OnnxValue[] outputValues =
          run(
              OnnxRuntime.ortApiHandle,
              nativeHandle,
              allocator.handle,
              inputNamesArray,
              inputHandles,
              inputNamesArray.length,
              outputNamesArray,
              outputNamesArray.length,
              runOptionsHandle);
      return new Result(outputNamesArray, outputValues);

export const predictModelfromUri = async (
  session: ort.InferenceSession,
  imageUri: string
): Promise<number> => {
  const imageFloat32 = await convertImageToFloat32Array(imageUri);
  const feeds: Record<string, ort.Tensor> = {};
  feeds[session.inputNames[0]] = new ort.Tensor(
    "float32",
    imageFloat32!,
    [1, 3, 224, 224]
  );
  const fetches = await session.run(feeds);
  const output: object = fetches[session.outputNames[0]].data;
  return findMaxId(Object.values(output));
};