统一template——matching的接口，添加mask的测试函数，在src中新建CVDL库

opencv_onnx.cpp

@@ -112,7 +112,7 @@ int main() {
 
     timer1.printElapsedTime("Time to preprocessing");
     timer1.restart();
-    for(int j = 0; j <30; j++) {
+    for(int j = 0; j <1; j++) {
         // 推理模型
         cv::Mat output = net.forward();
 
@@ -153,9 +153,6 @@ int main() {
 
             }
         }
-
-
-
         // 非极大值抑制
         std::vector<int> indices;
         std::vector<cv::Rect> boxes;
@@ -192,6 +189,41 @@ int main() {
         drawDetections(image, finalDetections);
         timer1.printElapsedTime("Time to run inference");
     }
+    int depth = inputImage.depth();    // 图像数据类型
+    int channels = inputImage.channels();  // 通道数
+
+    // 判断图像深度和通道数，打印类型
+    std::string depthStr;
+    switch (depth) {
+        case CV_8U:
+            depthStr = "8-bit unsigned integer";
+        break;
+        case CV_8S:
+            depthStr = "8-bit signed integer";
+        break;
+        case CV_16U:
+            depthStr = "16-bit unsigned integer";
+        break;
+        case CV_16S:
+            depthStr = "16-bit signed integer";
+        break;
+        case CV_32S:
+            depthStr = "32-bit signed integer";
+        break;
+        case CV_32F:
+            depthStr = "32-bit floating point";
+        break;
+        case CV_64F:
+            depthStr = "64-bit floating point";
+        break;
+        default:
+            depthStr = "Unknown depth";
+        break;
+    }
+
+    std::cout << "Image Depth: " << depthStr << std::endl;
+    std::cout << "Number of Channels: " << channels << std::endl;
+
     cv::imshow("Detections", inputImage);
     cv::waitKey(0);
 

src/CMakeLists.txt

@@ -3,6 +3,7 @@ add_library(Matrox
         Matrox/color_range.cpp
         Matrox/utils.cpp
         Matrox/template_matching.cpp
+        Matrox/mask.cpp
 )
 
 # 头文件路径

src/CVDL/OnnxRunner.cpp

@@ -0,0 +1,5 @@
+//
+// Created by zjc on 24-11-26.
+//
+
+#include "OnnxRunner.h"

src/CVDL/OnnxRunner.h

@@ -0,0 +1,16 @@
+//
+// Created by zjc on 24-11-26.
+//
+
+#ifndef ONNXRUNNER_H
+#define ONNXRUNNER_H
+
+
+
+class OnnxRunner {
+
+};
+
+
+
+#endif //ONNXRUNNER_H

src/Matrox/mask.cpp

@@ -1,7 +1,5 @@
-#include <opencv2/opencv.hpp>
-#include <vector>
-#include <iostream>
 
+#include "mask.h"
 // 读取二值化的单通道一位图片并生成掩膜
 std::vector<std::vector<bool>> generateMaskFromImage(const std::string& imagePath, int widthBlocks, int heightBlocks, int threshold = 10) {
     // 读取图像
@@ -52,25 +50,4 @@ std::vector<std::vector<bool>> generateMaskFromImage(const std::string& imagePat
     return mask;
 }
 
-int main() {
-    // 指定图像路径
-    std::string imagePath = "C:\\Users\\zjc\\Desktop\\diguandai.png";
 
-    // 设置分块数量和白色像素点阈值
-    int widthBlocks = 24;
-    int heightBlocks = 24;
-    int threshold = 20;
-
-    // 生成掩膜
-    std::vector<std::vector<bool>> mask = generateMaskFromImage(imagePath, widthBlocks, heightBlocks, threshold);
-
-    // 打印掩膜结果
-    for (int i = 0; i < heightBlocks; ++i) {
-        for (int j = 0; j < widthBlocks; ++j) {
-            std::cout << (mask[i][j] ? "1 " : "0 ");
-        }
-        std::cout << std::endl;
-    }
-
-    return 0;
-}

src/Matrox/mask.h

@@ -0,0 +1,16 @@
+//
+// Created by zjc on 24-11-26.
+//
+
+
+#ifndef MASK_H
+#define MASK_H
+
+#include <opencv2/opencv.hpp>
+#include <vector>
+#include <iostream>
+
+std::vector<std::vector<bool>> generateMaskFromImage(const std::string& imagePath, int widthBlocks, int heightBlocks, int threshold);
+
+
+#endif //MASK_H

src/Matrox/template_matching.cpp

@@ -237,7 +237,7 @@ void TemplateMatcher::loadConfig(const std::string& filename,
     file.close();
 }
 
-void TemplateMatcher::LoadTemplate(TemplateMatcher& matcher, std::map<std::string, int>& params)
+void TemplateMatcher::LoadTemplate(std::map<std::string, int>& params)
 {
     std::vector<std::string> template_paths;
     std::vector<MIL_INT> offsetX, offsetY, sizeX, sizeY;
@@ -245,26 +245,39 @@ void TemplateMatcher::LoadTemplate(TemplateMatcher& matcher, std::map<std::strin
 
     // 调用 loadConfig 并加载配置
     loadConfig("C:\\Users\\zjc\\Desktop\\config\\template_config.txt",
-               template_paths, offsetX, offsetY, sizeX, sizeY, drawColor);
+        template_paths, offsetX, offsetY, sizeX, sizeY, drawColor);
 
     // 调用 matcher 的 loadTemplates 方法
-    matcher.loadTemplates(template_paths, offsetX, offsetY, sizeX, sizeY, drawColor);
+    this->loadTemplates(template_paths, offsetX, offsetY, sizeX, sizeY, drawColor);
 }
 
 
-void TemplateMatcher::FindTemplates( const MIL_ID& inputImage, MIL_ID& outputImage,TemplateMatcher& matcher)
+void TemplateMatcher::FindTemplates( const MIL_ID& inputImage, MIL_ID& outputImage,const std::map<std::string, int> &params)
 {
     // Perform template matching
-    matcher.findModels(inputImage,outputImage);
+    this -> findModels(inputImage,outputImage);
 
     // Notify user that matching is complete
     cout << "Template matching completed.\n";
 }
 
-//TODO: 1加入加载多个模板的功能   已 + 加入配置文件 已
 
 
-//TODO: 5制作标准结构的函数，例如：matcher.findModels(MIL_ID inputImage, MIL_ID output_image, map);
-////未实现，因为加载和寻找分开后，要对加载和寻找函数传入类成员，无法统一，其余可用到的参数统一，加一个类成员即可。
-//TODO: 6完善相应部分的手册 已
+
+// TODO: Opencv ONNX runner,
+//       1. 构建相应的模型加载和模型运行函数
+//       2. 在src里头添加另一个cvdl库，专用于视觉深度学习
+//       3. 添加一个类OnnxRunner
+
+// TODO: 完善config文件，确保能够读取mask转换的相关参数
+
+// TODO: Opencv和matrox图像的转换函数，添加到Matrox/utils.cpp
+
+// TODO：构建统一的图像检测器类，可以一键加载，一键开启多进程快速预测
+
+// TODO：计算统一预测框架的预测时间
+
+// TODO: 完善模板和参数，添加陈棉模块，陈棉模块可通过配置进行启用和关闭。
+
+//TODO: 完善相应部分的手册 已
 

src/Matrox/template_matching.h

@@ -47,13 +47,13 @@ public:
                        const std::vector<MIL_DOUBLE>& drawColor);
 
     // Search for models in the input image
-void findModels(const MIL_ID& inputImage,MIL_ID& outputImage);
+    void findModels(const MIL_ID& inputImage,MIL_ID& outputImage);
 
-    void LoadTemplate(TemplateMatcher &matcher, std::map<std::string, int> &params);
+    void LoadTemplate(std::map<std::string, int> &params);
 
-    void FindTemplates(const MIL_ID &inputImage, MIL_ID &outputImage, TemplateMatcher &matcher);
+    void FindTemplates(const MIL_ID &inputImage, MIL_ID &outputImage,const std::map<std::string, int> &params);
 
-void loadConfig(const std::string& filename,
+    void loadConfig(const std::string& filename,
                 std::vector<std::string>& template_paths,
                 std::vector<MIL_INT>& offsetX,
                 std::vector<MIL_INT>& offsetY,

src/Matrox/utils.cpp

@@ -8,6 +8,7 @@
 #include <iostream>
 #include <vector>
 #include <cmath>
+#include <opencv2/core/mat.hpp>
 
 using namespace std;
 
@@ -120,3 +121,4 @@ void read_params_from_file(const std::string& filename, std::map<std::string, in
 }
 
 // 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
+// Mat Mil2cvImage(MIL_ID &input_image,Mat) {}

tests/CMakeLists.txt

@@ -13,4 +13,12 @@ add_executable(test_template_matching
 )
 
 # 链接 Matrox 模块和依赖库
-target_link_libraries(test_template_matching Matrox ${OpenCV_LIBS} ${MIL_LIBS})
+target_link_libraries(test_template_matching Matrox ${OpenCV_LIBS} ${MIL_LIBS})
+
+
+add_executable(test_mask
+        ${CMAKE_CURRENT_SOURCE_DIR}/test_mask.cpp
+)
+
+# 链接 Matrox 模块和依赖库
+target_link_libraries(test_mask Matrox ${OpenCV_LIBS} ${MIL_LIBS})

tests/test_mask.cpp

@@ -0,0 +1,30 @@
+//
+// Created by zjc on 24-11-26.
+//
+#include "vector"
+#include"iostream"
+#include"string"
+#include"Matrox/mask.h"
+int main() {
+    // 指定图像路径
+    std::string imagePath = "C:\\Users\\zjc\\Desktop\\diguandai.png";
+
+    // 设置分块数量和白色像素点阈值
+    int widthBlocks = 24;
+    int heightBlocks = 24;
+    int threshold = 20;
+
+    // 生成掩膜
+    std::vector<std::vector<bool>> mask = generateMaskFromImage(imagePath, widthBlocks, heightBlocks, threshold);
+
+    // 打印掩膜结果
+    for (int i = 0; i < heightBlocks; ++i) {
+        for (int j = 0; j < widthBlocks; ++j)
+        {
+            std::cout << (mask[i][j] ? "1 " : "0 ");
+        }
+        std::cout << std::endl;
+    }
+
+    return 0;
+}

tests/test_template_matching.cpp

@@ -49,9 +49,9 @@ int main() {
            M_IMAGE + M_PROC, &detection_resize);
         MimResize(detection_result,detection_resize,0.5,0.5,M_DEFAULT);
 
-        matcher.LoadTemplate(matcher,params);
-        matcher.FindTemplates(detection_resize,output_Image,matcher);
-        //最后的释放问题应该出在寻找模板里面
+        matcher.LoadTemplate(params);
+        matcher.FindTemplates(detection_resize,output_Image,params);
+
     });
     MbufSave(SAVE_PATH, detection_result);
     // Display result