Javascript Machine Learning Development Tutorials, Guides & Insights

Next, we’ll load a pre-trained model (e.g., MobileNet) when the component mounts. We can use the useEffect hook for this purpose:

import React, { useState, useEffect } from 'react';
import * as tf from '@tensorflow/tfjs';
import '@tensorflow/tfjs-backend-cpu';
import '@tensorflow/tfjs-backend-webgl';

function ImageClassifier() {
  const [image, setImage] = useState(null);
  const [model, setModel] = useState(null);

  useEffect(() => {
    const loadModel = async () => {
      const loadedModel = await tf.loadGraphModel('https://path-to-model/model.json');
      setModel(loadedModel);
    };

    loadModel();
  }, []);

  const handleImageUpload = (event) => {
    const file = event.target.files[0];
    const reader = new FileReader();

    reader.onload = () => {
      setImage(reader.result);
    };

    if (file) {
      reader.readAsDataURL(file);
    }
  };

  return (
    <div>
      <input type="file" accept="image/*" onChange={handleImageUpload} />
      {image && <img src={image} alt="Uploaded" />}
    </div>
  );
}

export default ImageClassifier;