Method _makeTensor

sloam/src/segmentation/inference.cpp:167–198

}

void Segmentation::_makeTensor(std::vector<std::vector<float>>& projected_data, std::vector<float>& tensor, std::vector<size_t>& invalid_idxs){
  // TODO LOAD THIS TOO
  std::vector<float> _img_means = {12.97};
  std::vector<float> _img_stds = {12.35};
  // arkansas 
  // std::vector<float> _img_means = {12.97, -0.21, -0.13, 0.26, 942.62};
  // std::vector<float> _img_stds = {12.35, 12.04, 12.95, 2.86, 1041.79};
  // kitti
  // std::vector<float> _img_means = {12.12, 10.88, 0.23, -1.04, 0.21};
  // std::vector<float> _img_stds = {12.32, 11.47, 6.91, 0.86, 0.16};

  int channel_offset = _img_h * _img_w;
  bool all_zeros = false;

  for (uint32_t pixel_id = 0; pixel_id < projected_data.size(); pixel_id++){
    // check if the pixel is invalid
    all_zeros = std::all_of(projected_data[pixel_id].begin(), projected_data[pixel_id].end(), [](int i) { return ((i==0.0f) || (isnan(i))); });
    if (all_zeros) {
      invalid_idxs.push_back(pixel_id);
    }
    for (int i = 0; i < _img_d; i++) {
      // normalize the data
      if (!all_zeros) {
        projected_data[pixel_id][i] = (projected_data[pixel_id][i] - _img_means[i]) / _img_stds[i];
      }

      int buffer_idx = channel_offset * i + pixel_id;
    //   ((float*)_hostBuffers[_inBindIdx])[buffer_idx] = projected_data[pixel_id][i];
      tensor[buffer_idx] = projected_data[pixel_id][i];
    }
  }
}

void Segmentation::_destaggerCloud(const Cloud::Ptr cloud, Cloud::Ptr& outCloud){
  bool col_valid = true;