Dewarp
Download the dewarp code here: https://bitbucket.org/mkraemer/decapod-dewarping
Installation Notes
DECAPOD STEREO DEWARPING ======================== required ------------------ - numpy - scipy - python-matplotlib - git (to download pyflann from source) - opencv - pyflann
git
- Required for downloading pyflann from source.
numpy
- Note numpy should be installed prior to pyVLFeat
- Install
sudo apt-get install python-numpy
- Version assuming v1.6.2?
scipy
- Install
sudo apt-get install python-scipy
- Version assuming 0.11.0rc2?
python-setuptools
- Note Python Setuptools is required to install pyflann from source.
- Install
sudo apt-get install python-setuptools
- Version ?
opencv
- follow the instructions here: http://www.samontab.com/web/2012/06/installing-opencv-2-4-1-ubuntu-12-04-lts/
- don't have to continue after make install
pyflann
- URL http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
- Install https://github.com/mariusmuja/flann/issues/15
- License BSD (see source code for license info)
- Note: Install according to link above. Copy
pyflann
directory fromusr/local/lib/python2.7/dist-packages/
to~/decapod-dewarping/
vlfeat
- URL http://www.vlfeat.org/index.html
- download binary or compile from source
- see http://www.vlfeat.org/install-shell.html for locations of files
- copy "sift" to "/usr/local/bin
- copy "libvl.so" to "/usr/local/lib
- run ldconfig
example usage - calibration
---------------------------
./calibrate.py calibration-images 9 6 calibration-data
This uses the chessboard images in directory calibration-images. Each
chessboard has 9x6 inner corners. The resulting camera matrices are
persisted into directory calibration-data.
example usage - dewarping
-------------------------
./dewarp.py calibration-data left.jpg right.jpg dewarped.png
This uses the calibration matrices from directory calibration-data to
perform stereo dewarping of the image pair given by left.jpg and right.jpg.
The dewarped output is then persisted to dewarped.png
Calibration notes
- 6 minutes to run calibration on 2 cores, 2 GB VM.
- 6 minutes to run calibration on 4 cores, 2 GB VM.