MLECO-3174: Minor refactoring to implemented use case APIS

Looks large but it is mainly just many small adjustments
Removed the inference runner code as it wasn't used
Fixes to doc strings
Consistent naming e.g. Asr/Kws instead of ASR/KWS

Signed-off-by: Richard Burton <richard.burton@arm.com>
Change-Id: I43b620b5c51d7910a29a63b509ac4d8a82c3a8fc

1 files changed, 22 insertions, 16 deletions

diff --git a/source/use_case/kws/include/KwsProcessing.hpp b/source/use_case/kws/include/KwsProcessing.hpp
index ddf38c1..d3de3b3 100644
--- a/source/use_case/kws/include/KwsProcessing.hpp
+++ b/source/use_case/kws/include/KwsProcessing.hpp
@@ -33,18 +33,21 @@ namespace app {
      *          Implements methods declared by BasePreProcess and anything else needed
      *          to populate input tensors ready for inference.
      */
-    class KWSPreProcess : public BasePreProcess {
+    class KwsPreProcess : public BasePreProcess {
 
     public:
         /**
          * @brief       Constructor
-         * @param[in]   model             Pointer to the KWS Model object.
-         * @param[in]   numFeatures       How many MFCC features to use.
-         * @param[in]   mfccFrameLength   Number of audio samples used to calculate one set of MFCC values when
-         *                                sliding a window through the audio sample.
-         * @param[in]   mfccFrameStride   Number of audio samples between consecutive windows.
+         * @param[in]   inputTensor        Pointer to the TFLite Micro input Tensor.
+         * @param[in]   numFeatures        How many MFCC features to use.
+         * @param[in]   numFeatureFrames   Number of MFCC vectors that need to be calculated
+         *                                 for an inference.
+         * @param[in]   mfccFrameLength    Number of audio samples used to calculate one set of MFCC values when
+         *                                 sliding a window through the audio sample.
+         * @param[in]   mfccFrameStride    Number of audio samples between consecutive windows.
          **/
-        explicit KWSPreProcess(Model* model, size_t numFeatures, int mfccFrameLength, int mfccFrameStride);
+        explicit KwsPreProcess(TfLiteTensor* inputTensor, size_t numFeatures, size_t numFeatureFrames,
+                               int mfccFrameLength, int mfccFrameStride);
 
         /**
          * @brief       Should perform pre-processing of 'raw' input audio data and load it into
@@ -60,8 +63,10 @@ namespace app {
         size_t m_audioDataStride;       /* Amount of audio to stride across if doing >1 inference in longer clips. */
 
     private:
+        TfLiteTensor* m_inputTensor;    /* Model input tensor. */
         const int m_mfccFrameLength;
         const int m_mfccFrameStride;
+        const size_t m_numMfccFrames;   /* How many sets of m_numMfccFeats. */
 
         audio::MicroNetKwsMFCC m_mfcc;
         audio::SlidingWindow<const int16_t> m_mfccSlidingWindow;
@@ -99,22 +104,23 @@ namespace app {
      *          Implements methods declared by BasePostProcess and anything else needed
      *          to populate result vector.
      */
-    class KWSPostProcess : public BasePostProcess {
+    class KwsPostProcess : public BasePostProcess {
 
     private:
-        Classifier& m_kwsClassifier;
-        const std::vector<std::string>& m_labels;
-        std::vector<ClassificationResult>& m_results;
+        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. */
 
     public:
         /**
          * @brief           Constructor
-         * @param[in]       classifier   Classifier object used to get top N results from classification.
-         * @param[in]       model        Pointer to the KWS Model object.
-         * @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.
+         * @param[in]       outputTensor   Pointer to the TFLite Micro output Tensor.
+         * @param[in]       classifier     Classifier object used to get top N results from classification.
+         * @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(Classifier& classifier, Model* model,
+        KwsPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
                        const std::vector<std::string>& labels,
                        std::vector<ClassificationResult>& results);