Mailman 3 May 2016 - scikit-image

Re: blob detection and dust removal
by Raphael Okoye 02 May '16

02 May '16

hi Vighnesh I plan to use this guy http://scikit-image.org/docs/dev/auto_examples/plot_regionprops.html. The documentation on regionprops ( http://scikit-image.org/docs/dev/api/skimage.measure.html#regionprops) says I can get parameters such as co-ordinate positions, equivalent diameter etc But first I need to think of a way to exclude the dust particles, that is the main challenge. Thanks Raphael On 2 May 2016 at 02:30, Vighnesh Birodkar <vighneshbirodkar(a)gmail.com> wrote: > How do you plan to find the position of the real crystals ? Maybe the > function you will use to find the original crystals will take a mask > argument ? > > On Mon, May 2, 2016 at 1:07 AM, Raphael Okoye <raphael(a)aims.ac.za> wrote: > >> hi Vighnesh, >> >> Further processing involves getting the size and positions of real >> crystals (I want to use the positions to estimate the pair correlation >> function and then using the pair correlation function to estimate the >> structure factor) The image comes from a sequence of time lapse images. >> There are dust particles of various sizes in the images so if they are not >> eliminated, a false structure factor will be determined. The median filter >> took care of the very little ones but didn’t work for the bigger ones. >> >> Thanks a lot. >> >> Raphael >> >> On 1 May 2016 at 21:27, Vighnesh Birodkar <vighneshbirodkar(a)gmail.com> >> wrote: >> >>> Hi >>> >>> That really depends on your application. What's your motivation for >>> removing these dust particles ? How are these images going to be processed >>> further ? >>> >>> Thanks >>> Vighnesh >>> >>> On Monday, May 2, 2016 at 12:13:27 AM UTC-4, Raphael wrote: >>>> >>>> hi Vighnesh, >>>> >>>> Thanks a bunch!! I see my error now. >>>> >>>> Actually that blob you detected a dust particle. Which operation would >>>> you suggest to erase it? I tried morphological erosion but it doesn't take >>>> it away. >>>> >>>> Thanks >>>> Raphael >>>> >>>> On 1 May 2016 at 18:27, Vighnesh Birodkar <vighnesh...(a)gmail.com> >>>> wrote: >>>> >>>>> Hello Raphael >>>>> >>>>> The error here is because the output of blob_doh in a numpy array of >>>>> blobs, it is not an image meant for display. If you notice the example the >>>>> blobs are being drawn separately inside the for loop. If no blobs are being >>>>> detected, you can adjust the threshold. Lowering the threshold will make >>>>> the function detect more blobs. It is clarified futher in the documentation >>>>> >>>>> http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.b… >>>>> >>>>> I was able to detect one blob in your image with the default threshold >>>>> value. See: >>>>> >>>>> https://gist.github.com/vighneshbirodkar/c16515126e648cf92f08d3319d3a023e >>>>> >>>>> Find the result attached. >>>>> >>>>> Thanks >>>>> Vighnesh >>>>> >>>>> On Saturday, April 30, 2016 at 2:02:51 AM UTC-4, Raphael wrote: >>>>> >>>>>> hi folks, >>>>>> >>>>>> Got a problem removing dust and identifying blobs/crytals. Kindly >>>>>> see my code below >>>>>> >>>>>> >>>>>> from __future__ import division, print_function >>>>>> import matplotlib.pyplot as plt >>>>>> import numpy as np >>>>>> from skimage import io, feature, color, measure, draw, img_as_float, >>>>>> exposure >>>>>> from skimage.filters.rank import median >>>>>> from skimage.feature import blob_dog, blob_log, blob_doh >>>>>> from skimage.morphology import disk >>>>>> >>>>>> #raw image >>>>>> image_raw = >>>>>> img_as_float((io.imread('/home/raphael/Documents/ScikitImage/Run >>>>>> 4-2_00061cropped.tif'))) (RawImage.tif attached) >>>>>> plt.imshow(image_raw) >>>>>> >>>>>> #converted to grayscale >>>>>> >>>>>> img_gray = >>>>>> color.rgb2gray(io.imread('/home/raphael/Documents/ScikitImage/Run >>>>>> 4-2_00061cropped.tif')) >>>>>> plt.imshow(image_gray) >>>>>> >>>>>> >>>>>> #applied median filter to take out small dust particles. But the big >>>>>> dust particle on the top right corner still persists (see median1.png >>>>>> attached) >>>>>> img_filtered=median(img_gray,disk(10)) >>>>>> plt.imshow(img_filtered) >>>>>> >>>>>> >>>>>> #applied adapthist to make image more clearer (see adaptive.png) >>>>>> >>>>>> img_equalized=exposure.equalize_adapthist(img_filtered) >>>>>> plt.imshow(img_equalized) >>>>>> >>>>>> #trying to detect the crystals/blobs. I followed the example here >>>>>> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob… >>>>>> But this gave an error. matplotlib was not happy with the data type >>>>>> blobs_doh = blob_doh(img_equalized, max_sigma=30, threshold=.1) >>>>>> plt.imshow(blobs_doh) >>>>>> >>>>>> My problems are: >>>>>> >>>>>> 1. I could not get the dust particle out especially the really big >>>>>> one on the top right. How can I get it out? >>>>>> >>>>>> 2. I could not detect the crystals/blobs in the image using blob_doh >>>>>> >>>>>> Any ideas/suggestions is highly appreciated. Thank you! >>>>>> >>>>> -- >>>>> You received this message because you are subscribed to a topic in the >>>>> Google Groups "scikit-image" group. >>>>> To unsubscribe from this topic, visit >>>>> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe >>>>> . >>>>> To unsubscribe from this group and all its topics, send an email to >>>>> scikit-image...(a)googlegroups.com. >>>>> To post to this group, send email to scikit...(a)googlegroups.com. >>>>> To view this discussion on the web, visit >>>>> https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d… >>>>> <https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d…> >>>>> . >>>>> >>>>> For more options, visit https://groups.google.com/d/optout. >>>>> >>>> >>>> -- >>> You received this message because you are subscribed to a topic in the >>> Google Groups "scikit-image" group. >>> To unsubscribe from this topic, visit >>> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. >>> To unsubscribe from this group and all its topics, send an email to >>> scikit-image+unsubscribe(a)googlegroups.com. >>> To post to this group, send email to scikit-image(a)googlegroups.com. >>> To view this discussion on the web, visit >>> https://groups.google.com/d/msgid/scikit-image/b9ede614-1c9d-4a22-a681-fab4… >>> <https://groups.google.com/d/msgid/scikit-image/b9ede614-1c9d-4a22-a681-fab4…> >>> . >>> >>> For more options, visit https://groups.google.com/d/optout. >>> >> >> -- >> You received this message because you are subscribed to a topic in the >> Google Groups "scikit-image" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. >> To unsubscribe from this group and all its topics, send an email to >> scikit-image+unsubscribe(a)googlegroups.com. >> To post to this group, send email to scikit-image(a)googlegroups.com. >> To view this discussion on the web, visit >> https://groups.google.com/d/msgid/scikit-image/CAFCvXeMTH9ke7Cv%3DucywhtaWP… >> <https://groups.google.com/d/msgid/scikit-image/CAFCvXeMTH9ke7Cv%3DucywhtaWP…> >> . >> >> For more options, visit https://groups.google.com/d/optout. >> > > -- > You received this message because you are subscribed to a topic in the > Google Groups "scikit-image" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > scikit-image+unsubscribe(a)googlegroups.com. > To post to this group, send email to scikit-image(a)googlegroups.com. > To view this discussion on the web, visit > https://groups.google.com/d/msgid/scikit-image/CAD82iYrA%2BgP0K2zopnj8Cp_Jg… > <https://groups.google.com/d/msgid/scikit-image/CAD82iYrA%2BgP0K2zopnj8Cp_Jg…> > . > > For more options, visit https://groups.google.com/d/optout. >

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Re: blob detection and dust removal
by Vighnesh Birodkar 02 May '16

02 May '16

How do you plan to find the position of the real crystals ? Maybe the function you will use to find the original crystals will take a mask argument ? On Mon, May 2, 2016 at 1:07 AM, Raphael Okoye <raphael(a)aims.ac.za> wrote: > hi Vighnesh, > > Further processing involves getting the size and positions of real > crystals (I want to use the positions to estimate the pair correlation > function and then using the pair correlation function to estimate the > structure factor) The image comes from a sequence of time lapse images. > There are dust particles of various sizes in the images so if they are not > eliminated, a false structure factor will be determined. The median filter > took care of the very little ones but didn’t work for the bigger ones. > > Thanks a lot. > > Raphael > > On 1 May 2016 at 21:27, Vighnesh Birodkar <vighneshbirodkar(a)gmail.com> > wrote: > >> Hi >> >> That really depends on your application. What's your motivation for >> removing these dust particles ? How are these images going to be processed >> further ? >> >> Thanks >> Vighnesh >> >> On Monday, May 2, 2016 at 12:13:27 AM UTC-4, Raphael wrote: >>> >>> hi Vighnesh, >>> >>> Thanks a bunch!! I see my error now. >>> >>> Actually that blob you detected a dust particle. Which operation would >>> you suggest to erase it? I tried morphological erosion but it doesn't take >>> it away. >>> >>> Thanks >>> Raphael >>> >>> On 1 May 2016 at 18:27, Vighnesh Birodkar <vighnesh...(a)gmail.com> wrote: >>> >>>> Hello Raphael >>>> >>>> The error here is because the output of blob_doh in a numpy array of >>>> blobs, it is not an image meant for display. If you notice the example the >>>> blobs are being drawn separately inside the for loop. If no blobs are being >>>> detected, you can adjust the threshold. Lowering the threshold will make >>>> the function detect more blobs. It is clarified futher in the documentation >>>> >>>> http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.b… >>>> >>>> I was able to detect one blob in your image with the default threshold >>>> value. See: >>>> >>>> https://gist.github.com/vighneshbirodkar/c16515126e648cf92f08d3319d3a023e >>>> >>>> Find the result attached. >>>> >>>> Thanks >>>> Vighnesh >>>> >>>> On Saturday, April 30, 2016 at 2:02:51 AM UTC-4, Raphael wrote: >>>> >>>>> hi folks, >>>>> >>>>> Got a problem removing dust and identifying blobs/crytals. Kindly >>>>> see my code below >>>>> >>>>> >>>>> from __future__ import division, print_function >>>>> import matplotlib.pyplot as plt >>>>> import numpy as np >>>>> from skimage import io, feature, color, measure, draw, img_as_float, >>>>> exposure >>>>> from skimage.filters.rank import median >>>>> from skimage.feature import blob_dog, blob_log, blob_doh >>>>> from skimage.morphology import disk >>>>> >>>>> #raw image >>>>> image_raw = >>>>> img_as_float((io.imread('/home/raphael/Documents/ScikitImage/Run >>>>> 4-2_00061cropped.tif'))) (RawImage.tif attached) >>>>> plt.imshow(image_raw) >>>>> >>>>> #converted to grayscale >>>>> >>>>> img_gray = >>>>> color.rgb2gray(io.imread('/home/raphael/Documents/ScikitImage/Run >>>>> 4-2_00061cropped.tif')) >>>>> plt.imshow(image_gray) >>>>> >>>>> >>>>> #applied median filter to take out small dust particles. But the big >>>>> dust particle on the top right corner still persists (see median1.png >>>>> attached) >>>>> img_filtered=median(img_gray,disk(10)) >>>>> plt.imshow(img_filtered) >>>>> >>>>> >>>>> #applied adapthist to make image more clearer (see adaptive.png) >>>>> >>>>> img_equalized=exposure.equalize_adapthist(img_filtered) >>>>> plt.imshow(img_equalized) >>>>> >>>>> #trying to detect the crystals/blobs. I followed the example here >>>>> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob… >>>>> But this gave an error. matplotlib was not happy with the data type >>>>> blobs_doh = blob_doh(img_equalized, max_sigma=30, threshold=.1) >>>>> plt.imshow(blobs_doh) >>>>> >>>>> My problems are: >>>>> >>>>> 1. I could not get the dust particle out especially the really big one >>>>> on the top right. How can I get it out? >>>>> >>>>> 2. I could not detect the crystals/blobs in the image using blob_doh >>>>> >>>>> Any ideas/suggestions is highly appreciated. Thank you! >>>>> >>>> -- >>>> You received this message because you are subscribed to a topic in the >>>> Google Groups "scikit-image" group. >>>> To unsubscribe from this topic, visit >>>> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. >>>> To unsubscribe from this group and all its topics, send an email to >>>> scikit-image...(a)googlegroups.com. >>>> To post to this group, send email to scikit...(a)googlegroups.com. >>>> To view this discussion on the web, visit >>>> https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d… >>>> <https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d…> >>>> . >>>> >>>> For more options, visit https://groups.google.com/d/optout. >>>> >>> >>> -- >> You received this message because you are subscribed to a topic in the >> Google Groups "scikit-image" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. >> To unsubscribe from this group and all its topics, send an email to >> scikit-image+unsubscribe(a)googlegroups.com. >> To post to this group, send email to scikit-image(a)googlegroups.com. >> To view this discussion on the web, visit >> https://groups.google.com/d/msgid/scikit-image/b9ede614-1c9d-4a22-a681-fab4… >> <https://groups.google.com/d/msgid/scikit-image/b9ede614-1c9d-4a22-a681-fab4…> >> . >> >> For more options, visit https://groups.google.com/d/optout. >> > > -- > You received this message because you are subscribed to a topic in the > Google Groups "scikit-image" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > scikit-image+unsubscribe(a)googlegroups.com. > To post to this group, send email to scikit-image(a)googlegroups.com. > To view this discussion on the web, visit > https://groups.google.com/d/msgid/scikit-image/CAFCvXeMTH9ke7Cv%3DucywhtaWP… > <https://groups.google.com/d/msgid/scikit-image/CAFCvXeMTH9ke7Cv%3DucywhtaWP…> > . > > For more options, visit https://groups.google.com/d/optout. >

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Re: dev version installation
by Raphael Okoye 02 May '16

02 May '16

hi all, I need help with installation of the latest version of scikit image(the version I have is 0.11.3 kindly find attached). I currently run Ubuntu 14.04 LTS. I'm not sure if sudo apt-get build-dep python-scikit-image is the way to go. Any guidance will be highly appreciated. Thank you. Raphael On Tuesday, 2 February 2016 14:11:46 UTC-8, stefanv wrote: > > On 2 February 2016 at 13:21, Simone Codeluppi <sim...(a)codeluppi.org > <javascript:>> wrote: > > from $ git log HEAD^... I get: > > > This output is a bit strange, so perhaps try: > > $ git checkout master > $ git fetch > $ git reset --hard origin/master > > Stéfan >

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Re: blob detection and dust removal
by Vighnesh Birodkar 02 May '16

02 May '16

Hi That really depends on your application. What's your motivation for removing these dust particles ? How are these images going to be processed further ? Thanks Vighnesh On Monday, May 2, 2016 at 12:13:27 AM UTC-4, Raphael wrote: > > hi Vighnesh, > > Thanks a bunch!! I see my error now. > > Actually that blob you detected a dust particle. Which operation would > you suggest to erase it? I tried morphological erosion but it doesn't take > it away. > > Thanks > Raphael > > On 1 May 2016 at 18:27, Vighnesh Birodkar <vighnesh...(a)gmail.com > <javascript:>> wrote: > >> Hello Raphael >> >> The error here is because the output of blob_doh in a numpy array of >> blobs, it is not an image meant for display. If you notice the example the >> blobs are being drawn separately inside the for loop. If no blobs are being >> detected, you can adjust the threshold. Lowering the threshold will make >> the function detect more blobs. It is clarified futher in the documentation >> >> http://scikit-image.org/docs/dev/api/skimage.feature.html#skimage.feature.b… >> >> I was able to detect one blob in your image with the default threshold >> value. See: >> https://gist.github.com/vighneshbirodkar/c16515126e648cf92f08d3319d3a023e >> >> Find the result attached. >> >> Thanks >> Vighnesh >> >> On Saturday, April 30, 2016 at 2:02:51 AM UTC-4, Raphael wrote: >> >>> hi folks, >>> >>> Got a problem removing dust and identifying blobs/crytals. Kindly see >>> my code below >>> >>> >>> from __future__ import division, print_function >>> import matplotlib.pyplot as plt >>> import numpy as np >>> from skimage import io, feature, color, measure, draw, img_as_float, >>> exposure >>> from skimage.filters.rank import median >>> from skimage.feature import blob_dog, blob_log, blob_doh >>> from skimage.morphology import disk >>> >>> #raw image >>> image_raw = >>> img_as_float((io.imread('/home/raphael/Documents/ScikitImage/Run >>> 4-2_00061cropped.tif'))) (RawImage.tif attached) >>> plt.imshow(image_raw) >>> >>> #converted to grayscale >>> >>> img_gray = >>> color.rgb2gray(io.imread('/home/raphael/Documents/ScikitImage/Run >>> 4-2_00061cropped.tif')) >>> plt.imshow(image_gray) >>> >>> >>> #applied median filter to take out small dust particles. But the big >>> dust particle on the top right corner still persists (see median1.png >>> attached) >>> img_filtered=median(img_gray,disk(10)) >>> plt.imshow(img_filtered) >>> >>> >>> #applied adapthist to make image more clearer (see adaptive.png) >>> >>> img_equalized=exposure.equalize_adapthist(img_filtered) >>> plt.imshow(img_equalized) >>> >>> #trying to detect the crystals/blobs. I followed the example here >>> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob… >>> But this gave an error. matplotlib was not happy with the data type >>> blobs_doh = blob_doh(img_equalized, max_sigma=30, threshold=.1) >>> plt.imshow(blobs_doh) >>> >>> My problems are: >>> >>> 1. I could not get the dust particle out especially the really big one >>> on the top right. How can I get it out? >>> >>> 2. I could not detect the crystals/blobs in the image using blob_doh >>> >>> Any ideas/suggestions is highly appreciated. Thank you! >>> >> -- >> You received this message because you are subscribed to a topic in the >> Google Groups "scikit-image" group. >> To unsubscribe from this topic, visit >> https://groups.google.com/d/topic/scikit-image/VtkzL9ZCY6Q/unsubscribe. >> To unsubscribe from this group and all its topics, send an email to >> scikit-image...(a)googlegroups.com <javascript:>. >> To post to this group, send email to scikit...(a)googlegroups.com >> <javascript:>. >> To view this discussion on the web, visit >> https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d… >> <https://groups.google.com/d/msgid/scikit-image/0fd22d80-4549-470f-b61b-f48d…> >> . >> >> For more options, visit https://groups.google.com/d/optout. >> > >

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blob detection and dust removal
by Raphael 01 May '16

01 May '16

hi folks, Got a problem removing dust and identifying blobs/crytals. Kindly see my code below from __future__ import division, print_function import matplotlib.pyplot as plt import numpy as np from skimage import io, feature, color, measure, draw, img_as_float, exposure from skimage.filters.rank import median from skimage.feature import blob_dog, blob_log, blob_doh from skimage.morphology import disk #raw image image_raw = img_as_float((io.imread('/home/raphael/Documents/ScikitImage/Run 4-2_00061cropped.tif'))) (RawImage.tif attached) plt.imshow(image_raw) #converted to grayscale img_gray = color.rgb2gray(io.imread('/home/raphael/Documents/ScikitImage/Run 4-2_00061cropped.tif')) plt.imshow(image_gray) #applied median filter to take out small dust particles. But the big dust particle on the top right corner still persists (see median1.png attached) img_filtered=median(img_gray,disk(10)) plt.imshow(img_filtered) #applied adapthist to make image more clearer (see adaptive.png) img_equalized=exposure.equalize_adapthist(img_filtered) plt.imshow(img_equalized) #trying to detect the crystals/blobs. I followed the example here http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob… But this gave an error. matplotlib was not happy with the data type blobs_doh = blob_doh(img_equalized, max_sigma=30, threshold=.1) plt.imshow(blobs_doh) My problems are: 1. I could not get the dust particle out especially the really big one on the top right. How can I get it out? 2. I could not detect the crystals/blobs in the image using blob_doh Any ideas/suggestions is highly appreciated. Thank you!

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Re: Please share your use cases
by Robin Wilson 01 May '16

01 May '16

If you'd like another example, then I've used scikit-image for processing satellite images to retrieve high-resolution maps of air pollution. I developed the method to do this during my PhD, and it uses scikit-image for most of the image processing parts of it, which involve edge-detection and segmentation, plus a number of more generic image processing tasks. If you'd like more details then feel free to contact me off-list, Robin On Sunday, 1 May 2016 08:14:10 UTC+1, Nadav Horesh wrote: > > My company (Visionsense) make stereoscopic medical video cameras for > endoscopic surgeries. I use a mix of opencv and scikit-image functions to > test and tune the image processing pipeline. Attached here a snapshot of a > utility I built for this purpose based on skimage widgets and plugins. As a > no-programmer, these tools are much more accessible and tailored to my > needs than the Qt widgets, and the line-profile tool is invaluable image > exploration tool. > > Nadav. > > 2016-04-13 20:49 GMT+03:00 Stéfan van der Walt <ste...(a)berkeley.edu > <javascript:>>: > >> Hi, everyone >> >> I am giving a talk on scikit-image soon, and would like to highlight how >> it is being used in practice. >> >> Please share your own applications with links to images or plots, or let >> me know if you spot someone else doing something cool! >> >> Thanks, >> Stéfan >> >> -- >> You received this message because you are subscribed to the Google Groups >> "scikit-image" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to scikit-image...(a)googlegroups.com <javascript:>. >> To post to this group, send email to scikit...(a)googlegroups.com >> <javascript:>. >> To view this discussion on the web, visit >> https://groups.google.com/d/msgid/scikit-image/CABDkGQkQgf7sGpd0agAReX5MHiN… >> <https://groups.google.com/d/msgid/scikit-image/CABDkGQkQgf7sGpd0agAReX5MHiN…> >> . >> For more options, visit https://groups.google.com/d/optout. >> > >

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Re: Please share your use cases
by Nadav Horesh 01 May '16

01 May '16

My company (Visionsense) make stereoscopic medical video cameras for endoscopic surgeries. I use a mix of opencv and scikit-image functions to test and tune the image processing pipeline. Attached here a snapshot of a utility I built for this purpose based on skimage widgets and plugins. As a no-programmer, these tools are much more accessible and tailored to my needs than the Qt widgets, and the line-profile tool is invaluable image exploration tool. Nadav. 2016-04-13 20:49 GMT+03:00 Stéfan van der Walt <stefanv(a)berkeley.edu>: > Hi, everyone > > I am giving a talk on scikit-image soon, and would like to highlight how > it is being used in practice. > > Please share your own applications with links to images or plots, or let > me know if you spot someone else doing something cool! > > Thanks, > Stéfan > > -- > You received this message because you are subscribed to the Google Groups > "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to scikit-image+unsubscribe(a)googlegroups.com. > To post to this group, send email to scikit-image(a)googlegroups.com. > To view this discussion on the web, visit > https://groups.google.com/d/msgid/scikit-image/CABDkGQkQgf7sGpd0agAReX5MHiN… > <https://groups.google.com/d/msgid/scikit-image/CABDkGQkQgf7sGpd0agAReX5MHiN…> > . > For more options, visit https://groups.google.com/d/optout. >

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