update

BaseModules/Hd_AI_algo_hanHou_L/CMakeLists.txt

@@ -0,0 +1,71 @@
+# 获取获取当前目录名
+get_filename_component(CURRENT_FOLDER ${CMAKE_CURRENT_SOURCE_DIR} NAME)
+string(TIMESTAMP RUN_TIME)
+message( " model start : " ${CURRENT_FOLDER}:${RUN_TIME})
+
+set(DLL_NAMES "opencv" "halcon" "halconAlgo" "myTools" "handdleAI")
+foreach(child ${DLL_NAMES})         
+    LIST(APPEND ENV_INCLUDE ${${child}_include})
+    LIST(APPEND ENV_LIB ${${child}_lib})
+    LIST(APPEND ENV_TARGET ${${child}_target_link})         
+endforeach()
+message("   ENV_INCLUDE : " ${ENV_INCLUDE} )
+message("   ENV_LIB : " ${ENV_LIB} )
+message("   ENV_TARGET : " ${ENV_TARGET} )
+include_directories(
+
+    ${ENV_INCLUDE}
+    )
+
+link_directories (
+    ${ENV_LIB}
+
+    )
+
+
+set(CMAKE_INCLUDE_CURRENT_DIR ON)
+SET(CMAKE_CXX_STANDARD 11)
+SET(CMAKE_CXX_STANDARD_REQUIRED ON)
+
+set(CMAKE_AUTOMOC ON)
+SET(CMAKE_AUTOUIC ON)
+set(CMAKE_AUTORCC ON)
+
+FILE(GLOB HEAD_FILES "./*.h" )
+FILE(GLOB SRC_FILES "./*.cpp")
+FILE(GLOB UI_FILES "./*.ui")
+
+
+#find_package(Qt5 COMPONENTS Core REQUIRED)
+find_package(QT NAMES Qt6 Qt5 COMPONENTS Core REQUIRED)
+find_package(Qt${QT_VERSION_MAJOR} COMPONENTS Core REQUIRED)
+find_package(Qt${QT_VERSION_MAJOR} COMPONENTS network REQUIRED)
+add_library(${CURRENT_FOLDER} SHARED
+    ${HEAD_FILES}
+    ${SRC_FILES}
+    ${UI_FILES}
+    )
+
+
+
+set_target_properties(${CURRENT_FOLDER} PROPERTIES LINKER_LANGUAGE C
+    RUNTIME_OUTPUT_DIRECTORY  ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}
+    LIBRARY_OUTPUT_DIRECTORY  ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}
+    ARCHIVE_OUTPUT_DIRECTORY  ${CMAKE_ARCHIVE_OUTPUT_DIRECTORY}
+    )
+
+
+target_link_libraries(${CURRENT_FOLDER} PRIVATE
+    ${ENV_TARGET}
+    Qt${QT_VERSION_MAJOR}::Core
+    Qt${QT_VERSION_MAJOR}::Network
+    )
+
+
+# target_compile_definitions(${CURRENT_FOLDER} PRIVATE HD_AIDEMO_MODULE_LIBRARY)
+
+
+
+
+string(TIMESTAMP RUN_TIME)
+message( " model end : " ${CURRENT_FOLDER}:${RUN_TIME})

BaseModules/Hd_AI_algo_hanHou_L/Hd_AI_algo_hanHou.h

@@ -0,0 +1,116 @@
+#ifndef Hd_AI_algo_hanHou_H
+#define Hd_AI_algo_hanHou_H
+
+#include <assert.h>
+#include <atlstr.h>
+#include <chrono>
+#include <QtCore/qglobal.h>
+
+#include <QByteArray>
+#include <iostream>
+#include <QDebug>
+#include <qqueue.h>
+#include <opencv2/imgproc.hpp>
+#include <string.h>
+#include <fstream>
+#include <string>
+#include <ctime>
+#include  <halconcpp/HalconCpp.h>
+#include <opencv2/opencv.hpp>
+#include "imgproc/imgproc_c.h"
+#include "base.h"
+#include "handleAI.h"
+#pragma execution_character_set("utf-8")
+
+
+
+//保存图片的结构体
+struct saveImgStruct;
+//{
+//    cv::Mat out_Mat; 
+//    std::string saveKey; //关键字，用于LOG日志
+//    std::string savePath; //保存路径
+//};
+
+//初始化流程（一次）：Hd_AI_algo_hanHou，initParas
+//运行流程：writeData主线程把数据传过来，run，readData此线程把数据传主线程
+class  Hd_AI_algo_hanHou :public Base
+{
+    Q_OBJECT
+public:
+    Hd_AI_algo_hanHou();
+    virtual ~Hd_AI_algo_hanHou();
+    //从类中读数据到实例对象
+    bool  readData(std::vector<cv::Mat>&,QByteArray&);
+    //实例对象把数据写入到类
+    bool  writeData(std::vector<cv::Mat>&, QByteArray&);
+    bool  initParas(QByteArray&);
+    //运行（Logic_taskthread.cpp）
+    bool run();
+    //线程状态
+    bool  checkStatus();// { return true; };
+
+    bool encodeResultValue(QVector<std::string> append_value,QByteArray &resultByte);
+    bool decodeAiValue(QByteArray byte,QVector<QByteArray> &vec_ret);
+    //---------检测流程，根据实际项目修改---------
+    bool AIdetect(cv::Mat img2D, QString saveKey, QString Dir2D, QString SN, QString DataTime);
+    handdleAI::pSegmentation* seg_hanHouSiLie;
+    handdleAI::pSegmentation* seg_hanHouFanZhe;
+    
+private:
+    int allNum = 0;
+    int StationNo=0;
+    int img2D = 2;
+
+    bool moduleStatus = true;
+
+    //输入图片队列
+    QQueue<cv::Mat> HikMat;
+    //输入关键字队列
+    QString  saveKey="saveKey";
+    //结果路径文件夹队列
+    QString  Dir2D="Dir2D";
+    //产品SN队列
+    QString  SN="SN";
+    //产品时间戳队列
+    QString  DateTime1="DateTime1";
+
+    int paramNum;
+
+    //是否使用线程检测方式
+    bool ifThreadRunDetect = false;
+    //检测结果图
+    std::vector<cv::Mat> resMat;
+    //检测结果
+    bool resIfNg = false;
+
+    QQueue<QByteArray> resByte;
+
+    //检测线程
+    void detectThread();
+    //存图线程
+    void saveImgThread();
+    
+    //保存图片队列
+    QQueue<saveImgStruct> saveStruct;
+
+    //判断文件夹是否存在，不存在则创建
+    void isDirExist(QString fullDirName);
+
+    //存图加入队列
+    void addImgToSaveStruct(cv::Mat img2D, QString saveKey, QString savePath);
+};
+
+extern "C"
+{
+   Q_DECL_EXPORT Hd_AI_algo_hanHou * create();
+    Q_DECL_EXPORT void destory(Hd_AI_algo_hanHou * ptr);
+}
+//保存图片的结构体
+struct saveImgStruct
+{
+    cv::Mat out_Mat;
+    std::string saveKey; //关键字，用于LOG日志
+    std::string savePath; //保存路径
+};
+#endif // Hd_AI_927_2D_module_H

BaseModules/Hd_AI_algo_hanHou_L/base.h

@@ -0,0 +1,69 @@
+#ifndef __BASECLASS_H__
+#define __BASECLASS_H__
+
+#include <iostream>
+#include <QObject>
+#include <QByteArray>
+#include <opencv2/opencv.hpp>
+#include <opencv2/core.hpp>
+#include <opencv2/imgproc.hpp>
+#include<QJsonDocument>
+#include<QJsonObject>
+#include<QJsonArray>
+
+class Base :public QObject
+{
+    Q_OBJECT
+public:
+    bool        init_flag;           //是否初始化,false,true
+    bool        status = true;              //相机状态（判断相机是否断开连接）
+    std::string paras;               //传输数据
+    std::vector<cv::Mat>     m_mat;  //传输图片
+    std::string moduleName;          //模块名称
+public:
+    Base(){}
+    virtual ~Base(){}
+    virtual bool  readData(std::vector<cv::Mat>&,QByteArray&){return true;}
+    virtual bool  writeData(std::vector<cv::Mat>&,QByteArray&){return true;}
+    virtual bool  initParas(QByteArray&){return true;}
+    virtual bool  run() {return true;}
+    virtual bool  checkStatus() { return true; }
+
+//signals:
+    //QByteArrayList，根据实际项目进行解析；因不确定每个参数的长度，固用队列的方式。每个QByteArray表示一个值，使用时先转换为QString
+    //参数,例：返回结果图;相机关键字（SN或userID）+保存路径+缺陷信息列表(缺陷名称，缺陷位置int（x,y,w,h）,画框颜色Scalar（a，b，c），缺陷面积double)
+    //void  sendResultData(cv::Mat resMat, QJsonObject resQbj);
+};
+
+/*
+//QJsonObject 转QByteArray
+{
+    QJsonDocument document;
+    QJsonObject obj;
+    obj.insert(password, "pwd");
+    obj.insert(userName, "usr");
+    document.setObject(obj);
+    QByteArray abyte = document.toJson(QJsonDocument::Compact);
+}
+
+//QByteArray转QJsonObject
+{
+    QByteArray ba = reply->readAll();
+    QJsonDocument doc = QJsonDocument::fromJson(ba);
+    QJsonObject obj = doc.object();
+}
+*/
+/*
+//从类中读数据到实例对象
+virtual bool  readData(std::vector<cv::Mat>&,QByteArray&){return true;}
+
+
+
+
+
+
+
+
+*/
+
+#endif

BaseModules/Hd_AI_algo_hanHou_T/Hd_AI_algo_hanHou.cpp

@@ -543,7 +543,10 @@ bool Hd_AI_algo_hanHou::readData(std::vector<cv::Mat>&vec_mat,QByteArray &data)
     //if (allNum++ % 2 == 0)
     //    data = "2*3*2";// resByte.dequeue();
     //else
-    data = "1*&" + fanzheResultText + "&" + silieResultText
+    data = "1*" + silieResultText + +"*" + fanzheResultText
+        + "*" + jiErWidth + "*" + jiErHeight
+        + "*" + hanYin1 + "*" + hanYin2
+        + "&" + fanzheResultText + "&" + silieResultText
         + "+" + fanzheResultText + "+" + silieResultText
         + "+" + jiErWidth + "+" + jiErHeight
         + "+" + hanYin1 + "+" + hanYin2
@@ -746,8 +749,8 @@ bool Hd_AI_algo_hanHou::initParas(QByteArray& byte)
 
 
     //StationNo = vec_ret.at(0).toInt();
-    seg_hanHouSiLie = handdleAI::CreateSegObjS("./model/seg-yuHanhanHouSiLie.BHD");
-    seg_hanHouFanZhe = handdleAI::CreateSegObjS("./model/seg-yuHanhanFanZhe.BHD");
+    seg_hanHouSiLie = handdleAI::CreateSegObjS("./model/seg-yuHanhanHouSiLie.BHD", 32, 0);
+    seg_hanHouFanZhe = handdleAI::CreateSegObjS("./model/seg-yuHanhanFanZhe.BHD",32 , 0);
     //InitThreads(StationNo, img2D);
     //InitModels(StationNo, img2D);
 
@@ -860,13 +863,13 @@ void halconAlgoProcess(cv::Mat& img,cv::Mat &Paint)//算法先画
         hanYin2 = QByteArray::number(leftEdge);
 
         putTextHusky(Paint, utf8_to_gbk("极耳高" + std::to_string(height)).c_str(),
-            cv::Point(0, 0), cv::Scalar(0, 255, 0), 300);
+            cv::Point(0, 0), cv::Scalar(0, 255, 0), 200);
         putTextHusky(Paint, utf8_to_gbk("极耳宽" + std::to_string(weight)).c_str(),
-            cv::Point(0, 250), cv::Scalar(0, 255, 0), 300);
+            cv::Point(0, 200), cv::Scalar(0, 255, 0), 200);
         putTextHusky(Paint, utf8_to_gbk("上间距" + std::to_string(upEdge)).c_str(),
-            cv::Point(0, 500), cv::Scalar(0, 255, 0), 300);
-        putTextHusky(Paint, utf8_to_gbk("下间距" + std::to_string(leftEdge)).c_str(),
-            cv::Point(0, 750), cv::Scalar(0, 255, 0), 300);
+            cv::Point(0, 400), cv::Scalar(0, 255, 0), 200);
+        putTextHusky(Paint, utf8_to_gbk("左间距" + std::to_string(leftEdge)).c_str(),
+            cv::Point(0, 600), cv::Scalar(0, 255, 0), 200);
     }
     else
         putTextHusky(Paint, utf8_to_gbk("算法异常1").c_str(), cv::Point(0, 0), cv::Scalar(0, 255, 0), 300);
@@ -886,7 +889,7 @@ void siLieProcess(cv::Mat& segRes, cv::Mat& Paint,bool& result)
         //int clsRes = clsPtr->Evaluate(clsImg);
         cv::Scalar color = cv::Scalar(0, 0, 255, 30);
         cv::rectangle(Paint, originRect, color, 4);
-        putTextHusky(Paint, utf8_to_gbk("撕裂").c_str(), cv::Point(rect.x - rect.width / 2, rect.y - rect.height / 2), cv::Scalar(0, 255, 0), 100);
+        putTextHusky(Paint, utf8_to_gbk("撕裂").c_str(), cv::Point(rect.x - rect.width / 2, rect.y - rect.height / 2 - 50), cv::Scalar(0, 255, 0), 50);
         result = false;
     }
 }
@@ -905,7 +908,7 @@ void fanZheProcess(cv::Mat& segRes, cv::Mat& Paint, bool& result)
         //int clsRes = clsPtr->Evaluate(clsImg);
         cv::Scalar color = cv::Scalar(0, 0, 255, 30);
         cv::rectangle(Paint, originRect, color, 4);
-        putTextHusky(Paint, utf8_to_gbk("翻折").c_str(), cv::Point(rect.x- rect.width/2, rect.y-rect.height/2), cv::Scalar(0, 255, 0), 100);
+        putTextHusky(Paint, utf8_to_gbk("翻折").c_str(), cv::Point(rect.x- rect.width/2, rect.y-rect.height/2-50), cv::Scalar(0, 255, 0), 50);
         result = false;
     }
 }
@@ -941,19 +944,20 @@ bool Hd_AI_algo_hanHou::AIdetect(cv::Mat img2D, QString mysaveKey, QString myDir
         //    csvName.close();
         //}
         //sourceImg = cv::imread("D:\\mySN15-46-33-86.bmp",-1);
-        sourceImg = cv::imread("D:/1/Image_20241017204025590.bmp", -1);
+        //sourceImg = cv::imread("D:/1/Image_20241017204025590.bmp", -1);
         cv::Mat Paint;
-        sourceImg.copyTo(Paint);
-        if(Paint.channels() == 1)
+        cv::Mat segProcess;
+        cv::resize(sourceImg, segProcess, cv::Size(), 0.5, 0.5);
+        segProcess.copyTo(Paint);
+        if (Paint.channels() == 1)
             cvtColor(Paint, Paint, COLOR_GRAY2BGR);
         QQueue<defectInfo> defectInfoList;
 
-        
+
         detect_mutex->lock();
-        
+
         auto futrue = std::async(std::launch::async, halconAlgoProcess, sourceImg, Paint);//异步执行
-        cv::Mat segProcess;
-        cv::resize(sourceImg, segProcess, cv::Size(), 0.5, 0.5);
+
         //撕裂检测
         cv::Mat siLieSegRes = ~seg_hanHouSiLie->Evaluate(segProcess);//撕裂
         cv::Mat fanZheSegRes = ~seg_hanHouFanZhe->Evaluate(segProcess);//翻折
@@ -964,14 +968,25 @@ bool Hd_AI_algo_hanHou::AIdetect(cv::Mat img2D, QString mysaveKey, QString myDir
 
 
         if (silieOk == true)//OK
-            putTextHusky(Paint, utf8_to_gbk("撕裂OK").c_str(), cv::Point(4800, 50), cv::Scalar(0, 255, 0), 500);
+        {
+            putTextHusky(Paint, utf8_to_gbk("撕裂OK").c_str(), cv::Point(1800, 50), cv::Scalar(0, 255, 0), 250);
+            silieResultText = "1";
+        }
         else
-            putTextHusky(Paint, utf8_to_gbk("撕裂NG").c_str(), cv::Point(4800, 50), cv::Scalar(0, 0, 255), 500);
-
+        {
+            putTextHusky(Paint, utf8_to_gbk("撕裂NG").c_str(), cv::Point(1800, 50), cv::Scalar(0, 0, 255), 250);
+            silieResultText = "2";
+        }
         if (fanZheOk == true)//OK
-            putTextHusky(Paint, utf8_to_gbk("翻折OK").c_str(), cv::Point(4800, 300), cv::Scalar(0, 255, 0), 500);
+        {
+            putTextHusky(Paint, utf8_to_gbk("翻折OK").c_str(), cv::Point(1800, 300), cv::Scalar(0, 255, 0), 250);
+            fanzheResultText = "1";
+        }
         else
-            putTextHusky(Paint, utf8_to_gbk("翻折NG").c_str(), cv::Point(4800, 300), cv::Scalar(0, 0, 255), 500);
+        {
+            putTextHusky(Paint, utf8_to_gbk("翻折NG").c_str(), cv::Point(1800, 300), cv::Scalar(0, 0, 255), 250);
+            fanzheResultText = "2";
+        }
 
         resMat.push_back(Paint);
         QJsonArray detaillists;