anubhavsinha

sudo yum update
sudo yum install -y tar wget
# Install Mesos dependencies
sudo wget http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo -O /etc/yum.repos.d/epel-apache-maven.repo
#sudo vi /etc/yum.repos.d/wandisco-svn.repo and add the following content
#[WANdiscoSVN]
#name=WANdisco SVN Repo 1.9
#enabled=1
#baseurl=http://opensource.wandisco.com/centos/7/svn-1.9/RPMS/$basearch/
#gpgcheck=1

anubhavsinha

aws logs put-log-events --log-group-name anubhav-PoC --log-stream-name anubhav-PoC --log-events "[{\"timestamp\":`date +%s%3N`, \"message\": \"Simple ElasticSearch Test\"}]"

anubhavsinha

# following Python packages needs to be installed 
# xlrd, xlsxrd, unidecode, MySQLdb

import xlrd
import xlsxrd
import MySQLdb as mdb
import re
import unidecode

anubhavsinha

# Running first a gaussian blur (kernel size = 3) 
# and then Canny edge detection (low/high = 1:2 or 1:3) 
# is a handy way to get the boundaries
from matplotlib import image
from matplotlib import pyplot
import numpy
import cv2

view_from_windshield = image.imread('test.jpg')
working_copy = numpy.copy(view_from_windshield)

anubhavsinha

yum groupinstall "Development Tools"
yum install kernel-devel kernel-headers dkms
yum install pciutils
lspci -nn | grep VGA # to check your NVIDIA product version
yum update
sudo sh NVIDIA-Linux-x86_64-340.32.run --kernel-source-path /usr/src/kernels/3.10.0-123.6.3.el7.x86_64

anubhavsinha

# Installing NVIDIA Official Driver
yum groupinstall "Development Tools"
yum install kernel-devel kernel-headers dkms
yum install pciutils
lspci -nn | grep VGA # to check your NVIDIA product version
yum update # For kernel source etc
sudo sh NVIDIA-Linux-x86_64-340.32.run --kernel-source-path /usr/src/kernels/3.10.0-123.6.3.el7.x86_64
# NVIDIA Driver got installed successfully!

# Installing NICE DCV

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# Region masking is a technique used to run a image processing or computer vision task within a specific region of interest
# Step 1. Build a selector for the region
# Step 2. Build a selector for the pixels of interest
# Step 3. AND the two selectors. It's that simple.

from matplotlib import image
from matplotlib import pyplot
import numpy

view_from_windshield = image.imread('test.jpg')

anubhavsinha

# Color selection
# Step1. Read the image
# Step2. Set the threshold (In our case it is to filter out everything except white)
# Step3. Build a selector and 
# Steo4. Apply the selector
# Picking the right color model is very important for a successful computer vision task.
# LUV, HSV, RGB, L*a*b etc.
# To be able to read the image file we will use the image package from matplotlib
from matplotlib import image
# To be able to render or plot the image we will use the pyplot package from matplotlib

anubhavsinha

# cleans all images
docker images | awk '{print $3}' | xargs docker rmi 

# cleans all stopped containers
docker rm $(docker ps -q -f status=exited)

anubhavsinha

du -sh */