[scikit-image] local maxima improvements

[Stefan van der Walt]

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