| /* |
| * 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. |
| */ |
| #include "VisualWakeWordProcessing.hpp" |
| #include "ImageUtils.hpp" |
| #include "VisualWakeWordModel.hpp" |
| #include "log_macros.h" |
| |
| namespace arm { |
| namespace app { |
| |
| VisualWakeWordPreProcess::VisualWakeWordPreProcess(TfLiteTensor* inputTensor) |
| :m_inputTensor{inputTensor} |
| {} |
| |
| bool VisualWakeWordPreProcess::DoPreProcess(const void* data, size_t inputSize) |
| { |
| if (data == nullptr) { |
| printf_err("Data pointer is null"); |
| } |
| |
| auto input = static_cast<const uint8_t*>(data); |
| |
| auto unsignedDstPtr = static_cast<uint8_t*>(this->m_inputTensor->data.data); |
| |
| /* VWW model has one channel input => Convert image to grayscale here. |
| * We expect images to always be RGB. */ |
| image::RgbToGrayscale(input, unsignedDstPtr, inputSize); |
| |
| /* VWW model pre-processing is image conversion from uint8 to [0,1] float values, |
| * then quantize them with input quantization info. */ |
| QuantParams inQuantParams = GetTensorQuantParams(this->m_inputTensor); |
| |
| auto signedDstPtr = static_cast<int8_t*>(this->m_inputTensor->data.data); |
| for (size_t i = 0; i < this->m_inputTensor->bytes; i++) { |
| auto i_data_int8 = static_cast<int8_t>( |
| ((static_cast<float>(unsignedDstPtr[i]) / 255.0f) / inQuantParams.scale) + inQuantParams.offset |
| ); |
| signedDstPtr[i] = std::min<int8_t>(INT8_MAX, std::max<int8_t>(i_data_int8, INT8_MIN)); |
| } |
| |
| debug("Input tensor populated \n"); |
| |
| return true; |
| } |
| |
| VisualWakeWordPostProcess::VisualWakeWordPostProcess(TfLiteTensor* outputTensor, Classifier& classifier, |
| const std::vector<std::string>& labels, std::vector<ClassificationResult>& results) |
| :m_outputTensor{outputTensor}, |
| m_vwwClassifier{classifier}, |
| m_labels{labels}, |
| m_results{results} |
| {} |
| |
| bool VisualWakeWordPostProcess::DoPostProcess() |
| { |
| return this->m_vwwClassifier.GetClassificationResults( |
| this->m_outputTensor, this->m_results, |
| this->m_labels, 1, true); |
| } |
| |
| } /* namespace app */ |
| } /* namespace arm */ |