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Diffstat (limited to 'source/application/api/use_case/ad/include')
4 files changed, 617 insertions, 0 deletions
diff --git a/source/application/api/use_case/ad/include/AdMelSpectrogram.hpp b/source/application/api/use_case/ad/include/AdMelSpectrogram.hpp new file mode 100644 index 0000000..05c5bfc --- /dev/null +++ b/source/application/api/use_case/ad/include/AdMelSpectrogram.hpp @@ -0,0 +1,97 @@ +/* + * 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 ADMELSPECTROGRAM_HPP +#define ADMELSPECTROGRAM_HPP + +#include "MelSpectrogram.hpp" + +namespace arm { +namespace app { +namespace audio { + + /* Class to provide anomaly detection specific Mel Spectrogram calculation requirements */ + class AdMelSpectrogram : public MelSpectrogram { + + public: + static constexpr uint32_t ms_defaultSamplingFreq = 16000; + static constexpr uint32_t ms_defaultNumFbankBins = 64; + static constexpr uint32_t ms_defaultMelLoFreq = 0; + static constexpr uint32_t ms_defaultMelHiFreq = 8000; + static constexpr bool ms_defaultUseHtkMethod = false; + + explicit AdMelSpectrogram(const size_t frameLen) + : MelSpectrogram(MelSpecParams( + ms_defaultSamplingFreq, ms_defaultNumFbankBins, + ms_defaultMelLoFreq, ms_defaultMelHiFreq, + frameLen, ms_defaultUseHtkMethod)) + {} + + AdMelSpectrogram() = delete; + ~AdMelSpectrogram() = default; + + protected: + + /** + * @brief Overrides base class implementation of this function. + * @param[in] fftVec Vector populated with FFT magnitudes + * @param[in] melFilterBank 2D Vector with filter bank weights + * @param[in] filterBankFilterFirst Vector containing the first indices of filter bank + * to be used for each bin. + * @param[in] filterBankFilterLast Vector containing the last indices of filter bank + * to be used for each bin. + * @param[out] melEnergies Pre-allocated vector of MEL energies to be + * populated. + * @return true if successful, false otherwise + */ + virtual bool ApplyMelFilterBank( + std::vector<float>& fftVec, + std::vector<std::vector<float>>& melFilterBank, + std::vector<uint32_t>& filterBankFilterFirst, + std::vector<uint32_t>& filterBankFilterLast, + std::vector<float>& melEnergies) override; + + /** + * @brief Override for the base class implementation convert mel + * energies to logarithmic scale. The difference from + * default behaviour is that the power is converted to dB + * and subsequently clamped. + * @param[in,out] melEnergies - 1D vector of Mel energies + **/ + virtual void ConvertToLogarithmicScale(std::vector<float>& melEnergies) override; + + /** + * @brief Given the low and high Mel values, get the normaliser + * for weights to be applied when populating the filter + * bank. Override for the base class implementation. + * @param[in] leftMel - low Mel frequency value + * @param[in] rightMel - high Mel frequency value + * @param[in] useHTKMethod - bool to signal if HTK method is to be + * used for calculation + * @return Return float value to be applied + * when populating the filter bank. + */ + virtual float GetMelFilterBankNormaliser( + const float& leftMel, + const float& rightMel, + const bool useHTKMethod) override; + }; + +} /* namespace audio */ +} /* namespace app */ +} /* namespace arm */ + +#endif /* ADMELSPECTROGRAM_HPP */ diff --git a/source/application/api/use_case/ad/include/AdModel.hpp b/source/application/api/use_case/ad/include/AdModel.hpp new file mode 100644 index 0000000..0436a89 --- /dev/null +++ b/source/application/api/use_case/ad/include/AdModel.hpp @@ -0,0 +1,55 @@ +/* + * 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. + */ +#ifndef AD_MODEL_HPP +#define AD_MODEL_HPP + +#include "Model.hpp" + +extern const int g_FrameLength; +extern const int g_FrameStride; +extern const float g_ScoreThreshold; +extern const float g_TrainingMean; + +namespace arm { +namespace app { + + class AdModel : 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; + + 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 = 6; + + /* A mutable op resolver instance */ + tflite::MicroMutableOpResolver<ms_maxOpCnt> m_opResolver; + }; + +} /* namespace app */ +} /* namespace arm */ + +#endif /* AD_MODEL_HPP */ diff --git a/source/application/api/use_case/ad/include/AdProcessing.hpp b/source/application/api/use_case/ad/include/AdProcessing.hpp new file mode 100644 index 0000000..abee75e --- /dev/null +++ b/source/application/api/use_case/ad/include/AdProcessing.hpp @@ -0,0 +1,231 @@ +/* + * 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 AD_PROCESSING_HPP +#define AD_PROCESSING_HPP + +#include "BaseProcessing.hpp" +#include "TensorFlowLiteMicro.hpp" +#include "AudioUtils.hpp" +#include "AdMelSpectrogram.hpp" +#include "log_macros.h" + +namespace arm { +namespace app { + + /** + * @brief Pre-processing class for anomaly detection use case. + * Implements methods declared by BasePreProcess and anything else needed + * to populate input tensors ready for inference. + */ + class AdPreProcess : public BasePreProcess { + + public: + /** + * @brief Constructor for AdPreProcess class objects + * @param[in] inputTensor input tensor pointer from the tensor arena. + * @param[in] melSpectrogramFrameLen MEL spectrogram's frame length + * @param[in] melSpectrogramFrameStride MEL spectrogram's frame stride + * @param[in] adModelTrainingMean Training mean for the Anomaly detection model being used. + */ + explicit AdPreProcess(TfLiteTensor* inputTensor, + uint32_t melSpectrogramFrameLen, + uint32_t melSpectrogramFrameStride, + float adModelTrainingMean); + + ~AdPreProcess() = default; + + /** + * @brief Function to invoke pre-processing and populate the input vector + * @param input pointer to input data. For anomaly detection, this is the pointer to + * the audio data. + * @param inputSize Size of the data being passed in for pre-processing. + * @return True if successful, false otherwise. + */ + bool DoPreProcess(const void* input, size_t inputSize) override; + + /** + * @brief Getter function for audio window size computed when constructing + * the class object. + * @return Audio window size as 32 bit unsigned integer. + */ + uint32_t GetAudioWindowSize(); + + /** + * @brief Getter function for audio window stride computed when constructing + * the class object. + * @return Audio window stride as 32 bit unsigned integer. + */ + uint32_t GetAudioDataStride(); + + /** + * @brief Setter function for current audio index. This is only used for evaluating + * if previously computed features can be re-used from cache. + */ + void SetAudioWindowIndex(uint32_t idx); + + private: + bool m_validInstance{false}; /**< Indicates the current object is valid. */ + uint32_t m_melSpectrogramFrameLen{}; /**< MEL spectrogram's window frame length */ + uint32_t m_melSpectrogramFrameStride{}; /**< MEL spectrogram's window frame stride */ + uint8_t m_inputResizeScale{}; /**< Downscaling factor for the MEL energy matrix. */ + uint32_t m_numMelSpecVectorsInAudioStride{}; /**< Number of frames to move across the audio. */ + uint32_t m_audioDataWindowSize{}; /**< Audio window size computed based on other parameters. */ + uint32_t m_audioDataStride{}; /**< Audio window stride computed. */ + uint32_t m_numReusedFeatureVectors{}; /**< Number of MEL vectors that can be re-used */ + uint32_t m_audioWindowIndex{}; /**< Current audio window index (from audio's sliding window) */ + + audio::SlidingWindow<const int16_t> m_melWindowSlider; /**< Internal MEL spectrogram window slider */ + audio::AdMelSpectrogram m_melSpec; /**< MEL spectrogram computation object */ + std::function<void + (std::vector<int16_t>&, int, bool, size_t, size_t)> m_featureCalc; /**< Feature calculator object */ + }; + + class AdPostProcess : public BasePostProcess { + public: + /** + * @brief Constructor for AdPostProcess object. + * @param[in] outputTensor Output tensor pointer. + */ + explicit AdPostProcess(TfLiteTensor* outputTensor); + + ~AdPostProcess() = default; + + /** + * @brief Function to do the post-processing on the output tensor. + * @return True if successful, false otherwise. + */ + bool DoPostProcess() override; + + /** + * @brief Getter function for an element from the de-quantised output vector. + * @param index Index of the element to be retrieved. + * @return index represented as a 32 bit floating point number. + */ + float GetOutputValue(uint32_t index); + + private: + TfLiteTensor* m_outputTensor{}; /**< Output tensor pointer */ + std::vector<float> m_dequantizedOutputVec{}; /**< Internal output vector */ + + /** + * @brief De-quantizes and flattens the output tensor into a vector. + * @tparam T template parameter to indicate data type. + * @return True if successful, false otherwise. + */ + template<typename T> + bool Dequantize() + { + TfLiteTensor* tensor = this->m_outputTensor; + if (tensor == nullptr) { + printf_err("Invalid output tensor.\n"); + return false; + } + T* tensorData = tflite::GetTensorData<T>(tensor); + + uint32_t totalOutputSize = 1; + for (int inputDim = 0; inputDim < tensor->dims->size; inputDim++){ + totalOutputSize *= tensor->dims->data[inputDim]; + } + + /* For getting the floating point values, we need quantization parameters */ + QuantParams quantParams = GetTensorQuantParams(tensor); + + this->m_dequantizedOutputVec = std::vector<float>(totalOutputSize, 0); + + for (size_t i = 0; i < totalOutputSize; ++i) { + this->m_dequantizedOutputVec[i] = quantParams.scale * (tensorData[i] - quantParams.offset); + } + + return true; + } + }; + + /* Templated instances available: */ + template bool AdPostProcess::Dequantize<int8_t>(); + + /** + * @brief Generic feature calculator factory. + * + * Returns lambda function to compute features using features cache. + * Real features math is done by a lambda function provided as a parameter. + * Features are written to input tensor memory. + * + * @tparam T feature vector type. + * @param inputTensor model input tensor pointer. + * @param cacheSize number of feature vectors to cache. Defined by the sliding window overlap. + * @param compute features calculator function. + * @return lambda function to compute features. + */ + template<class T> + std::function<void (std::vector<int16_t>&, size_t, bool, size_t, size_t)> + FeatureCalc(TfLiteTensor* inputTensor, size_t cacheSize, + std::function<std::vector<T> (std::vector<int16_t>& )> compute) + { + /* Feature cache to be captured by lambda function*/ + static std::vector<std::vector<T>> featureCache = std::vector<std::vector<T>>(cacheSize); + + return [=](std::vector<int16_t>& audioDataWindow, + size_t index, + bool useCache, + size_t featuresOverlapIndex, + size_t resizeScale) + { + T* tensorData = tflite::GetTensorData<T>(inputTensor); + std::vector<T> features; + + /* Reuse features from cache if cache is ready and sliding windows overlap. + * Overlap is in the beginning of sliding window with a size of a feature cache. */ + if (useCache && index < featureCache.size()) { + features = std::move(featureCache[index]); + } else { + features = std::move(compute(audioDataWindow)); + } + auto size = features.size() / resizeScale; + auto sizeBytes = sizeof(T); + + /* Input should be transposed and "resized" by skipping elements. */ + for (size_t outIndex = 0; outIndex < size; outIndex++) { + std::memcpy(tensorData + (outIndex*size) + index, &features[outIndex*resizeScale], sizeBytes); + } + + /* Start renewing cache as soon iteration goes out of the windows overlap. */ + if (index >= featuresOverlapIndex / resizeScale) { + featureCache[index - featuresOverlapIndex / resizeScale] = std::move(features); + } + }; + } + + template std::function<void (std::vector<int16_t>&, size_t , bool, size_t, size_t)> + FeatureCalc<int8_t>(TfLiteTensor* inputTensor, + size_t cacheSize, + std::function<std::vector<int8_t> (std::vector<int16_t>&)> compute); + + template std::function<void(std::vector<int16_t>&, size_t, bool, size_t, size_t)> + FeatureCalc<float>(TfLiteTensor *inputTensor, + size_t cacheSize, + std::function<std::vector<float>(std::vector<int16_t>&)> compute); + + std::function<void (std::vector<int16_t>&, int, bool, size_t, size_t)> + GetFeatureCalculator(audio::AdMelSpectrogram& melSpec, + TfLiteTensor* inputTensor, + size_t cacheSize, + float trainingMean); + +} /* namespace app */ +} /* namespace arm */ + +#endif /* AD_PROCESSING_HPP */ diff --git a/source/application/api/use_case/ad/include/MelSpectrogram.hpp b/source/application/api/use_case/ad/include/MelSpectrogram.hpp new file mode 100644 index 0000000..d3ea3f7 --- /dev/null +++ b/source/application/api/use_case/ad/include/MelSpectrogram.hpp @@ -0,0 +1,234 @@ +/* + * 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 MELSPECTROGRAM_HPP +#define MELSPECTROGRAM_HPP + +#include "PlatformMath.hpp" + +#include <vector> +#include <cstdint> +#include <cmath> +#include <limits> +#include <string> + +namespace arm { +namespace app { +namespace audio { + + /* Mel Spectrogram consolidated parameters */ + class MelSpecParams { + public: + float m_samplingFreq; + uint32_t m_numFbankBins; + float m_melLoFreq; + float m_melHiFreq; + uint32_t m_frameLen; + uint32_t m_frameLenPadded; + bool m_useHtkMethod; + + /** @brief Constructor */ + MelSpecParams(const float samplingFreq, const uint32_t numFbankBins, + const float melLoFreq, const float melHiFreq, + const uint32_t frameLen, const bool useHtkMethod); + + MelSpecParams() = delete; + ~MelSpecParams() = default; + + /** @brief String representation of parameters */ + std::string Str() const; + }; + + /** + * @brief Class for Mel Spectrogram feature extraction. + * Based on https://github.com/ARM-software/ML-KWS-for-MCU/blob/master/Deployment/Source/MFCC/mfcc.cpp + * This class is designed to be generic and self-sufficient but + * certain calculation routines can be overridden to accommodate + * use-case specific requirements. + */ + class MelSpectrogram { + + public: + /** + * @brief Extract Mel Spectrogram for one single small frame of + * audio data e.g. 640 samples. + * @param[in] audioData Vector of audio samples to calculate + * features for. + * @param[in] trainingMean Value to subtract from the the computed mel spectrogram, default 0. + * @return Vector of extracted Mel Spectrogram features. + **/ + std::vector<float> ComputeMelSpec(const std::vector<int16_t>& audioData, float trainingMean = 0); + + /** + * @brief Constructor + * @param[in] params Mel Spectrogram parameters + */ + explicit MelSpectrogram(const MelSpecParams& params); + + MelSpectrogram() = delete; + ~MelSpectrogram() = default; + + /** @brief Initialise */ + void Init(); + + /** + * @brief Extract Mel Spectrogram features and quantise for one single small + * frame of audio data e.g. 640 samples. + * @param[in] audioData Vector of audio samples to calculate + * features for. + * @param[in] quantScale quantisation scale. + * @param[in] quantOffset quantisation offset. + * @param[in] trainingMean training mean. + * @return Vector of extracted quantised Mel Spectrogram features. + **/ + template<typename T> + std::vector<T> MelSpecComputeQuant(const std::vector<int16_t>& audioData, + const float quantScale, + const int quantOffset, + float trainingMean = 0) + { + this->ComputeMelSpec(audioData, trainingMean); + float minVal = std::numeric_limits<T>::min(); + float maxVal = std::numeric_limits<T>::max(); + + std::vector<T> melSpecOut(this->m_params.m_numFbankBins); + const size_t numFbankBins = this->m_params.m_numFbankBins; + + /* Quantize to T. */ + for (size_t k = 0; k < numFbankBins; ++k) { + auto quantizedEnergy = std::round(((this->m_melEnergies[k]) / quantScale) + quantOffset); + melSpecOut[k] = static_cast<T>(std::min<float>(std::max<float>(quantizedEnergy, minVal), maxVal)); + } + + return melSpecOut; + } + + /* Constants */ + static constexpr float ms_logStep = /*logf(6.4)*/ 1.8562979903656 / 27.0; + static constexpr float ms_freqStep = 200.0 / 3; + static constexpr float ms_minLogHz = 1000.0; + static constexpr float ms_minLogMel = ms_minLogHz / ms_freqStep; + + protected: + /** + * @brief Project input frequency to Mel Scale. + * @param[in] freq input frequency in floating point + * @param[in] useHTKMethod bool to signal if HTK method is to be + * used for calculation + * @return Mel transformed frequency in floating point + **/ + static float MelScale(const float freq, + const bool useHTKMethod = true); + + /** + * @brief Inverse Mel transform - convert MEL warped frequency + * back to normal frequency + * @param[in] melFreq Mel frequency in floating point + * @param[in] useHTKMethod bool to signal if HTK method is to be + * used for calculation + * @return Real world frequency in floating point + **/ + static float InverseMelScale(const float melFreq, + const bool useHTKMethod = true); + + /** + * @brief Populates MEL energies after applying the MEL filter + * bank weights and adding them up to be placed into + * bins, according to the filter bank's first and last + * indices (pre-computed for each filter bank element + * by CreateMelFilterBank function). + * @param[in] fftVec Vector populated with FFT magnitudes + * @param[in] melFilterBank 2D Vector with filter bank weights + * @param[in] filterBankFilterFirst Vector containing the first indices of filter bank + * to be used for each bin. + * @param[in] filterBankFilterLast Vector containing the last indices of filter bank + * to be used for each bin. + * @param[out] melEnergies Pre-allocated vector of MEL energies to be + * populated. + * @return true if successful, false otherwise + */ + virtual bool ApplyMelFilterBank( + std::vector<float>& fftVec, + std::vector<std::vector<float>>& melFilterBank, + std::vector<uint32_t>& filterBankFilterFirst, + std::vector<uint32_t>& filterBankFilterLast, + std::vector<float>& melEnergies); + + /** + * @brief Converts the Mel energies for logarithmic scale + * @param[in,out] melEnergies 1D vector of Mel energies + **/ + virtual void ConvertToLogarithmicScale(std::vector<float>& melEnergies); + + /** + * @brief Given the low and high Mel values, get the normaliser + * for weights to be applied when populating the filter + * bank. + * @param[in] leftMel low Mel frequency value + * @param[in] rightMel high Mel frequency value + * @param[in] useHTKMethod bool to signal if HTK method is to be + * used for calculation + * @return Return float value to be applied + * when populating the filter bank. + */ + virtual float GetMelFilterBankNormaliser( + const float& leftMel, + const float& rightMel, + const bool useHTKMethod); + + private: + MelSpecParams m_params; + std::vector<float> m_frame; + std::vector<float> m_buffer; + std::vector<float> m_melEnergies; + std::vector<float> m_windowFunc; + std::vector<std::vector<float>> m_melFilterBank; + std::vector<uint32_t> m_filterBankFilterFirst; + std::vector<uint32_t> m_filterBankFilterLast; + bool m_filterBankInitialised; + arm::app::math::FftInstance m_fftInstance; + + /** + * @brief Initialises the filter banks. + **/ + void InitMelFilterBank(); + + /** + * @brief Signals whether the instance of MelSpectrogram has had its + * required buffers initialised + * @return True if initialised, false otherwise + **/ + bool IsMelFilterBankInited() const; + + /** + * @brief Create mel filter banks for Mel Spectrogram calculation. + * @return 2D vector of floats + **/ + std::vector<std::vector<float>> CreateMelFilterBank(); + + /** + * @brief Computes the magnitude from an interleaved complex array + **/ + void ConvertToPowerSpectrum(); + + }; + +} /* namespace audio */ +} /* namespace app */ +} /* namespace arm */ + + +#endif /* MELSPECTROGRAM_HPP */ |