sflite/services/onnx/runTinyYoloV...

import * as ort from "onnxruntime-react-native";
import { loadOnnxSession } from "./loadModel";

/**
 * TinyYOLOv2 (common export) expects float32 input NCHW [1,3,416,416]
 * output is typically [1, 125, 13, 13] (5 boxes * (5 + 20 classes) = 125)
 */
export async function runTinyYoloV2Dummy() {
  const session = await loadOnnxSession();

  const inputName = session.inputNames[0];
  const outputName = session.outputNames[0];

  // Standard Tiny YOLOv2 input size
  const W = 416, H = 416;
  const input = new Float32Array(1 * 3 * H * W).fill(0.5); // dummy data

  const feeds: Record<string, ort.Tensor> = {};
  feeds[inputName] = new ort.Tensor("float32", input, [1, 3, H, W]);

  const results = await session.run(feeds);
  const out = results[outputName];

  return {
    inputName,
    outputName,
    dims: out.dims,          // expected [1,125,13,13]
    dataLen: out.data.length // should match product(dims)
  };
}