Update onnx.js

onnx.js

@@ -128,3 +128,37 @@ function ObjectDetection() {
 }
 
 export default ObjectDetection;
+
+
+
+
+const preprocessImage = async (imageSrc) => {
+  const img = new Image();
+  img.src = imageSrc;
+  await new Promise((resolve) => (img.onload = resolve));
+
+  const canvas = document.createElement('canvas');
+  const context = canvas.getContext('2d');
+
+  // Resize to model input size
+  const modelInputWidth = 320; // Replace with your model's input width
+  const modelInputHeight = 320; // Replace with your model's input height
+  canvas.width = modelInputWidth;
+  canvas.height = modelInputHeight;
+
+  context.drawImage(img, 0, 0, modelInputWidth, modelInputHeight);
+
+  const imageData = context.getImageData(0, 0, modelInputWidth, modelInputHeight);
+
+  // Convert RGBA to RGB
+  const rgbData = new Uint8Array((imageData.data.length / 4) * 3); // 3 channels for RGB
+  for (let i = 0, j = 0; i < imageData.data.length; i += 4) {
+    rgbData[j++] = imageData.data[i];     // R
+    rgbData[j++] = imageData.data[i + 1]; // G
+    rgbData[j++] = imageData.data[i + 2]; // B
+    // Skip A (alpha) channel
+  }
+
+  // Create a tensor with shape [1, 320, 320, 3]
+  return new ort.Tensor('uint8', rgbData, [1, modelInputHeight, modelInputWidth, 3]);
+};