diff --git a/modules/dnn/include/opencv2/dnn/dnn.hpp b/modules/dnn/include/opencv2/dnn/dnn.hpp
index 83a2bbef24..d4a33a4199 100644
--- a/modules/dnn/include/opencv2/dnn/dnn.hpp
+++ b/modules/dnn/include/opencv2/dnn/dnn.hpp
@@ -523,7 +523,7 @@ CV__DNN_INLINE_NS_BEGIN
         virtual void setOutputs(const std::vector<Arg>& outputs) = 0;
         virtual const std::vector<Ptr<OpData> >& prog() const = 0;
         virtual void setProg(const std::vector<Ptr<OpData> >& newprog) = 0;
-https://github.com/opencv/opencv/pull/29018        virtual int opBackend(int opidx) const = 0;
+        virtual int opBackend(int opidx) const = 0;
     };
 
     /** @brief This class allows to create and manipulate comprehensive artificial neural networks.
diff --git a/modules/dnn/src/graph_block_layout.cpp b/modules/dnn/src/graph_block_layout.cpp
index f3d1b0bd86..f304807236 100644
--- a/modules/dnn/src/graph_block_layout.cpp
+++ b/modules/dnn/src/graph_block_layout.cpp
@@ -129,7 +129,7 @@ struct BlockLayoutTransformer
             std::string op_name = layer->type;
             std::string name = layer->name;
             vector<PGraph>* subgraphs = layer->subgraphs();
-\            bool deviceOp = g->opBackend((int)opidx) != DNN_BACKEND_OPENCV;
+            bool deviceOp = g->opBackend((int)opidx) != DNN_BACKEND_OPENCV;
             //std::cout << "name: " << name << ", op_name: " << op_name << ", inp0 layout: " << layoutToString(layouts[inputs[0].idx]) << "\n";
 
             if (subgraphs) {