10/30/2022 0 Comments Qt update gui from worker thread![]() ![]() Manages the work being done by your function in another thread. ![]() run ()Ĭonverts your function into one that returns a add_image ) # connect callback functions worker. Viewer () worker = average_large_image () # create "worker" object worker. Import napari import numpy as np from napari.qt.threading import thread_worker def average_large_image (): return np. The simplest way to run a function in another thread in napari is to decorate napari also provides a fewĬonvenience functions that allow you to easily run your long-running If you already have experience with any of these methods, you should be able to Of this document, but strategies generally fall into one of three camps:įor a good high level overview on concurrency in python, seeįor a good introduction to Python’s new async/await syntax. #Qt update gui from worker thread full#It’s a rich, complicated topic, and a full treatment is well beyond the scope The same time) in python, each with their own advantages and disadvantages. There are multiple ways to achieve “concurrency” (multiple things happening at ![]() You must run your function in another thread or process. In order to avoid freezing the viewer during a long-running blocking function, add_image ( image ) # the entire interface freezes! but if we trigger a long computation image = np. Import napari import numpy as np viewer = napari. Using Dask and napari to process & view large datasetsĪnnotating segmentation with text and bounding boxesĪn introduction to the event loop in napari ![]()
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