MLECO-3079: Implement image classification API

All ML related work for image classification seperated out and accessed via new Runner
Further work to improve profiling integration to be done in follow up ticket: MLECO-3154

Signed-off-by: Richard Burton <richard.burton@arm.com>
Change-Id: I0fe0550c932241a2d335a560ecb7abc329c934e9

3 files changed, 166 insertions, 51 deletions

diff --git a/source/use_case/img_class/include/ImgClassProcessing.hpp b/source/use_case/img_class/include/ImgClassProcessing.hpp
new file mode 100644
index 0000000..5a59b5f
--- /dev/null
+++ b/source/use_case/img_class/include/ImgClassProcessing.hpp
@@ -0,0 +1,63 @@
+/*
+ * 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 IMG_CLASS_PROCESSING_HPP
+#define IMG_CLASS_PROCESSING_HPP
+
+#include "BaseProcessing.hpp"
+#include "Model.hpp"
+#include "Classifier.hpp"
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   Pre-processing class for Image Classification use case.
+     *          Implements methods declared by BasePreProcess and anything else needed
+     *          to populate input tensors ready for inference.
+     */
+    class ImgClassPreProcess : public BasePreProcess {
+
+    public:
+        explicit ImgClassPreProcess(Model* model);
+
+        bool DoPreProcess(const void* input, size_t inputSize) override;
+    };
+
+    /**
+     * @brief   Post-processing class for Image Classification use case.
+     *          Implements methods declared by BasePostProcess and anything else needed
+     *          to populate result vector.
+     */
+    class ImgClassPostProcess : public BasePostProcess {
+
+    private:
+        Classifier& m_imgClassifier;
+        const std::vector<std::string>& m_labels;
+        std::vector<ClassificationResult>& m_results;
+
+    public:
+        ImgClassPostProcess(Classifier& classifier, Model* model,
+                            const std::vector<std::string>& labels,
+                            std::vector<ClassificationResult>& results);
+
+        bool DoPostProcess() override;
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* IMG_CLASS_PROCESSING_HPP */
\ No newline at end of file
diff --git a/source/use_case/img_class/src/ImgClassProcessing.cc b/source/use_case/img_class/src/ImgClassProcessing.cc
new file mode 100644
index 0000000..e33e3c1
--- /dev/null
+++ b/source/use_case/img_class/src/ImgClassProcessing.cc
@@ -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.
+ */
+#include "ImgClassProcessing.hpp"
+#include "ImageUtils.hpp"
+#include "log_macros.h"
+
+namespace arm {
+namespace app {
+
+    ImgClassPreProcess::ImgClassPreProcess(Model* model)
+    {
+        this->m_model = model;
+    }
+
+    bool ImgClassPreProcess::DoPreProcess(const void* data, size_t inputSize)
+    {
+        if (data == nullptr) {
+            printf_err("Data pointer is null");
+        }
+
+        auto input = static_cast<const uint8_t*>(data);
+        TfLiteTensor* inputTensor = this->m_model->GetInputTensor(0);
+
+        memcpy(inputTensor->data.data, input, inputSize);
+        debug("Input tensor populated \n");
+
+        if (this->m_model->IsDataSigned()) {
+            image::ConvertImgToInt8(inputTensor->data.data, inputTensor->bytes);
+        }
+
+        return true;
+    }
+
+    ImgClassPostProcess::ImgClassPostProcess(Classifier& classifier, Model* model,
+                                             const std::vector<std::string>& labels,
+                                             std::vector<ClassificationResult>& results)
+            :m_imgClassifier{classifier},
+             m_labels{labels},
+             m_results{results}
+    {
+        this->m_model = model;
+    }
+
+    bool ImgClassPostProcess::DoPostProcess()
+    {
+        return this->m_imgClassifier.GetClassificationResults(
+                this->m_model->GetOutputTensor(0), this->m_results,
+                this->m_labels, 5, false);
+    }
+
+} /* namespace app */
+} /* namespace arm */
\ No newline at end of file
diff --git a/source/use_case/img_class/src/UseCaseHandler.cc b/source/use_case/img_class/src/UseCaseHandler.cc
index 9061282..98e2b59 100644
--- a/source/use_case/img_class/src/UseCaseHandler.cc
+++ b/source/use_case/img_class/src/UseCaseHandler.cc
@@ -23,6 +23,7 @@
 #include "UseCaseCommonUtils.hpp"
 #include "hal.h"
 #include "log_macros.h"
+#include "ImgClassProcessing.hpp"
 
 #include <cinttypes>
 
@@ -31,20 +32,12 @@ using ImgClassClassifier = arm::app::Classifier;
 namespace arm {
 namespace app {
 
-    /**
-    * @brief           Helper function to load the current image into the input
-    *                  tensor.
-    * @param[in]       imIdx         Image index (from the pool of images available
-    *                                to the application).
-    * @param[out]      inputTensor   Pointer to the input tensor to be populated.
-    * @return          true if tensor is loaded, false otherwise.
-    **/
-    static bool LoadImageIntoTensor(uint32_t imIdx, TfLiteTensor* inputTensor);
-
-    /* Image inference classification handler. */
+    /* Image classification inference handler. */
     bool ClassifyImageHandler(ApplicationContext& ctx, uint32_t imgIndex, bool runAll)
     {
         auto& profiler = ctx.Get<Profiler&>("profiler");
+        auto& model = ctx.Get<Model&>("model");
+        auto initialImIdx = ctx.Get<uint32_t>("imgIndex");
 
         constexpr uint32_t dataPsnImgDownscaleFactor = 2;
         constexpr uint32_t dataPsnImgStartX = 10;
@@ -53,8 +46,6 @@ namespace app {
         constexpr uint32_t dataPsnTxtInfStartX = 150;
         constexpr uint32_t dataPsnTxtInfStartY = 40;
 
-        auto& model = ctx.Get<Model&>("model");
-
         /* If the request has a valid size, set the image index. */
         if (imgIndex < NUMBER_OF_FILES) {
             if (!SetAppCtxIfmIdx(ctx, imgIndex, "imgIndex")) {
@@ -66,11 +57,7 @@ namespace app {
             return false;
         }
 
-        auto curImIdx = ctx.Get<uint32_t>("imgIndex");
-
-        TfLiteTensor* outputTensor = model.GetOutputTensor(0);
         TfLiteTensor* inputTensor = model.GetInputTensor(0);
-
         if (!inputTensor->dims) {
             printf_err("Invalid input tensor dims\n");
             return false;
@@ -79,13 +66,20 @@ namespace app {
             return false;
         }
 
+        /* Get input shape for displaying the image. */
         TfLiteIntArray* inputShape = model.GetInputShape(0);
-
         const uint32_t nCols = inputShape->data[arm::app::MobileNetModel::ms_inputColsIdx];
         const uint32_t nRows = inputShape->data[arm::app::MobileNetModel::ms_inputRowsIdx];
         const uint32_t nChannels = inputShape->data[arm::app::MobileNetModel::ms_inputChannelsIdx];
 
+        /* Set up pre and post-processing. */
+        ImgClassPreProcess preprocess = ImgClassPreProcess(&model);
+
         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);
 
         do {
             hal_lcd_clear(COLOR_BLACK);
@@ -93,29 +87,42 @@ namespace app {
             /* Strings for presentation/logging. */
             std::string str_inf{"Running inference... "};
 
-            /* Copy over the data. */
-            LoadImageIntoTensor(ctx.Get<uint32_t>("imgIndex"), inputTensor);
+            const uint8_t* imgSrc = get_img_array(ctx.Get<uint32_t>("imgIndex"));
+            if (nullptr == imgSrc) {
+                printf_err("Failed to get image index %" PRIu32 " (max: %u)\n", ctx.Get<uint32_t>("imgIndex"),
+                           NUMBER_OF_FILES - 1);
+                return false;
+            }
 
             /* Display this image on the LCD. */
             hal_lcd_display_image(
-                static_cast<uint8_t *>(inputTensor->data.data),
+                imgSrc,
                 nCols, nRows, nChannels,
                 dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor);
 
-            /* If the data is signed. */
-            if (model.IsDataSigned()) {
-                image::ConvertImgToInt8(inputTensor->data.data, inputTensor->bytes);
-            }
-
             /* Display message on the LCD - inference running. */
             hal_lcd_display_text(str_inf.c_str(), str_inf.size(),
                                     dataPsnTxtInfStartX, dataPsnTxtInfStartY, false);
 
-            /* Run inference over this image. */
+            /* Select the image to run inference with. */
             info("Running inference on image %" PRIu32 " => %s\n", ctx.Get<uint32_t>("imgIndex"),
                 get_filename(ctx.Get<uint32_t>("imgIndex")));
 
-            if (!RunInference(model, profiler)) {
+            const size_t imgSz = inputTensor->bytes < IMAGE_DATA_SIZE ?
+                                  inputTensor->bytes : IMAGE_DATA_SIZE;
+
+            /* Run the pre-processing, inference and post-processing. */
+            if (!runner.PreProcess(imgSrc, imgSz)) {
+                return false;
+            }
+
+            profiler.StartProfiling("Inference");
+            if (!runner.RunInference()) {
+                return false;
+            }
+            profiler.StopProfiling();
+
+            if (!runner.PostProcess()) {
                 return false;
             }
 
@@ -124,15 +131,11 @@ namespace app {
             hal_lcd_display_text(str_inf.c_str(), str_inf.size(),
                                     dataPsnTxtInfStartX, dataPsnTxtInfStartY, false);
 
-            auto& classifier = ctx.Get<ImgClassClassifier&>("classifier");
-            classifier.GetClassificationResults(outputTensor, results,
-                                                ctx.Get<std::vector <std::string>&>("labels"),
-                                                5, false);
-
             /* Add results to context for access outside handler. */
             ctx.Set<std::vector<ClassificationResult>>("results", results);
 
 #if VERIFY_TEST_OUTPUT
+            TfLiteTensor* outputTensor = model.GetOutputTensor(0);
             arm::app::DumpTensor(outputTensor);
 #endif /* VERIFY_TEST_OUTPUT */
 
@@ -144,27 +147,10 @@ namespace app {
 
             IncrementAppCtxIfmIdx(ctx,"imgIndex");
 
-        } while (runAll && ctx.Get<uint32_t>("imgIndex") != curImIdx);
-
-        return true;
-    }
+        } while (runAll && ctx.Get<uint32_t>("imgIndex") != initialImIdx);
 
-    static bool LoadImageIntoTensor(uint32_t imIdx, TfLiteTensor* inputTensor)
-    {
-        const size_t copySz = inputTensor->bytes < IMAGE_DATA_SIZE ?
-                              inputTensor->bytes : IMAGE_DATA_SIZE;
-        const uint8_t* imgSrc = get_img_array(imIdx);
-        if (nullptr == imgSrc) {
-            printf_err("Failed to get image index %" PRIu32 " (max: %u)\n", imIdx,
-                       NUMBER_OF_FILES - 1);
-            return false;
-        }
-
-        memcpy(inputTensor->data.data, imgSrc, copySz);
-        debug("Image %" PRIu32 " loaded\n", imIdx);
         return true;
     }
 
-
 } /* namespace app */
 } /* namespace arm */