项目中需要实现人脸登陆功能，实现思路为在前端检测人脸，把人脸照片发送到后端识别，返回用户token登陆成功
前端调用摄像头使用tracking.js检测视频流中的人脸，检测到人脸后拍照上传后端。
后端使用face_recognition人脸识别库，使用Flask提供restfulAP供前端调用
实现效果如下图：
登陆界面：
摄像头检测人脸界面：
前端代码如下：
<template> <div> <h1>{{FaceisDetected}}</h1> <!-- <p>{{FaceisDetected}}</p> --> <div> <div> <video ref="videoDom" preload autoplay loop muted></video> <canvas ref="canvasDOM"></canvas> <div></div> </div> <div> <!-- <p>Image taken</p> --> <div :class="`img-item img-item-${index}`" v-for="(image, index) in images" :key="`img-wrp-${index}`" :style="`background-image: url('${image}')`" ></div> </div> </div> </div> </template> export default { name: 'facelogin', data() { return { count: 0, isdetected: '请您保持脸部在画面中央', videoEl: {}, canvasEL: {}, images: [], trackCcv: false, trackTracking: false, autoCaptureTrackTraking: false, userMediaConstraints: { audio: false, video: { // ideal（应用最理想的） width: { min: 320, ideal: 1280, max: 1920 }, height: { min: 240, ideal: 720, max: 1080 }, // frameRate受限带宽传输时，低帧率可能更适宜 frameRate: { min: 15, ideal: 30, max: 60 }, // 摄像头翻转 facingMode: 'user' } } } }, computed: { FaceisDetected() { return this.isdetected } }, created() { this.changeView() }, mounted() { // The getUserMedia interface is used for handling camera input. // Some browsers need a prefix so here we're covering all the options navigator.getMedia = navigator.getUserMedia || navigator.webkitGetUserMedia || navigator.mozGetUserMedia || navigator.msGetUserMedia this.init() }, methods: { async init() { this.videoEl = this.$refs.videoDom this.canvasEL = this.$refs.canvasDOM await navigator.mediaDevices .getUserMedia(this.userMediaConstraints) .then(this.getMediaStreamSuccess) .catch(this.getMediaStreamError) await this.onPlay() }, async onPlay() { debugHelper.log('onPlay') this.onTrackTracking() }, changeView() { this.setTitle('刷脸登陆') this.setBackDisabled(false) this.setBackIcon('arrow_back') msgbus.vm.setBottomNavVisible(false) msgbus.vm.setBottomBtnVisible(false) msgbus.vm.setMsgInputVisible({ value: false }) }, onTrackTracking() { const context = this const video = this.videoEl const canvas = this.canvasEL const canvasContext = canvas.getContext('2d') let tracker = new tracking.ObjectTracker('face') video.pause() video.src = '' tracker.setInitialScale(4) tracker.setStepSize(2) tracker.setEdgesDensity(0.1) tracking.track('#video_cam', tracker, { camera: true }) tracker.on('track', function(event) { const { autoCaptureTrackTraking } = context canvasContext.clearRect(0, 0, canvas.width, canvas.height) event.data.forEach(function({ x, y, width, height }) { canvasContext.strokeStyle = '#a64ceb' canvasContext.strokeRect(x, y, width, height) canvasContext.font = '11px Helvetica' canvasContext.fillStyle = '#fff' }) if (!isEmpty(event.data) && context.count <= 10) { if (context.count < 0) context.count = 0 context.count += 1 //debugHelper.log(context.count) if (context.count > 10) { context.isdetected = '已检测到人脸，正在登录' //context.$router.push({ name: 'pwdlogin' }) } } else { context.count -= 1 if (context.count < 0) context.isdetected = '请您保持脸部在画面中央' //this.isdetected = '已检测到人脸，正在登录' } }) }, onDownloadFile(item) { const link = document.createElement('a') link.href = item link.download = `cahyo-${new Date().toISOString()}.png` link.click() link.remove() }, onTakeCam() { const canvas = document.createElement('canvas') const video = this.$el.querySelector('#video_cam') const canvasContext = canvas.getContext('2d') if (video.videoWidth && video.videoHeight) { const isBiggerW = video.videoWidth > video.videoHeight const fixVidSize = isBiggerW ? video.videoHeight : video.videoWidth let offsetLeft = 0 let offsetTop = 0 if (isBiggerW) offsetLeft = (video.videoWidth - fixVidSize) / 2 else offsetTop = (video.videoHeight - fixVidSize) / 2 // make canvas size 300px canvas.width = canvas.height = 300 const { width, height } = canvas canvasContext.drawImage( video, offsetLeft, offsetTop, fixVidSize, fixVidSize, 0, 0, width, height ) const image = canvas.toDataURL('image/png') this.images.push(image) } }, onDetectFace(param, index) { const imgItem = document.querySelector(`.img-item-${index}`) const image = new Image() image.src = param const tracker = new tracking.ObjectTracker('face') tracker.setStepSize(1.7) tracking.track(image, tracker) tracker.on('track', function(event) { event.data.forEach(function(rect) { window.plot(rect.x, rect.y, rect.width, rect.height) }) }) window.plot = function(x, y, w, h) { const rect = document.createElement('div') document.querySelector(`.img-item-${index}`).appendChild(rect) rect.classList.add('rect') rect.style.width = w + 'px' rect.style.height = h + 'px' rect.style.left = x + 'px' rect.style.top = y + 'px' rect.style.border = '2px solid yellow' rect.style.position = 'absolute' } }, getMediaStreamSuccess(stream) { window.stream = stream // make stream available to browser console this.videoEl.srcObject = stream debugHelper.log('getMediaStreamSuccess1') //this.$store.commit('setVideoCanvasObject', this.videoEl) debugHelper.log('getMediaStreamSuccess2') }, // 视频媒体流失败 getMediaStreamError(error) { alert('视频媒体流获取错误' + error) }, // 结束媒体流 stopMediaStreamTrack() { clearInterval(this.timeInterval) if (typeof window.stream === 'object') { this.videoEl.srcObject = null //this.$store.commit('setVideoCanvasObject', '') window.stream.getTracks().forEach(track => track.stop()) } },
总结