//

// This software is released under the MIT License.

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

​

/* ===

ml5 Example

Webcam Image Classification using MobileNet and p5.js

This example uses a callback pattern to create the classifier

=== */

​

let classifier;

let video;

let langDropdown;

let selectedLang = "zh-CN";

// Before you run this example, you need to put in your own Google translate API key below</p>

// You will need to register and generate and get Google API key and also enable the Google Translate API in the Google Console.

// Read more here: https://cloud.google.com/translate/docs/quickstart-client-libraries#client-libraries-install-nodejs

const translateAPIKey = "Xxxxxxxxxxxxxxxxxx_xxxxxxxxxxxxxxxxxxxx";

// Create a new p5.speech object

// You can also control the Language, Rate, Pitch and Volumn of the voice

// Read more at http://ability.nyu.edu/p5.js-speech/

const myVoice = new p5.Speech();

​

function setup() {

  // Select a default voice and langauge

  myVoice.setLang("zh-CN");

  myVoice.setVoice(63);

​

  noCanvas();

  // Create a camera input

  video = createCapture(VIDEO);

  // Initialize the Image Classifier method with MobileNet and the video as the second argument

  classifier = ml5.imageClassifier("MobileNet", video, modelReady);

​

  langDropdown = select("#lang");

  langDropdown.changed(langChangedEvent);

}

​

function modelReady() {

  // Change the status of the model once its ready

  select("#status").html("Model Loaded");

  // Call the classifyVideo function to start classifying the video

  classifyVideo();

}

​

// Get a prediction for the current video frame

function classifyVideo() {

  classifier.classify(gotResult);

}

​

// When we get a result

function gotResult(err, results) {

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

  const resultText = results[0].label;

  select("#result").html(resultText);

  select("#probability").html(nf(results[0].confidence, 0, 2));

​

  // Get the first word of the result

  const resultWord = resultText.split(",")[0];

  // Translate the result to another language using Google translate API

  const url = `https://www.googleapis.com/language/translate/v2/?key=${translateAPIKey}&target=${selectedLang}&source=en&q=${resultWord}`;

  loadJSON(url, gotTranslation);

}

​

function gotTranslation(result) {

  if (result && result.data && result.data.translations) {

    const translatedRes = result.data.translations[0].translatedText;

    // Show the translated result

    select("#translatedResult").html(translatedRes);

    // Speak out the result

    myVoice.speak(translatedRes);

    // Continue to classify the view

    classifyVideo();

  }

}

​

function langChangedEvent() {

  selectedLang = langDropdown.value();

  // Set language

  myVoice.setLang(selectedLang);

  switch (selectedLang) {

    case "zh-CN":

      myVoice.setVoice(63);

      break;

    case "es":

      myVoice.setVoice(52);

      break;

    case "fr":

      myVoice.setVoice(54);

      break;

    default:

      myVoice.setVoice(63);

  }

}

​