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@@ -0,0 +1,71 @@
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# 获取获取当前目录名
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get_filename_component(CURRENT_FOLDER ${CMAKE_CURRENT_SOURCE_DIR} NAME)
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string(TIMESTAMP RUN_TIME)
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message( " model start : " ${CURRENT_FOLDER}:${RUN_TIME})
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set(DLL_NAMES "opencv" "halcon" "halconAlgo" "myTools" "handdleAI")
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foreach(child ${DLL_NAMES})
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LIST(APPEND ENV_INCLUDE ${${child}_include})
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LIST(APPEND ENV_LIB ${${child}_lib})
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LIST(APPEND ENV_TARGET ${${child}_target_link})
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endforeach()
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message(" ENV_INCLUDE : " ${ENV_INCLUDE} )
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message(" ENV_LIB : " ${ENV_LIB} )
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message(" ENV_TARGET : " ${ENV_TARGET} )
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include_directories(
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${ENV_INCLUDE}
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)
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link_directories (
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${ENV_LIB}
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)
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set(CMAKE_INCLUDE_CURRENT_DIR ON)
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SET(CMAKE_CXX_STANDARD 11)
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SET(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CMAKE_AUTOMOC ON)
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SET(CMAKE_AUTOUIC ON)
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set(CMAKE_AUTORCC ON)
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FILE(GLOB HEAD_FILES "./*.h" )
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FILE(GLOB SRC_FILES "./*.cpp")
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FILE(GLOB UI_FILES "./*.ui")
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#find_package(Qt5 COMPONENTS Core REQUIRED)
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find_package(QT NAMES Qt6 Qt5 COMPONENTS Core REQUIRED)
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find_package(Qt${QT_VERSION_MAJOR} COMPONENTS Core REQUIRED)
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find_package(Qt${QT_VERSION_MAJOR} COMPONENTS network REQUIRED)
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add_library(${CURRENT_FOLDER} SHARED
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${HEAD_FILES}
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${SRC_FILES}
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${UI_FILES}
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)
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set_target_properties(${CURRENT_FOLDER} PROPERTIES LINKER_LANGUAGE C
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RUNTIME_OUTPUT_DIRECTORY ${CMAKE_RUNTIME_OUTPUT_DIRECTORY}
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LIBRARY_OUTPUT_DIRECTORY ${CMAKE_LIBRARY_OUTPUT_DIRECTORY}
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ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_ARCHIVE_OUTPUT_DIRECTORY}
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)
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target_link_libraries(${CURRENT_FOLDER} PRIVATE
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${ENV_TARGET}
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Qt${QT_VERSION_MAJOR}::Core
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Qt${QT_VERSION_MAJOR}::Network
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)
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# target_compile_definitions(${CURRENT_FOLDER} PRIVATE HD_AIDEMO_MODULE_LIBRARY)
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string(TIMESTAMP RUN_TIME)
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message( " model end : " ${CURRENT_FOLDER}:${RUN_TIME})
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File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,166 @@
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#ifndef Hd_AI_algo_fanMianTieJiao_H
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#define Hd_AI_algo_fanMianTieJiao_H
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#include <assert.h>
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#include <atlstr.h>
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#include <chrono>
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#include <QtCore/qglobal.h>
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#include <QByteArray>
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#include <iostream>
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#include <QDebug>
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#include <qqueue.h>
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#include <opencv2/imgproc.hpp>
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#include <string.h>
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#include <fstream>
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#include <string>
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#include <ctime>
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#include <halconcpp/HalconCpp.h>
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#include <opencv2/opencv.hpp>
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#include "imgproc/imgproc_c.h"
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#include "base.h"
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#include "handleAI.h"
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#pragma execution_character_set("utf-8")
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using namespace handdleAI;
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//保存图片的结构体
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struct saveImgStruct;
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//{
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// cv::Mat out_Mat;
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// std::string saveKey; //关键字，用于LOG日志
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// std::string savePath; //保存路径
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//};
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//初始化流程（一次）：Hd_AI_algo_fanMianTieJiao，initParas
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//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
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class Hd_AI_algo_fanMianTieJiao :public Base
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{
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Q_OBJECT
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public:
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Hd_AI_algo_fanMianTieJiao();
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virtual ~Hd_AI_algo_fanMianTieJiao();
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//从类中读数据到实例对象
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bool readData(std::vector<cv::Mat>&,QByteArray&);
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//实例对象把数据写入到类
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bool writeData(std::vector<cv::Mat>&, QByteArray&);
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bool initParas(QByteArray&);
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//运行（Logic_taskthread.cpp）
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bool run();
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//线程状态
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bool checkStatus();// { return true; };
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bool encodeResultValue(QVector<std::string> append_value,QByteArray &resultByte);
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bool decodeAiValue(QByteArray byte,QVector<QByteArray> &vec_ret);
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//---------检测流程，根据实际项目修改---------
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bool AIdetect(std::vector<cv::Mat>& img2D, QString saveKey, QString Dir2D, QString SN, QString DataTime);
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private:
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pSegmentation* seg_yicizhuyeCanye;
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pClassification* cls_yicizhuyeCanye;
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int allNum = 0;
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int StationNo=0;
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int img2D = 2;
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bool moduleStatus = true;
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//输入图片队列
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QQueue<cv::Mat> HikMat;
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//输入关键字队列
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QString saveKey="saveKey";
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//结果路径文件夹队列
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QString Dir2D="Dir2D";
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//产品SN队列
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QString SN="SN";
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//产品时间戳队列
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QString DateTime1="DateTime1";
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int paramNum;
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//是否使用线程检测方式
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bool ifThreadRunDetect = false;
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//检测结果图
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std::vector<cv::Mat> resMat;
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//检测结果
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bool resIfNg = false;
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QQueue<QByteArray> resByte;
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//检测线程
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void detectThread();
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//存图线程
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void saveImgThread();
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//保存图片队列
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QQueue<saveImgStruct> saveStruct;
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//判断文件夹是否存在，不存在则创建
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void isDirExist(QString fullDirName);
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//存图加入队列
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void addImgToSaveStruct(cv::Mat img2D, QString saveKey, QString savePath);
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};
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extern "C"
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{
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Q_DECL_EXPORT Hd_AI_algo_fanMianTieJiao * create();
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Q_DECL_EXPORT void destory(Hd_AI_algo_fanMianTieJiao * ptr);
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}
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//保存图片的结构体
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struct saveImgStruct
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{
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cv::Mat out_Mat;
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std::string saveKey; //关键字，用于LOG日志
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std::string savePath; //保存路径
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};
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static cv::Mat LocalCutImg_DET(pDetection* pDet, cv::Mat src, float zoom, int checkNameId, cv::Rect& cutRoi)
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{
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cv::Mat dst;
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cv::resize(src, dst, cv::Size(src.cols / zoom, src.rows / zoom));
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vector<Bbox> resultBox = pDet->Evaluate(dst); //结果为中心点+宽高
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cv::Mat contourImg;
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std::vector<std::vector<cv::Point>> contours;
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//cv::threshold(dstImg, contourImg, pSeg->m_classes, 255, cv::THRESH_BINARY_INV);
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//cv::findContours(contourImg, contours, cv::noArray(), cv::RETR_EXTERNAL, cv::CHAIN_APPROX_NONE);
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cv::Mat roiImg;
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if (resultBox.size() <= 0)
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{
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cv::Mat rstMat = cv::Mat(100, 100, CV_8UC1, cv::Scalar(0, 0, 0));
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cutRoi = cv::Rect(0, 0, 100, 100);
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return rstMat;
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}
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double maxArea = 0;
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int index = -1;
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for (int j = 0; j < resultBox.size(); j++)
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{
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double area = resultBox[j].w * resultBox[j].h;
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if (area >= maxArea)
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{
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maxArea = area;
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index = j;
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}
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}
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//cv::Rect rect = cv::boundingRect(contours[index]);
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int addpixel = 15;
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cutRoi.x = ((resultBox[index].x - resultBox[index].w / 2) * zoom);
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cutRoi.y = ((resultBox[index].y - resultBox[index].h / 2) * zoom);
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cutRoi.width = (resultBox[index].w * zoom);
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cutRoi.height = (resultBox[index].h * zoom);
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//cv::rectangle(src, cutRoi, cv::Scalar(0, 0, 255), 2, 8);
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//cutRoi.x = rect.x * zoom;
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//cutRoi.y = rect.y * zoom;
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//cutRoi.width = rect.width * zoom;
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//cutRoi.height = rect.height * zoom;
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src(cutRoi).copyTo(roiImg);
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return roiImg;
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}
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#endif // Hd_AI_927_2D_module_H
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@@ -0,0 +1,69 @@
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#ifndef __BASECLASS_H__
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#define __BASECLASS_H__
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#include <iostream>
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#include <QObject>
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#include <QByteArray>
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#include <opencv2/opencv.hpp>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include<QJsonDocument>
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#include<QJsonObject>
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#include<QJsonArray>
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class Base :public QObject
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{
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Q_OBJECT
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public:
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bool init_flag; //是否初始化,false,true
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bool status = true; //相机状态（判断相机是否断开连接）
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std::string paras; //传输数据
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std::vector<cv::Mat> m_mat; //传输图片
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std::string moduleName; //模块名称
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public:
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Base(){}
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virtual ~Base(){}
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virtual bool readData(std::vector<cv::Mat>&,QByteArray&){return true;}
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virtual bool writeData(std::vector<cv::Mat>&,QByteArray&){return true;}
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virtual bool initParas(QByteArray&){return true;}
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virtual bool run() {return true;}
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virtual bool checkStatus() { return true; }
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//signals:
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//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
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//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)
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//void sendResultData(cv::Mat resMat, QJsonObject resQbj);
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};
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/*
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//QJsonObject 转QByteArray
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{
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QJsonDocument document;
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QJsonObject obj;
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obj.insert(password, "pwd");
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obj.insert(userName, "usr");
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document.setObject(obj);
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QByteArray abyte = document.toJson(QJsonDocument::Compact);
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}
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//QByteArray转QJsonObject
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{
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QByteArray ba = reply->readAll();
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QJsonDocument doc = QJsonDocument::fromJson(ba);
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QJsonObject obj = doc.object();
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}
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*/
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/*
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//从类中读数据到实例对象
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virtual bool readData(std::vector<cv::Mat>&,QByteArray&){return true;}
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*/
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#endif
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Reference in New Issue
Block a user