Briefly, the tools include:
- Recursive multi-scale image decompositions (pyramids), including Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These operate on 1D or 2D signals of arbitrary dimension.
- Fast 2D convolution routines, with subsampling and boundary-handling.
- Fast point-operations, histograms, histogram-matching.
- Fast synthetic image generation: sine gratings, zone plates, fractals, etc.
- Display routines for images and pyramids. These include several auto-scaling options, rounding to integer zoom factors to avoid resampling artifacts, and useful labeling (dimensions and gray-range).
This is a python 3 port of Eero Simoncelli's matlabPyrTools, but it does not attempt to recreate all of the matlab code from matlabPyrTools. The goal is to create a Python interface for the C code at the heart of matlabPyrTools.
It's recommended you install from pip: pip install pyrtools
. The pip
install has been tested on Linux and on OSX. Windows is NOT supported
because of issues with the C compiler (gcc
isn't necessarily
installed); if you have experience with C compilation on Windows,
please open a pull request. It's possible that the way to fix this is
to use Cython, ensuring that Cython is installed before attempting to
run the pip command, and then adding: from Cython.Build import cythonize
and wrapping the ext_modules
in the setup
call with
cythonize
, but I'm not sure.
If you wish to install from the master branch, it's still recommended
to use pip, just run pip install .
(or pip install -e .
if you
want the changes you make in the directory to be reflected in your
install) from the root directory of this project. The core of this
code is the C code, and the pip install will compile it nicely.
Python 3.5, 3.6, and 3.7 all officially supported.
Other requirements:
- numpy
- scipy
- matplotlib
- Pillow
- tqdm
- requests
IPython is optional. If it's not installed,
pyrtools.display_tools.animshow
must be called with as_html5=False
(but since this is for displaying the animated image in a Jupyter /
IPython notebook, you probably won't need that functionality).
For the C code to compile, we require gcc
version >= 6, because of
this
issue
If you would like to learn more about pyramids and why they're helpful for image processing, here are some resources to get you started:
- Brian Wandell's Foundations of Vision, chapter 8 (the rest of the book is helpful if you want to understand the basics of the visual system).
- Adelson et al, 1984, "Pyramid methods in image processing".
- Notes from David Heeger on steerable filters
- Notes from Eero Simoncelli on the Steerable Pyramid
Rob Young and Eero Simoncelli, 7/13
William Broderick, 6/17
William Broderick, Pierre-Étienne Fiquet, Zhuo Wang, Zahra Kadkhodaie, Nikhil Parthasarathy, and the Lab for Computational Vision, 4/19
method parameters mimic the matlab function parameters except that there's no need to pass pyr or pind, since the pyPyrTools version pyr and pyrSize are properties of the class.
- load modules (note that if you installed via pip, you can skip the first two lines):
import pyrtools as pt
- create pyramid:
pyr = pt.pyramids.LaplacianPyramid(img)
- reconstruct image from pyramid:
recon_img = pyr.recon_pyr()
Please see TUTORIALS/02_pyramids.ipynb
for more examples. You can
start this with: jupyter notebook 02_pyramids.ipynb
if you have iPython
and Jupyter installed.
All code should be considered a beta release. By that we mean that it is being
actively developed and tested. You can find unit tests in
TESTING/unitTests.py
.
and run
python unitTests.py
.
If you're using functions or parameters that do not have associated unit tests you should test this yourself to make sure the results are correct. You could then submit your test code, so that we can build more complete unit tests.
NOTE: If you just want to read the documentation, you do not need to do this; documentation is built automatically on readthedocs.
However, it can be built locally as well. You would do this if you've
made changes locally to the documentation (or the docstrings) that you
would like to examine before pushing. The virtual environment required
to do so is defined in docs/environment.yml
, so to create that
environment and build the docs, do the following from the project's
root directory:
# install sphinx and required packages to build documentation
conda env create -f docs/environment.yml
# activate the environment
conda activate pyrtools_docs
# install pyrtools
pip install -e .
# build documentation
cd docs/
make html
The index page of the documentation will then be located at
docs/_build/html/index.html
, open it in your browser to navigate
around.
The pyrtools_docs
environment you're creating contains the package
sphinx
and several extensions for it that are required to build the
documentation. You also need to install pyrtools
from your local
version so that sphinx
can import the library and grab all of the
docstrings (you're installing the local version so you can see all the
changes you've made).