• 【视频开发】【计算机视觉】doppia编译之四：安装其他库、编译和运行doppia

    （与本节内容无关///////////////////////////保存图片参数为—-gui.save_all_screenshots true////////////////////） 
    在我们安装好CUDA、boost、OpenCV之后，接下来的一些库（libSDL、protobuf等）的安装，我们都可以用系统内部的程序进行安装。比如

    安装libSDL,我们终端输入

    apt-cache search libsdl
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    系统会给出一系列程序，我们选择其中的libsdl1.2-dev进行安装。

    sudo apt-get install libsdl1.2-dev
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    (这里注意不要安装libsdl2-dev,因为安装之后生成的文件夹是SDL2,之后doppia调用时会出现找不到“SDL files”的错误)

    安装protobuf库，则是我经过多番测试，得到的能够通过v1,v2测试的安装方法。（之前尝试安装protobuf2.5.0和protobuf2.4.1,doppia都找不到路径，而想把它们删除又删除不了，很麻烦），之后我测试了几个自带的protobuf库，发现安装以下四个库能够通过v1,v2的测试，安装命令为：

    sudo apt-get install libprotobuf-dev libprotoc-dev python-protobuf protobuf-compiler
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    切换到doppia目录下，运行

    sudo sh ./generate_protocol_buffer_files.sh
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    protobuf通过doppia-v1检测的返回信息为

    Generating objects detection files...
(Ground plane and video input files not yet handled by this script)
End of game. Have a nice day!
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    protobuf通过doppia-v2检测的返回信息为

    + cd src/objects_detection/
+ protoc --cpp_out=./ detector_model.proto detections.proto
+ protoc --python_out=../../tools/objects_detection/ detector_model.proto detections.proto
+ cd ../..
+ cd src/stereo_matching/ground_plane/
+ protoc --cpp_out=./ plane3d.proto
+ protoc --python_out=../../../tools/stixels_evaluation plane3d.proto
+ cd ../../..
+ cd src/stereo_matching/stixels/
+ protoc --cpp_out=./ -I. -I../ground_plane --include_imports stixels.proto ground_top_and_bottom.proto
--include_imports only makes sense when combined with --descriptor_set_out.
+ protoc --python_out=../../../tools/stixels_evaluation -I. -I../ground_plane --include_imports stixels.proto ground_top_and_bottom.proto
--include_imports only makes sense when combined with --descriptor_set_out.
+ cd ../../..
+ cd src/video_input/calibration
+ protoc --cpp_out=./ calibration.proto
+ cd ../../..
+ cd src/helpers/data
+ protoc --cpp_out=./ DataSequenceHeader.proto
+ protoc --python_out=../../../tools/data_sequence DataSequenceHeader.proto
+ cd ../../..
+ cd src/helpers
+ cd ../..
+ cd src/tests/data_sequence/
+ protoc --cpp_out=./ TestData.proto
+ cd ../../..
+ echo End of game. Have a nice day!
End of game. Have a nice day!
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    到这里，我们该安装的库大部分已经安装成功，接下来就可以开始编译doppia啦！（至于可能还缺少的库，可以根据doppia的错误提示进行安装）

    编译运行doppia/src/applications/objects_detection 
    由于我只需要用到doppia的objects_detection的功能，而之前我在编译doppia-v2时，ground_estimation和stixel_world都能编译运行。所以这次在编译doppia-v1时，我就直接切入“主题”，编译运行objects_detection。下面也主要是列出我在编译objects_detection是遇到的问题以及相应的解决方案。

    错误一，创建(build)错误 
    error:

    /home/mx/doppia/src/applications/objects_detection/../../../src/helpers/data/DataSequence.hpp:293:56: error: invalid use of incomplete type ‘class google::protobuf::io::CodedInputStream’
     const bool read_size_success = input_coded_stream_p->ReadLittleEndian64(&size);
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    solution: 
    在

    doppia/src/helpers/data/DataSequence.hpp
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    头文件中，在

    #include "DataSequenceHeader.pb.h"
#include <google/protobuf/io/zero_copy_stream_impl.h>
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    两行之间添加一行新的引用，如下，

    #include "DataSequenceHeader.pb.h"
#include <google/protobuf/io/coded_stream.h>
#include <google/protobuf/io/zero_copy_stream_impl.h>
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    错误二，创建(build)错误 
    error:

    /home/mx/doppia/src/applications/objects_detection/../../../src/objects_detection/gpu/integral_channels_detector.cu.hpp:23:9: error: ‘fast_stage_t’ in ‘class doppia::SoftCascadeOverIntegralChannelsModel’ does not name a type
 typedef SoftCascadeOverIntegralChannelsModel::fast_stage_t cascade_stage_t;
         ^
/home/mx/doppia/src/applications/objects_detection/../../../src/objects_detection/gpu/integral_channels_detector.cu.hpp:33:36: error: ‘cascade_stage_t’ was not declared in this scope
 typedef Cuda::DeviceMemoryLinear2D<cascade_stage_t> gpu_detection_cascade_per_scale_t;
                                    ^
/home/mx/doppia/src/applications/objects_detection/../../../src/objects_detection/gpu/integral_channels_detector.cu.hpp:33:51: error: template argument 1 is invalid
 typedef Cuda::DeviceMemoryLinear2D<cascade_stage_t> gpu_detection_cascade_per_scale_t;
                                                   ^
/home/mx/doppia/src/applications/objects_detection/../../../src/objects_detection/gpu/integral_channels_detector.cu.hpp:33:86: error: invalid type in declaration before ‘;’ token
 typedef Cuda::DeviceMemoryLinear2D<cascade_stage_t> gpu_detection_cascade_per_scale_t;
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    这里出现错误原因是因为common_settings.cmake中没有添加cuda链接库路径。 
    solution: 
    编辑common_settings.cmake,在其中添加一个条件项

    elseif(${HOSTNAME} STREQUAL  "mx-pc")
  message(STATUS "Using mx-pc optimisation options")

  option(USE_GPU "Should the GPU be used ?" TRUE)
  set(CUDA_BUILD_CUBIN OFF)
  set(local_CUDA_LIB_DIR "/usr/local/cuda/lib64")
  set(cuda_LIBS "")
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    这里mx-pc是我电脑的主机名，你需要将它改成自己电脑的主机名。

    错误三，创建(build)错误 
    error:

    /home/mx/doppia/src/objects_detection/SoftCascadeOverIntegralChannelsFastFractionalStage.cpp:24:9: error: ‘swap’ is not a member of ‘std’
         std::swap(weak_classifier.level2_true_node, weak_classifier.level2_false_node);
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    solution: 
    在

    doppia/src/objects_detection/SoftCascadeOverIntegralChannelsFastFractionalStage.cpp
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    文件开头添加一行引用

    #include<iostream>
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    解决了以上三个错误后，doppia就可以创建(build)成功啦！但要想运行成功，还得改正以下2个错误。

    错误四，链接(link)错误 
    error:

    Linking CXX executable objects_detection
/usr/bin/ld: cannot find -lboost_program_options-mt
/usr/bin/ld: cannot find -lboost_filesystem-mt
/usr/bin/ld: cannot find -lboost_system-mt
/usr/bin/ld: cannot find -lboost_thread-mt
collect2: error: ld returned 1 exit status
make[2]: *** [objects_detection] 错误 1
make[1]: *** [CMakeFiles/objects_detection.dir/all] 错误 2
make: *** [all] 错误 2
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    这里出现错误的原因，是boost库链接出错，这时候我们需要修改CMakeList.txt文件，这里我就直接把CMakeList.txt贴出来，修改的地方做过注释。 
    solution:

    # This is a CMake build file, for more information consult:
# http://en.wikipedia.org/wiki/CMake
# and
# http://www.cmake.org/Wiki/CMake
# http://www.cmake.org/cmake/help/syntax.html
# http://www.cmake.org/Wiki/CMake_Useful_Variables
# http://www.cmake.org/cmake/help/cmake-2-8-docs.html

# to compile the local code you can use: cmake ./ && make -j2

# ----------------------------------------------------------------------
# Base CMake setup

cmake_minimum_required (VERSION 2.6)

set(doppia_root "../../..")

set(CMAKE_MODULE_PATH $ENV{CMAKE_MODULE_PATH})
set(CMAKE_MODULE_PATH "./" ${doppia_root} ${CMAKE_MODULE_PATH})
set(CMAKE_MODULE_PATH "/home/rodrigob/work/code/doppia_references/cuda/FindCUDA/CMake/cuda" ${CMAKE_MODULE_PATH})
set(CMAKE_MODULE_PATH "/users/visics/rbenenso/code/references/cuda/FindCUDA/CMake/cuda" ${CMAKE_MODULE_PATH})

# ----------------------------------------------------------------------
# Setup the project

include(FindPkgConfig)
project (ObjectsDetection)

# ----------------------------------------------------------------------
# Site specific configurations
include(${doppia_root}/common_settings.cmake)

# ----------------------------------------------------------------------
# Setup required libraries
pkg_check_modules(libpng REQUIRED libpng)
#pkg_check_modules(OpenEXR REQUIRED OpenEXR)
pkg_check_modules(opencv REQUIRED opencv>=2.3)
#set(vw_LIBRARIES "-lvwCore -lvwImage -lvwStereo -lvwFileIO -lvwMath -lvwInterestPoint")

set(opencv_LIBRARIES
    opencv_core opencv_imgproc opencv_highgui opencv_ml
    opencv_video opencv_features2d
    opencv_calib3d
    #opencv_objdetect opencv_contrib
    opencv_legacy opencv_flann
   ) # quick hack for opencv2.4 support

# 修改1:find where is boost 
#(+)find_package(Boost REQUIRED  
#(+)   COMPONENTS program_options filesystem system thread
#(+) )
find_package(Boost REQUIRED  
   COMPONENTS program_options filesystem system thread
) 

# ----------------------------------------------------------------------
# Setup CUDA
if(USE_GPU)
  find_package(CUDA 4.0 REQUIRED)
  include_directories(${CUDA_INCLUDE_DIRS} ${CUDA_CUT_INCLUDE_DIR})
endif(USE_GPU)

# ----------------------------------------------------------------------
# Setup link and include directories

set(local_LIBRARY_DIRS
  "/usr/local/lib"
  "/users/visics/rbenenso/no_backup/usr/local/lib"
  "/usr/lib64"
  "/usr/lib64/atlas"
  "/usr/lib/sse2/atlas"
  "/usr/lib/llvm-2.8/lib"
  ${local_CUDA_LIB_DIR}
)
set(local_INCLUDE_DIRS
  "/users/visics/rbenenso/no_backup/usr/local/include"
  "/usr/include/eigen2/"
   "/usr/local/include/eigen2"
   "/usr/local/cuda/include"
   ${CUDA_INCLUDE_DIRS}
)

link_directories(
  ${libpng_LIBRARY_DIRS}
  ${OpenEXR_LIBRARY_DIRS}
  ${opencv_LIBRARY_DIRS}
  ${local_LIBRARY_DIRS}
)

include_directories(
  "${doppia_root}/libs"
  "${doppia_root}/src"
  ${libpng_INCLUDE_DIRS}
  ${OpenEXR_INCLUDE_DIRS}
  ${opencv_INCLUDE_DIRS}
  ${local_INCLUDE_DIRS}
  "${doppia_root}/libs/cudatemplates/include"
)

if(USE_GPU)
cuda_include_directories("${doppia_root}/libs/")
endif(USE_GPU)

# ----------------------------------------------------------------------
# Collect source files

set(doppia_src "${doppia_root}/src")
set(doppia_stereo "${doppia_root}/src/stereo_matching")

file(GLOB SrcCpp
  "./ObjectsDetection*.cpp"
  "./draw*.cpp"
  "${doppia_src}/*.cpp"
  #"${doppia_src}/objects_detection/*.c*"
  "${doppia_src}/objects_detection/Abstract*.c*"
  "${doppia_src}/objects_detection/*Converter.c*"
  "${doppia_src}/objects_detection/Base*.c*"
  "${doppia_src}/objects_detection/*Factory.c*"
  "${doppia_src}/objects_detection/Greedy*.c*"
  "${doppia_src}/objects_detection/Detection*.c*"
  "${doppia_src}/objects_detection/*Model.c*"
  "${doppia_src}/objects_detection/*Stage.c*"
  "${doppia_src}/objects_detection/*Integral*.c*"
  "${doppia_src}/objects_detection/MultiscalesIntegral*.c*"
  "${doppia_src}/objects_detection/integral_channels/Integral*.cpp"
  "${doppia_src}/objects_detection/FastestPedestrian*.c*"
  "${doppia_src}/objects_detection/DetectorSearchRange.c*"
  "${doppia_src}/objects_detection/*.pb.c*"
  "${doppia_src}/objects_detection/non_maximal_suppression/*.c*"

  "${doppia_src}/objects_tracking/*.cpp"

  "${doppia_src}/applications/*.cpp"
  "${doppia_src}/applications/stixel_world/*Gui.cpp"
  "${doppia_src}/applications/stixel_world/draw*.cpp"

  #"${doppia_stereo}/*.cpp"
  "${doppia_stereo}/cost_volume/*CostVolume.cpp"
  "${doppia_stereo}/cost_volume/*CostVolumeEstimator*.cpp"
  "${doppia_stereo}/cost_volume/DisparityCostVolumeFromDepthMap.cpp"
  "${doppia_stereo}/cost_functions.cpp"
  "${doppia_stereo}/CensusCostFunction.cpp"
  "${doppia_stereo}/CensusTransform.cpp"
  "${doppia_stereo}/GradientTransform.cpp"
  "${doppia_stereo}/AbstractStereoMatcher.cpp"
  "${doppia_stereo}/AbstractStereoBlockMatcher.cpp"
  "${doppia_stereo}/SimpleBlockMatcher.cpp"
  "${doppia_stereo}/MutualInformationCostFunction.cpp"
  "${doppia_stereo}/ConstantSpaceBeliefPropagation.cpp"
  "${doppia_stereo}/qingxiong_yang/*.cpp"
  "${doppia_stereo}/SimpleTreesOptimizationStereo.cpp"
  "${doppia_stereo}/OpenCvStereo.cpp"

  "${doppia_stereo}/ground_plane/*.cpp"
  "${doppia_stereo}/stixels/*.cpp"
   #"${doppia_stereo}/stixels/*.cc"
  "${doppia_src}/video_input/*.cpp"
  "${doppia_src}/video_input/calibration/*.c*"
  "${doppia_src}/video_input/preprocessing/*.cpp"
  #"${doppia_src}/features_tracking/*.cpp"
  "${doppia_src}/image_processing/*.cpp"
  "${doppia_src}/drawing/gil/*.cpp"
)


file(GLOB HelpersCpp
  #"${doppia_src}/helpers/*.cpp"
  "${doppia_src}/helpers/data/*.c*"
  "${doppia_src}/helpers/any_to_string.cpp"
  "${doppia_src}/helpers/get_section_options.cpp"
  "${doppia_src}/helpers/Log.cpp"
  "${doppia_src}/helpers/loggers.cpp"
  "${doppia_src}/helpers/AlignedImage.cpp"
  "${doppia_src}/helpers/replace_environment_variables.cpp"
  "${doppia_src}/helpers/objects_detection/*.cpp"
)

file(GLOB SrcGpuCpp
  "${doppia_src}/objects_detection/Gpu*.cpp"
  "${doppia_src}/objects_detection/integral_channels/Gpu*.cpp"
  "${doppia_src}/helpers/gpu/*.cpp"

  #"${doppia_stereo}/SimpleTreesGpuStereo.cpp"
)

file(GLOB SrcCuda
  "${doppia_src}/objects_detection/integral_channels/gpu/*.cu"
  "${doppia_src}/objects_detection/integral_channels/gpu/*.cpp"
  "${doppia_src}/objects_detection/gpu/*.cu"
  "${doppia_src}/objects_detection/gpu/*.cpp"

  #"${doppia_src}/helpers/gpu/*.cu"

#  "${doppia_stereo}/*.cu.c*"
#  "${doppia_stereo}/*.cu"
#  "${doppia_stereo}/gpu/*.cu.c*"
#  "${doppia_stereo}/gpu/*.cu"
)

list(REMOVE_ITEM SrcCpp ${SrcCuda}) # just in case


if(USE_GPU)

# add GPU related source code to the executable list
list(APPEND SrcCpp ${SrcGpuCpp})

# add GPU related libraries
list(APPEND opencv_LIBRARIES opencv_gpu)

# ----------------------------------------------------------------------
# Compile CUDA stuff
cuda_include_directories(${local_CUDA_CUT_INCLUDE_DIRS})
cuda_include_directories(${CUDA_INCLUDE_DIRS} ${CUDA_CUT_INCLUDE_DIR} ${local_CUDA_CUT_INCLUDE_DIR})
link_directories(${local_CUDA_CUT_LIBRARY_DIRS})

cuda_add_library(cuda_stuff_library ${SrcCuda})
target_link_libraries(cuda_stuff_library
   ${CUDA_LIBRARIES}
   ${cutil_LIB}
)

#set(CUDA_NVCC_FLAGS ${CUDA_NVCC_FLAGS} --generate-line-info) # used during profiling

endif(USE_GPU)
# ----------------------------------------------------------------------
# Create the executable
#set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x") # required for unrestricted unions
#set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -p") # add gprof information

add_library(cpp_stuff_library  ${SrcCpp} ${HelpersCpp})

add_executable(objects_detection "./objects_detection.cpp")

target_link_libraries(objects_detection

   cpp_stuff_library

   ${cg_LIBRARIES}
   # linking with CgGL _after_ boost_program_options generates a segmentation fault ! boost_program_options 1.39 has a bug
   #修改2:link to boost
   #(-)boost_program_options-mt boost_filesystem-mt boost_system-mt boost_thread-mt
   #(+)${Boost_LIBRARIES}
   ${Boost_LIBRARIES}
   protobuf pthread
   SDL X11 Xext #Xrandr
   gomp
   ${libpng_LIBRARIES} jpeg
#  ${OpenEXR_LIBRARIES} 
   ${opencv_LIBRARIES}

   #${vw_LIBRARIES}
   #csparse sparse spblas mv
   #lapack blas atlas

   ${google_perftools_LIBS} # enables profiling, see http://code.google.com/p/google-perftools

   #`OcelotConfig -l`
   #ocelot
   #boost_system-mt boost_filesystem-mt boost_thread-mt
   #GLEW
   #LLVMAsmParser LLVMX86Disassembler LLVMX86AsmParser LLVMX86CodeGen LLVMSelectionDAG
   #LLVMAsmPrinter LLVMMCParser LLVMX86AsmPrinter LLVMX86Info LLVMJIT
   #LLVMExecutionEngine LLVMCodeGen LLVMScalarOpts LLVMInstCombine LLVMTransformUtils LLVMipa
   #LLVMAnalysis LLVMTarget LLVMMC LLVMCore LLVMSupport LLVMSystem
)   

if(USE_GPU)
target_link_libraries(objects_detection cuda_stuff_library ${local_CUDA_LIB})
endif(USE_GPU)
# ----------------------------------------------------------------------
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    到这里就OK啦！

    最后运行成功你会看到一个简短地video，以及下面这样的信息

    2015-05-09 16:33:23 {7feb06974880} [ BaseIntegralChannelsDetector ] : Warning: At scale index 47 the detection window size is larger than the biggest ground plane corridor. Setting the detection search to a single line.
scale_index == 47, original_height == 18, updated_height == 1
Expected speed gain == 5.28x (num pixels original/updated)
GpuVeryFastIntegralChannelsDetector::compute_v2 max search range (min_x, min_y; max_x, max_y) == (0, 0; 153, 58)
2015-05-09 16:33:23 {7feb06974880} [ GpuIntegralChannelsDetector ] : scaled_x == 640, scaled_y == 480
Requested frame number 11 but frames should be in range (0, 10)
Processed a total of 10 input frames
Average objects detection speed per iteration 29.36 [Hz] (in the last 10 iterations)
End of game, have a nice day.
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    好啦，doppia编译到此也就结束啦！ 
    希望这几篇文章能帮助正在读博客的你。

    doppia及作者相关介绍链接： 
    http://blog.csdn.net/xizero00/article/details/43227019 
    https://bitbucket.org/rodrigob/doppia
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  • 原文地址：https://www.cnblogs.com/huty/p/8517099.html
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