Hi Dzung Nguyen: 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: # python code maximg = maximum_filter(img, 3) local_max = maximg == img 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. YXDragonBest ----- 原始邮件 ----- 发件人：Dzung Nguyen email@example.com 收件人：firstname.lastname@example.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 StudentElectrical Engineering and Computer Science,Northwestern University, IL, USA http://users.eecs.northwestern.edu/~dtn419/
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