Most efficient way to calculate average value of labelled objects within an image

[Tamas H.]

How about this: maskimg is the image with the labels, img is the image you
want to analyze, then:

for i in range(1, maskimg.max()):
    img[ maskimg==i].mean()
...

On Fri, May 13, 2016 at 11:54 AM, 'Robin Wilson' via scikit-image <
scikit-image at googlegroups.com> wrote:

> Hi,
>
> I have a labelled image, where each individual connected object has a
> unique integer value (eg. as produced from skimage.measure.label), and I
> want to get the mean value of these pixels from another image (eg. the
> image that I originally segmented before labelling).
>
> What is the most efficient way to do this? The naive way is to loop over
> the values in the image calculating it for each one - but I assume that
> numpy (or skimage itself) has a far better way of doing this...
>
> Thanks,
>
> Robin
>
> Dr Robin Wilson
> Research Fellow
> University of Southampton, UK
>
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