Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/source/use_case/img_class/include/MobileNetModel.hpp b/source/use_case/img_class/include/MobileNetModel.hpp
new file mode 100644
index 0000000..f0521ce
--- /dev/null
+++ b/source/use_case/img_class/include/MobileNetModel.hpp
@@ -0,0 +1,55 @@
+/*
+ * 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;
+
+ const uint8_t* ModelPointer() override;
+
+ size_t ModelSize() 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 */
\ No newline at end of file
diff --git a/source/use_case/img_class/include/UseCaseHandler.hpp b/source/use_case/img_class/include/UseCaseHandler.hpp
new file mode 100644
index 0000000..a6cf104
--- /dev/null
+++ b/source/use_case/img_class/include/UseCaseHandler.hpp
@@ -0,0 +1,37 @@
+/*
+ * 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_EVT_HANDLER_HPP
+#define IMG_CLASS_EVT_HANDLER_HPP
+
+#include "AppContext.hpp"
+
+namespace arm {
+namespace app {
+
+ /**
+ * @brief Handles the inference event.
+ * @param[in] ctx Pointer to the application context.
+ * @param[in] imgIndex Index to the image to classify.
+ * @param[in] runAll Flag to request classification of all the available images.
+ * @return true or false based on execution success.
+ **/
+ bool ClassifyImageHandler(ApplicationContext& ctx, uint32_t imgIndex, bool runAll);
+
+} /* namespace app */
+} /* namespace arm */
+
+#endif /* IMG_CLASS_EVT_HANDLER_HPP */
\ No newline at end of file
diff --git a/source/use_case/img_class/src/MainLoop.cc b/source/use_case/img_class/src/MainLoop.cc
new file mode 100644
index 0000000..469907c
--- /dev/null
+++ b/source/use_case/img_class/src/MainLoop.cc
@@ -0,0 +1,109 @@
+/*
+ * 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 "hal.h" /* Brings in platform definitions. */
+#include "Classifier.hpp" /* Classifier. */
+#include "InputFiles.hpp" /* For input images. */
+#include "Labels.hpp" /* For label strings. */
+#include "MobileNetModel.hpp" /* Model class for running inference. */
+#include "UseCaseHandler.hpp" /* Handlers for different user options. */
+#include "UseCaseCommonUtils.hpp" /* Utils functions. */
+
+using ImgClassClassifier = arm::app::Classifier;
+
+enum opcodes
+{
+ MENU_OPT_RUN_INF_NEXT = 1, /* Run on next vector. */
+ MENU_OPT_RUN_INF_CHOSEN, /* Run on a user provided vector index. */
+ MENU_OPT_RUN_INF_ALL, /* Run inference on all. */
+ MENU_OPT_SHOW_MODEL_INFO, /* Show model info. */
+ MENU_OPT_LIST_IMAGES /* List the current baked images. */
+};
+
+static void DisplayMenu()
+{
+ printf("\n\nUser input required\n");
+ printf("Enter option number from:\n\n");
+ printf(" %u. Classify next image\n", MENU_OPT_RUN_INF_NEXT);
+ printf(" %u. Classify image at chosen index\n", MENU_OPT_RUN_INF_CHOSEN);
+ printf(" %u. Run classification on all images\n", MENU_OPT_RUN_INF_ALL);
+ printf(" %u. Show NN model info\n", MENU_OPT_SHOW_MODEL_INFO);
+ printf(" %u. List images\n\n", MENU_OPT_LIST_IMAGES);
+ printf(" Choice: ");
+}
+
+void main_loop(hal_platform& platform)
+{
+ arm::app::MobileNetModel model; /* Model wrapper object. */
+
+ /* Load the model. */
+ if (!model.Init()) {
+ printf_err("Failed to initialise model\n");
+ return;
+ }
+
+ /* Instantiate application context. */
+ arm::app::ApplicationContext caseContext;
+
+ caseContext.Set<hal_platform&>("platform", platform);
+ caseContext.Set<arm::app::Model&>("model", model);
+ caseContext.Set<uint32_t>("imgIndex", 0);
+
+ ImgClassClassifier classifier; /* Classifier wrapper object. */
+ caseContext.Set<arm::app::Classifier&>("classifier", classifier);
+
+ std::vector <std::string> labels;
+ GetLabelsVector(labels);
+ caseContext.Set<const std::vector <std::string>&>("labels", labels);
+
+ /* Loop. */
+ bool executionSuccessful = true;
+ constexpr bool bUseMenu = NUMBER_OF_FILES > 1 ? true : false;
+
+ /* Loop. */
+ do {
+ int menuOption = MENU_OPT_RUN_INF_NEXT;
+ if (bUseMenu) {
+ DisplayMenu();
+ menuOption = arm::app::ReadUserInputAsInt(platform);
+ printf("\n");
+ }
+ switch (menuOption) {
+ case MENU_OPT_RUN_INF_NEXT:
+ executionSuccessful = ClassifyImageHandler(caseContext, caseContext.Get<uint32_t>("imgIndex"), false);
+ break;
+ case MENU_OPT_RUN_INF_CHOSEN: {
+ printf(" Enter the image index [0, %d]: ", NUMBER_OF_FILES-1);
+ auto imgIndex = static_cast<uint32_t>(arm::app::ReadUserInputAsInt(platform));
+ executionSuccessful = ClassifyImageHandler(caseContext, imgIndex, false);
+ break;
+ }
+ case MENU_OPT_RUN_INF_ALL:
+ executionSuccessful = ClassifyImageHandler(caseContext, caseContext.Get<uint32_t>("imgIndex"), true);
+ break;
+ case MENU_OPT_SHOW_MODEL_INFO:
+ executionSuccessful = model.ShowModelInfoHandler();
+ break;
+ case MENU_OPT_LIST_IMAGES:
+ executionSuccessful = ListFilesHandler(caseContext);
+ break;
+ default:
+ printf("Incorrect choice, try again.");
+ break;
+ }
+ } while (executionSuccessful && bUseMenu);
+ info("Main loop terminated.\n");
+}
\ No newline at end of file
diff --git a/source/use_case/img_class/src/MobileNetModel.cc b/source/use_case/img_class/src/MobileNetModel.cc
new file mode 100644
index 0000000..eeaa109
--- /dev/null
+++ b/source/use_case/img_class/src/MobileNetModel.cc
@@ -0,0 +1,57 @@
+/*
+ * 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 "hal.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 defined(ARM_NPU)
+ 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;
+ }
+#endif /* ARM_NPU */
+ return true;
+}
+
+extern uint8_t* GetModelPointer();
+const uint8_t* arm::app::MobileNetModel::ModelPointer()
+{
+ return GetModelPointer();
+}
+
+extern size_t GetModelLen();
+size_t arm::app::MobileNetModel::ModelSize()
+{
+ return GetModelLen();
+}
\ 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
new file mode 100644
index 0000000..a412fec
--- /dev/null
+++ b/source/use_case/img_class/src/UseCaseHandler.cc
@@ -0,0 +1,269 @@
+/*
+ * 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 "UseCaseHandler.hpp"
+
+#include "Classifier.hpp"
+#include "InputFiles.hpp"
+#include "MobileNetModel.hpp"
+#include "UseCaseCommonUtils.hpp"
+#include "hal.h"
+
+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);
+
+ /**
+ * @brief Helper function to increment current image index.
+ * @param[in,out] ctx Pointer to the application context object.
+ **/
+ static void _IncrementAppCtxImageIdx(ApplicationContext& ctx);
+
+ /**
+ * @brief Helper function to set the image index.
+ * @param[in,out] ctx Pointer to the application context object.
+ * @param[in] idx Value to be set.
+ * @return true if index is set, false otherwise.
+ **/
+ static bool _SetAppCtxImageIdx(ApplicationContext& ctx, uint32_t idx);
+
+ /**
+ * @brief Presents inference results using the data presentation
+ * object.
+ * @param[in] platform Reference to the hal platform object.
+ * @param[in] results Vector of classification results to be displayed.
+ * @param[in] infTimeMs Inference time in milliseconds, if available
+ * otherwise, this can be passed in as 0.
+ * @return true if successful, false otherwise.
+ **/
+ static bool _PresentInferenceResult(hal_platform& platform,
+ const std::vector<ClassificationResult>& results);
+
+ /**
+ * @brief Helper function to convert a UINT8 image to INT8 format.
+ * @param[in,out] data Pointer to the data start.
+ * @param[in] kMaxImageSize Total number of pixels in the image.
+ **/
+ static void ConvertImgToInt8(void* data, size_t kMaxImageSize);
+
+ /* Image inference classification handler. */
+ bool ClassifyImageHandler(ApplicationContext& ctx, uint32_t imgIndex, bool runAll)
+ {
+ auto& platform = ctx.Get<hal_platform&>("platform");
+
+ constexpr uint32_t dataPsnImgDownscaleFactor = 2;
+ constexpr uint32_t dataPsnImgStartX = 10;
+ constexpr uint32_t dataPsnImgStartY = 35;
+
+ constexpr uint32_t dataPsnTxtInfStartX = 150;
+ constexpr uint32_t dataPsnTxtInfStartY = 40;
+
+ platform.data_psn->clear(COLOR_BLACK);
+
+ auto& model = ctx.Get<Model&>("model");
+
+ /* If the request has a valid size, set the image index. */
+ if (imgIndex < NUMBER_OF_FILES) {
+ if (!_SetAppCtxImageIdx(ctx, imgIndex)) {
+ return false;
+ }
+ }
+ if (!model.IsInited()) {
+ printf_err("Model is not initialised! Terminating processing.\n");
+ 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;
+ } else if (inputTensor->dims->size < 3) {
+ printf_err("Input tensor dimension should be >= 3\n");
+ return false;
+ }
+
+ 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];
+
+ std::vector<ClassificationResult> results;
+
+ do {
+ /* Strings for presentation/logging. */
+ std::string str_inf{"Running inference... "};
+
+ /* Copy over the data. */
+ _LoadImageIntoTensor(ctx.Get<uint32_t>("imgIndex"), inputTensor);
+
+ /* Display this image on the LCD. */
+ platform.data_psn->present_data_image(
+ (uint8_t*) inputTensor->data.data,
+ nCols, nRows, nChannels,
+ dataPsnImgStartX, dataPsnImgStartY, dataPsnImgDownscaleFactor);
+
+ /* If the data is signed. */
+ if (model.IsDataSigned()) {
+ ConvertImgToInt8(inputTensor->data.data, inputTensor->bytes);
+ }
+
+ /* Display message on the LCD - inference running. */
+ platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(),
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+
+ /* Run inference over this image. */
+ info("Running inference on image %u => %s\n", ctx.Get<uint32_t>("imgIndex"),
+ get_filename(ctx.Get<uint32_t>("imgIndex")));
+
+ RunInference(platform, model);
+
+ /* Erase. */
+ str_inf = std::string(str_inf.size(), ' ');
+ platform.data_psn->present_data_text(str_inf.c_str(), str_inf.size(),
+ dataPsnTxtInfStartX, dataPsnTxtInfStartY, 0);
+
+ auto& classifier = ctx.Get<ImgClassClassifier&>("classifier");
+ classifier.GetClassificationResults(outputTensor, results,
+ ctx.Get<std::vector <std::string>&>("labels"),
+ 5);
+
+ /* Add results to context for access outside handler. */
+ ctx.Set<std::vector<ClassificationResult>>("results", results);
+
+#if VERIFY_TEST_OUTPUT
+ arm::app::DumpTensor(outputTensor);
+#endif /* VERIFY_TEST_OUTPUT */
+
+ if (!_PresentInferenceResult(platform, results)) {
+ return false;
+ }
+
+ _IncrementAppCtxImageIdx(ctx);
+
+ } while (runAll && ctx.Get<uint32_t>("imgIndex") != curImIdx);
+
+ return true;
+ }
+
+ static bool _LoadImageIntoTensor(const 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 %u (max: %u)\n", imIdx,
+ NUMBER_OF_FILES - 1);
+ return false;
+ }
+
+ memcpy(inputTensor->data.data, imgSrc, copySz);
+ debug("Image %u loaded\n", imIdx);
+ return true;
+ }
+
+ static void _IncrementAppCtxImageIdx(ApplicationContext& ctx)
+ {
+ auto curImIdx = ctx.Get<uint32_t>("imgIndex");
+
+ if (curImIdx + 1 >= NUMBER_OF_FILES) {
+ ctx.Set<uint32_t>("imgIndex", 0);
+ return;
+ }
+ ++curImIdx;
+ ctx.Set<uint32_t>("imgIndex", curImIdx);
+ }
+
+ static bool _SetAppCtxImageIdx(ApplicationContext& ctx, const uint32_t idx)
+ {
+ if (idx >= NUMBER_OF_FILES) {
+ printf_err("Invalid idx %u (expected less than %u)\n",
+ idx, NUMBER_OF_FILES);
+ return false;
+ }
+ ctx.Set<uint32_t>("imgIndex", idx);
+ return true;
+ }
+
+ static bool _PresentInferenceResult(hal_platform& platform,
+ const std::vector<ClassificationResult>& results)
+ {
+ constexpr uint32_t dataPsnTxtStartX1 = 150;
+ constexpr uint32_t dataPsnTxtStartY1 = 30;
+
+ constexpr uint32_t dataPsnTxtStartX2 = 10;
+ constexpr uint32_t dataPsnTxtStartY2 = 150;
+
+ constexpr uint32_t dataPsnTxtYIncr = 16; /* Row index increment. */
+
+ platform.data_psn->set_text_color(COLOR_GREEN);
+
+ /* Display each result. */
+ uint32_t rowIdx1 = dataPsnTxtStartY1 + 2 * dataPsnTxtYIncr;
+ uint32_t rowIdx2 = dataPsnTxtStartY2;
+
+ for (uint32_t i = 0; i < results.size(); ++i) {
+ std::string resultStr =
+ std::to_string(i + 1) + ") " +
+ std::to_string(results[i].m_labelIdx) +
+ " (" + std::to_string(results[i].m_normalisedVal) + ")";
+
+ platform.data_psn->present_data_text(
+ resultStr.c_str(), resultStr.size(),
+ dataPsnTxtStartX1, rowIdx1, 0);
+ rowIdx1 += dataPsnTxtYIncr;
+
+ resultStr = std::to_string(i + 1) + ") " + results[i].m_label;
+ platform.data_psn->present_data_text(
+ resultStr.c_str(), resultStr.size(),
+ dataPsnTxtStartX2, rowIdx2, 0);
+ rowIdx2 += dataPsnTxtYIncr;
+
+ info("%u) %u (%f) -> %s\n", i, results[i].m_labelIdx,
+ results[i].m_normalisedVal, results[i].m_label.c_str());
+ }
+
+ return true;
+ }
+
+ static void ConvertImgToInt8(void* data, const size_t kMaxImageSize)
+ {
+ auto* tmp_req_data = (uint8_t*) data;
+ auto* tmp_signed_req_data = (int8_t*) data;
+
+ for (size_t i = 0; i < kMaxImageSize; i++) {
+ tmp_signed_req_data[i] = (int8_t) (
+ (int32_t) (tmp_req_data[i]) - 128);
+ }
+ }
+
+} /* namespace app */
+} /* namespace arm */
diff --git a/source/use_case/img_class/usecase.cmake b/source/use_case/img_class/usecase.cmake
new file mode 100644
index 0000000..440eabe
--- /dev/null
+++ b/source/use_case/img_class/usecase.cmake
@@ -0,0 +1,125 @@
+#----------------------------------------------------------------------------
+# 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.
+#----------------------------------------------------------------------------
+
+# If the path to a directory or source file has been defined,
+# get the type here (FILEPATH or PATH):
+if (DEFINED ${use_case}_FILE_PATH)
+ get_path_type(${${use_case}_FILE_PATH} PATH_TYPE)
+ # Set the default type if path is not a dir or file path (or undefined)
+ if (NOT ${PATH_TYPE} STREQUAL PATH AND NOT ${PATH_TYPE} STREQUAL FILEPATH)
+ message(FATAL_ERROR "Invalid ${use_case}_FILE_PATH. It should be a dir or file path.")
+ endif()
+else()
+ # Default is a directory path
+ set(PATH_TYPE PATH)
+endif()
+
+message(STATUS "${use_case}_FILE_PATH is of type: ${PATH_TYPE}")
+
+USER_OPTION(${use_case}_FILE_PATH "Directory with custom image files to use, or path to a single image, in the evaluation application"
+ ${CMAKE_CURRENT_SOURCE_DIR}/resources/${use_case}/samples/
+ ${PATH_TYPE})
+
+USER_OPTION(${use_case}_IMAGE_SIZE "Square image size in pixels. Images will be resized to this size."
+ 224
+ STRING)
+
+USER_OPTION(${use_case}_LABELS_TXT_FILE "Labels' txt file for the chosen model"
+ ${CMAKE_CURRENT_SOURCE_DIR}/resources/${use_case}/labels/labels_mobilenet_v2_1.0_224.txt
+ FILEPATH)
+
+# Generate input files
+generate_images_code("${${use_case}_FILE_PATH}"
+ ${SRC_GEN_DIR}
+ ${INC_GEN_DIR}
+ "${${use_case}_IMAGE_SIZE}")
+
+# Generate labels file
+set(${use_case}_LABELS_CPP_FILE Labels)
+generate_labels_code(
+ INPUT "${${use_case}_LABELS_TXT_FILE}"
+ DESTINATION_SRC ${SRC_GEN_DIR}
+ DESTINATION_HDR ${INC_GEN_DIR}
+ OUTPUT_FILENAME "${${use_case}_LABELS_CPP_FILE}"
+)
+
+USER_OPTION(${use_case}_ACTIVATION_BUF_SZ "Activation buffer size for the chosen model"
+ 0x00200000
+ STRING)
+
+# If there is no tflite file pointed to
+if (NOT DEFINED ${use_case}_MODEL_TFLITE_PATH)
+
+ set(MODEL_RESOURCES_DIR ${DOWNLOAD_DEP_DIR}/${use_case})
+ file(MAKE_DIRECTORY ${MODEL_RESOURCES_DIR})
+ set(MODEL_FILENAME mobilenet_v2_1.0_224_quantized_1_default_1.tflite)
+ set(DEFAULT_MODEL_PATH ${MODEL_RESOURCES_DIR}/${MODEL_FILENAME})
+
+ # Download the default model
+ set(ZOO_COMMON_SUBPATH "models/image_classification/mobilenet_v2_1.0_224/tflite_uint8")
+ set(ZOO_MODEL_SUBPATH "${ZOO_COMMON_SUBPATH}/${MODEL_FILENAME}")
+
+ download_file_from_modelzoo(${ZOO_MODEL_SUBPATH} ${DEFAULT_MODEL_PATH})
+
+ if (ETHOS_U55_ENABLED)
+ message(STATUS
+ "Ethos-U55 is enabled, but the model downloaded is not optimized by vela. "
+ "To use Ethos-U55 acceleration, optimise the downloaded model and pass it "
+ "as ${use_case}_MODEL_TFLITE_PATH to the CMake configuration.")
+ endif()
+
+ # If the target platform is native
+ if (${TARGET_PLATFORM} STREQUAL native)
+
+ # Download test vectors
+ set(ZOO_TEST_IFM_SUBPATH "${ZOO_COMMON_SUBPATH}/testing_input/input/0.npy")
+ set(ZOO_TEST_OFM_SUBPATH "${ZOO_COMMON_SUBPATH}/testing_output/output/0.npy")
+
+ set(${use_case}_TEST_IFM ${MODEL_RESOURCES_DIR}/ifm0.npy CACHE FILEPATH
+ "Input test vector for ${use_case}")
+ set(${use_case}_TEST_OFM ${MODEL_RESOURCES_DIR}/ofm0.npy CACHE FILEPATH
+ "Input test vector for ${use_case}")
+
+ download_file_from_modelzoo(${ZOO_TEST_IFM_SUBPATH} ${${use_case}_TEST_IFM})
+ download_file_from_modelzoo(${ZOO_TEST_OFM_SUBPATH} ${${use_case}_TEST_OFM})
+
+ set(TEST_SRC_GEN_DIR ${CMAKE_BINARY_DIR}/generated/${use_case}/tests/src)
+ set(TEST_INC_GEN_DIR ${CMAKE_BINARY_DIR}/generated/${use_case}/tests/include)
+ file(MAKE_DIRECTORY ${TEST_SRC_GEN_DIR} ${TEST_INC_GEN_DIR})
+
+ # Generate test data files to be included in x86 tests
+ generate_test_data_code(
+ INPUT_DIR "${DOWNLOAD_DEP_DIR}/${use_case}"
+ DESTINATION_SRC ${TEST_SRC_GEN_DIR}
+ DESTINATION_HDR ${TEST_INC_GEN_DIR}
+ USECASE "${use_case}")
+ endif()
+
+else()
+ set(DEFAULT_MODEL_PATH "N/A")
+endif()
+
+USER_OPTION(${use_case}_MODEL_TFLITE_PATH "NN models file to be used in the evaluation application. Model files must be in tflite format."
+ ${DEFAULT_MODEL_PATH}
+ FILEPATH
+ )
+
+# Generate model file
+generate_tflite_code(
+ MODEL_PATH ${${use_case}_MODEL_TFLITE_PATH}
+ DESTINATION ${SRC_GEN_DIR}
+ )