method 5 DONE
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@ -1,29 +1,28 @@
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#pragma once
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#include <filesystem>
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#include <opencv2/core/core.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/imgproc.hpp>
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#include <spdlog/spdlog.h>
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#include <string>
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#include <thread>
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#include <tuple>
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#include <vector>
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class ImageManipulator {
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public:
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ImageManipulator() = delete;
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ImageManipulator(const ImageManipulator& other);
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ImageManipulator(ImageManipulator&& other) noexcept;
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[[nodiscard]] auto operator=(const ImageManipulator& other)
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-> ImageManipulator;
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[[nodiscard]] auto operator=(ImageManipulator&& other) noexcept
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-> ImageManipulator;
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// Load image from input, and prepare for output
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ImageManipulator(std::filesystem::path const t_input_path,
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std::filesystem::path const t_output_path,
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/// \brief Copy contructor
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ImageManipulator(const ImageManipulator& other);
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/// \brief Move constructor
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ImageManipulator(ImageManipulator&& other) noexcept;
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/// \brief Load image from input, and prepare for output
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ImageManipulator(std::string const t_input_path,
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std::string const t_output_path,
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int const iterations);
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/// \brief Basically makes views from image
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ImageManipulator(cv::Mat const& t_origin_image,
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int const iterations,
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int const t_x,
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@ -31,57 +30,96 @@ class ImageManipulator {
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int const t_width,
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int const t_height);
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/// \brief Copy assignment operator
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[[nodiscard]] auto operator=(const ImageManipulator& other)
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-> ImageManipulator;
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/// \brief Move assignment operator
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[[nodiscard]] auto operator=(ImageManipulator&& other) noexcept
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-> ImageManipulator;
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/// \brief Execute the nth method on the current object
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void exec_method(int const t_nb_method,
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bool const t_controlled_size,
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int const t_cols,
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int const t_rows,
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int const t_submethod);
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/// \brief Write the generated image to the output path
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void write_file() const;
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/// \brief Returns a reference to the generated image
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[[nodiscard]] auto const& get_generated_image() const noexcept
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{
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return generated_image_;
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}
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//! Destructor
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/// \brief Destructor
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virtual ~ImageManipulator() noexcept = default;
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protected:
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private:
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/// \brief Calculates the euclidian distance between two images
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[[nodiscard]] auto euclidian_distance(cv::Mat const& t_img) const noexcept
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-> double;
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/// \brief Creates and returns a random color
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[[nodiscard]] auto random_color() const noexcept;
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/// \brief Generates random square coordinates
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[[nodiscard]] auto get_square_values() const noexcept;
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/// \brief Generates controlled random square coordinates
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[[nodiscard]] auto get_controlled_square_values() const noexcept;
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/// \brief Generates a candidate for image generation improvement
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[[nodiscard]] auto create_candidate(bool const t_controlled_size) const;
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[[nodiscard]] auto generate_tiles(int const t_cols, int const t_rows) const;
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/// \brief Gets all colors from the reference image
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void get_color_set();
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/// \brief Threaded helper for \ref get_color_set
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void threaded_get_color(int t_h);
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void adjust_size(cv::Point& t_top_left, int const size) noexcept;
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/// \brief Draw a square on an image
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void 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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/// \brief Update this object’s generated image
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void update_gen_image(cv::Mat const& t_img, double const t_diff);
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void merge_tiles(std::vector<std::vector<ImageManipulator>> t_tiles);
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/// \brief First method as described in the
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/// [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf)
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void method1();
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/// \brief Second method as described in the
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/// [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf)
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void method2();
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/// \brief Third method as described in the
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/// [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf)
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void method3();
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/// \brief Fourth method as described in the
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/// [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf)
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void method4(bool const t_controlled_size);
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/// \brief Fifth method as described in the
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/// [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf)
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void method5(bool const t_controlled_size,
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int cols,
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int const cols,
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int const rows,
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int const submethod);
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std::vector<std::array<uchar, 3>> colors_
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= std::vector<std::array<uchar, 3>>{};
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cv::Mat const reference_;
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= std::vector<std::array<uchar, 3>>{}; /*!< Color set from reference */
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cv::Mat const reference_; /*!< Reference image */
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cv::Mat generated_image_
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= cv::Mat{reference_.size().height, reference_.size().width, CV_8UC3,
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cv::Scalar(0, 0, 0)};
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mutable std::mutex colors_mutex_ = std::mutex{};
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std::string const output_path_{""};
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double diff_ = 0.0;
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int const total_iterations_ = 0;
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int remaining_iter_ = total_iterations_;
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int const width_ = reference_.size().width;
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int const height_ = reference_.size().height;
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cv::Scalar(0, 0, 0)}; /*!< Working, generated image */
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mutable std::mutex colors_mutex_
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= std::mutex{}; /*!< Thread mutex for color set generation */
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std::string const output_path_{""}; /*!< Write path for the generated image */
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double diff_ = euclidian_distance(generated_image_); /*!< Euclidian difference
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between \ref reference_ and \ref generated_image_ */
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int const total_iterations_ = 0; /*!< Number of iterations to perform */
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int remaining_iter_
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= total_iterations_; /*!< Remaining iterations to perform */
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int const width_ = reference_.size().width; /*!< Width of the image */
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int const height_ = reference_.size().height; /*!< Height of the image */
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};
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#include <filesystem>
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#include <tuple>
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/// \brief Parses the arguments passed to the program
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[[nodiscard]] auto parse_args(int, char**) -> std::tuple<std::filesystem::path,
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std::filesystem::path,
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int,
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src/methods.cc
328
src/methods.cc
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#include <array>
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#include <cmath>
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#include <cstdlib>
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#include <functional>
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#include <future>
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#include <iostream>
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#include <optional>
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#include <thread>
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#include <utility>
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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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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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{
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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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ImageManipulator::ImageManipulator(cv::Mat const& t_origin_image,
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int const t_iterations,
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int const t_x,
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int const t_y,
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int const t_width,
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int const t_height)
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: reference_{t_origin_image(
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cv::Range{t_y, std::min(t_y + t_height, t_origin_image.rows)},
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cv::Range{t_x, std::min(t_x + t_width, t_origin_image.cols)})},
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diff_{euclidian_distance(generated_image_)},
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total_iterations_{t_iterations}
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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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/**
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* Copy constructor of \ref ImageManipulator, will copy all of its members
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* except for its mutex.
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*
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* \param[in] other Element to copy
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*/
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ImageManipulator::ImageManipulator(const ImageManipulator& other)
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: colors_{other.colors_},
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reference_{other.reference_},
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@ -66,6 +31,12 @@ ImageManipulator::ImageManipulator(const ImageManipulator& other)
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{
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}
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/**
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* Move constructor of \ref ImageManipulator, will move all of the input’s
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* members except for its mutex, a new one will be made.
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*
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* \param[in] other Element to move
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*/
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ImageManipulator::ImageManipulator(ImageManipulator&& other) noexcept
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: colors_{std::move(other.colors_)},
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reference_{std::move(other.reference_)},
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@ -79,13 +50,78 @@ ImageManipulator::ImageManipulator(ImageManipulator&& other) noexcept
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{
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}
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/**
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* Creates an instance of \ref ImageManipulator based on an input path and an
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* output path. It will load the input image from its first argument, and will
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* write an output image when asked at the path passed as its second argument.
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*
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* \param[in] t_input_path Path for the input, reference image
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* \param[in] t_output_path Path to the output image to write
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*/
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ImageManipulator::ImageManipulator(std::string const t_input_path,
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std::string const t_output_path,
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int const t_iterations)
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: reference_{cv::imread(t_input_path, cv::IMREAD_COLOR)},
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output_path_{t_output_path},
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total_iterations_{t_iterations}
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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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}
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/**
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* Creates a view of the input image, and will generate an image based only on
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* that view.
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*
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* \param[in] t_origin_image Image to create a view from
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* \param[in] t_iterations Number of iterations to perform on this view
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* \param[in] t_x X value of the view’s origin (top left)
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* \param[in] t_y Y value of the view’s origin (top left)
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* \param[in] t_width Width of the view from its origin
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* \param[in] t_height Height of the view from its origin
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*/
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ImageManipulator::ImageManipulator(cv::Mat const& t_origin_image,
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int const t_iterations,
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int const t_x,
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int const t_y,
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int const t_width,
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int const t_height)
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: reference_{t_origin_image(
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cv::Range{t_y, std::min(t_y + t_height, t_origin_image.rows)},
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cv::Range{t_x, std::min(t_x + t_width, t_origin_image.cols)})},
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total_iterations_{t_iterations}
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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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}
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// operators //////////////////////////////////////////////////////////////////
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/**
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* Copy assignment operator, will copy all of the input’s members except for
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* its mutex, a new one will be generated.
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*
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* \param[in] other Element to copy
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* \return ImageManipulator
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*/
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[[nodiscard]] auto ImageManipulator::operator=(const ImageManipulator& other)
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-> ImageManipulator
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{
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return ImageManipulator(other);
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}
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/**
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* Move assignment operator, will move all of the input’s members except for
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* its mutex, a new one will be generated.
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*
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* \param[in] other Element to move
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* \return ImageManipulator
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*/
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[[nodiscard]] auto ImageManipulator::operator=(
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ImageManipulator&& other) noexcept -> ImageManipulator
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{
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}
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// public methods /////////////////////////////////////////////////////////////
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/**
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* Execute one of the methods as described in the report. If a non-valid
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* method is called, the program will be terminated. The argument
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* `t_controlled_size` allows the program to have some control over the random
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* size of the squares that will be generated. The arguments `t_cols`, `t_rows`
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* and `submethod` are relevant to the fifth method.
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*
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* \param[in] t_nb_method Method identifier
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* \param[in] t_controlled_size Control over the squares’ size
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* \param[in] t_cols Number of columns the reference should be divided into
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* \param[in] t_rows Number of rows the reference should be divided into
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* \param[in] t_submethod
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*/
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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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int const cols = 1,
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int const rows = 0,
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int const submethod = 1)
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int const t_cols = 1,
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int const t_rows = 0,
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int const t_submethod = 1)
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{
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switch (t_nb_method) {
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case 1: {
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@ -117,7 +167,7 @@ void ImageManipulator::exec_method(int const t_nb_method,
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break;
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}
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case 5: {
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method5(t_controlled_size, cols, rows, submethod);
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method5(t_controlled_size, t_cols, t_rows, t_submethod);
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break;
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}
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default:
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@ -126,6 +176,10 @@ void ImageManipulator::exec_method(int const t_nb_method,
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}
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}
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/**
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* Write the generated image as a file to the specified path stored in the
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* object
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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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// private methods ////////////////////////////////////////////////////////////
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/**
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* Calculates the euclidian distance between the reference image and the image
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* passed as an argument
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*
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* \param t_img Image with which the distance is computed
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* \return double
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*/
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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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return std::sqrt(euclidian);
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}
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/**
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* \return cv::Scalar
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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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/**
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* Generates random x/y coordinates for a square and the size of said square.
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*
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* \return Tuple of three ints
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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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return std::tuple<int, int, int>(rand_x, rand_y, size);
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}
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/**
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* Generates random x/y coordinates for a square’s origin (top left), and a
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* random size which’s max and minimal value are controled as mentionned in the
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* [report](https://labs.phundrak.fr/phundrak/genetic-images/blob/master/report/report.pdf).
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*
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* \return Tuple of three ints
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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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return std::tuple<int, int, int>(rand_x, rand_y, size);
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}
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/**
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* Creates a temporary image on which a random square is drawn. If its
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* euclidian distance with the reference image proves to be an improvement from
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* the latest improvement before, then both the image and the distance are
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* returned. Otherwise, nothing is returned.
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*
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* \param[in] t_controlled_size Enables controlled square size
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* \return Optional pair of cv::Mat and double
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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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@ -196,6 +281,33 @@ void ImageManipulator::write_file() const
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: std::nullopt;
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}
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[[nodiscard]] auto ImageManipulator::generate_tiles(int const t_cols,
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int const t_rows) const
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{
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std::vector<std::vector<ImageManipulator>> tiles{};
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int const tile_width = reference_.cols / t_cols;
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int const tile_height = reference_.rows / t_rows;
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for (int index_x = 0; index_x < t_cols; ++index_x) {
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std::vector<ImageManipulator> tile_col{};
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for (int index_y = 0; index_y < t_rows; ++index_y) {
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int const width = (index_x != t_cols - 1)
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? tile_width
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: tile_width + reference_.cols % tile_width;
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int const height = (index_y != t_rows - 1)
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? tile_height
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: tile_height + reference_.rows % tile_height;
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tile_col.emplace_back(reference_, total_iterations_, index_x * tile_width,
|
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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) {
|
||||
@ -211,6 +323,12 @@ void ImageManipulator::get_color_set()
|
||||
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 t_h)
|
||||
{
|
||||
if (t_h > reference_.size().height) {
|
||||
@ -229,19 +347,15 @@ void ImageManipulator::threaded_get_color(int t_h)
|
||||
}
|
||||
}
|
||||
|
||||
void ImageManipulator::adjust_size(cv::Point& t_top_left,
|
||||
int const size) noexcept
|
||||
{
|
||||
int const shape_total_width = t_top_left.x + size;
|
||||
int const shape_total_height = t_top_left.y + size;
|
||||
if (int const diff = shape_total_height + height_; diff > 0) {
|
||||
t_top_left.x += diff + 1;
|
||||
}
|
||||
if (int const diff = shape_total_width + width_; diff > 0) {
|
||||
t_top_left.x += diff + 1;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Draw a square on the image passed as its argument, following its passed
|
||||
* coordinates and with the passed color.
|
||||
*
|
||||
* \param[out] t_img Image to draw the square to
|
||||
* \param[in] t_top_left Origin of the square
|
||||
* \param[in] t_size Size of the square
|
||||
* \param[in] t_color Color of the square
|
||||
*/
|
||||
void ImageManipulator::draw_square(cv::Mat& t_img,
|
||||
cv::Point const& t_top_left,
|
||||
int const t_size,
|
||||
@ -255,6 +369,16 @@ void ImageManipulator::draw_square(cv::Mat& t_img,
|
||||
fillConvexPoly(t_img, points.get(), 4, 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)
|
||||
{
|
||||
@ -264,6 +388,22 @@ void ImageManipulator::update_gen_image(cv::Mat const& t_img,
|
||||
spdlog::debug("remaining iter: {}\tdiff: {}", remaining_iter_, diff_);
|
||||
}
|
||||
|
||||
void ImageManipulator::merge_tiles(
|
||||
std::vector<std::vector<ImageManipulator>> t_tiles)
|
||||
{
|
||||
std::vector<cv::Mat> columns{};
|
||||
for (auto const& col : t_tiles) {
|
||||
std::vector<cv::Mat> column_arr{};
|
||||
cv::Mat column_img{};
|
||||
for (auto const& tile : col) {
|
||||
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_);
|
||||
@ -311,6 +451,9 @@ void ImageManipulator::method3()
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* \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_);
|
||||
@ -334,45 +477,50 @@ void ImageManipulator::method4(bool const t_controlled_size)
|
||||
}
|
||||
}
|
||||
if (values.size() > 0) {
|
||||
size_t best = 0;
|
||||
for (size_t i = 0; i < values.size(); ++i) {
|
||||
if (values[i].second < values[best].second) {
|
||||
best = i;
|
||||
}
|
||||
}
|
||||
update_gen_image(values[best].first, values[best].second);
|
||||
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);
|
||||
// size_t best = 0;
|
||||
// for (size_t i = 0; i < values.size(); ++i) {
|
||||
// if (values[i].second < values[best].second) {
|
||||
// best = i;
|
||||
// }
|
||||
// }
|
||||
// update_gen_image(values[best].first, values[best].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 cols,
|
||||
int const rows,
|
||||
int const submethod)
|
||||
int const t_cols,
|
||||
int const t_rows,
|
||||
int const t_submethod)
|
||||
{
|
||||
spdlog::debug("Beginning method5, initial difference: {}", diff_);
|
||||
spdlog::debug("nb_total_iter: {}, nb_remaining_iter: {}", total_iterations_,
|
||||
remaining_iter_);
|
||||
spdlog::debug("Running on {} threads", thread_nbr);
|
||||
if (cols == 0) {
|
||||
cols = rows;
|
||||
}
|
||||
std::vector<std::vector<ImageManipulator>> tiles{};
|
||||
int const tile_width = reference_.cols / cols;
|
||||
int const tile_height = reference_.rows / rows;
|
||||
spdlog::debug("tile: width:{}\theight:{}", tile_width, tile_height);
|
||||
spdlog::debug("image: width:{}\theight:{}", reference_.cols, reference_.rows);
|
||||
for (int i = 0; i < rows; ++i) {
|
||||
std::vector<ImageManipulator> tile_row{};
|
||||
for (int j = 0; j < cols; ++j) {
|
||||
tile_row.emplace_back(
|
||||
reference_, total_iterations_, i * tile_height, j * tile_width,
|
||||
(i != rows - 1) ? tile_height
|
||||
: tile_height + reference_.cols % tile_height,
|
||||
(j != cols - 1) ? tile_width
|
||||
: tile_width + reference_.cols % tile_width);
|
||||
}
|
||||
tiles.push_back(tile_row);
|
||||
}
|
||||
auto tiles = generate_tiles((t_cols != 0) ? t_cols : t_rows, t_rows);
|
||||
spdlog::debug("{} tiles", tiles.size());
|
||||
|
||||
std::vector<std::thread> thread_list{};
|
||||
for (auto& row : tiles) {
|
||||
for (auto& tile : row) {
|
||||
thread_list.emplace_back(
|
||||
[&]() { tile.exec_method(t_submethod, t_controlled_size); });
|
||||
}
|
||||
}
|
||||
for (auto& th : thread_list) {
|
||||
th.join();
|
||||
}
|
||||
merge_tiles(tiles);
|
||||
}
|
||||
|
@ -1,6 +1,5 @@
|
||||
#include "parseargs.hh"
|
||||
#include <boost/program_options.hpp>
|
||||
#include <cstdlib>
|
||||
#include <iostream>
|
||||
|
||||
constexpr int DEFAULT_ITERATIONS = 2000;
|
||||
@ -8,11 +7,23 @@ constexpr int DEFAULT_ITERATIONS = 2000;
|
||||
using path = std::filesystem::path;
|
||||
namespace po = boost::program_options;
|
||||
|
||||
void processFilenames(po::variables_map const& vm,
|
||||
/**
|
||||
* \brief Ensures correct output path
|
||||
*
|
||||
* Checks if an output file exists, and if yes if it has an extension. In case
|
||||
* it doesn’t exist, `output_` is appended at the beginning of the input
|
||||
* filename. If the output path does not have an extension, the type `.png` is
|
||||
* appended at the end of the path.
|
||||
*
|
||||
* \param[in] t_vm Arguments passed to the program
|
||||
* \param[out] t_input Input path
|
||||
* \param[out] t_output Output path
|
||||
*/
|
||||
void processFilenames(po::variables_map const& t_vm,
|
||||
path const& t_input,
|
||||
path& t_output)
|
||||
{
|
||||
if (!vm.count("output")) {
|
||||
if (!t_vm.count("output")) {
|
||||
t_output.replace_filename("output_"
|
||||
+ std::string{t_input.filename().string()});
|
||||
}
|
||||
@ -21,6 +32,16 @@ void processFilenames(po::variables_map const& vm,
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Parses the arguments given to the program, formats them and returns them as
|
||||
* a tuple. If `-h` or `--help` or a malformed argument is passed, then the
|
||||
* list of arguments and their comment will be displayed, and the program will
|
||||
* exit.
|
||||
*
|
||||
* \param[in] t_ac Number of arguments passed to the program
|
||||
* \param[in] t_av Arguments passed to the program
|
||||
* \return Tuple of path, path, int, int, int, int, int, bool and bool
|
||||
*/
|
||||
[[nodiscard]] auto parse_args(int t_ac, char** t_av)
|
||||
-> std::tuple<path, path, int, int, int, int, int, bool, bool>
|
||||
{
|
||||
|
Loading…
Reference in New Issue
Block a user