pyapr 1.0.0rc2

Content-adaptive image processing using the Adaptive Particle Representation

pyapr

Documentation can be found here.

Content-adaptive storage and processing of large volumetric microscopy data using the Adaptive Particle Representation (APR).

The APR is an adaptive image representation designed primarily for large 3D fluorescence microscopy datasets. By replacing pixels with particles positioned according to the image content, it enables orders-of-magnitude compression of sparse image data while maintaining image quality. However, unlike most compression formats, the APR can be used directly in a wide range of processing tasks - even on the GPU!

For more detailed information about the APR and its use, see:

• Adaptive particle representation of fluorescence microscopy images (nature communications)
• Parallel Discrete Convolutions on Adaptive Particle Representations of Images (arXiv preprint)

pyapr is built on top of the C++ library LibAPR using pybind11.

Installation

For Windows 10, OSX, and Linux and Python versions 3.7-3.9 direct installation with OpenMP support should work via pip:

pip install pyapr

Note: Due to the use of OpenMP, it is encouraged to install as part of a virtualenv.

See INSTALL for manual build instructions.

Exclusive features

In addition to providing wrappers for most of the functionality of LibAPR, we provide a number of new features that simplify the generation and handling of the APR. For example:

• Interactive APR conversion (see get_apr_interactive_demo and get_apr_by_block_interactive_demo)
• Interactive APR z-slice viewer (see viewer_demo)
• Interactive APR raycast (maximum intensity projection) viewer (see raycast_demo)
• Interactive lossy compression of particle intensities (see compress_particles_demo)

For further examples see the demo scripts.

Also be sure to check out our (experimental) napari plugin: napari-apr-viewer.

License

pyapr is distributed under the terms of the Apache Software License 2.0.

Issues

If you encounter any problems, please file an issue with a short description.

Contact us

If you have a project or algorithm in which you would like to try using the APR, don't hesitate to get in touch with us. We would be happy to assist you!