For what it's worth, I strongly support the statement, and would prefer to
drop 2.7 support much earlier. This does *not* mean ignoring people
submitting 2.7 bug reports. It means that, like Python itself, *new*
versions would not support Py2.7. Bug fixes would be ported to e.g. the
0.13.x branch.
Yes from me.
On Wed, Jul 13, 2016 at 1:25 AM, Stéfan van der Walt
wrote:
> Hi, everyone
>
> Currently, our tutorial repo has no license. Everyone who has
> contributed, is it OK if I license it under CC-BY 4.0?
>
> Thanks!
> Stéfan
>
> --
> You received this message because you are subscribed t
@Emmanuelle I'm probably among the ones pushing hardest for this, and I can
tell you, I can't wait for this change in policy, and would be sorely
disappointed by having to work in an experimental branch of scikit-image.
Both @-matmul and keyword-only arguments are, imho, compelling reasons to
switc
Hi everyone,
First of all, I excitedly jumped on the bandwagon because Stefan mentioned
0.13, but I actually even I considered that a bit early for dropping Py2
when I read it. =) I would say that the right time to drop Py2 is either
0.15 or 1.0, and that we should follow a standard deprecation cy
Hi everyone,
We've had a couple of community fails on GitHub recently:
https://github.com/scikit-image/scikit-image/pull/1474#issuecomment-241283056
https://github.com/scikit-image/scikit-image/issues/2080
(The last one is missing a presumably-deleted comment where someone outside
the project reco
Hi Nadav,
Have a look at the filters lesson in github.com/scikit-image/skimage-tutorials.
It's not a "real" image processing application, but rather an illustration, but
it should be enough of a template for you to modify it.
Juan.
On 30 Aug 2016, 7:08 PM +1000, Nadav Horesh , wrote:
>
> I am
> This way your PRs are always checked against the latest master, not
whatever was around when they were first made
I thought Travis did this already?
https://docs.travis-ci.com/user/pull-requests
"Rather than test the commits that have been pushed to the branch the pull
request is from, we test
Yes, crazy timing! =D
On 15 September 2016 at 9:08:59 AM, Stefan van der Walt (
stef...@berkeley.edu) wrote:
On Mon, Aug 29, 2016, at 13:17, Stefan van der Walt wrote:
> I have some ideas around (1) that need fleshing out, but in the mean
> time I was looking at http://zube.io to address part o
Hi Ioannis,
Unfortunately the levels keyword is used as a hint to the function about
the number of levels when the image is uint16, because the possible number
of levels is huge. But if you want to convert the image to those levels,
you have to do it manually. I suggest you look at the "rescale_in
Hi Lluis,
We don't have a built-in function, but it should be relatively easy to
build this using:
scipy.ndimage.distance_transform:
http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.distance_transform_edt.html#scipy.ndimage.distance_transform_edt
skimage.morphology.watershed:
htt
Hi Dipu,
1. I assume you mean Jython. Most of the SciPy stack is not available for
Jython, unless things have changed dramatically since I last looked at it…
2. I am not aware of a document translating between scikit-image and
openCV. I suspect there is substantial non-overlap. Python bindings fo
Emma, you should try reading him Stéfan's letter as a lullaby, maybe it
will calm him down and it'll give you more time to work on scikit-image! =P
On 23 September 2016 at 4:17:38 am, Emmanuelle Gouillart (
emmanuelle.gouill...@nsup.org) wrote:
Dear Stéfan,
thanks for the initiative!
My "empl
Hi Parul,
Sorry for the silence! Sometimes we are busy and these PRs fall through the
cracks.
I'm doing a quick review of your code right now but I don't see any
questions regarding parameters on the issue itself?
For the gallery example, whatever code you used to apply the method to
`data.astro
Hi Jean-Patrick,
Why do you need to load everything into RAM to resize it? This a perfect
use-case for streaming data processing. Have a look at my notebook from
EuroSciPy 2015 for some examples:
https://github.com/jni/streaming-talk/blob/master/Big%20data%20in%20little%20laptop.ipynb
Specificall
ing to find a solution but if you have an idea on how to solve
> this problem, please tell me
>
> Thank you in advance
> Ioannis
>
>
>
> On Monday, 19 September 2016 15:41:07 UTC+1, ioannis...@gmail.com wrote:
>>
>> Thank you very much Juan for your quick reply.
Hi Jaime,
Sorry, it seems your message got lost in our flooded inboxes...
What does your source image look like? If the objects are segmented into
different labels, that is, you have an image where all the pixels of object
1 have value 1, all those of object 2 have value 2, etc., then you can
bui
er.
>
> Any other idea?
>
> Thanks, Jaime
>
>
>
> On Saturday, October 1, 2016 at 9:48:07 PM UTC-5, Juan Nunez-Iglesias
> wrote:
>
> Hi Jaime,
>
> Sorry, it seems your message got lost in our flooded inboxes...
>
> What does your source image look like? If the o
I would do something along these lines:
frames = []
for contour_id, contour in enumerate(contours):
current_frame = pd.DataFrame(contour, columns={'row', 'column'})
current_frame['contour'] = contour_id # creates column with
repeated valueframes.append(current_frame)
full_data =
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