BOE_FOG_DETECT/AlgorithmModule/src/AI_Second_Det.cpp

#include "AI_Edge_Algin.h"
#include "CheckErrorCodeDefine.hpp"
#include "AI_Second_Det.h"

AI_SecondDet::AI_SecondDet()
{
    m_bModelSucc_AD = false;
    m_bModelSucc_POL = false;
    CheckUtil::CreateDir("/home/aidlux/BOE/FOG/Second/POL/");
    CheckUtil::CreateDir("/home/aidlux/BOE/FOG/Second/AD/");
    m_pImageStorage = ImageStorage::getInstance();
    m_Show_Area = 0;
    m_Show_Len = 0;
    m_Len_P1 = cv::Point(0, 0);
    m_Len_P2 = cv::Point(0, 0);
    AI_Factory = AIFactory::GetInstance();
}

AI_SecondDet::~AI_SecondDet()
{
}

int AI_SecondDet::Detect(const cv::Mat &img, const cv::Mat &mask, DetConfigResult *pDetConfig)
{
    m_pdetlog = pDetConfig->pdetlog;
    // 二次求面积长度 功能关闭
    if (!pDetConfig->pfunction_secondDet->bOpen)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "function colse");
        return 1;
    }
    // cv::Mat temimg = mask.clone();
    // cv::rectangle(temimg, pDetConfig->qx_roi, cv::Scalar(128, 0, 0));
    cv::Rect AIroi = GetCutRoi(pDetConfig->qx_roi, img);

    if (AIroi.width <= 0 || AIroi.height <= 0)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "Error  Size");
        return 1;
    }
    if (!CheckUtil::RoiInImg(AIroi, img))
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "Error  ROI");
        return 1;
    }

    float min_set_param_area = 0;
    float max_set_param_area = 9999;
    if (pDetConfig->qx_type == CONFIG_QX_NAME_POL_Cell)
    {
        min_set_param_area = pDetConfig->pfunction_secondDet->pol_area_min;
        max_set_param_area = pDetConfig->pfunction_secondDet->pol_area_max;
    }
    if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
    {
        min_set_param_area = pDetConfig->pfunction_secondDet->andian_area_min;
        max_set_param_area = pDetConfig->pfunction_secondDet->andian_area_max;
    }
    float oldarea_mm2 = pDetConfig->old_Area * pDetConfig->fImgage_Scale_X * pDetConfig->fImgage_Scale_Y;
    if (oldarea_mm2 < min_set_param_area || oldarea_mm2 > max_set_param_area)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "error Area %0.2f out[%0.2f %0.2f] ", oldarea_mm2, min_set_param_area, max_set_param_area);
        return 1;
    }
    if (oldarea_mm2 < pDetConfig->min_DetArea)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "Error Area %0.2f < det param %0.2f ", oldarea_mm2, pDetConfig->min_DetArea);
        return 1;
    }
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "succ  Area %0.2f >= min det param  %0.2f and in [%0.2f %0.2f] ", oldarea_mm2, pDetConfig->min_DetArea, min_set_param_area, max_set_param_area);
    }

    cv::Mat detimg = img(AIroi).clone();

    cv::Mat outimg;
    int re12 = 0;
    //
    if (pDetConfig->qx_type == CONFIG_QX_NAME_POL_Cell)
    {
        if (pDetConfig->pfunction_secondDet->pol_saveProcessImg)
        {
            // printf("mask %d %d \n", mask.cols, mask.rows);
            // printf("AIroi %d %d  %d %d\n", AIroi.x, AIroi.y, AIroi.width, AIroi.height);
            detimg123 = mask(AIroi).clone();
            // printf("1111mask %d %d \n", mask.cols, mask.rows);
        }

        re12 = Det_Pol(detimg, pDetConfig);
    }
    if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
    {
        if (pDetConfig->pfunction_secondDet->andian_saveProcessImg)
        {
            // printf("mask %d %d \n", mask.cols, mask.rows);
            // printf("AIroi %d %d  %d %d\n", AIroi.x, AIroi.y, AIroi.width, AIroi.height);
            detimg123 = mask(AIroi).clone();
            // printf("2222mask %d %d \n", mask.cols, mask.rows);
        }
        re12 = Det_AD(detimg, pDetConfig);
    }
    if (re12 != 0)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE_POL /AD", "Error ");
        return 1;
    }
    return 0;
}

cv::Rect AI_SecondDet::GetCutRoi(cv::Rect &roi, const cv::Mat &img)
{
    std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_RE_POL;

    cv::Size sz;
    sz.width = pAI_Model->input_0.width;
    sz.height = pAI_Model->input_0.height;

    int Dst_Width = sz.width;
    int Dst_Height = sz.height;
    cv::Rect cutroi = cv::Rect(0, 0, 0, 0);
    if (Dst_Width >= img.cols || Dst_Height >= img.rows)
    {
        return cutroi;
    }
    if (roi.width >= Dst_Width || roi.height >= Dst_Height)
    {
        return cutroi;
    }

    int centerX = roi.x + roi.width / 2;
    int centerY = roi.y + roi.height / 2;

    // 构造一个以中心为中心的 128x128 矩形
    int halfSize = Dst_Width / 2; // 128 / 2
    int newX = centerX - halfSize;
    int newY = centerY - halfSize;
    int newWidth = Dst_Width;
    int newHeight = Dst_Height;

    // 检查矩形是否越界
    if (newX < 0)
    {
        newX = 0;
    }
    if (newY < 0)
    {
        newY = 0;
    }
    if (newX + newWidth > img.cols)
    {
        newX = img.cols - newWidth;
    }
    if (newY + newHeight > img.rows)
    {
        newY = img.rows - newHeight;
    }

    // 创建新的矩形
    cv::Rect newRect(newX, newY, newWidth, newHeight);
    int add = 3;
    // 重新计算 roi 在新的矩形中的位置
    int newRoiX = roi.x - newRect.x - add;
    int newRoiY = roi.y - newRect.y - add;
    int newRoiWidth = roi.width + 2 * add;
    int newRoiHeight = roi.height + 2 * add;

    // 确保新的 roi 在新的矩形内
    if (newRoiX < 0)
    {
        newRoiX = 0;
    }
    if (newRoiY < 0)
    {
        newRoiY = 0;
    }
    if (newRoiX + newRoiWidth > newRect.width)
    {
        newRoiWidth = newRect.width - newRoiX;
    }
    if (newRoiY + newRoiHeight > newRect.height)
    {
        newRoiHeight = newRect.height - newRoiY;
    }

    // 更新 roi
    roi = cv::Rect(newRoiX, newRoiY, newRoiWidth, newRoiHeight);

    // 返回新的矩形
    return newRect;
}
int AI_SecondDet::Det_Pol(const cv::Mat &img, DetConfigResult *pDetConfig)
{

    std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_RE_POL;
    int re = 0;
    cv::Mat outimg;
    m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", " POL start");

    re = pAI_Model->AIDet(img, outimg);
    if (re != 0)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE ", "Error POL AI Model Error");
        return 1;
    }

    if (outimg.empty())
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE ", "Error POL AI  Error");
        return 1;
    }
    cv::Mat AnalysisyImg = outimg(pDetConfig->qx_roi).clone();
    m_Show_Area = pDetConfig->old_Area;
    m_Show_Len = pDetConfig->old_len;
    // 开始分析mask;
    re = Analysisy(AnalysisyImg, pDetConfig);
    m_Len_P1.x += pDetConfig->qx_roi.x;
    m_Len_P1.y += pDetConfig->qx_roi.y;

    m_Len_P2.x += pDetConfig->qx_roi.x;
    m_Len_P2.y += pDetConfig->qx_roi.y;

    // 存储中间过程图片
    if (pDetConfig->pfunction_secondDet->pol_saveProcessImg)
    {
        if (true)
        {
            cv::rectangle(outimg, pDetConfig->qx_roi, cv::Scalar(128, 0, 0));
            cv::rectangle(detimg123, pDetConfig->qx_roi, cv::Scalar(128, 0, 0));

            cv::line(outimg, m_Len_P1, m_Len_P2, cv::Scalar(128, 0, 0));

            {
                char buffer[128];
                sprintf(buffer, " oA %d  -> nA %d ",
                        pDetConfig->old_Area, m_Show_Area);
                std::string st1 = buffer;
                cv::Point p(0, 10);
                cv::putText(outimg, st1, p, cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(200, 0, 255), 0.35, 1, 0);

                sprintf(buffer, " oL %0.2f -> nL %0.2f ",
                        pDetConfig->old_len, m_Show_Len);
                st1 = buffer;
                cv::Point p2(0, 20);
                cv::putText(outimg, st1, p2, cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(200, 0, 255), 0.35, 1, 0);
            }
        }
        SaveProcessImg(img, outimg, detimg123, pDetConfig);
    }

    return re;
}

int AI_SecondDet::Det_AD(const cv::Mat &img, DetConfigResult *pDetConfig)
{
    std::shared_ptr<AIModel_Base> pAI_Model = AI_Factory->AI_defect_RE_AD;
    int re = 0;
    cv::Mat outimg;
    m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", " AD start");
    re = pAI_Model->AIDet(img, outimg);

    if (re != 0)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE ", "Error AD AI Model Error");
        return 1;
    }

    if (outimg.empty())
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE ", "Error AD AI  Error");
        return 1;
    }
    if (!CheckUtil::RoiInImg(pDetConfig->qx_roi, outimg))
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "qx roi Error");
        return 1;
    }
    cv::Mat AnalysisyImg = outimg(pDetConfig->qx_roi).clone();

    m_Show_Area = pDetConfig->old_Area;
    m_Show_Len = pDetConfig->old_len;
    // 开始分析mask;
    re = Analysisy(AnalysisyImg, pDetConfig);

    m_Len_P1.x += pDetConfig->qx_roi.x;
    m_Len_P1.y += pDetConfig->qx_roi.y;

    m_Len_P2.x += pDetConfig->qx_roi.x;
    m_Len_P2.y += pDetConfig->qx_roi.y;

    if (pDetConfig->pfunction_secondDet->andian_saveProcessImg)
    {
        if (true)
        {
            cv::rectangle(outimg, pDetConfig->qx_roi, cv::Scalar(128, 0, 0));
            cv::rectangle(detimg123, pDetConfig->qx_roi, cv::Scalar(128, 0, 0));
            cv::line(outimg, m_Len_P1, m_Len_P2, cv::Scalar(128, 0, 0));
            {
                char buffer[128];
                sprintf(buffer, " oA %d  -> nA %d ",
                        pDetConfig->old_Area, m_Show_Area);
                std::string st1 = buffer;
                cv::Point p(0, 10);
                cv::putText(outimg, st1, p, cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(200, 0, 255), 0.35, 1, 0);

                sprintf(buffer, " oL %0.2f -> nL %0.2f ",
                        pDetConfig->old_len, m_Show_Len);
                st1 = buffer;
                cv::Point p2(0, 20);
                cv::putText(outimg, st1, p2, cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(200, 0, 255), 0.35, 1, 0);
            }
        }

        SaveProcessImg(img, outimg, detimg123, pDetConfig);
    }

    return re;
}

int AI_SecondDet::Analysisy(const cv::Mat &maskImg, DetConfigResult *pDetConfig)
{
    // 存储轮廓
    std::vector<std::vector<cv::Point>> contours;
    // 存储每个轮廓的层级
    std::vector<cv::Vec4i> hierarchy;

    // 寻找轮廓
    cv::findContours(maskImg, contours, hierarchy, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);

    double maxArea = 0;
    int maxIndex = -1;

    // 遍历每个轮廓，计算面积并找出最大的面积
    for (size_t i = 0; i < contours.size(); i++)
    {
        double area = cv::contourArea(contours[i]);
        if (area > maxArea)
        {
            maxArea = area;
            maxIndex = i;
        }
    }
    if (maxIndex < 0)
    {
        m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "second mask is error");
        return 1;
        /* code */
    }
    bool barea = false;
    bool blen = false;
    int oldArea = pDetConfig->old_Area;
    float oldLen = pDetConfig->old_len;
    if (pDetConfig->qx_type == CONFIG_QX_NAME_POL_Cell)
    {
        barea = pDetConfig->pfunction_secondDet->pol_Open_area;
        blen = pDetConfig->pfunction_secondDet->pol_Open_len;
    }
    if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
    {
        barea = pDetConfig->pfunction_secondDet->andian_Open_area;
        blen = pDetConfig->pfunction_secondDet->andian_Open_len;
    }
    // 计算面积
    // if (barea)
    {
        int maxContourPixelCount = 0;
        if (maxIndex >= 0)
        {
            cv::Mat mask = cv::Mat::zeros(maskImg.size(), CV_8UC1);
            cv::drawContours(mask, contours, maxIndex, cv::Scalar(255), cv::FILLED); // 绘制轮廓填充区域
            maxContourPixelCount = cv::countNonZero(mask);                           // 计算填充区域的像素个数
        }
        m_Show_Area = maxContourPixelCount;

        if (barea)
        {
            if (maxContourPixelCount > 0 && maxContourPixelCount < oldArea)
            {
                pDetConfig->new_Area = maxContourPixelCount;
            }
            m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "Use New Area :old area  %d (pixel) new %d", oldArea, pDetConfig->new_Area);
        }
        else
        {
            m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", " Not Use Area :old area  %d (pixel) new %d", oldArea, maxContourPixelCount);
        }
    }
    // else
    // {
    //     m_pTemCheck->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Area", "Cal Area is Close");
    // }

    // 计算长度
    // if (blen)
    {
        cv::RotatedRect rect = cv::minAreaRect(contours[maxIndex]);

        // 获取最小外接矩形的尺寸
        float width = rect.size.width;
        float height = rect.size.height;

        Point2f vertices[4];
        rect.points(vertices);

        if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
        {
            float len1 = sqrt((vertices[0].x - vertices[1].x) * (vertices[0].x - vertices[1].x) +
                              (vertices[0].y - vertices[1].y) * (vertices[0].y - vertices[1].y));

            float len2 = sqrt((vertices[2].x - vertices[1].x) * (vertices[2].x - vertices[1].x) +
                              (vertices[2].y - vertices[1].y) * (vertices[2].y - vertices[1].y));

            if (len1 > len2)
            {
                m_Len_P1.x = vertices[0].x;
                m_Len_P1.y = vertices[0].y;

                m_Len_P2.x = vertices[1].x;
                m_Len_P2.y = vertices[1].y;
            }
            else
            {
                m_Len_P1.x = vertices[2].x;
                m_Len_P1.y = vertices[2].y;

                m_Len_P2.x = vertices[1].x;
                m_Len_P2.y = vertices[1].y;
            }
        }
        else
        {
            m_Len_P1.x = vertices[2].x;
            m_Len_P1.y = vertices[2].y;

            m_Len_P2.x = vertices[0].x;
            m_Len_P2.y = vertices[0].y;
        }

        vector<Point2f> newcont;
        for (int i = 0; i < 4; ++i)
        {
            Point2f p;
            p.x = vertices[i].x * pDetConfig->fImgage_Scale_X;
            p.y = vertices[i].y * pDetConfig->fImgage_Scale_Y;
            newcont.push_back(p);
        }
        vector<vector<Point2f>> contours_New;
        contours_New.push_back(newcont);
        // Recreate the rotated rectangle with scaled vertices
        RotatedRect scaledRect = minAreaRect(contours_New[0]);

        // Calculate scaled width and height
        width = scaledRect.size.width;
        height = scaledRect.size.height;
        float new_len = width;
        if (width > 0 && height > 0)
        {
            if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
            {
                if (width > height)
                {
                    new_len = width;
                }
                else
                {
                    new_len = height;
                }
            }
            else
            {
                new_len = sqrt(width * width + height * height);
            }
        }
        else
        {
            if (width > height)
            {
                new_len = width;
            }
            else
            {
                new_len = height;
            }
        }

        // printf("oldLen %f  new_len %f \n", oldLen, new_len);
        m_Show_Len = new_len;
        if (blen)
        {
            if (new_len > 0 && new_len < oldLen)
            {
                pDetConfig->new_len = new_len;
            }
            m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Len", "Use New Len :old Len  %f (mm) new %f", oldLen, pDetConfig->new_len);
        }
        else
        {
            m_pdetlog->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Len", " Not Use Len :old Len  %f (mm) new %f", oldLen, new_len);
        }
    }
    // else
    // {
    //     m_pTemCheck->AddCheckstr(PrintLevel_3, DET_LOG_LEVEL_3, "AICheck_RE Len", "Cal Len is Close");
    // }

    return 0;
}

int AI_SecondDet::SaveProcessImg(const cv::Mat &inImg, const cv::Mat &outImg, const cv::Mat &oldmask, DetConfigResult *pDetConfig)
{

    if (inImg.empty() || outImg.empty())
    {
        return 1;
    }
    static int saveimgIdx_pol = 0;
    static int saveimgIdx_ad = 0;
    // 循环存储

    std::string str_Root = "/home/aidlux/BOE/FOG/Second/";
    if (pDetConfig->qx_type == CONFIG_QX_NAME_POL_Cell)
    {

        saveimgIdx_pol++;
        if (saveimgIdx_pol > 1000)
        {
            saveimgIdx_pol = 0;
        }
        str_Root += "POL/POl_" + pDetConfig->strChannel + "_" + std::to_string(saveimgIdx_pol);
    }
    if (pDetConfig->qx_type == CONFIG_QX_NAME_AD)
    {

        saveimgIdx_ad++;
        if (saveimgIdx_ad > 1000)
        {
            saveimgIdx_ad = 0;
        }
        str_Root += "AD/AD_" + pDetConfig->strChannel + "_" + std::to_string(saveimgIdx_ad);
    }
    std::string strIn = str_Root + +"_in.png";
    int re = 0;
    if (!inImg.empty())
    {
        re = m_pImageStorage->addImage(strIn, inImg);
    }

    if (re == 0)
    {
        std::string strmask = str_Root + "_in_mask.png";
        if (!outImg.empty())
        {
            m_pImageStorage->addImage(strmask, outImg, true); // 强制 存储
        }

        std::string stroldmask = str_Root + "_old_mask.png";
        if (!oldmask.empty())
        {
            m_pImageStorage->addImage(stroldmask, oldmask, true); // 强制 存储
        }
    }

    return 0;
}