Mailman 3 July 2017 - scikit-image

plot_matches() error?
by Riley Myers 27 Jul '17

27 Jul '17

Hello, I am currently having a bit of trouble with using scikit-image to align two images using ORB. At the moment, if I try to plot the images, keypoints and matches using plot_matches, I get a plot with only the images and the keypoints and then a large stack trace, attached below. I thought that my code might be the problem, but the same thing occurs if I run one of the ipython notebooks from the skimage-tutorials, specifically /lectures/adv3_panorama-stitching.ipynb, using all of their images, etc. This seems to imply that something is off with my setup. According to `conda list`, I'm using version 0.13.0 of scikit-image. Do any of you have any ideas? Thanks! Riley stack trace: https://pastebin.com/DtGTmmft conda list output: https://pastebin.com/fEzikbi2

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Re: [scikit-image] Sprint @ scipy: ticket triage and gathering ideas
by Nelle Varoquaux 15 Jul '17

15 Jul '17

Hi everyone, Quick email to remind that we are about to start a sprint at Scipy! Expect a lot of contributions today! Help reviewing would be appreciated. Cheers, Nelle On 11 July 2017 at 10:13, Nelle Varoquaux <nelle.varoquaux(a)gmail.com> wrote: > Hi folks, > > Scikit-image will be hosting a sprint this week-end at scipy. In order > to welcome new contributors, it'd be nice if we could gather ideas and > start triaging tickets. Contact me or Stéfan if you have any > questions. > > Also, expect an increase in pull request activity! This might be a > good opportunity to make progress and close some old pull requests. > > Cheers, > N

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Re: [scikit-image] Image intensity measure.regionprops
by Cedric Espenel 15 Jul '17

15 Jul '17

Hi Jeremy, Thank you for your answer, it makes a lot of sense to mask the intensity image with the label region before measuring the mean intensity, which is exactly what is in the source code: > np.mean(self.intensity_image[self.image]) I guess I should have check before sending an email but the thank you for your help! Best, Cedric 2017-07-14 6:49 GMT-07:00 Jeremy Chacon <chaco001(a)umn.edu>: > Hi Cedric, > > I'm just a user but my interpretation is that mean_intensity is the mean > intensity of the pixels in that labeled region, whereas intensity_image is > the region within its bounding box. So intensity_image can contain zeros > where the label isn't present. > > See this: > > from skimage import measure > import numpy as np > a = np.array([[2,3,4,5],[6,5,4,3]]) > b = np.array([[0,1,1,0],[0,1,0,0]]) > > rp = measure.regionprops(b, a) > > rp[0].mean_intensity # 4 > rp[0].intensity_image # contains a zero, making the mean of this < 4 > > > > On Fri, Jul 14, 2017 at 12:23 AM, Cedric Espenel <cedric.espenel(a)gmail.com > > wrote: > >> Hi scikit-image users/devs, >> >> I'm using skimage.measure.regionprops and I'm little bit confused about a >> result I get with it. >> >> I'm working with a zstack of a microscopy image that I have >> segmented/label and I'm trying to get the mean intensity of the labeled >> region: >> >> region_props = measure.regionprops(label_image, intensity_image) >>> >> >> If now I do: >> >> for prop in region_prop: >> >> print('x', prop.mean_intensity) >>>> >>> print('y', np.mean(prop.intensity_image)) >>>> >>> >> prop.mean_intensity and np.mean(prop.intensity_image) give me different >> value, which confuse me. Can someone help me understand why I'm getting >> something different? >> >> Thank you in advance for your help. >> >> Sincerely, >> >> Cedric >> >> >> _______________________________________________ >> scikit-image mailing list >> scikit-image(a)python.org >> https://mail.python.org/mailman/listinfo/scikit-image >> >> > > > -- > > *___________________________________________________________________________Jeremy > M. Chacon, Ph.D.* > > *Post-Doctoral Associate, Harcombe Lab* > *University of Minnesota* > *Ecology, Evolution and Behavior* > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image > >

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Re: [scikit-image] Image intensity measure.regionprops
by Jeremy Chacon 14 Jul '17

14 Jul '17

Hi Cedric, I'm just a user but my interpretation is that mean_intensity is the mean intensity of the pixels in that labeled region, whereas intensity_image is the region within its bounding box. So intensity_image can contain zeros where the label isn't present. See this: from skimage import measure import numpy as np a = np.array([[2,3,4,5],[6,5,4,3]]) b = np.array([[0,1,1,0],[0,1,0,0]]) rp = measure.regionprops(b, a) rp[0].mean_intensity # 4 rp[0].intensity_image # contains a zero, making the mean of this < 4 On Fri, Jul 14, 2017 at 12:23 AM, Cedric Espenel <cedric.espenel(a)gmail.com> wrote: > Hi scikit-image users/devs, > > I'm using skimage.measure.regionprops and I'm little bit confused about a > result I get with it. > > I'm working with a zstack of a microscopy image that I have > segmented/label and I'm trying to get the mean intensity of the labeled > region: > > region_props = measure.regionprops(label_image, intensity_image) >> > > If now I do: > > for prop in region_prop: > > print('x', prop.mean_intensity) >>> >> print('y', np.mean(prop.intensity_image)) >>> >> > prop.mean_intensity and np.mean(prop.intensity_image) give me different > value, which confuse me. Can someone help me understand why I'm getting > something different? > > Thank you in advance for your help. > > Sincerely, > > Cedric > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image > > -- *___________________________________________________________________________Jeremy M. Chacon, Ph.D.* *Post-Doctoral Associate, Harcombe Lab* *University of Minnesota* *Ecology, Evolution and Behavior*

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Re: [scikit-image] Numba on pypi
by Ralf Gommers 14 Jul '17

14 Jul '17

On Fri, Jul 14, 2017 at 8:15 PM, Matthew Brett <matthew.brett(a)gmail.com> wrote: > Hi, > > On Thu, Jul 13, 2017 at 9:10 AM, Matthew Brett <matthew.brett(a)gmail.com> > wrote: > > Hi, > > > > On Thu, Jul 13, 2017 at 8:50 AM, Ralf Gommers <ralf.gommers(a)gmail.com> > wrote: > >> > >> > >> On Thu, Jul 13, 2017 at 6:16 PM, Stefan van der Walt < > stefanv(a)berkeley.edu> > >> wrote: > >>> > >>> Hi everyone, > >>> > >>> As many of you know, speed has been a point of contention in > >>> scikit-image for a long time. We've made a very deliberate decision to > >>> focus on writing high-level, understandable code (via Python and > >>> Cython): both to lower the barrier to entry for newcomers, and to > lessen > >>> the burden on maintainers. But execution time comparisons, vs OpenCV > >>> e.g., left much to be desired. > >>> > >>> I think we have hit a turning point in the road. Binary wheels for > >>> Numba (actually, llvmlite) were recently uploaded to PyPi, making this > >>> technology available to users on both pip and conda installations. The > >>> importance of this release on pypi should not be dismissed, and I am > >>> grateful to the numba team and Continuum for making that decision. > >> > >> > >> Agreed. Note that there are no Windows wheels up on PyPI (yet, or not > >> coming?). Given that there are no SciPy wheels for Windows either I > don't > >> think that that changes your argument much - people should just use a > binary > >> distribution on Windows - but I thought I'd point it out anway. > > > > We might be close to a working scipy wheel - discussion evolving over > > at https://github.com/scipy/scipy/issues/7551#issuecomment-314922271 > > Following up on my own post - updates on progress for a scipy wheel here: > > https://github.com/scipy/scipy/issues/759 > > > If we do succeed, that would make the lack of a numba wheel for > > Windows much more significant. > > > > Does anyone know Continuum's plans in this matter? Is the numba > > wheel recipe open-source? > > Can anyone comment here? > > The basic question is - what would happen if Continuum stopped > supplying a pypi wheel? If the answer is the standard open source > answer - someone else would take over pretty quickly - that's fine. > Otherwise, it's a problem. > Can't read their mind, but did look at the build instructions. Doesn't look that hard to build and package, if the need arises (which is unlikely). And the current wheels will not disappear. So I don't really see an issue. Cheers, Ralf

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Re: [scikit-image] Numba on pypi
by Matthew Brett 14 Jul '17

14 Jul '17

Hi, On Thu, Jul 13, 2017 at 9:10 AM, Matthew Brett <matthew.brett(a)gmail.com> wrote: > Hi, > > On Thu, Jul 13, 2017 at 8:50 AM, Ralf Gommers <ralf.gommers(a)gmail.com> wrote: >> >> >> On Thu, Jul 13, 2017 at 6:16 PM, Stefan van der Walt <stefanv(a)berkeley.edu> >> wrote: >>> >>> Hi everyone, >>> >>> As many of you know, speed has been a point of contention in >>> scikit-image for a long time. We've made a very deliberate decision to >>> focus on writing high-level, understandable code (via Python and >>> Cython): both to lower the barrier to entry for newcomers, and to lessen >>> the burden on maintainers. But execution time comparisons, vs OpenCV >>> e.g., left much to be desired. >>> >>> I think we have hit a turning point in the road. Binary wheels for >>> Numba (actually, llvmlite) were recently uploaded to PyPi, making this >>> technology available to users on both pip and conda installations. The >>> importance of this release on pypi should not be dismissed, and I am >>> grateful to the numba team and Continuum for making that decision. >> >> >> Agreed. Note that there are no Windows wheels up on PyPI (yet, or not >> coming?). Given that there are no SciPy wheels for Windows either I don't >> think that that changes your argument much - people should just use a binary >> distribution on Windows - but I thought I'd point it out anway. > > We might be close to a working scipy wheel - discussion evolving over > at https://github.com/scipy/scipy/issues/7551#issuecomment-314922271 Following up on my own post - updates on progress for a scipy wheel here: https://github.com/scipy/scipy/issues/759 > If we do succeed, that would make the lack of a numba wheel for > Windows much more significant. > > Does anyone know Continuum's plans in this matter? Is the numba > wheel recipe open-source? Can anyone comment here? The basic question is - what would happen if Continuum stopped supplying a pypi wheel? If the answer is the standard open source answer - someone else would take over pretty quickly - that's fine. Otherwise, it's a problem. Cheers, Matthew

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Image intensity measure.regionprops
by Cedric Espenel 14 Jul '17

14 Jul '17

Hi scikit-image users/devs, I'm using skimage.measure.regionprops and I'm little bit confused about a result I get with it. I'm working with a zstack of a microscopy image that I have segmented/label and I'm trying to get the mean intensity of the labeled region: region_props = measure.regionprops(label_image, intensity_image) > If now I do: for prop in region_prop: print('x', prop.mean_intensity) >> > print('y', np.mean(prop.intensity_image)) >> > prop.mean_intensity and np.mean(prop.intensity_image) give me different value, which confuse me. Can someone help me understand why I'm getting something different? Thank you in advance for your help. Sincerely, Cedric

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Re: [scikit-image] Numba on pypi
by Stefan van der Walt 14 Jul '17

14 Jul '17

On 13 July 2017 22:30:03 Nadav Horesh <nadavh.horesh(a)gmail.com> wrote: > I'd make numba dependency optional, since keeping llvm and llvmlite > versions in sync requires special attention (at least with the Linux > distros I used), what makes numba availability below 100%. I don't think we need to keep these things in sync (if llvmlite is available at all, we're fine). And for pip installs we can consider precompiled binary modules, I guess? Best regards Stéfan

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Re: [scikit-image] Numba on pypi
by Nadav Horesh 14 Jul '17

14 Jul '17

I'd make numba dependency optional, since keeping llvm and llvmlite versions in sync requires special attention (at least with the Linux distros I used), what makes numba availability below 100%. Nadav. On Jul 14, 2017 5:23 AM, "Gregory Lee" <grlee77(a)gmail.com> wrote: > I am also +1 on allowing numba code in scikit-image. I have tended to > prefer Cython in the past, but it has been a while since I looked at numba > and it seems it has come a long way in recent years. Juan's blog post and > the simple example you provided are great examples of relevant use cases. > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image > >

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Re: [scikit-image] Numba on pypi
by Gregory Lee 14 Jul '17

14 Jul '17

I am also +1 on allowing numba code in scikit-image. I have tended to prefer Cython in the past, but it has been a while since I looked at numba and it seems it has come a long way in recent years. Juan's blog post and the simple example you provided are great examples of relevant use cases.

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scikit-image July 2017