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qimage2ndarray

qimage2ndarray is a small python extension for quickly converting between QImages and numpy.ndarrays (in both directions). These are very common tasks when programming e.g. scientific visualizations in Python using PyQt4 as the GUI library.

• Supports conversion of scalar and RGB data, with arbitrary dtypes and memory layout, with and without alpha channels, into QImages (e.g. for display or saving using Qt).

• qimage2ndarray makes it possible to create ndarrays that are views into a given QImage's memory.

  This allows for very efficient data handling and makes it possible to modify Qt image data in-place (e.g. for brightness/gamma or alpha mask modifications).

• qimage2ndarray is stable and unit-tested:

  • proper reference counting even with views (ndarray.base_ points to the underlying QImage)

  • handles non-standard widths and respects QImage's 32-bit row alignment

• Masked arrays_ are also supported and are converted into QImages with transparent pixels.

• Supports recarrays_ (and comes with an appropriate dtype) for convenient access to RGB(A) channels.

• Supports value scaling / normalization to 0..255 for convenient display of arbitrary NumPy arrays.

• Recent additions are convenient image loading / saving methods

.. _masked arrays: http://docs.scipy.org/doc/numpy/reference/maskedarray.generic.html .. _recarrays: http://docs.scipy.org/doc/numpy/reference/generated/numpy.recarray.html

Code

The extension is open source, BSD-licensed, and the repository can be browsed online_ or cloned using Git:

git clone https://github.com/hmeine/qimage2ndarray.git

Documentation

Documentation can be found in the doc/ subdirectory or on GitHub:

http://hmeine.github.io/qimage2ndarray

Contributors

This package is written and maintained by Hans Meine [email protected].

I am grateful for feedback from Ullrich Köthe, PowerPC/endianness testing by Helge Kreutzmann and initial PyQt5 support by Rudolf Höfler.

.. _browsed online: https://github.com/hmeine/qimage2ndarray .. _ndarray.base: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.base.html