// Copyright (c), ETH Zurich and UNC Chapel Hill.
// All rights reserved.
//
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// modification, are permitted provided that the following conditions are met:
//
//     * Redistributions of source code must retain the above copyright
//       notice, this list of conditions and the following disclaimer.
//
//     * Redistributions in binary form must reproduce the above copyright
//       notice, this list of conditions and the following disclaimer in the
//       documentation and/or other materials provided with the distribution.
//
//     * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
//       its contributors may be used to endorse or promote products derived
//       from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// POSSIBILITY OF SUCH DAMAGE.

#include "colmap/mvs/fusion.h"

#include "colmap/math/math.h"
#include "colmap/util/eigen_alignment.h"
#include "colmap/util/endian.h"
#include "colmap/util/file.h"
#include "colmap/util/misc.h"
#include "colmap/util/threading.h"
#include "colmap/util/timer.h"

#include <fstream>
#include <unordered_set>

#include <Eigen/Geometry>

namespace colmap {
namespace mvs {
namespace internal {

// Use the sparse model to find most connected image that has not yet been
// fused. This is used as a heuristic to ensure that the workspace cache reuses
// already cached images as efficient as possible.
int FindNextImage(const std::vector<std::vector<int>>& overlapping_images,
                  const std::vector<char>& used_images,
                  const std::vector<char>& fused_images,
                  const int prev_image_idx) {
  THROW_CHECK_EQ(used_images.size(), fused_images.size());

  for (const auto image_idx : overlapping_images.at(prev_image_idx)) {
    if (used_images.at(image_idx) && !fused_images.at(image_idx)) {
      return image_idx;
    }
  }

  // If none of the overlapping images are not yet fused, simply return the
  // first image that has not yet been fused.
  for (size_t image_idx = 0; image_idx < fused_images.size(); ++image_idx) {
    if (used_images[image_idx] && !fused_images[image_idx]) {
      return image_idx;
    }
  }

  return -1;
}

}  // namespace internal

void StereoFusionOptions::Print() const {
#define PrintOption(option) LOG(INFO) << #option ": " << (option);
  LOG_HEADING2("StereoFusion::Options");
  PrintOption(mask_path);
  PrintOption(max_image_size);
  PrintOption(min_num_pixels);
  PrintOption(max_num_pixels);
  PrintOption(max_traversal_depth);
  PrintOption(max_reproj_error);
  PrintOption(max_depth_error);
  PrintOption(max_normal_error);
  PrintOption(check_num_images);
  PrintOption(use_cache);
  PrintOption(cache_size);
  const auto& bbox_min = bounding_box.first.transpose().eval();
  const auto& bbox_max = bounding_box.second.transpose().eval();
  PrintOption(bbox_min);
  PrintOption(bbox_max);
#undef PrintOption
}

bool StereoFusionOptions::Check() const {
  CHECK_OPTION_GE(min_num_pixels, 0);
  CHECK_OPTION_LE(min_num_pixels, max_num_pixels);
  CHECK_OPTION_GT(max_traversal_depth, 0);
  CHECK_OPTION_GE(max_reproj_error, 0);
  CHECK_OPTION_GE(max_depth_error, 0);
  CHECK_OPTION_GE(max_normal_error, 0);
  CHECK_OPTION_GT(check_num_images, 0);
  CHECK_OPTION_GT(cache_size, 0);
  return true;
}

StereoFusion::StereoFusion(const StereoFusionOptions& options,
                           const std::filesystem::path& workspace_path,
                           const std::string& workspace_format,
                           const std::string& pmvs_option_name,
                           const std::string& input_type)
    : options_(options),
      workspace_path_(workspace_path),
      workspace_format_(workspace_format),
      pmvs_option_name_(pmvs_option_name),
      input_type_(input_type),
      max_squared_reproj_error_(options_.max_reproj_error *
                                options_.max_reproj_error),
      min_cos_normal_error_(std::cos(DegToRad(options_.max_normal_error))) {
  THROW_CHECK(options_.Check());
}

const std::vector<PlyPoint>& StereoFusion::GetFusedPoints() const {
  return fused_points_;
}

const std::vector<std::vector<int>>& StereoFusion::GetFusedPointsVisibility()
    const {
  return fused_points_visibility_;
}

void StereoFusion::Run() {
  Timer run_timer;
  run_timer.Start();

  fused_points_.clear();
  fused_points_visibility_.clear();

  options_.Print();

  LOG(INFO) << "Reading workspace...";

  Workspace::Options workspace_options;

  auto workspace_format_lower_case = workspace_format_;
  StringToLower(&workspace_format_lower_case);
  if (workspace_format_lower_case == "pmvs") {
    workspace_options.stereo_folder =
        StringPrintf("stereo-%s", pmvs_option_name_.c_str());
  }

  workspace_options.num_threads = options_.num_threads;
  workspace_options.max_image_size = options_.max_image_size;
  workspace_options.image_as_rgb = true;
  workspace_options.cache_size = options_.cache_size;
  workspace_options.workspace_path = workspace_path_;
  workspace_options.workspace_format = workspace_format_;
  workspace_options.input_type = input_type_;

  const auto image_names = ReadTextFileLines(
      workspace_path_ / workspace_options.stereo_folder / "fusion.cfg");
  int num_threads = 1;
  if (options_.use_cache) {
    workspace_ = std::make_unique<CachedWorkspace>(workspace_options);
  } else {
    workspace_ = std::make_unique<Workspace>(workspace_options);
    workspace_->Load(image_names);
    num_threads = GetEffectiveNumThreads(options_.num_threads);
  }

  if (CheckIfStopped()) {
    run_timer.PrintMinutes();
    return;
  }

  LOG(INFO) << "Reading configuration...";

  const auto& model = workspace_->GetModel();

  const double kMinTriangulationAngle = 0;
  if (model.GetMaxOverlappingImagesFromPMVS().empty()) {
    overlapping_images_ = model.GetMaxOverlappingImages(
        options_.check_num_images, kMinTriangulationAngle);
  } else {
    overlapping_images_ = model.GetMaxOverlappingImagesFromPMVS();
  }

  task_fused_points_.resize(num_threads);
  task_fused_points_visibility_.resize(num_threads);

  used_images_.resize(model.images.size(), false);
  fused_images_.resize(model.images.size(), false);
  fused_pixel_masks_.resize(model.images.size());
  depth_map_sizes_.resize(model.images.size());
  bitmap_scales_.resize(model.images.size());
  P_.resize(model.images.size());
  inv_P_.resize(model.images.size());
  inv_R_.resize(model.images.size());

  for (const auto& image_name : image_names) {
    const int image_idx = model.GetImageIdx(image_name);

    if (!workspace_->HasBitmap(image_idx) ||
        !workspace_->HasDepthMap(image_idx) ||
        !workspace_->HasNormalMap(image_idx)) {
      LOG(WARNING) << StringPrintf(
          "Ignoring image %s, because input does not exist.",
          image_name.c_str());
      continue;
    }

    const auto& image = model.images.at(image_idx);
    const auto& depth_map = workspace_->GetDepthMap(image_idx);

    used_images_.at(image_idx) = true;

    InitFusedPixelMask(image_idx, depth_map.GetWidth(), depth_map.GetHeight());

    depth_map_sizes_.at(image_idx) =
        std::make_pair(depth_map.GetWidth(), depth_map.GetHeight());

    bitmap_scales_.at(image_idx) = std::make_pair(
        static_cast<float>(depth_map.GetWidth()) / image.GetWidth(),
        static_cast<float>(depth_map.GetHeight()) / image.GetHeight());

    Eigen::Matrix<float, 3, 3, Eigen::RowMajor> K =
        Eigen::Map<const Eigen::Matrix<float, 3, 3, Eigen::RowMajor>>(
            image.GetK());
    K(0, 0) *= bitmap_scales_.at(image_idx).first;
    K(0, 2) *= bitmap_scales_.at(image_idx).first;
    K(1, 1) *= bitmap_scales_.at(image_idx).second;
    K(1, 2) *= bitmap_scales_.at(image_idx).second;

    ComposeProjectionMatrix(
        K.data(), image.GetR(), image.GetT(), P_.at(image_idx).data());
    ComposeInverseProjectionMatrix(
        K.data(), image.GetR(), image.GetT(), inv_P_.at(image_idx).data());
    inv_R_.at(image_idx) =
        Eigen::Map<const Eigen::Matrix<float, 3, 3, Eigen::RowMajor>>(
            image.GetR())
            .transpose();
  }

  LOG(INFO) << StringPrintf("Starting fusion with %d threads", num_threads);
  ThreadPool thread_pool(num_threads);

  // Using a row stride of 10 to avoid starting parallel processing in rows that
  // are too close to each other which may lead to duplicated work, since nearby
  // pixels are likely to get fused into the same point.
  const int kRowStride = 10;
  auto ProcessImageRows = [&, this](const int row_start,
                                    const int height,
                                    const int width,
                                    const int image_idx,
                                    const Mat<char>& fused_pixel_mask) {
    const int row_end = std::min(height, row_start + kRowStride);
    for (int row = row_start; row < row_end; ++row) {
      for (int col = 0; col < width; ++col) {
        if (fused_pixel_mask.Get(row, col) > 0) {
          continue;
        }
        const int thread_id = thread_pool.GetThreadIndex();
        Fuse(thread_id, image_idx, row, col);
      }
    }
  };

  size_t num_fused_images = 0;
  size_t total_fused_points = 0;
  for (int image_idx = 0; image_idx >= 0;
       image_idx = internal::FindNextImage(
           overlapping_images_, used_images_, fused_images_, image_idx)) {
    if (CheckIfStopped()) {
      break;
    }

    Timer timer;
    timer.Start();

    LOG(INFO) << StringPrintf("Fusing image [%d/%d] with index %d",
                              num_fused_images + 1,
                              model.images.size(),
                              image_idx)
              << std::flush;

    const int width = depth_map_sizes_.at(image_idx).first;
    const int height = depth_map_sizes_.at(image_idx).second;
    const auto& fused_pixel_mask = fused_pixel_masks_.at(image_idx);

    for (int row_start = 0; row_start < height; row_start += kRowStride) {
      thread_pool.AddTask(ProcessImageRows,
                          row_start,
                          height,
                          width,
                          image_idx,
                          fused_pixel_mask);
    }
    thread_pool.Wait();

    num_fused_images += 1;
    fused_images_.at(image_idx) = true;

    total_fused_points = 0;
    for (const auto& task_fused_points : task_fused_points_) {
      total_fused_points += task_fused_points.size();
    }
    LOG(INFO) << StringPrintf(
        " in %.3fs (%d points)", timer.ElapsedSeconds(), total_fused_points);
  }

  fused_points_.reserve(total_fused_points);
  fused_points_visibility_.reserve(total_fused_points);
  for (size_t thread_id = 0; thread_id < task_fused_points_.size();
       ++thread_id) {
    fused_points_.insert(fused_points_.end(),
                         task_fused_points_[thread_id].begin(),
                         task_fused_points_[thread_id].end());
    task_fused_points_[thread_id].clear();

    fused_points_visibility_.insert(
        fused_points_visibility_.end(),
        task_fused_points_visibility_[thread_id].begin(),
        task_fused_points_visibility_[thread_id].end());
    task_fused_points_visibility_[thread_id].clear();
  }

  if (fused_points_.empty()) {
    LOG(WARNING)
        << "Could not fuse any points. This is likely caused by "
           "incorrect settings - filtering must be enabled for the last "
           "call to patch match stereo.";
  }

  LOG(INFO) << "Number of fused points: " << fused_points_.size();
  run_timer.PrintMinutes();
}

void StereoFusion::InitFusedPixelMask(int image_idx,
                                      size_t width,
                                      size_t height) {
  Bitmap mask;
  Mat<char>& fused_pixel_mask = fused_pixel_masks_.at(image_idx);
  const std::string mask_image_name =
      workspace_->GetModel().GetImageName(image_idx);
  auto mask_path = options_.mask_path / (mask_image_name + ".png");
  if (!ExistsFile(mask_path) && HasFileExtension(mask_image_name, ".png")) {
    mask_path = options_.mask_path / mask_image_name;
  }
  fused_pixel_mask = Mat<char>(width, height, 1);
  if (!options_.mask_path.empty() && ExistsFile(mask_path) &&
      mask.Read(mask_path, false)) {
    mask.Rescale(static_cast<int>(width),
                 static_cast<int>(height),
                 Bitmap::RescaleFilter::kBox);
    for (size_t row = 0; row < height; ++row) {
      for (size_t col = 0; col < width; ++col) {
        const auto color = mask.GetPixel(col, row);
        fused_pixel_mask.Set(row, col, (!color || color->r == 0) ? 1 : 0);
      }
    }
  } else {
    fused_pixel_mask.Fill(0);
  }
}

void StereoFusion::Fuse(const int thread_id,
                        const int image_idx,
                        const int row,
                        const int col) {
  // Next points to fuse.
  std::vector<FusionData> fusion_queue;
  fusion_queue.emplace_back(image_idx, row, col, 0);

  Eigen::Vector4f fused_ref_point = Eigen::Vector4f::Zero();
  Eigen::Vector3f fused_ref_normal = Eigen::Vector3f::Zero();

  // Points of different pixels of the currently point to be fused.
  std::vector<float> fused_point_x;
  std::vector<float> fused_point_y;
  std::vector<float> fused_point_z;
  std::vector<float> fused_point_nx;
  std::vector<float> fused_point_ny;
  std::vector<float> fused_point_nz;
  std::vector<uint8_t> fused_point_r;
  std::vector<uint8_t> fused_point_g;
  std::vector<uint8_t> fused_point_b;
  std::unordered_set<int> fused_point_visibility;

  while (!fusion_queue.empty()) {
    const auto data = fusion_queue.back();
    const int image_idx = data.image_idx;
    const int row = data.row;
    const int col = data.col;
    const int traversal_depth = data.traversal_depth;

    fusion_queue.pop_back();

    // Check if pixel already fused.
    auto& fused_pixel_mask = fused_pixel_masks_.at(image_idx);
    if (fused_pixel_mask.Get(row, col) > 0) {
      continue;
    }

    const auto& depth_map = workspace_->GetDepthMap(image_idx);
    const float depth = depth_map.Get(row, col);

    // Pixels with negative depth are filtered.
    if (depth <= 0.0f) {
      continue;
    }

    // If the traversal depth is greater than zero, the initial reference
    // pixel has already been added and we need to check for consistency.
    if (traversal_depth > 0) {
      // Project reference point into current view.
      const Eigen::Vector3f proj = P_.at(image_idx) * fused_ref_point;

      // Depth error of reference depth with current depth.
      const float depth_error = std::abs((proj(2) - depth) / depth);
      if (depth_error > options_.max_depth_error) {
        continue;
      }

      // Reprojection error reference point in the current view.
      const float col_diff = proj(0) / proj(2) - col;
      const float row_diff = proj(1) / proj(2) - row;
      const float squared_reproj_error =
          col_diff * col_diff + row_diff * row_diff;
      if (squared_reproj_error > max_squared_reproj_error_) {
        continue;
      }
    }

    // Determine normal direction in global reference frame.
    const auto& normal_map = workspace_->GetNormalMap(image_idx);
    const Eigen::Vector3f normal =
        inv_R_.at(image_idx) * Eigen::Vector3f(normal_map.Get(row, col, 0),
                                               normal_map.Get(row, col, 1),
                                               normal_map.Get(row, col, 2));

    // Check for consistent normal direction with reference normal.
    if (traversal_depth > 0) {
      const float cos_normal_error = fused_ref_normal.dot(normal);
      if (cos_normal_error < min_cos_normal_error_) {
        continue;
      }
    }

    // Determine 3D location of current depth value.
    const Eigen::Vector3f xyz =
        inv_P_.at(image_idx) *
        Eigen::Vector4f(col * depth, row * depth, depth, 1.0f);

    // Read the color of the pixel.
    const auto& bitmap_scale = bitmap_scales_.at(image_idx);
    const auto color =
        workspace_->GetBitmap(image_idx)
            .InterpolateNearestNeighbor(col / bitmap_scale.first,
                                        row / bitmap_scale.second)
            .value_or(BitmapColor<uint8_t>(0));

    // Set the current pixel as visited.
    fused_pixel_mask.Set(row, col, 1);

    // Pixels out of bounds are filtered
    if (xyz(0) < options_.bounding_box.first(0) ||
        xyz(1) < options_.bounding_box.first(1) ||
        xyz(2) < options_.bounding_box.first(2) ||
        xyz(0) > options_.bounding_box.second(0) ||
        xyz(1) > options_.bounding_box.second(1) ||
        xyz(2) > options_.bounding_box.second(2)) {
      continue;
    }

    // Accumulate statistics for fused point.
    fused_point_x.push_back(xyz(0));
    fused_point_y.push_back(xyz(1));
    fused_point_z.push_back(xyz(2));
    fused_point_nx.push_back(normal(0));
    fused_point_ny.push_back(normal(1));
    fused_point_nz.push_back(normal(2));
    fused_point_r.push_back(color.r);
    fused_point_g.push_back(color.g);
    fused_point_b.push_back(color.b);
    fused_point_visibility.insert(image_idx);

    // Remember the first pixel as the reference.
    if (traversal_depth == 0) {
      fused_ref_point = Eigen::Vector4f(xyz(0), xyz(1), xyz(2), 1.0f);
      fused_ref_normal = normal;
    }

    if (fused_point_x.size() >= static_cast<size_t>(options_.max_num_pixels)) {
      break;
    }

    if (traversal_depth >= options_.max_traversal_depth - 1) {
      continue;
    }

    for (const auto next_image_idx : overlapping_images_.at(image_idx)) {
      if (!used_images_.at(next_image_idx) ||
          fused_images_.at(next_image_idx)) {
        continue;
      }

      const Eigen::Vector3f next_proj =
          P_.at(next_image_idx) * xyz.homogeneous();
      const int next_col =
          static_cast<int>(std::round(next_proj(0) / next_proj(2)));
      const int next_row =
          static_cast<int>(std::round(next_proj(1) / next_proj(2)));

      const auto& depth_map_size = depth_map_sizes_.at(next_image_idx);
      if (next_col < 0 || next_row < 0 || next_col >= depth_map_size.first ||
          next_row >= depth_map_size.second) {
        continue;
      }
      fusion_queue.emplace_back(
          next_image_idx, next_row, next_col, traversal_depth + 1);
    }
  }

  const size_t num_pixels = fused_point_x.size();
  if (num_pixels >= static_cast<size_t>(options_.min_num_pixels)) {
    PlyPoint fused_point;

    Eigen::Vector3f fused_normal;
    fused_normal.x() = Median(fused_point_nx);
    fused_normal.y() = Median(fused_point_ny);
    fused_normal.z() = Median(fused_point_nz);
    const float fused_normal_norm = fused_normal.norm();
    if (fused_normal_norm < std::numeric_limits<float>::epsilon()) {
      return;
    }

    fused_point.x = Median(fused_point_x);
    fused_point.y = Median(fused_point_y);
    fused_point.z = Median(fused_point_z);

    fused_point.nx = fused_normal.x() / fused_normal_norm;
    fused_point.ny = fused_normal.y() / fused_normal_norm;
    fused_point.nz = fused_normal.z() / fused_normal_norm;

    fused_point.r =
        TruncateCast<float, uint8_t>(std::round(Median(fused_point_r)));
    fused_point.g =
        TruncateCast<float, uint8_t>(std::round(Median(fused_point_g)));
    fused_point.b =
        TruncateCast<float, uint8_t>(std::round(Median(fused_point_b)));

    task_fused_points_[thread_id].push_back(fused_point);
    task_fused_points_visibility_[thread_id].emplace_back(
        fused_point_visibility.begin(), fused_point_visibility.end());
  }
}

void WritePointsVisibility(
    const std::filesystem::path& path,
    const std::vector<std::vector<int>>& points_visibility) {
  std::fstream file(path, std::ios::out | std::ios::binary);
  THROW_CHECK_FILE_OPEN(file, path);

  WriteBinaryLittleEndian<uint64_t>(&file, points_visibility.size());

  for (const auto& visibility : points_visibility) {
    WriteBinaryLittleEndian<uint32_t>(&file, visibility.size());
    for (const auto& image_idx : visibility) {
      WriteBinaryLittleEndian<uint32_t>(&file, image_idx);
    }
  }
}

std::vector<std::vector<int>> ReadPointsVisibility(
    const std::filesystem::path& path, size_t num_points) {
  std::fstream file(path, std::ios::in | std::ios::binary);
  THROW_CHECK_FILE_OPEN(file, path);

  const size_t file_num_points = ReadBinaryLittleEndian<uint64_t>(&file);
  THROW_CHECK_EQ(file_num_points, num_points);

  std::vector<std::vector<int>> visibility(num_points);
  for (size_t i = 0; i < num_points; ++i) {
    const uint32_t num_visible = ReadBinaryLittleEndian<uint32_t>(&file);
    visibility[i].resize(num_visible);
    for (uint32_t j = 0; j < num_visible; ++j) {
      visibility[i][j] =
          static_cast<int>(ReadBinaryLittleEndian<uint32_t>(&file));
    }
  }
  return visibility;
}

}  // namespace mvs
}  // namespace colmap
