This suite of scripts will find camera matrix and distortion parameters with a set of checkerboard images, then use thos parameters to remove distortion from photos.
You need to install numpy and opencv:
pip install numpy
sudo apt-get install python-opencv exiftool
First you will need to take some photos of a black and white chessboard with a white border, like this one.
Then you will run the opencv_calibrate.py script to generate the matrix and distortion files.
python opencv_calibrate.py ./sample/chessboard/ 10 7
The first argument is the path to the chessboard. You will also have to input the chessboard dimensions (the number of squares in x and y) Optional arguments:
--out path if you want to output the parameters and the image outputs to a specific path. otherwise it gets writting to ./out
--square_size float if your chessboard squares are not square, you can change this. default is 1.0
With the photos and the produced matrix.txt and distortion.txt, run the following:
python undistort.py --matrix matrix.txt --distortion distortion.txt "/path/to/images/"
Note: Do not forget the quotes in "/path/to/images"
This assumes you already have the distortion and matrix parameters. Put the matri.txt and distortion.txt in their own directory (eg. sample/config) and do the following:
Build:
docker build -t cc_undistort .
Run: (using sample images in this example)
docker run -v ~/CameraCalibration/sample/images:/app/images \
-v ~/CameraCalibration/sample/config:/app/config \
cc_undistort