Skip to content

Instantly share code, notes, and snippets.

View AlexR1712's full-sized avatar
🏠
Working from home

Alexander J. Rodriguez D. AlexR1712

🏠
Working from home
View GitHub Profile
@onyxfish
onyxfish / example1.py
Created March 5, 2010 16:51
Basic example of using NLTK for name entity extraction.
import nltk
with open('sample.txt', 'r') as f:
sample = f.read()
sentences = nltk.sent_tokenize(sample)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)
@alkavan
alkavan / gource-commands.txt
Created April 11, 2010 16:41
Gource and ffmpeg Commands
################################
gource commands
################################
# basic command for big and long projects
gource --max-user-speed 500 --seconds-per-day 0.05 --file-idle-time 10 -e 0.005 -f --max-files 300 --hide-files
# some easy to understand commands
# for output file
--output-ppm-stream ~/ppm/ppm-kohana
@rafi
rafi / gource-commands.txt
Created April 14, 2010 15:26 — forked from alkavan/gource-commands.txt
Gource command
################################
gource commands
################################
# basic command for big and long projects
gource --max-user-speed 500 --seconds-per-day 0.05 --file-idle-time 10 -e 0.005 -f --max-files 300 --hide-files
# some easy to understand commands
# for output file
--output-ppm-stream ~/ppm/ppm-kohana
@vxnick
vxnick / gist:380904
Created April 27, 2010 15:52
Array of country codes (ISO 3166-1 alpha-2) and corresponding names
<?php
$countries = array
(
'AF' => 'Afghanistan',
'AX' => 'Aland Islands',
'AL' => 'Albania',
'DZ' => 'Algeria',
'AS' => 'American Samoa',
'AD' => 'Andorra',
@isaacs
isaacs / node-and-npm-in-30-seconds.sh
Last active November 2, 2024 12:56
Use one of these techniques to install node and npm without having to sudo. Discussed in more detail at http://joyeur.com/2010/12/10/installing-node-and-npm/ Note: npm >=0.3 is *safer* when using sudo.
echo 'export PATH=$HOME/local/bin:$PATH' >> ~/.bashrc
. ~/.bashrc
mkdir ~/local
mkdir ~/node-latest-install
cd ~/node-latest-install
curl http://nodejs.org/dist/node-latest.tar.gz | tar xz --strip-components=1
./configure --prefix=~/local
make install # ok, fine, this step probably takes more than 30 seconds...
curl https://www.npmjs.org/install.sh | sh
@mrkmg
mrkmg / genColorCodeFromText.php
Created January 13, 2012 17:22
Generate a unique color based on text input
<?php
/*
* Outputs a color (#000000) based Text input
*
* @param $text String of text
* @param $min_brightness Integer between 0 and 100
* @param $spec Integer between 2-10, determines how unique each color will be
*/
function genColorCodeFromText($text,$min_brightness=100,$spec=10)
@oodavid
oodavid / README.md
Last active October 11, 2024 00:36 — forked from aronwoost/README.md
Deploy your site with git

Deploy your site with git

This gist assumes:

  • you have a local git repo
  • with an online remote repository (github / bitbucket etc)
  • and a cloud server (Rackspace cloud / Amazon EC2 etc)
    • your (PHP) scripts are served from /var/www/html/
    • your webpages are executed by apache
  • apache's home directory is /var/www/
@blongden
blongden / benchmark.php
Created April 10, 2012 16:22
Benchmark a PHP function
<?php
$calibration = benchmark(function() { });
$benchmark = benchmark(function() {
sleep(1);
});
echo "Calibration run: ".number_format($calibration)."/sec\n";
echo "Benchmark run: ".number_format($benchmark)."/sec\n";
echo 'Approximate code execution time (seconds): '.number_format((1/$benchmark) - (1/$calibration), 10);
<?php
echo file_get_contents('http://tinyurl.com/api-create.php?url='.'http://www.example.com/');
/* For example
http://tinyurl.com/api-create.php?url=http://www.fullondesign.co.uk/
Would return:
http://tinyurl.com/d4px9f
*/
?>
@npinto
npinto / cv2_detect.py
Created September 5, 2012 07:13
Simple face detection with OpenCV 'cv2' python bindings from 2.4.x
import cv2
import cv2.cv as cv
def detect(img, cascade_fn='haarcascades/haarcascade_frontalface_alt.xml',
scaleFactor=1.3, minNeighbors=4, minSize=(20, 20),
flags=cv.CV_HAAR_SCALE_IMAGE):
cascade = cv2.CascadeClassifier(cascade_fn)
rects = cascade.detectMultiScale(img, scaleFactor=scaleFactor,