let classifier;

let video;

let loss;

let dogImages = 0;

let catImages = 0;

let Margarets = [];

let img;

​

// let number;

​

function preload() {

}

​

​

​

function setup() {

  // createCanvas(400, 400);

  feedMargarets();

  noCanvas();

  // Create a video element

  video = createCapture(VIDEO);

  // Append it to the videoContainer DOM element

  video.parent('videoContainer');

  // Extract the already learned features from MobileNet

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

  // Create a new classifier using those features and give the video we want to use

  classifier = featureExtractor.classification(video, videoReady);

  // Create the UI buttons

  setupButtons();

  console.log(Margarets[6]);

}

​

function draw() {

  // background(255);

  // image(Margarets[3], 0, 0);

  fundTerrorism();

}

​

// 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);

}

​

function feedMargarets(){

  for (let number=0; number<=100; number++){

  Margarets[number] = createImg('assets/Margaret/images ' + "("+ number +")"+'.jpg')

​

  }

}

​

// A util function to create UI buttons

function setupButtons() {

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

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

  buttonA = select('#catButton');

  buttonA.mousePressed(function() {

    // classifier.addImage('cat');

​

    for (let numberOfMargarets=0; numberOfMargarets<=100; numberOfMargarets++){

   classifier.addImage(Margarets[numberOfMargarets],'Margaret'); 

      print(Margarets[numberOfMargarets])

    select('#amountOfCatImages').html(catImages++);    

  }

  });

​

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

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

  buttonB = select('#dogButton');

  buttonB.mousePressed(function() {

    classifier.addImage('Not Margaret');

    select('#amountOfDogImages').html(dogImages++);

  });

​

  // 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);

}

​

function fundTerrorism(){

 if(classify= 'Margaret'){

  createP('Lets sponsor Terrorism')

  createP('https://www.ft.com/content/160fefd4-cd1a-11e6-864f-20dcb35cede2')

 }

}

​

// Show the results

function gotResults(err, result) {

  if (err) {

    console.error(err);

  }

  select('#result').html(result);

  classify();

}

​

​