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 _______________________________________________ scikit-image mailing list scikit-image@python.org https://mail.python.org/mailman/listinfo/scikit-image
