Small modifications/additions to http://april.eecs.umich.edu/media/apriltag/apriltag-2015-03-18.tgz
Added a new quad detector and a few various speedups.
Please note: I am not the maintainer of the pypi package listed at https://pypi.org/project/apriltag/ – GitHub issues filed here reporting problems with that package will be summarily closed. Sorry, I don't have time to support someone else's unofficial package.
cd /path/to/apriltag
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j4
If you want to install the library and important binaries to your system directories, you can then type
sudo make install
You can run aprilag_opencv_demo
to do stuff, run with -h
to get help.
So for example, you can run
./apriltag_opencv_demo -B ../images/mapping_feb_2014/*.JPG
./apriltag_opencv_demo -B -c ../images/mapping_feb_2014/*.JPG
to benchmark the new code against the old code.
Note that you must build the software per the instructions above before the Python wrapper can
be used. If you did not install the libraries to the system-wide library directory and you
are not running Python code from the python directory in this repository, your Python code
must specify the path for the apriltag shared library when constructing an
apriltag.Detector
object.
I recently added the ability to estimate 3D tag poses to the Python wrapper. To demonstrate this, after building the software, go to the python directory and run
python apriltag.py -c -k '(765.00, 764.18, 393.72, 304.66)' -s .127 ../images/mapping_feb_2014/*JPG
To estimate tag pose, you need to know the intrinsic camera parameters, which can be estimated using the calibrate_camera.py script.
You also need to know the tag size in order to scale the estimated translation vectors correctly.
Although this functionality is implmemented in the C library, it is not yet coded into the C/C++ demos; I may add it someday if requested.