ubuntu 12.04 on citrix xenserver 5.6

After upgrading my virtualized Ubuntu 11.10 installation to Ubuntu 12.04 Precise Pangolin, I've had strange problems on booting up the virtual machine: Sometimes it booted up smoothly, sometimes it hung, sometimes it reported a read-only filesystem due to errors (which actually could not be found using fsck). After some investigation, I decided to re-install the system.

I wanted to install Ubuntu 12.04 LTS para-virtualized (PV), but this is not supported out of the box by Citrix XenServer 5.6 SP2. However, I've found some really useful instructions in the Citrix Forums written for for Ubuntu 11.04, also working for Ubuntu 12.04:

1. Enter the XenServer Console and get the UUID of the Ubuntu 10.10 template:

   xe template-list name-label="Ubuntu Lucid Lynx 10.04 (64-bit) (experimental)" --minimal

2. Clone the Ubuntu 10.10 template:

   xe vm-clone uuid=[UUID from step 1 here] new-name-label="Ubuntu Precise Pangolin 12.04 (64-bit)"

3. Configute the new Ubuntu 12.04 template:

   xe template-param-set other-config:default_template=true other-config:debian-release=precise uuid=[UUID from step 2 here]

4. Create a new VM and choose your newly created Ubuntu 12.04 template.
5. Enter the following url under "Install from URL:"

   http://archive.ubuntu.net/ubuntu/

6. Create a separate /boot partition at the beginning of the virtual disk (I chose 256 MB).
7. After the installation is completed, log into your new VM and become root.

   sudo -s

8. Install the virtual kernel image:

   apt-get install linux-virtual linux-image-virtual linux-headers-virtual

9. Remove the generic kernel image:

   apt-get remove linux-generic linux-headers-generic linux-image-generic

10. Update the grub boot loader:

    update-grub

11. Insert the XenServer Tools xs-tools.iso and mount it:

    mount /dev/xvdd /mnt

12. Install the XenServer Tools:

    cd /mnt/Linux
    dpkg -i *amd64.deb

13. Unmount the ISO and reboot:

    cd
    umount /mnt
    reboot

14. That's it!
    

I haven't tried, but this might work for Citrix XenServer 6, too.

Install OpenCV 2.4 on Ubuntu 12.04

If you’re going to process live streams from cameras or videos, the most important library needed for OpenCV is ffmpeg. You can find a good tutorial on how to compile and install ffmpeg on Ubuntu here.
You need to follow those steps, the only difference necessary is to add

--enable-shared --enable-pic

to all configurations. For example this is the configuration needed for ffmpeg:

./configure --enable-gpl --enable-libfaac --enable-libmp3lame --enable-libopencore-amrnb 
    --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libvpx 
    --enable-nonfree --enable-version3 --enable-x11grab --enable-shared --enable-pic

If you forget to do so it’s likely you get this error when compiling ffmpeg:

undefined reference to `x264_encoder_open_124'

Once ffmpeg is installed you’re ready to compile OpenCV. There is a short introduction in the official documentation on how to compile and install OpenCV.

Installation in Linux

These steps have been tested for Ubuntu 10.04 but should work with other distros.

cd ~/<my_working _directory>
svn co http://code.opencv.org/svn/opencv/trunk

Following those steps should be very easy. After running cmake a summary is printed which is important and you should pay attention to. This is the configuration summary on my system:

-- General configuration for OpenCV 2.4.0 =====================================
-- Version control:                 svn:8310M
-- 
--   Platform:
--     Host:                        Linux 3.2.0-24-generic x86_64
--     CMake:                       2.8.7
--     CMake generator:             Unix Makefiles
--     CMake build tool:            /usr/bin/make
--     Configuration:               RELEASE
-- 
--   C/C++:
--     Built as dynamic libs?:      YES
--     C++ Compiler:                /usr/bin/c++ (ver 4.6.3)
--     C++ flags (Release):         -Wall -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -ffunction-sections -O3 -DNDEBUG   -DNDEBUG
--     C++ flags (Debug):           -Wall -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -ffunction-sections -g  -O0 -DDEBUG -D_DEBUG -ggdb3
--     C Compiler:                  /usr/bin/gcc
--     C flags (Release):           -Wall -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -ffunction-sections -O3 -DNDEBUG  -DNDEBUG
--     C flags (Debug):             -Wall -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -ffunction-sections -g  -O0 -DDEBUG -D_DEBUG -ggdb3
--     Linker flags (Release):      
--     Linker flags (Debug):        
-- 
--   OpenCV modules:
--     To be built:                 calib3d contrib core features2d flann gpu highgui imgproc legacy ml nonfree objdetect photo python stitching ts video videostab
--     Disabled by user:            -
--     Disabled by dependency:      -
--     Unavailable:                 androidcamera java
-- 
--   GUI: 
--     QT 4.x:                      YES (ver 4.8.1 EDITION = OpenSource)
--     QT OpenGL support:           YES (/usr/lib/x86_64-linux-gnu/libQtOpenGL.so)
--     OpenGL support:              YES (/usr/lib/x86_64-linux-gnu/libGLU.so /usr/lib/x86_64-linux-gnu/libGL.so /usr/lib/libSM.so /usr/lib/x86_64-linux-gnu/libICE.so /usr/lib/x86_64-linux-gnu/libX11.so /usr/lib/x86_64-linux-gnu/libXext.so)
-- 
--   Media I/O: 
--     ZLib:                        /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.3.4)
--     JPEG:                        /usr/lib/x86_64-linux-gnu/libjpeg.so (ver )
--     PNG:                         /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.2.46)
--     TIFF:                        /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42)
--     JPEG 2000:                   /usr/lib/x86_64-linux-gnu/libjasper.so (ver 1.900.1)
--     OpenEXR:                     /usr/lib/libImath.so /usr/lib/libIlmImf.so /usr/lib/libIex.so /usr/lib/libHalf.so /usr/lib/libIlmThread.so (ver 1.6.1)
--     OpenNI:                      NO
--     OpenNI PrimeSensor Modules:  NO
-- 
--   Video I/O:
--     DC1394 1.x:                  NO
--     DC1394 2.x:                  YES (ver 2.2.0)
--     GStreamer:                   
--       base:                      YES (ver 0.10.36)
--       app:                       YES (ver 0.10.36)
--       video:                     YES (ver 0.10.36)
--     UniCap:                      NO
--     UniCap ucil:                 NO
--     PvAPI:                       NO
--     V4L/V4L2:                    Using libv4l (ver 0.8.5)
--     Xine:                        NO
--     FFMPEG:                      YES
--       codec:                     YES (ver 53.7.0)
--       format:                    YES (ver 53.4.0)
--       util:                      YES (ver 51.9.1)
--       swscale:                   YES (ver 2.0.0)
--       gentoo-style:              YES
-- 
--   Other third-party libraries:
--     Use IPP:                     NO
--     Use TBB:                     YES (ver 4.0 interface 6000)
--     Use Cuda:                    NO
--     Use Eigen:                   YES (ver 2.0.17)
--     Use Clp:                     NO
-- 
--   Python:
--     Interpreter:                 /usr/bin/python (ver 2.7.3)
--     Libraries:                   /usr/lib/libpython2.7.so
--     numpy:                       /usr/lib/python2.7/dist-packages/numpy/core/include (ver 1.6.1)
--     packages path:               lib/python2.7/dist-packages
-- 
--   Documentation:
--     Build Documentation:         YES
--     Sphinx:                      /usr/local/bin/sphinx-build (ver 1.1.3)
--     PdfLaTeX compiler:           /usr/bin/pdflatex
-- 
--   Tests and samples:
--     Tests:                       YES
--     Performance tests:           YES
--     Examples:                    NO
-- 
--   Install path:                  /usr/local
-- 
--   cvconfig.h is in:              /home/shambool/code/libs/opencv_svn/build
-- -----------------------------------------------------------------

It’s a good idea to install Intel TBB if you don’t have it already, to improve the speed of some methods. As you can see in the summary my system doesn’t support CUDA and hence OpenCV couldn’t find the libraries. There are two ways to change these parameters. One is to pass the value of the parameters to cmake, and the second is to edit

opencv/CMakeLists.txt

and change the value of the parameters. I prefer the former, and have enabled the support for OpenGL and QT.

Update: there is an installation guide here that you may find useful, particularly if you don’t know what libraries are needed for OpenCV. And you can find the official documentation [url=”http://docs.opencv.org/”here[/url].

Installing OpenCV 2.2 in Ubuntu 11.04

Many people have used my previous tutorial about installing OpenCV 2.1 in Ubuntu 9.10. In the comments of that post, I noticed great interest for using OpenCV with Python and the Intel Threading Building Blocks (TBB). Since new versions of OpenCV and Ubuntu are available, I decided to create a new post with detailed instructions for installing the latest version of OpenCV, 2.2, in the latest version of Ubuntu, 11.04, with Python and TBB support.

First, you need to install many dependencies, such as support for reading and writing image files, drawing on the screen, some needed tools, etc… This step is very easy, you only need to write the following command in the Terminal

1	sudo apt-get install build-essential libgtk2.0-dev libjpeg62-dev libtiff4-dev libjasper-dev libopenexr-dev cmake python-dev python-numpy libtbb-dev libeigen2-dev yasm libfaac-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev

Now we need to get and compile the ffmpeg source code so that video files work properly with OpenCV. This section is partially based on the method discussed here.

1

cd ~

2	wget http://ffmpeg.org/releases/ffmpeg-0.7-rc1.tar.gz

3	tar -xvzf ffmpeg-0.7-rc1.tar.gz

4	cd ffmpeg-0.7-rc1

5	./configure --enable-gpl --enable-version3 --enable-nonfree --enable-postproc --enable-libfaac --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libtheora --enable-libvorbis --enable-libxvid --enable-x11grab --enable-swscale --enable-shared

6

make

7	sudo make install

The next step is to get the OpenCV 2.2 code:

1

cd ~

2	wgethttp://downloads.sourceforge.net/project/opencvlibrary/opencv-unix/2.2/OpenCV-2.2.0.tar.bz2

3	tar -xvf OpenCV-2.2.0.tar.bz2

4	cd OpenCV-2.2.0/

Now we have to generate the Makefile by using cmake. In here we can define which parts of OpenCV we want to compile. Since we want to use Python and TBB with OpenCV, here is where we set that. Just execute the following line at the console to create the appropriate Makefile. Note that there is a dot at the end of the line, it is an argument for the cmake program and it means current directory.

1	cmake -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=OFF -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON .

Check that the above command produces no error and that in particular it reports FFMPEG as 1. If this is not the case you will not be able to read or write videos. Also, check that Python reports ON and Python numpy reports YES. Also, check that under Use TBB it says YES. If anything is wrong, go back, correct the errors by maybe installing extra packages and then run cmake again. You should see something similar to this:

Now, you are ready to compile and install OpenCV 2.2:

1

make

2	sudo make install

Now you have to configure OpenCV. First, open the opencv.conf file with the following code:

1	sudo gedit /etc/ld.so.conf.d/opencv.conf

Add the following line at the end of the file(it may be an empty file, that is ok) and then save it:

1	/usr/local/lib

Run the following code to configure the library:

1	sudo ldconfig

Now you have to open another file:

1	sudo gedit /etc/bash.bashrc

Add these two lines at the end of the file and save it:

1	PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig

2	export PKG_CONFIG_PATH

Finally, close the console and open a new one, restart the computer or logout and then login again. OpenCV will not work correctly until you do this.

There is a final step to configure Python with OpenCV. You need to copy the file cv.so into the correct place. You can do that by just executing the following command:

1	sudo cp /usr/local/lib/python2.7/site-packages/cv.so /usr/local/lib/python2.7/dist-packages/cv.so

Now you have OpenCV 2.2 installed in your computer with Python and TBB support.

Let’s check some demos included in OpenCV.
First, let’s see some C demos:

1	cd ~/OpenCV-2.2.0/samples/c

2	chmod +x build_all.sh

3	./build_all.sh

Some of the training data for object detection is stored in /usr/local/share/opencv/haarcascades. You need to tell OpenCV which training data to use. I will use one of the frontal face detectors available. Let’s find a face:

1	./facedetect --cascade="/usr/local/share/opencv/haarcascades/haarcascade_frontalface_alt.xml"--scale=1.5 lena.jpg

Note the scale parameter. It allows you to increase or decrease the size of the smallest object found in the image (faces in this case). Smaller numbers allows OpenCV to find smaller faces, which may lead to increasing the number of false detections. Also, the computation time needed gets larger when searching for smaller objects.

You can also detect smaller objects that are inside larger ones. For example you can search for eyes inside any detected face. You can do that with the nested-cascade parameter:

1	./facedetect --cascade="/usr/local/share/opencv/haarcascades/haarcascade_frontalface_alt.xml" --nested-cascade="/usr/local/share/opencv/haarcascades/haarcascade_eye.xml" --scale=1.5 lena.jpg

Feel free to experiment with other features like mouth or nose for example using the corresponding cascades provided in the haarcascades directory.

Now let’s check some C++ demos:

1	cd ~/OpenCV-2.2.0/samples/cpp

2

make

Now all the C++ demos are built in ~/OpenCV-2.2.0/bin. Let’s see a couple of them. For example, a simulated chessboard calibration:

1	~/OpenCV-2.2.0/bin/calibration_artificial

In OpenCV 2.2, the grabcut algorithm is provided as a C++ sample. This is a very nice segmentation algorithm that needs very little user input to segment the objects in the image. For using the demo, you need to select a rectangle of the area you want to segment. Then, hold the Control key and left click to select the background (in Blue). After that, hold the Shift key and left click to select the foreground (in Red). Then press the n key to generate the segmentation. You can press n again to continue to the next iteration of the algorithm.

1	~/OpenCV-2.2.0/bin/grabcut ~/OpenCV-2.2.0/samples/cpp/lena.jpg

This image shows the initial rectangle for defining the object that I want to segment.

Now I roughly set the foreground (red) and background (blue).

When you are ready, press the n key to run the grabcut algorithm. This image shows the result of the first iteration of the algorithm.

Now let’s see some background subtraction from a video. The original video shows a hand moving in front of some trees. OpenCV allows you to separate the foreground (hand) from the background (trees).

1	~/OpenCV-2.2.0/bin/bgfg_segm ~/OpenCV-2.2.0/samples/c/tree.avi

And finally, let’s see Python working with OpenCV:

1	cd ~/OpenCV-2.2.0/samples/python/

Let’s run the kmeans.py example. This script starts with randomly generated 2D points and then uses a clustering method called k-means. Each cluster is presented in a different color.

1	python kmeans.py

Now let’s see the convexhull.py demo. This algorithm basically calculates the smallest convex polygon that encompasses the data points.

1	python convexhull.py

Python scripts can also be executed directly like the following example. This script reads a video file (../c/tree.avi) within pyhton and shows the first frame on screen:

1	./minidemo.py

Have fun with OpenCV in C, C++ or Python…

Ubuntu VPS的中文和中文乱码问题解决

我们的Ubuntu vps缺省是英文环境，如果要想在Ubuntu VPS下面能显示，输入中文，必须要做一番设置。

方法一：

首先，如果用putty进行SSH登录到Ubuntu VPS上，要先保证putty支持中文，请参考：putty的常见配置

重要的还是Ubuntu VPS的中文配置：

创建文件/var/lib/locales/supported.d/zh，内容为：

zh_CN.UTF-8 UTF-8
zh_CN.GBK GBK

运行locale-gen产生中文的locale，然后修改文件/etc/environment其中的LANG部分为：

LANG="zh_CN.UTF-8"

然后重启VPS，重启后就可以正常显示和输入中文了

方法二：

redhat下mysql集群的安装与配置

我是在虚拟机上测试的，三台机子分别为：

192.168.2.100，管理节点。

192.168.2.101，数据节点和SQL节点。

192.168.2.102，数据节点和SQL节点。

装的系统是：Red Hat Enterprise Linux 4。

软件包是：mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz。

安装步骤

1.管理节点的安装
#groupadd mysql
#useradd mysql -g mysql
#mv mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz /usr/local/
#cd /usr/local/
#tar zxvf mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz
#rm -f mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz
#mv mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23 mysql
#chown -R mysql:mysql mysql
#cd mysql
#scripts/mysql_install_db --user=mysql

2.管理节点的配置
#mkdir /var/lib/mysql-cluster
#cd /var/lib/mysql-cluster
#vi config.ini                //这里需要手动添加如下内容
[ndbd default]
NoOfReplicas=2
DataMemory=80M
IndexMemory=18M
[ndb_mgmd]
Id=1
Hostname=192.168.2.100
datadir=/usr/local/mysql/logs
[ndbd]
Id=2
Hostname=192.168.2.101
datadir=/usr/local/mysql/data/

[ndbd]
Id=3
Hostname=192.168.2.102
datadir=/usr/local/mysql/data/
[MYSQLD]
[MYSQLD]

3.安装和配置数据节点

这里2台机器数据节点安装是相同的.

#groupadd mysql
#useradd mysql -g mysql
#mv mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz /usr/local/
#cd /usr/local/
#tar zxvf mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz
#rm -f mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23.tar.gz
#mv mysql-cluster-gpl-7.1.2a-beta-linux-i686-glibc23 mysql
#chown -R mysql:mysql mysql
#cd mysql
#scripts/mysql_install_db --user=mysql
#cp support-files/my-medium.cnf /etc/my.cnf
#cp support-files/mysql.server /etc/init.d/mysqld
#vi /etc/my.cnf         //这里需要手动添加如下的内容
 [mysqld]
datadir=/usr/local/mysql/data/       //这里要与管理节点的 config.ini相同
ndbcluster
ndb-connectstring=192.168.2.100
[ndbd]
connect-string=192.168.2.100
[mysql_cluster]
ndb-connectstring=192.168.2.100
[ndb_mgm]
connect-string=192.168.2.100
[ndb_mgmd]
config-file=/var/lib/mysql-cluster/config.ini  //这里要指定管理节点配置文件路径

 
4.启动相关服务

在管理节点启动相关服务:
#/usr/local/mysql/bin/ndb_mgmd -f /var/lib/mysql-cluster/config.ini
#netstat -lntpu
tcp        0      0 0.0.0.0:1186                0.0.0.0:*                   LISTEN      7797/ndb_mgmd

看到1186端口开放了说明启动是正常的.

在数据节点启动相关服务:
#/usr/local/mysql/bin/ndbd --initial
#netstat -lntpu
tcp        0      0 192.168.2.101:32772         0.0.0.0:*                   LISTEN      3392/ndbd
tcp        0      0 192.168.2.101:32773         0.0.0.0:*                   LISTEN      3392/ndbd
tcp        0      0 192.168.2.101:32774         0.0.0.0:*                   LISTEN      3392/ndbd

#service mysqld start
#netstat -lntpu
tcp        0      0 :::3306                     :::*                        LISTEN      3557/mysqld

可以看到相关的ndbd服务以及mysql已经启动ok了.

RedHat RHEL 6.1安装gcc的方法

RHEL 6.1默认是没有gcc和gcc-c++环境的，而且我也没有$购买正版服务。

只能想办法本地安装了，总结方法如下：

上传安装镜像rhel-server-6.1-x86_64-dvd.iso，

然后将镜像文件挂，如/mnt

# mount -o loop rhel-server-6.1-x86_64-dvd.iso /mnt

# cd /mnt/Packages

# rpm -ivh glibc-common-2.12-1.25.el6.x86_64.rpm

# rpm -ivh kernel-headers-2.6.32-131.0.15.el6.x86_64.rpm

# rpm -ivh libgcc-4.4.5-6.el6.x86_64.rpm

# rpm -ivh glibc-2.12-1.25.el6.x86_64.rpm

# rpm -ivh libgomp-4.4.5-6.el6.x86_64.rpm

# rpm -ivh nscd-2.12-1.25.el6.x86_64.rpm

# rpm -ivh glibc-headers-2.12-1.25.el6.x86_64.rpm

# rpm -ivh glibc-devel-2.12-1.25.el6.x86_64.rpm

# rpm -ivh mpfr-2.4.1-6.el6.x86_64.rpm

# rpm -ivh ppl-0.10.2-11.el6.x86_64.rpm

# rpm -ivh cloog-ppl-0.15.7-1.2.el6.x86_64.rpm

# rpm -ivh cpp-4.4.5-6.el6.x86_64.rpm

# rpm -ivh gcc-4.4.5-6.el6.x86_64.rpm

注：以上是安装gcc，软件安装顺序不能错。
******************************************
# rpm -ivh libstdc++-4.4.5-6.el6.x86_64.rpm

# rpm -ivh libstdc++-devel-4.4.5-6.el6.x86_64.rpm

# rpm -ivh gcc-c++-4.4.5-6.el6.x86_64.rpm

注：以上是安装gcc-c++

redhat 网络设置

用[]表示用户自己填写

Ip配置：

临时-shell:ifconfig  eth0  [ipaddr]  netmask [netmaskn]

---------------------------------------------------------------------------

永久-配置文件：  /etc/sysconfig/network-scripts/ifcfg-eth0

动态ip:

DEVICE=eth0

ONBOOT=yes

BOOTPROTO=dhcp

HWADDR=[mac]

静态ip:

DEVICE=eth0

ONBOOT=yes

BOOTPROTO=static

IPADDR=[一个合适你的ip]

NETMASK=[根据你的ip填写]

注意：如果你的配置文件改了，需要重启响应的硬件，这里的话，是网卡，service network restart

--------------------------------------------------------------------------------------------------------------------------------------

网关：/etc/sysconfig/network

NETWORKING=yes                 /*IPv4*/

NETWORKING_IPV6=no

HOSTNAME=[你的主机名]

GATEWAY=[你的网关]                      /*静态ip的时候一定要设置这里才可以访问外网的哦~*/

--------------------------------------------------------------------------------------------------------------------------------------

Dns: /etc/resolv.conf

Nameserver [你的域名服务器，比如218.30.19.40]

--------------------------------------------------------------------------------------------------------------------------------------

检测你的本机网络

Ping

1、    与网关：ping [your gateway]

2、    与外网交互，比如下载一个东西：

wget http://www.qq.com/

--------------------------------------------------------------------------------------------------------------------------------------

一个机子绑定多个ip

Shell下:

ifconfig eth0:0  [ipaddr] netmask [子网掩码] up

ifconfig eth0:1  [ipaddr] netmask [子网掩码] up

去掉一个：

ifconfig eth0:1 down

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route:

查看路由信息： route –n

设置默认网关： route add default gw [ipaddr]

添加一个静态路由：route add –net [netaddr] netmask [掩码] gw [ipaddr]  [eth0]

/*netaddr 为上图destination*/

删除一个静态路由：route del –net [netaddr] netmask [掩码] gw [ipaddr] [eth0]