1 files changed, 1 insertions, 84 deletions

diff --git a/source/use_case/asr/src/MainLoop.cc b/source/use_case/asr/src/MainLoop.cc
index 51b0b18..a1a9540 100644
--- a/source/use_case/asr/src/MainLoop.cc
+++ b/source/use_case/asr/src/MainLoop.cc
@@ -14,15 +14,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-#include "hal.h"                     /* Brings in platform definitions. */
 #include "Labels.hpp"                /* For label strings. */
 #include "UseCaseHandler.hpp"        /* Handlers for different user options. */
 #include "Wav2LetterModel.hpp"       /* Model class for running inference. */
 #include "UseCaseCommonUtils.hpp"    /* Utils functions. */
 #include "AsrClassifier.hpp"         /* Classifier. */
 #include "InputFiles.hpp"            /* Generated audio clip header. */
-#include "Wav2LetterPreprocess.hpp"  /* Pre-processing class. */
-#include "Wav2LetterPostprocess.hpp" /* Post-processing class. */
 #include "log_macros.h"
 
 enum opcodes
@@ -48,23 +45,9 @@ static void DisplayMenu()
     fflush(stdout);
 }
 
-/** @brief Verify input and output tensor are of certain min dimensions. */
+/** @brief   Verify input and output tensor are of certain min dimensions. */
 static bool VerifyTensorDimensions(const arm::app::Model& model);
 
-/** @brief Gets the number of MFCC features for a single window. */
-static uint32_t GetNumMfccFeatures(const arm::app::Model& model);
-
-/** @brief Gets the number of MFCC feature vectors to be computed. */
-static uint32_t GetNumMfccFeatureVectors(const arm::app::Model& model);
-
-/** @brief Gets the output context length (left and right) for post-processing. */
-static uint32_t GetOutputContextLen(const arm::app::Model& model,
-                                    uint32_t inputCtxLen);
-
-/** @brief Gets the output inner length for post-processing. */
-static uint32_t GetOutputInnerLen(const arm::app::Model& model,
-                                  uint32_t outputCtxLen);
-
 void main_loop()
 {
     arm::app::Wav2LetterModel model;  /* Model wrapper object. */
@@ -78,21 +61,6 @@ void main_loop()
         return;
     }
 
-    /* Initialise pre-processing. */
-    arm::app::audio::asr::Preprocess prep(
-                                GetNumMfccFeatures(model),
-                                g_FrameLength,
-                                g_FrameStride,
-                                GetNumMfccFeatureVectors(model));
-
-    /* Initialise post-processing. */
-    const uint32_t outputCtxLen = GetOutputContextLen(model, g_ctxLen);
-    const uint32_t blankTokenIdx = 28;
-    arm::app::audio::asr::Postprocess postp(
-                                outputCtxLen,
-                                GetOutputInnerLen(model, outputCtxLen),
-                                blankTokenIdx);
-
     /* Instantiate application context. */
     arm::app::ApplicationContext caseContext;
     std::vector <std::string> labels;
@@ -109,8 +77,6 @@ void main_loop()
     caseContext.Set<uint32_t>("ctxLen", g_ctxLen);  /* Left and right context length (MFCC feat vectors). */
     caseContext.Set<const std::vector <std::string>&>("labels", labels);
     caseContext.Set<arm::app::AsrClassifier&>("classifier", classifier);
-    caseContext.Set<arm::app::audio::asr::Preprocess&>("preprocess", prep);
-    caseContext.Set<arm::app::audio::asr::Postprocess&>("postprocess", postp);
 
     bool executionSuccessful = true;
     constexpr bool bUseMenu = NUMBER_OF_FILES > 1 ? true : false;
@@ -184,52 +150,3 @@ static bool VerifyTensorDimensions(const arm::app::Model& model)
 
     return true;
 }
-
-static uint32_t GetNumMfccFeatures(const arm::app::Model& model)
-{
-    TfLiteTensor* inputTensor = model.GetInputTensor(0);
-    const int inputCols = inputTensor->dims->data[arm::app::Wav2LetterModel::ms_inputColsIdx];
-    if (0 != inputCols % 3) {
-        printf_err("Number of input columns is not a multiple of 3\n");
-    }
-    return std::max(inputCols/3, 0);
-}
-
-static uint32_t GetNumMfccFeatureVectors(const arm::app::Model& model)
-{
-    TfLiteTensor* inputTensor = model.GetInputTensor(0);
-    const int inputRows = inputTensor->dims->data[arm::app::Wav2LetterModel::ms_inputRowsIdx];
-    return std::max(inputRows, 0);
-}
-
-static uint32_t GetOutputContextLen(const arm::app::Model& model, const uint32_t inputCtxLen)
-{
-    const uint32_t inputRows = GetNumMfccFeatureVectors(model);
-    const uint32_t inputInnerLen = inputRows - (2 * inputCtxLen);
-    constexpr uint32_t ms_outputRowsIdx = arm::app::Wav2LetterModel::ms_outputRowsIdx;
-
-    /* Check to make sure that the input tensor supports the above
-     * context and inner lengths. */
-    if (inputRows <= 2 * inputCtxLen || inputRows <= inputInnerLen) {
-        printf_err("Input rows not compatible with ctx of %" PRIu32 "\n",
-            inputCtxLen);
-        return 0;
-    }
-
-    TfLiteTensor* outputTensor = model.GetOutputTensor(0);
-    const uint32_t outputRows = std::max(outputTensor->dims->data[ms_outputRowsIdx], 0);
-
-    const float tensorColRatio = static_cast<float>(inputRows)/
-                                     static_cast<float>(outputRows);
-
-    return std::round(static_cast<float>(inputCtxLen)/tensorColRatio);
-}
-
-static uint32_t GetOutputInnerLen(const arm::app::Model& model,
-                                  const uint32_t outputCtxLen)
-{
-    constexpr uint32_t ms_outputRowsIdx = arm::app::Wav2LetterModel::ms_outputRowsIdx;
-    TfLiteTensor* outputTensor = model.GetOutputTensor(0);
-    const uint32_t outputRows = std::max(outputTensor->dims->data[ms_outputRowsIdx], 0);
-    return (outputRows - (2 * outputCtxLen));
-}