MLECO-3164: Additional refactoring of KWS API

Part 1
* Add KwsClassifier
* KwsPostProcess can now be told to average results
* Averaging is handlded by KwsClassifier
* Current sliding window index is now an argument of DoPreProcess

Change-Id: I07626da595ad1cbd982e8366f0d1bb56d1040459
diff --git a/source/application/api/common/source/Classifier.cc b/source/application/api/common/source/Classifier.cc
index 6fabebe..1b5fc64 100644
--- a/source/application/api/common/source/Classifier.cc
+++ b/source/application/api/common/source/Classifier.cc
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * Copyright (c) 2021-2022 Arm Limited. All rights reserved.
  * SPDX-License-Identifier: Apache-2.0
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
@@ -31,10 +31,9 @@
 namespace app {
 
     void Classifier::SetVectorResults(std::set<std::pair<float, uint32_t>>& topNSet,
-                          std::vector<ClassificationResult>& vecResults,
-                          const std::vector <std::string>& labels)
+            std::vector<ClassificationResult>& vecResults,
+            const std::vector <std::string>& labels)
     {
-
         /* Reset the iterator to the largest element - use reverse iterator. */
 
         auto topNIter = topNSet.rbegin();
@@ -46,11 +45,9 @@
     }
 
     bool Classifier::GetTopNResults(const std::vector<float>& tensor,
-                                    std::vector<ClassificationResult>& vecResults,
-                                    uint32_t topNCount,
-                                    const std::vector <std::string>& labels)
+            std::vector<ClassificationResult>& vecResults,
+            uint32_t topNCount, const std::vector <std::string>& labels)
     {
-
         std::set<std::pair<float , uint32_t>> sortedSet;
 
         /* NOTE: inputVec's size verification against labels should be
@@ -80,12 +77,9 @@
         return true;
     }
 
-    bool  Classifier::GetClassificationResults(
-        TfLiteTensor* outputTensor,
-        std::vector<ClassificationResult>& vecResults,
-        const std::vector <std::string>& labels,
-        uint32_t topNCount,
-        bool useSoftmax)
+    bool Classifier::GetClassificationResults(TfLiteTensor* outputTensor,
+            std::vector<ClassificationResult>& vecResults, const std::vector <std::string>& labels,
+            uint32_t topNCount, bool useSoftmax)
     {
         if (outputTensor == nullptr) {
             printf_err("Output vector is null pointer.\n");