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#pragma once

#include "colmap/scene/database_cache.h"
#include "colmap/util/types.h"

#include <memory>
#include <vector>

namespace colmap {

// Scene clustering approach using normalized cuts on the scene graph. The scene
// is hierarchically partitioned into overlapping clusters until a maximum
// number of images is in a leaf node.
class SceneClustering {
 public:
  struct Options {
    // Flag for hierarchical vs flat clustering
    bool is_hierarchical = true;

    // The branching factor of the hierarchical clustering.
    int branching = 2;

    // The number of overlapping images between child clusters.
    int image_overlap = 50;

    // The max related images matches to look for in a flat cluster
    int num_image_matches = 20;

    // The maximum number of images in a leaf node cluster, otherwise the
    // cluster is further partitioned using the given branching factor. Note
    // that a cluster leaf node will have at most `leaf_max_num_images +
    // overlap` images to satisfy the overlap constraint.
    int leaf_max_num_images = 500;

    bool Check() const;
  };

  struct Cluster {
    std::vector<image_t> image_ids;
    std::vector<Cluster> child_clusters;
  };

  explicit SceneClustering(const Options& options);

  void Partition(const std::vector<std::pair<image_t, image_t>>& image_pairs,
                 const std::vector<int>& num_inliers);

  const Cluster* GetRootCluster() const;
  std::vector<const Cluster*> GetLeafClusters() const;

  static SceneClustering Create(const Options& options,
                                const DatabaseCache& database_cache);

 private:
  void PartitionHierarchicalCluster(
      const std::vector<std::pair<int, int>>& edges,
      const std::vector<int>& weights,
      Cluster* cluster);

  void PartitionFlatCluster(const std::vector<std::pair<int, int>>& edges,
                            const std::vector<int>& weights);

  const Options options_;
  std::unique_ptr<Cluster> root_cluster_;
};

}  // namespace colmap
