1.项目后端整体迁移至PaddleOCR-NCNN算法,已通过基本的兼容性测试 2.工程改为使用CMake组织,后续为了更好地兼容第三方库,不再提供QMake工程 3.重整权利声明文件,重整代码工程,确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN,切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
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Git clone ncnn repo with submodule
$ git clone https://github.com/Tencent/ncnn.git
$ cd ncnn
$ git submodule update --init
- Build for Linux / NVIDIA Jetson / Raspberry Pi
- Build for Windows x64 using VS2017
- Build for macOS
- Build for ARM Cortex-A family with cross-compiling
- Build for Hisilicon platform with cross-compiling
- Build for Android
- Build for iOS on macOS with xcode
- Build for WebAssembly
- Build for AllWinner D1
- Build for Loongson 2K1000
- Build for Termux on Android
Build for Linux
Install required build dependencies:
- git
- g++
- cmake
- protocol buffer (protobuf) headers files and protobuf compiler
- vulkan header files and loader library
- glslang
- (optional) opencv # For building examples
Generally if you have Intel, AMD or Nvidia GPU from last 10 years, Vulkan can be easily used.
On some systems there are no Vulkan drivers easily available at the moment (October 2020), so you might need to disable use of Vulkan on them. This applies to Raspberry Pi 3 (but there is experimental open source Vulkan driver in the works, which is not ready yet). Nvidia Tegra series devices (like Nvidia Jetson) should support Vulkan. Ensure you have most recent software installed for best experience.
On Debian, Ubuntu or Raspberry Pi OS, you can install all required dependencies using:
sudo apt install build-essential git cmake libprotobuf-dev protobuf-compiler libvulkan-dev vulkan-utils libopencv-dev
To use Vulkan backend install Vulkan header files, a vulkan driver loader, GLSL to SPIR-V compiler and vulkaninfo tool. Preferably from your distribution repositories. Alternatively download and install full Vulkan SDK (about 200MB in size; it contains all header files, documentation and prebuilt loader, as well some extra tools and source code of everything) from https://vulkan.lunarg.com/sdk/home
wget https://sdk.lunarg.com/sdk/download/1.2.189.0/linux/vulkansdk-linux-x86_64-1.2.189.0.tar.gz?Human=true -O vulkansdk-linux-x86_64-1.2.189.0.tar.gz
tar -xf vulkansdk-linux-x86_64-1.2.189.0.tar.gz
export VULKAN_SDK=$(pwd)/1.2.189.0/x86_64
To use Vulkan after building ncnn later, you will also need to have Vulkan driver for your GPU. For AMD and Intel GPUs these can be found in Mesa graphics driver, which usually is installed by default on all distros (i.e. sudo apt install mesa-vulkan-drivers
on Debian/Ubuntu). For Nvidia GPUs the proprietary Nvidia driver must be downloaded and installed (some distros will allow easier installation in some way). After installing Vulkan driver, confirm Vulkan libraries and driver are working, by using vulkaninfo
or vulkaninfo | grep deviceType
, it should list GPU device type. If there are more than one GPU installed (including the case of integrated GPU and discrete GPU, commonly found in laptops), you might need to note the order of devices to use later on.
Nvidia Jetson
The Vulkan driver is a default component of the Linux For Tegra BSP release, check the device list.
cd ncnn
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_TOOLCHAIN_FILE=../toolchains/jetson.toolchain.cmake -DNCNN_VULKAN=ON -DNCNN_BUILD_EXAMPLES=ON ..
make -j$(nproc)
Raspberry Pi
Vulkan drivers do exists, but are not mature. You are free to experiment at your own discretion, and report results and performance.
cd ncnn
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_VULKAN=ON -DNCNN_SYSTEM_GLSLANG=ON -DNCNN_BUILD_EXAMPLES=ON ..
make -j$(nproc)
You can add -GNinja
to cmake
above to use Ninja build system (invoke build using ninja
or cmake --build .
).
For Rasberry Pi 3, add -DCMAKE_TOOLCHAIN_FILE=../toolchains/pi3.toolchain.cmake -DPI3=ON
to cmake. You can also consider disabling Vulkan support as the Vulkan drivers for Rasberry Pi are still not mature, but it doesn't hurt to build the support in, but not use it.
Verification
Verify build by running some examples:
cd ../examples
../build/examples/squeezenet ../images/256-ncnn.png
[0 AMD RADV FIJI (LLVM 10.0.1)] queueC=1[4] queueG=0[1] queueT=0[1]
[0 AMD RADV FIJI (LLVM 10.0.1)] bugsbn1=0 buglbia=0 bugcopc=0 bugihfa=0
[0 AMD RADV FIJI (LLVM 10.0.1)] fp16p=1 fp16s=1 fp16a=0 int8s=1 int8a=1
532 = 0.163452
920 = 0.093140
716 = 0.061584
You can also run benchmarks (the 4th argument is a GPU device index to use, refer to vulkaninfo
, if you have more than one GPU):
cd ../benchmark
../build/benchmark/benchncnn 10 $(nproc) 0 0
[0 AMD RADV FIJI (LLVM 10.0.1)] queueC=1[4] queueG=0[1] queueT=0[1]
[0 AMD RADV FIJI (LLVM 10.0.1)] bugsbn1=0 buglbia=0 bugcopc=0 bugihfa=0
[0 AMD RADV FIJI (LLVM 10.0.1)] fp16p=1 fp16s=1 fp16a=0 int8s=1 int8a=1
num_threads = 4
powersave = 0
gpu_device = 0
cooling_down = 1
squeezenet min = 4.68 max = 4.99 avg = 4.85
squeezenet_int8 min = 38.52 max = 66.90 avg = 48.52
...
To run benchmarks on a CPU, set the 5th argument to -1
.
Build for Windows x64 using Visual Studio Community 2017
Download and Install Visual Studio Community 2017 from https://visualstudio.microsoft.com/vs/community/
Start the command prompt: Start → Programs → Visual Studio 2017 → Visual Studio Tools → x64 Native Tools Command Prompt for VS 2017
Download protobuf-3.4.0 from https://github.com/google/protobuf/archive/v3.4.0.zip
Build protobuf library:
cd <protobuf-root-dir>
mkdir build
cd build
cmake -G"NMake Makefiles" -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=%cd%/install -Dprotobuf_BUILD_TESTS=OFF -Dprotobuf_MSVC_STATIC_RUNTIME=OFF ../cmake
nmake
nmake install
(optional) Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home
Build ncnn library (replace with a proper path):
cd <ncnn-root-dir>
mkdir -p build
cd build
cmake -G"NMake Makefiles" -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=%cd%/install -DProtobuf_INCLUDE_DIR=<protobuf-root-dir>/build/install/include -DProtobuf_LIBRARIES=<protobuf-root-dir>/build/install/lib/libprotobuf.lib -DProtobuf_PROTOC_EXECUTABLE=<protobuf-root-dir>/build/install/bin/protoc.exe -DNCNN_VULKAN=ON ..
nmake
nmake install
Note: To speed up compilation process on multi core machines, configuring cmake
to use jom
or ninja
using -G
flag is recommended.
Build for macOS
We've published ncnn to brew now, you can just use following method to install ncnn if you have the Xcode Command Line Tools installed.
brew update
brew install ncnn
Or if you want to compile and build ncnn locally, first install Xcode or Xcode Command Line Tools according to your needs.
Then install protobuf
and libomp
via homebrew
brew install protobuf libomp
Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home
wget https://sdk.lunarg.com/sdk/download/1.2.189.0/mac/vulkansdk-macos-1.2.189.0.dmg?Human=true -O vulkansdk-macos-1.2.189.0.dmg
hdiutil attach vulkansdk-macos-1.2.189.0.dmg
sudo /Volumes/vulkansdk-macos-1.2.189.0/InstallVulkan.app/Contents/MacOS/InstallVulkan --root `pwd`/vulkansdk-macos-1.2.189.0 --accept-licenses --default-answer --confirm-command install
hdiutil detach /Volumes/vulkansdk-macos-1.2.189.0
# setup env
export VULKAN_SDK=`pwd`/vulkansdk-macos-1.2.189.0/macOS
cd <ncnn-root-dir>
mkdir -p build
cd build
cmake -DCMAKE_OSX_ARCHITECTURES="x86_64;arm64" \
-DVulkan_INCLUDE_DIR=`pwd`/../vulkansdk-macos-1.2.189.0/MoltenVK/include \
-DVulkan_LIBRARY=`pwd`/../vulkansdk-macos-1.2.189.0/MoltenVK/dylib/macOS/libMoltenVK.dylib \
-DNCNN_VULKAN=ON -DNCNN_BUILD_EXAMPLES=ON ..
cmake --build . -j 4
cmake --build . --target install
Note: If you encounter libomp
related errors during installation, you can also check our GitHub Actions at here to install and use openmp
.
Build for ARM Cortex-A family with cross-compiling
Download ARM toolchain from https://developer.arm.com/open-source/gnu-toolchain/gnu-a/downloads
export PATH="<your-toolchain-compiler-path>:${PATH}"
Alternatively install a cross-compiler provided by the distribution (i.e. on Debian / Ubuntu, you can do sudo apt install g++-arm-linux-gnueabi g++-arm-linux-gnueabihf g++-aarch64-linux-gnu
).
Depending on your needs build one or more of the below targets.
AArch32 target with soft float (arm-linux-gnueabi)
cd <ncnn-root-dir>
mkdir -p build-arm-linux-gnueabi
cd build-arm-linux-gnueabi
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabi.toolchain.cmake ..
make -j$(nproc)
AArch32 target with hard float (arm-linux-gnueabihf)
cd <ncnn-root-dir>
mkdir -p build-arm-linux-gnueabihf
cd build-arm-linux-gnueabihf
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabihf.toolchain.cmake ..
make -j$(nproc)
AArch64 GNU/Linux target (aarch64-linux-gnu)
cd <ncnn-root-dir>
mkdir -p build-aarch64-linux-gnu
cd build-aarch64-linux-gnu
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/aarch64-linux-gnu.toolchain.cmake ..
make -j$(nproc)
Build for Hisilicon platform with cross-compiling
Download and install Hisilicon SDK. The toolchain should be in /opt/hisi-linux/x86-arm
cd <ncnn-root-dir>
mkdir -p build
cd build
# Choose one cmake toolchain file depends on your target platform
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/hisiv300.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/hisiv500.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/himix100.toolchain.cmake ..
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/himix200.toolchain.cmake ..
make -j$(nproc)
make install
Build for Android
You can use the pre-build ncnn-android-lib.zip from https://github.com/Tencent/ncnn/releases
Download Android NDK from http://developer.android.com/ndk/downloads/index.html and install it, for example:
unzip android-ndk-r21d-linux-x86_64.zip
export ANDROID_NDK=<your-ndk-root-path>
(optional) remove the hardcoded debug flag in Android NDK android-ndk issue
# open $ANDROID_NDK/build/cmake/android.toolchain.cmake
# delete "-g" line
list(APPEND ANDROID_COMPILER_FLAGS
-g
-DANDROID
Build armv7 library
cd <ncnn-root-dir>
mkdir -p build-android-armv7
cd build-android-armv7
cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake" \
-DANDROID_ABI="armeabi-v7a" -DANDROID_ARM_NEON=ON \
-DANDROID_PLATFORM=android-14 ..
# If you want to enable Vulkan, platform api version >= android-24 is needed
cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake" \
-DANDROID_ABI="armeabi-v7a" -DANDROID_ARM_NEON=ON \
-DANDROID_PLATFORM=android-24 -DNCNN_VULKAN=ON ..
make -j$(nproc)
make install
Pick build-android-armv7/install
folder for further JNI usage.
Build aarch64 library:
cd <ncnn-root-dir>
mkdir -p build-android-aarch64
cd build-android-aarch64
cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake"\
-DANDROID_ABI="arm64-v8a" \
-DANDROID_PLATFORM=android-21 ..
# If you want to enable Vulkan, platform api version >= android-24 is needed
cmake -DCMAKE_TOOLCHAIN_FILE="$ANDROID_NDK/build/cmake/android.toolchain.cmake" \
-DANDROID_ABI="arm64-v8a" \
-DANDROID_PLATFORM=android-24 -DNCNN_VULKAN=ON ..
make -j$(nproc)
make install
Pick build-android-aarch64/install
folder for further JNI usage.
Build for iOS on macOS with xcode
You can use the pre-build ncnn.framework glslang.framework and openmp.framework from https://github.com/Tencent/ncnn/releases
Install xcode
You can replace -DENABLE_BITCODE=0
to -DENABLE_BITCODE=1
in the following cmake arguments if you want to build bitcode enabled libraries.
Download and install openmp for multithreading inference feature on iPhoneOS
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-11.0.0/openmp-11.0.0.src.tar.xz
tar -xf openmp-11.0.0.src.tar.xz
cd openmp-11.0.0.src
# apply some compilation fix
sed -i'' -e '/.size __kmp_unnamed_critical_addr/d' runtime/src/z_Linux_asm.S
sed -i'' -e 's/__kmp_unnamed_critical_addr/___kmp_unnamed_critical_addr/g' runtime/src/z_Linux_asm.S
mkdir -p build-ios
cd build-ios
cmake -DCMAKE_TOOLCHAIN_FILE=<ncnn-root-dir>/toolchains/ios.toolchain.cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=install \
-DIOS_PLATFORM=OS -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 -DIOS_ARCH="armv7;arm64;arm64e" \
-DPERL_EXECUTABLE=/usr/local/bin/perl \
-DLIBOMP_ENABLE_SHARED=OFF -DLIBOMP_OMPT_SUPPORT=OFF -DLIBOMP_USE_HWLOC=OFF ..
cmake --build . -j 4
cmake --build . --target install
# copy openmp library and header files to xcode toolchain sysroot
# <xcode-dir> is usually /Applications/Xcode.app or /Applications/Xcode-beta.app depends on your Xcode version
sudo cp install/include/* <xcode-dir>/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/include
sudo cp install/lib/libomp.a <xcode-dir>/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/lib
Download and install openmp for multithreading inference feature on iPhoneSimulator
wget https://github.com/llvm/llvm-project/releases/download/llvmorg-11.0.0/openmp-11.0.0.src.tar.xz
tar -xf openmp-11.0.0.src.tar.xz
cd openmp-11.0.0.src
# apply some compilation fix
sed -i'' -e '/.size __kmp_unnamed_critical_addr/d' runtime/src/z_Linux_asm.S
sed -i'' -e 's/__kmp_unnamed_critical_addr/___kmp_unnamed_critical_addr/g' runtime/src/z_Linux_asm.S
mkdir -p build-ios-sim
cd build-ios-sim
cmake -DCMAKE_TOOLCHAIN_FILE=<ncnn-root-dir>/toolchains/ios.toolchain.cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=install \
-DIOS_PLATFORM=SIMULATOR -DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 -DIOS_ARCH="i386;x86_64" \
-DPERL_EXECUTABLE=/usr/local/bin/perl \
-DLIBOMP_ENABLE_SHARED=OFF -DLIBOMP_OMPT_SUPPORT=OFF -DLIBOMP_USE_HWLOC=OFF ..
cmake --build . -j 4
cmake --build . --target install
# copy openmp library and header files to xcode toolchain sysroot
# <xcode-dir> is usually /Applications/Xcode.app or /Applications/Xcode-beta.app depends on your Xcode version
sudo cp install/include/* <xcode-dir>/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/include
sudo cp install/lib/libomp.a <xcode-dir>/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/lib
Package openmp framework:
cd <openmp-root-dir>
mkdir -p openmp.framework/Versions/A/Headers
mkdir -p openmp.framework/Versions/A/Resources
ln -s A openmp.framework/Versions/Current
ln -s Versions/Current/Headers openmp.framework/Headers
ln -s Versions/Current/Resources openmp.framework/Resources
ln -s Versions/Current/openmp openmp.framework/openmp
lipo -create build-ios/install/lib/libomp.a build-ios-sim/install/lib/libomp.a -o openmp.framework/Versions/A/openmp
cp -r build-ios/install/include/* openmp.framework/Versions/A/Headers/
sed -e 's/__NAME__/openmp/g' -e 's/__IDENTIFIER__/org.llvm.openmp/g' -e 's/__VERSION__/11.0/g' <ncnn-root-dir>/Info.plist > openmp.framework/Versions/A/Resources/Info.plist
Download and install Vulkan SDK from https://vulkan.lunarg.com/sdk/home
wget https://sdk.lunarg.com/sdk/download/1.2.189.0/mac/vulkansdk-macos-1.2.189.0.dmg?Human=true -O vulkansdk-macos-1.2.189.0.dmg
hdiutil attach vulkansdk-macos-1.2.189.0.dmg
sudo /Volumes/vulkansdk-macos-1.2.189.0/InstallVulkan.app/Contents/MacOS/InstallVulkan --root `pwd`/vulkansdk-macos-1.2.189.0 --accept-licenses --default-answer --confirm-command install
hdiutil detach /Volumes/vulkansdk-macos-1.2.189.0
# setup env
export VULKAN_SDK=`pwd`/vulkansdk-macos-1.2.189.0/macOS
Build library for iPhoneOS:
cd <ncnn-root-dir>
git submodule update --init
mkdir -p build-ios
cd build-ios
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DIOS_PLATFORM=OS -DIOS_ARCH="armv7;arm64;arm64e" \
-DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 \
-DOpenMP_C_FLAGS="-Xclang -fopenmp" -DOpenMP_CXX_FLAGS="-Xclang -fopenmp" \
-DOpenMP_C_LIB_NAMES="libomp" -DOpenMP_CXX_LIB_NAMES="libomp" \
-DOpenMP_libomp_LIBRARY="/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/lib/libomp.a" \
-DNCNN_BUILD_BENCHMARK=OFF ..
# vulkan is only available on arm64 devices
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DIOS_PLATFORM=OS64 -DIOS_ARCH="arm64;arm64e" \
-DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 \
-DOpenMP_C_FLAGS="-Xclang -fopenmp" -DOpenMP_CXX_FLAGS="-Xclang -fopenmp" \
-DOpenMP_C_LIB_NAMES="libomp" -DOpenMP_CXX_LIB_NAMES="libomp" \
-DOpenMP_libomp_LIBRARY="/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/lib/libomp.a" \
-DVulkan_INCLUDE_DIR=$VULKAN_SDK/../MoltenVK/include \
-DVulkan_LIBRARY=$VULKAN_SDK/../MoltenVK/dylib/iOS/libMoltenVK.dylib \
-DNCNN_VULKAN=ON -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Build library for iPhoneSimulator:
cd <ncnn-root-dir>
mkdir -p build-ios-sim
cd build-ios-sim
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/ios.toolchain.cmake -DIOS_PLATFORM=SIMULATOR -DIOS_ARCH="i386;x86_64" \
-DENABLE_BITCODE=0 -DENABLE_ARC=0 -DENABLE_VISIBILITY=0 \
-DOpenMP_C_FLAGS="-Xclang -fopenmp" -DOpenMP_CXX_FLAGS="-Xclang -fopenmp" \
-DOpenMP_C_LIB_NAMES="libomp" -DOpenMP_CXX_LIB_NAMES="libomp" \
-DOpenMP_libomp_LIBRARY="/Applications/Xcode.app/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/lib/libomp.a" \
-DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Package glslang framework:
cd <ncnn-root-dir>
mkdir -p glslang.framework/Versions/A/Headers
mkdir -p glslang.framework/Versions/A/Resources
ln -s A glslang.framework/Versions/Current
ln -s Versions/Current/Headers glslang.framework/Headers
ln -s Versions/Current/Resources glslang.framework/Resources
ln -s Versions/Current/glslang glslang.framework/glslang
libtool -static build-ios/install/lib/libglslang.a build-ios/install/lib/libSPIRV.a build-ios/install/lib/libOGLCompiler.a build-ios/install/lib/libOSDependent.a -o build-ios/install/lib/libglslang_combined.a
libtool -static build-ios-sim/install/lib/libglslang.a build-ios-sim/install/lib/libSPIRV.a build-ios-sim/install/lib/libOGLCompiler.a build-ios-sim/install/lib/libOSDependent.a -o build-ios-sim/install/lib/libglslang_combined.a
lipo -create build-ios/install/lib/libglslang_combined.a build-ios-sim/install/lib/libglslang_combined.a -o glslang.framework/Versions/A/glslang
cp -r build/install/include/glslang glslang.framework/Versions/A/Headers/
sed -e 's/__NAME__/glslang/g' -e 's/__IDENTIFIER__/org.khronos.glslang/g' -e 's/__VERSION__/1.0/g' Info.plist > glslang.framework/Versions/A/Resources/Info.plist
Package ncnn framework:
cd <ncnn-root-dir>
mkdir -p ncnn.framework/Versions/A/Headers
mkdir -p ncnn.framework/Versions/A/Resources
ln -s A ncnn.framework/Versions/Current
ln -s Versions/Current/Headers ncnn.framework/Headers
ln -s Versions/Current/Resources ncnn.framework/Resources
ln -s Versions/Current/ncnn ncnn.framework/ncnn
lipo -create build-ios/install/lib/libncnn.a build-ios-sim/install/lib/libncnn.a -o ncnn.framework/Versions/A/ncnn
cp -r build-ios/install/include/* ncnn.framework/Versions/A/Headers/
sed -e 's/__NAME__/ncnn/g' -e 's/__IDENTIFIER__/com.tencent.ncnn/g' -e 's/__VERSION__/1.0/g' Info.plist > ncnn.framework/Versions/A/Resources/Info.plist
Pick ncnn.framework
glslang.framework
and openmp.framework
folder for app development.
Build for WebAssembly
Install Emscripten
git clone https://github.com/emscripten-core/emsdk.git
cd emsdk
./emsdk install 2.0.8
./emsdk activate 2.0.8
source emsdk/emsdk_env.sh
Build without any extension for general compatibility:
mkdir -p build
cd build
cmake -DCMAKE_TOOLCHAIN_FILE=../emsdk/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
-DNCNN_THREADS=OFF -DNCNN_OPENMP=OFF -DNCNN_SIMPLEOMP=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=OFF -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
-DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Build with WASM SIMD extension:
mkdir -p build-simd
cd build-simd
cmake -DCMAKE_TOOLCHAIN_FILE=../emsdk/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
-DNCNN_THREADS=OFF -DNCNN_OPENMP=OFF -DNCNN_SIMPLEOMP=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=ON -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
-DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Build with WASM Thread extension:
mkdir -p build-threads
cd build-threads
cmake -DCMAKE_TOOLCHAIN_FILE=../emsdk/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
-DNCNN_THREADS=ON -DNCNN_OPENMP=ON -DNCNN_SIMPLEOMP=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=OFF -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
-DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Build with WASM SIMD and Thread extension:
mkdir -p build-simd-threads
cd build-simd-threads
cmake -DCMAKE_TOOLCHAIN_FILE=../emsdk/upstream/emscripten/cmake/Modules/Platform/Emscripten.cmake \
-DNCNN_THREADS=ON -DNCNN_OPENMP=ON -DNCNN_SIMPLEOMP=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_SSE2=ON -DNCNN_AVX2=OFF -DNCNN_AVX=OFF \
-DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF -DNCNN_BUILD_BENCHMARK=OFF ..
cmake --build . -j 4
cmake --build . --target install
Pick build-XYZ/install
folder for further usage.
Build for AllWinner D1
Download c906 toolchain package from https://occ.t-head.cn/community/download?id=3913221581316624384
tar -xf riscv64-linux-x86_64-20210512.tar.gz
export RISCV_ROOT_PATH=/home/nihui/osd/riscv64-linux-x86_64-20210512
Build ncnn with riscv-v vector and simpleocv enabled:
mkdir -p build-c906
cd build-c906
cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/c906.toolchain.cmake \
-DCMAKE_BUILD_TYPE=relwithdebinfo -DNCNN_OPENMP=OFF -DNCNN_THREADS=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_RVV=ON \
-DNCNN_SIMPLEOCV=ON -DNCNN_BUILD_EXAMPLES=ON ..
cmake --build . -j 4
cmake --build . --target install
Pick build-c906/install
folder for further usage.
You can upload binary inside build-c906/examples
folder and run on D1 board for testing.
Build for Loongson 2K1000
For gcc version < 8.5, you need to fix msa.h header for workaround msa fmadd/fmsub/maddv/msubv bug.
Open /usr/lib/gcc/mips64el-linux-gnuabi64/8/include/msa.h
, find __msa_fmadd
and __msa_fmsub
and apply changes as the following
// #define __msa_fmadd_w __builtin_msa_fmadd_w
// #define __msa_fmadd_d __builtin_msa_fmadd_d
// #define __msa_fmsub_w __builtin_msa_fmsub_w
// #define __msa_fmsub_d __builtin_msa_fmsub_d
#define __msa_fmadd_w(a, b, c) __builtin_msa_fmadd_w(c, b, a)
#define __msa_fmadd_d(a, b, c) __builtin_msa_fmadd_d(c, b, a)
#define __msa_fmsub_w(a, b, c) __builtin_msa_fmsub_w(c, b, a)
#define __msa_fmsub_d(a, b, c) __builtin_msa_fmsub_d(c, b, a)
find __msa_maddv
and __msa_msubv
and apply changes as the following
// #define __msa_maddv_b __builtin_msa_maddv_b
// #define __msa_maddv_h __builtin_msa_maddv_h
// #define __msa_maddv_w __builtin_msa_maddv_w
// #define __msa_maddv_d __builtin_msa_maddv_d
// #define __msa_msubv_b __builtin_msa_msubv_b
// #define __msa_msubv_h __builtin_msa_msubv_h
// #define __msa_msubv_w __builtin_msa_msubv_w
// #define __msa_msubv_d __builtin_msa_msubv_d
#define __msa_maddv_b(a, b, c) __builtin_msa_maddv_b(c, b, a)
#define __msa_maddv_h(a, b, c) __builtin_msa_maddv_h(c, b, a)
#define __msa_maddv_w(a, b, c) __builtin_msa_maddv_w(c, b, a)
#define __msa_maddv_d(a, b, c) __builtin_msa_maddv_d(c, b, a)
#define __msa_msubv_b(a, b, c) __builtin_msa_msubv_b(c, b, a)
#define __msa_msubv_h(a, b, c) __builtin_msa_msubv_h(c, b, a)
#define __msa_msubv_w(a, b, c) __builtin_msa_msubv_w(c, b, a)
#define __msa_msubv_d(a, b, c) __builtin_msa_msubv_d(c, b, a)
Build ncnn with mips msa and simpleocv enabled:
mkdir -p build
cd build
cmake -DNCNN_DISABLE_RTTI=ON -DNCNN_DISABLE_EXCEPTION=ON -DNCNN_RUNTIME_CPU=OFF -DNCNN_MSA=ON -DNCNN_MMI=ON -DNCNN_SIMPLEOCV=ON ..
cmake --build . -j 2
cmake --build . --target install
Pick build/install
folder for further usage.
You can run binary inside build/examples
folder for testing.
Build for Termux on Android
Install app Termux on your phone,and install Ubuntu in Termux.
If you want use ssh, just install openssh in Termux
pkg install proot-distro
proot-distro install ubuntu
or you can see what system can be installed using proot-distro list
while you install ubuntu successfully, using proot-distro login ubuntu
to login Ubuntu.
Then make ncnn,no need to install any other dependencies.
git clone https://github.com/Tencent/ncnn.git
cd ncnn
git submodule update --init
mkdir -p build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DNCNN_BUILD_EXAMPLES=ON -DNCNN_PLATFORM_API=OFF -DNCNN_SIMPLEOCV=ON ..
make -j$(nproc)
Then you can run a test
on my Pixel 3 XL using Qualcomm 845,cant load
256-ncnn.png
cd ../examples
../build/examples/squeezenet ../images/128-ncnn.png