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Code viewer for World: Character recognition neur... 

// Cloned by Abdelshafa Abdala on 2 Dec 2022 from World "Character recognition neural network (clone by Akash Gupta) (clone by Abdelshafa Abdala)" by Abdelshafa Abdala 
// Please leave this clone trail here.
 


// Cloned by Abdelshafa Abdala on 2 Dec 2022 from World "Character recognition neural network (clone by Akash Gupta)" by Akash Gupta 
// Please leave this clone trail here.
 
const PIXELS=28,PIXELSSQUARED=PIXELS*PIXELS;var requiredPixels=24;const NOTRAIN=6e4,NOTEST=1e4,noinput=PIXELSSQUARED,nohidden=64,nooutput=10,learningrate=.1;let do_training=!0;const TRAINPERSTEP=30,TESTPERSTEP=5,ZOOMFACTOR=7,ZOOMPIXELS=7*PIXELS,canvaswidth=PIXELS+ZOOMPIXELS+50,canvasheight=3*ZOOMPIXELS+100,DOODLE_THICK=18,DOODLE_BLUR=0;let mnist,nn,doodle,demo,trainrun=1,train_index=0,testrun=1,test_index=0,total_tests=0,total_correct=0,doodle_exists=!1,demo_exists=!1,mousedrag=!1;var train_inputs,test_inputs,demo_inputs,doodle_inputs,thehtml;function randomWeight(){return AB.randomFloatAtoB(-.5,.5)}AB.headerCSS({"max-height":"95vh"}),thehtml="<hr> <h1> 1. Doodle </h1> Top row: Doodle (left) and shrunk (right). <br>  Draw your doodle in top LHS. <button onclick='wipeDoodle();' class='normbutton' >Clear doodle</button> <br> ",AB.msg(thehtml,1),thehtml="<hr> <h1> 2. Training </h1> Middle row: Training image magnified (left) and original (right). <br>   <button onclick='do_training = false;' class='normbutton' >Stop training</button> <br> ",AB.msg(thehtml,3),thehtml="<h3> Hidden tests </h3> ",AB.msg(thehtml,5),thehtml="<hr> <h1> 3. Demo </h1> Bottom row: Test image magnified (left) and  original (right). <br> The network is <i>not</i> trained on any of these images. <br>  <button onclick='makeDemo();' class='normbutton' >Demo test image</button> <br> ",AB.msg(thehtml,7);const greenspan="<span style='font-weight:bold; font-size:x-large; color:darkgreen'> ";function imageToCenter(t,e){for(var n=oneDimensionTo2D(t,e),o=getIndexOfCorners(n,Number.MAX_VALUE,Number.MAX_VALUE,-1,-1),s=Math.floor((e-o[3]-o[2])/2),i=Math.floor((e-o[1]-o[0])/2),a=[],r=0;r<e;r++){a[r]=[];for(var l=0;l<e;l++)a[r][l]=0}for(r=o[2];r<=o[3];r++)for(l=o[0];l<=o[1];l++)a[r+s][l+i]=n[r][l];return result=twoDto1D(a,e),result}function twoDto1D(t,e){for(var n=[],o=0;o<e;o++)for(var s=0;s<e;s++)n[o*e+s]=t[o][s];return n}function getIndexOfCorners(t,e,n,o,s){for(var i=0;i<t.length;i++){var a=t[i].indexOf(255),r=t[i].lastIndexOf(255);a>=0&&a<n&&(n=a),r>=0&&r>s&&(s=r),a>=0&&i<e&&(e=i),a>=0&&i>o&&(o=i)}return[n,s,e,o]}function oneDimensionTo2D(t,e){for(var n=[],o=0;o<e;o++){n[o]=[];for(var s=0;s<e;s++)n[o][s]=t[4*(o*e+s)]}return n}function guessTheDigit(){var t=doodle.get();t.resize(PIXELS,PIXELS),t.loadPixels();let e=[];for(let n=0;n<PIXELSSQUARED;n++)e[n]=t.pixels[4*n]/255;doodle_inputs=e;var n=updateImageFormat(imageToCenter(t.pixels,PIXELS),24),o=find12(cnn.classifyImages([n])[0].values);thehtml=" We classify it as: "+greenspan+o[0]+"</span> <br> No.2 guess is: "+greenspan+o[1]+"</span>",AB.msg(thehtml,2)}function loadNetworkFromJSON(t){cnn=new WebCNN,void 0!=t.momentum&&cnn.setMomentum(t.momentum),void 0!=t.lambda&&cnn.setLambda(t.lambda),void 0!=t.learningRate&&cnn.setLearningRate(t.learningRate);for(var e=0;e<t.layers.length;++e){let n=t.layers[e];cnn.newLayer(n)}for(e=0;e<t.layers.length;++e){let n=t.layers[e];switch(t.layers[e].type){case LAYER_TYPE_CONV:case LAYER_TYPE_FULLY_CONNECTED:void 0!=n.weights&&void 0!=n.biases&&cnn.layers[e].setWeightsAndBiases(n.weights,n.biases)}}return cnn.initialize(),cnn}function setup(){createCanvas(canvaswidth,canvasheight),(doodle=createGraphics(ZOOMPIXELS,ZOOMPIXELS)).pixelDensity(1),AB.loadingScreen(),$.getScript("/uploads/codingtrain/matrix.js",function(){$.getScript("/uploads/codingtrain/nn.js",function(){$.getScript("/uploads/codingtrain/mnist.js",function(){$.getScript("/uploads/akash037/mathutils.js",function(){$.getScript("/uploads/akash037/webcnn.js",function(){$.getJSON("/uploads/akash037/cnn_mnist_10_20_98accuracy.json",function(t,e){console.log("All JS loaded"),cnn=loadNetworkFromJSON(t),(nn=new NeuralNetwork(noinput,nohidden,nooutput)).setLearningRate(learningrate),loadData()})})})})})})}function loadData(){loadMNIST(function(t){mnist=t,console.log("All data loaded into mnist object:"),console.log(mnist),AB.removeLoading()})}function updateImageFormat(t){return{width:24,height:24,data:getRequiredImage(reduceImageSize(t)).pixels}}function reduceImageSize(t){for(var e=PIXELS-24,n=Math.floor(Math.random()*e),o=Math.floor(Math.random()*e),s=n+24,i=o+24,a=[],r=n;r<s;r++)for(let e=o;e<i;e++)a.push(t[r*PIXELS+e]);return a}function getRequiredImage(t){let e=createImage(24,24);e.loadPixels();for(let n=0;n<576;n++){let o=t[n],s=4*n;e.pixels[s+0]=o,e.pixels[s+1]=o,e.pixels[s+2]=o,e.pixels[s+3]=255}return e.updatePixels(),e}function getImage(t){let e=createImage(PIXELS,PIXELS);e.loadPixels();for(let n=0;n<PIXELSSQUARED;n++){let o=t[n],s=4*n;e.pixels[s+0]=o,e.pixels[s+1]=o,e.pixels[s+2]=o,e.pixels[s+3]=255}return e.updatePixels(),e}function getInputs(t){let e=[];for(let n=0;n<PIXELSSQUARED;n++){let o=t[n];e[n]=o/255}return e}function trainit(t){let e=mnist.train_images[train_index],n=mnist.train_labels[train_index];if(t){var o=getImage(e);image(o,0,ZOOMPIXELS+50,ZOOMPIXELS,ZOOMPIXELS),image(o,ZOOMPIXELS+50,ZOOMPIXELS+50,PIXELS,PIXELS)}let s=getInputs(e),i=[0,0,0,0,0,0,0,0,0,0];i[n]=1,train_inputs=s,nn.train(s,i),thehtml=" trainrun: "+trainrun+"<br> no: "+train_index,AB.msg(thehtml,4),++train_index==NOTRAIN&&(train_index=0,console.log("finished trainrun: "+trainrun),trainrun++)}function testItWithCNN(){var t=mnist.test_images[test_index],e=mnist.test_labels[test_index],n=updateImageFormat(t,24),o=find12(cnn.classifyImages([n])[0].values);total_tests++,o[0]==e&&total_correct++;var s=total_correct/total_tests*100;thehtml=" testrun: "+testrun+"<br> no: "+total_tests+" <br>  correct: "+total_correct+"<br>  score: "+greenspan+s.toFixed(2)+"</span>",AB.msg(thehtml,6),++test_index==NOTEST&&(console.log("finished testrun: "+testrun+" score: "+s.toFixed(2)),testrun++,test_index=0,total_tests=0,total_correct=0)}function testit(){let t=mnist.test_images[test_index],e=mnist.test_labels[test_index],n=getInputs(t);test_inputs=n;let o=findMax(nn.predict(n));total_tests++,o==e&&total_correct++;let s=total_correct/total_tests*100;thehtml=" testrun: "+testrun+"<br> no: "+total_tests+" <br>  correct: "+total_correct+"<br>  score: "+greenspan+s.toFixed(2)+"</span>",AB.msg(thehtml,6),++test_index==NOTEST&&(console.log("finished testrun: "+testrun+" score: "+s.toFixed(2)),testrun++,test_index=0,total_tests=0,total_correct=0)}function find12(t){let e=0,n=0,o=0,s=0;for(let i=0;i<t.length;i++)t[i]>o?(n=e,s=o,e=i,o=t[i]):t[i]>s&&(n=i,s=t[i]);return[e,n]}function findMax(t){let e=0,n=0;for(let o=0;o<t.length;o++)t[o]>n&&(e=o,n=t[o]);return e}function draw(){if(void 0!==mnist){if(background("black"),do_training){for(let t=0;t<TRAINPERSTEP;t++)trainit(0==t);for(let t=0;t<TESTPERSTEP;t++)testItWithCNN()}if(demo_exists&&(drawDemo(),guessDemo()),doodle_exists&&(drawDoodle(),guessTheDigit()),mouseIsPressed){var t=ZOOMPIXELS+20;mouseX<t&&mouseY<t&&pmouseX<t&&pmouseY<t&&(mousedrag=!0,doodle_exists=!0,doodle.stroke("white"),doodle.strokeWeight(DOODLE_THICK),doodle.line(mouseX,mouseY,pmouseX,pmouseY))}else mousedrag&&(mousedrag=!1,doodle.filter(BLUR,DOODLE_BLUR))}}function makeDemo(){demo_exists=!0;var t=AB.randomIntAtoB(0,NOTEST-1);demo=mnist.test_images[t];var e=mnist.test_labels[t];thehtml="Test image no: "+t+"<br>Classification: "+e+"<br>",AB.msg(thehtml,8)}function drawDemo(){var t=getImage(demo);image(t,0,canvasheight-ZOOMPIXELS,ZOOMPIXELS,ZOOMPIXELS),image(t,ZOOMPIXELS+50,canvasheight-ZOOMPIXELS,PIXELS,PIXELS)}function guessDemo(){let t=getInputs(demo);demo_inputs=t;let e=findMax(nn.predict(t));thehtml=" We classify it as: "+greenspan+e+"</span>",AB.msg(thehtml,9)}function drawDoodle(){let t=doodle.get();image(t,0,0,ZOOMPIXELS,ZOOMPIXELS),image(t,ZOOMPIXELS+50,0,PIXELS,PIXELS)}function guessDoodle(){let t=doodle.get();t.resize(PIXELS,PIXELS),t.loadPixels();let e=[];for(let n=0;n<PIXELSSQUARED;n++)e[n]=t.pixels[4*n]/255;console.log(e),doodle_inputs=e;let n=find12(nn.predict(e));thehtml=" We classify it as: "+greenspan+n[0]+"</span> <br> No.2 guess is: "+greenspan+n[1]+"</span>",AB.msg(thehtml,2)}function wipeDoodle(){doodle_exists=!1,doodle.background("black")}function showInputs(t){var e="";for(let n=0;n<t.length;n++){n%PIXELS==0&&(e+="\n"),e=e+" "+t[n].toFixed(2)}console.log(e)}