Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/source/application/main/UseCaseCommonUtils.cc b/source/application/main/UseCaseCommonUtils.cc
new file mode 100644
index 0000000..4ea5e4d
--- /dev/null
+++ b/source/application/main/UseCaseCommonUtils.cc
@@ -0,0 +1,119 @@
+/*
+ * 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 "UseCaseCommonUtils.hpp"
+
+#include "InputFiles.hpp"
+
+namespace arm {
+namespace app {
+
+ bool RunInference(hal_platform& platform, arm::app::Model& model)
+ {
+ Profiler profiler{&platform, "Inference"};
+ profiler.StartProfiling();
+
+ bool runInf = model.RunInference();
+
+ profiler.StopProfiling();
+ std::string profileResults = profiler.GetResultsAndReset();
+ info("%s\n", profileResults.c_str());
+
+ return runInf;
+ }
+
+ int ReadUserInputAsInt(hal_platform& platform)
+ {
+ char chInput[128];
+ memset(chInput, 0, sizeof(chInput));
+
+ platform.data_acq->get_input(chInput, sizeof(chInput));
+ return atoi(chInput);
+ }
+
+ void DumpTensor(TfLiteTensor* tensor, const size_t lineBreakForNumElements)
+ {
+ char strhex[8];
+ std::string strdump;
+
+ if (!tensor) {
+ printf_err("invalid tensor\n");
+ return;
+ }
+
+ const uint32_t tensorSz = tensor->bytes;
+ const uint8_t* tensorData = tflite::GetTensorData<uint8_t>(tensor);
+
+ for (size_t i = 0; i < tensorSz; ++i) {
+ if (0 == i % lineBreakForNumElements) {
+ printf("%s\n\t", strdump.c_str());
+ strdump.clear();
+ }
+ snprintf(strhex, sizeof(strhex) - 1,
+ "0x%02x, ", tensorData[i]);
+ strdump += std::string(strhex);
+ }
+
+ if (strdump.size()) {
+ printf("%s\n", strdump.c_str());
+ }
+ }
+
+ bool ListFilesHandler(ApplicationContext& ctx)
+ {
+ auto& model = ctx.Get<Model&>("model");
+ auto& platform = ctx.Get<hal_platform&>("platform");
+
+ constexpr uint32_t dataPsnTxtStartX = 20;
+ constexpr uint32_t dataPsnTxtStartY = 40;
+
+ if (!model.IsInited()) {
+ printf_err("Model is not initialised! Terminating processing.\n");
+ return false;
+ }
+
+ /* Clear the LCD */
+ platform.data_psn->clear(COLOR_BLACK);
+
+ /* Show the total number of embedded files. */
+ std::string strNumFiles = std::string{"Total Number of Files: "} +
+ std::to_string(NUMBER_OF_FILES);
+ platform.data_psn->present_data_text(strNumFiles.c_str(),
+ strNumFiles.size(),
+ dataPsnTxtStartX,
+ dataPsnTxtStartY,
+ 0);
+
+#if NUMBER_OF_FILES > 0
+ constexpr uint32_t dataPsnTxtYIncr = 16;
+ info("List of Files:\n");
+ uint32_t yVal = dataPsnTxtStartY + dataPsnTxtYIncr;
+ for (uint32_t i = 0; i < NUMBER_OF_FILES; ++i, yVal += dataPsnTxtYIncr) {
+
+ std::string currentFilename{get_filename(i)};
+ platform.data_psn->present_data_text(currentFilename.c_str(),
+ currentFilename.size(),
+ dataPsnTxtStartX, yVal, 0);
+
+ info("\t%u => %s\n", i, currentFilename.c_str());
+ }
+#endif /* NUMBER_OF_FILES > 0 */
+
+ return true;
+ }
+
+} /* namespace app */
+} /* namespace arm */
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