Based on computer vision algorithms, this software enables to synchronize slides with the corresponding video recording.
Note
slideotracker = slides + video + tracking
- Author : Sebastien Campion / INRIA Texmex Team / http://www.irisa.fr/texmex
GNU AFFERO GENERAL PUBLIC LICENSE v3
make deb
make pydist
https://github.com/scampion/slideotracker
Usage: slideotracker.py [options]
Options: -h, --help show this help message and exit -i index, --index=index
index file is a simple text file, the first line in the video path, others lines are paths on slide images (use ImageMagick, to convert pdf in several images)
-p PRECISION, --precision=PRECISION precision in number of frame (default 25) -o OUTFILE, --out=OUTFILE output file name, by default results.js -f FORMAT, --format=FORMAT output file format js (default),csv -d, --debug debug trace
Usage: slideotracker.py [options]
Options: -h, --help show this help message and exit -i index, --index=index
index file is a simple text file, the first line in the video path, others lines are paths on slide images (use ImageMagick, to convert pdf in several images)
-p PRECISION, --precision=PRECISION precision in number of frame (default 25) -o OUTFILE, --out=OUTFILE output file name, by default results.js -f FORMAT, --format=FORMAT output file format js (default),csv -d, --debug debug trace
- Download and extract :
- http://slideotracker.gforge.inria.fr/demo/demo.tar.gz
Run
slideo -i tests/data/test.txt
#extract pdf pages to jpeg using ImageMagick
mkdir /tmp/mypdf/
convert <your.pdf> /tmp/mypdf/slide.jpg
#build a index file
echo './path/to/my/video.ogv' > /tmp/index
ls -1 /tmp/mypdf/slide* >>/tmp/index
#Run the tracker
python slideotracker.py -i /tmp/index -o results.txt
- try also :
- python slideotracker.py -i tests/data/short_test.txt
Results in Javascript format :
slides=[0, 1, 2];
frames=[500, 850, 950];
Results in CSV format :
#slide_number;star_frame;end_frame
0;0;500
1;500;850
2;850;950
... .. .
Open the following file with your browser
/usr/share/slideo/html/player.html?mediafile=data/video.ogv&slidedir=data/slides&fps=25
- scikit-learn
- OpenCV 2.1
- geometric robustification ... in progress
- optimize time computing
- documentation / How it works
- Images used for the logo : Dropline Nuovo! from http://art.gnome.org/themes/icon
- RMLL 2010 video for the data test