Clean up config retrievals using get_from_any_maps

Author: RHeckerIntel

src/cpp/include/tasks/detection/ssd.h

@@ -9,6 +9,7 @@
 
 #include "adapters/inference_adapter.h"
 #include "tasks/results.h"
+#include "utils/config.h"
 #include "utils/preprocessing.h"
 
 enum SSDOutputMode { single, multi };
@@ -29,20 +30,8 @@ class SSD {
 
     SSD(std::shared_ptr<InferenceAdapter> adapter, cv::Size input_shape) : adapter(adapter), input_shape(input_shape) {
         auto config = adapter->getModelConfig();
-        {
-            auto iter = config.find("labels");
-            if (iter != config.end()) {
-                labels = iter->second.as<std::vector<std::string>>();
-            } else {
-                std::cout << "could not find labels from model config" << std::endl;
-            }
-        }
-        {
-            auto iter = config.find("confidence_threshold");
-            if (iter != config.end()) {
-                confidence_threshold = iter->second.as<float>();
-            }
-        }
+        labels = utils::get_from_any_maps("labels", config, {}, labels);
+        confidence_threshold = utils::get_from_any_maps("confidence_threshold", config, {}, confidence_threshold);
     }
     std::map<std::string, ov::Tensor> preprocess(cv::Mat);
     DetectionResult postprocess(InferenceResult& infResult);

src/cpp/include/tasks/instance_segmentation.h

@@ -10,6 +10,7 @@
 
 #include "adapters/inference_adapter.h"
 #include "tasks/results.h"
+#include "utils/config.h"
 #include "utils/vision_pipeline.h"
 
 class InstanceSegmentation {
@@ -30,20 +31,10 @@ class InstanceSegmentation {
             });
 
         auto config = adapter->getModelConfig();
-        auto iter = config.find("labels");
-        if (iter != config.end()) {
-            labels = iter->second.as<std::vector<std::string>>();
-        } else {
-            std::cout << "could not find labels from model config" << std::endl;
-        }
-
-        {
-            auto iter = config.find("confidence_threshold");
-            if (iter != config.end()) {
-                confidence_threshold = iter->second.as<float>();
-            }
-        }
+        labels = utils::get_from_any_maps("labels", config, {}, labels);
+        confidence_threshold = utils::get_from_any_maps("confidence_threshold", config, {}, confidence_threshold);
     }
+
     static cv::Size serialize(std::shared_ptr<ov::Model>& ov_model);
     static InstanceSegmentation load(const std::string& model_path);
 

src/cpp/include/tasks/semantic_segmentation.h

@@ -9,6 +9,7 @@
 
 #include "adapters/inference_adapter.h"
 #include "tasks/results.h"
+#include "utils/config.h"
 #include "utils/preprocessing.h"
 #include "utils/vision_pipeline.h"
 
@@ -27,26 +28,9 @@ class SemanticSegmentation {
             });
 
         auto config = adapter->getModelConfig();
-        auto iter = config.find("labels");
-        if (iter != config.end()) {
-            labels = iter->second.as<std::vector<std::string>>();
-        } else {
-            std::cout << "could not find labels from model config" << std::endl;
-        }
-
-        {
-            auto iter = config.find("soft_threshold");
-            if (iter != config.end()) {
-                soft_threshold = iter->second.as<float>();
-            }
-        }
-
-        {
-            auto iter = config.find("blur_strength");
-            if (iter != config.end()) {
-                blur_strength = iter->second.as<int>();
-            }
-        }
+        labels = utils::get_from_any_maps("labels", config, {}, labels);
+        soft_threshold = utils::get_from_any_maps("soft_threshold", config, {}, soft_threshold);
+        blur_strength = utils::get_from_any_maps("blur_strength", config, {}, blur_strength);
     }
 
     static cv::Size serialize(std::shared_ptr<ov::Model>& ov_model);

src/cpp/src/tasks/detection/ssd.cpp

@@ -148,15 +148,6 @@ void SSD::prepareMultipleOutputs(std::shared_ptr<ov::Model> ov_model) {
     for (auto& name : output_names) {
         std::cout << "output name: " << name << std::endl;
     }
-
-    // ov::preprocess::PrePostProcessor ppp(ov_model);
-
-    // for (const auto& output_name : output_names) {
-    //     if (output_name != "labels") { //TODO: Discover why this isnt needed in original?
-    //         ppp.output(output_name).tensor().set_element_type(ov::element::f32);
-    //     }
-    // }
-    // ov_model = ppp.build();
 }
 
 std::vector<std::string> SSD::filterOutXai(const std::vector<std::string>& names) {