ubuntu14.04下安装opencv-2.4.9
因为这一个月都在使用ubuntu系统，遇到很多问题，其中安装opencv的过程中也遇到各种安装出错的问题。
发现按照这篇博客的方法，从始至终一路畅通的安装好了原博客地址
**
一、准备工作
**
step 1，从官网下载opencv-2.4.9
或者从我的百度云盘；http://pan.baidu.com/s/1qXFXZmk
下载之后解压到ubuntu系统下的“下载”文件夹（也可以根据需要解压到别的文件夹）；
step 2 install build-essential；
build-essential 软件包，涵盖gcc/g++/gdb/make；
sudo apt-get install build-essentialstep 3 install pakcage about multi-media；支持读写图片以及视频等,about 100MB
sudo apt-get install libgtk2.0-dev libavcodec-dev libavformat-dev libtiff4-dev libswscale-dev libjasper-dev step 4 install cmake
sudo apt-get install cmakestep 5 install pkg-config
pkg-config，它是一个提供从源代码中编译软件时查询已安装的库时使用的统一接口的计算机软件。
sudo apt-get install pkg-config 二、编译安装过程
2.1 环境监测：
使用cmake来检测编译环境以及生成makefile以及其他project信息，在使用cmake过程可以设置一些参数。
在本目录下(opencv源码目录)使用cmake，注意后面的点表示在当前目录下寻找CMakeLists.txt。（cmake和“.”之间有一个空格）
cmake . 结果简略如下：
...
-- Configuring done
-- Generating done
-- Build files have been written to: /media/sda_m/opencv-2.4.92.2 使用make编译
耗时间20分钟，下一步试试有没有已经编译好的bin文件；
make 正确编译结果是：
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/traincascade.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/cascadeclassifier.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/boost.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/features.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/haarfeatures.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/lbpfeatures.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/HOGfeatures.cpp.o
[100%] Building CXX object apps/traincascade/CMakeFiles/opencv_traincascade.dir/imagestorage.cpp.o
Linking CXX executable ../../bin/opencv_traincascade
2.3 使用make install 安装
sudo make install 正确的结果提示是：
...
-- Set runtime path of "/usr/local/bin/opencv_haartraining" to "/usr/local/lib"
-- Installing: /usr/local/bin/opencv_createsamples
-- Set runtime path of "/usr/local/bin/opencv_createsamples" to "/usr/local/lib"
-- Installing: /usr/local/bin/opencv_performance
-- Set runtime path of "/usr/local/bin/opencv_performance" to "/usr/local/lib"
-- Installing: /usr/local/bin/opencv_traincascade
-- Set runtime path of "/usr/local/bin/opencv_traincascade" to "/usr/local/lib"
12.4 添加动态库信息
在文件/etc/ld.so.conf中添加 /usr/local/lib（这个跟安装目录有关， {CMAKE_INSTALL_PREFIX}/lib），
也可以在/etc/ld.so.conf.d 目录下增加一个conf文件（可以命名为 opencv.conf），同样添加 /usr/local/lib；
查看已经生成的动态库
root@noya-VirtualBox:/usr/local/lib# ls
libopencv_calib3d.so libopencv_gpu.so libopencv_nonfree.so libopencv_superres.so
libopencv_calib3d.so.2.4 libopencv_gpu.so.2.4 libopencv_nonfree.so.2.4 libopencv_superres.so.2.4
libopencv_calib3d.so.2.4.9 libopencv_gpu.so.2.4.9 libopencv_nonfree.so.2.4.9 libopencv_superres.so.2.4.9
libopencv_contrib.so libopencv_highgui.so libopencv_objdetect.so libopencv_ts.a
libopencv_contrib.so.2.4 libopencv_highgui.so.2.4 libopencv_objdetect.so.2.4 libopencv_video.so
libopencv_contrib.so.2.4.9 libopencv_highgui.so.2.4.9 libopencv_objdetect.so.2.4.9 libopencv_video.so.2.4
libopencv_core.so libopencv_imgproc.so libopencv_ocl.so libopencv_video.so.2.4.9
libopencv_core.so.2.4 libopencv_imgproc.so.2.4 libopencv_ocl.so.2.4 libopencv_videostab.so
libopencv_core.so.2.4.9 libopencv_imgproc.so.2.4.9 libopencv_ocl.so.2.4.9 libopencv_videostab.so.2.4
libopencv_features2d.so libopencv_legacy.so libopencv_photo.so libopencv_videostab.so.2.4.9
libopencv_features2d.so.2.4 libopencv_legacy.so.2.4 libopencv_photo.so.2.4 pkgconfig
libopencv_features2d.so.2.4.9 libopencv_legacy.so.2.4.9 libopencv_photo.so.2.4.9 python2.7
libopencv_flann.so libopencv_ml.so libopencv_stitching.so
libopencv_flann.so.2.4 libopencv_ml.so.2.4 libopencv_stitching.so.2.4
libopencv_flann.so.2.4.9 libopencv_ml.so.2.4.9 libopencv_stitching.so.2.4.9使用下面的动态库管理命令ldconfig，让opencv的相关链接库被系统共享；
sudo ldconfig -v 如果成功的话，我的检测方法如下，正确的结果将会发现前面动态库的名字
sudo ldconfig -v >temp.so.txt && cat temp.so.txt|grep opencv2.5 指定头文件位置
完成了动态库的共享，还不能使用opencv来编程，还需要为程序指定openvc的头文件位置。这里使用pkg-config命令来完成。首先在 /etc/profile 中添加
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
pkg-config 维护着一个关于opencv的配置文件，这个文件（opencv.pc）在目录 /usr/local/lib/pkgconfig，这个文件记录着opencv的一些动态库信息，还有头文件信息
输入pkg-config –cflags opencv 和pkg-config –libs opencv ,可以发现以下信息。
正确的结果是如下：
root@noya-VirtualBox:/usr/local/lib# pkg-config --cflags opencv
-I/usr/local/include/opencv -I/usr/local/include
root@noya-VirtualBox:/usr/local/lib# pkg-config --libs opencv
/usr/local/lib/libopencv_calib3d.so /usr/local/lib/libopencv_contrib.so /usr/local/lib/libopencv_core.so /usr/local/lib/libopencv_features2d.so /usr/local/lib/libopencv_flann.so /usr/local/lib/libopencv_gpu.so /usr/local/lib/libopencv_highgui.so /usr/local/lib/libopencv_imgproc.so /usr/local/lib/libopencv_legacy.so /usr/local/lib/libopencv_ml.so /usr/local/lib/libopencv_nonfree.so /usr/local/lib/libopencv_objdetect.so /usr/local/lib/libopencv_ocl.so /usr/local/lib/libopencv_photo.so /usr/local/lib/libopencv_stitching.so /usr/local/lib/libopencv_superres.so /usr/local/lib/libopencv_ts.a /usr/local/lib/libopencv_video.so /usr/local/lib/libopencv_videostab.so -lrt -lpthread -lm -ldl 这一步我没有出现这些信息；但是不影响后面的使用；
3 .测试
编译sample
在解压的opencv目录下找到 samples/c/build_all.sh，运行该文件
noya@noya-VirtualBox:/media/sda_m/opencv-2.4.9/samples/c$ ./build_all.sh
compiling contours.c
compiling convert_cascade.c
compiling delaunay.c
compiling fback_c.c
compiling morphology.c
compiling motempl.c
compiling polar_transforms.c
compiling pyramid_segmentation.c
compiling adaptiveskindetector.cpp
compiling bgfg_codebook.cpp
compiling blobtrack_sample.cpp
compiling facedetect.cpp
compiling find_obj.cpp
compiling find_obj_calonder.cpp
compiling find_obj_ferns.cpp
compiling latentsvmdetect.cpp
compiling mser_sample.cpp
compiling mushroom.cpp
compiling one_way_sample.cpp
compiling smiledetect.cpp
compiling tree_engine.cpplist all the executive;
find . -perm /u=x,g=x,o=x.
./find_obj_calonder #?
./adaptiveskindetector #?
./delaunay #ok
./facedetect #ok
./mser_sample #？
./blobtrack_sample #？
./one_way_sample #?
./latentsvmdetect #ok
./tree_engine #?
./bgfg_codebook #?
./motempl #?
./fback_c #?
./polar_transforms #?
./contours #ok
./find_obj #Ok
./smiledetect #ok
./mushroom #?
./convert_cascade #?
./morphology #ok
./pyramid_segmentation #ok
./find_obj_ferns #?末尾表示为 #?是当前不知道作用的，其他的ok都有结果的;可以自己调用；