2 files changed, 22 insertions, 33 deletions

diff --git a/source/use_case/vww/src/UseCaseHandler.cc b/source/use_case/vww/src/UseCaseHandler.cc
index 7681f89..267e6c4 100644
--- a/source/use_case/vww/src/UseCaseHandler.cc
+++ b/source/use_case/vww/src/UseCaseHandler.cc
@@ -53,7 +53,7 @@ namespace app {
         }
 
         TfLiteTensor* inputTensor = model.GetInputTensor(0);
-
+        TfLiteTensor* outputTensor = model.GetOutputTensor(0);
         if (!inputTensor->dims) {
             printf_err("Invalid input tensor dims\n");
             return false;
@@ -75,15 +75,13 @@ namespace app {
         const uint32_t displayChannels = 3;
 
         /* Set up pre and post-processing. */
-        VisualWakeWordPreProcess preprocess = VisualWakeWordPreProcess(&model);
+        VisualWakeWordPreProcess preProcess = VisualWakeWordPreProcess(inputTensor);
 
         std::vector<ClassificationResult> results;
-        VisualWakeWordPostProcess postprocess = VisualWakeWordPostProcess(
-                ctx.Get<Classifier&>("classifier"), &model,
+        VisualWakeWordPostProcess postProcess = VisualWakeWordPostProcess(outputTensor,
+                ctx.Get<Classifier&>("classifier"),
                 ctx.Get<std::vector<std::string>&>("labels"), results);
 
-        UseCaseRunner runner = UseCaseRunner(&preprocess, &postprocess, &model);
-
         do {
             hal_lcd_clear(COLOR_BLACK);
 
@@ -115,17 +113,18 @@ namespace app {
                                  inputTensor->bytes : IMAGE_DATA_SIZE;
 
             /* Run the pre-processing, inference and post-processing. */
-            if (!runner.PreProcess(imgSrc, imgSz)) {
+            if (!preProcess.DoPreProcess(imgSrc, imgSz)) {
+                printf_err("Pre-processing failed.");
                 return false;
             }
 
-            profiler.StartProfiling("Inference");
-            if (!runner.RunInference()) {
+            if (!RunInference(model, profiler)) {
+                printf_err("Inference failed.");
                 return false;
             }
-            profiler.StopProfiling();
 
-            if (!runner.PostProcess()) {
+            if (!postProcess.DoPostProcess()) {
+                printf_err("Post-processing failed.");
                 return false;
             }
 
@@ -138,7 +137,6 @@ namespace app {
             ctx.Set<std::vector<ClassificationResult>>("results", results);
 
 #if VERIFY_TEST_OUTPUT
-            TfLiteTensor* outputTensor = model.GetOutputTensor(0);
             arm::app::DumpTensor(outputTensor);
 #endif /* VERIFY_TEST_OUTPUT */
 
diff --git a/source/use_case/vww/src/VisualWakeWordProcessing.cc b/source/use_case/vww/src/VisualWakeWordProcessing.cc
index 94eae28..a9863c0 100644
--- a/source/use_case/vww/src/VisualWakeWordProcessing.cc
+++ b/source/use_case/vww/src/VisualWakeWordProcessing.cc
@@ -22,13 +22,9 @@
 namespace arm {
 namespace app {
 
-    VisualWakeWordPreProcess::VisualWakeWordPreProcess(Model* model)
-    {
-        if (!model->IsInited()) {
-            printf_err("Model is not initialised!.\n");
-        }
-        this->m_model = model;
-    }
+    VisualWakeWordPreProcess::VisualWakeWordPreProcess(TfLiteTensor* inputTensor)
+    :m_inputTensor{inputTensor}
+    {}
 
     bool VisualWakeWordPreProcess::DoPreProcess(const void* data, size_t inputSize)
     {
@@ -37,9 +33,8 @@ namespace app {
         }
 
         auto input = static_cast<const uint8_t*>(data);
-        TfLiteTensor* inputTensor = this->m_model->GetInputTensor(0);
 
-        auto unsignedDstPtr = static_cast<uint8_t*>(inputTensor->data.data);
+        auto unsignedDstPtr = static_cast<uint8_t*>(this->m_inputTensor->data.data);
 
         /* VWW model has one channel input => Convert image to grayscale here.
          * We expect images to always be RGB. */
@@ -47,10 +42,10 @@ namespace app {
 
         /* VWW model pre-processing is image conversion from uint8 to [0,1] float values,
          * then quantize them with input quantization info. */
-        QuantParams inQuantParams = GetTensorQuantParams(inputTensor);
+        QuantParams inQuantParams = GetTensorQuantParams(this->m_inputTensor);
 
-        auto signedDstPtr = static_cast<int8_t*>(inputTensor->data.data);
-        for (size_t i = 0; i < inputTensor->bytes; i++) {
+        auto signedDstPtr = static_cast<int8_t*>(this->m_inputTensor->data.data);
+        for (size_t i = 0; i < this->m_inputTensor->bytes; i++) {
             auto i_data_int8 = static_cast<int8_t>(
                     ((static_cast<float>(unsignedDstPtr[i]) / 255.0f) / inQuantParams.scale) + inQuantParams.offset
                     );
@@ -62,22 +57,18 @@ namespace app {
         return true;
     }
 
-    VisualWakeWordPostProcess::VisualWakeWordPostProcess(Classifier& classifier, Model* model,
+    VisualWakeWordPostProcess::VisualWakeWordPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
             const std::vector<std::string>& labels, std::vector<ClassificationResult>& results)
-            :m_vwwClassifier{classifier},
+            :m_outputTensor{outputTensor},
+             m_vwwClassifier{classifier},
              m_labels{labels},
              m_results{results}
-    {
-        if (!model->IsInited()) {
-            printf_err("Model is not initialised!.\n");
-        }
-        this->m_model = model;
-    }
+    {}
 
     bool VisualWakeWordPostProcess::DoPostProcess()
     {
         return this->m_vwwClassifier.GetClassificationResults(
-                this->m_model->GetOutputTensor(0), this->m_results,
+                this->m_outputTensor, this->m_results,
                 this->m_labels, 1, true);
     }