From 263e32e9a0916d0d1e2db25cbfa34348dfed2b33 Mon Sep 17 00:00:00 2001 From: zjc-zjc-123 <1714105370@qq.com> Date: Mon, 18 Nov 2024 17:25:11 +0800 Subject: [PATCH] =?UTF-8?q?=E7=BB=86=E5=BE=AE=E8=B0=83=E6=95=B4?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- CMakeLists.txt | 8 +- Matrox/color_range.cpp | 253 +++++++++++++++++++++++------------------ Matrox/color_range.h | 58 ++++++++++ Matrox/utils.cpp | 9 ++ Matrox/utils.h | 21 ++++ 5 files changed, 237 insertions(+), 112 deletions(-) create mode 100644 Matrox/utils.cpp create mode 100644 Matrox/utils.h diff --git a/CMakeLists.txt b/CMakeLists.txt index 299634d..bb94a0c 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -43,7 +43,8 @@ add_executable(cotton_color cotton_color.cpp) target_link_libraries(cotton_color Qt6::Widgets ${OpenCV_LIBS} comdlg32) # 添加可执行文件 cotton_color -add_executable(cotton_range Matrox/color_range.cpp) +add_executable(cotton_range Matrox/color_range.cpp + Matrox/color_range.h Matrox/utils.h Matrox/utils.cpp) # 链接 OpenCV 和 Qt 库 target_link_libraries(cotton_range Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS}) @@ -52,11 +53,12 @@ add_executable(cotton_color2 cotton_color2.cpp) # 链接 OpenCV 和 Qt 库 target_link_libraries(cotton_color2 Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS}) -add_executable(color_matching Matrox/template_matching.cpp) +add_executable(color_matching Matrox/template_matching.cpp + Matrox/utils.cpp + Matrox/utils.h) target_link_libraries(color_matching Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS}) - add_executable(ui Matrox/ui.cpp) target_link_libraries(ui Qt6::Widgets) diff --git a/Matrox/color_range.cpp b/Matrox/color_range.cpp index e4d93ef..a3b1e60 100644 --- a/Matrox/color_range.cpp +++ b/Matrox/color_range.cpp @@ -1,44 +1,22 @@ -// -// Created by zjc on 24-11-12. -// - -#include #include -#include -#define IMAGE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\cotton2.bmp") +#include +#include +#include +#include "utils.h" -// 全局变量，方便在各个函数中使用 +#define IMAGE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\cotton_image\\174.bmp") +#define SAVE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\diguandai.png") + + +// Global variables MIL_ID MilApplication = M_NULL, MilSystem = M_NULL, MilDisplay = M_NULL; - -// 时间测量模板函数 -template -void measureExecutionTime(Func func) { - // 获取当前时间作为起点 - auto start = std::chrono::high_resolution_clock::now(); - - // 执行传入的函数 - func(); - - // 获取当前时间作为结束点 - auto end = std::chrono::high_resolution_clock::now(); - - // 计算时间差并转换为毫秒 - auto duration = std::chrono::duration_cast(end - start); - - std::cout << "Function execution time: " << duration.count() << " milliseconds" << std::endl; -} - -// LabProcess 函数，支持通过参数控制阈值范围，提供默认值 -void LabProcess(MIL_ID& inputImage, MIL_ID& outputImageLab, - MIL_DOUBLE lowerL = 101.0, MIL_DOUBLE upperL = 135.0, - MIL_DOUBLE lowerA = 101.0, MIL_DOUBLE upperA = 120.0, - MIL_DOUBLE lowerB = 95.0, MIL_DOUBLE upperB = 134.0) +// Optimized LabProcess function +void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::map& params) { MIL_ID MilLabImage = M_NULL, MilLChannel = M_NULL, MilAChannel = M_NULL, MilBChannel = M_NULL; - MIL_ID MilBinaryL = M_NULL, MilBinaryA = M_NULL, MilBinaryB = M_NULL; - // 检查输入图像的通道数 + // Check number of bands MIL_INT NumBands = 0; MbufInquire(inputImage, M_SIZE_BAND, &NumBands); if (NumBands != 3) @@ -47,62 +25,84 @@ void LabProcess(MIL_ID& inputImage, MIL_ID& outputImageLab, return; } - // 分配用于存储 Lab 图像的缓冲区 - MbufAllocColor(MbufInquire(inputImage, M_OWNER_SYSTEM, M_NULL), 3, - MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), - 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, - &MilLabImage); + // Inquire image properties once + MIL_ID MilSystem = MbufInquire(inputImage, M_OWNER_SYSTEM, M_NULL); + MIL_INT SizeX = MbufInquire(inputImage, M_SIZE_X, M_NULL); + MIL_INT SizeY = MbufInquire(inputImage, M_SIZE_Y, M_NULL); - // 将图像从 sRGB 转换到 Lab + // Allocate buffer for Lab image + MbufAllocColor(MilSystem, 3, SizeX, SizeY, 8 + M_UNSIGNED, M_IMAGE + M_PROC, &MilLabImage); + + // Convert image from sRGB to Lab MimConvert(inputImage, MilLabImage, M_SRGB_TO_LAB); - // 创建 Lab 通道的子缓冲区 + // Create child buffers for L, a, b channels MbufChildColor(MilLabImage, 0, &MilLChannel); MbufChildColor(MilLabImage, 1, &MilAChannel); MbufChildColor(MilLabImage, 2, &MilBChannel); - // 分配二值图像缓冲区 - MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, &MilBinaryL); - MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, &MilBinaryA); - MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, &MilBinaryB); + // Allocate output image as 1-bit image + MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &outputImageLab); + MbufClear(outputImageLab, 0); // Initialize to 0 - // 对每个通道进行阈值分割 - MimBinarize(MilLChannel, MilBinaryL, M_IN_RANGE, lowerL, upperL); - MimBinarize(MilAChannel, MilBinaryA, M_IN_RANGE, lowerA, upperA); - MimBinarize(MilBChannel, MilBinaryB, M_IN_RANGE, lowerB, upperB); + // Pre-allocate binary buffers as 1-bit images + MIL_ID MilBinaryL = M_NULL, MilBinaryA = M_NULL, MilBinaryB = M_NULL, MilResultLab = M_NULL; + MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilBinaryL); + MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilBinaryA); + MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilBinaryB); + MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilResultLab); - // 分配输出图像缓冲区 - MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, &outputImageLab); + const std::vector colors = {"green", "blue", "orange", "black", "red", "purple"}; - // 将结果合并 - MimArith(MilBinaryL, MilBinaryA, outputImageLab, M_AND); - MimArith(outputImageLab, MilBinaryB, outputImageLab, M_AND); + // Iterate over colors + // 遍历颜色 + for (const auto& color : colors) { + // 构建参数键 + std::string L_min_key = color + "_L_min"; + std::string L_max_key = color + "_L_max"; + std::string a_min_key = color + "_a_min"; + std::string a_max_key = color + "_a_max"; + std::string b_min_key = color + "_b_min"; + std::string b_max_key = color + "_b_max"; - // 释放资源 + // 获取参数值 + int L_min = params.at(L_min_key); + int L_max = params.at(L_max_key); + int a_min = params.at(a_min_key); + int a_max = params.at(a_max_key); + int b_min = params.at(b_min_key); + int b_max = params.at(b_max_key); + + // 对每个通道进行二值化 + MimBinarize(MilLChannel, MilBinaryL, M_IN_RANGE, L_min, L_max); + MimBinarize(MilAChannel, MilBinaryA, M_IN_RANGE, a_min, a_max); + MimBinarize(MilBChannel, MilBinaryB, M_IN_RANGE, b_min, b_max); + + // 合并阈值结果 + MimArith(MilBinaryL, MilBinaryA, MilResultLab, M_AND); + MimArith(MilResultLab, MilBinaryB, MilResultLab, M_AND); + + // 与输出图像合并 + MimArith(outputImageLab, MilResultLab, outputImageLab, M_OR); + } + + // Free binary buffers MbufFree(MilBinaryL); MbufFree(MilBinaryA); MbufFree(MilBinaryB); + MbufFree(MilResultLab); + + // Free resources MbufFree(MilLChannel); MbufFree(MilAChannel); MbufFree(MilBChannel); MbufFree(MilLabImage); } -// HSVProcess 函数，支持通过参数控制饱和度阈值，提供默认值 -void HSVProcess(MIL_ID& inputImage, MIL_ID& outputImageHSV, MIL_DOUBLE saturationThreshold = 120.0) +void hsv_process(const MIL_ID& inputImage, MIL_ID& outputImageHSV, const std::map& params) { MIL_ID MilHSVImage = M_NULL, MilHChannel = M_NULL, MilSChannel = M_NULL, MilVChannel = M_NULL; - + int saturationThreshold = params.at("saturation_threshold"); // 检查输入图像的通道数 MIL_INT NumBands = 0; MbufInquire(inputImage, M_SIZE_BAND, &NumBands); @@ -134,7 +134,8 @@ void HSVProcess(MIL_ID& inputImage, MIL_ID& outputImageHSV, MIL_DOUBLE saturatio M_IMAGE + M_PROC + M_DISP, &outputImageHSV); // 对 S 通道进行阈值分割 - MimBinarize(MilSChannel, outputImageHSV, M_GREATER, saturationThreshold, M_NULL); + MimBinarize(MilSChannel, outputImageHSV, M_GREATER, + saturationThreshold, M_NULL); // 释放资源 MbufFree(MilHChannel); @@ -143,62 +144,96 @@ void HSVProcess(MIL_ID& inputImage, MIL_ID& outputImageHSV, MIL_DOUBLE saturatio MbufFree(MilHSVImage); } -// 综合测试函数，调用 LabProcess 和 HSVProcess 并合并结果 -void test_hsv(MIL_ID& inputImage, - MIL_DOUBLE lowerL = 101.0, MIL_DOUBLE upperL = 135.0, - MIL_DOUBLE lowerA = 101.0, MIL_DOUBLE upperA = 120.0, - MIL_DOUBLE lowerB = 95.0, MIL_DOUBLE upperB = 134.0, - MIL_DOUBLE saturationThreshold = 120.0) -{ - MIL_ID MilResultLab = M_NULL, MilResultHSV = M_NULL, MilCombinedResult = M_NULL; +void high_sat_detect(const MIL_ID& inputImage, MIL_ID& outputImage, const std::map& params) { + MIL_ID output_hsv=M_NULL, output_lab=M_NULL; - // 调用 LabProcess - LabProcess(inputImage, MilResultLab, lowerL, upperL, lowerA, upperA, lowerB, upperB); + hsv_process(inputImage, output_hsv, params); + lab_process(inputImage, output_lab, params); - // 调用 HSVProcess - HSVProcess(inputImage, MilResultHSV, saturationThreshold); - - // 分配合并结果的缓冲区 MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL), - MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED, - M_IMAGE + M_PROC + M_DISP, &MilCombinedResult); + MbufInquire(inputImage, M_SIZE_Y, M_NULL), 1 + M_UNSIGNED, + M_IMAGE + M_PROC, &outputImage); // 合并 Lab 和 HSV 的结果（取“或”运算） - MimArith(MilResultLab, MilResultHSV, MilCombinedResult, M_OR); + MimArith(output_hsv, output_lab, outputImage, M_OR); - //// 显示合并后的结果图像 - MdispSelect(MilDisplay, MilCombinedResult); - - //// 等待用户查看处理后的图像 - printf("图像已处理并合并，按下 退出程序。\n"); - getchar(); - - // 释放资源 - MbufFree(MilResultLab); - MbufFree(MilResultHSV); - MbufFree(MilCombinedResult); + MbufFree(output_lab); + MbufFree(output_hsv); } - int main() { + // Initialize MIL application + MappAllocDefault(M_DEFAULT, &MilApplication, &MilSystem, &MilDisplay, M_NULL, + M_NULL); + + // Load input image MIL_ID MilImage = M_NULL; - - // 初始化 MIL 应用程序 - MappAllocDefault(M_DEFAULT, &MilApplication, &MilSystem, &MilDisplay, M_NULL, M_NULL); - - // 加载输入图像 MbufRestore(IMAGE_PATH, MilSystem, &MilImage); - // 使用 lambda 表达式测量 test_hsv() 的执行时间 - measureExecutionTime([&]() { - test_hsv(MilImage); - }); + // Define color ranges + std::map params; + params["green_L_min"] = 68; + params["green_L_max"] = 125; + params["green_a_min"] = 101; + params["green_a_max"] = 120; + params["green_b_min"] = 130; + params["green_b_max"] = 140; + params["blue_L_min"] = 45; + params["blue_L_max"] = 66; + params["blue_a_min"] = 130; + params["blue_a_max"] = 145; + params["blue_b_min"] = 95; + params["blue_b_max"] = 105; - // 释放资源 + params["orange_L_min"] = 166; + params["orange_L_max"] = 191; + params["orange_a_min"] = 135; + params["orange_a_max"] = 142; + params["orange_b_min"] = 160; + params["orange_b_max"] = 174; + + params["black_L_min"] = 0; + params["black_L_max"] = 21; + params["black_a_min"] = 127; + params["black_a_max"] = 133; + params["black_b_min"] = 126; + params["black_b_max"] = 134; + + params["red_L_min"] = 71; + params["red_L_max"] = 97; + params["red_a_min"] = 143; + params["red_a_max"] = 153; + params["red_b_min"] = 33; + params["red_b_max"] = 154; + + params["purple_L_min"] = 171; + params["purple_L_max"] = 197; + params["purple_a_min"] = 131; + params["purple_a_max"] = 141; + params["purple_b_min"] = 108; + params["purple_b_max"] = 123; + + params["saturation_threshold"] = 150; + + // Initialize combined result + MIL_ID detection_result = M_NULL; + + // Measure execution time + measure_execution_time([&]() { + high_sat_detect(MilImage, detection_result, params); + }); + MbufSave(SAVE_PATH, detection_result); + // Display result + + std::cout << "所有颜色检测已完成并合并。按 退出。" << std::endl; + getchar(); + + // Free resources + MbufFree(detection_result); MbufFree(MilImage); MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL); return 0; -} \ No newline at end of file +} diff --git a/Matrox/color_range.h b/Matrox/color_range.h index 8a567e9..0c4cfcc 100644 --- a/Matrox/color_range.h +++ b/Matrox/color_range.h @@ -5,4 +5,62 @@ #ifndef COLOR_RANGE_H #define COLOR_RANGE_H +#include +#include +#include + +void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::map& params); +// 用法 +// std::map params; +// params["saturation_threshold"] = 150; + +void hsv_process(const MIL_ID& inputImage, MIL_ID& outputImageHSV, const std::map& params); +// 用法 +// std::map params; +// params["green_L_min"] = 68; +// params["green_L_max"] = 125; +// params["green_a_min"] = 101; +// params["green_a_max"] = 120; +// params["green_b_min"] = 130; +// params["green_b_max"] = 140; +// +// params["blue_L_min"] = 45; +// params["blue_L_max"] = 66; +// params["blue_a_min"] = 130; +// params["blue_a_max"] = 145; +// params["blue_b_min"] = 95; +// params["blue_b_max"] = 105; +// +// params["orange_L_min"] = 166; +// params["orange_L_max"] = 191; +// params["orange_a_min"] = 135; +// params["orange_a_max"] = 142; +// params["orange_b_min"] = 160; +// params["orange_b_max"] = 174; +// +// params["black_L_min"] = 0; +// params["black_L_max"] = 21; +// params["black_a_min"] = 127; +// params["black_a_max"] = 133; +// params["black_b_min"] = 126; +// params["black_b_max"] = 134; +// +// params["red_L_min"] = 71; +// params["red_L_max"] = 97; +// params["red_a_min"] = 143; +// params["red_a_max"] = 153; +// params["red_b_min"] = 33; +// params["red_b_max"] = 154; +// +// params["purple_L_min"] = 171; +// params["purple_L_max"] = 197; +// params["purple_a_min"] = 131; +// params["purple_a_max"] = 141; +// params["purple_b_min"] = 108; +// params["purple_b_max"] = 123; +// + + + + #endif //COLOR_RANGE_H diff --git a/Matrox/utils.cpp b/Matrox/utils.cpp new file mode 100644 index 0000000..6db5430 --- /dev/null +++ b/Matrox/utils.cpp @@ -0,0 +1,9 @@ +// +// Created by zjc on 24-11-18. +// + +#include "utils.h" + + + +// 图片转换函数，输入4096*1024*3的图片，输出为(4096 / n_valves) * (1024 / n_merge_vertical) * 1 diff --git a/Matrox/utils.h b/Matrox/utils.h new file mode 100644 index 0000000..154a12a --- /dev/null +++ b/Matrox/utils.h @@ -0,0 +1,21 @@ +// +// Created by zjc on 24-11-18. +// + +#ifndef UTILS_H +#define UTILS_H + +#include +#include +template +// Time measurement function +void measure_execution_time(Func func) { + std::chrono::time_point start; + start = std::chrono::steady_clock::now(); + func(); + auto end = std::chrono::steady_clock::now(); + auto duration = std::chrono::duration_cast(end - start); + std::cout << "Function execution time: " << duration.count() << " milliseconds" << std::endl; +} + +#endif //UTILS_H