Optimize addImage for image streaming: fast path bypasses full pipeline#4524
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physwkim wants to merge 4 commits intosilx-kit:mainfrom
Open
Optimize addImage for image streaming: fast path bypasses full pipeline#4524physwkim wants to merge 4 commits intosilx-kit:mainfrom
physwkim wants to merge 4 commits intosilx-kit:mainfrom
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When updating an existing image with same-shape data and the backend renderer supports direct updates (updateData), bypass the full item dirty/remove/add cycle and update the renderer directly. Fast path conditions: - Backend renderer exists and has updateData method - Data shape is unchanged from previous frame - No alternative/alpha images provided (ImageData) Changes: - ImageData.setData: early fast path before data copy - ImageDataBase.setData: direct renderer update when shape unchanged - PlotWidget.addImage: skip redundant setActiveImage on same image - Fix double copy in ImageData.setData (copy=False to super)
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Summary
While testing large image handling for another PR
#4520
I noticed a performance bottleneck when streaming large images (~4096×4096) using
addImage(). Each frame update goes through the full pipeline:For streaming scenarios where the image shape does not change, this introduces unnecessary overhead (renderer recreation, colormap recomputation, and extra data copies).
This PR introduces a fast path allowing the backend renderer to update image data directly when possible.
Changes
Renderer fast path
If the following conditions are met:
updateDataalternativeoralphaimagethen
ImageDataBase.setData()directly calls:This bypasses the remove/add renderer cycle.
Avoid redundant
setActiveImage()callsPlotWidget.addImage()now avoids callingsetActiveImage()if the image is already active, preventing unnecessary signal disconnect/reconnect during streaming.Fix unnecessary double copy
ImageData.setData()previously triggered an additional copy through:This PR changes it to:
File:
This avoids an extra ~64MB memory copy per frame for a 4096×4096 float32 image.
Performance (4096×4096 float32)
copy=True)copy=False)Notes
This optimization was discovered while investigating performance issues during large image testing in PR #4520.
The fast path is conservative and activates only when safe, without introducing new public APIs.