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batch_size: int = 1 - number of frames to include in each batch passed to the frame processing function
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block: bool = False - method returns immediately (False) or blocks until function returns (True)
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complete_func: Callable[[], None] = None - function to call when frame processing is complete
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display_progress: bool = True - display progress as frames are processed
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func: Callable[[npt.NDArray[np.uint8]], None] - function to process the Sketch's pixels, one batch at a time
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hook_post_draw: bool = False - attach hook to Sketch's post_draw method instead of draw
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limit: int = 0 - total number of frames to pass to the frame processing function
@@ -30,6 +31,8 @@ The `queue_limit` parameter specifies a maximum queue size. If frames are added
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By default this function will return right away and will process frames in the background while the Sketch is running. Set the `block` parameter to `True` to instruct the method to not return until the processing is complete or the Sketch terminates. This blocking feature is not available on macOS when the Sketch is executed through an IPython kernel.
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By default this function will report its progress as frames are processed. If you are using a Jupyter Notebook and happen to be processing tens of thousands of frames, this might cause Jupyter to crash. To avoid that fate, set the `display_progress` parameter to `False`.
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Use the `sketch` parameter to specify a different running Sketch, such as a Sketch created using Class mode. If your Sketch has a `post_draw()` method, use the `hook_post_draw` parameter to make this function run after `post_draw()` instead of `draw()`. This is important when using Processing libraries that support `post_draw()` such as Camera3D or ColorBlindness.
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