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// config start
    var OUTLINES = false;
    // config end

window.hotSpots = [];

var content = $('#dmotion');
        var canvases = $('canvas');

var lastImageData;
        var canvasSource = $("#canvas-source")[0];
        var canvasBlended = $("#canvas-blended")[0];

var contextSource = canvasSource.getContext('2d');
        var contextBlended = canvasBlended.getContext('2d');

var video;
        //var sensitivity = 3;

function startMotion() {

console.log("Motion detection started.");

//change this to remote
        video = $('#remote')[0];

var resize = function () {
            var ratio = video.width / video.height;
            var w = $(this).width();
            var h = $(this).height() - 110;

if (content.width() > w) {
                content.width(w);
                content.height(w / ratio);
            } else {
                content.height(h);
                content.width(h * ratio);
            }
            canvases.width(content.width());
            canvases.height(content.height());
        }
        $(window).resize(resize);
        $(window).ready(function () {
            resize();

});

// mirror video
        contextSource.translate(canvasSource.width, 0);
        contextSource.scale(-1, 1);

var c = 5;

start();
        } //end function

function start() {
        //$('.loading').fadeOut();
        $('#hotSpots').fadeIn();
       // $('body').addClass('black-background');
       // $(".instructions").delay(600).fadeIn();
        $(canvasSource).delay(600).fadeIn();
        $(canvasBlended).delay(600).fadeIn();
        $('#canvas-highlights').delay(600).fadeIn();
        $(window).trigger('start');
        update();
    }

window.requestAnimFrame = (function () {
        return window.requestAnimationFrame ||
			   window.webkitRequestAnimationFrame ||
			   window.mozRequestAnimationFrame ||
			   window.oRequestAnimationFrame ||
			   window.msRequestAnimationFrame ||
			function (callback) {
			    window.setTimeout(callback, 1000 / 60);
			};
    })();

function update() {
        drawVideo();
        blend();
        checkAreas();
        requestAnimFrame(update);
    }

function drawVideo() {
        contextSource.drawImage(video, 0, 0, video.width, video.height);
    }

function blend() {
        var width = canvasSource.width;
        var height = canvasSource.height;
        // get webcam image data
        var sourceData = contextSource.getImageData(0, 0, width, height);
        // create an image if the previous image doesn’t exist
        if (!lastImageData) lastImageData = contextSource.getImageData(0, 0, width, height);
        // create a ImageData instance to receive the blended result
        var blendedData = contextSource.createImageData(width, height);
        // blend the 2 images
        differenceAccuracy(blendedData.data, sourceData.data, lastImageData.data);
        // draw the result in a canvas
        contextBlended.putImageData(blendedData, 0, 0);
        // store the current webcam image
        lastImageData = sourceData;
    }

function fastAbs(value) {
        // funky bitwise, equal Math.abs
        return (value ^ (value >> 31)) - (value >> 31);
    }

function threshold(value) {
        return (value > 0x15) ? 0xFF : 0;
    }

function difference(target, data1, data2) {
        // blend mode difference
        if (data1.length != data2.length) return null;
        var i = 0;
        while (i < (data1.length * 0.25)) {
            target[4 * i] = data1[4 * i] == 0 ? 0 : fastAbs(data1[4 * i] - data2[4 * i]);
            target[4 * i + 1] = data1[4 * i + 1] == 0 ? 0 : fastAbs(data1[4 * i + 1] - data2[4 * i + 1]);
            target[4 * i + 2] = data1[4 * i + 2] == 0 ? 0 : fastAbs(data1[4 * i + 2] - data2[4 * i + 2]);
            target[4 * i + 3] = 0xFF;
            ++i;
        }
    }

function differenceAccuracy(target, data1, data2) {
        if (data1.length != data2.length) return null;
        var i = 0;
        while (i < (data1.length * 0.25)) {
            var average1 = (data1[4 * i] + data1[4 * i + 1] + data1[4 * i + 2]) / 3;
            var average2 = (data2[4 * i] + data2[4 * i + 1] + data2[4 * i + 2]) / 3;
            var diff = threshold(fastAbs(average1 - average2));
            target[4 * i] = diff;
            target[4 * i + 1] = diff;
            target[4 * i + 2] = diff;
            target[4 * i + 3] = 0xFF;
            ++i;
        }
    }

//This is still setup for looking at individual hotspots. Could be simplified to con
    function checkAreas() {
        var data;
        
        for (var h = 0; h < hotSpots.length; h++) {
            var blendedData = contextBlended.getImageData(hotSpots[h].x, hotSpots[h].y, hotSpots[h].width, hotSpots[h].height);
            var i = 0;
            var average = 0;
            while (i < (blendedData.data.length * 0.25)) {
                // make an average between the color channel
                average += (blendedData.data[i * 4] + blendedData.data[i * 4 + 1] + blendedData.data[i * 4 + 2]) / 3;
                ++i;
            }
            // calculate an average between the color values of the spot area
            average = Math.round(average / (blendedData.data.length * 0.25));
            
            //CHAD: Value below was originaly 10 - made very sensisitve
            if (average > 1) {
                // over a small limit, consider that a movement is detected
                data = { confidence: average, spot: hotSpots[h] };
                $(data.spot.el).trigger('motion', data);
            }
        } }