flag:
        break
    face_detect_demo(frame)
    if ord(' ') == cv2.waitKey(10):  # 按空格，退出
        break
cv2.destroyAllWindows()
cap.release()
# print(names)