update 优化支架搜边

AlgorithmModule/include/ImageAllResult.h

@@ -64,6 +64,8 @@ public:
     cv::Mat detImg;
     // 裁剪后的彩色检测图(保留原图通道,供裁剪图 _RE_CutImg 输出;灰度源图时为空)
     cv::Mat detColorImg;
+    // 只做"裁剪"、不叠加任何 mask 的检测图(同 detImg 尺寸/坐标系)
+    cv::Mat detImgNoMask;
     // AI 推理的mask图片
     cv::Mat AIMaskImg;
     // 结果图片

ConfigModule/include/CheckConfigDefine.h

@@ -934,9 +934,10 @@ struct Function_Support_Det
 	float r_offset; // 支架旋转偏移阈值（度）：支架旋转矩形长轴(对应左/右边缘)与产品左/右边缘夹角超过该值判偏移；<=0 不判定
 	float support_min_area; // 支架缺失判定：支架面积阈值(单位 mm²)。支架由 Align_Inner 模型(smallmask)检出，支架面积 < 该值判缺失；<=0 不判定
 	// 支架边缘原图精细化（Support_Detect.form.support_param，均可选；仅对 edge_select 选中的边缘生效）：
-	// 沿边缘按步长采样，从边缘向产品内侧逐像素找第一个 255 像素作为新边缘点，再重新拟合边缘线
+	// 沿边缘按步长采样，从边缘向产品内侧逐像素找第一个灰度 >= 阈值的像素作为新边缘点，再重新拟合边缘线
 	float edge_refine_search; // edge_refine_search：最多向内搜索的像素数；<=0=未配置(默认 80)
 	float edge_refine_step;   // edge_refine_step：沿边采样步长(像素，不需要每个点都找)；<=0=未配置(默认 40)
+	float edge_refine_gray;   // edge_refine_gray：边缘点灰度阈值(0~255，灰度 >= 该值视为产品边缘)；<=0=未配置(默认 240)
 	// 支架方向精细化（Support_Detect.form.support_param，均可选）：模型 smallmask 精度低
 	// (1696×800 上采样回原图)，minAreaRect 求支架方向角误差大；改为在原图(detImg)上拟合支架长边求方向角
 	float support_refine_search;   // support_refine_search：取模型支架外接矩形最外侧多少列作为边缘搜索带；<=0=未配置(默认 30)
@@ -982,6 +983,7 @@ struct Function_Support_Det
 		support_min_area = 0;
 		edge_refine_search = 0;
 		edge_refine_step = 0;
+		edge_refine_gray = 0;
 		support_refine_search = 0;
 		support_refine_step = 0;
 		support_refine_segments = 0;
@@ -1016,6 +1018,7 @@ struct Function_Support_Det
 		this->support_min_area = tem.support_min_area;
 		this->edge_refine_search = tem.edge_refine_search;
 		this->edge_refine_step = tem.edge_refine_step;
+		this->edge_refine_gray = tem.edge_refine_gray;
 		this->support_refine_search = tem.support_refine_search;
 		this->support_refine_step = tem.support_refine_step;
 		this->support_refine_segments = tem.support_refine_segments;
@@ -1037,16 +1040,16 @@ struct Function_Support_Det
 	}
 	void print(std::string str)
 	{
-		printf("%s>>bDetSupport %d bDrawSupport %d bUseTraditionEdge %d bDetHandle %d bDetTag %d  x_standard %f y_standard %f  x_offset %f y_offset %f r_offset %f support_min_area %f  edgeRefine[search %.0f step %.0f]  supportRefine[search %.0f step %.0f seg %.0f]  edge num %ld  handleRegion num %ld  handle_diff %f  handleRange[size %.2f~%.2f search %.1f depth %.1f area %.1f margin %.1f(0=自动,<0=默认)]  BQ[area %f energy %f len %f hj %f]\n",
+		printf("%s>>bDetSupport %d bDrawSupport %d bUseTraditionEdge %d bDetHandle %d bDetTag %d  x_standard %f y_standard %f  x_offset %f y_offset %f r_offset %f support_min_area %f  edgeRefine[search %.0f step %.0f gray %.0f]  supportRefine[search %.0f step %.0f seg %.0f]  edge num %ld  handleRegion num %ld  handle_diff %f  handleRange[size %.2f~%.2f search %.1f depth %.1f area %.1f margin %.1f(0=自动,<0=默认)]  BQ[area %f energy %f len %f hj %f]\n",
-			   str.c_str(), bDetSupport, bDrawSupport, bUseTraditionEdge, bDetHandle, bDetTag, x_standard, y_standard, x_offset, y_offset, r_offset, support_min_area, edge_refine_search, edge_refine_step, support_refine_search, support_refine_step, support_refine_segments, edge_select.size(), handleRegions.size(), handle_diff,
+			   str.c_str(), bDetSupport, bDrawSupport, bUseTraditionEdge, bDetHandle, bDetTag, x_standard, y_standard, x_offset, y_offset, r_offset, support_min_area, edge_refine_search, edge_refine_step, edge_refine_gray, support_refine_search, support_refine_step, support_refine_segments, edge_select.size(), handleRegions.size(), handle_diff,
 			   handle_size_min_ratio, handle_size_max_ratio, handle_search_ratio, handle_min_depth_coef, handle_min_area_coef, handle_edge_margin_coef,
 			   BQ_area, BQ_energy, BQ_len, BQ_hj);
 	}
 	std::string GetInfo(std::string str)
 	{
 		char buffer[1024];
-		sprintf(buffer, "%s>>bDetSupport %d bDrawSupport %d bUseTraditionEdge %d bDetHandle %d bDetTag %d  x_standard %f y_standard %f  x_offset %f y_offset %f r_offset %f support_min_area %f  edgeRefine[search %.0f step %.0f]  supportRefine[search %.0f step %.0f seg %.0f]  edge num %ld  handleRegion num %ld  handle_diff %f  handleRange[size %.2f~%.2f search %.1f depth %.1f area %.1f margin %.1f(0=自动,<0=默认)]  BQ[area %f energy %f len %f hj %f]\n",
+		sprintf(buffer, "%s>>bDetSupport %d bDrawSupport %d bUseTraditionEdge %d bDetHandle %d bDetTag %d  x_standard %f y_standard %f  x_offset %f y_offset %f r_offset %f support_min_area %f  edgeRefine[search %.0f step %.0f gray %.0f]  supportRefine[search %.0f step %.0f seg %.0f]  edge num %ld  handleRegion num %ld  handle_diff %f  handleRange[size %.2f~%.2f search %.1f depth %.1f area %.1f margin %.1f(0=自动,<0=默认)]  BQ[area %f energy %f len %f hj %f]\n",
-				str.c_str(), bDetSupport, bDrawSupport, bUseTraditionEdge, bDetHandle, bDetTag, x_standard, y_standard, x_offset, y_offset, r_offset, support_min_area, edge_refine_search, edge_refine_step, support_refine_search, support_refine_step, support_refine_segments, edge_select.size(), handleRegions.size(), handle_diff,
+				str.c_str(), bDetSupport, bDrawSupport, bUseTraditionEdge, bDetHandle, bDetTag, x_standard, y_standard, x_offset, y_offset, r_offset, support_min_area, edge_refine_search, edge_refine_step, edge_refine_gray, support_refine_search, support_refine_step, support_refine_segments, edge_select.size(), handleRegions.size(), handle_diff,
 				handle_size_min_ratio, handle_size_max_ratio, handle_search_ratio, handle_min_depth_coef, handle_min_area_coef, handle_edge_margin_coef,
 				BQ_area, BQ_energy, BQ_len, BQ_hj);
 		std::string str123 = buffer;

ConfigModule/src/JsonConfig.cpp

@@ -962,9 +962,10 @@ int BaseFuntonConfigJson::GetFunction(Json::Value value)
                 _config.supportDet.support_min_area = value_param["support_min_area"].asFloat();
             }
 
-            // 支架边缘原图精细化（可选）：沿边缘采样，从边缘向内找第一个 255 像素作为新边缘点，
+            // 支架边缘原图精细化（可选）：沿边缘采样，从边缘向内找第一个灰度 >= 阈值的像素作为新边缘点，
             //   edge_refine_search：最多向内搜索像素数（未配置默认 80）
             //   edge_refine_step  ：沿边采样步长(像素)（未配置默认 40，不需要每个点都找）
+            //   edge_refine_gray  ：边缘点灰度阈值(0~255，灰度 >= 该值视为产品边缘)（未配置默认 240）
             if (value_param["edge_refine_search"])
             {
                 _config.supportDet.edge_refine_search = value_param["edge_refine_search"].asFloat();
@@ -973,6 +974,10 @@ int BaseFuntonConfigJson::GetFunction(Json::Value value)
             {
                 _config.supportDet.edge_refine_step = value_param["edge_refine_step"].asFloat();
             }
+            if (value_param["edge_refine_gray"])
+            {
+                _config.supportDet.edge_refine_gray = value_param["edge_refine_gray"].asFloat();
+            }
 
             // 支架方向精细化（可选）：模型 smallmask 精度低(1696×800 上采样回原图)，
             //   minAreaRect 求支架方向角误差大，改为在 detImg 灰度原图上拟合支架长边求方向角。