// Cloned by test on 13 Jan 2020 from World "Daniel Peres - MNIST Character Recognition - Final Version!" by Daniel Peres 
// Please leave this clone trail here.
 
const PIXELS=28,PIXELSSQUARED=PIXELS*PIXELS,NOTRAIN=6e4,NOTEST=1e4,LETBORDER=0,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=4*ZOOMPIXELS+100,DOODLE_THICK=18,DOODLE_BLUR=3;let mnist,nn,doodle,demo,trainrun=1,train_index=0,testrun=1,test_index=0,total_tests=0,total_correct=0,totalCorrectByInput=[],doodle_exists=!1,demo_exists=!1,mousedrag=!1;var train_inputs,test_inputs,demo_inputs,doodle_inputs,thehtml,useBestSlowApproach=1,useVariableLearningRate=!1;function randomWeight(){return AB.randomFloatAtoB(-.5,.5)}$("#runheaderbox").css({"max-height":"95vh"}),thehtml="<hr> <h1> 1. Doodle </h1> Top row: Doodle (left) and shrunk (right). <br>  Draw your doodle in top LHS. <button onclick='wipeDoodle();' class='normbutton' >Clear doodle</button> <br> ",AB.msg(thehtml,1),thehtml="<hr> <h1> 2. Training </h1> Middle row: Training image magnified (left) and original (right). <br>   <button onclick='do_training = false;' class='normbutton' >Stop training</button> <br> ",AB.msg(thehtml,3),thehtml="<h3> Hidden tests </h3> ",AB.msg(thehtml,5),thehtml="<hr> <h1> 3. Demo </h1> Bottom row: Test image magnified (left) and  original (right). <br> The network is <i>not</i> trained on any of these images. <br>  <button onclick='makeDemo();' class='normbutton' >Demo test image</button> <br> ",AB.msg(thehtml,7),thehtml="<hr> <h1> 4. Upload </h1> <br/> Test the uploaded image <br/>",AB.msg(thehtml,13),AB.msg("<input type='file' onchange='handleFileUpload(this.files)' id='imageUpload' style='position: absolute; left: 0px; top: 0px;'>",14);const greenspan="<span style='font-weight:bold; font-size:x-large; color:darkgreen'> ";var uploadImageContent,uploadImage,uploadImageResized;function handleFileUpload(e){const t=new FileReader;t.onload=function(e){uploadImageContent=e.target.result},t.readAsDataURL(e[0]),uploadImage=void 0}function Accuracy(){}function setup(){let e=0;for(totalCorrectByInput=[],e=0;e<10;e++)totalCorrectByInput[e]=new Accuracy,totalCorrectByInput[e].input=e,totalCorrectByInput[e].total=0,totalCorrectByInput[e].correct=0;createCanvas(canvaswidth,canvasheight),(doodle=createGraphics(ZOOMPIXELS,ZOOMPIXELS)).pixelDensity(1),doodle.background("black"),AB.loadingScreen(),$.getScript("/uploads/codingtrain/matrix.js",function(){$.getScript("/uploads/codingtrain/nn.js",function(){$.getScript("/uploads/codingtrain/mnist.js",function(){console.log("All JS loaded"),(nn=new NeuralNetwork(noinput,nohidden,nooutput)).setLearningRate(learningrate),loadData()})})})}function loadData(){loadMNIST(function(e){mnist=e,console.log("All data loaded into mnist object:"),console.log(mnist),AB.removeLoading()})}function getImage(e){let t=createImage(PIXELS,PIXELS);t.loadPixels();for(let o=0;o<PIXELSSQUARED;o++){let a=e[o],n=4*o;t.pixels[n+0]=a,t.pixels[n+1]=a,t.pixels[n+2]=a,t.pixels[n+3]=255}return t.updatePixels(),t}function getInputs(e){let t=[];for(let o=0;o<PIXELSSQUARED;o++){let a=e[o];t[o]=a/255}return t}function trainit(e){let t=mnist.train_images[train_index],o=mnist.train_labels[train_index],a=[];if(useBestSlowApproach){var n=cropImage(getImage(t),LETBORDER);n.resize(PIXELS,PIXELS),a=getInputsFromImage(n)}else a=getInputs(t);if(e){var i=getImage(t);image(i,0,ZOOMPIXELS+50,ZOOMPIXELS,ZOOMPIXELS),image(i,ZOOMPIXELS+50,ZOOMPIXELS+50,PIXELS,PIXELS)}let s=[0,0,0,0,0,0,0,0,0,0];if(s[o]=1,train_inputs=a,useVariableLearningRate){let e=total_correct/total_tests*100;if(!e||e<=60)nn.setLearningRate(learningrate);else{let e=totalCorrectByInput[o].accuracy;if(!e||e<=60)nn.setLearningRate(learningrate);else{let t=learningrate*(1-Math.pow(e/100,8)+.05);nn.setLearningRate(t)}}}nn.train(a,s),thehtml=" trainrun: "+trainrun+"<br> no: "+train_index,AB.msg(thehtml,4),++train_index==NOTRAIN&&(train_index=0,do_training=!1,console.log("finished trainrun: "+trainrun),trainrun++)}function testit(){let e=mnist.test_images[test_index],t=mnist.test_labels[test_index],o=[];if(useBestSlowApproach){var a=cropImage(getImage(e),LETBORDER);a.resize(PIXELS,PIXELS),o=getInputsFromImage(a)}else o=getInputs(e);test_inputs=o;let n=findMax(nn.predict(o));total_tests++,totalCorrectByInput[t].total++,n==t&&totalCorrectByInput[t].correct++,n==t&&total_correct++;let i=total_correct/total_tests*100;thehtml=" testrun: "+testrun+"<br> no: "+total_tests+" <br>  correct: "+total_correct+"<br>  score: "+greenspan+i.toFixed(2)+"</span>",thehtml+="<br/><h3>Accuracy by input</h3>";let s=0;for(s=0;s<totalCorrectByInput.length;s++)totalCorrectByInput[s].accuracy=totalCorrectByInput[s].correct/totalCorrectByInput[s].total*100;var r=totalCorrectByInput.slice();for(r.sort(function(e,t){return t.accuracy-e.accuracy}),s=0;s<r.length;s++)thehtml+=r[s].input+" : "+r[s].accuracy.toFixed(2)+"% out of "+r[s].total+" tests<br/>";AB.msg(thehtml,6),++test_index==NOTEST&&(console.log("finished testrun: "+testrun+" score: "+i.toFixed(2)),testrun++,do_training=!1,test_index=0,total_tests=0,total_correct=0)}function findAllPredictionsSorted(e){let t=0;var o=[];for(t=0;t<e.length;t++)o[t]=[t,(100*e[t]).toFixed(2)];return o.sort(function(e,t){return t[1]-e[1]}),o}function findMax(e){let t=0,o=0;for(let a=0;a<e.length;a++)e[a]>o&&(t=a,o=e[a]);return t}function draw(){if(void 0!==mnist){if(background("black"),do_training&&!mouseIsPressed){for(let e=0;e<TRAINPERSTEP;e++)trainit(0==e);for(let e=0;e<TESTPERSTEP;e++)testit()}if(demo_exists&&(drawDemo(),guessDemo()),doodle_exists&&(drawDoodle(),guessDoodle()),(uploadImageContent||uploadImage)&&(drawUpload(),guessUpload()),mouseIsPressed){var e=ZOOMPIXELS+20;mouseX<e&&mouseY<e&&pmouseX<e&&pmouseY<e&&(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 e=AB.randomIntAtoB(0,NOTEST-1);demo=mnist.test_images[e];var t=mnist.test_labels[e];thehtml="Test image no: "+e+"<br>Classification: "+t+"<br>",AB.msg(thehtml,8)}function drawDemo(){var e=getImage(demo);image(e,0,canvasheight-2*ZOOMPIXELS,ZOOMPIXELS,ZOOMPIXELS),image(e,ZOOMPIXELS+50,canvasheight-2*ZOOMPIXELS,PIXELS,PIXELS)}function guessDemo(){let e=[];if(useBestSlowApproach){var t=cropImage(getImage(demo),LETBORDER);t.resize(PIXELS,PIXELS),e=getInputsFromImage(t)}else e=getInputs(demo);demo_inputs=e;let o=findMax(nn.predict(e));thehtml=" We classify it as: "+greenspan+o+"</span>",AB.msg(thehtml,9)}function drawDoodle(){theimage=doodle.get(),image(theimage,0,0,ZOOMPIXELS,ZOOMPIXELS),image(theimage,ZOOMPIXELS+50,0,PIXELS,PIXELS)}function drawUpload(){if(uploadImage||uploadImageContent){if(!uploadImage&&uploadImageContent){var e=uploadImageContent.trim();"data"!=e.substring(0,4)&&(e="data:image/png;base64,"+e),uploadImageContent=e;var t=new Image;t.src=uploadImageContent,t.onload=function(){(uploadImage=createImage(t.width,t.height)).drawingContext.drawImage(t,0,0),uploadImage.loadPixels(),(uploadImageResized=createImage(t.width,t.height)).drawingContext.drawImage(t,0,0),uploadImageResized.loadPixels()},uploadImageContent=void 0}uploadImage&&(image(uploadImage,0,canvasheight-ZOOMPIXELS,ZOOMPIXELS,ZOOMPIXELS),image(uploadImage,ZOOMPIXELS+50,canvasheight-ZOOMPIXELS,PIXELS,PIXELS))}}function resizeKeepingAspectRatio(e,t){return e.height>e.width?e.resize(0,t):e.resize(t,0),e}function getImageOnMnistFormat(e){e.loadPixels();let t=resizeKeepingAspectRatio(cropImage(e,LETBORDER),20),o=(PIXELS-t.width)/2,a=(PIXELS-t.height)/2,n=createImage(PIXELS,PIXELS);n.loadPixels();for(let e=0;e<PIXELS;e++)for(let i=0;i<PIXELS;i++){let s=0;s=e<o||i<a?[0,0,0,255]:e>o+t.width||i>a+t.height?[0,0,0,255]:t.get(e-o,i-a),n.set(e,i,s)}return n.updatePixels(),n}function guessDoodle(){let e=doodle.get();if(useBestSlowApproach){var t=cropImage(e,LETBORDER);t.resize(PIXELS,PIXELS),inputs=getInputsFromImage(t)}else{let t=getImageOnMnistFormat(e);inputs=getInputsFromImage(t)}doodle_inputs=inputs;let o=findAllPredictionsSorted(nn.predict(inputs)),a=0;for(thehtml=" Best guess is "+greenspan+o[0][0]+"</span> and the probabilities are: <br/>",a=0;a<o.length;a++)thehtml+=o[a][0]+" : "+o[a][1]+"%<br/>";AB.msg(thehtml,2)}function guessUpload(){if(!uploadImage)return;let e=[];if(useBestSlowApproach){var t=cropImage(uploadImageResized,LETBORDER);t.resize(PIXELS,PIXELS),e=getInputsFromImage(t)}else{e=getInputsFromImage(getImageOnMnistFormat(uploadImageResized))}let o=findAllPredictionsSorted(nn.predict(e)),a=0;for(thehtml=" Best guess is "+greenspan+o[0][0]+"</span> and the probabilities are: <br/>",a=0;a<o.length;a++)thehtml+=o[a][0]+" : "+o[a][1]+"%<br/>";AB.msg(thehtml,15)}function wipeDoodle(){doodle_exists=!1,doodle.background("black")}function listToMatrix(e,t){var o,a,n=[];for(o=0,a=-1;o<e.length;o++)o%t==0&&(n[++a]=[]),n[a].push(e[o]);return n}function getMatrixUsedBoundaries(e){let t,o,a=1/0,n=1/0,i=-1/0,s=-1/0;for(t=0;t<e.length;t++)for(o=0;o<e[0].length;o++){0!=e[t][o]&&(a>t&&(a=t),i<t&&(i=t),n>o&&(n=o),s<o&&(s=o))}return{minPosX:n,minPosY:a,maxPosX:s,maxPosY:i}}function getImageFromMatrix(e){let t=createImage(e.length,e[0].length);t.loadPixels();for(let o=0;o<e.length;o++)for(let a=0;a<e[0].length;a++){let n=e[o][a],i=4*o;t.pixels[i+0]=n,t.pixels[i+1]=n,t.pixels[i+2]=n,t.pixels[i+3]=255}return t.updatePixels(),t}function cropImage(e,t){e.loadPixels();let o=[];for(let t=0;t<e.width*e.height;t++)o[t]=e.pixels[4*t];let a,n,i,s,r=getMatrixUsedBoundaries(listToMatrix(o,e.width));a=Math.max(0,r.minPosX-t),n=Math.max(0,r.minPosY-t);let l=r.maxPosX-r.minPosX,d=r.maxPosY-r.minPosY;return i=Math.min(e.width,l+t+t),s=Math.min(e.height,d+t+t),e.get(a,n,i,s)}function getInputsFromImage(e){0==e.pixels.length&&e.loadPixels();let t=[];for(let o=0;o<PIXELSSQUARED;o++)t[o]=e.pixels[4*o]/255;return t}function keyPressed(){if("S"==keyPressed.arguments[0].key||"s"==keyPressed.arguments[0].key)if(useBestSlowApproach){if(doodle_exists){let e=doodle.get();e.save("best_doodle_original");let t=cropImage(e,LETBORDER);t.resize(PIXELS,PIXELS),t.save("best_doodle_used")}if(uploadImageResized){uploadImageResized.save("best_upload_original");let e=cropImage(uploadImageResized,LETBORDER);e.resize(PIXELS,PIXELS),e.save("best_upload_used")}if(train_index){let e=getImage(mnist.train_images[train_index]);e.save("best_train_original");let t=cropImage(e,LETBORDER);t.resize(PIXELS,PIXELS),t.save("best_train_used")}if(demo_exists){let e=getImage(demo);e.save("best_demo_original");let t=cropImage(e,LETBORDER);t.resize(PIXELS,PIXELS),t.save("best_demo_used")}}else{if(doodle_exists){let e=doodle.get();e.save("mnist_doodle_original"),getImageOnMnistFormat(e).save("mnist_doodle_used")}if(uploadImageResized){uploadImageResized.save("mnist_upload_original"),getImageOnMnistFormat(uploadImageResized).save("mnist_upload_used")}if(train_index){getImage(mnist.train_images[train_index]).save("mnist_train_original_used")}if(demo_exists){getImage(demo).save("mnist_train_original_used")}}}function showInputs(e){var t="";for(let o=0;o<e.length;o++){o%PIXELS==0&&(t+="\n"),t=t+" "+e[o].toFixed(2)}console.log(t)}