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添加开闭运算
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@ -5,4 +5,70 @@ include_directories(E:/QTexamble/matrox/Include)
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# 添加 MIL 库的库文件路径
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link_directories(E:/QTexamble/matrox/LIB)
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file(GLOB MIL_LIBS E:/QTexamble/matrox/LIB/*.lib)
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同理 将E:/QTexamble/matrox/LIB部分替换为安装目录下的.../Matrox Imaging/MIL/LIB 即可
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同理 将E:/QTexamble/matrox/LIB部分替换为安装目录下的.../Matrox Imaging/MIL/LIB 即可
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## 鲜艳色彩检测功能
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对应函数：
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```c++
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void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::map<std::string, int>& params);
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// 用法
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// std::map<std::string, int> params;
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// params["saturation_threshold"] = 150;
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// params["saturation_denoising"] = 2;
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void hsv_process(const MIL_ID& inputImage, MIL_ID& outputImageHSV, const std::map<std::string, int>& params);
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// std::map<std::string, int> params;
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// params["green_L_min"] = 68;
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// params["green_L_max"] = 125;
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// params["green_a_min"] = 101;
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// params["green_a_max"] = 120;
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// params["green_b_min"] = 130;
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// params["green_b_max"] = 140;
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//
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// params["blue_L_min"] = 45;
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// params["blue_L_max"] = 66;
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// params["blue_a_min"] = 130;
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// params["blue_a_max"] = 145;
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// params["blue_b_min"] = 95;
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// params["blue_b_max"] = 105;
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//
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// params["orange_L_min"] = 166;
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// params["orange_L_max"] = 191;
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// params["orange_a_min"] = 135;
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// params["orange_a_max"] = 142;
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// params["orange_b_min"] = 160;
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// params["orange_b_max"] = 174;
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//
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// params["black_L_min"] = 0;
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// params["black_L_max"] = 21;
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// params["black_a_min"] = 127;
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// params["black_a_max"] = 133;
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// params["black_b_min"] = 126;
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// params["black_b_max"] = 134;
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//
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// params["red_L_min"] = 71;
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// params["red_L_max"] = 97;
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// params["red_a_min"] = 143;
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// params["red_a_max"] = 153;
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// params["red_b_min"] = 33;
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// params["red_b_max"] = 154;
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//
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// params["purple_L_min"] = 171;
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// params["purple_L_max"] = 197;
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// params["purple_a_min"] = 131;
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// params["purple_a_max"] = 141;
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// params["purple_b_min"] = 108;
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// params["purple_b_max"] = 123;
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// params["lab_denoising"] = 1;
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```
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| | hsv_denoising = 0 | hsv_denoising = 1 | hsv_denoising = 2 |
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| ----------------- | ----------------- | ----------------- | ------------------------------------------- |
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| lab_denoising = 0 | | | |
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| lab_denoising = 1 | | |  |
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| lab_denoising = 2 | | | |
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@ -15,6 +15,10 @@ MIL_ID MilApplication = M_NULL, MilSystem = M_NULL, MilDisplay = M_NULL;
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void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::map<std::string, int>& params)
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{
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MIL_ID MilLabImage = M_NULL, MilLChannel = M_NULL, MilAChannel = M_NULL, MilBChannel = M_NULL;
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MIL_ID lab_result=M_NULL;
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int denoising = params.at("lab_denoising");
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// Check number of bands
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MIL_INT NumBands = 0;
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@ -51,7 +55,7 @@ void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::ma
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MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilBinaryA);
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MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilBinaryB);
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MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &MilResultLab);
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MbufAlloc2d(MilSystem, SizeX, SizeY, 1 + M_UNSIGNED, M_IMAGE + M_PROC, &lab_result);
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const std::vector<std::string> colors = {"green", "blue", "orange", "black", "red", "purple"};
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// Iterate over colors
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@ -83,8 +87,11 @@ void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::ma
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MimArith(MilResultLab, MilBinaryB, MilResultLab, M_AND);
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// 与输出图像合并
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MimArith(outputImageLab, MilResultLab, outputImageLab, M_OR);
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MimArith(lab_result, MilResultLab, lab_result, M_OR);
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}
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MimClose(lab_result, MilResultLab, denoising, M_BINARY);
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MimOpen(MilResultLab, outputImageLab, denoising, M_BINARY);
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// Free binary buffers
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MbufFree(MilBinaryL);
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@ -97,12 +104,17 @@ void lab_process(const MIL_ID& inputImage, MIL_ID& outputImageLab, const std::ma
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MbufFree(MilAChannel);
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MbufFree(MilBChannel);
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MbufFree(MilLabImage);
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MbufFree(lab_result);
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}
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void hsv_process(const MIL_ID& inputImage, MIL_ID& outputImageHSV, const std::map<std::string, int>& params)
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{
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MIL_ID MilHSVImage = M_NULL, MilHChannel = M_NULL, MilSChannel = M_NULL, MilVChannel = M_NULL;
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MIL_ID hsv_result = M_NULL;
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MIL_ID hsv_denoising = M_NULL;
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int saturationThreshold = params.at("saturation_threshold");
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int denoising = params.at("saturation_denoising");
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// 检查输入图像的通道数
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MIL_INT NumBands = 0;
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MbufInquire(inputImage, M_SIZE_BAND, &NumBands);
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@ -131,17 +143,28 @@ void hsv_process(const MIL_ID& inputImage, MIL_ID& outputImageHSV, const std::ma
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// 分配输出图像缓冲区
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MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL),
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MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED,
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M_IMAGE + M_PROC + M_DISP, &outputImageHSV);
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M_IMAGE + M_PROC + M_DISP, &hsv_result);
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MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL),
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MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED,
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M_IMAGE + M_PROC + M_DISP, &hsv_denoising);
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MbufAlloc2d(MilSystem, MbufInquire(inputImage, M_SIZE_X, M_NULL),
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MbufInquire(inputImage, M_SIZE_Y, M_NULL), 8 + M_UNSIGNED,
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M_IMAGE + M_PROC + M_DISP, &outputImageHSV);
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// 对 S 通道进行阈值分割
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MimBinarize(MilSChannel, outputImageHSV, M_GREATER,
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MimBinarize(MilSChannel, hsv_result, M_GREATER,
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saturationThreshold, M_NULL);
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MimClose(hsv_result, hsv_denoising, denoising, M_BINARY);
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MimOpen(hsv_denoising, outputImageHSV, denoising, M_BINARY);
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// 释放资源
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MbufFree(MilHChannel);
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MbufFree(MilSChannel);
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MbufFree(MilVChannel);
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MbufFree(MilHSVImage);
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MbufFree(hsv_result);
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MbufFree(hsv_denoising);
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}
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void high_sat_detect(const MIL_ID& inputImage, MIL_ID& outputImage, const std::map<std::string, int>& params) {
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@ -214,8 +237,10 @@ int main()
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params["purple_a_max"] = 141;
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params["purple_b_min"] = 108;
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params["purple_b_max"] = 123;
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params["lab_denoising"] = 1;
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params["saturation_threshold"] = 150;
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params["saturation_denoising"] = 1;
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// Initialize combined result
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MIL_ID detection_result = M_NULL;
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