fixed warns unused vars, init order, signed/unsigned cmp (#3227)

Author: vladimir-dudnik

demos/gesture_recognition_demo/cpp_gapi/src/tracker.cpp

@@ -49,15 +49,15 @@ void Tracker::solveAssignmentProblem(
     cv::Mat dissimilarity;
     computeDissimilarityMatrix(track_ids, detections, &dissimilarity);
 
-    auto res = KuhnMunkres().Solve(dissimilarity);
+    std::vector<int> res = KuhnMunkres().Solve(dissimilarity);
 
     for (size_t i = 0; i < detections.size(); i++) {
         unmatched_detections->insert(i);
     }
 
     size_t i = 0;
-    for (auto id : track_ids) {
-        if (res[i] < detections.size()) {
+    for (size_t id : track_ids) {
+        if (res[i] < (int)detections.size()) {
             matches->emplace(id, res[i], 1 - dissimilarity.at<float>(i, res[i]));
         } else {
             unmatched_tracks->insert(id);
@@ -67,7 +67,8 @@ void Tracker::solveAssignmentProblem(
 }
 
 bool Tracker::eraseTrackIfBBoxIsOutOfFrame(size_t track_id) {
-    if (tracks_.find(track_id) == tracks_.end()) return true;
+    if (tracks_.find(track_id) == tracks_.end())
+        return true;
     auto c = center(tracks_.at(track_id).back().rect);
     if (frame_size_ != cv::Size() &&
             (c.x < 0 || c.y < 0 || c.x > frame_size_.width ||

demos/pedestrian_tracker_demo/cpp/src/tracker.cpp

@@ -237,15 +237,15 @@ void PedestrianTracker::SolveAssignmentProblem(
     ComputeDissimilarityMatrix(track_ids, detections, descriptors,
                                &dissimilarity);
 
-    auto res = KuhnMunkres().Solve(dissimilarity);
+    std::vector<int> res = KuhnMunkres().Solve(dissimilarity);
 
     for (size_t i = 0; i < detections.size(); i++) {
         unmatched_detections->insert(i);
     }
 
     size_t i = 0;
-    for (auto id : track_ids) {
-        if (res[i] < detections.size()) {
+    for (size_t id : track_ids) {
+        if (res[i] < (int)detections.size()) {
             matches->emplace(id, res[i], 1 - dissimilarity.at<float>(i, res[i]));
         } else {
             unmatched_tracks->insert(id);

demos/smart_classroom_demo/cpp/src/tracker.cpp

@@ -67,15 +67,15 @@ void Tracker::SolveAssignmentProblem(
     cv::Mat dissimilarity;
     ComputeDissimilarityMatrix(track_ids, detections, &dissimilarity);
 
-    auto res = KuhnMunkres().Solve(dissimilarity);
+    std::vector<int> res = KuhnMunkres().Solve(dissimilarity);
 
     for (size_t i = 0; i < detections.size(); i++) {
         unmatched_detections->insert(i);
     }
 
     size_t i = 0;
-    for (auto id : track_ids) {
-        if (res[i] < detections.size()) {
+    for (size_t id : track_ids) {
+        if (res[i] < (int)detections.size()) {
             matches->emplace(id, res[i], 1 - dissimilarity.at<float>(i, res[i]));
         } else {
             unmatched_tracks->insert(id);

demos/text_detection_demo/cpp/include/cnn.hpp

@@ -25,16 +25,16 @@ class Cnn {
     const cv::Size& input_size() const { return m_input_size; }
 
 protected:
-    int m_channels;
-    cv::Size m_input_size;
-    cv::Size m_new_input_resolution;
     const std::string m_modelPath;
     const std::string m_modelType;
     const std::string m_deviceName;
+    ov::Core& m_core;
+    cv::Size m_new_input_resolution;
+    int m_channels;
+    cv::Size m_input_size;
     std::string m_input_name;
     std::vector<std::string> m_output_names;
     ov::Layout m_modelLayout;
-    ov::Core& m_core;
     ov::InferRequest m_infer_request;
     std::shared_ptr<ov::Model> m_model;
 

demos/text_detection_demo/cpp/main.cpp

@@ -254,8 +254,6 @@ int main(int argc, char* argv[]) {
         cv::Size graphSize{static_cast<int>(image.cols / 4), 60};
         Presenter presenter(FLAGS_u, image.rows - graphSize.height - 10, graphSize);
 
-        uint32_t framesProcessed = 0;
-
         do {
             cv::Mat demoImage = image.clone();
 

demos/text_detection_demo/cpp/src/cnn.cpp

@@ -16,7 +16,7 @@ Cnn::Cnn(
     ov::Core& core, const cv::Size& new_input_resolution) :
     m_modelPath(modelPath), m_modelType(modelType), m_deviceName(deviceName),
     m_core(core), m_new_input_resolution(new_input_resolution),
-    m_time_elapsed(0), m_ncalls(0)
+    m_channels(0), m_time_elapsed(0), m_ncalls(0)
 {
     slog::info << "Reading model: " << m_modelPath << slog::endl;
     m_model = m_core.read_model(m_modelPath);

demos/text_detection_demo/cpp/src/text_recognition.cpp

@@ -277,7 +277,6 @@ std::map<std::string, ov::runtime::Tensor> TextRecognizer::Infer(const cv::Mat&
         const float* output_data_decoder = m_infer_request_decoder.get_tensor(m_out_dec_symbol_name).data<float>();
 
         auto max_elem_vector = std::max_element(output_data_decoder, output_data_decoder + num_classes);
-        float a = *max_elem_vector;
         auto argmax = static_cast<size_t>(std::distance(output_data_decoder, max_elem_vector));
         for (size_t i = 0; i < num_classes; i++)
             data_targets[num_decoder * num_classes + i] = output_data_decoder[i];