64 lines
1.7 KiB
JavaScript
64 lines
1.7 KiB
JavaScript
const tf = require('@tensorflow/tfjs-node');
|
|
const fs = require('fs');
|
|
const path = require('path');
|
|
|
|
// Path ke model
|
|
const modelPath = path.join(
|
|
__dirname,
|
|
'../resources/ResNet-50_tomato-leaf-disease-tfjs_v8/model.json'
|
|
);
|
|
|
|
let model;
|
|
|
|
// Fungsi untuk memuat model
|
|
const loadModel = async () => {
|
|
try {
|
|
model = await tf.loadLayersModel(`file://${modelPath}`);
|
|
console.log('Model loaded successfully.');
|
|
} catch (err) {
|
|
console.error('Error loading model:', err);
|
|
throw new Error('Model loading failed.');
|
|
}
|
|
};
|
|
|
|
// Memuat model saat aplikasi dimulai
|
|
loadModel();
|
|
|
|
const preprocessImage = async (imagePath) => {
|
|
const imageBuffer = fs.readFileSync(imagePath);
|
|
let tensor = tf.node.decodeImage(imageBuffer, 3);
|
|
tensor = tf.image.resizeBilinear(tensor, [224, 224]);
|
|
tensor = tensor.expandDims(0);
|
|
//tensor = tensor.toFloat().div(tf.scalar(255.0));
|
|
return tensor;
|
|
};
|
|
|
|
// Fungsi untuk mengklasifikasikan gambar
|
|
const classifyImage = async (imagePath) => {
|
|
try {
|
|
const classes = [
|
|
'bacterial_spot',
|
|
'healthy',
|
|
'late_blight',
|
|
'leaf_curl_virus',
|
|
'leaf_mold',
|
|
'mosaic_virus',
|
|
'septoria_leaf_spot',
|
|
];
|
|
|
|
const tensor = await preprocessImage(imagePath);
|
|
const predictions = model.predict(tensor);
|
|
const predictedClassIndex = predictions.argMax(-1).dataSync()[0];
|
|
|
|
// Ambil nama kelas berdasarkan indeks
|
|
const predictedClassName = classes[predictedClassIndex];
|
|
|
|
return { index: predictedClassIndex, class: predictedClassName };
|
|
} catch (err) {
|
|
console.error('Error during classification:', err);
|
|
throw new Error('Error during classification.');
|
|
}
|
|
};
|
|
|
|
module.exports = { classifyImage };
|