face-api.js 基于tensorflow.js打造的人脸识别、检测、追踪、表情检测、性别年龄检测插件

face-api.js 基于tensorflow.js打造的人脸识别、检测、追踪、表情检测、性别年龄检测插件

第一步引入bfwone

第二步执行插件，首先要加载模型

模型分为以下几种ageGenderNet,faceExpressionNet,faceLandmark68Net,faceLandmark68TinyNet,faceRecognitionNet,ssdMobilenetv1,tinyFaceDetector,mtcnn,tinyYolov2

await faceapi.nets.ssdMobilenetv1.loadFromUri('/models')
// accordingly for the other models:
// await faceapi.nets.faceLandmark68Net.loadFromUri('/models')
// await faceapi.nets.faceRecognitionNet.loadFromUri('/models')

const net = new faceapi.SsdMobilenetv1()
await net.loadFromUri('/models')

// using fetch
net.load(await faceapi.fetchNetWeights('/models/face_detection_model.weights'))

// using axios
const res = await axios.get('/models/face_detection_model.weights', { responseType: 'arraybuffer' })
const weights = new Float32Array(res.data)
net.load(weights)

<img id="myImg" src="images/example.png" />
<video id="myVideo" src="media/example.mp4" />
<canvas id="myCanvas" />

const input = document.getElementById('myImg')
// const input = document.getElementById('myVideo')
// const input = document.getElementById('myCanvas')
// or simply:
// const input = 'myImg'
const detections = await faceapi.detectAllFaces(input)