commit b40ecf8522052809d2351677a96195d69e4d0c16
author Richard Burton <richard.burton@arm.com> Fri Apr 22 16:14:57 2022 +0100
committer Richard Burton <richard.burton@arm.com> Fri Apr 22 16:14:57 2022 +0100
tree 8647dfdae7bcae0ec6d9564ba7a971819fdda431
parent c291144b7f08c21d08cdaf79cc64dc420ca70070

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

source/use_case/img_class/src/UseCaseHandler.cc

diff --git a/source/use_case/img_class/src/UseCaseHandler.cc b/source/use_case/img_class/src/UseCaseHandler.cc
index c68d816..5cc3959 100644
--- a/source/use_case/img_class/src/UseCaseHandler.cc
+++ b/source/use_case/img_class/src/UseCaseHandler.cc
@@ -59,6 +59,7 @@
         }
 
         TfLiteTensor* inputTensor = model.GetInputTensor(0);
+        TfLiteTensor* outputTensor = model.GetOutputTensor(0);
         if (!inputTensor->dims) {
             printf_err("Invalid input tensor dims\n");
             return false;
@@ -74,13 +75,12 @@
         const uint32_t nChannels = inputShape->data[arm::app::MobileNetModel::ms_inputChannelsIdx];
 
         /* Set up pre and post-processing. */
-        ImgClassPreProcess preprocess = ImgClassPreProcess(&model);
+        ImgClassPreProcess preProcess = ImgClassPreProcess(inputTensor, model.IsDataSigned());
 
         std::vector<ClassificationResult> results;
-        ImgClassPostProcess postprocess = ImgClassPostProcess(ctx.Get<ImgClassClassifier&>("classifier"), &model,
-                ctx.Get<std::vector<std::string>&>("labels"), results);
-
-        UseCaseRunner runner = UseCaseRunner(&preprocess, &postprocess, &model);
+        ImgClassPostProcess postProcess = ImgClassPostProcess(outputTensor,
+                ctx.Get<ImgClassClassifier&>("classifier"), ctx.Get<std::vector<std::string>&>("labels"),
+                results);
 
         do {
             hal_lcd_clear(COLOR_BLACK);
@@ -113,17 +113,18 @@
                                   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;
             }
 
@@ -136,7 +137,6 @@
             ctx.Set<std::vector<ClassificationResult>>("results", results);
 
 #if VERIFY_TEST_OUTPUT
-            TfLiteTensor* outputTensor = model.GetOutputTensor(0);
             arm::app::DumpTensor(outputTensor);
 #endif /* VERIFY_TEST_OUTPUT */