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require(esm) Backported to Node.js 20, Paving the Way for ESM-Only Packages
require(esm) backported to Node.js 20, easing the transition to ESM-only packages and reducing complexity for developers as Node 18 nears end-of-life.
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).
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.
qimage2ndarray is stable and unit-tested.
FAQs
Conversion between QImages and numpy.ndarrays.
We found that qimage2ndarray demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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