PoseNet is a machine learning model that allows for Real-time Human Pose Estimation.
PoseNet can be used to estimate either a single pose or multiple poses, meaning there is a version of the algorithm that can detect only one person in an image/video and one version that can detect multiple persons in an image/video.
The original PoseNet model was ported to TensorFlow.js by Dan Oved.
Quickstart
const video = document.getElementById('video');
// Create a new poseNet method
const poseNet = ml5.poseNet(video, modelLoaded);
// When the model is loaded
function modelLoaded() {
console.log('Model Loaded!');
}
// Listen to new 'pose' events
poseNet.on('pose', (results) => {
poses = results;
});
Initialize : There are a couple ways to initialize ml5.poseNet.
// Initialize with video, type and callback
const poseNet = ml5.poseNet(?video, ?type, ?callback);
// OR Initialize with video, options and callback
const poseNet = ml5.poseNet(?video, ?options, ?callback);
// OR Initialize WITHOUT video. Just options and callback here
const poseNet = ml5.poseNet(?callback, ?options);
Parameters :
video : OPTIONAL. Optional HTMLVideoElement input to run poses on.
type : OPTIONAL. A String value to run single or multiple estimation. Changes the detectionType property of the options. Default is multiple.
callback : OPTIONAL. A function that is called when the model is loaded.
options : OPTIONAL. A object that contains properties that effect the posenet model accuracy, results, etc.
{
architecture: 'MobileNetV1',
imageScaleFactor: 0.3,
outputStride: 16,
flipHorizontal: false,
minConfidence: 0.5,
maxPoseDetections: 5,
scoreThreshold: 0.5,
nmsRadius: 20,
detectionType: 'multiple',
inputResolution: 513,
multiplier: 0.75,
quantBytes: 2,
};
