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/*
* 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, bool rgb2Gray)
:m_inputTensor{inputTensor},
m_rgb2Gray{rgb2Gray}
{}
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);
uint8_t* unsignedDstPtr = this->m_inputTensor->data.uint8;
if (this->m_rgb2Gray) {
image::RgbToGrayscale(input, unsignedDstPtr, inputSize);
} else {
std::memcpy(unsignedDstPtr, input, 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);
int8_t* signedDstPtr = this->m_inputTensor->data.int8;
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 */
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