arm ncnn

ncnn网址：https://github.com/Tencent/ncnn

1、

sudo apt-get update

sudo apt-get upgrade

2、

命令：sudo apt-get install g++-4.8-arm-linux-gnueabihf

sudo apt-get install gcc-4.8-arm-linux-gnueabihf

测试：

$arm-linux-gnueabihf-g++-4.8 --version

arm-linux-gnueabihf-g++-4.8 (Ubuntu/Linaro 4.8.5-4ubuntu1) 4.8.5

Copyright (C) 2015 Free Software Foundation, Inc.

This is free software; see the source for copying conditions.  There is NO

warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

sudo ln -s /usr/bin/arm-linux-gnueabihf-g++-4.8 /usr/bin/arm-linux-gnueabihf-g++

sudo ln -s /usr/bin/arm-linux-gnueabihf-gcc-4.8 /usr/bin/arm-linux-gnueabihf-gcc

arm linux 64位交叉编译器

网址：https://releases.linaro.org/components/toolchain/binaries/6.3-2017.05/aarch64-linux-gnu/

下载：gcc-linaro-6.3.1-2017.05-x86_64_aarch64-linux-gnu.tar.xz

vi ~/.bashrc

export PATH=/home/Your Name/armlinux/gcc-linaro-6.3.1-2017.05-x86_64_aarch64-linux-gnu/bin:$PATH

source ~/.bashrc

测试：

aarch64-linux-gnu-g++ --version

输出：

aarch64-linux-gnu-g++ (Linaro GCC 6.3-2017.05) 6.3.1 20170404
Copyright (C) 2016 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

　　

3、在ncnn目录下的CMakeLists.txt，在cmake_minimum_required(VERSION 2.8.10)下面添加

set(CMAKE_C_COMPILER arm-linux-gnueabihf-gcc)
set(CMAKE_CXX_COMPILER arm-linux-gnueabihf-g++)
add_definitions(-D__ARM_NEON)
add_definitions("-mfpu=neon")

4、 src文件夹下，修改该文件夹下的CMakeLists.txt文件。删除如下图所示代码：

CMakeLists.txt为

##############################################

configure_file(platform.h.in ${CMAKE_CURRENT_BINARY_DIR}/platform.h)

include_directories(${CMAKE_CURRENT_SOURCE_DIR})
include_directories(${CMAKE_CURRENT_BINARY_DIR})
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/layer)

set(ncnn_SRCS
    allocator.cpp
    blob.cpp
    cpu.cpp
    layer.cpp
    mat.cpp
    mat_pixel.cpp
    modelbin.cpp
    net.cpp
    opencv.cpp
    paramdict.cpp
    benchmark.cpp
)

macro(ncnn_add_layer class)
    string(TOLOWER ${class} name)

    # WITH_LAYER_xxx option
    if(${ARGC} EQUAL )
        option(WITH_LAYER_${name} "build with layer ${name}" ${ARGV1})
    else()
        option(WITH_LAYER_${name} "build with layer ${name}" ON)
    endif()

    message("WITH_LAYER_${name} = ${WITH_LAYER_${name}}")

    if(WITH_LAYER_${name})
        list(APPEND ncnn_SRCS "${CMAKE_CURRENT_SOURCE_DIR}/layer/${name}.cpp")

        # look for arch specific implementation and append source
        # optimized implementation for armv7 aarch64
            if(EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/layer/arm/${name}_arm.cpp")
                list(APPEND ncnn_SRCS "${CMAKE_CURRENT_SOURCE_DIR}/layer/arm/${name}_arm.cpp")
                set(WITH_LAYER_${name}_arm )
            endif()

    endif()

    # generate layer_declaration and layer_registry file
    if(WITH_LAYER_${name})
        if(WITH_LAYER_${name}_arm)
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_declaration.h
                "extern Layer* ${class}_arm_layer_creator();\n")
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_registry.h
                "#if NCNN_STRING\n{\"${class}\",${class}_arm_layer_creator},\n#else\n{${class}_arm_layer_creator},\n#endif\n")
        elseif(WITH_LAYER_${name}_x86)
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_declaration.h
                "extern Layer* ${class}_x86_layer_creator();\n")
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_registry.h
                "#if NCNN_STRING\n{\"${class}\",${class}_x86_layer_creator},\n#else\n{${class}_x86_layer_creator},\n#endif\n")
        else()
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_declaration.h
                "extern Layer* ${class}_layer_creator();\n")
            file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_registry.h
                "#if NCNN_STRING\n{\"${class}\",${class}_layer_creator},\n#else\n{${class}_layer_creator},\n#endif\n")
        endif()
    else()
        file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_registry.h "#if NCNN_STRING\n{\"${class}\",0},\n#else\n{0},\n#endif\n")
    endif()

    # generate layer_type_enum file
    file(APPEND ${CMAKE_CURRENT_BINARY_DIR}/layer_type_enum.h "${class} = ${__LAYER_TYPE_ENUM_INDEX},\n")
    math(EXPR __LAYER_TYPE_ENUM_INDEX "${__LAYER_TYPE_ENUM_INDEX}+1")
endmacro()

# create new
file(REMOVE ${CMAKE_CURRENT_BINARY_DIR}/layer_declaration.h)
file(REMOVE ${CMAKE_CURRENT_BINARY_DIR}/layer_registry.h)
file(REMOVE ${CMAKE_CURRENT_BINARY_DIR}/layer_type_enum.h)
set(__LAYER_TYPE_ENUM_INDEX )

# layer implementation
ncnn_add_layer(AbsVal)
ncnn_add_layer(ArgMax OFF)
ncnn_add_layer(BatchNorm)
ncnn_add_layer(Bias)
ncnn_add_layer(BNLL)
ncnn_add_layer(Concat)
ncnn_add_layer(Convolution)
ncnn_add_layer(Crop)
ncnn_add_layer(Deconvolution)
ncnn_add_layer(Dropout)
ncnn_add_layer(Eltwise)
ncnn_add_layer(ELU)
ncnn_add_layer(Embed)
ncnn_add_layer(Exp)
ncnn_add_layer(Flatten)
ncnn_add_layer(InnerProduct)
ncnn_add_layer(Input)
ncnn_add_layer(Log)
ncnn_add_layer(LRN)
ncnn_add_layer(MemoryData)
ncnn_add_layer(MVN)
ncnn_add_layer(Pooling)
ncnn_add_layer(Power)
ncnn_add_layer(PReLU)
ncnn_add_layer(Proposal)
ncnn_add_layer(Reduction)
ncnn_add_layer(ReLU)
ncnn_add_layer(Reshape)
ncnn_add_layer(ROIPooling)
ncnn_add_layer(Scale)
ncnn_add_layer(Sigmoid)
ncnn_add_layer(Slice)
ncnn_add_layer(Softmax)
ncnn_add_layer(Split)
ncnn_add_layer(SPP OFF)
ncnn_add_layer(TanH)
ncnn_add_layer(Threshold)
ncnn_add_layer(Tile OFF)
ncnn_add_layer(RNN OFF)
ncnn_add_layer(LSTM OFF)
ncnn_add_layer(BinaryOp)
ncnn_add_layer(UnaryOp)
ncnn_add_layer(ConvolutionDepthWise)
ncnn_add_layer(Padding)
ncnn_add_layer(Squeeze)
ncnn_add_layer(ExpandDims)
ncnn_add_layer(Normalize)
ncnn_add_layer(Permute)
ncnn_add_layer(PriorBox)
ncnn_add_layer(DetectionOutput)
ncnn_add_layer(Interp)
ncnn_add_layer(DeconvolutionDepthWise)
ncnn_add_layer(ShuffleChannel)
ncnn_add_layer(InstanceNorm)
ncnn_add_layer(Clip)
ncnn_add_layer(Reorg)
ncnn_add_layer(YoloDetectionOutput)
ncnn_add_layer(Quantize)
ncnn_add_layer(Dequantize)
ncnn_add_layer(Yolov3DetectionOutput)

add_library(ncnn STATIC ${ncnn_SRCS})

if(COVERAGE)
    target_compile_options(ncnn PRIVATE --coverage)
endif()

install(TARGETS ncnn ARCHIVE DESTINATION lib)
install(FILES
    allocator.h
    blob.h
    cpu.h
    layer.h
    layer_type.h
    mat.h
    modelbin.h
    net.h
    opencv.h
    paramdict.h
    benchmark.h
    ${CMAKE_CURRENT_BINARY_DIR}/layer_type_enum.h
    ${CMAKE_CURRENT_BINARY_DIR}/platform.h
    DESTINATION include
)

编译

git clone https://github.com/Tencent/ncnn
cd ncnn
mkdir build
cd build
cmake ..
make -j
make install

检查：

readelf libncnn.a –a

最后出现

Tag_Advanced_SIMD_arch: NEONv1  编译正确