Apply suggestions from code review

Co-authored-by: Zlobin Vladimir <[email protected]>

Author: ivikhrev

demos/classification_benchmark_demo/cpp/grid_mat.hpp

@@ -101,14 +101,14 @@ class GridMat {
         cv::Scalar textColor;
         switch (predictionResul) {
             case PredictionResult::Correct:
-                textColor = cv::Scalar(75, 255, 75);
-                break;  // green
+                textColor = cv::Scalar(75, 255, 75);  // green
+                break;
             case PredictionResult::Incorrect:
-                textColor = cv::Scalar(50, 50, 255);
-                break;  // red
+                textColor = cv::Scalar(50, 50, 255);  // red
+                break;
             case PredictionResult::Unknown:
-                textColor = cv::Scalar(200, 10, 10);
-                break;  // blue
+                textColor = cv::Scalar(200, 10, 10);  // blue
+                break;
             default:
                 throw std::runtime_error("Undefined type of prediction result");
         }
@@ -150,6 +150,4 @@ class GridMat {
     cv::Size testMessageSize;
 };
 
-// defenition of the static member needed to remove clang build error
-// https://stackoverflow.com/questions/8016780/undefined-reference-to-static-constexpr-char
 constexpr const char GridMat::testMessage[];

demos/common/cpp/models/src/detection_model_faceboxes.cpp

@@ -225,22 +225,18 @@ std::vector<ModelFaceBoxes::Anchor> filterBoxes(const ov::Tensor& boxesTensor,
 }
 
 std::unique_ptr<ResultBase> ModelFaceBoxes::postprocess(InferenceResult& infResult) {
-    // --------------------------- Filter scores and get valid indices for bounding
-    // boxes----------------------------------
+    // Filter scores and get valid indices for bounding boxes
     const auto scoresTensor = infResult.outputsData[outputsNames[1]];
     const auto scores = filterScores(scoresTensor, confidenceThreshold);
 
-    // --------------------------- Filter bounding boxes on indices
-    // -------------------------------------------------------
+    // Filter bounding boxes on indices
     auto boxesTensor = infResult.outputsData[outputsNames[0]];
     std::vector<Anchor> boxes = filterBoxes(boxesTensor, anchors, scores.first, variance);
 
-    // --------------------------- Apply Non-maximum Suppression
-    // ----------------------------------------------------------
+    // Apply Non-maximum Suppression
     const std::vector<int> keep = nms(boxes, scores.second, boxIOUThreshold);
 
-    // --------------------------- Create detection result objects
-    // --------------------------------------------------------
+    // Create detection result objects
     DetectionResult* result = new DetectionResult(infResult.frameId, infResult.metaData);
     const auto imgWidth = infResult.internalModelData->asRef<InternalImageModelData>().inputImgWidth;
     const auto imgHeight = infResult.internalModelData->asRef<InternalImageModelData>().inputImgHeight;