Function GetTopLabels

tensorflow/contrib/pi_examples/camera/camera.cc:258–281

Analyzes the output of the Inception graph to retrieve the highest scores and their positions in the tensor, which correspond to categories.

// Analyzes the output of the Inception graph to retrieve the highest scores and
// their positions in the tensor, which correspond to categories.
Status GetTopLabels(const std::vector<Tensor>& outputs, int how_many_labels,
                    Tensor* out_indices, Tensor* out_scores) {
  const Tensor& unsorted_scores_tensor = outputs[0];
  auto unsorted_scores_flat = unsorted_scores_tensor.flat<float>();
  std::vector<std::pair<int, float>> scores;
  for (int i = 0; i < unsorted_scores_flat.size(); ++i) {
    scores.push_back(std::pair<int, float>({i, unsorted_scores_flat(i)}));
  }
  std::sort(scores.begin(), scores.end(),
            [](const std::pair<int, float>& left,
               const std::pair<int, float>& right) {
              return left.second > right.second;
            });
  scores.resize(how_many_labels);
  Tensor sorted_indices(tensorflow::DT_INT32, {scores.size()});
  Tensor sorted_scores(tensorflow::DT_FLOAT, {scores.size()});
  for (int i = 0; i < scores.size(); ++i) {
    sorted_indices.flat<int>()(i) = scores[i].first;
    sorted_scores.flat<float>()(i) = scores[i].second;
  }
  *out_indices = sorted_indices;
  *out_scores = sorted_scores;
  return Status::OK();
}

// Takes a file name, and loads a list of labels from it, one per line, and
// returns a vector of the strings. It pads with empty strings so the length