outputsToNMSPredictionsYoloV8 method

List<ResultObjectDetection> outputsToNMSPredictionsYoloV8(List<double> outputs)

Implementation

List<ResultObjectDetection> outputsToNMSPredictionsYoloV8(
    List<double> outputs) {
  List<ResultObjectDetection> results = [];
  for (int i = 0; i < outputRow; i++) {
    double x = outputs[i];
    double y = outputs[outputRow + i];
    double w = outputs[2 * outputRow + i];
    double h = outputs[3 * outputRow + i];

    double left = (x - w / 2);
    double top = (y - h / 2);
    double right = (x + w / 2);
    double bottom = (y + h / 2);

    double max = outputs[4 * outputRow + i];
    int cls = 0;
    for (int j = 4; j < outputColumn; j++) {
      if (outputs[j * outputRow + i] > max) {
        max = outputs[j * outputRow + i];
        cls = j - 4;
      }
    }

    if (max > scoreThreshold) {
      PyTorchRect rect = PyTorchRect(
        left: left / imageWidth,
        top: top / imageHeight,
        right: right / imageWidth,
        bottom: bottom / imageHeight,
        width: w / imageWidth,
        height: h / imageHeight,
      );
      ResultObjectDetection result =
          ResultObjectDetection(classIndex: cls, score: max, rect: rect);

      results.add(result);
    }
  }

  print("Result length before processing ${results.length}");
  return nonMaxSuppression(results); // Please implement this method
}