Does you want to mark every 'circle like' parts in the region? peak_local_max will result too many points, may be you should use h_maxima, unfortunatly, h_maximu is also slow. I had mailed befor.
if you want to get the local_max without any other limit, you can use a scipy.ndimage.maximum_filter:
And you may be intresting in my Project, ImagePy:
https://github.com/Image-Py, Which is a imagej of python. or a photoshop with scikit-image core. you can do many things interactively. I use my spare time in the last year, Now it has did a
A small effect. (In the imagepy.ipyalg.hydrology I had implemented a fast findmax function), two snapshots in the attachment.----- 原始邮件 -----
发件人：Dzung Nguyen <dzungng89@gmail.com>
收件人：scikit-image@python.org
主题：[scikit-image] peak_local_max
日期：2017年11月07日 07点37分
Hi all,
I might take the issue
#2758 for my 2nd PR to scikit-image. Could someone point out the potential problems? It does take >20 second on my computer. I looked at the code briefly, and it seems that the bottleneck is _get_high_intensity_peaks?
Thanks,
--
Dzung Nguyen
PhD Student
Electrical Engineering and Computer Science,
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