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feat 清理把手检测多余配置

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dev_lsy
liusiyang 4 weeks ago
parent d8e953e160
commit b7b8c100ef
4 changed files with 58 additions and 206 deletions
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10
AlgorithmModule/include/ImgCheckAnalysisy.hpp
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@ -50,18 +50,16 @@ enum AT_THRESHOLD_TYPE_
// 全局静态变量， 记录图像灰度值异常累计数量
static int g_nImgBrightnessErrorCount = 0;
// 把手候选：bigmask 凸起 + 实测特征（后续增加面积/灰阶等判定时直接用这些实测值）
// 把手候选：bigmask 凸起 + 实测特征（面积/填充率，仅供日志排查）
struct Handle_Candidate_
{
Mask_Protrusion_ protr; // 凸起几何信息（roi / 沿边长度 / 深度 / 面积 / 填充率）
int nLen; // 沿边长度（像素）
int nDepth; // 垂直深度（像素）
float fGrayDiff; // 凸起区域与周边背景的平均灰度差（预留灰阶判定）
Handle_Candidate_()
{
nLen = 0;
nDepth = 0;
fGrayDiff = 0.0f;
}
};
@ -158,15 +156,13 @@ private:
// 发布本图定位结果/失败标记(供同产品其它相机复用)
void PublishAlignShare(bool bSucc);
// 用 bigmask 检测把手（bigmask 主体近似矩形，把手是四周凸起的矩形块）
int CheckHandleByBigMask(const cv::Mat &img, const cv::Mat &bigmask);
int CheckHandleByBigMask(const cv::Mat &bigmask);
// 标签检测(独立步骤)：用 (图像 + bigmask) 跑 Tag_Loc 模型，检出结果存 m_tag_roiList
// 明场传自身 bigmask；暗场不做定位模型，传复用明场的 bigmask
int CheckTagByBigMask(const cv::Mat &img, const cv::Mat &bigmask);
// 在某个把手区域附近找宽高匹配的凸起：返回凸起在 candList 中的下标（-1=没找到）
int MatchHandleRegion(const std::vector<Handle_Candidate_> &candList, const std::vector<bool> &usedList,
const cv::Rect &boxRegion, const Handle_Check_Param &param, cv::Rect &roiHandle);
// 计算凸起区域与周边背景的平均灰度差（灰阶判定的预留量测值，img 需为单通道）
float CalProtrusionGrayDiff(const cv::Mat &grayImg, const cv::Rect &roi);
const cv::Rect &boxRegion, cv::Rect &roiHandle);
// 计算产品尺寸
int CalProductSize();
// 图片预处理

103
AlgorithmModule/src/ImgCheckAnalysisy.cpp
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@ -21,7 +21,7 @@
#define HANDLE_SIZE_MAX_RATIO 1.2f
// "附近"的搜索范围：把手区域外接矩形在宽/高方向各外扩该比例
#define HANDLE_NEAR_EXPAND_RATIO 5
// 凸起填充率下限等参数的默认值在 Handle_Check_Param（CheckConfigDefine.h）里
// 把手缺失检测开关见 Function_Support_Det::bDetHandle（CheckConfigDefine.h）
// 用于排序轮廓的比较函数
static bool compareContourAreas(const vector<Point> &contour1, const vector<Point> &contour2)
@ -811,7 +811,7 @@ int ImgCheckAnalysisy::CheckRun()
// 定位模型不跑，但把手检测仍要执行：暗场图像 + 明场 bigmask
{
long handle_s = CheckUtil::getcurTime();
CheckHandleByBigMask(m_CheckResult_shareP->in_shareImage->img, m_pEdge_Align_Result->bigmask);
CheckHandleByBigMask(m_pEdge_Align_Result->bigmask);
long handle_e = CheckUtil::getcurTime();
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle", "handle detect use time %ld", handle_e - handle_s);
}
@ -2552,7 +2552,7 @@ int ImgCheckAnalysisy::AI_Edge(const cv::Mat &img, cv::RotatedRect &outerRoi, cv
/*使用m_pEdge_Align_Result->bigmask检测把手是否缺失*/
{
long handle_s = CheckUtil::getcurTime();
CheckHandleByBigMask(img, m_pEdge_Align_Result->bigmask);
CheckHandleByBigMask(m_pEdge_Align_Result->bigmask);
long handle_e = CheckUtil::getcurTime();
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle", "handle detect use time %ld", handle_e - handle_s);
}
@ -2565,7 +2565,7 @@ int ImgCheckAnalysisy::AI_Edge(const cv::Mat &img, cv::RotatedRect &outerRoi, cv
// 3、参数里每个非空的"把手区域"附近都应该有一个把手：在区域附近找凸起，
// 凸起宽高与区域外接矩形宽高相近（HANDLE_SIZE_MIN_RATIO ~ HANDLE_SIZE_MAX_RATIO）才算匹配
// 4、凸起本身不算 NG，只有"某个把手区域附近找不到匹配的凸起"才算把手缺失（NG 由 CheckRun 上报）
int ImgCheckAnalysisy::CheckHandleByBigMask(const cv::Mat &img, const cv::Mat &bigmask)
int ImgCheckAnalysisy::CheckHandleByBigMask(const cv::Mat &bigmask)
{
m_bHandleDetSucc = false;
m_bHandleFound = false;
@ -2589,38 +2589,23 @@ int ImgCheckAnalysisy::CheckHandleByBigMask(const cv::Mat &img, const cv::Mat &b
}
m_bHandleDetSucc = true;
// 2、把手判定参数 + 把手区域（最多4个，非空区域表示该处应该有一个把手）
Handle_Check_Param handleParam;
// 2、把手检测开关 + 把手区域（最多4个，非空区域表示该处应该有一个把手）
bool bDetHandle = false;
std::vector<cv::Rect> regionBoxList;
if (m_pFuntion != NULL)
{
const Function_Support_Det &supportDet = m_pFuntion->function.f_supportDet;
handleParam = supportDet.handleParam;
bDetHandle = supportDet.bDetHandle;
for (size_t i = 0; i < supportDet.handleBoxes.size() && i < HANDLE_REGION_MAX_NUM; i++)
{
regionBoxList.push_back(supportDet.handleBoxes[i]);
}
}
m_bHandleExpect = (handleParam.bOpen && !regionBoxList.empty());
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle", "protrusion num %ld handle region num %ld expect %s",
protrusionList.size(), regionBoxList.size(), BOOL_TO_STR(m_bHandleExpect));
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle", "%s", handleParam.GetInfo("judge").c_str());
m_bHandleExpect = (bDetHandle && !regionBoxList.empty());
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle", "protrusion num %ld handle region num %ld bDetHandle %s expect %s",
protrusionList.size(), regionBoxList.size(), BOOL_TO_STR(bDetHandle), BOOL_TO_STR(m_bHandleExpect));
// 灰阶判定是预留项：只有开启时才做灰度换算，避免无谓开销
cv::Mat grayImg;
if (handleParam.bJudgeGray && !img.empty())
{
if (img.channels() != 1)
{
cv::cvtColor(img, grayImg, cv::COLOR_BGR2GRAY);
}
else
{
grayImg = img;
}
}
// 3、凸起候选实测特征（面积/填充率/灰度差，供日志与后续判定用）
// 3、凸起候选实测特征（面积/填充率，仅用于日志排查）
for (size_t i = 0; i < protrusionList.size(); i++)
{
Handle_Candidate_ cand;
@ -2629,17 +2614,11 @@ int ImgCheckAnalysisy::CheckHandleByBigMask(const cv::Mat &img, const cv::Mat &b
bool bHorz = (cand.protr.nSide == 0 || cand.protr.nSide == 1);
cand.nLen = bHorz ? cand.protr.roi.height : cand.protr.roi.width;
cand.nDepth = bHorz ? cand.protr.roi.width : cand.protr.roi.height;
if (!grayImg.empty())
{
cand.fGrayDiff = CalProtrusionGrayDiff(grayImg, cand.protr.roi);
}
m_HandleCandList.push_back(cand);
// grayDiff 打印 -1 表示本次未开启灰阶判定（未计算）
m_pdetlog->AddCheckstr(PrintLevel_1, DET_LOG_LEVEL_3, "Handle",
"protrusion %ld side %d roi [%d %d %d %d] len %d depth %d area %0.0f fill %0.2f grayDiff %0.1f",
"protrusion %ld side %d roi [%d %d %d %d] len %d depth %d area %0.0f fill %0.2f",
i, cand.protr.nSide, cand.protr.roi.x, cand.protr.roi.y, cand.protr.roi.width, cand.protr.roi.height,
cand.nLen, cand.nDepth, cand.protr.fArea, cand.protr.fFillRatio,
grayImg.empty() ? -1.0f : cand.fGrayDiff);
cand.nLen, cand.nDepth, cand.protr.fArea, cand.protr.fFillRatio);
}
// 4、逐个把手区域：在区域附近找宽高匹配的凸起（同一个凸起只匹配给一个区域）
@ -2650,7 +2629,7 @@ int ImgCheckAnalysisy::CheckHandleByBigMask(const cv::Mat &img, const cv::Mat &b
Handle_Region_Result_ result;
result.nIdx = (int)ir + 1;
result.boxRegion = regionBoxList[ir];
int nMatchIdx = MatchHandleRegion(m_HandleCandList, usedList, result.boxRegion, handleParam, result.roiHandle);
int nMatchIdx = MatchHandleRegion(m_HandleCandList, usedList, result.boxRegion, result.roiHandle);
result.bFound = (nMatchIdx >= 0);
if (result.bFound)
{
@ -2844,10 +2823,9 @@ int ImgCheckAnalysisy::CheckTagByBigMask(const cv::Mat &img, const cv::Mat &bigm
// 在某个把手区域附近找宽高匹配的凸起
// 匹配条件：1、凸起中心落在把手区域附近（区域宽/高各外扩 HANDLE_NEAR_EXPAND_RATIO）
// 2、凸起宽高与该区域外接矩形宽高的比值都在 [HANDLE_SIZE_MIN_RATIO, HANDLE_SIZE_MAX_RATIO]（允许横竖互换）
// 3、填充率、预留的面积/灰阶等开关条件都满足
// 返回凸起在 candList 中的下标，-1 表示没找到
int ImgCheckAnalysisy::MatchHandleRegion(const std::vector<Handle_Candidate_> &candList, const std::vector<bool> &usedList,
const cv::Rect &boxRegion, const Handle_Check_Param &param, cv::Rect &roiHandle)
const cv::Rect &boxRegion, cv::Rect &roiHandle)
{
if (boxRegion.width <= 0 || boxRegion.height <= 0)
{
@ -2890,24 +2868,6 @@ int ImgCheckAnalysisy::MatchHandleRegion(const std::vector<Handle_Candidate_> &c
nNearIdx = (int)i;
}
// 类似矩形块：凸起区域内掩膜填充率要高
if (param.bJudgeFill && cand.protr.fFillRatio < param.fFillMin)
{
continue;
}
// 预留：凸起面积
if (param.bJudgeArea && param.fAreaMax > param.fAreaMin &&
(cand.protr.fArea < param.fAreaMin || cand.protr.fArea > param.fAreaMax))
{
continue;
}
// 预留：凸起与背景的灰度差
if (param.bJudgeGray && param.fGrayMax > param.fGrayMin &&
(cand.fGrayDiff < param.fGrayMin || cand.fGrayDiff > param.fGrayMax))
{
continue;
}
// 宽高：与把手区域外接矩形的宽高相近（允许横竖互换）
float fw = (float)roi.width;
float fh = (float)roi.height;
@ -2948,39 +2908,6 @@ int ImgCheckAnalysisy::MatchHandleRegion(const std::vector<Handle_Candidate_> &c
return nBestIdx;
}
// 计算凸起区域与周边背景的平均灰度差（灰阶判定的预留量测值，grayImg 需为单通道）
float ImgCheckAnalysisy::CalProtrusionGrayDiff(const cv::Mat &grayImg, const cv::Rect &roi)
{
if (grayImg.empty() || grayImg.channels() != 1 || roi.width <= 0 || roi.height <= 0)
{
return 0.0f;
}
// 凸起区域通常整个都在掩膜内，向外扩一圈才能取到背景
int nExpand = std::max(20, std::min(roi.width, roi.height) / 2);
cv::Rect roiBg(roi.x - nExpand, roi.y - nExpand, roi.width + 2 * nExpand, roi.height + 2 * nExpand);
roiBg &= cv::Rect(0, 0, grayImg.cols, grayImg.rows);
if (roiBg.width <= 0 || roiBg.height <= 0)
{
return 0.0f;
}
cv::Mat grayRoi = grayImg(roiBg);
cv::Mat maskIn = cv::Mat::zeros(roiBg.size(), CV_8UC1);
cv::Rect inter = roi & roiBg;
cv::rectangle(maskIn, inter - roiBg.tl(), cv::Scalar(255), cv::FILLED);
cv::Mat maskOut;
cv::bitwise_not(maskIn, maskOut);
if (cv::countNonZero(maskIn) <= 0 || cv::countNonZero(maskOut) <= 0)
{
return 0.0f;
}
double fMeanIn = cv::mean(grayRoi, maskIn)[0];
double fMeanOut = cv::mean(grayRoi, maskOut)[0];
double fDiff = fMeanIn - fMeanOut;
return (float)(fDiff >= 0 ? fDiff : -fDiff);
}
int ImgCheckAnalysisy::CalProductSize()
{
float fw = m_outer_roi.width * m_fImgage_Scale_X;

73
ConfigModule/include/CheckConfigDefine.h
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@ -937,68 +937,23 @@ struct Function_Image_Align
// 把手区域最大数量（参数里最多可画4个把手区域）
#define HANDLE_REGION_MAX_NUM 4
// 把手缺失判定参数：
// 判定标准：参数里非空的"把手区域"附近必须存在一个凸起，且凸起宽高与区域宽高相近
// （比值范围见 ImgCheckAnalysisy 里的 HANDLE_SIZE_MIN_RATIO ~ HANDLE_SIZE_MAX_RATIO）
// 面积/灰阶等参数保留开关，后续需要时再启用
struct Handle_Check_Param
{
bool bOpen; // 是否检测把手缺失（false 时不做把手判定，也不报 NG）
// 默认关闭，由 "Support_QX_Detect" 检测项开启时置为 true（可用 handle_disabled 单独关闭）
bool bJudgeFill; // 是否用"类矩形块"填充率判定
float fFillMin; // 填充率下限
bool bJudgeArea; // 预留：凸起面积判定
float fAreaMin;
float fAreaMax;
bool bJudgeGray; // 预留：凸起与背景灰度差判定
float fGrayMin;
float fGrayMax;
Handle_Check_Param()
{
Init();
}
void Init()
{
bOpen = false;
bJudgeFill = true;
fFillMin = 0.75f;
bJudgeArea = false;
fAreaMin = 0;
fAreaMax = 0;
bJudgeGray = false;
fGrayMin = 0;
fGrayMax = 0;
}
void copy(Handle_Check_Param tem)
{
// 全为基本类型，直接赋值（避免后续加字段时漏拷）
*this = tem;
}
std::string GetInfo(std::string str)
{
char buffer[256];
sprintf(buffer, "%s>>bOpen %d fill[%d %0.2f] area[%d %0.0f %0.0f] gray[%d %0.0f %0.0f]\n",
str.c_str(), bOpen, bJudgeFill, fFillMin,
bJudgeArea, fAreaMin, fAreaMax, bJudgeGray, fGrayMin, fGrayMax);
std::string str123 = buffer;
return str123;
}
};
// 支架检测
struct Function_Support_Det
{
bool bOpen; // 是否开启
// 支架参数
bool bDetSupport;
std::vector<cv::Point> supportRegion;
cv::RotatedRect supportRect;
float x_offset;
float y_offset;
float r_offset;
// 把手区域（最多 HANDLE_REGION_MAX_NUM 个，只保存非空的；区域宽高用于把手卡控）
bool bDetHandle; // 把手缺失检测开关
std::vector<std::vector<cv::Point>> handleRegions;
std::vector<cv::Rect> handleBoxes;
Handle_Check_Param handleParam; // 把手缺失判定参数
// 标签参数
bool bDetTag;
Function_Support_Det ()
{
@ -1008,40 +963,42 @@ struct Function_Support_Det
void Init()
{
bOpen = false;
bDetSupport = false;
supportRegion.clear();
supportRect = cv::RotatedRect();
x_offset = 0;
y_offset = 0;
r_offset = 0;
bDetHandle = false;
handleRegions.clear();
handleBoxes.clear();
handleParam.Init();
bDetTag = false;
}
void copy(Function_Support_Det tem)
{
this->bOpen = tem.bOpen;
this->bDetSupport = tem.bDetSupport;
this->supportRegion.assign(tem.supportRegion.begin(), tem.supportRegion.end());
this->supportRect = tem.supportRect;
this->x_offset = tem.x_offset;
this->y_offset = tem.y_offset;
this->r_offset = tem.r_offset;
this->bDetHandle = tem.bDetHandle;
this->handleRegions.assign(tem.handleRegions.begin(), tem.handleRegions.end());
this->handleBoxes.assign(tem.handleBoxes.begin(), tem.handleBoxes.end());
this->handleParam.copy(tem.handleParam);
this->bDetTag = tem.bDetTag;
}
void print(std::string str)
{
printf("%s>>bOpen %d x_offset %f y_offset %f r_offset %f handleRegion num %ld\n", str.c_str(),
bOpen, x_offset, y_offset, r_offset, handleRegions.size());
printf("%s", handleParam.GetInfo("handleParam").c_str());
printf("%s>>bOpen %d bDetSupport %d bDetHandle %d bDetTag %d x_offset %f y_offset %f r_offset %f handleRegion num %ld\n",
str.c_str(), bOpen, bDetSupport, bDetHandle, bDetTag, x_offset, y_offset, r_offset, handleRegions.size());
}
std::string GetInfo(std::string str)
{
char buffer[256];
sprintf(buffer, "%s>>bOpen %d x_offset %f y_offset %f r_offset %f handleRegion num %ld\n", str.c_str(),
bOpen, x_offset, y_offset, r_offset, handleRegions.size());
sprintf(buffer, "%s>>bOpen %d bDetSupport %d bDetHandle %d bDetTag %d x_offset %f y_offset %f r_offset %f handleRegion num %ld\n",
str.c_str(), bOpen, bDetSupport, bDetHandle, bDetTag, x_offset, y_offset, r_offset, handleRegions.size());
std::string str123 = buffer;
str123 += handleParam.GetInfo("handleParam");
return str123;
}

78
ConfigModule/src/JsonConfig.cpp
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@ -421,6 +421,11 @@ int ChannelFuntonConfigJson::GetFunction(Json::Value value, CheckFunction &funct
{
// 支架参数
{
if (value_f["form"]["support_param"]["bDetSupport"])
{
function.f_supportDet.bDetSupport = value_f["form"]["support_param"]["bDetSupport"].asBool();
}
auto value_region = value_f["form"]["support_param"]["support_region"];
if (value_region.isArray())
{
@ -437,22 +442,26 @@ int ChannelFuntonConfigJson::GetFunction(Json::Value value, CheckFunction &funct
function.f_supportDet.supportRect = minAreaRect(function.f_supportDet.supportRegion);
}
}
}
if (value_f["form"]["support_param"]["x_offset"])
{
function.f_supportDet.x_offset = value_f["form"]["support_param"]["x_offset"].asFloat();
}
if (value_f["form"]["support_param"]["y_offset"])
{
function.f_supportDet.y_offset = value_f["form"]["support_param"]["y_offset"].asFloat();
}
if (value_f["form"]["support_param"]["r_offset"])
{
function.f_supportDet.r_offset = value_f["form"]["support_param"]["r_offset"].asFloat();
}
if (value_f["form"]["support_param"]["x_offset"])
{
function.f_supportDet.x_offset = value_f["form"]["support_param"]["x_offset"].asFloat();
}
if (value_f["form"]["support_param"]["y_offset"])
{
function.f_supportDet.y_offset = value_f["form"]["support_param"]["y_offset"].asFloat();
}
if (value_f["form"]["support_param"]["r_offset"])
{
function.f_supportDet.r_offset = value_f["form"]["support_param"]["r_offset"].asFloat();
}
}
// 把手参数
{
if (value_f["form"]["handle_param"]["bDetHandle"])
{
function.f_supportDet.bDetHandle = value_f["form"]["handle_param"]["bDetHandle"].asBool();
}
auto handle_p = value_f["form"]["handle_param"];
bool bNewFormat = handle_p["handle_region1"].isArray();
for (int idx = 0; idx < HANDLE_REGION_MAX_NUM; idx++)
@ -493,48 +502,11 @@ int ChannelFuntonConfigJson::GetFunction(Json::Value value, CheckFunction &funct
function.f_supportDet.handleBoxes.push_back(cv::boundingRect(region));
}
}
// 把手缺失判定参数
// 标签参数
{
auto handle_p = value_f["form"]["handle_param"];
Handle_Check_Param &handleParam = function.f_supportDet.handleParam;
// "Support_QX_Detect" 检测项开启时，默认做把手缺失检测
handleParam.bOpen = true;
if (handle_p["handle_disabled"].isBool())
{
handleParam.bOpen = !handle_p["handle_disabled"].asBool();
}
if (handle_p["handle_fill_disabled"].isBool())
{
handleParam.bJudgeFill = !handle_p["handle_fill_disabled"].asBool();
}
if (handle_p["handle_fill_min"].isNumeric())
{
handleParam.fFillMin = handle_p["handle_fill_min"].asFloat();
}
if (handle_p["handle_area_disabled"].isBool())
{
handleParam.bJudgeArea = !handle_p["handle_area_disabled"].asBool();
}
if (handle_p["handle_area_min"].isNumeric())
{
handleParam.fAreaMin = handle_p["handle_area_min"].asFloat();
}
if (handle_p["handle_area_max"].isNumeric())
{
handleParam.fAreaMax = handle_p["handle_area_max"].asFloat();
}
if (handle_p["handle_gray_disabled"].isBool())
{
handleParam.bJudgeGray = !handle_p["handle_gray_disabled"].asBool();
}
if (handle_p["handle_gray_min"].isNumeric())
{
handleParam.fGrayMin = handle_p["handle_gray_min"].asFloat();
}
if (handle_p["handle_gray_max"].isNumeric())
if (value_f["form"]["tag_param"]["bDetTag"])
{
handleParam.fGrayMax = handle_p["handle_gray_max"].asFloat();
function.f_supportDet.bDetTag = value_f["form"]["tag_param"]["bDetTag"].asBool();
}
}
}

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