[OpenCV] To install OpenCV on Debian and create a test project using Netbeans

This document is the steps to install OpenCV on Debian and create a test project using Netbeans for my reference in case.

#Prepare the build environment GCC、Cmake、pkgconfig

$sudo apt-get -y install build-essential cmake pkg-config

#Install ImageI/O libraries

$sudo apt-get -y install libjpeg62-dev libtiff4-dev libjasper-dev

#Install Viode I/O libraries

$sudo apt-get -y install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
$sudo apt-get -y install libdc1394-22-dev libxine2-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev

#Install GTK+2.x and QT libraries

$sudo apt-get -y install  libgtk2.0-dev libqt4-dev

[Hadoop] Setting up a Single Node Cluster

Basically these resource links are good enough to do a single node cluster of Hadoop MapReduce. But I still want to add some comments for my reference.
http://www.thebigdata.cn/Hadoop/15184.html
http://www.powerxing.com/install-hadoop/

Login the user "hadoop"

# sudo su - hadoop

Go to the location of Hadoop

# /usr/local/hadoop

Add the variables in ~/.bashrc

export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64
export HADOOP_HOME=/usr/local/hadoop
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export HADOOP_INSTALL=/usr/local/hadoop
export PATH=$PATH:$HADOOP_INSTALL/bin
export PATH=$PATH:$HADOOP_INSTALL/sbin
export HADOOP_MAPRED_HOME=$HADOOP_INSTALL
export HADOOP_COMMON_HOME=$HADOOP_INSTALL
export HADOOP_HDFS_HOME=$HADOOP_INSTALL
export YARN_HOME=$HADOOP_INSTALL

Modify $JAVA_HOME in etc/hadoop/hadoop-env.sh

export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64

Start dfs and yarn

# sbin/start-dfs.sh

# sbin/start-yarn.sh

Finally, we can try the Hadoop MapReduce example as follows:

# bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.0.jar grep input output 'dfs[a-z.]+'

P.S:
In order to forcefully let the namenode leave safemode, following command should be executed:

# hdfs dfsadmin -safemode leave

[Tensorflow] Fizz-Buzz example enhancement

I am just based on this Fizz-Buzz example as below to add 2nd convolution layer and guess what? The result is quicker to be learn. But, this is just the first step to learn "Deep Learning"...
There is still a lot of things and knowledge that need to learn more.
http://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/

Before



After


Reference
http://www.slideshare.net/WrangleConf/wrangle-2016-lightning-talk-fizzbuzz-in-tensorflow