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/*
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//图片基本处理
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*/
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#ifndef ImageResultJudge_H_
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#define ImageResultJudge_H_
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#include "CheckConfigDefine.h"
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#include <mutex>
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#include <vector>
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#include <thread>
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#include <string>
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#include <stdio.h>
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#include <condition_variable>
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#include "Define_Base.h"
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#include "ImgCheckBase.h"
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#include "ImageDetBase.h"
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#include "ImgCheckConfig.h"
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#include "CheckErrorCodeDefine.hpp"
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#include "ConfigBase.h"
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#include "CheckConfigDefine.h"
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#include "ImageDetConfig.h"
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#include "Define_Product.hpp"
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#include "CameraResult.h"
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#include "DetLog.h"
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#include "QX_Merge_Analysis.h"
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class ImageResultJudge
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{
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private:
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enum DrawType
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{
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Draw_rect,
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Draw_circle,
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Draw_str,
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};
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struct txtDrawBackgroundk
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{
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std::vector<cv::Rect> txtDrawRoi;
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cv::Rect findNonOverlappingPos(
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const cv::Rect &newRect,
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int step = 5,
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int maxRadius = 800)
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{
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// 如果本身就不重叠，直接返回
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bool overlap = false;
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for (const auto &r : txtDrawRoi)
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{
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if ((newRect & r).area() > 0)
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{
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overlap = true;
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break;
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}
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}
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if (!overlap)
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return newRect;
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// 螺旋搜索
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for (int radius = step; radius <= maxRadius; radius += step)
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{
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for (int dx = -radius; dx <= radius; dx += step)
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{
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for (int dy = -radius; dy <= radius; dy += step)
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{
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cv::Rect candidate = newRect + cv::Point(dx, dy);
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bool conflict = false;
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for (const auto &r : txtDrawRoi)
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{
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if ((candidate & r).area() > 0)
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{
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conflict = true;
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break;
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}
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}
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if (!conflict)
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{
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return candidate; // 找到合适位置
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}
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}
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}
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}
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// printf("find fail ============= \n");
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// 实在找不到，就返回原始位置
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return newRect;
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}
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};
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struct DrawInfo
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{
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cv::Mat drawImg;
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DrawType type = Draw_rect;
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std::vector<std::string> strlist;
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cv::Point txtP = cv::Point(0, 0);
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cv::Rect roi = cv::Rect(0, 0, 0, 0);
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cv::Scalar color = cv::Scalar(255, 0, 255);
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cv::Point cp = cv::Point(0, 0);
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int dr = 0;
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float txtsize = 0.8;
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std::shared_ptr<txtDrawBackgroundk> txtbackgroundk;
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};
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public:
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ImageResultJudge(/* args */);
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~ImageResultJudge();
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int SetAnalysisyConfig(AnalysisyConfigST *pAnalysisyConfig);
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int ResultJudge(std::shared_ptr<ImageAllResult> pImageResult);
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int UpdateMergedet(std::shared_ptr<CameraResult> pCheck_Result);
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int MergeResult(std::shared_ptr<ImageAllResult> pImageResult, QX_Analysis_Result_List *ptemre);
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int UpdateConfig(std::string strcameraName);
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int DrawResult(std::shared_ptr<ImageAllResult> pImageResult);
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// 盲失联合判断：主通道(ms_main_channel)检出的盲失(Other)若在过滤通道(ms_filter_channels)同位置存在缺陷
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// (不限制缺陷类型)，则不算盲失(撤销NG)。同位置判断参考暗点联合分析：双方按 ms_expand 扩张后计算 IOU, 大于 ms_iou 认为同位置
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int FilterMsBlindNG(std::shared_ptr<CameraResult> pCheck_Result);
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// cell黑白点联合判断：主通道(cellbw_main_channel)检出的cell黑白点在过滤通道(cellbw_filter_channels)
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// 同位置存在缺陷(不限制缺陷类型)时不算cell黑白点(撤销NG)
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// 同位置判断参考暗点联合分析：双方按 cellbw_expand 扩张后计算 IOU, 大于 cellbw_iou 认为同位置
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int FilterCellBwNG(std::shared_ptr<CameraResult> pCheck_Result);
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private:
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// 获取 缺陷在参数列表的位置
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int GetParamidx();
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int UpdateImgageScale();
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int SetInDetConfig(std::string strcameraName);
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int SetMergeConfig(std::string strcameraName);
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// 参数缺陷类型转 结果参数类型
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int ConfigTypeToResultType(int nconfigType);
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cv::Rect GetCutRoi(cv::Rect &roi, const cv::Mat &img);
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// 获取缺陷 对应的AI输入 输出图片，
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int GetAIDetImg(std::shared_ptr<ImageAllResult> pImageResult, cv::Point pcenter, cv::Mat &AI_InImg, cv::Mat &AI_OutImg);
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// 绘制并保存结果图开关（base 配置 bDrawAndSave，替代 SAVE_RESIMG 宏）
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bool NeedDrawAndSave();
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int sendTask(std::shared_ptr<DrawInfo> task);
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std::shared_ptr<ImageResultJudge::DrawInfo> GetTask();
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void ThreadDraw();
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int DrawResultTask(std::shared_ptr<ImageResultJudge::DrawInfo> task);
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// 等待 绘制完成
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int WaiteDrawComplate();
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int AnalysisResult_Pre(QX_ERROR_INFO_ *QX_info); // 弱化处理
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// 撤销单个缺陷的NG结果：恢复为OK，移除对应NG小图并回退计数
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int UndoNGResult(std::shared_ptr<ImageAllResult> pImageResult, int qxidx, QX_ERROR_INFO_ *QX_info);
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// 跨通道同位置判断：当前缺陷(产品坐标系ROI)在过滤通道是否存在同位置缺陷(双方按 expand 扩张后计算IOU)
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bool IsOverlapQxInFilterChannels(const std::vector<std::shared_ptr<ImageAllResult>> &imgResults,
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const std::string &cur_channel_name,
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const std::vector<std::string> &filter_channels,
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const std::vector<int> &match_qx_types,
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const cv::Rect &qx_product_roi,
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int roi_expand, float iou_threshold,
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const std::string &strTag,
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std::shared_ptr<DetLog> plog);
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// 判断盲失(产品坐标系ROI)在配置的过滤通道是否存在同位置缺陷(不限制类型，双方按 expand 扩张后计算IOU)
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bool IsOverlapQxInMsFilterChannel(const std::vector<std::shared_ptr<ImageAllResult>> &imgResults,
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const std::string &cur_channel_name,
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const cv::Rect &qx_product_roi,
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int roi_expand, float iou_threshold,
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std::shared_ptr<DetLog> plog);
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// 跨通道联合判断(通用)：主通道中指定类型的NG缺陷，若在过滤通道同位置存在指定类型的缺陷，则撤销该NG
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int FilterCrossChannelNG(std::shared_ptr<CameraResult> pCheck_Result,
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const std::vector<std::string> &main_channels,
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const std::vector<std::string> &filter_channels,
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const std::vector<int> &main_qx_types,
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const std::vector<int> &match_qx_types,
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int roi_expand, float iou_threshold,
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const std::string &strTag,
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const std::string &strReason);
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// 关联过滤源过滤：撤销与关联通道过滤源缺陷重叠的暗点NG结果(含单图判定的单点NG)
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int FilterCorrelatedDirtyNG(std::shared_ptr<ImageAllResult> pImageResult);
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ChannelCheckFunction *GetChannelFuntion(std::string strChannelName); // 获得 通道的检测功能
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int ConfigTypeToQXAnalysis(int nconfigType);
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private:
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bool m_bExit;
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float m_fImgage_Scale_X = 0.1;
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float m_fImgage_Scale_Y = 0.1;
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// 检测分析参数
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AnalysisyConfigST *m_pAnalysisyConfig;
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CommonConfigNodeST *m_pCommonAnalysisyConfig;
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ALLChannelCheckFunction *m_pChannelFuntion; // 画面检测功能
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BaseCheckFunction *m_pbaseCheckFunction; // 基础检测
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RegionConfigST *m_pRegionAnalysisyParam; // 分析参数
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BasicConfig *m_pBasicConfig;
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// 检查缺陷对应参数中的位置。
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int m_QxInParamListIdx[CONFIG_QX_NAME_count];
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std::queue<std::shared_ptr<DrawInfo>> m_DrawInfoList;
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std::mutex m_task_mutex_;
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std::condition_variable m_task_cv_;
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std::shared_ptr<std::thread> ptr_thread_Draw;
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std::condition_variable m_drawComplate_cv_;
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std::shared_ptr<QX_Merge_Analysis> m_pQX_Merge_Analysis;
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};
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#endif |
