genetic-images/src/methods.cc

#include "methods.hh"

#include <algorithm>
#include <future>
#include <optional>
#include <thread>

static auto const thread_nbr = std::thread::hardware_concurrency();

///////////////////////////////////////////////////////////////////////////////
//                                   Public                                  //
///////////////////////////////////////////////////////////////////////////////

// constructors ///////////////////////////////////////////////////////////////
/**
 *  Copy constructor of \ref ImageManipulator, will copy all of its members
 *  except for its mutex.
 *
 *  \param[in] other Element to copy
 */
ImageManipulator::ImageManipulator(const ImageManipulator &other)
    : colors_{other.colors_}, reference_{other.reference_},
      generated_image_{other.generated_image_}, shape_{other.shape_},
      output_path_{other.output_path_}, diff_{other.diff_},
      total_iterations_{other.total_iterations_},
      remaining_iter_{other.remaining_iter_}, width_{other.width_},
      height_{other.height_}
{
}

/**
 *  Move constructor of \ref ImageManipulator, will move all of the input’s
 *  members except for its mutex, a new one will be made.
 *
 *  \param[in] other Element to move
 */
ImageManipulator::ImageManipulator(ImageManipulator &&other) noexcept
    : colors_{std::move(other.colors_)}, reference_{std::move(
                                             other.reference_)},
      generated_image_{std::move(other.generated_image_)}, shape_{std::move(
                                                               other.shape_)},
      output_path_{std::move(other.output_path_)},
      diff_{std::move(other.diff_)}, total_iterations_{other.total_iterations_},
      remaining_iter_{other.remaining_iter_}, width_{other.width_},
      height_{other.height_}
{
}

/**
 *  Creates an instance of \ref ImageManipulator based on an input path and an
 *  output path. It will load the input image from its first argument, and will
 *  write an output image when asked at the path passed as its second argument.
 *
 *  \param[in] t_input_path Path for the input, reference image
 *  \param[in] t_output_path Path to the output image to write
 */
ImageManipulator::ImageManipulator(std::string const t_input_path,
                                   std::string const t_output_path,
                                   int const t_iterations,
                                   Shape::ShapeType const t_shape)
    : reference_{cv::imread(t_input_path, cv::IMREAD_COLOR)}, shape_{Shape{
                                                                  t_shape}},
      output_path_{t_output_path}, total_iterations_{t_iterations}
{
  if (!reference_.data) {
    spdlog::critical("Could not open or find image!\n");
    exit(-1);
  }
}

/**
 *  Creates a view of the input image, and will generate an image based only on
 *  that view.
 *
 *  \param[in] t_origin_image Image to create a view from
 *  \param[in] t_iterations Number of iterations to perform on this view
 *  \param[in] t_x X value of the view’s origin (top left)
 *  \param[in] t_y Y value of the view’s origin (top left)
 *  \param[in] t_width Width of the view from its origin
 *  \param[in] t_height Height of the view from its origin
 */
ImageManipulator::ImageManipulator(cv::Mat const &t_origin_image,
                                   int const t_iterations,
                                   Shape::ShapeType const t_shape,
                                   int const t_x, int const t_y,
                                   int const t_width, int const t_height)
    : reference_{t_origin_image(
        cv::Range{t_y, std::min(t_y + t_height, t_origin_image.rows)},
        cv::Range{t_x, std::min(t_x + t_width, t_origin_image.cols)})},
      shape_{Shape{t_shape}}, total_iterations_{t_iterations}
{
  if (!reference_.data) {
    spdlog::critical("Could not open or find image!\n");
    exit(-1);
  }
}

// public methods /////////////////////////////////////////////////////////////

/**
 *  Execute one of the methods as described in the report. If a non-valid
 *  method is called, the program will be terminated. The argument
 *  `t_controlled_size` allows the program to have some control over the random
 *  size of the squares that will be generated. The arguments `t_cols`, `t_rows`
 *  and `submethod` are relevant to the fifth method.
 *
 *  \param[in] t_nb_method Method identifier
 *  \param[in] t_controlled_size Control over the squares’ size
 *  \param[in] t_cols Number of columns the reference should be divided into
 *  \param[in] t_rows Number of rows the reference should be divided into
 *  \param[in] t_submethod
 */
void ImageManipulator::exec_method(int const t_nb_method,
                                   bool const t_controlled_size = false,
                                   int const t_cols = 1, int const t_rows = 0,
                                   int const t_submethod = 1)
{
  switch (t_nb_method) {
  case 1: method1(); break;
  case 2: method2(); break;
  case 3: method3(); break;
  case 4: method4(t_controlled_size); break;
  case 5: method5(t_controlled_size, t_cols, t_rows, t_submethod); break;
  default:
    spdlog::error("Requested method {} is not implemented.", t_nb_method);
    std::exit(-1);
  }
}

///////////////////////////////////////////////////////////////////////////////
//                                  Private                                  //
///////////////////////////////////////////////////////////////////////////////

// methods ////////////////////////////////////////////////////////////////////

/**
 *  \return cv::Scalar
 */
[[nodiscard]] auto ImageManipulator::random_color() const noexcept
{
  return cv::Scalar(rand() % 255, rand() % 255, rand() % 255);
}

void ImageManipulator::create_shape() noexcept
{
  shape_.update(cv::Point{reference_.size().width, reference_.size().height},
                std::min(reference_.size().width, reference_.size().height));
}

void ImageManipulator::create_controlled_shape() noexcept
{
  float const coef = static_cast<float>(remaining_iter_)
                     / static_cast<float>(total_iterations_);
  int const min_size
      = static_cast<int>((static_cast<float>(std::min(reference_.size().width,
                                                      reference_.size().height))
                          / 2.0f)
                         * coef);
  int const max_size = min_size * 2 + 1;
  shape_.update(cv::Point{reference_.size().width, reference_.size().height},
                max_size, min_size);
}

/**
 *  Creates a temporary image on which a random square is drawn. If its
 *  euclidian distance with the reference image proves to be an improvement from
 *  the latest improvement before, then both the image and the distance are
 *  returned. Otherwise, nothing is returned.
 *
 *  \param[in] t_controlled_size Enables controlled square size
 *  \return Optional pair of cv::Mat and double
 */
[[nodiscard]] auto
ImageManipulator::create_candidate(bool const t_controlled_size = false)
{
  auto temp_img     = generated_image_.clone();
  auto const &color = colors_[rand() % colors_.size()];
  if (t_controlled_size) {
    create_controlled_shape();
  } else {
    create_shape();
  }
  draw_shape(temp_img, cv::Scalar{static_cast<double>(color[0]),
                                  static_cast<double>(color[1]),
                                  static_cast<double>(color[2])});
  const auto new_diff = cv::norm(reference_, temp_img);
  return (new_diff < diff_)
             ? std::optional<std::pair<cv::Mat, double>>{std::make_pair(
                 std::move(temp_img), new_diff)}
             : std::nullopt;
}

/**
 *  Generates views and stores them in a double vector so the tiles (views) are
 *  stored by column top to bottom, and within the columns left to right.
 *
 *  \param t_cols Number of columns the reference image should be divided into
 *  \param t_rows Number of rows the reference image should be divided into
 *  \return Collection of tiles (vector<vector<ImageManipulator>>)
 */
[[nodiscard]] auto ImageManipulator::generate_tiles(int const t_cols,
                                                    int const t_rows) const
{
  std::vector<std::vector<ImageManipulator>> tiles{};
  int const tile_width  = reference_.cols / t_cols;
  int const tile_height = reference_.rows / t_rows;
  for (int index_x = 0; index_x < t_cols; ++index_x) {
    std::vector<ImageManipulator> tile_col{};
    for (int index_y = 0; index_y < t_rows; ++index_y) {
      int const width = (index_x != t_cols - 1)
                            ? tile_width
                            : tile_width + reference_.cols % tile_width;
      int const height = (index_y != t_rows - 1)
                             ? tile_height
                             : tile_height + reference_.rows % tile_height;
      tile_col.emplace_back(reference_, total_iterations_, shape_.get_type(),
                            index_x * tile_width, index_y * tile_height, width,
                            height);
    }
    tiles.push_back(tile_col);
  }
  return tiles;
}

/**
 *  Will analyse the reference image and will store each color found in member
 *  variable \ref colors_. Works on multithreading.
 */
void ImageManipulator::get_color_set()
{
  for (int h = 0; h < reference_.size().height; h += thread_nbr) {
    std::vector<std::thread> thread_list{};
    for (auto i = 0u; i < thread_nbr; ++i) {
      thread_list.push_back(
          std::thread(&ImageManipulator::threaded_get_color, this, h + i));
    }
    std::for_each(thread_list.begin(), thread_list.end(),
                  [](auto &th) { th.join(); });
  }
  colors_.shrink_to_fit();
}

/**
 *  Will search for every color found in its designated column. If a new color
 *  is found, pauses all its other similar threads, adds the new color in \ref
 *  colors_, then resumes the other threads. Helper function for \ref
 *  get_color_set
 */
void ImageManipulator::threaded_get_color(int const t_h)
{
  if (t_h > reference_.size().height) {
    return;
  }
  for (int w = 0; w < reference_.size().width; w += 3) {
    std::array<uchar, 3> temp
        = {reference_.at<uchar>(t_h, w), reference_.at<uchar>(t_h, w + 1),
           reference_.at<uchar>(t_h, w + 2)};
    auto pos = std::find(std::begin(colors_), std::end(colors_), temp);
    if (pos == std::end(colors_)) {
      std::lock_guard<std::mutex> lock(colors_mutex_);
      colors_.push_back(std::move(temp));
    }
  }
}

void ImageManipulator::draw_shape(cv::Mat &t_img, cv::Scalar &&t_color)
{
  fillConvexPoly(t_img, shape_.get_points().data(), shape_.get_nb_points(),
                 t_color);
}

/**
 *  Updates the object’s current generated image and difference with its
 *  reference by replacing them with the arguments passed in this function. This
 *  function should only be called if the passed elements are improving the
 *  generated image and reduce the euclidian distance between said image and its
 *  reference.
 *
 *  \param[in] t_img Image to replace \ref generated_image_
 *  \param[in] t_diff New euclidian distance
 */
void ImageManipulator::update_gen_image(cv::Mat const &t_img,
                                        double const t_diff)
{
  diff_ = t_diff;
  t_img.copyTo(generated_image_);
  --remaining_iter_;
  spdlog::debug("remaining iter: {}\tdiff: {}", remaining_iter_, diff_);
}

/**
 *  Merges the tiles generated by \ref method5 into a single image. The tiles
 *  are organized by column top to bottom, within each they are stored in order,
 *  left to right. They will be merged in \ref generated_image_.
 *
 *  \param t_tiles Collection of tiles to be merged together
 */
void ImageManipulator::merge_tiles(
    std::vector<std::vector<ImageManipulator>> const &t_tiles)
{
  std::vector<cv::Mat> columns{};
  std::for_each(t_tiles.begin(), t_tiles.end(), [&columns](auto const &col) {
    std::vector<cv::Mat> column_arr{};
    cv::Mat column_img{};
    std::for_each(col.begin(), col.end(), [&column_arr](auto const &tile) {
      column_arr.push_back(tile.get_generated_image());
    });
    vconcat(column_arr, column_img);
    columns.push_back(std::move(column_img));
  });
  hconcat(columns, generated_image_);
}

void ImageManipulator::method1()
{
  spdlog::debug("Beginning method1, initial difference: {}", diff_);
  while (remaining_iter_ > 0 && diff_ > 0.0) {
    auto temp_image = generated_image_.clone();
    create_shape();
    draw_shape(temp_image, random_color());
    if (auto const new_diff = cv::norm(reference_, temp_image);
        new_diff < diff_) {
      update_gen_image(temp_image, new_diff);
    }
  }
}

void ImageManipulator::method2()
{
  spdlog::debug("Beginning method2, initial difference: {}", diff_);
  spdlog::debug("Running on {} threads", thread_nbr);
  get_color_set();
  spdlog::debug("{} colors detected", colors_.size());
  while (remaining_iter_ > 0 && diff_ > 0.0) {
    if (auto result = create_candidate(); result.has_value()) {
      update_gen_image(result->first, result->second);
    }
  }
}

void ImageManipulator::method3()
{
  spdlog::debug("Beginning method3, initial difference: {}", diff_);
  spdlog::debug("Running on {} threads", thread_nbr);
  get_color_set();
  spdlog::debug("{} colors detected", colors_.size());
  while (remaining_iter_ > 0 && diff_ > 0.0) {
    auto temp_image = generated_image_.clone();
    if (auto result = create_candidate(true); result.has_value()) {
      update_gen_image(result->first, result->second);
    }
  }
}

/**
 *  \param[in] t_controlled_size Enables control over the random squares’ size
 */
void ImageManipulator::method4(bool const t_controlled_size)
{
  spdlog::debug("Beginning method4, initial difference: {}", diff_);
  spdlog::debug("Running on {} threads", thread_nbr);
  get_color_set();
  spdlog::debug("{} colors detected", colors_.size());
  while (remaining_iter_ > 0 && diff_ > 0.0) {
    std::vector<std::future<std::optional<std::pair<cv::Mat, double>>>>
        results{};
    std::vector<std::pair<cv::Mat, double>> values{};
    // launch asynchronously candidate image generation
    for (size_t i = 0; i < thread_nbr; ++i) {
      results.push_back(std::async(std::launch::async,
                                   &ImageManipulator::create_candidate, this,
                                   t_controlled_size));
    }
    // if candidate is a success, store it
    std::for_each(results.begin(), results.end(), [&values, this](auto &elem) {
      if (auto res = elem.get(); res.has_value() && res->second < this->diff_) {
	values.push_back(*res);
      }
    });
    // apply best candidate
    if (values.size() > 0) {
      auto const pos
          = std::min_element(std::begin(values), std::end(values),
                             [](const auto &elem1, const auto &elem2) {
	                       return elem1.second < elem2.second;
                             });
      update_gen_image(pos->first, pos->second);
    }
  }
}

/**
 *  \param[in] t_controlled_size Enables control over the random squares’ size
 *  \param[in] t_cols Number of colomns the reference should be divided into
 *  \param[in] t_rows Number of rows the reference should be divided into
 *  \param[in] t_submethod Method to be used on each tile
 */
void ImageManipulator::method5(bool const t_controlled_size, int const t_cols,
                               int const t_rows, int const t_submethod)
{
  spdlog::debug("Beginning method5, initial difference: {}", diff_);
  spdlog::debug("Running on {} threads", thread_nbr);

  auto tiles = generate_tiles((t_cols != 0) ? t_cols : t_rows, t_rows);
  spdlog::debug("{} tiles", tiles.size());

  std::vector<std::thread> thread_list{};
  std::for_each(tiles.begin(), tiles.end(), [&](auto &row) {
    std::for_each(row.begin(), row.end(), [&](auto &tile) {
      thread_list.emplace_back(
          [&]() { tile.exec_method(t_submethod, t_controlled_size); });
    });
  });
  std::for_each(thread_list.begin(), thread_list.end(),
                [](auto &th) { th.join(); });
  merge_tiles(tiles);
}