Inspired by "Trainable Camera", Created by Andreas Refsgaard - https://editor.p5js.org/AndreasRef/sketches/BynhuHsqX

*/

​

let video;

let myResults

let resultLabel

let myColor;

let detector

let detections=[]

​

​

let featureExtractor;

let classifier;

let loss; 

let imagesOfA = 0;

let imagesOfB = 0;

let classificationResult;

let confidence = 0;

​

let pg;

let lastSnapShot;

​

let timer = 0;

let showLatestPhoto = false;

​

let nCurrentClass = 0;

let shutter; 

​

​

function setup() {

  createCanvas(640, 480);

  pixelDensity(1);

​

  video = createCapture(VIDEO);

  video.size(640, 480);

  video.hide();

  speech = new p5.Speech(voiceReady); //callback, speech synthesis object

  // speech.onLOad = voiceReady;

  speech.started(startSpeaking);

  //speech.ended(endSpeaking);

​

  function startSpeaking() {

    background(0, 255, 0);

  }

​

  function voiceReady() {

    console.log(speech.voices);

  }

  // input name field

  // myButton = createButton("Create Label");

  // myButton.position(512, 120);

  // // myButton.mousePressed(getText);

  // myButton.elt.style.fontSize = "20px";

​

  // myInput = createInput("Relplace this text with your name?");

  // myInput.position(0, 300);

  // myInput.size(500);

  // myInput.elt.style.fontSize = "20px";

  // Extract the already learned features from MobileNet

  featureExtractor = ml5.featureExtractor('MobileNet', modelReady);

  //Specify the number of classes/labels

  const options = { numLabels: 2 }; 

  classifier = featureExtractor.classification(video, options);

​

  shutter = loadSound('shutter.wav');

  pg = createGraphics(width, height);

  setupButtons();

}

​

function gotDetections(error, results) {

  if (error) {

    console.error(error);

  }

  detections = results;

  detector.detect(video, gotDetections);

}

​

// function getText() {

//   const inputValue = myInput.value();

//   console.log("myinput", inputValue);

//   if (!inputValue || inputValue.length <= 0) {

//     return;

//   }

//   // set label value to inputted text

// }

​

function draw() {

  background(122);

  image(video, 0, 0);

  if (classificationResult == 'A') {

    nCurrentClass = 0;

  } else if (classificationResult == 'B') {

    nCurrentClass++;

  }

​

  //Show the last image taken for a short period

  if (showLatestPhoto) {

    image(pg, 0, 0);

  }

​

  //Flash effect

  if (timer < 5) {

    background(timer * 25 + 130);

  } else if (timer < 8) {

    background(255);

  }

​

  if (timer > 100) {

    showLatestPhoto = false;

  }

  timer++;

​

  if (classificationResult == 'B' && nCurrentClass > 50) {

    takePicture();

    speech.speak('CHEATING!! Alert CHEATING Alert')

    speech.speak('Student in seat 3B is engaging in foulplay. Warning! Remove from exam room. Warning!')

  }

}

​

function takePicture() {

  save('myCanvas.jpg'); //Does not work in iFrames, but should work if you run the code locally outside of the p5js web editor

  shutter.play();

  pg.image(video, 0, 0);

  timer = 0;

  showLatestPhoto = true;

  nCurrentClass = 0;

}

​

// A function to be called when the model has been loaded

function modelReady() {

  select('#modelStatus').html('Base Model (MobileNet) loaded!');

}

​

// A function to be called when the video has loaded

function videoReady() {

  select('#videoStatus').html('Video ready!');

}

​

// Classify the current frame.

function classify() {

  classifier.classify(gotResults);

}

​

// A util function to create UI buttons

function setupButtons() {

  // When the A button is pressed, add the current frame

  // from the video with a label of "A" to the classifier

  buttonA = select('#ButtonA');

  buttonA.mousePressed(function() {

    classifier.addImage('A');

    select('#amountOfAImages').html(imagesOfA++);

  });

​

  // When the B button is pressed, add the current frame

  // from the video with a label of "B" to the classifier

  buttonB = select('#ButtonB');

  buttonB.mousePressed(function() {

    classifier.addImage('B');

    select('#amountOfBImages').html(imagesOfB++);

  });

​

// Train Button

  train = select('#train');

  train.mousePressed(function() {

    classifier.train(function(lossValue) {

      if (lossValue) {

        loss = lossValue;

        select('#loss').html('Loss: ' + loss);

      } else {

        select('#loss').html('Done Training! Final Loss: ' + loss);

      }

    });

  });

​

  // Predict Button

  buttonPredict = select('#buttonPredict');

  buttonPredict.mousePressed(classify);

  // Save model

  saveBtn = select('#save');

  saveBtn.mousePressed(function() {

    classifier.save();

  });

​

  // Load model

  loadBtn = select('#load');

  loadBtn.changed(function() {

    classifier.load(loadBtn.elt.files, function(){

      select('#modelStatus').html('Custom Model Loaded!');

    });

  });

}

​

// Show the results

function gotResults(err, result) {

  // Display any error

  if (err) {

    console.error(err);

  }

  select('#result').html(result[0].label);

  select('#confidence').html(nf(result[0].confidence,0,2));

​

  classificationResult = result[0].label;

  confidence = result[0].confidence;

  classify();

}