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

3 files changed, 77 insertions, 12 deletions

diff --git a/source/application/api/use_case/kws/include/KwsClassifier.hpp b/source/application/api/use_case/kws/include/KwsClassifier.hpp
new file mode 100644
index 0000000..d050e85
--- /dev/null
+++ b/source/application/api/use_case/kws/include/KwsClassifier.hpp
@@ -0,0 +1,66 @@
+/*
+ * Copyright (c) 2022 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef KWS_CLASSIFIER_HPP
+#define KWS_CLASSIFIER_HPP
+
+#include "ClassificationResult.hpp"
+#include "TensorFlowLiteMicro.hpp"
+#include "Classifier.hpp"
+
+#include <vector>
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   KWS Classifier - a helper class to get certain number of top
+     *          results from the output vector from a classification NN.
+     *          Allows for averaging of previous results.
+     **/
+    class KwsClassifier : public Classifier {
+    public:
+
+        /**
+         * @brief           Gets the top N classification results from the
+         *                  output vector.
+         * @param[in]       outputTensor   Inference output tensor from an NN model.
+         * @param[out]      vecResults     A vector of classification results.
+         *                                 populated by this function.
+         * @param[in]       labels         Labels vector to match classified classes.
+         * @param[in]       topNCount      Number of top classifications to pick. Default is 1.
+         * @param[in]       useSoftmax     Whether Softmax normalisation should be applied to output. Default is false.
+         * @param[in/out]   resultHistory  History of previous classification results to be updated.
+         * @return          true if successful, false otherwise.
+         **/
+         using Classifier::GetClassificationResults;  /* We are overloading not overriding. */
+         bool GetClassificationResults(TfLiteTensor* outputTensor, std::vector<ClassificationResult>& vecResults,
+                 const std::vector <std::string>& labels, uint32_t topNCount,
+                 bool use_softmax, std::vector<std::vector<float>>& resultHistory);
+
+        /**
+         * @brief        Average the given history of results.
+         * @param[in]    resultHistory   The history of results to take on average of.
+         * @param[out]   averageResult   The calculated average.
+         **/
+         static void AveragResults(const std::vector<std::vector<float>>& resultHistory,
+                 std::vector<float>& averageResult);
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* KWS_CLASSIFIER_HPP */
diff --git a/source/application/api/use_case/kws/include/KwsProcessing.hpp b/source/application/api/use_case/kws/include/KwsProcessing.hpp
index 0ede425..e2d3ff9 100644
--- a/source/application/api/use_case/kws/include/KwsProcessing.hpp
+++ b/source/application/api/use_case/kws/include/KwsProcessing.hpp
@@ -19,7 +19,7 @@
 
 #include "AudioUtils.hpp"
 #include "BaseProcessing.hpp"
-#include "Classifier.hpp"
+#include "KwsClassifier.hpp"
 #include "MicroNetKwsMfcc.hpp"
 
 #include <functional>
@@ -55,9 +55,8 @@ namespace app {
          * @param[in]   inputSize  Size of the input data.
          * @return      true if successful, false otherwise.
          **/
-        bool DoPreProcess(const void* input, size_t inputSize) override;
+        bool DoPreProcess(const void* input, size_t inferenceIndex = 0) override;
 
-        size_t m_audioWindowIndex = 0;  /* Index of audio slider, used when caching features in longer clips. */
         size_t m_audioDataWindowSize;   /* Amount of audio needed for 1 inference. */
         size_t m_audioDataStride;       /* Amount of audio to stride across if doing >1 inference in longer clips. */
 
@@ -106,11 +105,11 @@ namespace app {
     class KwsPostProcess : public BasePostProcess {
 
     private:
-        TfLiteTensor* m_outputTensor;                   /* Model output tensor. */
-        Classifier& m_kwsClassifier;                    /* KWS Classifier object. */
-        const std::vector<std::string>& m_labels;       /* KWS Labels. */
-        std::vector<ClassificationResult>& m_results;   /* Results vector for a single inference. */
-
+        TfLiteTensor* m_outputTensor;                      /* Model output tensor. */
+        KwsClassifier& m_kwsClassifier;                    /* KWS Classifier object. */
+        const std::vector<std::string>& m_labels;          /* KWS Labels. */
+        std::vector<ClassificationResult>& m_results;      /* Results vector for a single inference. */
+        std::vector<std::vector<float>> m_resultHistory;   /* Store previous results so they can be averaged. */
     public:
         /**
          * @brief           Constructor
@@ -119,9 +118,9 @@ namespace app {
          * @param[in]       labels         Vector of string labels to identify each output of the model.
          * @param[in/out]   results        Vector of classification results to store decoded outputs.
          **/
-        KwsPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
+        KwsPostProcess(TfLiteTensor* outputTensor, KwsClassifier& classifier,
                        const std::vector<std::string>& labels,
-                       std::vector<ClassificationResult>& results);
+                       std::vector<ClassificationResult>& results, size_t averagingWindowLen = 1);
 
         /**
          * @brief    Should perform post-processing of the result of inference then
diff --git a/source/application/api/use_case/kws/include/KwsResult.hpp b/source/application/api/use_case/kws/include/KwsResult.hpp
index 38f32b4..e0bb868 100644
--- a/source/application/api/use_case/kws/include/KwsResult.hpp
+++ b/source/application/api/use_case/kws/include/KwsResult.hpp
@@ -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");
@@ -47,7 +47,7 @@ namespace kws {
             this->m_inferenceNumber = inferenceIdx;
 
             this->m_resultVec = ResultVec();
-            for (auto & i : resultVec) {
+            for (auto& i : resultVec) {
                 if (i.m_normalisedVal >= this->m_threshold) {
                     this->m_resultVec.emplace_back(i);
                 }