pyqt的人脸识别 基于face_recognition库

参考文献：

1、python face_recognition实现人脸识别系统_python facerecognition检测人脸-CSDN博客

2、cv2.VideoCapture()_cv2.videocapture(0)-CSDN博客

1、camera.py文件代码如下；目录如下

import sys
from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QPushButton, QVBoxLayout
from PyQt5.QtGui import QPixmap, QImage
from PyQt5.QtCore import QTimer
import cv2
import face_recognition
import os

class VideoPlayer(QWidget):
    def __init__(self):
        super().__init__()

        self.initUI()

    def initUI(self):
        self.setWindowTitle("Video Player")
        self.setGeometry(100, 100, 800, 600)

        # 创建显示视频的标签
        self.label = QLabel(self)
        self.label.resize(640, 480)
        self.label.move(80, 40)

        # 创建按钮
        self.button = QPushButton('Play/Stop', self)
        self.button.move(350, 550)
        self.button.clicked.connect(self.toggle_video)

        # 加载已知人脸数据
        self.known_faces = {}
        for person_name in os.listdir("known_faces"):
            person_dir = os.path.join("known_faces", person_name)
            if os.path.isdir(person_dir):
                person_faces = []
                for filename in os.listdir(person_dir):
                    image_path = os.path.join(person_dir, filename)
                    image = face_recognition.load_image_file(image_path)
                    encoding = face_recognition.face_encodings(image)[0]
                    person_faces.append(encoding)
                self.known_faces[person_name] = person_faces

        # 初始化摄像头
        self.video_capture = cv2.VideoCapture(0)

        # 设置定时器，每隔33毫秒刷新一次
        self.timer = QTimer(self)
        self.timer.timeout.connect(self.next_frame)
        self.timer.start(33)

    def next_frame(self):
        # 读取视频流
        ret, frame = self.video_capture.read()

        # 转换为RGB格式
        rgb_frame = frame[:, :, ::-1]

        # 检测人脸
        face_locations = face_recognition.face_locations(rgb_frame)
        face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

        # 对比已知人脸
        for face_encoding in face_encodings:
            found = False
            for person_name, known_face_encodings in self.known_faces.items():
                matches = face_recognition.compare_faces(known_face_encodings, face_encoding, tolerance=0.4)
                if True in matches:
                    cv2.putText(frame, f" {person_name}!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
                    found = True
                    break
            if found:
                break

        # 将视频帧显示在标签中
        height, width, channel = frame.shape
        bytesPerLine = 3 * width
        qImg = QImage(frame.data, width, height, bytesPerLine, QImage.Format_RGB888)
        pixmap = QPixmap.fromImage(qImg)
        self.label.setPixmap(pixmap)

    def toggle_video(self):
        if self.timer.isActive():
            self.timer.stop()
        else:
            self.timer.start(33)

if __name__ == '__main__':
    app = QApplication(sys.argv)
    player = VideoPlayer()
    player.show()
    sys.exit(app.exec_())

2、运行效果图

原文地址：https://blog.csdn.net/weixin_44098348/article/details/137822107

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