onnxruntime-node test

nodejs/onnxruntime.js

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+const fs = require('fs');
+const sharp = require('sharp');
+const ort = require('onnxruntime-node');
+
+(async () => {
+  try {
+    // Step 1: Load and preprocess the image
+    const imageBuffer = await sharp('./training_images/shirt/00e745c9-97d9-429d-8c3f-d3db7a2d2991.jpg')
+      .resize(128, 128) // Resize to 128x128
+      .raw() // Get raw pixel data
+      .toBuffer();
+
+    // Convert to Float32 and normalize pixel values to [0, 1]
+    const imgArray = Float32Array.from(imageBuffer).map(value => value / 255.0);
+
+    // Add batch dimension [1, 128, 128, 3]
+    const inputTensor = new ort.Tensor('float32', imgArray, [1, 128, 128, 3]);
+
+    // Step 2: Load ONNX model
+    const session = await ort.InferenceSession.create('./saved-model/model.onnx');
+
+    // Step 3: Run inference
+    const results = await session.run({ [session.inputNames[0]]: inputTensor });
+
+    console.log('Inference outputs:', results[session.outputNames[0]]);
+  } catch (err) {
+    console.error('Error:', err);
+  }
+})();