// Cloned by Cian on 4 Dec 2021 from World "Recognise any image" by Starter user 
// Please leave this clone trail here.
 

 
// ML5 image recognition using MobileNet 
// uses AB framework
// enter URL of image at runtime

 
// no run, pause, step
AB.drawRunControls = false;

let classifier;
let img;




// asynchronous loads of resources, with callback functions when ready 
var classifierLoaded = false;
var imgLoaded = false;


	
AB.world.newRun = function()
{
    
 	ABWorld.init (  'lightblue'  ); 
    //AB.headerRHS();   
 		
    // DoodleNet load pretrained
    doodleClassifier = ml5.imageClassifier('DoodleNet', modelReady)


    function modelReady() {
        console.log('model loaded');
        // pass canvas itself and pass it to model for prediction (retreive from gotResults)
        doodleClassifier.classify(canvas, gotResults);

    }
    // callback prediction from nn
    function gotResults(error, results){
        if (error){
            console.error(error);
            return;
        }
        console.log(results);
        
    }
};

//---- setup -------------------------------------------------------
// Do NOT make a setup function.
// This is done for you in the API. The API setup just creates a canvas.
// Anything else you want to run at the start should go into the following two functions.

let clearButton;
let canvas;

function beforesetup()      // Optional 
{
	// Anything you want to run at the start BEFORE the canvas is created 
  clearButton = createButton('clear');
  clearButton.mousePressed(clearCanvas);
}

function clearCanvas() {
  background(255);
}

function aftersetup()       // Optional
{
	// Anything you want to run at the start AFTER the canvas is created 
}


//---- draw -------------------------------------------------------

function draw()             // Optional
{
	// Can put P5 instructions to be executed every step here, or in AB.world.nextStep()  
	if (mouseIsPressed) {
     strokeWeight(8);
     line(mouseX, mouseY, pmouseX, pmouseY);
  }
}