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Copy pathapp.js
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154 lines (124 loc) · 4.62 KB
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let faceDetectionSupported = false;
let animationTimer = null;
let numberOfFaces = 0;
let emojiBoxes = [];
// Our <video> element
const video = document.getElementById('webcam');
// Mapping expression to emoji
const emojiMap = {
happy: '😄',
sad: '😭',
surprised: '😯',
angry: '😡',
fearful: '😱',
neutral: '🎃',
disgusted: '🤢'
}
// Instantiate our preferred face detector
const faceDetector = new faceapi.TinyFaceDetectorOptions();
function showEmoji(index, expression, x = 0, y = 0, height, width) {
// Get emoji Unicode for our expression
const emoji = emojiMap[expression] || emojiMap.neutral;
// Detected face is roughly 15% of height lower than we want
const topAdjustment = height * .15;
// Emoji size is roughly 13% of the height
const fontSize = height * .13;
// Look up an existing emojiBox...
let emojiBox = emojiBoxes[index];
// ...or create a new one...
if (!emojiBox) {
emojiBox = document.createElement('span');
emojiBox.classList.add('emojibox');
document.body.appendChild(emojiBox);
// ...and remember it
emojiBoxes[index] = emojiBox;
}
// Render the emojiBox
emojiBox.innerHTML = emoji;
emojiBox.style.top = `${y - topAdjustment}px`;
emojiBox.style.left = `${x}px`;
emojiBox.style.width = `${width}px`;
emojiBox.style.height = `${height}px`;
emojiBox.style.fontSize = `${fontSize}vh`;
}
function cleanupBoxes(numberOfBoxes) {
// If we're storing more boxes than number of detection boxes...
if (emojiBoxes.length > numberOfBoxes) {
// ...loop through the difference...
for (let i = numberOfBoxes; i < emojiBoxes.length; i++) {
const emojiBox = emojiBoxes[i];
// ...and remove them from the DOM
emojiBox.remove();
}
// Forget extra boxes from storage
emojiBoxes = emojiBoxes.slice(0, numberOfBoxes);
}
}
function animateFace() {
// Animation loop
animationTimer = requestAnimationFrame(async () => {
if (faceDetectionSupported) {
// Detect all possible faces
const rawFaces = await faceapi.detectAllFaces(video, faceDetector).withFaceLandmarks().withFaceExpressions();
// Clean-up extra emoji boxes if people left
numberOfFaces = rawFaces.length;
cleanupBoxes(numberOfFaces);
if (numberOfFaces) {
const videoSize = video.getBoundingClientRect();
// face-api can resize detection boxes for our <video> size
const faces = faceapi.resizeResults(rawFaces, {
height: videoSize.height,
width: videoSize.width
});
// Loop through our faces and...
faces.forEach((face, index) => {
// Pick the most likely expression
const emotion = face.expressions.asSortedArray()[0];
// Only use that emotion if it's pretty likely accurate
const expression = emotion.probability > .5 ? emotion.expression : '';
// Get dimensions of the face detection
const box = face.detection.box;
// Show the Emoji box
showEmoji(index, expression, box.left + videoSize.left, box.top, box.height, box.width);
});
}
}
// Do it again
animateFace();
});
}
function startVideo() {
if (navigator.mediaDevices) {
navigator.mediaDevices.getUserMedia({
// We don't need audio
audio: false,
// Prefer user-facing camera
video: { facingMode: 'user' }
})
// Pass the stream to our <video>
.then(stream => video.srcObject = stream)
.catch(err => console.error(err));
}
}
function everythingWorked() {
faceDetectionSupported = true;
startVideo();
}
function somethingFailed(reason) {
console.error(reason);
faceDetectionSupported = false;
startVideo();
}
// <video> event listeners
video.addEventListener('play', animateFace);
video.addEventListener('pause', () => cancelAnimationFrame(animationTimer));
video.addEventListener('error', () => cancelAnimationFrame(animationTimer));
// Load all our ML models to kick things off
Promise.all([
faceapi.nets.tinyFaceDetector.loadFromUri('./models'),
faceapi.nets.faceRecognitionNet.loadFromUri('./models'),
faceapi.nets.faceLandmark68Net.loadFromUri('./models'),
faceapi.nets.faceExpressionNet.loadFromUri('./models')
])
.then(everythingWorked)
.catch(somethingFailed);