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rebuilt by autoport with build requirements: libopenexr-devel>=3.0.4-1mamba [release 1.11.1-2mamba;Thu Jun 24 2021]

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Silvan Calarco 2024-01-06 06:02:36 +01:00
parent d7ab405d13
commit 050b3951b0
4 changed files with 227 additions and 24 deletions
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139
libvigra-1.11.1-fix-incorrect-template-parameter-type.patch Normal file
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@ -0,0 +1,139 @@
From 81958d302494e137f98a8b1d7869841532f90388 Mon Sep 17 00:00:00 2001
From: JaimeIvanCervantes <jimmycc80@hotmail.com>
Date: Fri, 16 Jun 2017 13:21:45 -0700
Subject: [PATCH] multi_convolution: Fix for incorrect template parameter type
when using unsigned int N for TinyVector SIZE. (Fixes #414)
---
include/vigra/multi_convolution.hxx | 28 ++++++++++++++--------------
1 file changed, 14 insertions(+), 14 deletions(-)
diff --git a/include/vigra/multi_convolution.hxx b/include/vigra/multi_convolution.hxx
index 1b5efa740..ec89bcf58 100644
--- a/include/vigra/multi_convolution.hxx
+++ b/include/vigra/multi_convolution.hxx
@@ -1426,7 +1426,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
class T2, class S2>
void
gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
double sigma,
ConvolutionOptions<N> opt = ConvolutionOptions<N>());
@@ -1435,7 +1435,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
class T2, class S2>
void
gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
ConvolutionOptions<N> opt);
// likewise, but execute algorithm in parallel
@@ -1443,7 +1443,7 @@ gaussianSmoothMultiArray(MultiArrayView<N, T1, S1> const & source,
class T2, class S2>
void
gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
BlockwiseConvolutionOptions<N> opt);
}
\endcode
@@ -1590,7 +1590,7 @@ template <unsigned int N, class T1, class S1,
class T2, class S2>
inline void
gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
ConvolutionOptions<N> opt )
{
if(opt.to_point != typename MultiArrayShape<N>::type())
@@ -1614,7 +1614,7 @@ template <unsigned int N, class T1, class S1,
class T2, class S2>
inline void
gaussianGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
double sigma,
ConvolutionOptions<N> opt = ConvolutionOptions<N>())
{
@@ -1653,7 +1653,7 @@ gaussianGradientMagnitudeImpl(MultiArrayView<N+1, T1, S1> const & src,
dest.init(0.0);
typedef typename NumericTraits<T1>::RealPromote TmpType;
- MultiArray<N, TinyVector<TmpType, N> > grad(dest.shape());
+ MultiArray<N, TinyVector<TmpType, int(N)> > grad(dest.shape());
using namespace multi_math;
@@ -1771,7 +1771,7 @@ gaussianGradientMagnitude(MultiArrayView<N+1, Multiband<T1>, S1> const & src,
class T2, class S2>
void
symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
ConvolutionOptions<N> opt = ConvolutionOptions<N>());
// execute algorithm in parallel
@@ -1779,7 +1779,7 @@ gaussianGradientMagnitude(MultiArrayView<N+1, Multiband<T1>, S1> const & src,
class T2, class S2>
void
symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
BlockwiseConvolutionOptions<N> opt);
}
\endcode
@@ -1895,7 +1895,7 @@ template <unsigned int N, class T1, class S1,
class T2, class S2>
inline void
symmetricGradientMultiArray(MultiArrayView<N, T1, S1> const & source,
- MultiArrayView<N, TinyVector<T2, N>, S2> dest,
+ MultiArrayView<N, TinyVector<T2, int(N)>, S2> dest,
ConvolutionOptions<N> opt = ConvolutionOptions<N>())
{
if(opt.to_point != typename MultiArrayShape<N>::type())
@@ -2214,14 +2214,14 @@ laplacianOfGaussianMultiArray(MultiArrayView<N, T1, S1> const & source,
template <unsigned int N, class T1, class S1,
class T2, class S2>
void
- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
MultiArrayView<N, T2, S2> divergence,
ConvolutionOptions<N> const & opt);
template <unsigned int N, class T1, class S1,
class T2, class S2>
void
- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
MultiArrayView<N, T2, S2> divergence,
double sigma,
ConvolutionOptions<N> opt = ConvolutionOptions<N>());
@@ -2231,7 +2231,7 @@ laplacianOfGaussianMultiArray(MultiArrayView<N, T1, S1> const & source,
template <unsigned int N, class T1, class S1,
class T2, class S2>
void
- gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
+ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
MultiArrayView<N, T2, S2> divergence,
BlockwiseConvolutionOptions<N> const & opt);
}
@@ -2324,7 +2324,7 @@ gaussianDivergenceMultiArray(Iterator vectorField, Iterator vectorFieldEnd,
template <unsigned int N, class T1, class S1,
class T2, class S2>
inline void
-gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
+gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
MultiArrayView<N, T2, S2> divergence,
ConvolutionOptions<N> const & opt)
{
@@ -2338,7 +2338,7 @@ gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & ve
template <unsigned int N, class T1, class S1,
class T2, class S2>
inline void
-gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, N>, S1> const & vectorField,
+gaussianDivergenceMultiArray(MultiArrayView<N, TinyVector<T1, int(N)>, S1> const & vectorField,
MultiArrayView<N, T2, S2> divergence,
double sigma,
ConvolutionOptions<N> opt = ConvolutionOptions<N>())

21
libvigra-1.11.1-openexr-3.0.1.patch Normal file
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@ -0,0 +1,21 @@
diff --git a/config/FindOpenEXR.cmake b/config/FindOpenEXR.cmake
index ef36cdbf..0423e247 100644
--- a/config/FindOpenEXR.cmake
+++ b/config/FindOpenEXR.cmake
@@ -23,6 +23,16 @@
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+find_package(OpenEXR 3.0 CONFIG QUIET)
+if(TARGET OpenEXR::OpenEXR)
+ find_package(Threads)
+ SET(OPENEXR_FOUND TRUE)
+ SET(OPENEXR_INCLUDE_DIR OpenEXR::OpenEXR)
+ SET(OPENEXR_LIBRARIES OpenEXR::OpenEXR)
+ SET(OPENEXR_VERSION ${OpenEXR_VERSION})
+ return()
+endif()
+
FIND_PATH(OPENEXR_INCLUDE_DIR ImfRgbaFile.h PATH_SUFFIXES OpenEXR)
FOREACH(V "" -2_2 -2_1 -2_0 -1_7)

19
libvigra-1.11.1-python-3.7.patch Normal file
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@ -0,0 +1,19 @@
diff -u -r vigra-1.11.1/vigranumpy/src/core/vigranumpycore.cxx vigra-1.11.1-py3.7/vigranumpy/src/core/vigranumpycore.cxx
--- vigra-1.11.1/vigranumpy/src/core/vigranumpycore.cxx 2017-05-19 17:01:08.000000000 +0200
+++ vigra-1.11.1-py3.7/vigranumpy/src/core/vigranumpycore.cxx 2018-07-29 18:29:46.514547076 +0200
@@ -59,10 +59,14 @@
Py_ssize_t size = PyUnicode_GET_DATA_SIZE(s.ptr());
const char * data = PyUnicode_AS_DATA(s.ptr());
return checksum(data, size);
-#else
+#elif (PY_MAJOR_VERSION == 3) && (PY_MINOR_VERSION < 7)
Py_ssize_t size = 0;
char * data = PyUnicode_AsUTF8AndSize(s.ptr(), &size);
return checksum(data, size);
+#else
+ Py_ssize_t size = 0;
+ const char * data = PyUnicode_AsUTF8AndSize(s.ptr(), &size);
+ return checksum(data, size);
#endif
}

72
libvigra.spec
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@ -1,33 +1,34 @@
%define pkgver %(echo %version | tr . -)
Name: libvigra
Version: 1.10.0
Release: 3mamba
Version: 1.11.1
Release: 2mamba
Summary: A computer vision library that puts its main emphasize on customizable algorithms and data structures
Group: System/Libraries
Vendor: openmamba
Distribution: openmamba
Packager: Silvan Calarco <silvan.calarco@mambasoft.it>
URL: http://hci.iwr.uni-heidelberg.de/vigra
Source: https://github.com/ukoethe/vigra/releases/download/Version-%{pkgver}/vigra-%{version}-src-with-docu.tar.gz
#Source: http://hci.iwr.uni-heidelberg.de/vigra/vigra-%{version}-src.tar.gz
URL: https://ukoethe.github.io/vigra/
Source: https://github.com/ukoethe/vigra.git/Version-%{pkgver}/vigra-%{version}.tar.bz2
Patch0: libvigra-1.11.1-fix-incorrect-template-parameter-type.patch
Patch1: libvigra-1.11.1-python-3.7.patch
Patch2: libvigra-1.11.1-openexr-3.0.1.patch
License: MIT
## AUTOBUILDREQ-BEGIN
BuildRequires: glibc-devel
BuildRequires: libboost-devel
BuildRequires: libfftw-devel
BuildRequires: libgcc
BuildRequires: libhdf5-devel
BuildRequires: libimath-devel
BuildRequires: libjpeg-devel
BuildRequires: libopenexr-devel
BuildRequires: libpng-devel
BuildRequires: libpython-devel
BuildRequires: libpython27-devel
BuildRequires: libpython3-devel
BuildRequires: libstdc++6-devel
BuildRequires: libtiff-devel
BuildRequires: libz-devel
BuildRequires: python-boost-devel
## AUTOBUILDREQ-END
BuildRequires: python-nose
BuildRequires: python-numpy
BuildRoot: %{_tmppath}/%{name}-%{version}-root
BuildRequires: libopenexr-devel >= 3.0.4-1mamba
%description
VIGRA stands for "Vision with Generic Algorithms". It's a novel computer vision library that puts its main emphasize on customizable algorithms and data structures. By using template techniques similar to those in the C++ Standard Template Library, you can easily adapt any VIGRA component to the needs of your application, without thereby giving up execution speed.
@ -41,13 +42,31 @@ Requires: %{name} = %{?epoch:%epoch:}%{version}-%{release}
VIGRA stands for "Vision with Generic Algorithms". It's a novel computer vision library that puts its main emphasize on customizable algorithms and data structures. By using template techniques similar to those in the C++ Standard Template Library, you can easily adapt any VIGRA component to the needs of your application, without thereby giving up execution speed.
This package contains static libraries and header files need for development.
%package -n python-vigra-py3
Group: System/Libraries/Python
Summary: Python bindings for %{name}
Requires: %{name} = %{?epoch:%epoch:}%{version}-%{release}
%description -n python-vigra-py3
VIGRA stands for "Vision with Generic Algorithms". It's a novel computer vision library that puts its main emphasize on customizable algorithms and data structures. By using template techniques similar to those in the C++ Standard Template Library, you can easily adapt any VIGRA component to the needs of your application, without thereby giving up execution speed.
%debug_package
%prep
%setup -q -n vigra-%{version}
%patch0 -p1
%patch1 -p1
%patch2 -p1
%build
%cmake -d build \
-DWITH_OPENEXR=1 \
-DDOCINSTALL=share/doc
-DDOCINSTALL=share/doc \
-DPYTHON_EXECUTABLE=%{__python3} \
-DWITH_OPENEXR=true \
-DWITH_VIGRANUMPY=1 \
-DCMAKE_C_FLAGS="-DH5_USE_110_API" \
-DCMAKE_CXX_FLAGS="-DH5_USE_110_API"
%make
%install
@ -62,10 +81,6 @@ rm -f %{buildroot}%{_docdir}/vigranumpy/.buildinfo
%files
%defattr(-,root,root)
%{_libdir}/libvigraimpex.so.*
%ifnarch arm
%dir %{python_sitearch}/vigra
%{python_sitearch}/vigra/*
%endif
#%doc README.txt
%files devel
@ -74,18 +89,27 @@ rm -f %{buildroot}%{_docdir}/vigranumpy/.buildinfo
%dir %{_includedir}/vigra
%{_includedir}/vigra/*
%{_libdir}/vigra/*.cmake
%ifnarch arm
%{_libdir}/vigranumpy/VigranumpyConfig.cmake
%endif
%{_libdir}/libvigraimpex.so
%{_libdir}/vigranumpy/VigranumpyConfig.cmake
%dir %{_docdir}/vigra
%{_docdir}/vigra/*
%dir %{_docdir}/vigranumpy
%{_docdir}/vigranumpy/*
#%dir %{_docdir}/vigranumpy
#%{_docdir}/vigranumpy/*
%files -n python-vigra-py3
%defattr(-,root,root)
%dir %{python3_sitearch}/vigra
%{python3_sitearch}/vigra/*
%changelog
* Thu Apr 13 2017 Ercole 'ercolinux' Carpanetto <ercole69@gmail.com> 1.10.0-3mamba
- Added support for openEXR
* Thu Jun 24 2021 Silvan Calarco <silvan.calarco@mambasoft.it> 1.11.1-2mamba
- rebuilt by autoport with build requirements: libopenexr-devel>=3.0.4-1mamba
* Sat May 15 2021 Silvan Calarco <silvan.calarco@mambasoft.it> 1.11.1-1mamba
- update to 1.11.1
* Fri May 20 2016 Silvan Calarco <silvan.calarco@mambasoft.it> 1.11.0-1mamba
- update to 1.11.0
* Sun Dec 13 2015 Silvan Calarco <silvan.calarco@mambasoft.it> 1.10.0-2mamba
- rebuilt with gcc 5.2.0