Backport patch to fix build from upstream git master
This commit is contained in:
Adam Williamson
parent
e11a841058
commit
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@ -0,0 +1,139 @@
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From 81958d302494e137f98a8b1d7869841532f90388 Mon Sep 17 00:00:00 2001
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From: JaimeIvanCervantes <jimmycc80@hotmail.com>
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Date: Fri, 16 Jun 2017 13:21:45 -0700
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Subject: [PATCH] multi_convolution: Fix for incorrect template parameter type
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when using unsigned int N for TinyVector SIZE. (Fixes #414)
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---
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include/vigra/multi_convolution.hxx | 28 ++++++++++++++--------------
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1 file changed, 14 insertions(+), 14 deletions(-)
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diff --git a/include/vigra/multi_convolution.hxx b/include/vigra/multi_convolution.hxx
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index 1b5efa740..ec89bcf58 100644
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--- a/include/vigra/multi_convolution.hxx
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+++ b/include/vigra/multi_convolution.hxx
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@@ -1426,7 +1426,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
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class T2, class S2>
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void
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gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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double sigma,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>());
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@@ -1435,7 +1435,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
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class T2, class S2>
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void
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gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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ConvolutionOptions<N> opt);
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// likewise, but execute algorithm in parallel
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@@ -1443,7 +1443,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
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class T2, class S2>
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void
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gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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BlockwiseConvolutionOptions<N> opt);
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}
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\endcode
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@@ -1590,7 +1590,7 @@ template <unsigned int N, class T1, class S1,
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class T2, class S2>
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inline void
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gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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ConvolutionOptions<N> opt )
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{
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if(opt.to_point != typename MultiArrayShape<N>::type())
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@@ -1614,7 +1614,7 @@ template <unsigned int N, class T1, class S1,
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class T2, class S2>
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inline void
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gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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double sigma,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>())
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{
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@@ -1653,7 +1653,7 @@ gaussianGradientMagnitudeImpl(MultiArrayView<N+1, T1, S1> const & src,
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dest.init(0.0);
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typedef typename NumericTraits<T1>::RealPromote TmpType;
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- MultiArray<N, TinyVector<TmpType, N> > grad(dest.shape());
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+ MultiArray<N, TinyVector<TmpType, int(N)> > grad(dest.shape());
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using namespace multi_math;
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@@ -1771,7 +1771,7 @@ gaussianGradientMagnitude(MultiArrayView<N+1, Multiband<T1>, S1> const & src,
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class T2, class S2>
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void
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symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>());
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// execute algorithm in parallel
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@@ -1779,7 +1779,7 @@ gaussianGradientMagnitude(MultiArrayView<N+1, Multiband<T1>, S1> const & src,
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class T2, class S2>
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void
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symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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BlockwiseConvolutionOptions<N> opt);
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}
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\endcode
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@@ -1895,7 +1895,7 @@ template <unsigned int N, class T1, class S1,
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class T2, class S2>
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inline void
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symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
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- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
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+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>())
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{
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if(opt.to_point != typename MultiArrayShape<N>::type())
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@@ -2214,14 +2214,14 @@ laplacianOfGaussianMultiArray(MultiArrayView<N, T1, S1> const & source,
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template <unsigned int N, class T1, class S1,
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class T2, class S2>
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void
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- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
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+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
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MultiArrayView<N, T2, S2> divergence,
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ConvolutionOptions<N> const & opt);
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template <unsigned int N, class T1, class S1,
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class T2, class S2>
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void
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- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
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+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
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MultiArrayView<N, T2, S2> divergence,
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double sigma,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>());
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@@ -2231,7 +2231,7 @@ laplacianOfGaussianMultiArray(MultiArrayView<N, T1, S1> const & source,
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template <unsigned int N, class T1, class S1,
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class T2, class S2>
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void
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- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
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+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
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MultiArrayView<N, T2, S2> divergence,
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BlockwiseConvolutionOptions<N> const & opt);
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}
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@@ -2324,7 +2324,7 @@ gaussianDivergenceMultiArray(Iterator vectorField, Iterator vectorFieldEnd,
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template <unsigned int N, class T1, class S1,
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class T2, class S2>
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inline void
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-gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
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+gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
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MultiArrayView<N, T2, S2> divergence,
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ConvolutionOptions<N> const & opt)
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{
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@@ -2338,7 +2338,7 @@ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & ve
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template <unsigned int N, class T1, class S1,
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class T2, class S2>
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inline void
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-gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
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+gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
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MultiArrayView<N, T2, S2> divergence,
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double sigma,
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ConvolutionOptions<N> opt = ConvolutionOptions<N>())
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12
vigra.spec
12
vigra.spec
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@ -16,6 +16,12 @@ Group: Development/Libraries
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# tar zcf vigra-1.11.1-src-clean.tar.gz vigra-1.11.1/
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Source0: %{name}-%{version}-src-clean.tar.gz
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Source1: vigra-config.sh
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# Backported from upstream master, fixes a build failure:
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# https://github.com/ukoethe/vigra/issues/414
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Patch0: https://github.com/ukoethe/vigra/commit/81958d302494e137f98a8b1d7869841532f90388.patch
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# Avoid attempt to install non-free 'lenna' files
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Patch1: vigra-1.10.0-no-lenna.patch
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Patch2: vigra-1.11.1.docdir.patch
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URL: http://ukoethe.github.io/vigra/
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BuildRequires: gcc-c++ zlib-devel libjpeg-devel libpng-devel libtiff-devel fftw-devel >= 3
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BuildRequires: cmake boost-devel doxygen
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@ -26,8 +32,6 @@ BuildRequires: python3-numpy-f2py boost-python3
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%else
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Requires: python
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%endif
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Patch2: vigra-1.10.0-no-lenna.patch
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Patch3: vigra-1.11.1.docdir.patch
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%description
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VIGRA stands for "Vision with Generic Algorithms". It's a novel computer vision
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@ -78,9 +82,7 @@ The python3-vigra package provides python 3 bindings for vigra
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%endif
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%prep
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%setup -q
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%patch2 -p1 -b .no-lenna
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%patch3 -p1
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%autosetup -p1
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%build
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# Will need to set LEMON_DIR to /usr/share/coin-or-lemon/cmake to compile WITH_LEMON
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