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/*
This example was provided by Andreas Refsgaard using ML5.
https://editor.p5js.org/AndreasRef/sketches/Z2OChCuHk
*/
let featureExtractor;
let regressor;
let video;
let loss;
let slider;
let samples = 0;
let rectSize = 50;
let lerpedResult = 0.5;
let allowedToPredict = true;
function setup() {
createCanvas(640, 480);
// Create a video element
video = createCapture(VIDEO);
video.size(640, 480);
video.hide();
// Extract the features from MobileNet
featureExtractor = ml5.featureExtractor('MobileNet', modelReady);
// Create a new regressor using those features and give the video we want to use
regressor = featureExtractor.regression(video, videoReady);
// Create the UI buttons
setupButtons();
rectMode(CENTER);
}
function draw() {
image(video, 0, 0, width, height);
noStroke();
fill(255, 0, 0, 100);
//slider.value() is your key variable to do something with on prediction.
rect(width / 2, height / 2, slider.value() * 300, slider.value() * 300);
}
// A function to be called when the model has been loaded
function modelReady() {
select('#modelStatus').html('Model loaded!');
}
// A function to be called when the video has loaded
function videoReady() {
select('#videoStatus').html('Video ready!');
}
// Classify the current frame.
function predict() {
allowedToPredict = true;
regressor.predict(gotResults);
}
function stopPredicting() {
allowedToPredict = false;
}
// A util function to create UI buttons
function setupButtons() {
slider = select('#slider');
select('#addSample').mousePressed(function() {
regressor.addImage(slider.value());
select('#amountOfSamples').html(samples++);
});
// Train Button
select('#train').mousePressed(function() {
regressor.train(function(lossValue) {
if (lossValue) {
loss = lossValue;
select('#loss').html('Loss: ' + loss);
} else {
select('#loss').html('Done Training! Final Loss: ' + loss);
}
});
});
// Predict Button
select('#buttonPredict').mousePressed(predict);
select('#buttonStopPredict').mousePressed(stopPredicting);
// Save model
saveBtn = select('#save');
saveBtn.mousePressed(function() {
regressor.save();
});
// Load model
loadBtn = select('#load');
loadBtn.changed(function() {
regressor.load(loadBtn.elt.files, function() {
select('#modelStatus').html('Custom Model Loaded!');
});
});
}
// Show the results
function gotResults(err, result) {
if (err) {
console.error(err);
}
if (result && result.value && allowedToPredict) {
lerpedResult = lerp(lerpedResult, result.value, 0.50);
slider.value(lerpedResult); //update the slider wiht the predicted result. !
predict();
}
}