Hello all,
actually, local_maxima should be equivalent to h-maxima, with h=1
h-maxima (and also local_maxima) give non ponctual locations. There
might be a need for a function of ultimate erosion. Does it exist
somewhere ?
I totally agree with you, the official watershed demo should be modified.
Yann GAVET
Assistant Professor - Ecole des Mines de Saint-Etienne
158 Cours Fauriel, 42023 Saint-Etienne cedex 2, FRANCE
Tel: (33) - 4 7742 0170
On 04/12/2018 09:08 AM, imag...@sina.com wrote:
Hi，everyone
I think we should not use peak_local_max for find watershed's seeds. why
not use h_maxima? which can give a h tolerance.
I think if we should replace it in the official demo? It would cause a
misunderstanding.
And scikit-image's h_maxima, h_minima is very slow. here I implements
one with numba,
https://github.com/Image-Py/imagepy/blob/master/imagepy/ipyalg/hydrology/findmax.py.
you can see if it is useful.
yxdragon
----- 原始邮件 -----
发件人：Stefan van der Walt <stef...@berkeley.edu>
收件人："Mailing list for scikit-image (http://scikit-image.org)"
<scikit-image@python.org>
主题：Re: [scikit-image] local maxima improvements
日期：2018年04月12日 03点08分
On Wed, 11 Apr 2018 12:44:45 +1000, Juan Nunez-Iglesias wrote:
> In [7]: image
> Out[7]:
> array([[ 0., 0., 0., 0., 0., 0.],
> [ 0., 1., 0., 0., 0., 0.],
> [ 0., 0., 0., 0., 0., 0.],
> [ 2., 2., 2., 4., 4., 2.],
> [ 2., 2., 2., 4., 4., 2.],
> [ 2., 2., 2., 2., 2., 2.]])
>
> In [15]: feature.peak_local_max(image)
> In [17]: image_peak[tuple(feature.peak_local_max(image).T)] = 1
>
> In [18]: image_peak
> Out[18]:
> array([[ 0., 0., 0., 0., 0., 0.],
> [ 0., 1., 0., 0., 0., 0.],
> [ 0., 0., 0., 0., 0., 0.],
> [ 0., 1., 0., 1., 1., 0.],
> [ 0., 1., 0., 1., 1., 0.],
> [ 0., 0., 0., 0., 0., 0.]])
That output in column 1 looks highly suspect! This is a great example
for a regression test, thanks Yann.
Stéfan
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