| #!/bin/sh | |
| # Based on gist.github.com/gboudreau/install-ffmpeg-amazon-linux.sh | |
| # and https://trac.ffmpeg.org/wiki/CompilationGuide/Centos | |
| if [ "`/usr/bin/whoami`" != "root" ]; then | |
| echo "You need to execute this script as root." | |
| exit 1 | |
| fi | |
| cat > /etc/yum.repos.d/centos.repo<<EOF |
The OpenCV library implements tons of useful image processing and computer vision algorithms, as well as the high-level GUI API. Written in C++, it has bindings in Python, Java, MATLAB/Octave, C#, Perl and Ruby. We present the Lua bindings that are based on Torch, made by VisionLabs with support from Facebook and Google Deepmind.
By combining OpenCV with scientific computation abilities of Torch, one gets an even more powerful framework capable of handling computer vision routines (e.g. face detection), interfacing video streams (including cameras), easier data visualization, GUI interaction and many more. In addition, most of the computationally intensive algorithms are available on GPU via Cutorch. All these features may be essentially useful for those dealing with deep learning applied to images.
| # Backup | |
| docker exec CONTAINER /usr/bin/mysqldump -u root --password=root DATABASE > backup.sql | |
| # Restore | |
| cat backup.sql | docker exec -i CONTAINER /usr/bin/mysql -u root --password=root DATABASE | |
| Because I couldn't find these with a quick Google search on 28 April 2015: | |
| Usage: | |
| rails new APP_PATH [options] | |
| Options: | |
| -r, [--ruby=PATH] # Path to the Ruby binary of your choice | |
| # Default: /home/brian/.rvm/rubies/ruby-2.2.0/bin/ruby | |
| -m, [--template=TEMPLATE] # Path to some application template (can be a filesystem path or URL) | |
| [--skip-gemfile], [--no-skip-gemfile] # Don't create a Gemfile |
| // Run this from the commandline: | |
| // phantomjs runner.js | ffmpeg -y -c:v png -f image2pipe -r 24 -t 10 -i - -c:v libx264 -pix_fmt yuv420p -movflags +faststart output.mp4 | |
| var page = require('webpage').create(), | |
| address = 'http://s.codepen.io/phanan/fullembedgrid/YPLewm?type=embed&safe=true&_t=1424767252279', | |
| duration = 3, // duration of the video, in seconds | |
| framerate = 24, // number of frames per second. 24 is a good value. | |
| counter = 0, | |
| width = 500, | |
| height = 500; |
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
The following document is a written account of the Code School screencasting framework. It should be used as a reference of the accompanying screencast on the topic.
You're probably aren't going to take the time to read this document if you're not interested, but there are a lot of nice side effects caused by learning how to create quality screencasts.
- Communicating more effectively - At Envy Labs we produce screencasts for our clients all the time. Whether it's demoing a new feature or for a presentation for an invester, they're often much more effective and pleasent than a phone call or screen sharing.