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gil/test/extension/numeric/convolve_2d.cpp
Mateusz Łoskot dafcaa169e Extract GIL-specific Boost.Test utilities from test/unit_test.hpp (#338)
Add separate header `test/unit_test_utility.hpp` for printers and
other utilities for better integration of GIL types with Boost.Test.
2019-07-18 17:49:05 +02:00

91 lines
3.2 KiB
C++

//
// Copyright 2019 Mateusz Loskot <mateusz at loskot dot net>
//
// Distributed under the Boost Software License, Version 1.0
// See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt
//
#include <boost/gil.hpp>
#include <boost/gil/extension/numeric/convolve.hpp>
#include <tuple>
#include <type_traits>
#define BOOST_TEST_MODULE test_ext_numeric_colvolve_2d
#include "unit_test.hpp"
#include "unit_test_utility.hpp"
#include "test_fixture.hpp"
#include "core/image/test_fixture.hpp"
namespace gil = boost::gil;
namespace fixture = boost::gil::test::fixture;
namespace {
template <typename Pixel, typename SrcView, typename Kernel, typename DstView>
void convolve2d(SrcView const& src_view, Kernel const& kernel, DstView const& dst_view)
{
gil::convolve_rows<Pixel>(src_view, kernel, dst_view);
gil::convolve_cols<Pixel>(src_view, kernel, dst_view);
}
} // unnamed namespace
BOOST_AUTO_TEST_SUITE(convolve_2d)
BOOST_AUTO_TEST_CASE_TEMPLATE(image_1x1_kernel_1x1_identity, Image, fixture::image_types)
{
auto const img = fixture::create_image<Image>(1, 1, 7);
Image img_out(img);
using pixel_t = typename Image::value_type;
using channel_t = typename gil::channel_type<pixel_t>::type;
auto const kernel = fixture::create_kernel<channel_t>({1});
convolve2d<pixel_t>(const_view(img_out), kernel, view(img_out));
// 1x1 kernel reduces convolution to multiplication
BOOST_TEST(gil::const_view(img).front() == gil::const_view(img_out).front());
}
BOOST_AUTO_TEST_CASE_TEMPLATE(image_1x1_kernel_3x3_identity, Image, fixture::image_types)
{
auto const img = fixture::create_image<Image>(1, 1, 7);
Image img_out(img);
using pixel_t = typename Image::value_type;
using channel_t = typename gil::channel_type<pixel_t>::type;
auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
convolve2d<pixel_t>(const_view(img_out), kernel, view(img_out));
BOOST_TEST(gil::const_view(img).front() == gil::const_view(img_out).front());
}
BOOST_AUTO_TEST_CASE_TEMPLATE(image_3x3_kernel_3x3_identity, Image, fixture::image_types)
{
using pixel_t = typename Image::value_type;
using channel_t = typename gil::channel_type<pixel_t>::type;
auto const img = fixture::generate_image<Image>(3, 3, fixture::random_value<channel_t>{});
Image img_out(img);
auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
convolve2d<pixel_t>(const_view(img_out), kernel, view(img_out));
BOOST_TEST(gil::equal_pixels(gil::const_view(img), gil::const_view(img_out)));
}
BOOST_AUTO_TEST_CASE_TEMPLATE(image_5x5_kernel_3x3_identity, Image, fixture::image_types)
{
using pixel_t = typename Image::value_type;
using channel_t = typename gil::channel_type<pixel_t>::type;
auto const img = fixture::generate_image<Image>(5, 5, fixture::random_value<channel_t>{});
Image img_out(img);
auto const kernel = fixture::create_kernel<channel_t>({0, 0, 0, 0, 1, 0, 0, 0, 0});
convolve2d<pixel_t>(const_view(img_out), kernel, view(img_out));
// TODO: Test different boundary options
BOOST_TEST(gil::equal_pixels(gil::const_view(img), gil::const_view(img_out)));
}
BOOST_AUTO_TEST_SUITE_END()