70 lines
3.1 KiB
C++
70 lines
3.1 KiB
C++
/*
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* Copyright (c) 2018 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "LaplacianReconstruct.h"
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#include "arm_compute/core/Types.h"
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#include "tests/validation/reference/ArithmeticOperations.h"
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#include "tests/validation/reference/DepthConvertLayer.h"
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#include "tests/validation/reference/Scale.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace reference
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{
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template <typename T, typename U>
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SimpleTensor<U> laplacian_reconstruct(const std::vector<SimpleTensor<T>> &pyramid, const SimpleTensor<T> &low_res, BorderMode border_mode, T constant_border_value)
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{
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std::vector<SimpleTensor<T>> tmp_pyramid(pyramid);
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const size_t last_level = pyramid.size() - 1;
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const DataType data_type = low_res.data_type();
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// input + L(n-1)
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tmp_pyramid[last_level] = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, low_res, pyramid[last_level], data_type, ConvertPolicy::SATURATE);
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// Scale levels n-1 to 1, and add levels n-2 to 0
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for(size_t i = last_level; i-- > 0;)
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{
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const float scale_x = static_cast<float>(tmp_pyramid[i].shape().x()) / tmp_pyramid[i + 1].shape().x();
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const float scale_y = static_cast<float>(tmp_pyramid[i].shape().y()) / tmp_pyramid[i + 1].shape().y();
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tmp_pyramid[i] = reference::scale(tmp_pyramid[i + 1], scale_x, scale_y, InterpolationPolicy::NEAREST_NEIGHBOR,
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border_mode, constant_border_value, SamplingPolicy::CENTER, false);
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tmp_pyramid[i] = reference::arithmetic_operation(reference::ArithmeticOperation::ADD, tmp_pyramid[i], pyramid[i], data_type, ConvertPolicy::SATURATE);
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}
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return reference::depth_convert<T, U>(tmp_pyramid[0], DataType::U8, ConvertPolicy::SATURATE, 0);
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}
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template SimpleTensor<uint8_t> laplacian_reconstruct(const std::vector<SimpleTensor<int16_t>> &pyramid, const SimpleTensor<int16_t> &low_res, BorderMode border_mode, int16_t constant_border_value);
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} // namespace reference
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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