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bw face landmarker on white bg for Sajjad
<!-- Copyright 2023 The MediaPipe Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. -->
<html>
<head>
<meta charset="utf-8">
<meta http-equiv="Cache-control" content="no-cache, no-store, must-revalidate">
<meta http-equiv="Pragma" content="no-cache">
<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no">
<title>Face Landmarker</title>
<link href="https://unpkg.com/material-components-web@latest/dist/material-components-web.min.css" rel="stylesheet">
<script src="https://unpkg.com/material-components-web@latest/dist/material-components-web.min.js"></script>
</head>
<body>
<div id="liveView" class="videoView">
<button id="webcamButton" class="mdc-button mdc-button--raised">
<span class="mdc-button__ripple"></span>
<span class="mdc-button__label">ENABLE WEBCAM</span>
</button>
<div style="position: relative;">
<video id="webcam" autoplay playsinline></video>
<canvas class="output_canvas" id="output_canvas"></canvas>
</div>
</div>
<div class="blend-shapes">
<ul class="blend-shapes-list" id="video-blend-shapes"></ul>
</div>
</section>
</body>
</html>
// Copyright 2023 The MediaPipe Authors.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import vision from "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.3";
const { FaceLandmarker, FilesetResolver, DrawingUtils } = vision;
const demosSection = document.getElementById("demos");
const imageBlendShapes = document.getElementById("image-blend-shapes");
const videoBlendShapes = document.getElementById("video-blend-shapes");
let faceLandmarker;
let runningMode: "IMAGE" | "VIDEO" = "IMAGE";
let enableWebcamButton: HTMLButtonElement;
let webcamRunning: Boolean = false;
const videoWidth = 480;
// Before we can use HandLandmarker class we must wait for it to finish
// loading. Machine Learning models can be large and take a moment to
// get everything needed to run.
async function createFaceLandmarker() {
const filesetResolver = await FilesetResolver.forVisionTasks(
"https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.3/wasm"
);
faceLandmarker = await FaceLandmarker.createFromOptions(filesetResolver, {
baseOptions: {
modelAssetPath: `https://storage.googleapis.com/mediapipe-models/face_landmarker/face_landmarker/float16/1/face_landmarker.task`,
delegate: "GPU"
},
outputFaceBlendshapes: true,
runningMode,
numFaces: 1
});
demosSection.classList.remove("invisible");
}
createFaceLandmarker();
/********************************************************************
// Demo 1: Grab a bunch of images from the page and detection them
// upon click.
********************************************************************/
// In this demo, we have put all our clickable images in divs with the
// CSS class 'detectionOnClick'. Lets get all the elements that have
// this class.
const imageContainers = document.getElementsByClassName("detectOnClick");
// Now let's go through all of these and add a click event listener.
for (let imageContainer of imageContainers) {
// Add event listener to the child element whichis the img element.
imageContainer.children[0].addEventListener("click", handleClick);
}
// When an image is clicked, let's detect it and display results!
async function handleClick(event) {
if (!faceLandmarker) {
console.log("Wait for faceLandmarker to load before clicking!");
return;
}
if (runningMode === "VIDEO") {
runningMode = "IMAGE";
await faceLandmarker.setOptions({ runningMode });
}
// Remove all landmarks drawed before
const allCanvas = event.target.parentNode.getElementsByClassName("canvas");
for (var i = allCanvas.length - 1; i >= 0; i--) {
const n = allCanvas[i];
n.parentNode.removeChild(n);
}
// We can call faceLandmarker.detect as many times as we like with
// different image data each time. This returns a promise
// which we wait to complete and then call a function to
// print out the results of the prediction.
const faceLandmarkerResult = faceLandmarker.detect(event.target);
const canvas = document.createElement("canvas") as HTMLCanvasElement;
canvas.setAttribute("class", "canvas");
canvas.setAttribute("width", event.target.naturalWidth + "px");
canvas.setAttribute("height", event.target.naturalHeight + "px");
canvas.style.left = "0px";
canvas.style.top = "0px";
canvas.style.width = `${event.target.width}px`;
canvas.style.height = `${event.target.height}px`;
event.target.parentNode.appendChild(canvas);
const ctx = canvas.getContext("2d");
const drawingUtils = new DrawingUtils(ctx);
for (const landmarks of faceLandmarkerResult.faceLandmarks) {
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_TESSELATION,
{ color: "#C0C0C070", lineWidth: 1 }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_EYE,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_EYEBROW,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_EYE,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_EYEBROW,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_FACE_OVAL,
{ color: "#000000" }
);
drawingUtils.drawConnectors(landmarks, FaceLandmarker.FACE_LANDMARKS_LIPS, {
color: "#000000"
});
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_IRIS,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_IRIS,
{ color: "#000000" }
);
}
drawBlendShapes(imageBlendShapes, faceLandmarkerResult.faceBlendshapes);
}
/********************************************************************
// Demo 2: Continuously grab image from webcam stream and detect it.
********************************************************************/
const video = document.getElementById("webcam") as HTMLVideoElement;
const canvasElement = document.getElementById(
"output_canvas"
) as HTMLCanvasElement;
const canvasCtx = canvasElement.getContext("2d");
// Check if webcam access is supported.
function hasGetUserMedia() {
return !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia);
}
// If webcam supported, add event listener to button for when user
// wants to activate it.
if (hasGetUserMedia()) {
enableWebcamButton = document.getElementById(
"webcamButton"
) as HTMLButtonElement;
enableWebcamButton.addEventListener("click", enableCam);
} else {
console.warn("getUserMedia() is not supported by your browser");
}
// Enable the live webcam view and start detection.
function enableCam(event) {
if (!faceLandmarker) {
console.log("Wait! faceLandmarker not loaded yet.");
return;
}
if (webcamRunning === true) {
webcamRunning = false;
enableWebcamButton.innerText = "ENABLE PREDICTIONS";
} else {
webcamRunning = true;
enableWebcamButton.innerText = "DISABLE PREDICTIONS";
}
// getUsermedia parameters.
const constraints = {
video: true
};
// Activate the webcam stream.
navigator.mediaDevices.getUserMedia(constraints).then((stream) => {
video.srcObject = stream;
video.addEventListener("loadeddata", predictWebcam);
});
}
let lastVideoTime = -1;
let results = undefined;
const drawingUtils = new DrawingUtils(canvasCtx);
async function predictWebcam() {
const radio = video.videoHeight / video.videoWidth;
video.style.width = videoWidth + "px";
video.style.height = videoWidth * radio + "px";
canvasElement.style.width = videoWidth + "px";
canvasElement.style.height = videoWidth * radio + "px";
canvasElement.width = video.videoWidth;
canvasElement.height = video.videoHeight;
// Now let's start detecting the stream.
if (runningMode === "IMAGE") {
runningMode = "VIDEO";
await faceLandmarker.setOptions({ runningMode: runningMode });
}
let startTimeMs = performance.now();
if (lastVideoTime !== video.currentTime) {
lastVideoTime = video.currentTime;
results = faceLandmarker.detectForVideo(video, startTimeMs);
}
if (results.faceLandmarks) {
for (const landmarks of results.faceLandmarks) {
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_TESSELATION,
{ color: "#C0C0C070", lineWidth: 1 }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_EYE,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_EYEBROW,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_EYE,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_EYEBROW,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_FACE_OVAL,
{ color: "#E0E0E0" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LIPS,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_RIGHT_IRIS,
{ color: "#000000" }
);
drawingUtils.drawConnectors(
landmarks,
FaceLandmarker.FACE_LANDMARKS_LEFT_IRIS,
{ color: "#000000" }
);
}
}
drawBlendShapes(videoBlendShapes, results.faceBlendshapes);
// Call this function again to keep predicting when the browser is ready.
if (webcamRunning === true) {
window.requestAnimationFrame(predictWebcam);
}
}
function drawBlendShapes(el: HTMLElement, blendShapes: any[]) {
if (!blendShapes.length) {
return;
}
console.log(blendShapes[0]);
let htmlMaker = "";
blendShapes[0].categories.map((shape) => {
htmlMaker += `
<li class="blend-shapes-item">
<span class="blend-shapes-label">${
shape.displayName || shape.categoryName
}</span>
<span class="blend-shapes-value" style="width: calc(${
+shape.score * 100
}% - 120px)">${(+shape.score).toFixed(4)}</span>
</li>
`;
});
el.innerHTML = htmlMaker;
}
/* Copyright 2023 The MediaPipe Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
/* Copyright 2022 The MediaPipe Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
@use "@material";
body {
font-family: helvetica, arial, sans-serif;
margin: 2em;
color: #3d3d3d;
--mdc-theme-primary: #007f8b;
--mdc-theme-on-primary: #f1f3f4;
}
html, body {
height: 100%; /* Ensure the body takes up the full viewport */
margin: 0; /* Remove default margins */
overflow: hidden; /* Prevent scrollbars if content is larger */
}
.blend-shapes{
/*visibility:hidden;*/
}
#webcam{
visibility:hidden;
}
#webcam, #output_canvas {
position: fixed; /* Ensure they are positioned relative to the viewport */
left: 0;
top: 0;
width: 100%;
height: 100%;
object-fit: cover; /* Make video fill the space while maintaining aspect ratio */
z-index: -1; /* Optional: Put the video behind the canvas if you need to draw on it */
}
h1 {
font-style: italic;
color: #ff6f00;
color: #007f8b;
}
h2 {
clear: both;
}
em {
font-weight: bold;
}
video {
clear: both;
display: block;
transform: rotateY(180deg);
-webkit-transform: rotateY(180deg);
-moz-transform: rotateY(180deg);
}
section {
opacity: 1;
transition: opacity 500ms ease-in-out;
}
header,
footer {
clear: both;
}
.removed {
display: none;
}
.invisible {
opacity: 0.2;
}
.note {
font-style: italic;
font-size: 130%;
}
.videoView,
.detectOnClick,
.blend-shapes {
position: relative;
float: left;
width: 48%;
margin: 2% 1%;
cursor: pointer;
}
.videoView p,
.detectOnClick p {
position: absolute;
padding: 5px;
background-color: #007f8b;
color: #fff;
border: 1px dashed rgba(255, 255, 255, 0.7);
z-index: 2;
font-size: 12px;
margin: 0;
}
.highlighter {
background: rgba(0, 255, 0, 0.25);
border: 1px dashed #fff;
z-index: 1;
position: absolute;
}
.canvas {
z-index: 1;
position: absolute;
pointer-events: none;
}
.output_canvas {
transform: rotateY(180deg);
-webkit-transform: rotateY(180deg);
-moz-transform: rotateY(180deg);
}
.detectOnClick {
z-index: 0;
}
.detectOnClick img {
width: 100%;
}
.blend-shapes-item {
display: flex;
align-items: center;
height: 20px;
}
.blend-shapes-label {
display: flex;
width: 120px;
justify-content: flex-end;
align-items: center;
margin-right: 4px;
}
.blend-shapes-value {
display: flex;
height: 16px;
align-items: center;
background-color: #007f8b;
}
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