# pyrtools: tools for multi-scale image processing
[](https://pypi.org/project/pyrtools/)
[](https://github.com/LabForComputationalVision/pyrtools/blob/main/LICENSE)
[](https://github.com/LabForComputationalVision/pyrtools/actions?query=workflow%3Abuild)
[](https://pyrtools.readthedocs.io/en/latest/?badge=latest)
[](https://zenodo.org/doi/10.5281/zenodo.10161031)
[](https://mybinder.org/v2/gh/LabForComputationalVision/pyrtools/v1.0.4?filepath=TUTORIALS%2F)
[](https://codecov.io/gh/LabForComputationalVision/pyrtools)
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](https://github.com/LabForComputationalVision/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.
**NOTE**: If you are only interested in the complex steerable pyramid, we have a
pytorch implementation in the
[plenoptic](https://github.com/LabForComputationalVision/plenoptic/) package;
the implementation in plenoptic is differentiable.
# Citing us
If you use `pyrtools` in a published academic article or presentation, please
cite us! You can find the link to the most recent release on Zenodo
[here](https://zenodo.org/doi/10.5281/zenodo.10161031) (though please specify
the version you used not the most recent one!). You can also get a formatted
citation at the top right of our [GitHub
repo](https://github.com/LabForComputationalVision/pyrtools)
# Installation
It's recommended you install from pip: `pip install pyrtools`.
If you wish to install from the main 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.
# Pyramid resources
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](https://foundationsofvision.stanford.edu/chapter-8-multiresolution-image-representations/),
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".](http://persci.mit.edu/pub_pdfs/RCA84.pdf)
- Notes from David Heeger on [steerable
filters](http://www.cns.nyu.edu/~david/handouts/steerable.pdf)
- Notes from Eero Simoncelli on [the Steerable
Pyramid](http://www.cns.nyu.edu/~eero/STEERPYR/)
# Usage:
- load modules:
```
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.
# For developres
## Testing
You can find unit tests in `TESTS/unitTests.py` and run them with `python
TESTS/unitTests.py`.
## Build the documentation
NOTE: If you just want to read the documentation, you do not need to
do this; documentation is built automatically on
[readthedocs](https://pyrtools.readthedocs.io/en/latest/).
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.
```
# create a new virtual environment and then...
# install pyrtools with sphinx and documentation-related dependencies
pip install -e .[docs]
# 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.
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"description": "# pyrtools: tools for multi-scale image processing\n\n[](https://pypi.org/project/pyrtools/)\n[](https://github.com/LabForComputationalVision/pyrtools/blob/main/LICENSE)\n\n[](https://github.com/LabForComputationalVision/pyrtools/actions?query=workflow%3Abuild)\n[](https://pyrtools.readthedocs.io/en/latest/?badge=latest)\n[](https://zenodo.org/doi/10.5281/zenodo.10161031)\n[](https://mybinder.org/v2/gh/LabForComputationalVision/pyrtools/v1.0.4?filepath=TUTORIALS%2F)\n[](https://codecov.io/gh/LabForComputationalVision/pyrtools)\n\nBriefly, the tools include:\n - Recursive multi-scale image decompositions (pyramids), including\n Laplacian pyramids, QMFs, Wavelets, and steerable pyramids. These\n operate on 1D or 2D signals of arbitrary dimension.\n - Fast 2D convolution routines, with subsampling and boundary-handling.\n - Fast point-operations, histograms, histogram-matching.\n - Fast synthetic image generation: sine gratings, zone plates, fractals, etc.\n - Display routines for images and pyramids. These include several\n auto-scaling options, rounding to integer zoom factors to avoid\n resampling artifacts, and useful labeling (dimensions and gray-range).\n\nThis is a python 3 port of Eero Simoncelli's\n[matlabPyrTools](https://github.com/LabForComputationalVision/matlabPyrTools),\nbut it does not attempt to recreate all of the matlab code from matlabPyrTools.\nThe goal is to create a Python interface for the C code at the heart of\nmatlabPyrTools.\n\n**NOTE**: If you are only interested in the complex steerable pyramid, we have a\npytorch implementation in the\n[plenoptic](https://github.com/LabForComputationalVision/plenoptic/) package;\nthe implementation in plenoptic is differentiable.\n\n# Citing us\n\nIf you use `pyrtools` in a published academic article or presentation, please\ncite us! You can find the link to the most recent release on Zenodo\n[here](https://zenodo.org/doi/10.5281/zenodo.10161031) (though please specify\nthe version you used not the most recent one!). You can also get a formatted\ncitation at the top right of our [GitHub\nrepo](https://github.com/LabForComputationalVision/pyrtools)\n\n# Installation\n\nIt's recommended you install from pip: `pip install pyrtools`.\n\nIf you wish to install from the main branch, it's still recommended\nto use pip, just run `pip install .` (or `pip install -e .` if you\nwant the changes you make in the directory to be reflected in your\ninstall) from the root directory of this project. The core of this\ncode is the C code, and the pip install will compile it nicely.\n\n# Pyramid resources\n\nIf you would like to learn more about pyramids and why they're helpful\nfor image processing, here are some resources to get you started:\n\n - Brian Wandell's [Foundations of\n Vision](https://foundationsofvision.stanford.edu/chapter-8-multiresolution-image-representations/),\n chapter 8 (the rest of the book is helpful if you want to\n understand the basics of the visual system).\n - [Adelson et al, 1984, \"Pyramid methods in image\n processing\".](http://persci.mit.edu/pub_pdfs/RCA84.pdf)\n - Notes from David Heeger on [steerable\n filters](http://www.cns.nyu.edu/~david/handouts/steerable.pdf)\n - Notes from Eero Simoncelli on [the Steerable\n Pyramid](http://www.cns.nyu.edu/~eero/STEERPYR/)\n\n# Usage:\n\n- load modules:\n```\nimport pyrtools as pt\n```\n\n- create pyramid:\n```\npyr = pt.pyramids.LaplacianPyramid(img)\n```\n\n- reconstruct image from pyramid:\n```\nrecon_img = pyr.recon_pyr()\n```\n\nPlease see `TUTORIALS/02_pyramids.ipynb` for more examples.\n\n# For developres\n\n## Testing\n\nYou can find unit tests in `TESTS/unitTests.py` and run them with `python\nTESTS/unitTests.py`.\n\n## Build the documentation\n\nNOTE: If you just want to read the documentation, you do not need to\ndo this; documentation is built automatically on\n[readthedocs](https://pyrtools.readthedocs.io/en/latest/).\n\nHowever, it can be built locally as well. You would do this if you've\nmade changes locally to the documentation (or the docstrings) that you\nwould like to examine before pushing.\n\n```\n# create a new virtual environment and then...\n# install pyrtools with sphinx and documentation-related dependencies\npip install -e .[docs]\n# build documentation\ncd docs/\nmake html\n```\n\nThe index page of the documentation will then be located at\n`docs/_build/html/index.html`, open it in your browser to navigate\naround.\n",
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