Dist/Tizen: Add spec and manifest files for Tizen/RPM packagingaccepted/tizen/unified/x/20240307.010632accepted/tizen/unified/toolchain/20240311.064848accepted/tizen/unified/dev/20240620.000407accepted/tizen/unified/20240306.011940sandbox/wooksong

This patch adds RPM spec and manifest files for Tizen packaging.

Signed-off-by: Wook Song <wook16.song@samsung.com>

2 files changed, 116 insertions, 0 deletions

diff --git a/packaging/ncnn.manifest b/packaging/ncnn.manifest
new file mode 100644
index 0000000..017d22d
--- /dev/null
+++ b/packaging/ncnn.manifest
@@ -0,0 +1,5 @@
+<manifest>
+ <request>
+    <domain name="_"/>
+ </request>
+</manifest>
diff --git a/packaging/ncnn.spec b/packaging/ncnn.spec
new file mode 100644
index 0000000..f921d3f
--- /dev/null
+++ b/packaging/ncnn.spec
@@ -0,0 +1,111 @@
+%define		builddir	build
+%define		upstream_release_version	20240102
+
+###########################################################################
+# Package and sub-package definitions
+Name:		ncnn
+Summary:	A high-performance neural network inference framework optimized for the mobile platform
+Version:	%{upstream_release_version}
+Release:	1e88fb8
+Group:		Machine Learning/ML Framework
+Packager:	Wook Song <wook16.song@samsung.com>
+License:	BSD-3-Clause
+Source0:	%{name}-%{version}.tar
+Source1001:	%{name}.manifest
+
+## Define build requirements ##
+BuildRequires: cmake
+BuildRequires: ninja
+BuildRequires: protobuf-lite-devel
+BuildRequires: opencv-devel
+BuildRequires: vulkan-loader-devel
+
+## Define Packages ##
+%description
+ncnn is a high-performance neural network inference computing framework
+optimized for mobile platforms. ncnn is deeply considerate about deployment
+and uses on mobile phones from the beginning of design. ncnn does not have
+third party dependencies. It is cross-platform, and runs faster than all known
+open source frameworks on mobile phone cpu. Developers can easily deploy deep
+learning algorithm models to the mobile platform by using efficient ncnn
+implementation, create intelligent APPs, and bring the artificial intelligence
+to your fingertips. ncnn is currently being used in many Tencent applications,
+such as QQ, Qzone, WeChat, Pitu and so on.
+
+%package devel
+Summary:	Development package for the ncnn framework
+%description devel
+Development package for the ncnn framework.
+This contains corresponding header files and static archives.
+
+%package tools
+Summary:	Binary package for tools included in the ncnn framework
+%description tools
+This is a binary package that provides tools and model converters included in
+the ncnn framework.
+
+%package examples
+Summary:	Binary package for native examples
+%description examples
+This is a binary package that contains native examples developed based on
+the APIs of the ncnn framework.
+
+%prep
+rm -rf ./%{builddir}
+%setup -q
+cp %{SOURCE1001} .
+
+%build
+CXXFLAGS=`echo -std=c++11 -fno-builtin $CXXFLAGS`
+%define cmake_common_options -DNCNN_VERSION=%{upstream_release_version}-%{release} -DCMAKE_BUILD_TYPE=release -DNCNN_SHARED_LIB=ON -G Ninja
+%ifnarch aarch64 i586 x86_64
+%define cmake_arch_options -DNCNN_ENABLE_LTO=OFF
+%else
+%define cmake_arch_options -DNCNN_ENABLE_LTO=ON
+%endif
+
+mkdir -p %{builddir}
+pushd %{builddir}
+cmake .. %{cmake_common_options} %{cmake_arch_options}
+cmake --build .
+popd
+
+%install
+pushd %{builddir}
+DESTDIR=%{buildroot} cmake --install . --prefix %{_prefix}
+install -p -m 755 benchmark/benchncnn %{buildroot}%{_bindir}
+mkdir -p %{buildroot}%{_bindir}/ncnn_examples
+find examples -type f -executable -exec install -p -m 755 {} %{buildroot}%{_bindir}/ncnn_examples \;
+popd
+
+%post -p /sbin/ldconfig
+
+%postun -p /sbin/ldconfig
+
+%files
+%manifest %{name}.manifest
+%defattr(-,root,root,-)
+%license LICENSE.txt
+%{_libdir}/*.so.*
+%{_bindir}/benchncnn
+
+%files devel
+%defattr(-,root,root,-)
+%{_includedir}/ncnn/*.h
+%{_libdir}/pkgconfig/*.pc
+%{_libdir}/cmake/ncnn/*.cmake
+%{_libdir}/*.so
+
+%files tools
+%{_bindir}/ncnn2mem
+%{_bindir}/ncnnmerge
+%{_bindir}/ncnnoptimize
+%{_bindir}/caffe2ncnn
+%{_bindir}/darknet2ncnn
+%{_bindir}/mxnet2ncnn
+%{_bindir}/ncnn2int8
+%{_bindir}/ncnn2table
+%{_bindir}/onnx2ncnn
+
+%files examples
+%{_bindir}/ncnn_examples/*