unioil-loyalty-rn-app/ios/Pods/Flipper-Boost-iOSX/boost/gil/extension/numeric/algorithm.hpp

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//
// Copyright 2005-2007 Adobe Systems Incorporated
// Copyright 2019 Pranam Lashkari <plashkari628@gmail.com>
//
// 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
//
#ifndef BOOST_GIL_EXTENSION_NUMERIC_ALGORITHM_HPP
#define BOOST_GIL_EXTENSION_NUMERIC_ALGORITHM_HPP
#include <boost/gil/extension/numeric/pixel_numeric_operations.hpp>
#include <boost/gil/metafunctions.hpp>
#include <boost/gil/pixel_iterator.hpp>
#include <boost/gil/image.hpp>
#include <boost/assert.hpp>
#include <algorithm>
#include <iterator>
#include <numeric>
#include <type_traits>
namespace boost { namespace gil {
/// \brief Reference proxy associated with a type that has a \p "reference" member type alias.
///
/// The reference proxy is the reference type, but with stripped-out C++ reference.
/// Models PixelConcept.
template <typename T>
struct pixel_proxy : std::remove_reference<typename T::reference> {};
/// \brief std::for_each for a pair of iterators
template <typename Iterator1, typename Iterator2, typename BinaryFunction>
BinaryFunction for_each(Iterator1 first1, Iterator1 last1, Iterator2 first2, BinaryFunction f)
{
while (first1 != last1)
f(*first1++, *first2++);
return f;
}
template <typename SrcIterator, typename DstIterator>
inline
auto assign_pixels(SrcIterator src, SrcIterator src_end, DstIterator dst) -> DstIterator
{
for_each(src, src_end, dst,
pixel_assigns_t
<
typename pixel_proxy<typename std::iterator_traits<SrcIterator>::value_type>::type,
typename pixel_proxy<typename std::iterator_traits<DstIterator>::value_type>::type
>());
return dst + (src_end - src);
}
namespace detail {
template <std::size_t Size>
struct inner_product_k_t
{
template
<
class InputIterator1,
class InputIterator2,
class T,
class BinaryOperation1,
class BinaryOperation2
>
static T apply(
InputIterator1 first1,
InputIterator2 first2, T init,
BinaryOperation1 binary_op1,
BinaryOperation2 binary_op2)
{
init = binary_op1(init, binary_op2(*first1, *first2));
return inner_product_k_t<Size - 1>::template apply(
first1 + 1, first2 + 1, init, binary_op1, binary_op2);
}
};
template <>
struct inner_product_k_t<0>
{
template
<
class InputIterator1,
class InputIterator2,
class T,
class BinaryOperation1,
class BinaryOperation2
>
static T apply(
InputIterator1 first1,
InputIterator2 first2,
T init,
BinaryOperation1 binary_op1,
BinaryOperation2 binary_op2)
{
return init;
}
};
} // namespace detail
/// static version of std::inner_product
template
<
std::size_t Size,
class InputIterator1,
class InputIterator2,
class T,
class BinaryOperation1,
class BinaryOperation2
>
BOOST_FORCEINLINE
T inner_product_k(
InputIterator1 first1,
InputIterator2 first2,
T init,
BinaryOperation1 binary_op1,
BinaryOperation2 binary_op2)
{
return detail::inner_product_k_t<Size>::template apply(
first1, first2, init, binary_op1, binary_op2);
}
/// \brief 1D un-guarded cross-correlation with a variable-size kernel
template
<
typename PixelAccum,
typename SrcIterator,
typename KernelIterator,
typename Size,
typename DstIterator
>
inline
auto correlate_pixels_n(
SrcIterator src_begin,
SrcIterator src_end,
KernelIterator kernel_begin,
Size kernel_size,
DstIterator dst_begin)
-> DstIterator
{
using src_pixel_ref_t = typename pixel_proxy
<
typename std::iterator_traits<SrcIterator>::value_type
>::type;
using dst_pixel_ref_t = typename pixel_proxy
<
typename std::iterator_traits<DstIterator>::value_type
>::type;
using kernel_value_t = typename std::iterator_traits<KernelIterator>::value_type;
PixelAccum accum_zero;
pixel_zeros_t<PixelAccum>()(accum_zero);
while (src_begin != src_end)
{
pixel_assigns_t<PixelAccum, dst_pixel_ref_t>()(
std::inner_product(
src_begin,
src_begin + kernel_size,
kernel_begin,
accum_zero,
pixel_plus_t<PixelAccum, PixelAccum, PixelAccum>(),
pixel_multiplies_scalar_t<src_pixel_ref_t, kernel_value_t, PixelAccum>()),
*dst_begin);
++src_begin;
++dst_begin;
}
return dst_begin;
}
/// \brief 1D un-guarded cross-correlation with a fixed-size kernel
template
<
std::size_t Size,
typename PixelAccum,
typename SrcIterator,
typename KernelIterator,
typename DstIterator
>
inline
auto correlate_pixels_k(
SrcIterator src_begin,
SrcIterator src_end,
KernelIterator kernel_begin,
DstIterator dst_begin)
-> DstIterator
{
using src_pixel_ref_t = typename pixel_proxy
<
typename std::iterator_traits<SrcIterator>::value_type
>::type;
using dst_pixel_ref_t = typename pixel_proxy
<
typename std::iterator_traits<DstIterator>::value_type
>::type;
using kernel_type = typename std::iterator_traits<KernelIterator>::value_type;
PixelAccum accum_zero;
pixel_zeros_t<PixelAccum>()(accum_zero);
while (src_begin != src_end)
{
pixel_assigns_t<PixelAccum, dst_pixel_ref_t>()(
inner_product_k<Size>(
src_begin,
kernel_begin,
accum_zero,
pixel_plus_t<PixelAccum, PixelAccum, PixelAccum>(),
pixel_multiplies_scalar_t<src_pixel_ref_t, kernel_type, PixelAccum>()),
*dst_begin);
++src_begin;
++dst_begin;
}
return dst_begin;
}
/// \brief destination is set to be product of the source and a scalar
/// \tparam PixelAccum - TODO
/// \tparam SrcView Models ImageViewConcept
/// \tparam DstView Models MutableImageViewConcept
template <typename PixelAccum, typename SrcView, typename Scalar, typename DstView>
inline
void view_multiplies_scalar(SrcView const& src_view, Scalar const& scalar, DstView const& dst_view)
{
static_assert(std::is_scalar<Scalar>::value, "Scalar is not scalar");
BOOST_ASSERT(src_view.dimensions() == dst_view.dimensions());
using src_pixel_ref_t = typename pixel_proxy<typename SrcView::value_type>::type;
using dst_pixel_ref_t = typename pixel_proxy<typename DstView::value_type>::type;
using y_coord_t = typename SrcView::y_coord_t;
y_coord_t const height = src_view.height();
for (y_coord_t y = 0; y < height; ++y)
{
typename SrcView::x_iterator it_src = src_view.row_begin(y);
typename DstView::x_iterator it_dst = dst_view.row_begin(y);
typename SrcView::x_iterator it_src_end = src_view.row_end(y);
while (it_src != it_src_end)
{
pixel_assigns_t<PixelAccum, dst_pixel_ref_t>()(
pixel_multiplies_scalar_t<src_pixel_ref_t, Scalar, PixelAccum>()(*it_src, scalar),
*it_dst);
++it_src;
++it_dst;
}
}
}
/// \ingroup ImageAlgorithms
/// \brief Boundary options for image boundary extension
enum class boundary_option
{
output_ignore, /// do nothing to the output
output_zero, /// set the output to zero
extend_padded, /// assume the source boundaries to be padded already
extend_zero, /// assume the source boundaries to be zero
extend_constant /// assume the source boundaries to be the boundary value
};
namespace detail
{
template <typename SrcView, typename RltView>
void extend_row_impl(
SrcView const& src_view,
RltView result_view,
std::size_t extend_count,
boundary_option option)
{
std::ptrdiff_t extend_count_ = static_cast<std::ptrdiff_t>(extend_count);
if (option == boundary_option::extend_constant)
{
for (std::ptrdiff_t i = 0; i < result_view.height(); i++)
{
if(i >= extend_count_ && i < extend_count_ + src_view.height())
{
assign_pixels(
src_view.row_begin(i - extend_count_),
src_view.row_end(i - extend_count_),
result_view.row_begin(i)
);
}
else if(i < extend_count_)
{
assign_pixels(src_view.row_begin(0), src_view.row_end(0), result_view.row_begin(i));
}
else
{
assign_pixels(
src_view.row_begin(src_view.height() - 1),
src_view.row_end(src_view.height() - 1),
result_view.row_begin(i)
);
}
}
}
else if (option == boundary_option::extend_zero)
{
typename SrcView::value_type acc_zero;
pixel_zeros_t<typename SrcView::value_type>()(acc_zero);
for (std::ptrdiff_t i = 0; i < result_view.height(); i++)
{
if (i >= extend_count_ && i < extend_count_ + src_view.height())
{
assign_pixels(
src_view.row_begin(i - extend_count_),
src_view.row_end(i - extend_count_),
result_view.row_begin(i)
);
}
else
{
std::fill_n(result_view.row_begin(i), result_view.width(), acc_zero);
}
}
}
else if (option == boundary_option::extend_padded)
{
auto original_view = subimage_view(
src_view,
0,
-extend_count,
src_view.width(),
src_view.height() + (2 * extend_count)
);
for (std::ptrdiff_t i = 0; i < result_view.height(); i++)
{
assign_pixels(
original_view.row_begin(i),
original_view.row_end(i),
result_view.row_begin(i)
);
}
}
else
{
BOOST_ASSERT_MSG(false, "Invalid boundary option");
}
}
} //namespace detail
/// \brief adds new row at top and bottom.
/// Image padding introduces new pixels around the edges of an image.
/// The border provides space for annotations or acts as a boundary when using advanced filtering techniques.
/// \tparam SrcView Models ImageViewConcept
/// \tparam extend_count number of rows to be added each side
/// \tparam option - TODO
template <typename SrcView>
auto extend_row(
SrcView const& src_view,
std::size_t extend_count,
boundary_option option
) -> typename gil::image<typename SrcView::value_type>
{
typename gil::image<typename SrcView::value_type>
result_img(src_view.width(), src_view.height() + (2 * extend_count));
auto result_view = view(result_img);
detail::extend_row_impl(src_view, result_view, extend_count, option);
return result_img;
}
/// \brief adds new column at left and right.
/// Image padding introduces new pixels around the edges of an image.
/// The border provides space for annotations or acts as a boundary when using advanced filtering techniques.
/// \tparam SrcView Models ImageViewConcept
/// \tparam extend_count number of columns to be added each side
/// \tparam option - TODO
template <typename SrcView>
auto extend_col(
SrcView const& src_view,
std::size_t extend_count,
boundary_option option
) -> typename gil::image<typename SrcView::value_type>
{
auto src_view_rotate = rotated90cw_view(src_view);
typename gil::image<typename SrcView::value_type>
result_img(src_view.width() + (2 * extend_count), src_view.height());
auto result_view = rotated90cw_view(view(result_img));
detail::extend_row_impl(src_view_rotate, result_view, extend_count, option);
return result_img;
}
/// \brief adds new row and column at all sides.
/// Image padding introduces new pixels around the edges of an image.
/// The border provides space for annotations or acts as a boundary when using advanced filtering techniques.
/// \tparam SrcView Models ImageViewConcept
/// \tparam extend_count number of rows/column to be added each side
/// \tparam option - TODO
template <typename SrcView>
auto extend_boundary(
SrcView const& src_view,
std::size_t extend_count,
boundary_option option
) -> typename gil::image<typename SrcView::value_type>
{
if (option == boundary_option::extend_padded)
{
typename gil::image<typename SrcView::value_type>
result_img(src_view.width()+(2 * extend_count), src_view.height()+(2 * extend_count));
typename gil::image<typename SrcView::value_type>::view_t result_view = view(result_img);
auto original_view = subimage_view(
src_view,
-extend_count,
-extend_count,
src_view.width() + (2 * extend_count),
src_view.height() + (2 * extend_count)
);
for (std::ptrdiff_t i = 0; i < result_view.height(); i++)
{
assign_pixels(
original_view.row_begin(i),
original_view.row_end(i),
result_view.row_begin(i)
);
}
return result_img;
}
auto auxilary_img = extend_col(src_view, extend_count, option);
return extend_row(view(auxilary_img), extend_count, option);
}
}} // namespace boost::gil
#endif