#ifndef PCL_TRACKING_IMPL_KLD_ADAPTIVE_PARTICLE_OMP_FILTER_H_
#define PCL_TRACKING_IMPL_KLD_ADAPTIVE_PARTICLE_OMP_FILTER_H_

#include <pcl/tracking/kld_adaptive_particle_filter_omp.h>

namespace pcl {
namespace tracking {
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename StateT>
void
KLDAdaptiveParticleFilterOMPTracker<PointInT, StateT>::setNumberOfThreads(
    unsigned int nr_threads)
{
  if (nr_threads == 0)
#ifdef _OPENMP
    threads_ = omp_get_num_procs();
#else
    threads_ = 1;
#endif
  else
    threads_ = nr_threads;
}

//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename StateT>
void
KLDAdaptiveParticleFilterOMPTracker<PointInT, StateT>::weight()
{
  if (!use_normal_) {
    // clang-format off
#pragma omp parallel for \
  default(none) \
  num_threads(threads_)
    // clang-format on
    for (int i = 0; i < particle_num_; i++)
      this->computeTransformedPointCloudWithoutNormal((*particles_)[i],
                                                      *transed_reference_vector_[i]);

    PointCloudInPtr coherence_input(new PointCloudIn);
    this->cropInputPointCloud(input_, *coherence_input);
    if (change_counter_ == 0) {
      // test change detector
      if (!use_change_detector_ || this->testChangeDetection(coherence_input)) {
        changed_ = true;
        change_counter_ = change_detector_interval_;
        coherence_->setTargetCloud(coherence_input);
        coherence_->initCompute();
        // clang-format off
#pragma omp parallel for \
  default(none) \
  num_threads(threads_)
        // clang-format on
        for (int i = 0; i < particle_num_; i++) {
          IndicesPtr indices;
          coherence_->compute(
              transed_reference_vector_[i], indices, (*particles_)[i].weight);
        }
      }
      else
        changed_ = false;
    }
    else {
      --change_counter_;
      coherence_->setTargetCloud(coherence_input);
      coherence_->initCompute();
      // clang-format off
#pragma omp parallel for \
  default(none) \
  num_threads(threads_)
      // clang-format on
      for (int i = 0; i < particle_num_; i++) {
        IndicesPtr indices;
        coherence_->compute(
            transed_reference_vector_[i], indices, (*particles_)[i].weight);
      }
    }
  }
  else {
    std::vector<IndicesPtr> indices_list(particle_num_);
    for (int i = 0; i < particle_num_; i++) {
      indices_list[i] = IndicesPtr(new pcl::Indices);
    }
    // clang-format off
#pragma omp parallel for \
  default(none) \
  shared(indices_list) \
  num_threads(threads_)
    // clang-format on
    for (int i = 0; i < particle_num_; i++) {
      this->computeTransformedPointCloudWithNormal(
          (*particles_)[i], *indices_list[i], *transed_reference_vector_[i]);
    }

    PointCloudInPtr coherence_input(new PointCloudIn);
    this->cropInputPointCloud(input_, *coherence_input);

    coherence_->setTargetCloud(coherence_input);
    coherence_->initCompute();
    // clang-format off
#pragma omp parallel for \
  default(none) \
  shared(indices_list) \
  num_threads(threads_)
    // clang-format on
    for (int i = 0; i < particle_num_; i++) {
      coherence_->compute(
          transed_reference_vector_[i], indices_list[i], (*particles_)[i].weight);
    }
  }

  normalizeWeight();
}
} // namespace tracking
} // namespace pcl

#define PCL_INSTANTIATE_KLDAdaptiveParticleFilterOMPTracker(T, ST)                     \
  template class PCL_EXPORTS pcl::tracking::KLDAdaptiveParticleFilterOMPTracker<T, ST>;

#endif
