Use ncnn to deploy pytorch model to Android phone

1. Open graphics card support when compiling NCNN. Vulkan is for gpu -DNCNN_VULKAN=ON
2. MobileNetV3

Open CMAKE 0091 feature when compiling into MT

cmake_minimum_required(VERSION 3.20.0)
cmake_policy(SET CMP0091 NEW)
set(CMAKE_MSVC_RUNTIME_LIBRARY "MultiThreaded$<$<CONFIG:Debug>:Debug>")
project("client-project")

Train YOLO

\Envs\torch\Scripts\activate.ps1
python train.py --batch 6 --workers 2 --imgsz 960 --epochs 300 --data "\Core\yaml\data.yaml" --cfg "\Core\yaml\cfg.yaml" --weights \ Core\weights\best.pt --device 0

Conversion model

from torch import nn
import torch.utils.model_zoo as model_zoo
import torch.onnx
from libs import define
from libs.net import Net
from libs.dataset import ImageDataset
import os

test_data = ImageDataset(define.testPath,False)
test_loader = torch.utils.data.DataLoader( test_data, batch_size=1, shuffle=True)

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = Net(out_dim=19).to(device)
model.load_state_dict(torch.load( "./widget/last.pt" ))
model.eval()

def saveOnnx():
    for data, target in test_loader:
        data, target = data.to(device), target.to(device)
        label = target.long()
        y = model(data)
        # Export the model
        torch.onnx.export(model, # model being run
                        data, # model input (or a tuple for multiple inputs)
                        "./widget/best.onnx", # where to save the model (can be a file or file-like object)
                        export_params=True, # store the trained parameter weights inside the model file
                        opset_version=10, # the ONNX version to export the model to
                        do_constant_folding=True, # whether to execute constant folding for optimization
                        input_names = ['input'], # the model's input names
                        output_names = ['output'], # the model's output names
                        dynamic_axes={'input': {0:'batch_size'}, # variable lenght axes
                                        'output': {0:'batch_size'}})

        traced_script_module = torch.jit.trace(model, data)
        return

saveOnnx()
# Conversion
os.system("python -m onnxsim ./widget/best.onnx ./widgetbest-sim.onnx")
os.system("./bin/onnx2ncnn.exe ./widget/best-sim.onnx ./widget/best.param ./widget/best.bin")
os.system("./bin/ncnnoptimize.exe ./widget/best.param ./widget/best.bin ./widget/best-opt.param ./widget/best-opt.bin 65536")

python .\export.py –weights weights/best.pt –img 960 –batch 1 –train python -m onnxsim best.onnx best-sim.onnx .\onnx2ncnn.exe best-sim.onnx best.param best.bin ncnnoptimize best.param best.bin best-opt.param best-opt.bin 65536

### 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-linux)
*   [Build for Windows x64 using VS2017](#build-for-windows-x64-using-visual-studio-community-2017)
*   [Build for macOS](#build-for-macos)
*   [Build for ARM Cortex-A family with cross-compiling](#build-for-arm-cortex-a-family-with-cross-compiling)
*   [Build for Hisilicon platform with cross-compiling](#build-for-hisilicon-platform-with-cross-compiling)
*   [Build for Android](#build-for-android)
*   [Build for iOS on macOS with xcode](#build-for-ios-on-macos-with-xcode)
*   [Build for WebAssembly](#build-for-webassembly)
*   [Build for AllWinner D1](#build-for-allwinner-d1)
*   [Build for Loongson 2K1000](#build-for-loongson-2k1000)
*   [Build for Termux on Android](#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 expirience.

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 devices the Vulkan support should be present in Nvidia provided SDK (Jetpack) or prebuild OS images.

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 Nvidia Jetson devices, add `-DCMAKE_TOOLCHAIN_FILE=../toolchains/jetson.toolchain.cmake` to cmake.

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.

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 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 <protobuf-root-dir> with a proper path):

cd mkdir -p build cd build cmake -G"NMake Makefiles" -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=%cd%/install -DProtobuf_INCLUDE_DIR=/build/install/include -DProtobuf_LIBRARIES=/build/install/lib/libprotobuf.lib -DProtobuf_PROTOC_EXECUTABLE=/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

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](https://github.com/Tencent/ncnn/blob/d91cccf/.github/workflows/macos-x64-gpu.yml#L50-L68) 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](https://github.com/android-ndk/ndk/issues/243)

```
# 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=../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
sudo cp install/include/* /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS.sdk/usr/include
sudo cp install/lib/libomp.a /Applications/Xcode.app/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=../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
sudo cp install/include/* /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneSimulator.platform/Developer/SDKs/iPhoneSimulator.sdk/usr/include
sudo cp install/lib/libomp.a /Applications/Xcode.app/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' 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>
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=`pwd`/../vulkansdk-macos-1.2.189.0/MoltenVK/include \
    -DVulkan_LIBRARY=`pwd`/../vulkansdk-macos-1.2.189.0/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 bug.

Open `/usr/lib/gcc/mips64el-linux-gnuabi64/8/include/msa.h`, find `__msa_fmadd_w` and apply changes as the following

```
// #define __msa_fmadd_w __builtin_msa_fmadd_w
#define __msa_fmadd_w(a, b, c) __builtin_msa_fmadd_w(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
```