<!DOCTYPE html>
<html>
<head>
<script src="face-api.js"></script>
<script src="js/commons.js"></script>
<script src="js/drawing.js"></script>
<script src="js/faceDetectionControls.js"></script>
<script src="js/bbt.js"></script>
<link rel="stylesheet" href="styles.css">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/css/materialize.css">
<script type="text/javascript" src="https://code.jquery.com/jquery-2.1.1.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/materialize/0.100.2/js/materialize.min.js"></script>
</head>
<body>
<div id="navbar"></div>
<div class="center-content page-container">
<div class="progress" id="loader">
<div class="indeterminate"></div>
</div>
<div style="position: relative" class="margin">
<video onloadedmetadata="onPlay(this)" id="inputVideo" autoplay muted></video>
<canvas id="overlay" />
</div>
<div class="row side-by-side">
<!-- face_detector_selection_control -->
<div id="face_detector_selection_control" class="row input-field" style="margin-right: 20px;">
<select id="selectFaceDetector">
<option value="ssd_mobilenetv1">SSD Mobilenet V1</option>
<option value="tiny_face_detector">Tiny Face Detector</option>
<option value="mtcnn">MTCNN</option>
</select>
<label>Select Face Detector</label>
</div>
<!-- face_detector_selection_control -->
<!-- fps_meter -->
<div id="fps_meter" class="row side-by-side">
<div>
<label for="time">Time:</label>
<input disabled value="-" id="time" type="text" class="bold">
<label for="fps">Estimated Fps:</label>
<input disabled value="-" id="fps" type="text" class="bold">
</div>
</div>
<!-- fps_meter -->
</div>
<!-- ssd_mobilenetv1_controls -->
<span id="ssd_mobilenetv1_controls">
<div class="row side-by-side">
<div class="row">
<label for="minConfidence">Min Confidence:</label>
<input disabled value="0.5" id="minConfidence" type="text" class="bold">
</div>
<button
class="waves-effect waves-light btn"
onclick="onDecreaseMinConfidence()"
>
<i class="material-icons left">-</i>
</button>
<button
class="waves-effect waves-light btn"
onclick="onIncreaseMinConfidence()"
>
<i class="material-icons left">+</i>
</button>
</div>
</span>
<!-- ssd_mobilenetv1_controls -->
<!-- tiny_face_detector_controls -->
<span id="tiny_face_detector_controls">
<div class="row side-by-side">
<div class="row input-field" style="margin-right: 20px;">
<select id="inputSize">
<option value="" disabled selected>Input Size:</option>
<option value="128">128 x 128</option>
<option value="160">160 x 160</option>
<option value="224">224 x 224</option>
<option value="320">320 x 320</option>
<option value="416">416 x 416</option>
<option value="512">512 x 512</option>
<option value="608">608 x 608</option>
</select>
<label>Input Size</label>
</div>
<div class="row">
<label for="scoreThreshold">Score Threshold:</label>
<input disabled value="0.5" id="scoreThreshold" type="text" class="bold">
</div>
<button
class="waves-effect waves-light btn"
onclick="onDecreaseScoreThreshold()"
>
<i class="material-icons left">-</i>
</button>
<button
class="waves-effect waves-light btn"
onclick="onIncreaseScoreThreshold()"
>
<i class="material-icons left">+</i>
</button>
</div>
</span>
<!-- tiny_face_detector_controls -->
<!-- mtcnn_controls -->
<span id="mtcnn_controls">
<div class="row side-by-side">
<div class="row">
<label for="minFaceSize">Minimum Face Size:</label>
<input disabled value="20" id="minFaceSize" type="text" class="bold">
</div>
<button
class="waves-effect waves-light btn"
onclick="onDecreaseMinFaceSize()"
>
<i class="material-icons left">-</i>
</button>
<button
class="waves-effect waves-light btn"
onclick="onIncreaseMinFaceSize()"
>
<i class="material-icons left">+</i>
</button>
</div>
</span>
<!-- mtcnn_controls -->
<script>
let forwardTimes = []
let faceMatcher = null
function updateTimeStats(timeInMs) {
forwardTimes = [timeInMs].concat(forwardTimes).slice(0, 30)
const avgTimeInMs = forwardTimes.reduce((total, t) => total + t) / forwardTimes.length
$('#time').val(`${Math.round(avgTimeInMs)} ms`)
$('#fps').val(`${faceapi.round(1000 / avgTimeInMs)}`)
}
async function onPlay() {
const videoEl = $('#inputVideo').get(0)
if (videoEl.paused || videoEl.ended || !isFaceDetectionModelLoaded())
return setTimeout(() => onPlay())
const options = getFaceDetectorOptions()
const ts = Date.now()
const result = await faceapi.detectSingleFace(videoEl, options).withFaceLandmarks()
updateTimeStats(Date.now() - ts)
if (result) {
//drawDetections(videoEl, $('#overlay').get(0), [result])
drawLandmarks(videoEl, $('#overlay').get(0), [result], true)
}
setTimeout(() => onPlay())
}
async function run() {
// load face detection model
await changeFaceDetector(TINY_FACE_DETECTOR)
await faceapi.loadFaceRecognitionModel('/')
await faceapi.loadFaceLandmarkModel('/')
changeInputSize(224)
// try to access users webcam and stream the images
// to the video element
faceMatcher = await createBbtFaceMatcher(1)
const stream = await navigator.mediaDevices.getUserMedia({video: {}})
const videoEl = $('#inputVideo').get(0)
videoEl.srcObject = stream
updateResults();
}
async function updateResults() {
if(!isFaceDetectionModelLoaded())
{
return
}
const videoEl = $('#inputVideo').get(0)
//receive full description of faces from input image
const options = getFaceDetectorOptions()
const results = await faceapi
.detectAllFaces(videoEl, options)
.withFaceLandmarks()
.withFaceDescriptors()
drawFaceRecognitionResults(results)
}
function drawFaceRecognitionResults(results)
{
const canvas = $('#inputVideo').get(0)
resizedResults = resizeCanvasAndResults($('#inputVideo').get(0), canvas, results)
const boxesWithText = resizedResults.map(({ detection, descriptor }) =>
new faceapi.BoxWithText(
detection.box,
faceMatcher.findBestMatch(descriptor).toString()//for string name
)
)
//draw bounding box
faceapi.drawDetection(canvas, boxesWithText)
}
$(document).ready(function () {
renderNavBar('#navbar', 'webcam_face_detection')
initFaceDetectionControls()
run()
})
</script>
</body>
</html>