Welcome to the new home for the LikeLines player component. The original prototype is still available on the Knight-Mozilla repository.
Conventional online video players do not make the inner structure of the video apparent, making it hard to jump straight to the interesting parts. LikeLines provides users with a navigable heat map of interesting regions for the videos they are watching. The novelty of LikeLines lies in its combination of content analysis and both explicit and implicit user interactions.
The LikeLines system is being developed in the Delft Multimedia Information Retrieval Lab at the Delft University of Technology.
Using LikeLines on your Web page is quite easy. First, the following libraries and files are needed:
- jQuery >= 1.7.2
- likelines.js
- likelines.css
These need to be included in the <head> of your Web page.
For example:
<head>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.7.2/jquery.min.js"></script>
<script src="/js/likelines.js"></script>
<link rel="stylesheet" href="/css/likelines.css">
</head>Just make sure that jQuery is loaded before the LikeLines script is included.
Finally, put a div with an id in your Web page where you want the
LikeLines player to appear and create a new LikeLines.Player object
in JavaScript like in the example below:
<div id="myFirstLikeLinesPlayer"></div>
<script>
player = new LikeLines.Player('myFirstLikeLinesPlayer', {
video: 'http://www.youtube.com/watch?v=wPTilA0XxYE',
backend: 'http://likelines-shinnonoir.dotcloud.com/'
});
</script>The LikeLines.Player constructor requires to arguments:
- A
divor itsidin which the LikeLines player will be embedded. - A configuration object.
The configuration object requires at the minimum a video entry pointing
to the video that needs to be played and a backend entry pointing to an
existing LikeLines server.
Optional configuration parameters include:
widthandheightfor the internal video player.onReadycallback that is called when the LikeLines player is fully loaded.
In case you want to run your own LikeLines backend server, you have two options. You can either install the required software on your own machine or deploy it on the dotCloud application platform.
The LikeLines server requires Python 2.6 or 2.7 to run, which can be obtained from http://www.python.org/download/, and MongoDB for storage.
In addition to Python and MongoDB, the following Python packages are needed:
- Flask
- PyMongo
- Flask-PyMongo
The simplest way of installing these packages is using pip. You can install
pip by first installing easy_install by following the instructions
listed on this page.
You can then execute the following command in a terminal to obtain pip:
$ easy_install pipThe required Python packages can then be installed as follows:
$ pip install Flask
$ pip install PyMongo
$ pip install Flask-PyMongoNote: Windows users should follow PyMongo installation instructions listed here.
This section assumes you have downloaded the full LikeLines source code
via git or through the Github Web interface. Once downloaded and unpacked
to a directory, the following two processes need to be started.
The first process to be started is a MongoDB server on the the default port.
You can start the MongoDB server by simply executing mongod in a terminal:
$ mongodThe second process is the actual LikeLines backend server that will
receive requests to store and aggregate user playback behaviour.
To start this process, go into the server subdirectory and run
the LikeLines.server Python module. The example below shows how
to run the LikeLines server on port 9090.
$ cd likelines_source/server
$ python -m LikeLines.server -p 9090LikeLines supports deploying a server to the dotCloud platform out of the box. Instructions on installing the dotCloud tool and configuring it can be found here.
Once dotCloud has been set up, download the full LikeLines source code
either via git or through the Github Web interface. Then use a terminal
to go into the LikeLines source code directory and enter the following
commands to deploy the LikeLines server to the dotCloud platform:
$ cd likelines_source
$ dotcloud create likelines
$ dotcloud pushRunning the demo requires:
- A HTML5-compatible browser supporting the Canvas element and JavaScript.
- Internet access (for the YouTube API and jQuery library).
- The LikeLines server running on the local machine (see instructions above).
The demo also requires a Web server that will serve examples/demo.html.
Note that you cannot simply open the web page locally (the browser would
simply refuse to execute JavaScript in a local context).
A simple way of hosting the demo example is to use Python's builtin
HTTP server:
$ cd likelines_source
$ python -m SimpleHTTPServer 8080Assuming the LikeLines server is already running on the same machine, the demo can be started by pointing your HTML5-compatible browser to http://localhost:8080/examples/demo.html.
- March 2013: Make LikeLines deployable on at least one cloud platform.
- March 2013: Finalize support for content analysis indexing.
- Future: Add HTML5
- Future: Improve UI.
- Future: Introduce a SMILA component that treats a LikeLines server as a data source for indexing purposes.
