| /* |
| * 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. |
| */ |
| #include "InputFiles.hpp" /* For input images. */ |
| #include "Labels_micronetkws.hpp" /* For MicroNetKws label strings. */ |
| #include "Labels_wav2letter.hpp" /* For Wav2Letter label strings. */ |
| #include "Classifier.hpp" /* KWS classifier. */ |
| #include "AsrClassifier.hpp" /* ASR classifier. */ |
| #include "MicroNetKwsModel.hpp" /* KWS model class for running inference. */ |
| #include "Wav2LetterModel.hpp" /* ASR model class for running inference. */ |
| #include "UseCaseCommonUtils.hpp" /* Utils functions. */ |
| #include "UseCaseHandler.hpp" /* Handlers for different user options. */ |
| #include "log_macros.h" /* Logging functions */ |
| #include "BufAttributes.hpp" /* Buffer attributes to be applied */ |
| |
| namespace arm { |
| namespace app { |
| |
| namespace asr { |
| extern uint8_t* GetModelPointer(); |
| extern size_t GetModelLen(); |
| } /* namespace asr */ |
| |
| namespace kws { |
| extern uint8_t* GetModelPointer(); |
| extern size_t GetModelLen(); |
| } /* namespace kws */ |
| static uint8_t tensorArena[ACTIVATION_BUF_SZ] ACTIVATION_BUF_ATTRIBUTE; |
| } /* namespace app */ |
| } /* namespace arm */ |
| |
| using KwsClassifier = 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_AUDIO_CLIPS /* List the current baked audio clips. */ |
| }; |
| |
| static void DisplayMenu() |
| { |
| printf("\n\n"); |
| printf("User input required\n"); |
| printf("Enter option number from:\n\n"); |
| printf(" %u. Classify next audio clip\n", MENU_OPT_RUN_INF_NEXT); |
| printf(" %u. Classify audio clip at chosen index\n", MENU_OPT_RUN_INF_CHOSEN); |
| printf(" %u. Run classification on all audio clips\n", MENU_OPT_RUN_INF_ALL); |
| printf(" %u. Show NN model info\n", MENU_OPT_SHOW_MODEL_INFO); |
| printf(" %u. List audio clips\n\n", MENU_OPT_LIST_AUDIO_CLIPS); |
| printf(" Choice: "); |
| fflush(stdout); |
| } |
| |
| /** @brief Verify input and output tensor are of certain min dimensions. */ |
| static bool VerifyTensorDimensions(const arm::app::Model& model); |
| |
| void main_loop() |
| { |
| /* Model wrapper objects. */ |
| arm::app::MicroNetKwsModel kwsModel; |
| arm::app::Wav2LetterModel asrModel; |
| |
| /* Load the models. */ |
| if (!kwsModel.Init(arm::app::tensorArena, |
| sizeof(arm::app::tensorArena), |
| arm::app::kws::GetModelPointer(), |
| arm::app::kws::GetModelLen())) { |
| printf_err("Failed to initialise KWS model\n"); |
| return; |
| } |
| |
| /* Initialise the asr model using the same allocator from KWS |
| * to re-use the tensor arena. */ |
| if (!asrModel.Init(arm::app::tensorArena, |
| sizeof(arm::app::tensorArena), |
| arm::app::asr::GetModelPointer(), |
| arm::app::asr::GetModelLen(), |
| kwsModel.GetAllocator())) { |
| printf_err("Failed to initialise ASR model\n"); |
| return; |
| } else if (!VerifyTensorDimensions(asrModel)) { |
| printf_err("Model's input or output dimension verification failed\n"); |
| return; |
| } |
| |
| /* Instantiate application context. */ |
| arm::app::ApplicationContext caseContext; |
| |
| arm::app::Profiler profiler{"kws_asr"}; |
| caseContext.Set<arm::app::Profiler&>("profiler", profiler); |
| caseContext.Set<arm::app::Model&>("kwsModel", kwsModel); |
| caseContext.Set<arm::app::Model&>("asrModel", asrModel); |
| caseContext.Set<uint32_t>("clipIndex", 0); |
| caseContext.Set<uint32_t>("ctxLen", arm::app::asr::g_ctxLen); /* Left and right context length (MFCC feat vectors). */ |
| caseContext.Set<int>("kwsFrameLength", arm::app::kws::g_FrameLength); |
| caseContext.Set<int>("kwsFrameStride", arm::app::kws::g_FrameStride); |
| caseContext.Set<float>("kwsScoreThreshold", arm::app::kws::g_ScoreThreshold); /* Normalised score threshold. */ |
| caseContext.Set<uint32_t >("kwsNumMfcc", arm::app::kws::g_NumMfcc); |
| caseContext.Set<uint32_t >("kwsNumAudioWins", arm::app::kws::g_NumAudioWins); |
| |
| caseContext.Set<int>("asrFrameLength", arm::app::asr::g_FrameLength); |
| caseContext.Set<int>("asrFrameStride", arm::app::asr::g_FrameStride); |
| caseContext.Set<float>("asrScoreThreshold", arm::app::asr::g_ScoreThreshold); /* Normalised score threshold. */ |
| |
| KwsClassifier kwsClassifier; /* Classifier wrapper object. */ |
| arm::app::AsrClassifier asrClassifier; /* Classifier wrapper object. */ |
| caseContext.Set<arm::app::Classifier&>("kwsClassifier", kwsClassifier); |
| caseContext.Set<arm::app::AsrClassifier&>("asrClassifier", asrClassifier); |
| |
| std::vector<std::string> asrLabels; |
| arm::app::asr::GetLabelsVector(asrLabels); |
| std::vector<std::string> kwsLabels; |
| arm::app::kws::GetLabelsVector(kwsLabels); |
| caseContext.Set<const std::vector <std::string>&>("asrLabels", asrLabels); |
| caseContext.Set<const std::vector <std::string>&>("kwsLabels", kwsLabels); |
| |
| /* KWS keyword that triggers ASR and associated checks */ |
| std::string triggerKeyword = std::string("no"); |
| if (std::find(kwsLabels.begin(), kwsLabels.end(), triggerKeyword) != kwsLabels.end()) { |
| caseContext.Set<const std::string &>("triggerKeyword", triggerKeyword); |
| } |
| else { |
| printf_err("Selected trigger keyword not found in labels file\n"); |
| return; |
| } |
| |
| /* 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(); |
| printf("\n"); |
| } |
| switch (menuOption) { |
| case MENU_OPT_RUN_INF_NEXT: |
| executionSuccessful = ClassifyAudioHandler( |
| caseContext, |
| caseContext.Get<uint32_t>("clipIndex"), |
| false); |
| break; |
| case MENU_OPT_RUN_INF_CHOSEN: { |
| printf(" Enter the audio clip index [0, %d]: ", |
| NUMBER_OF_FILES-1); |
| fflush(stdout); |
| auto clipIndex = static_cast<uint32_t>( |
| arm::app::ReadUserInputAsInt()); |
| executionSuccessful = ClassifyAudioHandler(caseContext, |
| clipIndex, |
| false); |
| break; |
| } |
| case MENU_OPT_RUN_INF_ALL: |
| executionSuccessful = ClassifyAudioHandler( |
| caseContext, |
| caseContext.Get<uint32_t>("clipIndex"), |
| true); |
| break; |
| case MENU_OPT_SHOW_MODEL_INFO: |
| executionSuccessful = kwsModel.ShowModelInfoHandler(); |
| executionSuccessful = asrModel.ShowModelInfoHandler(); |
| break; |
| case MENU_OPT_LIST_AUDIO_CLIPS: |
| executionSuccessful = ListFilesHandler(caseContext); |
| break; |
| default: |
| printf("Incorrect choice, try again."); |
| break; |
| } |
| } while (executionSuccessful && bUseMenu); |
| info("Main loop terminated.\n"); |
| } |
| |
| static bool VerifyTensorDimensions(const arm::app::Model& model) |
| { |
| /* Populate tensor related parameters. */ |
| 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; |
| } |
| |
| TfLiteTensor* outputTensor = model.GetOutputTensor(0); |
| if (!outputTensor->dims) { |
| printf_err("Invalid output tensor dims\n"); |
| return false; |
| } else if (outputTensor->dims->size < 3) { |
| printf_err("Output tensor dimension should be >= 3\n"); |
| return false; |
| } |
| |
| return true; |
| } |