//

// This software is released under the MIT License.

// https://opensource.org/licenses/MIT

​

/* ===

ml5 Example

Webcam Image Classification using a pre-trianed customized model and p5.js

This example uses p5 preload function to create the classifier

=== */

​

const checkpoint = 'https://storage.googleapis.com/tm-pro-a6966.appspot.com/eyeo-test-yining/model.json';

let classifier;

let video;

let resultsP;

​

function preload() {

  // Create a camera input

  video = createCapture(VIDEO);

  // Initialize the Image Classifier method with a pre-trained customized model and the video as the second argument

  classifier = ml5.imageClassifier(checkpoint);

}

​

function setup() {

  noCanvas();

  // ml5 also supports using callback pattern to create the classifier

  // classifier = ml5.imageClassifier(checkpoint, video, modelReady);

  // If you would like to load the model from local files

  // classifier = ml5.imageClassifier('model/image-model.json', video, modelReady);

  resultsP = createP('Loading model and video...');

  classifyVideo();

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  classifier.classify(video, gotResult);

}

​

// If you use callback pattern to create the classifier, you can use the following callback function

// function modelReady() {

//   console.log('Model Ready');

//   classifyVideo();

// }

​

// When we get a result

function gotResult(err, results) {

  // The results are in an array ordered by confidence.

  resultsP.html(`Label: ${results[0].label  } ${nf(results[0].confidence, 0, 2)}`);

  classifyVideo();

}

​