silly
Brett
parent
0c66fe85c6
commit
096c87cbf5
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@ -10,3 +10,6 @@
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[submodule "lib/stb"]
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path = lib/stb
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url = https://github.com/nothings/stb
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[submodule "lib/blt-graphics"]
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path = lib/blt-graphics
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url = https://git.tpgc.me/tri11paragon/BLT-With-Graphics-Template.git
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@ -1,5 +1,5 @@
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cmake_minimum_required(VERSION 3.25)
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project(image-gp-6 VERSION 0.0.4)
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project(image-gp-6 VERSION 0.0.5)
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include(FetchContent)
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@ -10,6 +10,7 @@ option(ENABLE_TSAN "Enable the thread data race sanitizer" OFF)
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set(CMAKE_CXX_STANDARD 17)
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add_subdirectory(lib/blt-gp)
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add_subdirectory(lib/blt-graphics)
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find_package( OpenCV REQUIRED )
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@ -25,7 +26,7 @@ add_executable(image-gp-6 ${PROJECT_BUILD_FILES})
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target_compile_options(image-gp-6 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
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target_link_options(image-gp-6 PRIVATE -Wall -Wextra -Wpedantic -Wno-comment)
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target_link_libraries(image-gp-6 PRIVATE BLT blt-gp ${OpenCV_LIBS})
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target_link_libraries(image-gp-6 PRIVATE BLT BLT_WITH_GRAPHICS blt-gp ${OpenCV_LIBS})
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if (${ENABLE_ADDRSAN} MATCHES ON)
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target_compile_options(image-gp-6 PRIVATE -fsanitize=address)
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@ -0,0 +1 @@
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Subproject commit 1470d8469d583f4a1b5aaf8916abbd4be2bba1ed
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2
lib/stb
2
lib/stb
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@ -1 +1 @@
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Subproject commit 013ac3beddff3dbffafd5177e7972067cd2b5083
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Subproject commit f7f20f39fe4f206c6f19e26ebfef7b261ee59ee4
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183
src/main.cpp
183
src/main.cpp
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@ -15,11 +15,6 @@
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <https://www.gnu.org/licenses/>.
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*/
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#define STB_IMAGE_RESIZE_IMPLEMENTATION
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#define STB_IMAGE_IMPLEMENTATION
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#define STB_IMAGE_WRITE_IMPLEMENTATION
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#define STB_PERLIN_IMPLEMENTATION
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#include <blt/gp/program.h>
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#include <blt/profiling/profiler_v2.h>
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#include <blt/gp/tree.h>
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@ -29,8 +24,12 @@
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#include <stb_image_resize2.h>
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#include <stb_image_write.h>
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#include <stb_perlin.h>
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#include <blt/gfx/window.h>
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#include "blt/gfx/renderer/resource_manager.h"
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#include "blt/gfx/renderer/batch_2d_renderer.h"
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#include "blt/gfx/renderer/camera.h"
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#include <imgui.h>
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <random>
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@ -39,6 +38,11 @@ static constexpr long IMAGE_SIZE = 128;
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static constexpr blt::size_t CHANNELS = 3;
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static constexpr blt::size_t DATA_SIZE = IMAGE_SIZE * IMAGE_SIZE;
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blt::gfx::matrix_state_manager global_matrices;
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blt::gfx::resource_manager resources;
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blt::gfx::batch_renderer_2d renderer_2d(resources, global_matrices);
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blt::gfx::first_person_camera_2d camera;
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struct context
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{
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float x, y;
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@ -46,34 +50,39 @@ struct context
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struct image_t
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{
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std::array<blt::u8, DATA_SIZE> image_data;
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std::array<blt::u8, DATA_SIZE> gray_data;
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};
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struct full_image_t
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{
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std::array<blt::u8, DATA_SIZE * CHANNELS> image_data;
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std::array<blt::u8, DATA_SIZE * CHANNELS> rgb_data;
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void load(const std::string& path)
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{
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int width, height, channels;
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auto data = stbi_load(path.c_str(), &width, &height, &channels, CHANNELS);
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stbir_resize_uint8_linear(data, width, height, 0, image_data.data(), IMAGE_SIZE, IMAGE_SIZE, 0, static_cast<stbir_pixel_layout>(CHANNELS));
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stbir_resize_uint8_linear(data, width, height, 0, rgb_data.data(), IMAGE_SIZE, IMAGE_SIZE, 0, static_cast<stbir_pixel_layout>(CHANNELS));
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stbi_image_free(data);
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}
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void save(const std::string& str)
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{
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stbi_write_png(str.c_str(), IMAGE_SIZE, IMAGE_SIZE, CHANNELS, image_data.data(), 0);
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stbi_write_png(str.c_str(), IMAGE_SIZE, IMAGE_SIZE, CHANNELS, rgb_data.data(), 0);
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}
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};
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using fitness_data_t = std::array<image_t, 50>;
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//
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//using fitness_data_t = std::array<image_t, 50>;
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//
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//fitness_data_t fitness_red;
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//fitness_data_t fitness_green;
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//fitness_data_t fitness_blue;
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std::array<double, 64> fitness_values;
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std::array<full_image_t, 64> generation_images;
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std::vector<blt::gfx::texture_gl2D> gl_images;
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fitness_data_t fitness_red;
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fitness_data_t fitness_green;
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fitness_data_t fitness_blue;
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full_image_t base_data;
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full_image_t found_data;
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@ -100,7 +109,7 @@ blt::gp::prog_config_t config = blt::gp::prog_config_t()
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.set_max_generations(50)
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.set_mutation_chance(0.4)
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.set_crossover_chance(0.9)
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.set_pop_size(50)
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.set_pop_size(64)
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.set_thread_count(0);
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blt::gp::type_provider type_system;
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@ -230,50 +239,53 @@ inline context get_ctx(blt::size_t i)
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return ctx;
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}
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constexpr auto create_fitness_function(fitness_data_t& fitness_data, blt::size_t channel)
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constexpr auto create_fitness_function(blt::size_t channel)
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{
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return [&fitness_data, channel](blt::gp::tree_t& current_tree, blt::gp::fitness_t& fitness, blt::size_t in) {
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auto& v = fitness_data[in];
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return [channel](blt::gp::tree_t& current_tree, blt::gp::fitness_t& fitness, blt::size_t in) {
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auto& v = generation_images[in];
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for (blt::size_t i = 0; i < DATA_SIZE; i++)
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{
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context ctx = get_ctx(i);
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v.image_data[i] = static_cast<blt::u8>(current_tree.get_evaluation_value<float>(&ctx) * 255);
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auto dist = static_cast<float>(v.image_data[i]) - static_cast<float>(base_data.image_data[i * CHANNELS + channel]);
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fitness.raw_fitness += std::sqrt(dist * dist);
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v.rgb_data[i * CHANNELS + channel] = static_cast<blt::u8>(current_tree.get_evaluation_value<float>(&ctx) * 255);
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}
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BLT_TRACE("Hello1");
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cv::Mat img(IMAGE_SIZE, IMAGE_SIZE, CV_8UC3, v.image_data.data());
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BLT_TRACE("Hello2");
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cv::Mat img_hsv;
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BLT_TRACE("Hello3");
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cv::cvtColor(img, img_hsv, cv::COLOR_RGB2HSV);
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BLT_TRACE("Hello4");
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cv::Mat hist;
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BLT_TRACE("Hello5");
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cv::calcHist(&img_hsv, 1, channels, cv::Mat(), hist, 2, histSize, ranges, true, false);
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BLT_TRACE("Hello6");
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cv::normalize(hist, hist, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
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BLT_TRACE("Hello7");
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fitness.raw_fitness = fitness_values[in];
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fitness.standardized_fitness = fitness.raw_fitness;
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fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness));
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// auto& v = fitness_data[in];
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// for (blt::size_t i = 0; i < DATA_SIZE; i++)
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// {
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// context ctx = get_ctx(i);
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// v.gray_data[i] = static_cast<blt::u8>(current_tree.get_evaluation_value<float>(&ctx) * 255);
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//
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// auto dist = static_cast<float>(v.gray_data[i]) - static_cast<float>(base_data.rgb_data[i * CHANNELS + channel]);
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//
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// fitness.raw_fitness += std::sqrt(dist * dist);
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// }
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// cv::Mat img(IMAGE_SIZE, IMAGE_SIZE, CV_8UC1, v.gray_data.data());
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// cv::Mat img_rgb;
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// cv::Mat img_hsv;
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// cv::cvtColor(img, img_rgb, cv::COLOR_GRAY2RGB);
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// cv::cvtColor(img_rgb, img_hsv, cv::COLOR_RGB2HSV);
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// cv::Mat hist;
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// cv::calcHist(&img_hsv, 1, channels, cv::Mat(), hist, 2, histSize, ranges, true, false);
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// cv::normalize(hist, hist, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
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//
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// auto comp = 1.0 - cv::compareHist(base_image_hist, hist, cv::HISTCMP_CHISQR);
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//
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// fitness.raw_fitness *= comp;
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auto comp = cv::compareHist(base_image_hist, hist, cv::HISTCMP_CORREL);
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fitness.standardized_fitness = fitness.raw_fitness / IMAGE_SIZE;
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fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness)) * comp;
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// fitness.standardized_fitness = fitness.raw_fitness / IMAGE_SIZE;
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// fitness.adjusted_fitness = (1.0 / (1.0 + fitness.standardized_fitness));
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};
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}
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constexpr auto fitness_function_red = create_fitness_function(fitness_red, 0);
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constexpr auto fitness_function_red = create_fitness_function(0);
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constexpr auto fitness_function_green = create_fitness_function(fitness_green, 1);
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constexpr auto fitness_function_green = create_fitness_function(1);
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constexpr auto fitness_function_blue = create_fitness_function(fitness_blue, 2);
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constexpr auto fitness_function_blue = create_fitness_function(2);
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void evaluate_program(blt::gp::gp_program& program)
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{
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BLT_DEBUG("Begin Generation Loop");
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while (!program.should_terminate())
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void execute_generation(blt::gp::gp_program& program)
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{
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BLT_TRACE("------------{Begin Generation %ld}------------", program.get_current_generation());
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BLT_START_INTERVAL("Image Test", "Gen");
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@ -288,6 +300,14 @@ void evaluate_program(blt::gp::gp_program& program)
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BLT_TRACE("----------------------------------------------");
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std::cout << std::endl;
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}
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void evaluate_program(blt::gp::gp_program& program)
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{
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BLT_DEBUG("Begin Generation Loop");
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while (!program.should_terminate())
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{
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execute_generation(program);
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}
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}
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void print_stats(blt::gp::gp_program& program)
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@ -332,9 +352,9 @@ void write_tree(blt::size_t index, blt::size_t best_red, blt::size_t best_blue,
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for (blt::size_t i = 0; i < DATA_SIZE; i++)
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{
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found_data.image_data[i * CHANNELS] = fitness_red[best_red].image_data[i];
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found_data.image_data[i * CHANNELS + 1] = fitness_green[best_green].image_data[i];
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found_data.image_data[i * CHANNELS + 2] = fitness_blue[best_blue].image_data[i];
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found_data.rgb_data[i * CHANNELS] = generation_images[best_red].rgb_data[i * CHANNELS];
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found_data.rgb_data[i * CHANNELS + 1] = generation_images[best_green].rgb_data[i * CHANNELS + 1];
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found_data.rgb_data[i * CHANNELS + 2] = generation_images[best_blue].rgb_data[i * CHANNELS + 2];
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}
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found_data.save("best_image_" + std::to_string(index) + ".png");
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@ -386,15 +406,23 @@ void make_operator_image(T op, Args... args)
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stbi_write_png((blt::type_string<T> + ".png").c_str(), IMAGE_SIZE, IMAGE_SIZE, CHANNELS, value.get(), 0);
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}
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int main()
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void init(const blt::gfx::window_data&)
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{
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using namespace blt::gfx;
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for (blt::size_t i = 0; i < config.population_size; i++)
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{
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gl_images.emplace_back(IMAGE_SIZE, IMAGE_SIZE, GL_RGB8);
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resources.set(std::to_string(i), &gl_images.back());
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}
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BLT_INFO("Starting BLT-GP Image Test");
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BLT_INFO("Using Seed: %ld", SEED);
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BLT_START_INTERVAL("Image Test", "Main");
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BLT_DEBUG("Setup Base Image");
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base_data.load("../Rolex_De_Grande_-_Joo.png");
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cv::Mat base_image_mat{IMAGE_SIZE, IMAGE_SIZE, CV_8UC3, base_data.image_data.data()};
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cv::Mat base_image_mat{IMAGE_SIZE, IMAGE_SIZE, CV_8UC3, base_data.rgb_data.data()};
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cv::cvtColor(base_image_mat, base_image_hsv, cv::COLOR_RGB2HSV);
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cv::calcHist(&base_image_hsv, 1, channels, cv::Mat(), base_image_hist, 2, histSize, ranges, true, false);
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@ -412,9 +440,54 @@ int main()
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program_green.generate_population(type_system.get_type<float>().id(), fitness_function_green);
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program_blue.generate_population(type_system.get_type<float>().id(), fitness_function_blue);
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evaluate_program(program_red);
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evaluate_program(program_green);
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evaluate_program(program_blue);
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// evaluate_program(program_red);
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// evaluate_program(program_green);
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// evaluate_program(program_blue);
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global_matrices.create_internals();
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resources.load_resources();
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renderer_2d.create();
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}
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void update(const blt::gfx::window_data& data)
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{
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global_matrices.update_perspectives(data.width, data.height, 90, 0.1, 2000);
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camera.update();
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camera.update_view(global_matrices);
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global_matrices.update();
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for (blt::size_t i = 0; i < config.population_size; i++)
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gl_images[i].upload(generation_images[i].rgb_data.data(), IMAGE_SIZE, IMAGE_SIZE, GL_RGB);
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if (ImGui::Begin("Program Control"))
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{
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ImGui::Button("Run Generation");
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if (ImGui::IsItemClicked())
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{
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execute_generation(program_red);
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execute_generation(program_green);
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execute_generation(program_blue);
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}
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ImGui::End();
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}
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for (blt::size_t i = 0; i < config.population_size; i++)
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{
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renderer_2d.drawRectangleInternal(std::to_string(i),
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{static_cast<float>(IMAGE_SIZE * i), static_cast<float>(IMAGE_SIZE * i), IMAGE_SIZE, IMAGE_SIZE});
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}
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renderer_2d.render(data.width, data.height);
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}
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int main()
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{
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blt::gfx::init(blt::gfx::window_data{"My Sexy Window", init, update}.setSyncInterval(1));
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global_matrices.cleanup();
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resources.cleanup();
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renderer_2d.cleanup();
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blt::gfx::cleanup();
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BLT_END_INTERVAL("Image Test", "Main");
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Loading…
Reference in New Issue