GSOC 2015 project for Red Hen Labs. More details here http://vasanthkalingeri.github.io/CommercialDetection/

##Instructions to run

*Run dependencies.sh script

*Create a database in Mysql to store fingerprints

*Open src/constants.py, edit the line

CONFIG = {
  "database": {
      "host": "127.0.0.1",
      "user": <username>,
      "passwd": <password>,
      "db": <name of the database created>
  }
}

###To teach new commercials

*Create a file like data/labels for the given video

python src/main.py -g data/video.mpg data/labels

*The above creates a directory called db containing the commercials labelled. The system also learns from these commercials

###To detect commercials

python src/main.py -r data/test.mpg

*This will create a file called output.txt containing the detected commercials.

*It will have unclassified sections which can later be seen and edited. The edited file can be used as labels file for learning new commercials.

*Edit content in output.txt after watching the video manually.

*Now using output.txt as labels for test.mpg, run the program again to update the db with new commercials.

python src/main.py -g data/test.mpg output.txt

##Results The program was tested on Ubuntu 14.04 64 bit LTS. With the following versions of libraries

*Opencv cv = 2.4.8

*Numpy = 1.8.2

*Scipy = 0.13.3

*ffmpeg = 2.6.2