| /* |
| * 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(arm::app::Model& model, Profiler& profiler) |
| { |
| profiler.StartProfiling("Inference"); |
| bool runInf = model.RunInference(); |
| profiler.StopProfiling(); |
| |
| 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 */ |