anujonthemove

namespace cv {
    // calculates the median value of a single channel
    // based on https://github.com/arnaudgelas/OpenCVExamples/blob/master/cvMat/Statistics/Median/Median.cpp
    double median( cv::Mat channel )
    {
        double m = (channel.rows*channel.cols) / 2;
        int bin = 0;
        double med = -1.0;

        int histSize = 256;

anujonthemove

// OpenCV imports
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

// C++ imports
#include <iostream>

// namespaces
using namespace std;
using namespace cv;

anujonthemove

anujonthemove

// takes the form field value and returns true on valid number
function valid_credit_card(value) {
  // accept only digits, dashes or spaces
	if (/[^0-9-\s]+/.test(value)) return false;

	// The Luhn Algorithm. It's so pretty.
	var nCheck = 0, nDigit = 0, bEven = false;
	value = value.replace(/\D/g, "");

	for (var n = value.length - 1; n >= 0; n--) {

anujonthemove

CAP_PROP_POS_MSEC       =0, //!< Current position of the video file in milliseconds.
CAP_PROP_POS_FRAMES     =1, //!< 0-based index of the frame to be decoded/captured next.
CAP_PROP_POS_AVI_RATIO  =2, //!< Relative position of the video file: 0=start of the film, 1=end of the film.
CAP_PROP_FRAME_WIDTH    =3, //!< Width of the frames in the video stream.
CAP_PROP_FRAME_HEIGHT   =4, //!< Height of the frames in the video stream.
CAP_PROP_FPS            =5, //!< Frame rate.
CAP_PROP_FOURCC         =6, //!< 4-character code of codec. see VideoWriter::fourcc .
CAP_PROP_FRAME_COUNT    =7, //!< Number of frames in the video file.
CAP_PROP_FORMAT         =8, //!< Format of the %Mat objects returned by VideoCapture::retrieve().
CAP_PROP_MODE           =9, //!< Backend-specific value indicating the current capture mode.

anujonthemove

import tensorflow as tf

x = tf.Variable(2, name='x', dtype=tf.float32)
log_x = tf.log(x)
log_x_squared = tf.square(log_x)

optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(log_x_squared)

init = tf.initialize_all_variables()

anujonthemove

# Commands to install virtual environments
# With this setup, all your virtual environments will be placed
# at one place inside .virtualenvs folder under home directory in Linux

sudo apt update
sudo pip install virtualenv virtualenvwrapper

# open .bashrc file and copy paste the following lines below:

# virtualenv and virtualenvwrapper

anujonthemove

export CUDA_HOME=/usr/local/cuda
export PATH=/usr/local/cuda/bin:$PATH
export CPATH=/usr/local/cuda/include:$CPATH
export LIBRARY_PATH=/usr/local/cuda/lib64:$LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH

anujonthemove

# add jupyter kernel
# if you are working inside a virtual environment, activate it and run the following command (change the names accordingly, of course!)
python -m ipykernel install --user --name video-analytics --display-name "Python2 (video-analytics)"

# list all available kernels
jupyter kernelspec list

# remove a kernel
jupyter kernelspec remove "kernel-name" (without quotes)

anujonthemove

# taken entirely from: https://dzone.com/articles/password-less-ssh-access-for-automation
## Proxy ##
## Forward all local port 8888 traffic to port 8888 on the remote server ## 
Host <your host name>
    HostName <your IP>
    ForwardX11 yes
    User <your username>
	IdentityFile /path/to/<your pem file>.pem
	LocalForward localhost <or some of your IP>:8888 <server IP address>:8888