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

Author: akorobeinikov

demos/common/cpp/models/include/models/detection_model_yolov3_onnx.h

@@ -22,7 +22,6 @@
 #include <openvino/openvino.hpp>
 
 #include "models/detection_model.h"
-#include "utils/image_utils.h"
 
 class ModelYoloV3ONNX: public DetectionModel {
 public:

demos/common/cpp/models/include/models/detection_model_yolox.h

@@ -15,19 +15,13 @@
 */
 
 #pragma once
-#include <stddef.h>
-#include <stdint.h>
-
-#include <map>
 #include <memory>
 #include <string>
+#include <vector>
 
-#include <openvino/op/region_yolo.hpp>
 #include <openvino/openvino.hpp>
 
 #include "models/detection_model.h"
-#include "utils/image_utils.h"
-#include "utils/nms.hpp"
 
 class ModelYoloX: public DetectionModel {
 public:

demos/common/cpp/models/src/detection_model_yolov3_onnx.cpp

@@ -76,8 +76,8 @@ void ModelYoloV3ONNX::prepareInputsOutputs(std::shared_ptr<ov::Model>& model) {
     const ov::Layout& infoLayout = getInputLayout(inputs.at(1));
 
     if (infoShape.size() != 2 && infoShape[ov::layout::channels_idx(infoLayout)] != 2) {
-            throw std::logic_error("Expected 2D image info input with 2 channels");
-        }
+        throw std::logic_error("Expected 2D image info input with 2 channels");
+    }
 
     ppp.input(infoInputName).tensor().set_element_type(ov::element::i32);
 
@@ -96,7 +96,7 @@ void ModelYoloV3ONNX::prepareInputsOutputs(std::shared_ptr<ov::Model>& model) {
     for (auto& output : outputs) {
         const ov::Shape& currentShape = output.get_partial_shape().get_max_shape();
         std::string currentName = output.get_any_name();
-        if (currentShape[currentShape.size() - 1] == 3) {
+        if (currentShape.back() == 3) {
             indicesOutputName = currentName;
             ppp.output(currentName).tensor().set_element_type(ov::element::i32);
         } else if (currentShape[2] == 4) {
@@ -106,7 +106,8 @@ void ModelYoloV3ONNX::prepareInputsOutputs(std::shared_ptr<ov::Model>& model) {
             scoresOutputName = currentName;
             ppp.output(currentName).tensor().set_element_type(ov::element::f32);
         } else {
-            throw std::logic_error("Expected shapes [:,:,4], [:,numClasses,:] and [:,3] for outputs");
+            throw std::logic_error("Expected shapes [:,:,4], [:,"
+                + std::to_string(numberOfClasses) + ",:] and [:,3] for outputs");
         }
         outputsNames.push_back(currentName);
     }

demos/common/cpp/models/src/detection_model_yolox.cpp

@@ -102,7 +102,7 @@ void ModelYoloX::prepareGridsAndStrides() {
     for (size_t size_index = 0; size_index < hsizes.size(); ++size_index) {
         for (size_t h_index = 0; h_index < hsizes[size_index]; ++h_index) {
             for (size_t w_index = 0; w_index < wsizes[size_index]; ++w_index) {
-                grids.push_back({w_index, h_index});
+                grids.emplace_back(w_index, h_index);
                 expandedStrides.push_back(strides[size_index]);
             }
         }

demos/common/cpp/models/src/image_model.cpp

@@ -52,7 +52,6 @@ std::shared_ptr<InternalModelData> ImageModel::preprocess(const InputData& input
         }
         img = resizeImageExt(img, width, height, resizeMode, interpolationMode);
     }
-
     request.set_tensor(inputsNames[0], wrapMat2Tensor(img));
     return std::make_shared<InternalImageModelData>(origImg.cols, origImg.rows);
 }