Vue+tracking.js如何实现前端人脸检测功能-成都创新互联网站建设

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Vue+tracking.js如何实现前端人脸检测功能

这篇文章主要为大家展示了Vue+tracking.js如何实现前端人脸检测功能,内容简而易懂,希望大家可以学习一下,学习完之后肯定会有收获的,下面让小编带大家一起来看看吧。

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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:

Vue+tracking.js如何实现前端人脸检测功能

摄像头检测人脸界面:

Vue+tracking.js如何实现前端人脸检测功能

前端代码如下:



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())
 }
 },

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