要在web端实现基于face-api.js和facenet的人脸识别,你需要遵循以下步骤:
- 引入face-api.js库。
- 加载模型。
- 访问用户摄像头。
- 实时检测视频中的脸部。
- 将检测到的脸部与数据库中的面孔进行匹配。
以下是实现这些步骤的示例代码:
<!DOCTYPE html>
<html>
<head>
<title>Face Recognition</title>
<script src="https://cdn.jsdelivr.net/npm/face-api.js/dist/face-api.min.js"></script>
</head>
<body>
<video id="videoElement" width="720" height="560" autoplay muted></video>
<script>
const video = document.getElementById('videoElement');
Promise.all([
faceapi.nets.tinyFaceDetector.loadFromUri('/models'),
faceapi.nets.faceLandmark68Net.loadFromUri('/models'),
faceapi.nets.faceRecognitionNet.loadFromUri('/models'),
faceapi.loadLabeledImages('/labeled_images')
]).then(startVideo);
function startVideo() {
navigator.mediaDevices.getUserMedia({ video: {} })
.then((stream) => {
video.srcObject = stream;
}).catch(err => console.error(err));
}
setInterval(async () => {
const displaySize = { width: video.width, height: video.height };
faceapi.resizeCanvas(displaySize);
const resized = true;
const detections = await faceapi.detectAllFaces(video, new faceapi.TinyFaceDetectorOptions()).withFaceLandmarks().withFaceDescriptors();
const faceImages = detections.map(detection => {
const img = new Image(detection.width, detection.height);
img.src = detection.getImageData(resized ? displaySize : new faceapi.Point(detection.x, detection.y), resized ? displaySize : new faceapi.Rect(0, 0, detection.width, detection.height));
return img;
});
const labeledFaceImages = await Promise.all(faceImages.map(async (img, i) => {
const descriptors = await faceapi.computeFaceDescriptor(img);
let label = 'Unknown';
const bestMatch = await faceapi.findBestMatch(descriptors, ['Class1', 'Class2', ...]);
if (bestMatch._