[scikit-image] Memory consumption of measure.label (compared to matlab)

[Jaime Fernández del Río]

On Wed, Jul 12, 2017 at 7:29 PM, Martin Fleck <martin.fleck at uni-konstanz.de>
wrote:

> Hello skimage users and devs,
>
> in an image analysis of mine, I use skimage.measure.label and
> skimage.morphology of  skimage 0.13.0 .
>

I have no answer to your question, but if anyone more knowledgeable on
skimage internals could confirm if any of these operations rely on
scipy.ndimage functionality, I could try to look at potential improvements
there.


>
> My problem my analysis uses much more memory than I expect.
> I attached output from the memory_profiler package, with which I tried
> to keep track of the memory consumption of my analysis.
> You can see that for an ~8MiB file that I used for testing,
> skimage.measure.label needs to use 56MiB of memory, which surprised me.
> My first question is: Am I doing something wrong here?
> The memory consumption is skimage.morphology.remove_small_objects is
> surprisingly high, too.
>
> I want to be able to process images of several GiB on my machine.
> I hope I can excuse the following comparison with matlab by pointing to
> the similarity between skimage.measure.regionprops and matlabs regionprops:
> With Matlab I don't run into any memory problems on the very same machine.
>
> I would be very glad if I could continue using python for this analysis
> and not have to rely on matlab.
> Is there a way for me to reduce the memory consumption if I want to use
> skimage.morphology.remove_small_objects() and
> skimage.measure.regionprops() for which I need the label()?
>
> Best Regards,
> Martin
>
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>
>


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