[Haar Classifier] Train your own OpenCV Haar classifier

I just keep a record for myself because there are a lot of documents teaching how to train your haar classifier and almost of them seem to don't work well. The following 2 items are clear and easy to understand.

The Data Image Source (cars) I use.

1. Train your own OpenCV Haar classifier

find ./positive_images -iname "*.pgm" > positives.txt
find ./negative_images -iname "*.pgm" > negatives.txt

perl bin/ positives.txt negatives.txt samples 550\
  "opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1\
  -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 48 -h 24"

python ./tools/ -v samples/ -o samples.vec

opencv_traincascade -data classifier -vec samples.vec -bg negatives.txt\
  -numStages 10 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 1000\
  -numNeg 600 -w 48 -h 24 -mode ALL -precalcValBufSize 1024\

[Image] How to resize, convert & modify images from the Linux

$ sudo apt-get install imagemagick

Converting Between Formats
$ convert howtogeek.png howtogeek.jpg

You can also specify a compression level for JPEG images:
$ convert howtogeek.png -quality 95 howtogeek.jpg

Resizing Images
$ convert example.png -resize 200×100 example.png
  - to force the image to become a specific size – even if it messes up the aspect ratio
$ convert example.png -resize 200×100! example.png

$ convert example.png -resize 200 example.png
$ convert example.png -resize x100 example.png

Rotating an Image
convert howtogeek.jpg -rotate 90 howtogeek-rotated.jpg

Applying Effects
ImageMagick can apply a variety of effects to an image.
  - For example,   the following command applies the “charcoal” effect to an image:
$ convert howtogeek.jpg -charcoal 2 howtogeek-charcoal.jpg
  - the “Implode” effect with a strength of 1:
# convert howtogeek.jpg -implode 1 howtogeek-imploded.jpg

Batch Processing
for file in *.png; do convert $file -rotate 90 rotated-$file; done


[TensorFlow] My case to install TensorFlow with GPU enabled

My Operation System is Ubuntu 14.04 LTS 5 and GPU card is GeForce GTX 750Ti

1. Go to and download the driver ( 2. For Nvidia to find linux header files (*):
$ sudo apt-get install build-essential linux-headers-$(uname -r)

3. To enable full screen text mode (nomodeset):
$ sudo gedit /etc/default/grub
>> Edit GRUB_CMDLINE_LINUX_DEFAULT="quiet splash nomodeset"
Save it and reboot
$ sudo update-grub
$ sudo reboot

4. Log into with Ctl +Alt + F1

5. Stop the X Server service
$ sudo service lightdm stop

6. Install nVidia driver
$ sudo ./
7. Install CUDA (GPUs on Linux) Download and install Cuda Toolkit sudo dpkg -i cuda-repo-ubuntu1404-8-0-local_8.0.44-1_amd64.deb sudo apt-get update sudo apt-get install cuda
8. Download and install cuDNN tar xvzf cudnn-8.0-linux-x64-v5.1.tgz cd cuda
sudo cp include/cudnn.h /usr/local/cuda-8.0/includ…

[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
#(Optional)Install support for Firewire video cameras
$sudo apt-get -y install libdc1394-22-dev
#(Optional)Install video streaming libraries
$sudo apt-get -y install libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev
#(Optional)Install the Python development environment and the Python Numerical libraries
$sudo apt-get -y install python-dev python-numpy

[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.

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/
export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64
Start dfs and yarn
# sbin/ sbin/
Finally, we can try the Hadoop MapReduce example as follows:
# bin/hadoop…

[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.




[Neutron] The first glance of L3HA mode in OpenStack Neutron ( Liberty version )

I just quickly take the first glance of L3HA mode in OpenStack Neutron ( Liberty version ) and is based on my tenant environment as follows:
My tenant environment # neutron router-list

# neutron net-list
# neutron subnet-list
The Topology view looks like this:

Here I have 2 instances in my tenant:

So, if I use the instance: daanny_vm1 to ping danny_vm2, due to the different subnets, this action will trigger L3 vrouter function.

# ping ( danny_vm2 )

# ip netns exec qrouter-f1e03fef-cccf-43de-9d35-56d11d636765 tcpdump -eln -i qr-4433f31f-5d icmp

The interface qr-4433f31f-5d is my subnet's gateway port as follows:
# neutron --os-tenant-name danny port-list | grep 4433f31f-5d | 4433f31f-5d93-4fe4-868a-04ddcc38be20 | | fa:16:3e:25:22:b3 | {"subnet_id": "d169f180-4304-42f0-b11f-e094287bcd00", "ip_address": ""} | Keepalived related L3HA mode is havily relied on…