添加MIL到OpenCV转换，支持彩色图像转换

2025-11-09 11:13:54 +00:00 · 2024-11-27 00:10:44 +08:00 · 2024-11-27 00:10:44 +08:00 · 50058f4ad1
commit 50058f4ad1
parent cf1dde8a62
8 changed files with 101 additions and 226 deletions
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@ -4,6 +4,7 @@ project(cotton_color)
 set(CMAKE_CXX_STANDARD 17)

 add_definitions(-DUNICODE -D_UNICODE)
+add_compile_options(/utf-8)

 # 设置 OpenCV 路径
 if(DEFINED ENV{OpenCV_DIR})
@ -42,40 +43,8 @@ file(GLOB MIL_LIBS E:/QTexamble/matrox/LIB/*.lib)
 add_subdirectory(src)
 add_subdirectory(tests)

-## 添加可执行文件 cotton_color
-#add_executable(cotton_color cotton_color.cpp)
-## 链接 OpenCV 和 Qt 库
-#target_link_libraries(cotton_color Qt6::Widgets ${OpenCV_LIBS} comdlg32)
-#
-## 添加可执行文件 cotton_color
-#add_executable(cotton_range src/Matrox/color_range.cpp
-#        src/Matrox/color_range.h src/Matrox/utils.h src/Matrox/utils.cpp)
-## 链接 OpenCV 和 Qt 库
-#target_link_libraries(cotton_range Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS})
-#
-## 添加可执行文件 cotton_color2
-#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(template_matching src/Matrox/template_matching.cpp
-#        src/Matrox/color_range.cpp src/Matrox/color_range.h
-#        src/Matrox/utils.cpp src/Matrox/utils.h)
-#target_link_libraries(template_matching Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS})
-#
-#
-#add_executable(ui src/Matrox/ui.cpp)
-#target_link_libraries(ui Qt6::Widgets)
-#
-#
-#add_executable(onnx src/Matrox/onnx_running.cpp)
-#target_link_libraries(onnx Qt6::Widgets ${MIL_LIBS})
-#
+
 add_executable(opencv_onnx opencv_onnx.cpp)
 # 链接 OpenCV 和 Qt 库
 target_link_libraries(opencv_onnx Qt6::Widgets ${OpenCV_LIBS} comdlg32)
-#
-#
-#add_executable(create_mask src/Matrox/mask.cpp)
-#target_link_libraries(create_mask Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS})
-#add_executable(test_color_range tests/test_color_range.cpp)
+
--- a/src/Matrox/utils.cpp
+++ b/src/Matrox/utils.cpp
@ -11,7 +11,13 @@
 #include <opencv2/core/mat.hpp>
 #include "Mil.h"
 #include <opencv2/opencv.hpp>
+
+#include <fstream>
+#include <string>
+#include <sstream>
+#include <unordered_map>
 using namespace std;
+using namespace cv;

 /**
 * Convert Lab values from Photoshop range to OpenCV range.
@ -121,11 +127,6 @@ void read_params_from_file(const std::string& filename, std::map<std::string, in
    }
 }

-#include <fstream>
-#include <string>
-#include <sstream>
-#include <unordered_map>
-


 // 函数：从配置文件中读取参数
@ -167,61 +168,52 @@ std::unordered_map<std::string, int> loadConfig(const std::string& filename){

 // 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

-#include "mil.h"  // 包含 MIL 库的头文件
+Mat mil2mat(const MIL_ID mil_img) {
+    // 获取 MIL 图像的宽度、高度和通道数
+    MIL_INT width, height, channels;
+    MbufInquire(mil_img, M_SIZE_X, &width);
+    MbufInquire(mil_img, M_SIZE_Y, &height);
+    MbufInquire(mil_img, M_SIZE_BAND, &channels);

-// cv::Mat milToMat(MIL_ID milImage, MIL_ID MilSystem) {
-//     // 获取图像的宽度、高度和像素格式
-//     int width, height, channels;
-//     MbufInquire(milImage, M_SIZE_X, &width);  // 获取图像宽度
-//     MbufInquire(milImage, M_SIZE_Y, &height); // 获取图像高度
-//     MbufInquire(milImage, M_SIZE_BAND, &channels); // 获取图像通道数
-//
-//     // 为图像数据分配内存
-//     byte* buf = new byte[width * height]();  // 初始化内存
-//
-//     // 如果是彩色图像，则转换为灰度图
-//     if (channels > 1) {
-//         MIL_ID grayscaleImage;
-//         // 分配一个新的灰度图像缓冲区
-//         MbufAlloc2d(MilSystem, width, height, 8 + M_UNSIGNED, M_IMAGE + M_PROC + M_DISP, &grayscaleImage);
-//         // 将彩色图像转换为灰度图
-//         MimConvert(milImage, grayscaleImage, M_RGB_TO_L);
-//         // 获取转换后的灰度图像数据
-//         MbufGet(grayscaleImage, buf);
-//         MbufFree(grayscaleImage);  // 释放灰度图像缓冲区
-//     } else {
-//         // 如果本身是灰度图像，直接获取数据
-//         MbufGet(milImage, buf);
-//     }
-//
-//     // 将数据封装成OpenCV Mat对象
-//     cv::Mat cvMat(height, width, CV_8UC1, buf);
-//     return cvMat;
-// }
-cv::Mat milToMat(MIL_ID milImage) {
-    // 获取图像的宽度、高度和像素格式
-    int width, height;
-    MIL_INT pixelFormat;
-    MbufInquire(milImage, M_SIZE_X, &width);  // 获取图像宽度
-    MbufInquire(milImage, M_SIZE_Y, &height); // 获取图像高度
-    MbufInquire(milImage, M_TYPE, &pixelFormat); // 获取图像像素格式
-
-    // 判断像素格式并选择适当的数据类型
-    // MIL_INT 和 M_UINT8 是典型的像素格式，OpenCV 处理不同的类型会有不同的实现
-    cv::Mat matImage;
-    if (pixelFormat == M_RGB)
-    {
-        // 如果是RGB图像
-        matImage = cv::Mat(height, width, CV_8UC3);
+    if (channels == 1) {
+        // 单通道图像，直接读取整个缓冲区
+        Mat grayImage(height, width, CV_8UC1);
+        MbufGet(mil_img, grayImage.data);
+        return grayImage;
    }
-    else
-    {// 如果是其他类型的图像，你需要根据实际格式进行调整
-        std::cerr << "Unsupported MIL image format!" << std::endl;
-        return matImage;
+    if (channels == 3) {
+        // 多通道图像，分通道读取
+        MIL_ID redChannel, greenChannel, blueChannel;
+        MbufAlloc2d(M_DEFAULT, width, height, 8 + M_UNSIGNED, M_IMAGE + M_PROC, &redChannel);
+        MbufAlloc2d(M_DEFAULT, width, height, 8 + M_UNSIGNED, M_IMAGE + M_PROC, &greenChannel);
+        MbufAlloc2d(M_DEFAULT, width, height, 8 + M_UNSIGNED, M_IMAGE + M_PROC, &blueChannel);
+
+        // 将 MIL 图像的各个通道复制到单通道缓冲区
+        MbufCopyColor(mil_img, redChannel, M_RED);
+        MbufCopyColor(mil_img, greenChannel, M_GREEN);
+        MbufCopyColor(mil_img, blueChannel, M_BLUE);
+
+        // 分别读取每个通道的数据
+        Mat redMat(height, width, CV_8UC1);
+        Mat greenMat(height, width, CV_8UC1);
+        Mat blueMat(height, width, CV_8UC1);
+        MbufGet(redChannel, redMat.data);
+        MbufGet(greenChannel, greenMat.data);
+        MbufGet(blueChannel, blueMat.data);
+        // 释放通道缓冲区
+        MbufFree(redChannel);
+        MbufFree(greenChannel);
+        MbufFree(blueChannel);
+
+        // 合并通道
+        std::vector<Mat> bgrChannels = {blueMat, greenMat, redMat};
+        Mat colorImage;
+        cv::merge(bgrChannels, colorImage);
+
+        return colorImage;
    }
-
-    // 获取图像数据并复制到 OpenCV Mat
-    MbufGet(milImage, matImage.data);  // 获取 MIL 图像数据并拷贝到 Mat 对象
-
-    return matImage;
+    // 不支持的通道数
+    std::cerr << "[Error] Unsupported number of channels: " << channels << std::endl;
+    return Mat();
 }
+
--- a/src/Matrox/utils.h
+++ b/src/Matrox/utils.h
@ -39,7 +39,7 @@ MIL_ID convert_to_uint8(MIL_ID input_img);

 std::wstring convert_to_wstring(const std::string& str);
 void read_params_from_file(const std::string& filename, std::map<std::string, int>& params) ;
-cv::Mat milToMat(MIL_ID MilImage);
+cv::Mat mil2mat(MIL_ID mil_img);
 void processImage(cv::Mat& img);

 std::unordered_map<std::string, int> loadConfig(const std::string& filename);
--- a/tests/CMakeLists.txt
+++ b/tests/CMakeLists.txt
@ -14,7 +14,6 @@ add_executable(test_template_matching
 target_link_libraries(test_template_matching Matrox ${OpenCV_LIBS} ${MIL_LIBS})


-
 #测试用例 3：test_mask
 add_executable(test_mask
        ${CMAKE_CURRENT_SOURCE_DIR}/test_mask.cpp)
@ -27,11 +26,11 @@ add_executable(test_onnx
 # 链接 Matrox 模块和依赖库
 target_link_libraries(test_onnx CVDL ${OpenCV_LIBS} ${MIL_LIBS})

-#测试用例 4：test_onnx
+#测试用例 4：test_MIltoMat
 add_executable(test_MILtoMat
        ${CMAKE_CURRENT_SOURCE_DIR}/test_MILtoMat.cpp)
 # 链接 Matrox 模块和依赖库
-target_link_libraries(test_MILtoMat CVDL ${OpenCV_LIBS} ${MIL_LIBS})
+target_link_libraries(test_MILtoMat Matrox CVDL ${OpenCV_LIBS} ${MIL_LIBS})

 #测试用例 4：test_onnx
 add_executable(test_total
--- a/tests/test_MILtoMat.cpp
+++ b/tests/test_MILtoMat.cpp
@ -1,82 +1,63 @@
 #include <iostream>
+#include <Matrox/utils.h>
 #include <opencv2/opencv.hpp>
 #include "Mil.h"  // 引入 MIL 库

-#define IMAGE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\8.bmp")
-#define SAVE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\suspect.png")
+#define IMAGE_PATH MIL_TEXT(".\\test_imgs\\test_gray.png")
+#define IMAGE_PATH_COLOR MIL_TEXT(".\\test_imgs\\8.bmp")
+#define SAVE_PATH MIL_TEXT(".\\runs\\test_MILtoMat.png")
+
+using namespace std;
+
+void show_img_info(const MIL_ID mil_img) {
+    // 获取图像尺寸和通道数
+    MIL_INT width, height, channels;
+    MbufInquire(mil_img, M_SIZE_X, &width);  // 获取图像宽度
+    MbufInquire(mil_img, M_SIZE_Y, &height); // 获取图像高度
+    MbufInquire(mil_img, M_SIZE_BAND, &channels); // 获取图像通道数
+    cout << "Gray MIL Image loaded successfully!" << endl;
+    cout << "Width: " << width << endl;
+    cout << "Height: " << height << endl;
+    cout << "Channels: " << channels << endl;
+}

 int main() {
    MIL_ID MilApplication = M_NULL, MilSystem = M_NULL, MilDisplay = M_NULL;
    MIL_ID MilImage = M_NULL;
-
    // 初始化 MIL 应用程序、系统和显示
    MappAllocDefault(M_DEFAULT, &MilApplication, &MilSystem, &MilDisplay, M_NULL, M_NULL);
-    if (MilApplication == M_NULL || MilSystem == M_NULL || MilDisplay == M_NULL) {
-        std::cerr << "MIL Initialization failed!" << std::endl;
-        return -1;
-    }

-    // 加载图像
+    // 测试用例1：灰度图测试
    MbufRestore(IMAGE_PATH, MilSystem, &MilImage);
-    if (MilImage == M_NULL) {
-        std::cerr << "Failed to load MIL image!" << std::endl;
-        MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL);
-        return -1;
-    }
-
-    // 获取图像尺寸和通道数
-    int width, height, channels;
-    MbufInquire(MilImage, M_SIZE_X, &width);  // 获取图像宽度
-    MbufInquire(MilImage, M_SIZE_Y, &height); // 获取图像高度
-    MbufInquire(MilImage, M_SIZE_BAND, &channels); // 获取图像通道数
-
-    // 为图像数据分配缓冲区
-    unsigned char* m_AvsBuffer = (unsigned char*)malloc(width * height * channels);
-
-    if (m_AvsBuffer == NULL) {
-        std::cerr << "Memory allocation for image buffer failed!" << std::endl;
-        MbufFree(MilImage);
-        MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL);
-        return -1;
-    }
-
-    // 获取 MIL 图像数据
-    MbufGet(MilImage, m_AvsBuffer);
-
-    // 将 MIL 图像数据转换为 OpenCV 格式
-    cv::Mat cvImage;
-
-    if (channels == 1) {
-        // 灰度图像（1 通道）
-        cvImage = cv::Mat(height, width, CV_8UC1, m_AvsBuffer);
-    } else if (channels == 3) {
-        // 彩色图像（3 通道，BGR）
-        cvImage = cv::Mat(height, width, CV_8UC3, m_AvsBuffer);
-    } else {
-        std::cerr << "Unsupported number of channels: " << channels << std::endl;
-        free(m_AvsBuffer);
-        MbufFree(MilImage);
-        MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL);
-        return -1;
-    }
-
-    // 显示图像
-    MdispSelect(MilDisplay, MilImage);  // 在 MIL 显示中显示图像
-    cv::imshow("MIL Image", cvImage);   // 使用 OpenCV 显示图像
-
+    show_img_info(MilImage);
+    cv::Mat cvImg = mil2mat(MilImage);
+    cout << "MIL Image converted successfully!" << endl;
+    cv::imshow("MIL Image", cvImg);   // 使用 OpenCV 显示图像
    // 等待按键并关闭窗口
    cv::waitKey(0);
-
    // 保存图像
-    std::string savepath = "C:\\Users\\zjc\\Desktop\\suspect.png";
-    if (!cv::imwrite(savepath, cvImage)) {
-        std::cerr << "Failed to save image!" << std::endl;
+    string savepath = ".\\runs\\test_MILtoMat_gray.png";
+    if (!cv::imwrite(savepath, cvImg)) {
+        cerr << "Failed to save image!" << endl;
    }

-    // 释放资源
-    free(m_AvsBuffer);  // 释放缓冲区
-    MbufFree(MilImage); // 释放 MIL 图像资源
-    MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL);  // 释放 MIL 系统资源
+    //测试用例2：彩色图测试
+    MIL_ID MilImage2 = M_NULL;
+    MbufRestore(IMAGE_PATH_COLOR, MilSystem, &MilImage2);
+    // show_img_info(MilImage2);
+    cv::Mat cvImgColor = mil2mat(MilImage2);
+    cout << "MIL Image converted successfully!" << endl;
+    cv::imshow("MIL Image COLOR", cvImgColor);   // 使用 OpenCV 显示图像
+    // 等待按键并关闭窗口
+    cv::waitKey(0);
+    // 保存图像
+    savepath = ".\\runs\\test_MILtoMat_color.png";
+    if (!imwrite(savepath, cvImgColor)) {
+        cerr << "Failed to save image!" << endl;
+    }

+    MbufFree(MilImage); // 释放 MIL 图像资源
+    MbufFree(MilImage2);
+    MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL, M_NULL);  // 释放 MIL 系统资源
    return 0;
 }
--- a/tests/test_imgs/8.bmp
+++ b/tests/test_imgs/8.bmp
--- a/tests/test_imgs/test_gray.png
+++ b/tests/test_imgs/test_gray.png
--- a/tests/test_onnx.cpp
+++ b/tests/test_onnx.cpp
@ -1,69 +1,3 @@
-// #include "vector"
-// #include"iostream"
-// #include"string"
-// #include"Matrox/utils.h"
-// #include"opencv2/opencv.hpp"
-//
-// #define IMAGE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\8.bmp")
-// #define SAVE_PATH MIL_TEXT("C:\\Users\\zjc\\Desktop\\suspect.png")
-
-// int main() {
-//     MIL_ID MilImage = M_NULL;
-//     MIL_ID MilApplication = M_NULL, MilSystem = M_NULL, MilDisplay = M_NULL;
-//
-//     MappAllocDefault(M_DEFAULT, &MilApplication, &MilSystem, &MilDisplay, M_NULL,
-//       M_NULL);
-//     MbufRestore(IMAGE_PATH, MilSystem, &MilImage);
-//     cv::Mat opencvImage = milToMat(MilImage);
-//     imshow("opencv", opencvImage);
-//     // MosGetch();
-//
-//     return 0;
-// }
-// int main() {
-//     MIL_ID MilApplication = M_NULL, MilSystem = M_NULL, MilDisplay = M_NULL;
-//     MIL_ID MilImage = M_NULL;
-//
-//     // 初始化 MIL 应用程序、系统和显示
-//     MappAllocDefault(M_DEFAULT, &MilApplication, &MilSystem, &MilDisplay, M_NULL, M_NULL);
-//     if (MilApplication == M_NULL || MilSystem == M_NULL || MilDisplay == M_NULL) {
-//         std::cerr << "MIL Initialization failed!" << std::endl;
-//         return -1;
-//     }
-//
-//     // 加载图像
-//     MbufRestore(IMAGE_PATH, MilSystem, &MilImage);
-//     if (MilImage == M_NULL) {
-//         std::cerr << "Failed to load MIL image!" << std::endl;
-//         MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL,M_NULL);
-//         return -1;
-//     }
-//
-//     // 转换并显示
-//     cv::Mat opencvImage = milToMat(MilImage);
-//     if (!opencvImage.empty()) {
-//         cv::imshow("opencv", opencvImage);
-//         cv::waitKey(0);
-//     }
-//     std:: string savepath="C:\\Users\\zjc\\Desktop\\suspect.png";
-//     cv::imwrite(savepath,opencvImage);
-//     // 释放资源
-//     MbufFree(MilImage);
-//     MappFreeDefault(MilApplication, MilSystem, MilDisplay, M_NULL,M_NULL);  // 使用 MappFreeDefault 代替 MappFree
-//
-//     return 0;
-// }
-
-// int main() {
-//     cv::Mat img = cv::imread("C:\\Users\\zjc\\Desktop\\suspect.png");
-//     if (img.empty()) {
-//         std::cout << "图像加载失败!" << std::endl;
-//         return -1;
-//     }
-//
-//     // 处理图像
-//     processImage(img);
-// }

 #include "CVDL/OnnxRunner.h"

@ -99,7 +33,7 @@ int main() {
    // Create and show the detection mask
    cv::Mat detectionMask = createDetectionMask(image, finalDetections, scale, padTop, padLeft);

-    cv::imshow("Detection Mask", detectionMask);
+    // cv::imshow("Detection Mask", detectionMask);

    // Save the result