ml5/demos/05-image-classifier-vanilla-js.html

<!DOCTYPE html>
<html lang="en" class="loading">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Image Classifier</title>
  <link rel="stylesheet" href="css/normalize.css">
  <link rel="stylesheet" href="css/style.css">
  <style>
    .hidden {
      display: none;
    }
    .loading .display-loading {
      display: block;
    }
    .running .display-running {
      display: block;
    }
    #results {
      background-color: white;
      width: 20rem;
      min-height: 6rem;
      display: none;
      justify-content: center;
      align-items: center;
      font-weight: bold;
      font-size: 2rem;
    }
    .running #results {
      display: flex;
    }
  </style>
</head>
<body>
  <h1 class="h1">Image Classifier</h1>
  <h2 id="state"></h2>
  <canvas id="canvas" class="fancy-shadow hidden display-running"></canvas>
  <div id="results" class="fancy-shadow hidden display-running"></div>
  <script src="https://unpkg.com/ml5@1/dist/ml5.js"></script>
  <script>

    const $canvas = document.querySelector('#canvas');
    const $results = document.querySelector('#results');
    const $state = document.querySelector('#state');

    let video, ctx;
    let classifier;
    let classificationResults = [];

    const STATE_LOADING = "loading";
    const STATE_RUNNING = "running";
    const ALL_STATES = [STATE_LOADING, STATE_RUNNING];
    let state = STATE_LOADING;

    const setState = (value) => {
      console.log('setState', value);
      state = value;
      $state.textContent = state;
      document.documentElement.classList.remove(...ALL_STATES);
      document.documentElement.classList.add(state);
    };

    const preload = async () => {
      setState(STATE_LOADING);
      requestAnimationFrame(draw);
      classifier = ml5.imageClassifier("MobileNet");
      await classifier.ready;
      console.log('model ready');
      setup();
    }

    const setup = async () => {
      console.log('setup');
      ctx = $canvas.getContext('2d');
      // create a video stream - specify a fixed size
      const stream = await navigator.mediaDevices.getUserMedia({ video: {
        width: 640,
        height: 480
      } });
      video = document.createElement('video');
      video.srcObject = stream;
      video.play();
      // set canvas & video size
      $canvas.width = video.width = 640;
      $canvas.height = video.height = 480;
      // start detecting poses - use the canvas instead of the video (BlazePose compatibility)
      // classifier.classify(video, gotResults);
      classifier.classifyStart(video, (results) => {
        // store in a global
        classificationResults = results;
      });
      // start the app
      setState(STATE_RUNNING);
    }

    const draw = () => {
      if (state === STATE_RUNNING) {
        ctx.drawImage(video, 0, 0, $canvas.width, $canvas.height);
        $results.innerHTML = classificationResults
          .map(result => `${result.label} (${result.confidence.toFixed(2)})`)
          .join('<br>');
      }
      requestAnimationFrame(draw);
    }

    preload();
  </script>
</body>
</html>