Springboot实现人脸识别与WebSocket长连接的实现"/>
Springboot实现人脸识别与WebSocket长连接的实现
0.什么是WebSocket,由于普通的请求是间断式发送的,如果要同一时间发生大量的请求,必然导致响应速度慢(因为根据tcp协议要经过三层握手,如果不持续发送,就会导致n多次握手,关闭连接,打开连接)
1.业务需求: 由于我需要使用java来处理视频的问题,视频其实就是图片,相当于每张图片就是帧,不停发送帧去实现人脸失败,然后返回处理结果,(支付宝刷脸支付也是同样的道理)
2.前端建立WebSocket()对象,onMessage函数监听返回的结果
<!DOCTYPE html>
<html>
<head><title>视频帧捕获</title>
</head>
<body><video id="videoElement" autoplay></video><canvas id="canvasElement" style="display: none;"></canvas><script>//如果是https协议的话,就需要改为 wssvar socket = new WebSocket("ws://localhost:8080/facedetect");const video = document.getElementById('videoElement');const canvas = document.getElementById('canvasElement');const context = canvas.getContext('2d');socket.onopen = function() {console.log("xxxx");// 每1秒发送一次视频帧数据,必须要在这里写定时器,因为打开连接后才能发送请求,不然每次都会报Websocket close的错误setInterval(captureFrame,10000)};socket.onmessage = function(event) {var result = event.data;// 处理服务器返回的结果console.log(result);//打印出结果};socket.onclose = function(event) {console.log("WebSocket已关闭");};socket.onerror = function(event) {console.error('WebSocket错误:', event);};navigator.mediaDevices.getUserMedia({ video: true }).then(stream => {video.srcObject = stream;}).catch(error => {console.error('无法访问摄像头:', error);});function captureFrame() {context.drawImage(video, 0, 0, canvas.width, canvas.height);const imageDataUrl = canvas.toDataURL('image/jpeg', 0.5);console.log(imageDataUrl) socket.send(imageDataUrl);// 将数据URL发送到WebSocket服务器}// 每隔一段时间捕获一帧并发送到Servlet</script>
</body>
</html>
3.后端写配置类,配置websocket的路径
@Configuration
@EnableWebSocket
public class WebSocketConfig implements WebSocketConfigurer {@Overridepublic void registerWebSocketHandlers(WebSocketHandlerRegistry registry) {//录入人脸数据页面registry.addHandler(myHandler(), "/face").setAllowedOrigins("*");//人脸识别页面registry.addHandler(myHandler1(), "/facedetect").setAllowedOrigins("*");}@Beanpublic WebSocketHandler myHandler() {return new FaceController();}@Beanpublic WebSocketHandler myHandler1() {return new FaceController1();}
}
4.写controller
//人脸录入的controller
@Controller
@RequestMapping("/face")
@CrossOrigin
public class FaceController extends TextWebSocketHandler {private WebSocketSession session;// 处理WebSocket连接请求@Overridepublic void afterConnectionEstablished(WebSocketSession session) throws Exception {System.out.println("WebSocket连接已建立");// 保存WebSocket会话this.session = session;}// 处理WebSocket文本消息@Overrideprotected void handleTextMessage(WebSocketSession session, TextMessage message) throws Exception {String text = message.getPayload();System.out.println(text);text = text.replaceFirst("^data:image/[^;]+;base64,?\\s*", "");text = text.replaceAll("[^A-Za-z0-9+/=]", "");System.out.println(text);byte[] imageBytes = Base64.getDecoder().decode(text);if (imageBytes != null) {try {// 读取字节数组并返回BufferedImage对象ByteArrayInputStream bis = new ByteArrayInputStream(imageBytes);BufferedImage bufferedImage = ImageIO.read(bis);if (bufferedImage != null) {// 示例：显示图像宽度和高度int width = bufferedImage.getWidth();int height = bufferedImage.getHeight();System.out.println("图像宽度：" + width);System.out.println("图像高度：" + height);//录入人脸Employee e1 = HRService.addEmp(UUID.randomUUID().toString().substring(0,10), bufferedImage);ImageService.saveFaceImage(bufferedImage, e1.getCode());// 保存员工照片文件System.out.println(e1.getCode());// 在这里可以对BufferedImage对象进行其他操作} else {System.out.println("无法读取图像");}} catch (Exception e) {e.printStackTrace();}} else {System.out.println("无效的base64数据");}}// 根据接收到的文本消息进行相应的处理}
//人脸检测的控制器
@Controller
@RequestMapping("/facedetect")
@CrossOrigin
public class FaceController1 extends TextWebSocketHandler {
private WebSocketSession session;// 处理WebSocket连接请求@Overridepublic void afterConnectionEstablished(WebSocketSession session) throws Exception {System.out.println("WebSocket连接已建立");// 保存WebSocket会话this.session = session;}// 处理WebSocket文本消息@Overrideprotected void handleTextMessage(WebSocketSession session, TextMessage message) throws Exception {System.out.println("detect");String text = message.getPayload();System.out.println(text);text = text.replaceFirst("^data:image/[^;]+;base64,?\\s*", "");text = text.replaceAll("[^A-Za-z0-9+/=]", "");System.out.println(text);byte[] imageBytes = Base64.getDecoder().decode(text);if (imageBytes != null) {try {// 读取字节数组并返回BufferedImage对象ByteArrayInputStream bis = new ByteArrayInputStream(imageBytes);BufferedImage bufferedImage = ImageIO.read(bis);if (bufferedImage != null) {FaceEngineService.loadAllFaceFeature();FaceFeature faceFeature = FaceEngineService.getFaceFeature(bufferedImage);// 获取当前帧中出现的人脸对应的特征码String code = FaceEngineService.detectFace(faceFeature);System.out.println(code);if (code != null) {// 如果特征码不为null，表明画面中存在某员工的人脸Employee e = HRService.getEmp(code);// 根据特征码获取员工对象HRService.addClockInRecord(e);// 为此员工添加打卡记录// 文本域添加提示信息session.sendMessage(new TextMessage("打卡成功"));}// 在这里可以对BufferedImage对象进行其他操作} else {session.sendMessage(new TextMessage("打卡成功"));}} catch (Exception e) {e.printStackTrace();}} else {System.out.println("无效的base64数据");}}// 根据接收到的文本消息进行相应的处理}
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