289 lines
9.5 KiB
C++
289 lines
9.5 KiB
C++
#include "methods.hh"
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#include <algorithm>
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#include <array>
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#include <cmath>
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#include <cstdlib>
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#include <future>
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#include <iostream>
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#include <optional>
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#include <utility>
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std::mutex colors_mutex;
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auto const thread_nbr = std::thread::hardware_concurrency();
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///////////////////////////////////////////////////////////////////////////////
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// class implementation //
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///////////////////////////////////////////////////////////////////////////////
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// constructors ///////////////////////////////////////////////////////////////
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ImageManipulator::ImageManipulator(std::filesystem::path const t_input_path,
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std::filesystem::path const t_output_path,
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int const t_iterations)
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: reference_{cv::imread(t_input_path.native(), cv::IMREAD_COLOR)},
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generated_image_{cv::Mat{reference_.size().height,
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reference_.size().width, CV_8UC3,
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cv::Scalar(0, 0, 0)}},
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output_path_{t_output_path.native()},
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diff_{euclidian_distance(generated_image_)},
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total_iterations_{t_iterations},
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remaining_iter_{t_iterations},
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width_{reference_.size().width},
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height_{reference_.size().height}
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{
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if (!reference_.data) {
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spdlog::critical("Could not open or find image!\n");
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exit(-1);
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}
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spdlog::debug("Image loaded!");
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spdlog::debug("Width:\t{}", reference_.size().width);
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spdlog::debug("Height:\t{}", reference_.size().height);
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}
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// public methods /////////////////////////////////////////////////////////////
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void ImageManipulator::exec_method(int const t_nb_method,
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bool const t_controlled_size = false)
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{
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switch (t_nb_method) {
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case 1: {
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method1();
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break;
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}
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case 2: {
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method2();
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break;
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}
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case 3: {
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method3();
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break;
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}
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case 4: {
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method4(t_controlled_size);
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break;
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}
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default:
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spdlog::error("Requested method {} is not implemented.", t_nb_method);
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std::exit(-1);
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}
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}
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void ImageManipulator::write_file() const
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{
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cv::imwrite(output_path_, generated_image_);
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}
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// private methods ////////////////////////////////////////////////////////////
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[[nodiscard]] auto ImageManipulator::euclidian_distance(
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cv::Mat const& t_img) const noexcept -> double
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{
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double euclidian = 0.0;
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for (auto itr1 = reference_.begin<uchar>(), itr2 = t_img.begin<uchar>();
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itr1 != reference_.end<uchar>() && itr2 != t_img.end<uchar>();
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++itr1, ++itr2) {
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euclidian += std::pow(*itr1 - *itr2, 2);
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}
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return std::sqrt(euclidian);
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}
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[[nodiscard]] auto ImageManipulator::random_color() const noexcept
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{
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return cv::Scalar(rand() % 255, rand() % 255, rand() % 255);
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}
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[[nodiscard]] auto ImageManipulator::get_square_values() const noexcept
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{
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int rand_x = rand() % reference_.size().width;
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int rand_y = rand() % reference_.size().height;
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int size = rand()
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% std::min(reference_.size().width - rand_x,
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reference_.size().height - rand_y);
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return std::tuple<int, int, int>(rand_x, rand_y, size);
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}
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[[nodiscard]] auto ImageManipulator::get_controlled_square_values() const
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noexcept
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{
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int rand_x = rand() % reference_.size().width;
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int rand_y = rand() % reference_.size().height;
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float const coef = static_cast<float>(remaining_iter_)
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/ static_cast<float>(total_iterations_);
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int const min_size
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= static_cast<int>((static_cast<float>(std::min(reference_.size().width,
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reference_.size().height))
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/ 2.0f)
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* coef);
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int const max_size = min_size * 2 + 1;
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int size = rand() % (max_size - min_size) + min_size;
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return std::tuple<int, int, int>(rand_x, rand_y, size);
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}
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[[nodiscard]] auto ImageManipulator::create_candidate(
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bool const t_controlled_size = false) const
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{
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auto temp_image = generated_image_.clone();
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auto const [rand_x, rand_y, size] = t_controlled_size
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? get_controlled_square_values()
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: get_square_values();
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auto const& color = colors_[rand() % colors_.size()];
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draw_square(
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temp_image, cv::Point{rand_x, rand_y}, size,
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cv::Scalar{static_cast<double>(color[0]), static_cast<double>(color[1]),
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static_cast<double>(color[2])});
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auto new_diff = euclidian_distance(temp_image);
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return (new_diff < diff_)
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? std::optional<std::pair<cv::Mat, double>>{std::make_pair(
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std::move(temp_image), new_diff)}
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: std::nullopt;
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}
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void ImageManipulator::get_color_set()
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{
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for (int h = 0; h < reference_.size().height;
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h += std::thread::hardware_concurrency()) {
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std::vector<std::thread> thread_list{};
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for (auto i = 0u; i < std::thread::hardware_concurrency(); ++i) {
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thread_list.push_back(
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std::thread(&ImageManipulator::threaded_get_color, this, h + i));
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}
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for (auto& th : thread_list) {
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th.join();
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}
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}
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colors_.shrink_to_fit();
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}
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void ImageManipulator::threaded_get_color(int t_h)
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{
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if (t_h > reference_.size().height) {
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return;
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}
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for (int w = 0; w < reference_.size().width; w += 3) {
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std::array<uchar, 3> temp
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= {reference_.at<uchar>(t_h, w), reference_.at<uchar>(t_h, w + 1),
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reference_.at<uchar>(t_h, w + 2)};
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auto pos = std::find(std::begin(colors_), std::end(colors_), temp);
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if (pos == std::end(colors_)) {
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colors_mutex_.lock();
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colors_.push_back(std::move(temp));
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colors_mutex_.unlock();
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}
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}
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}
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void ImageManipulator::adjust_size(cv::Point& t_top_left,
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int const size) noexcept
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{
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int const shape_total_width = t_top_left.x + size;
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int const shape_total_height = t_top_left.y + size;
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if (int const diff = shape_total_height + height_; diff > 0) {
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t_top_left.x += diff + 1;
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}
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if (int const diff = shape_total_width + width_; diff > 0) {
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t_top_left.x += diff + 1;
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}
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}
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void ImageManipulator::draw_square(cv::Mat& t_img,
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cv::Point const& t_top_left,
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int const t_size,
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cv::Scalar const& t_color) const
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{
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auto points = std::make_unique<cv::Point[]>(4);
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points[0] = t_top_left;
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points[1] = cv::Point{t_top_left.x, t_top_left.y + t_size};
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points[2] = cv::Point{t_top_left.x + t_size, t_top_left.y + t_size};
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points[3] = cv::Point{t_top_left.x + t_size, t_top_left.y};
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fillConvexPoly(t_img, points.get(), 4, t_color);
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}
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void ImageManipulator::update_gen_image(cv::Mat const& t_img,
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double const t_diff)
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{
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diff_ = t_diff;
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t_img.copyTo(generated_image_);
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--remaining_iter_;
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spdlog::debug("remaining iter: {}\tdiff: {}", remaining_iter_, diff_);
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}
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void ImageManipulator::method1()
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{
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spdlog::debug("Beginning method1, initial difference: {}", diff_);
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spdlog::debug("nb_total_iter: {}, nb_remaining_iter: {}", total_iterations_,
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remaining_iter_);
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while (remaining_iter_ > 0 && diff_ > 0.0) {
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auto temp_image = generated_image_.clone();
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auto const [rand_x, rand_y, size] = get_square_values();
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draw_square(temp_image, cv::Point{rand_x, rand_y}, size, random_color());
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if (auto const new_diff = euclidian_distance(temp_image);
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new_diff < diff_) {
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update_gen_image(temp_image, new_diff);
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}
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}
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}
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void ImageManipulator::method2()
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{
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spdlog::debug("Beginning method2, initial difference: {}", diff_);
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spdlog::debug("nb_total_iter: {}, nb_remaining_iter: {}", total_iterations_,
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remaining_iter_);
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spdlog::debug("Running on {} threads", std::thread::hardware_concurrency());
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get_color_set();
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spdlog::debug("{} colors detected", colors_.size());
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while (remaining_iter_ > 0 && diff_ > 0.0) {
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if (auto result = create_candidate(); result.has_value()) {
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update_gen_image(result->first, result->second);
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}
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}
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}
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void ImageManipulator::method3()
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{
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spdlog::debug("Beginning method2, initial difference: {}", diff_);
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spdlog::debug("nb_total_iter: {}, nb_remaining_iter: {}", total_iterations_,
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remaining_iter_);
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spdlog::debug("Running on {} threads", std::thread::hardware_concurrency());
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get_color_set();
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spdlog::debug("{} colors detected", colors_.size());
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while (remaining_iter_ > 0 && diff_ > 0.0) {
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auto temp_image = generated_image_.clone();
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if (auto result = create_candidate(true); result.has_value()) {
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update_gen_image(result->first, result->second);
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}
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}
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}
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void ImageManipulator::method4(bool const t_controlled_size)
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{
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spdlog::debug("Beginning method2, initial difference: {}", diff_);
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spdlog::debug("nb_total_iter: {}, nb_remaining_iter: {}", total_iterations_,
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remaining_iter_);
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spdlog::debug("Running on {} threads", std::thread::hardware_concurrency());
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get_color_set();
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spdlog::debug("{} colors detected", colors_.size());
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while(remaining_iter_ > 0 && diff_ > 0.0)
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{
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std::vector<std::future<std::optional<std::pair<cv::Mat, double>>>>
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results{};
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std::vector<std::pair<cv::Mat, double>> values{};
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for (size_t i = 0; i < std::thread::hardware_concurrency(); ++i) {
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results.push_back(std::async(std::launch::async,
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&ImageManipulator::create_candidate, this,
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t_controlled_size));
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}
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for (auto& elem : results) {
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if(auto res = elem.get(); res.has_value() && res->second < diff_) {
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values.push_back(*res);
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}
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}
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if(values.size() > 0) {
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size_t best = 0;
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for(size_t i = 0; i < values.size(); ++i) {
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if(values[i].second < values[best].second) {
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best = i;
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}
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}
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update_gen_image(values[best].first, values[best].second);
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}
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}
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}
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