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BOE_CELL_AOI_Detect_CD4Pattern
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v1.2.3

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dev_lsy
liusiyang 5 days ago
parent d13a6d5f39
commit 2a987af65f
4 changed files with 18 additions and 95 deletions
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1
.gitignore vendored
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@ -3,4 +3,5 @@
/include
/data
/SaveImg
/tmp
.vscode/launch.json

16
AlgorithmModule/src/ALLImgCheckAnalysisy.cpp
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@ -351,22 +351,6 @@ int ALLImgCheckAnalysisy::GetUpdateParamOut(const std::string &strCamera, Update
return 0;
}
// 兜底: 缓存中没有时, 直接按相机名从参数模块实时取一次
if (m_pConfigManager != nullptr)
{
auto itConfig = m_pConfigManager->Config_instances_.find(strCamera);
if (itConfig != m_pConfigManager->Config_instances_.end() && itConfig->second)
{
AnalysisyConfigST analysisyConfig;
if (itConfig->second->GetConfig(ConfigType_Analysisy_Common_XL, &analysisyConfig) == 0)
{
FillUpdateParamOut(analysisyConfig, outParam);
m_UpdateParamOutMap[strCamera] = outParam;
return 0;
}
}
}
return 1;
}

80
AlgorithmModule/src/CameraCheckAnalysisy.cpp
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@ -1627,82 +1627,6 @@ int CameraCheckAnalysisy::GetLine(const cv::Mat &img, std::vector<cv::Point> &po
return 0;
}
// 找到图像中产品(亮色区域)所在的第一行(顶部边缘), 用于左右图上下对齐
// 从上往下逐行扫描, 当某一行亮像素数量超过阈值比例时, 认为该行是产品顶边
int CameraCheckAnalysisy::GetProductFirstRow(const cv::Mat &img, int &outRow)
{
outRow = -1;
if (img.empty())
{
return 1;
}
cv::Mat gray;
if (img.channels() == 1)
{
gray = img;
}
else if (img.channels() == 3)
{
cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);
}
else
{
return 1;
}
const uchar brightThreshold = 35; // 亮像素灰度阈值(与背景判断阈值保持一致)
const int needBrightCount = std::max(1, (int)(gray.cols * 0.02)); // 该行亮像素数量占比超过 20% 认为是产品所在行
const int rowStep = 16; // 跳行扫描步长
// 判断某一行是否为产品所在行(亮像素数量达到阈值)
auto isProductRow = [&](int row) -> bool
{
const uchar *p = gray.ptr<uchar>(row);
int brightCount = 0;
for (int col = 0; col < gray.cols; ++col)
{
if (p[col] >= brightThreshold)
{
if (++brightCount >= needBrightCount)
{
return true;
}
}
}
return false;
};
// 1、跳行粗扫: 每隔 rowStep 行扫描一次, 定位产品顶边的大致位置
int rowFound = -1;
for (int row = 0; row < gray.rows; row += rowStep)
{
if (isProductRow(row))
{
rowFound = row;
break;
}
}
if (rowFound < 0)
{
return 2; // 未找到产品顶边
}
// 2、在上一个采样行与 rowFound 之间逐行精确定位
int rowStart = std::max(0, rowFound - rowStep + 1);
for (int row = rowStart; row <= rowFound; ++row)
{
if (isProductRow(row))
{
outRow = row;
return 0;
}
}
return 2; // 理论上不会走到这里
}
// 拟合图像中产品(亮色区域)的顶边直线段: 对顶边上的点做最小二乘拟合, 得到 y = k * x + b
// 产品倾斜时顶边在每一列的高度不同, 用逐列顶边点拟合出的直线才能真正反映倾斜,
// 左右两张图各拟合一条线段后, 就可以让它们在拼接缝处首尾相连。
@ -1734,8 +1658,8 @@ int CameraCheckAnalysisy::FitProductTopLine(const cv::Mat &img, float &outK, flo
return 1;
}
const uchar brightThreshold = 45; // 亮像素灰度阈值(与背景判断阈值保持一致)
const int needBrightCount = std::max(1, (int)(gray.cols * 0.1)); // 该行亮像素数量占比超过 20% 认为是产品所在行
const uchar brightThreshold = 35; // 亮像素灰度阈值(与背景判断阈值保持一致)
const int needBrightCount = std::max(1, (int)(gray.cols * 0.02)); // 该行亮像素数量占比超过 20% 认为是产品所在行
const int rowStep = 16; // 跳行扫描步长
// 判断某一行是否为产品所在行(亮像素数量达到阈值)

16
AlgorithmModule/src/ImgCheckAnalysisy.cpp
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@ -181,7 +181,7 @@ int ImgCheckAnalysisy::GetStatus()
std::string ImgCheckAnalysisy::GetVersion()
{
return std::string("BOE_1.2.1");
return std::string("BOE_1.2.3");
}
std::string ImgCheckAnalysisy::GetErrorInfo()
@ -702,6 +702,13 @@ int ImgCheckAnalysisy::Adapt_Config(Mat img, Rect cur_roi, cv::RotatedRect& rot_
// cv::line(show_img, cur_regionConfigArr[i].basicInfo.pointArry.back(), cur_regionConfigArr[i].basicInfo.pointArry.front(), Scalar(255,0,0), 10);
// }
// }
// if (cur_traditional_region.size() >= 2)
// {
// for(size_t i = 0 ; i < cur_traditional_region.size() - 1; i++){
// cv::line(show_img, cur_traditional_region[i], cur_traditional_region[i+1], Scalar(0,0,255), 20);
// }
// cv::line(show_img, cur_traditional_region.back(), cur_traditional_region.front(), Scalar(0,0,255), 20);
// }
// imwrite(m_AnalysisyConfig.commonCheckConfig.baseConfig.strCamearName +"_org_img.tiff", show_img);
/*使用仿射矩阵进行修改*/
@ -763,6 +770,13 @@ int ImgCheckAnalysisy::Adapt_Config(Mat img, Rect cur_roi, cv::RotatedRect& rot_
// cv::line(show_img, cur_regionConfigArr[i].basicInfo.pointArry.back(), cur_regionConfigArr[i].basicInfo.pointArry.front(), Scalar(255,0,0), 10);
// }
// }
// if (cur_traditional_region.size() >= 2)
// {
// for(size_t i = 0 ; i < cur_traditional_region.size() - 1; i++){
// cv::line(show_img, cur_traditional_region[i], cur_traditional_region[i+1], Scalar(0,0,255), 20);
// }
// cv::line(show_img, cur_traditional_region.back(), cur_traditional_region.front(), Scalar(0,0,255), 20);
// }
// imwrite(m_AnalysisyConfig.commonCheckConfig.baseConfig.strCamearName +"_show_img.tiff", show_img);
return 0;

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