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/img_class/CMakeLists.txt b/source/application/api/use_case/img_class/CMakeLists.txt
new file mode 100644
index 0000000..f4818d8
--- /dev/null
+++ b/source/application/api/use_case/img_class/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.
+#----------------------------------------------------------------------------
+#########################################################
+# IMG CLASS API library #
+#########################################################
+cmake_minimum_required(VERSION 3.15.6)
+
+set(IMG_CLASS_API_TARGET img_class_api)
+project(${IMG_CLASS_API_TARGET}
+ DESCRIPTION "Image classification use case API library"
+ LANGUAGES C CXX)
+
+# Create static library
+add_library(${IMG_CLASS_API_TARGET} STATIC
+ src/ImgClassProcessing.cc
+ src/MobileNetModel.cc)
+
+target_include_directories(${IMG_CLASS_API_TARGET} PUBLIC include)
+
+target_link_libraries(${IMG_CLASS_API_TARGET} PUBLIC common_api)
+
+message(STATUS "*******************************************************")
+message(STATUS "Library : " ${IMG_CLASS_API_TARGET})
+message(STATUS "CMAKE_SYSTEM_PROCESSOR : " ${CMAKE_SYSTEM_PROCESSOR})
+message(STATUS "*******************************************************")
diff --git a/source/application/api/use_case/img_class/include/ImgClassProcessing.hpp b/source/application/api/use_case/img_class/include/ImgClassProcessing.hpp
new file mode 100644
index 0000000..55b5ce1
--- /dev/null
+++ b/source/application/api/use_case/img_class/include/ImgClassProcessing.hpp
@@ -0,0 +1,91 @@
+/*
+ * 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 "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:
+ /**
+ * @brief Constructor
+ * @param[in] inputTensor Pointer to the TFLite Micro input Tensor.
+ * @param[in] convertToInt8 Should the image be converted to Int8 range.
+ **/
+ explicit ImgClassPreProcess(TfLiteTensor* inputTensor, bool convertToInt8);
+
+ /**
+ * @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_convertToInt8;
+ };
+
+ /**
+ * @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 {
+
+ 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] labels Vector of string labels to identify each output of the model.
+ * @param[in] results Vector of classification results to store decoded outputs.
+ **/
+ ImgClassPostProcess(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;
+
+ private:
+ TfLiteTensor* m_outputTensor;
+ Classifier& m_imgClassifier;
+ const std::vector<std::string>& m_labels;
+ std::vector<ClassificationResult>& m_results;
+ };
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* IMG_CLASS_PROCESSING_HPP */
\ No newline at end of file
diff --git a/source/application/api/use_case/img_class/include/MobileNetModel.hpp b/source/application/api/use_case/img_class/include/MobileNetModel.hpp
new file mode 100644
index 0000000..adaa9c2
--- /dev/null
+++ b/source/application/api/use_case/img_class/include/MobileNetModel.hpp
@@ -0,0 +1,51 @@
+/*
+ * 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.
+ */
+#ifndef IMG_CLASS_MOBILENETMODEL_HPP
+#define IMG_CLASS_MOBILENETMODEL_HPP
+
+#include "Model.hpp"
+
+namespace arm {
+namespace app {
+
+ class MobileNetModel : 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 /* IMG_CLASS_MOBILENETMODEL_HPP */
diff --git a/source/application/api/use_case/img_class/src/ImgClassProcessing.cc b/source/application/api/use_case/img_class/src/ImgClassProcessing.cc
new file mode 100644
index 0000000..491e751
--- /dev/null
+++ b/source/application/api/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(TfLiteTensor* inputTensor, bool convertToInt8)
+ :m_inputTensor{inputTensor},
+ m_convertToInt8{convertToInt8}
+ {}
+
+ bool ImgClassPreProcess::DoPreProcess(const void* data, size_t inputSize)
+ {
+ if (data == nullptr) {
+ printf_err("Data pointer is null");
+ return false;
+ }
+
+ auto input = static_cast<const uint8_t*>(data);
+
+ std::memcpy(this->m_inputTensor->data.data, input, inputSize);
+ debug("Input tensor populated \n");
+
+ if (this->m_convertToInt8) {
+ image::ConvertImgToInt8(this->m_inputTensor->data.data, this->m_inputTensor->bytes);
+ }
+
+ return true;
+ }
+
+ ImgClassPostProcess::ImgClassPostProcess(TfLiteTensor* outputTensor, Classifier& classifier,
+ const std::vector<std::string>& labels,
+ std::vector<ClassificationResult>& results)
+ :m_outputTensor{outputTensor},
+ m_imgClassifier{classifier},
+ m_labels{labels},
+ m_results{results}
+ {}
+
+ bool ImgClassPostProcess::DoPostProcess()
+ {
+ return this->m_imgClassifier.GetClassificationResults(
+ this->m_outputTensor, this->m_results,
+ this->m_labels, 5, false);
+ }
+
+} /* namespace app */
+} /* namespace arm */
\ No newline at end of file
diff --git a/source/application/api/use_case/img_class/src/MobileNetModel.cc b/source/application/api/use_case/img_class/src/MobileNetModel.cc
new file mode 100644
index 0000000..b700d70
--- /dev/null
+++ b/source/application/api/use_case/img_class/src/MobileNetModel.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 "MobileNetModel.hpp"
+#include "log_macros.h"
+
+const tflite::MicroOpResolver& arm::app::MobileNetModel::GetOpResolver()
+{
+ return this->m_opResolver;
+}
+
+bool arm::app::MobileNetModel::EnlistOperations()
+{
+ this->m_opResolver.AddDepthwiseConv2D();
+ this->m_opResolver.AddConv2D();
+ this->m_opResolver.AddAveragePool2D();
+ this->m_opResolver.AddAdd();
+ this->m_opResolver.AddReshape();
+ this->m_opResolver.AddSoftmax();
+
+ 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;
+}