74 lines
3.4 KiB
C++
74 lines
3.4 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 "LaplacianPyramid.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/Gaussian5x5.h"
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#include "tests/validation/reference/GaussianPyramidHalf.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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std::vector<SimpleTensor<U>> laplacian_pyramid(const SimpleTensor<T> &src, SimpleTensor<U> &dst, size_t num_levels, BorderMode border_mode, uint8_t constant_border_value)
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{
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std::vector<SimpleTensor<T>> pyramid_conv;
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std::vector<SimpleTensor<U>> pyramid_dst;
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// First, a Gaussian pyramid with SCALE_PYRAMID_HALF is created
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std::vector<SimpleTensor<T>> gaussian_level_pyramid = reference::gaussian_pyramid_half(src, border_mode, constant_border_value, num_levels);
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// For each level i, the corresponding image Ii is blurred with Gaussian 5x5
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// filter, and the difference between the two images is the corresponding
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// level Li of the Laplacian pyramid
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for(size_t i = 0; i < num_levels; ++i)
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{
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const SimpleTensor<T> level_filtered = reference::gaussian5x5(gaussian_level_pyramid[i], border_mode, constant_border_value);
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pyramid_conv.push_back(level_filtered);
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const SimpleTensor<U> level_filtered_converted = depth_convert<T, U>(level_filtered, DataType::S16, ConvertPolicy::WRAP, 0);
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const SimpleTensor<U> gaussian_level_converted = depth_convert<T, U>(gaussian_level_pyramid[i], DataType::S16, ConvertPolicy::WRAP, 0);
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const SimpleTensor<U> level_sub = reference::arithmetic_operation<U>(reference::ArithmeticOperation::SUB, gaussian_level_converted, level_filtered_converted, dst.data_type(), ConvertPolicy::WRAP);
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pyramid_dst.push_back(level_sub);
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}
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// Return the lowest resolution image and the pyramid
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dst = depth_convert<T, U>(pyramid_conv[num_levels - 1], DataType::S16, ConvertPolicy::WRAP, 0);
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return pyramid_dst;
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}
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template std::vector<SimpleTensor<int16_t>> laplacian_pyramid(const SimpleTensor<uint8_t> &src, SimpleTensor<int16_t> &dst, size_t num_levels, BorderMode border_mode, uint8_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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