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script.js
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const video = document.getElementById("video");
Promise.all([
faceapi.nets.ssdMobilenetv1.loadFromUri("/models"),
faceapi.nets.faceRecognitionNet.loadFromUri("/models"),
faceapi.nets.faceLandmark68Net.loadFromUri("/models"),
]).then(startWebcam);
function startWebcam() {
navigator.mediaDevices
.getUserMedia({
video: true,
audio: true,
})
.then((stream) => {
video.srcObject = stream;
})
.catch((error) => {
console.error(error);
});
}
function getLabeledFaceDescriptions() {
const labels = ["MESSI","Santhosh"];
return Promise.all(
labels.map(async (label) => {
const descriptions = [];
for (let i = 1; i <= 2; i++) {
const img = await faceapi.fetchImage(`./labels/${label}/${i}.jpg`);
const detections = await faceapi
.detectSingleFace(img)
.withFaceLandmarks()
.withFaceDescriptor();
descriptions.push(detections.descriptor);
}
return new faceapi.LabeledFaceDescriptors(label, descriptions);
})
);
}
video.addEventListener("play", async () => {
const labeledFaceDescriptors = await getLabeledFaceDescriptions();
const faceMatcher = new faceapi.FaceMatcher(labeledFaceDescriptors);
const canvas = faceapi.createCanvasFromMedia(video);
document.body.append(canvas);
const displaySize = { width: video.width, height: video.height };
faceapi.matchDimensions(canvas, displaySize);
setInterval(async () => {
const detections = await faceapi
.detectAllFaces(video)
.withFaceLandmarks()
.withFaceDescriptors();
const resizedDetections = faceapi.resizeResults(detections, displaySize);
canvas.getContext("2d").clearRect(0, 0, canvas.width, canvas.height);
const results = resizedDetections.map((d) => {
return faceMatcher.findBestMatch(d.descriptor);
});
results.forEach((result, i) => {
const box = resizedDetections[i].detection.box;
const drawBox = new faceapi.draw.DrawBox(box, {
label: result,
});
drawBox.draw(canvas);
});
}, 100);
});