case eClassifier:
        {
            TensorflowClassifier *c = static_cast<TensorflowClassifier*>(m_cnn);
            C2DTrackingsHistoryData* t = static_cast<C2DTrackingsHistoryData*>
                        (current->dataSet()[IHistoryData::et2DTrackings].get());
            C2DTrackings tracks = t->get2DTrackings();
            std::cout << "!!!!name!!!! : " << m_cnn->getName() <<  " " << m_cnn->getInputHeight() << " " << m_cnn->getInputWidth() << std::endl;
            std::cout << "!!!!tracks!!!! : " << tracks.size() << std::endl;
            //std::vector<cv::Mat> class_imgs;

            cv::Mat cl_img;
            std::vector<int> classes_indices;
            for (const S2DTracking& tr: tracks) {
                if (tr.label != "Sign") {
                    std::cout << "!!!!OUTPUT!!!! : " << tr.label << std::endl;
                    continue;
                }
                const float x = tr.left * img.cols;
                const float y = tr.top * img.rows;
                const float w = tr.width * img.cols;
                const float h = tr.height * img.rows;
                cl_img = img(cv::Rect(x, y, w, h));
                c->inference({cl_img});
                classes_indices.push_back(c->getClassesOutputAsIndices()[0]);
                //class_imgs.push_back(cl_img);
            }

//            if(!class_imgs.size()) {
//                return true;
//            }
            //c->inference(class_imgs);

            if (!c) {
                LOG_ERROR("Empty classification model");
                return false;
            }

            //auto classes_indices = c->getClassesOutputAsIndices();

//            if (classes_indices.empty()) {
//                LOG_ERROR("Empty results");
//                return false;
//            }

            auto labels = c->getLabelNames();

            for (auto l: classes_indices) {
                std::cout << "!!!!OUTPUT!!!! : " << c->getLabelNames()[l] << std::endl;
            }

            current->dataSet()[IHistoryData::etClassificationData] =
                    IHistoryDataPtr(new ClassificationHistoryData(classes_indices, labels));

        } break;