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80 lines
2.9 KiB
C++
80 lines
2.9 KiB
C++
//
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// Copyright 2019 Mateusz Loskot <mateusz at loskot dot net>
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//
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// Distributed under the Boost Software License, Version 1.0
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// See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt
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//
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#include <boost/gil.hpp>
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#include <boost/gil/extension/numeric/convolve.hpp>
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#include <tuple>
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#include <type_traits>
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#define BOOST_TEST_MODULE test_ext_numeric_colvolve_2d
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#include "unit_test.hpp"
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#include "unit_test_utility.hpp"
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#include "test_fixture.hpp"
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#include "core/image/test_fixture.hpp"
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namespace gil = boost::gil;
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namespace fixture = boost::gil::test::fixture;
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BOOST_AUTO_TEST_SUITE(convolve_1d)
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BOOST_AUTO_TEST_CASE_TEMPLATE(image_1x1_kernel_1x1_identity, Image, fixture::image_types)
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{
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auto const img = fixture::create_image<Image>(1, 1, 7);
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Image img_out(img);
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using pixel_t = typename Image::value_type;
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using channel_t = typename gil::channel_type<pixel_t>::type;
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auto const kernel = fixture::create_kernel<channel_t>({1});
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gil::convolve_1d<pixel_t>(const_view(img_out), kernel, view(img_out));
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// 1x1 kernel reduces convolution to multiplication
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BOOST_TEST(gil::const_view(img).front() == gil::const_view(img_out).front());
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}
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BOOST_AUTO_TEST_CASE_TEMPLATE(image_1x1_kernel_3x3_identity, Image, fixture::image_types)
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{
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auto const img = fixture::create_image<Image>(1, 1, 7);
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Image img_out(img);
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using pixel_t = typename Image::value_type;
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using channel_t = typename gil::channel_type<pixel_t>::type;
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auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
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gil::convolve_1d<pixel_t>(const_view(img_out), kernel, view(img_out));
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BOOST_TEST(gil::const_view(img).front() == gil::const_view(img_out).front());
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}
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BOOST_AUTO_TEST_CASE_TEMPLATE(image_3x3_kernel_3x3_identity, Image, fixture::image_types)
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{
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using pixel_t = typename Image::value_type;
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using channel_t = typename gil::channel_type<pixel_t>::type;
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auto const img = fixture::generate_image<Image>(3, 3, fixture::random_value<channel_t>{});
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Image img_out(img);
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auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
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gil::convolve_1d<pixel_t>(const_view(img_out), kernel, view(img_out));
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BOOST_TEST(gil::equal_pixels(gil::const_view(img), gil::const_view(img_out)));
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}
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BOOST_AUTO_TEST_CASE_TEMPLATE(image_5x5_kernel_3x3_identity, Image, fixture::image_types)
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{
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using pixel_t = typename Image::value_type;
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using channel_t = typename gil::channel_type<pixel_t>::type;
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auto const img = fixture::generate_image<Image>(5, 5, fixture::random_value<channel_t>{});
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Image img_out(img);
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auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
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gil::convolve_1d<pixel_t>(const_view(img_out), kernel, view(img_out));
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// TODO: Test different boundary options
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BOOST_TEST(gil::equal_pixels(gil::const_view(img), gil::const_view(img_out)));
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}
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BOOST_AUTO_TEST_SUITE_END()
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