// Cloned by sagar gatla on 3 Dec 2022 from World "CharRecognition_UsingCNN (clone by Dheera(21261395))" by Dheera
// Please leave this clone trail here.
const PIXELS=28,PIXELSSQUARED=PIXELS*PIXELS,NOTRAIN=124800,NOTEST=20800,noinput=PIXELSSQUARED,nohidden=64,nooutput=10,learningrate=.1;let do_training=!0;const TRAINPERSTEP=15,TESTPERSTEP=5,ZOOMFACTOR=7,ZOOMPIXELS=7*PIXELS,canvaswidth=PIXELS+ZOOMPIXELS+50,canvasheight=3*ZOOMPIXELS+100,DOODLE_THICK=18,DOODLE_BLUR=3;let mnist,mycnn,mycnnTrain,mycnnModel,doodle,demo,alphabets=["A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z"],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 and Re-draw</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' >Pause training</button> <button onclick='do_training = true;' class='normbutton' >Resume 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 bluespan="<span style='font-weight:bold; font-size:large; color:darkblue'> ";function setup(){createCanvas(canvaswidth,canvasheight),(doodle=createGraphics(ZOOMPIXELS,ZOOMPIXELS)).pixelDensity(1),wipeDoodle(),AB.loadingScreen(),$.getScript("/uploads/codingtrain/matrix.js",function(){$.getScript("/uploads/dheera0704/convnet3.js",function(){$.getScript("/uploads/dheera0704/mnistDhe.js",function(){console.log("All JS Files loaded");let t=[];t.push({type:"input",out_sx:28,out_sy:28,out_depth:1}),t.push({type:"conv",sx:5,filters:8,stride:1,pad:2,activation:"relu"}),t.push({type:"pool",sx:2,stride:2}),t.push({type:"conv",sx:5,filters:16,stride:1,pad:2,activation:"relu"}),t.push({type:"pool",sx:3,stride:3}),t.push({type:"softmax",num_classes:26}),(mycnnModel=new convnetjs.Net).makeLayers(t),mycnnTrain=new convnetjs.SGDTrainer(mycnnModel,{method:"adadelta",momentum:.9,batch_size:10,l2_decay:.001}),loadData()})})})}function loadData(){loadMNIST(function(t){mnist=t;let e=0;for(;e<NOTRAIN;e++)rotateImage(mnist.train_images[e]);for(e=0;e<NOTEST;e++)rotateImage(mnist.test_images[e]);console.log("All data loaded into Emnist object."),console.log(mnist),AB.removeLoading()})}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 rotateImage(t){for(let e=0;e<PIXELS;e++)for(let n=e;n<PIXELS;n++){let o=e*PIXELS+n,s=n*PIXELS+e,i=t[o];t[o]=t[s],t[s]=i}}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);train_inputs=s;{let t=getmycnnInputs(s);mycnnTrain.train(t,n)}thehtml=" trainrun: "+trainrun+"<br> no: "+train_index,AB.msg(thehtml,4),++train_index==NOTRAIN&&(train_index=0,console.log("finished trainrun: "+trainrun),trainrun++)}function getmycnnInputs(t){for(var e=new convnetjs.Vol(28,28,1,0),n=0;n<PIXELSSQUARED;n++)e.w[n]=t[n];return e}function testit(){let t=mnist.test_images[test_index],e=mnist.test_labels[test_index],n=getInputs(t),o=getmycnnInputs(n);test_inputs=n;let s=findMax(mycnnModel.forward(o).w);var i=getImage(t);image(i,0,ZOOMPIXELS+50,ZOOMPIXELS,ZOOMPIXELS),image(i,ZOOMPIXELS+50,ZOOMPIXELS+50,PIXELS,PIXELS),total_tests++,s==e&&total_correct++;let a=total_correct/total_tests*100;thehtml=" testrun: "+testrun+"<br> no: "+total_tests+" <br> correct: "+total_correct+"<br> score: "+bluespan+a.toFixed(2)+"</span>",AB.msg(thehtml,6),++test_index==NOTEST&&(console.log("finished testrun: "+testrun+" score: "+a.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"),strokeWeight(1),stroke("green"),rect(0,0,ZOOMPIXELS,ZOOMPIXELS),textSize(10),textAlign(CENTER),text("DOODLE HERE",ZOOMPIXELS/2,ZOOMPIXELS/2),do_training){for(let t=0;t<TRAINPERSTEP;t++)trainit(0===t);for(let t=0;t<TESTPERSTEP;t++)testit()}if(demo_exists&&(drawDemo(),guessDemo()),doodle_exists&&(drawDoodle(),guessDoodle()),mouseIsPressed){var t=ZOOMPIXELS+20;mouseX<t&&mouseY<t&&pmouseX<t&&pmouseY<t&&(mousedrag=!0,doodle_exists=!0,doodle.stroke("red"),strokeJoin(ROUND),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: "+alphabets[e-1]+"<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=getmycnnInputs(t),n=findMax(mycnnModel.forward(e).w);thehtml=" We classify it as: "+bluespan+alphabets[n-1]+"</span>",AB.msg(thehtml,9)}function drawDoodle(){let t=doodle.get();image(t,0,0,ZOOMPIXELS,ZOOMPIXELS),image(t,ZOOMPIXELS+20,0,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;doodle_inputs=e;let n=getmycnnInputs(e),o=find12(mycnnModel.forward(n).w);thehtml=" Our 1st Guess is: "+bluespan+alphabets[o[0]-1]+"</span> <br> Our 2nd Guess is: "+bluespan+alphabets[o[1]-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)}