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vue实现肢体识别

2026-01-08 04:47:58VUE

Vue 中实现肢体识别的方法

在 Vue 项目中实现肢体识别通常需要结合第三方库或 API，例如 TensorFlow.js、MediaPipe 或 OpenCV。以下是几种常见的实现方式：

使用 TensorFlow.js 和 PoseNet

TensorFlow.js 是一个 JavaScript 机器学习库，PoseNet 是其提供的预训练模型，可用于人体姿态估计。

安装 TensorFlow.js 和 PoseNet：

npm install @tensorflow/tfjs @tensorflow-models/posenet

在 Vue 组件中加载模型并检测姿态：

import * as tf from '@tensorflow/tfjs';
import * as posenet from '@tensorflow-models/posenet';

export default {
  data() {
    return {
      videoElement: null,
      poses: null,
    };
  },
  async mounted() {
    await this.loadModel();
  },
  methods: {
    async loadModel() {
      const net = await posenet.load();
      this.videoElement = document.getElementById('video');
      const stream = await navigator.mediaDevices.getUserMedia({ video: true });
      this.videoElement.srcObject = stream;
      this.detectPose(net);
    },
    async detectPose(net) {
      const pose = await net.estimateSinglePose(this.videoElement);
      this.poses = pose;
      requestAnimationFrame(() => this.detectPose(net));
    },
  },
};

使用 MediaPipe

MediaPipe 是 Google 提供的跨平台框架，支持实时肢体识别。其 Pose 解决方案可以直接在浏览器中运行。

安装 MediaPipe：

npm install @mediapipe/pose

在 Vue 组件中使用：

import { Pose } from '@mediapipe/pose';
import { Camera } from '@mediapipe/camera_utils';

export default {
  data() {
    return {
      pose: null,
    };
  },
  mounted() {
    this.initPoseDetection();
  },
  methods: {
    initPoseDetection() {
      this.pose = new Pose({
        locateFile: (file) => `https://cdn.jsdelivr.net/npm/@mediapipe/pose/${file}`,
      });
      this.pose.setOptions({
        modelComplexity: 1,
        smoothLandmarks: true,
      });
      this.pose.onResults(this.onResults);
      const camera = new Camera(document.getElementById('video'), {
        onFrame: async () => {
          await this.pose.send({ image: document.getElementById('video') });
        },
        width: 640,
        height: 480,
      });
      camera.start();
    },
    onResults(results) {
      console.log(results.poseLandmarks);
    },
  },
};

使用 OpenCV.js

OpenCV.js 是 OpenCV 的 JavaScript 版本，可以结合 Haar 级联或 DNN 模型实现肢体识别。

加载 OpenCV.js 并检测肢体：

<template>
  <div>
    <video id="video" width="640" height="480" autoplay></video>
    <canvas id="canvas" width="640" height="480"></canvas>
  </div>
</template>

<script>
export default {
  mounted() {
    this.loadOpenCV();
  },
  methods: {
    loadOpenCV() {
      const script = document.createElement('script');
      script.src = 'https://docs.opencv.org/4.5.5/opencv.js';
      script.onload = this.initOpenCV;
      document.body.appendChild(script);
    },
    initOpenCV() {
      const video = document.getElementById('video');
      navigator.mediaDevices.getUserMedia({ video: true })
        .then((stream) => {
          video.srcObject = stream;
          this.processVideo();
        });
    },
    processVideo() {
      const video = document.getElementById('video');
      const canvas = document.getElementById('canvas');
      const ctx = canvas.getContext('2d');
      const processFrame = () => {
        ctx.drawImage(video, 0, 0, canvas.width, canvas.height);
        const src = cv.imread(canvas);
        // 肢体识别处理逻辑
        cv.imshow(canvas, src);
        requestAnimationFrame(processFrame);
      };
      processFrame();
    },
  },
};
</script>