MLECO-3183: Refactoring application sources

Platform agnostic application sources are moved into application
api module with their own independent CMake projects.

Changes for MLECO-3080 also included - they create CMake projects
individial API's (again, platform agnostic) that dependent on the
common logic. The API for KWS_API "joint" API has been removed and
now the use case relies on individual KWS, and ASR API libraries.

Change-Id: I1f7748dc767abb3904634a04e0991b74ac7b756d
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>
diff --git a/source/application/api/use_case/vww/CMakeLists.txt b/source/application/api/use_case/vww/CMakeLists.txt
new file mode 100644
index 0000000..b933d32
--- /dev/null
+++ b/source/application/api/use_case/vww/CMakeLists.txt
@@ -0,0 +1,39 @@
+#----------------------------------------------------------------------------
+#  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.
+#----------------------------------------------------------------------------
+#########################################################
+#             VISUAL WAKE WORD API library              #
+#########################################################
+cmake_minimum_required(VERSION 3.15.6)
+
+set(VWW_API_TARGET vww_api)
+project(${VWW_API_TARGET}
+        DESCRIPTION     "Visual wake word use case API library"
+        LANGUAGES       C CXX)
+
+# Create static library
+add_library(${VWW_API_TARGET} STATIC
+        src/VisualWakeWordProcessing.cc
+        src/VisualWakeWordModel.cc)
+
+target_include_directories(${VWW_API_TARGET} PUBLIC include)
+
+target_link_libraries(${VWW_API_TARGET} PUBLIC common_api)
+
+message(STATUS "*******************************************************")
+message(STATUS "Library                                : " ${VWW_API_TARGET})
+message(STATUS "CMAKE_SYSTEM_PROCESSOR                 : " ${CMAKE_SYSTEM_PROCESSOR})
+message(STATUS "*******************************************************")
diff --git a/source/application/api/use_case/vww/include/VisualWakeWordModel.hpp b/source/application/api/use_case/vww/include/VisualWakeWordModel.hpp
new file mode 100644
index 0000000..a34b904
--- /dev/null
+++ b/source/application/api/use_case/vww/include/VisualWakeWordModel.hpp
@@ -0,0 +1,50 @@
+/*
+ * Copyright (c) 2021 - 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 VISUAL_WAKE_WORD_MODEL_HPP
+#define VISUAL_WAKE_WORD_MODEL_HPP
+
+#include "Model.hpp"
+
+namespace arm {
+namespace app {
+
+    class VisualWakeWordModel : public Model {
+
+    public:
+        /* Indices for the expected model - based on input tensor shape */
+        static constexpr uint32_t ms_inputRowsIdx     = 1;
+        static constexpr uint32_t ms_inputColsIdx     = 2;
+        static constexpr uint32_t ms_inputChannelsIdx = 3;
+
+    protected:
+        /** @brief   Gets the reference to op resolver interface class. */
+        const tflite::MicroOpResolver& GetOpResolver() override;
+
+        /** @brief   Adds operations to the op resolver instance. */
+        bool EnlistOperations() override;
+    private:
+        /* Maximum number of individual operations that can be enlisted. */
+        static constexpr int ms_maxOpCnt = 7;
+
+        /* A mutable op resolver instance. */
+        tflite::MicroMutableOpResolver<ms_maxOpCnt> m_opResolver;
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* VISUAL_WAKE_WORD_MODEL_HPP */
diff --git a/source/application/api/use_case/vww/include/VisualWakeWordProcessing.hpp b/source/application/api/use_case/vww/include/VisualWakeWordProcessing.hpp
new file mode 100644
index 0000000..f9f9d72
--- /dev/null
+++ b/source/application/api/use_case/vww/include/VisualWakeWordProcessing.hpp
@@ -0,0 +1,93 @@
+/*
+ * 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 VWW_PROCESSING_HPP
+#define VWW_PROCESSING_HPP
+
+#include "BaseProcessing.hpp"
+#include "Model.hpp"
+#include "Classifier.hpp"
+
+namespace arm {
+namespace app {
+
+    /**
+     * @brief   Pre-processing class for Visual Wake Word use case.
+     *          Implements methods declared by BasePreProcess and anything else needed
+     *          to populate input tensors ready for inference.
+     */
+    class VisualWakeWordPreProcess : public BasePreProcess {
+
+    public:
+        /**
+         * @brief       Constructor
+         * @param[in]   inputTensor   Pointer to the TFLite Micro input Tensor.
+         * @param[in]   rgb2Gray      Convert image from 3 channel RGB to 1 channel grayscale.
+         **/
+        explicit VisualWakeWordPreProcess(TfLiteTensor* inputTensor, bool rgb2Gray=true);
+
+        /**
+         * @brief       Should perform pre-processing of 'raw' input image data and load it into
+         *              TFLite Micro input tensors ready for inference
+         * @param[in]   input      Pointer to the data that pre-processing will work on.
+         * @param[in]   inputSize  Size of the input data.
+         * @return      true if successful, false otherwise.
+         **/
+        bool DoPreProcess(const void* input, size_t inputSize) override;
+
+    private:
+        TfLiteTensor* m_inputTensor;
+        bool m_rgb2Gray;
+    };
+
+    /**
+     * @brief   Post-processing class for Visual Wake Word use case.
+     *          Implements methods declared by BasePostProcess and anything else needed
+     *          to populate result vector.
+     */
+    class VisualWakeWordPostProcess : public BasePostProcess {
+
+    private:
+        TfLiteTensor* m_outputTensor;
+        Classifier& m_vwwClassifier;
+        const std::vector<std::string>& m_labels;
+        std::vector<ClassificationResult>& m_results;
+
+    public:
+        /**
+         * @brief       Constructor
+         * @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]   model          Pointer to the VWW classification Model object.
+         * @param[in]   labels         Vector of string labels to identify each output of the model.
+         * @param[out]  results        Vector of classification results to store decoded outputs.
+         **/
+        VisualWakeWordPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
+                const std::vector<std::string>& labels,
+                std::vector<ClassificationResult>& results);
+
+        /**
+         * @brief    Should perform post-processing of the result of inference then
+         *           populate classification result data for any later use.
+         * @return   true if successful, false otherwise.
+         **/
+        bool DoPostProcess() override;
+    };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* VWW_PROCESSING_HPP */
\ No newline at end of file
diff --git a/source/application/api/use_case/vww/src/VisualWakeWordModel.cc b/source/application/api/use_case/vww/src/VisualWakeWordModel.cc
new file mode 100644
index 0000000..2d8a125
--- /dev/null
+++ b/source/application/api/use_case/vww/src/VisualWakeWordModel.cc
@@ -0,0 +1,42 @@
+/*
+ * Copyright (c) 2021 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 "VisualWakeWordModel.hpp"
+#include "log_macros.h"
+
+const tflite::MicroOpResolver& arm::app::VisualWakeWordModel::GetOpResolver()
+{
+    return this->m_opResolver;
+}
+
+bool arm::app::VisualWakeWordModel::EnlistOperations()
+{
+    this->m_opResolver.AddDepthwiseConv2D();
+    this->m_opResolver.AddConv2D();
+    this->m_opResolver.AddAveragePool2D();
+    this->m_opResolver.AddReshape();
+    this->m_opResolver.AddPad();
+    this->m_opResolver.AddAdd();
+
+    if (kTfLiteOk == this->m_opResolver.AddEthosU()) {
+        info("Added %s support to op resolver\n",
+            tflite::GetString_ETHOSU());
+    } else {
+        printf_err("Failed to add Arm NPU support to op resolver.");
+        return false;
+    }
+    return true;
+}
diff --git a/source/application/api/use_case/vww/src/VisualWakeWordProcessing.cc b/source/application/api/use_case/vww/src/VisualWakeWordProcessing.cc
new file mode 100644
index 0000000..4ae8a54
--- /dev/null
+++ b/source/application/api/use_case/vww/src/VisualWakeWordProcessing.cc
@@ -0,0 +1,80 @@
+/*
+ * 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 "VisualWakeWordProcessing.hpp"
+
+#include "ImageUtils.hpp"
+#include "VisualWakeWordModel.hpp"
+#include "log_macros.h"
+
+namespace arm {
+namespace app {
+
+    VisualWakeWordPreProcess::VisualWakeWordPreProcess(TfLiteTensor* inputTensor, bool rgb2Gray)
+    :m_inputTensor{inputTensor},
+     m_rgb2Gray{rgb2Gray}
+    {}
+
+    bool VisualWakeWordPreProcess::DoPreProcess(const void* data, size_t inputSize)
+    {
+        if (data == nullptr) {
+            printf_err("Data pointer is null");
+        }
+
+        auto input = static_cast<const uint8_t*>(data);
+
+        uint8_t* unsignedDstPtr = this->m_inputTensor->data.uint8;
+
+        if (this->m_rgb2Gray) {
+            image::RgbToGrayscale(input, unsignedDstPtr, inputSize);
+        } else {
+            std::memcpy(unsignedDstPtr, input, inputSize);
+        }
+
+        /* VWW model pre-processing is image conversion from uint8 to [0,1] float values,
+         * then quantize them with input quantization info. */
+        QuantParams inQuantParams = GetTensorQuantParams(this->m_inputTensor);
+
+        int8_t* signedDstPtr = this->m_inputTensor->data.int8;
+        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
+                    );
+            signedDstPtr[i] = std::min<int8_t>(INT8_MAX, std::max<int8_t>(i_data_int8, INT8_MIN));
+        }
+
+        debug("Input tensor populated \n");
+
+        return true;
+    }
+
+    VisualWakeWordPostProcess::VisualWakeWordPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
+            const std::vector<std::string>& labels, std::vector<ClassificationResult>& results)
+            :m_outputTensor{outputTensor},
+             m_vwwClassifier{classifier},
+             m_labels{labels},
+             m_results{results}
+    {}
+
+    bool VisualWakeWordPostProcess::DoPostProcess()
+    {
+        return this->m_vwwClassifier.GetClassificationResults(
+                this->m_outputTensor, this->m_results,
+                this->m_labels, 1, true);
+    }
+
+} /* namespace app */
+} /* namespace arm */
\ No newline at end of file