Created
December 4, 2019 02:24
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Body tracking with frame counter on data
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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta charset="UTF-8" /> | |
<title>Kinect Azure Example</title> | |
<link | |
rel="stylesheet" | |
href="../assets/vendors/bootstrap-4.3.1-dist/css/bootstrap.css" | |
/> | |
<link | |
rel="stylesheet" | |
href="../assets/vendors/bootstrap-4.3.1-dist/css/docs.min.css" | |
/> | |
</head> | |
<body class="container-fluid py-3"> | |
<div class="d-flex align-items-baseline justify-content-between"> | |
<h1 class="bd-title">Body Tracking (2D)</h1> | |
<button | |
onclick="require('electron').remote.getCurrentWebContents().openDevTools()" | |
> | |
open dev tools | |
</button> | |
</div> | |
<p> | |
This demo shows the 2D Skeleton Information. | |
</p> | |
<canvas id="outputCanvas" class="img-fluid"></canvas> | |
<script> | |
{ | |
const KinectAzure = require("kinect-azure"); | |
const kinect = new KinectAzure(); | |
const $outputCanvas = document.getElementById("outputCanvas"), | |
outputCtx = $outputCanvas.getContext("2d"); | |
let outputImageData; | |
const init = () => { | |
startKinect(); | |
}; | |
let frameCtr = 0; | |
let startTime = 0; | |
const startKinect = () => { | |
if (kinect.open()) { | |
kinect.startCameras({ | |
depth_mode: KinectAzure.K4A_DEPTH_MODE_NFOV_UNBINNED, | |
color_format: KinectAzure.K4A_IMAGE_FORMAT_COLOR_BGRA32, | |
color_resolution: KinectAzure.K4A_COLOR_RESOLUTION_1080P, | |
camera_fps: KinectAzure.K4A_FRAMES_PER_SECOND_30 | |
}); | |
kinect.createTracker(); | |
kinect.startListening(data => { | |
// console.log("getting data"); | |
if (Date.now() > startTime + 1000) { | |
console.log("frames ", frameCtr); | |
frameCtr = 0; | |
startTime = Date.now(); | |
} else { | |
frameCtr++; | |
} | |
// if (!outputImageData && data.colorImageFrame.width > 0) { | |
// $outputCanvas.width = data.colorImageFrame.width; | |
// $outputCanvas.height = data.colorImageFrame.height; | |
// outputImageData = outputCtx.createImageData( | |
// $outputCanvas.width, | |
// $outputCanvas.height | |
// ); | |
// } | |
// // if (outputImageData) { | |
// // renderBGRA32ColorFrame(data); | |
// // } | |
// if (data.bodyFrame.bodies) { | |
// console.log(data.bodyFrame.bodies); | |
// // render the skeleton joints on top of the color feed | |
// outputCtx.save(); | |
// outputCtx.fillStyle = "red"; | |
// data.bodyFrame.bodies.forEach(body => { | |
// body.skeleton.joints.forEach(joint => { | |
// outputCtx.fillRect(joint.colorX, joint.colorY, 10, 10); | |
// }); | |
// }); | |
// outputCtx.restore(); | |
// } | |
}); | |
} | |
}; | |
const renderBGRA32ColorFrame = data => { | |
const newPixelData = Buffer.from(data.colorImageFrame.imageData); | |
const pixelArray = outputImageData.data; | |
for (let i = 0; i < outputImageData.data.length; i += 4) { | |
pixelArray[i] = newPixelData[i + 2]; | |
pixelArray[i + 1] = newPixelData[i + 1]; | |
pixelArray[i + 2] = newPixelData[i]; | |
pixelArray[i + 3] = 0xff; | |
} | |
outputCtx.putImageData(outputImageData, 0, 0); | |
}; | |
init(); | |
} | |
</script> | |
</body> | |
</html> |
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