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machine learning image classification

Jerome Scott answered on December 13, 2022 Popularity 10/10 Helpfulness 1/10

answer machine learning image classification

machine learning image classification

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// Initialize the Image Classifier method with MobileNet. A callback needs to be passed.
// Create a YOLO method
const yolo = ml5.YOLO(modelReady);
let img;
let objects = [];
let status;

function setup() {
  createCanvas(640, 420);
  img = createImg('images/cat2.JPG', imageReady);
  img.hide();
  img.size(640, 420);

}

// Change the status when the model loads.
function modelReady() {
  console.log("model Ready!")
  status = true;
}

// When the image has been loaded,
// get a prediction for that image
function imageReady() {
  console.log('Detecting') 
  yolo.detect(img, gotResult);
}

// A function to run when we get any errors and the results
function gotResult(err, results) {
  if (err) {
    console.log(err);
  }
  console.log(results)
  objects = results;
}


function draw() {
  // unless the model is loaded, do not draw anything to canvas
  if (status != undefined) {
    image(img, 0, 0)

    for (let i = 0; i < objects.length; i++) {
      noStroke();
      fill(0, 255, 0);
      text(objects[i].label + " " + nfc(objects[i].confidence * 100.0, 2) + "%", objects[i].x * width + 5, objects[i].y * height + 15);
      noFill();
      strokeWeight(4);
      stroke(0, 255, 0);
      rect(objects[i].x * width, objects[i].y * height, objects[i].w * width, objects[i].h * height);
    }
  }
}

Popularity 10/10 Helpfulness 1/10 Language javascript

Source: editor.p5js.org

Tags: image-classification javascript machine-learning

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Contributed on Dec 13 2022

Jerome Scott

0 Answers Avg Quality 2/10

machine learning image classification

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