From siqueiraaf at gmail.com  Wed Nov  9 09:56:07 2016
From: siqueiraaf at gmail.com (Alexandre Fioravante de Siqueira)
Date: Wed, 9 Nov 2016 15:56:07 +0100
Subject: [scikit-image] Fitting figures with missing parts
Message-ID: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>

Dear all,
I have these contours from the same object. However, there was another
object over it. Its contour was divided, and I don't have the "center" part.
I'd like to use a tool and show that they're belong to the same part. I was
trying to use an ellipse to do that, but the results are really bad.
Could you help me with that? I appreciate any idea.
Thank you very much!
Kind regards,

Alex

-- 
------------------------------------------------------------------------------
Dr. Alexandre 'Jaguar' Fioravante de Siqueira
Office 306 - Institut f?r Geologie
Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
Technische Universit?t Bergakademie Freiberg
Bernhard-von-Cotta-Stra?e, 2
Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
Personal site: http://www.programandociencia.com/about/
Github: http://www.github.com/alexandrejaguar/
Skype: alexandrejaguar
Twitter: http://www.twitter.com/alexdesiqueira/
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From hellomurasaki at gmail.com  Thu Nov 10 08:54:44 2016
From: hellomurasaki at gmail.com (Viji C)
Date: Thu, 10 Nov 2016 19:24:44 +0530
Subject: [scikit-image]  Fitting figures with missing parts
In-Reply-To: <CANjPQS7sAUzQ=eRY=TPpiU+TvhtdEsGOt_hAuwSxFnszBWNL7g@mail.gmail.com>
References: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
 <CANjPQS7sAUzQ=eRY=TPpiU+TvhtdEsGOt_hAuwSxFnszBWNL7g@mail.gmail.com>
Message-ID: <CANjPQS5_9Cn6E9ZzqOs_q5AnpBqT6x0Twp2fpXYY00EzwW4rGQ@mail.gmail.com>

---------- Forwarded message ----------
From: *Viji C* <hellomurasaki at gmail.com
<javascript:_e(%7B%7D,'cvml','hellomurasaki at gmail.com');>>
Date: Thursday, November 10, 2016
Subject: [scikit-image] Fitting figures with missing parts
To: Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com
<javascript:_e(%7B%7D,'cvml','siqueiraaf at gmail.com');>>


Hello Mr. Alex,

Please try Fractal Analysis. I couldn't understand the morphology of the
contours exactly from your mail. But if the contours are self similar, then
Fractals can help you. FracLac is one of tool for Fractal Analysis.

I'm newbie to Vision Research. Kindly get suggestions from experts before
proceeding to implement Fractals.

Regards,
C.Viji



On Wednesday, November 9, 2016, Alexandre Fioravante de Siqueira <
siqueiraaf at gmail.com> wrote:

> Dear all,
> I have these contours from the same object. However, there was another
> object over it. Its contour was divided, and I don't have the "center" part.
> I'd like to use a tool and show that they're belong to the same part. I
> was trying to use an ellipse to do that, but the results are really bad.
> Could you help me with that? I appreciate any idea.
> Thank you very much!
> Kind regards,
>
> Alex
>
> --
> ------------------------------------------------------------
> ------------------
> Dr. Alexandre 'Jaguar' Fioravante de Siqueira
> Office 306 - Institut f?r Geologie
> Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
> Technische Universit?t Bergakademie Freiberg
> Bernhard-von-Cotta-Stra?e, 2
> Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
> Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
> Personal site: http://www.programandociencia.com/about/
> Github: http://www.github.com/alexandrejaguar/
> Skype: alexandrejaguar
> Twitter: http://www.twitter.com/alexdesiqueira/
> ------------------------------------------------------------
> ------------------
>
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From kevin.keraudren at googlemail.com  Thu Nov 10 09:51:23 2016
From: kevin.keraudren at googlemail.com (Kevin Keraudren)
Date: Thu, 10 Nov 2016 14:51:23 +0000
Subject: [scikit-image] Fitting figures with missing parts
In-Reply-To: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
References: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
Message-ID: <CADe6jSrHccuL+ZRsn41hxLETfvck_85xu_3BAxAF8-BJr9cSXA@mail.gmail.com>

Hi Alex,

Why not use the Hough transform to detect lines as in
http://scikit-image.org/docs/dev/auto_examples/plot_
line_hough_transform.html ?

See adapted code and output attached.

Kevin

On Wed, Nov 9, 2016 at 2:56 PM, Alexandre Fioravante de Siqueira <
siqueiraaf at gmail.com> wrote:

> Dear all,
> I have these contours from the same object. However, there was another
> object over it. Its contour was divided, and I don't have the "center" part.
> I'd like to use a tool and show that they're belong to the same part. I
> was trying to use an ellipse to do that, but the results are really bad.
> Could you help me with that? I appreciate any idea.
> Thank you very much!
> Kind regards,
>
> Alex
>
> --
> ------------------------------------------------------------
> ------------------
> Dr. Alexandre 'Jaguar' Fioravante de Siqueira
> Office 306 - Institut f?r Geologie
> Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
> Technische Universit?t Bergakademie Freiberg
> Bernhard-von-Cotta-Stra?e, 2
> Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
> Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
> Personal site: http://www.programandociencia.com/about/
> Github: http://www.github.com/alexandrejaguar/
> Skype: alexandrejaguar
> Twitter: http://www.twitter.com/alexdesiqueira/
> ------------------------------------------------------------
> ------------------
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>
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From jeanpatrick.pommier at gmail.com  Thu Nov 10 11:47:40 2016
From: jeanpatrick.pommier at gmail.com (Jean-Patrick Pommier)
Date: Thu, 10 Nov 2016 17:47:40 +0100
Subject: [scikit-image] Fitting figures with missing parts
In-Reply-To: <CANjPQS5_9Cn6E9ZzqOs_q5AnpBqT6x0Twp2fpXYY00EzwW4rGQ@mail.gmail.com>
References: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
 <CANjPQS7sAUzQ=eRY=TPpiU+TvhtdEsGOt_hAuwSxFnszBWNL7g@mail.gmail.com>
 <CANjPQS5_9Cn6E9ZzqOs_q5AnpBqT6x0Twp2fpXYY00EzwW4rGQ@mail.gmail.com>
Message-ID: <CAJHHrbsmzeXuMnrZv9iPwwU1Pu1qvY09nWxkKu1=pqHP8qMD3A@mail.gmail.com>

The attached notebook proposes a solution

2016-11-10 14:54 GMT+01:00 Viji C <hellomurasaki at gmail.com>:

>
>
> ---------- Forwarded message ----------
> From: *Viji C* <hellomurasaki at gmail.com>
> Date: Thursday, November 10, 2016
> Subject: [scikit-image] Fitting figures with missing parts
> To: Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com>
>
>
> Hello Mr. Alex,
>
> Please try Fractal Analysis. I couldn't understand the morphology of the
> contours exactly from your mail. But if the contours are self similar, then
> Fractals can help you. FracLac is one of tool for Fractal Analysis.
>
> I'm newbie to Vision Research. Kindly get suggestions from experts before
> proceeding to implement Fractals.
>
> Regards,
> C.Viji
>
>
>
> On Wednesday, November 9, 2016, Alexandre Fioravante de Siqueira <
> siqueiraaf at gmail.com> wrote:
>
>> Dear all,
>> I have these contours from the same object. However, there was another
>> object over it. Its contour was divided, and I don't have the "center" part.
>> I'd like to use a tool and show that they're belong to the same part. I
>> was trying to use an ellipse to do that, but the results are really bad.
>> Could you help me with that? I appreciate any idea.
>> Thank you very much!
>> Kind regards,
>>
>> Alex
>>
>> --
>> ------------------------------------------------------------
>> ------------------
>> Dr. Alexandre 'Jaguar' Fioravante de Siqueira
>> Office 306 - Institut f?r Geologie
>> Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
>> Technische Universit?t Bergakademie Freiberg
>> Bernhard-von-Cotta-Stra?e, 2
>> Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
>> Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
>> Personal site: http://www.programandociencia.com/about/
>> Github: http://www.github.com/alexandrejaguar/
>> Skype: alexandrejaguar
>> Twitter: http://www.twitter.com/alexdesiqueira/
>> ------------------------------------------------------------
>> ------------------
>>
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>


-- 
http://dip4fish.blogspot.fr/
Dedicated to Digital Image Processing for FISH, QFISH and other things
about the telomeres.
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From jeanpatrick.pommier at gmail.com  Thu Nov 10 11:49:34 2016
From: jeanpatrick.pommier at gmail.com (Jean-Patrick Pommier)
Date: Thu, 10 Nov 2016 17:49:34 +0100
Subject: [scikit-image] Fitting figures with missing parts
In-Reply-To: <CAJHHrbsmzeXuMnrZv9iPwwU1Pu1qvY09nWxkKu1=pqHP8qMD3A@mail.gmail.com>
References: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
 <CANjPQS7sAUzQ=eRY=TPpiU+TvhtdEsGOt_hAuwSxFnszBWNL7g@mail.gmail.com>
 <CANjPQS5_9Cn6E9ZzqOs_q5AnpBqT6x0Twp2fpXYY00EzwW4rGQ@mail.gmail.com>
 <CAJHHrbsmzeXuMnrZv9iPwwU1Pu1qvY09nWxkKu1=pqHP8qMD3A@mail.gmail.com>
Message-ID: <CAJHHrbthuaXQ-S3oOJOvJ7Onu5gVU=YVv3s=6Hze2t6zEOOt8w@mail.gmail.com>

?the picture is in the previous notebook

2016-11-10 17:47 GMT+01:00 Jean-Patrick Pommier <
jeanpatrick.pommier at gmail.com>:

> The attached notebook proposes a solution
>
> 2016-11-10 14:54 GMT+01:00 Viji C <hellomurasaki at gmail.com>:
>
>>
>>
>> ---------- Forwarded message ----------
>> From: *Viji C* <hellomurasaki at gmail.com>
>> Date: Thursday, November 10, 2016
>> Subject: [scikit-image] Fitting figures with missing parts
>> To: Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com>
>>
>>
>> Hello Mr. Alex,
>>
>> Please try Fractal Analysis. I couldn't understand the morphology of the
>> contours exactly from your mail. But if the contours are self similar, then
>> Fractals can help you. FracLac is one of tool for Fractal Analysis.
>>
>> I'm newbie to Vision Research. Kindly get suggestions from experts before
>> proceeding to implement Fractals.
>>
>> Regards,
>> C.Viji
>>
>>
>>
>> On Wednesday, November 9, 2016, Alexandre Fioravante de Siqueira <
>> siqueiraaf at gmail.com> wrote:
>>
>>> Dear all,
>>> I have these contours from the same object. However, there was another
>>> object over it. Its contour was divided, and I don't have the "center" part.
>>> I'd like to use a tool and show that they're belong to the same part. I
>>> was trying to use an ellipse to do that, but the results are really bad.
>>> Could you help me with that? I appreciate any idea.
>>> Thank you very much!
>>> Kind regards,
>>>
>>> Alex
>>>
>>> --
>>> ------------------------------------------------------------
>>> ------------------
>>> Dr. Alexandre 'Jaguar' Fioravante de Siqueira
>>> Office 306 - Institut f?r Geologie
>>> Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
>>> Technische Universit?t Bergakademie Freiberg
>>> Bernhard-von-Cotta-Stra?e, 2
>>> Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
>>> Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
>>> Personal site: http://www.programandociencia.com/about/
>>> Github: http://www.github.com/alexandrejaguar/
>>> Skype: alexandrejaguar
>>> Twitter: http://www.twitter.com/alexdesiqueira/
>>> ------------------------------------------------------------
>>> ------------------
>>>
>>
>>
>> _______________________________________________
>> scikit-image mailing list
>> scikit-image at python.org
>> https://mail.python.org/mailman/listinfo/scikit-image
>>
>>
>
>
> --
> http://dip4fish.blogspot.fr/
> Dedicated to Digital Image Processing for FISH, QFISH and other things
> about the telomeres.
>



-- 
http://dip4fish.blogspot.fr/
Dedicated to Digital Image Processing for FISH, QFISH and other things
about the telomeres.
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From jiri.borovec at fel.cvut.cz  Sun Nov 13 10:51:15 2016
From: jiri.borovec at fel.cvut.cz (=?UTF-8?B?SmnFmcOtIEJvcm92ZWM=?=)
Date: Sun, 13 Nov 2016 16:51:15 +0100
Subject: [scikit-image] BPDL in skimage?
In-Reply-To: <1476209251.998616.752709505.31E31A16@webmail.messagingengine.com>
References: <CAGFatNhyf5trG4rKFmoNs8a-Oq1f1z+nSs218WN0euGTOPoXxg@mail.gmail.com>
 <1476209251.998616.752709505.31E31A16@webmail.messagingengine.com>
Message-ID: <CAGFatNhD+iFw2oL53iDw_DnNgHJ9Qu1Ti8usHQF6Q6tERa6YAQ@mail.gmail.com>

Ok, it means wait until it will be generally proved that it is useful
method, correct?

--
Best regards, Jiri Borovec
------------------------------------------------------------------------
Ing. Jiri Borovec, MSc  <jiri.borovec at fel.cvut.cz>
PhD student at CMP CTU, http://cmp.felk.cvut.cz/~borovji3

On 11 October 2016 at 20:07, Stefan van der Walt <stefanv at berkeley.edu>
wrote:

> Hi Jiri
>
> On Mon, Oct 10, 2016, at 04:42, Ji?? Borovec wrote:
>
> recently we made a new method Binary Pattern Dictionary learning for
> estimation an atlas from set of binary images where we detect and decompose
> frequent patterns in the image set, see paper in attachment. I was
> wondering if you are interested to have this method as contribution to the
> scikit-image library?
>
>
> We typically wait a while for papers to gain popularity before we
> implement them in scikit-image.
>
> That said, I think it's an excellent idea to make the code available with
> proper licensing and documentation until such time that we can include it.
>
> Best regards
> St?fan
>
>
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From stefanv at berkeley.edu  Sun Nov 13 11:30:03 2016
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Sun, 13 Nov 2016 08:30:03 -0800
Subject: [scikit-image] BPDL in skimage?
In-Reply-To: <CAGFatNhD+iFw2oL53iDw_DnNgHJ9Qu1Ti8usHQF6Q6tERa6YAQ@mail.gmail.com>
References: <CAGFatNhyf5trG4rKFmoNs8a-Oq1f1z+nSs218WN0euGTOPoXxg@mail.gmail.com>
 <1476209251.998616.752709505.31E31A16@webmail.messagingengine.com>
 <CAGFatNhD+iFw2oL53iDw_DnNgHJ9Qu1Ti8usHQF6Q6tERa6YAQ@mail.gmail.com>
Message-ID: <1479054603.1661771.786254929.27BD7882@webmail.messagingengine.com>

Hi Jiri

On Sun, Nov 13, 2016, at 07:51, Ji?? Borovec wrote:
> Ok, it means wait until it will be generally proved that it is useful
> method, correct?

Yes, that's our approach in general.  But, as mentioned before, it's so
easy to publish a package on pypi now that there's no reason to get the
code out into the hands of others already.  And you should feel free to
post announcements related to the package on this list.

Best regards
St?fan
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From luecks at gmail.com  Mon Nov 14 04:20:47 2016
From: luecks at gmail.com (=?UTF-8?Q?Stefanie_L=C3=BCck?=)
Date: Mon, 14 Nov 2016 10:20:47 +0100
Subject: [scikit-image] statistical region merging
Message-ID: <CAHvaZnbMfMeWHgM30dkABoGMePOcLGK_BLZ_66Qxu_JS1cvqjg@mail.gmail.com>

Hi!

I am looking for a statistical region merging segmentation. Is there
anything like this in skimage?

Thanks in advance,
Stefanie
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From siqueiraaf at gmail.com  Mon Nov 14 14:38:53 2016
From: siqueiraaf at gmail.com (Alexandre Fioravante de Siqueira)
Date: Mon, 14 Nov 2016 20:38:53 +0100
Subject: [scikit-image] Fitting figures with missing parts
In-Reply-To: <CAJHHrbthuaXQ-S3oOJOvJ7Onu5gVU=YVv3s=6Hze2t6zEOOt8w@mail.gmail.com>
References: <CANPz1oYKtFtAq9TRtHzqZbWLb-XX+rZvb=U8GpUmuuF1_FVvXw@mail.gmail.com>
 <CANjPQS7sAUzQ=eRY=TPpiU+TvhtdEsGOt_hAuwSxFnszBWNL7g@mail.gmail.com>
 <CANjPQS5_9Cn6E9ZzqOs_q5AnpBqT6x0Twp2fpXYY00EzwW4rGQ@mail.gmail.com>
 <CAJHHrbsmzeXuMnrZv9iPwwU1Pu1qvY09nWxkKu1=pqHP8qMD3A@mail.gmail.com>
 <CAJHHrbthuaXQ-S3oOJOvJ7Onu5gVU=YVv3s=6Hze2t6zEOOt8w@mail.gmail.com>
Message-ID: <CANPz1oZ4FopAxUTSHduO98LN5sMBDbWVVn5bVU0ndTE9PGUdbw@mail.gmail.com>

Dear Jean, Viji and Kevin,
thank you very much for your proposed solutions! Kevin's solution looks
nice, although Jean's one is very good too.
I'll try to apply them on my problem this week. After that I return to
contact you with the results.
Thanks again for your support,

Alex

2016-11-10 17:49 GMT+01:00 Jean-Patrick Pommier <
jeanpatrick.pommier at gmail.com>:

>
> ?the picture is in the previous notebook
>
> 2016-11-10 17:47 GMT+01:00 Jean-Patrick Pommier <
> jeanpatrick.pommier at gmail.com>:
>
>> The attached notebook proposes a solution
>>
>> 2016-11-10 14:54 GMT+01:00 Viji C <hellomurasaki at gmail.com>:
>>
>>>
>>>
>>> ---------- Forwarded message ----------
>>> From: *Viji C* <hellomurasaki at gmail.com>
>>> Date: Thursday, November 10, 2016
>>> Subject: [scikit-image] Fitting figures with missing parts
>>> To: Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com>
>>>
>>>
>>> Hello Mr. Alex,
>>>
>>> Please try Fractal Analysis. I couldn't understand the morphology of the
>>> contours exactly from your mail. But if the contours are self similar, then
>>> Fractals can help you. FracLac is one of tool for Fractal Analysis.
>>>
>>> I'm newbie to Vision Research. Kindly get suggestions from experts
>>> before proceeding to implement Fractals.
>>>
>>> Regards,
>>> C.Viji
>>>
>>>
>>>
>>> On Wednesday, November 9, 2016, Alexandre Fioravante de Siqueira <
>>> siqueiraaf at gmail.com> wrote:
>>>
>>>> Dear all,
>>>> I have these contours from the same object. However, there was another
>>>> object over it. Its contour was divided, and I don't have the "center" part.
>>>> I'd like to use a tool and show that they're belong to the same part. I
>>>> was trying to use an ellipse to do that, but the results are really bad.
>>>> Could you help me with that? I appreciate any idea.
>>>> Thank you very much!
>>>> Kind regards,
>>>>
>>>> Alex
>>>>
>>>> --
>>>> ------------------------------------------------------------
>>>> ------------------
>>>> Dr. Alexandre 'Jaguar' Fioravante de Siqueira
>>>> Office 306 - Institut f?r Geologie
>>>> Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
>>>> Technische Universit?t Bergakademie Freiberg
>>>> Bernhard-von-Cotta-Stra?e, 2
>>>> Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
>>>> Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
>>>> Personal site: http://www.programandociencia.com/about/
>>>> Github: http://www.github.com/alexandrejaguar/
>>>> Skype: alexandrejaguar
>>>> Twitter: http://www.twitter.com/alexdesiqueira/
>>>> ------------------------------------------------------------
>>>> ------------------
>>>>
>>>
>>>
>>> _______________________________________________
>>> scikit-image mailing list
>>> scikit-image at python.org
>>> https://mail.python.org/mailman/listinfo/scikit-image
>>>
>>>
>>
>>
>> --
>> http://dip4fish.blogspot.fr/
>> Dedicated to Digital Image Processing for FISH, QFISH and other things
>> about the telomeres.
>>
>
>
>
> --
> http://dip4fish.blogspot.fr/
> Dedicated to Digital Image Processing for FISH, QFISH and other things
> about the telomeres.
>



-- 
------------------------------------------------------------------------------
Dr. Alexandre 'Jaguar' Fioravante de Siqueira
Office 306 - Institut f?r Geologie
Fakult?t f?r Geowissenschaften, Geotechnik und Bergbau
Technische Universit?t Bergakademie Freiberg
Bernhard-von-Cotta-Stra?e, 2
Freiberg (09599), Mittelsachsen - Sachsen - Deutschland
Lattes curriculum: http://lattes.cnpq.br/3936721630855880/
Personal site: http://www.programandociencia.com/about/
Github: http://www.github.com/alexandrejaguar/
Skype: alexandrejaguar
Twitter: http://www.twitter.com/alexdesiqueira/
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From jni.soma at gmail.com  Mon Nov 14 19:51:01 2016
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Mon, 14 Nov 2016 19:51:01 -0500
Subject: [scikit-image] statistical region merging
In-Reply-To: <CAHvaZnb2QhUc7NaAWN7-0vU1HNRizoeYfcMy3+ia3SGqzPnUxA@mail.gmail.com>
References: <CAHvaZnbMfMeWHgM30dkABoGMePOcLGK_BLZ_66Qxu_JS1cvqjg@mail.gmail.com>
 <CA+JHcKQNBq1T60-ea_4t_CLN=s79kByeRu+GjPjcQ3GUPq5ffg@mail.gmail.com>
 <CAHvaZnb2QhUc7NaAWN7-0vU1HNRizoeYfcMy3+ia3SGqzPnUxA@mail.gmail.com>
Message-ID: <CA+JHcKQrU34h_Nbr--CfJUduFVMw9hLeNmamaTDHpkw_PcKGdQ@mail.gmail.com>

Hi Stefanie,

Sorry, these responses should all be CCd to the list, so that others can
benefit from the discussion ? my bad for dropping that thread. Could you
please:

- provide an example segmentation where skimage is doing worse than Fiji
- provide the script and parameter settings for both

Then we can help troubleshoot. I don?t know what you mean by the results
?were very strange?, for example, so it?s hard to diagnose the problem. =)

Starting to merge directly from pixels, as the Fiji plugin does, is
expensive and can be error prone. SLIC is a fast, initial pixel merging
step, from which we can merge regions according to various criteria.  With
the right parameters, SLIC + RAG mean color agglomeration should give quite
similar results to Fiji?s approach?

Juan.

On 15 November 2016 at 2:39:45 am, Stefanie L?ck (luecks at gmail.com) wrote:

Hi Juan,

thank you for your reply! I have seen and tested the RAG examples but I did
not understand the SLIC step and the results were very strange... Is there
any advantage? I am using SLIC anyway at the moment but the statistical
region merging of ImageJ gives me better results.

Thanks
Stefanie



2016-11-14 13:44 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:

> Hi Stefanie!
>
> Have a look at skimage.future.graph! There are some relevant examples in
> the gallery, too:
>
> http://scikit-image.org/docs/dev/auto_examples/#segmentation-of-objects
>
> The future.graph API is still experimental (that?s why it?s in ?future?),
> so we really appreciate any feedback you have about it!
>
> Juan.
>
>
>
> On 14 November 2016 at 8:21:12 pm, Stefanie L?ck (luecks at gmail.com) wrote:
>
> Hi!
>
> I am looking for a statistical region merging segmentation. Is there
> anything like this in skimage?
>
> Thanks in advance,
> Stefanie
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
>
>
-------------- next part --------------
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From luecks at gmail.com  Tue Nov 15 03:11:12 2016
From: luecks at gmail.com (=?UTF-8?Q?Stefanie_L=C3=BCck?=)
Date: Tue, 15 Nov 2016 09:11:12 +0100
Subject: [scikit-image] statistical region merging
In-Reply-To: <CA+JHcKQrU34h_Nbr--CfJUduFVMw9hLeNmamaTDHpkw_PcKGdQ@mail.gmail.com>
References: <CAHvaZnbMfMeWHgM30dkABoGMePOcLGK_BLZ_66Qxu_JS1cvqjg@mail.gmail.com>
 <CA+JHcKQNBq1T60-ea_4t_CLN=s79kByeRu+GjPjcQ3GUPq5ffg@mail.gmail.com>
 <CAHvaZnb2QhUc7NaAWN7-0vU1HNRizoeYfcMy3+ia3SGqzPnUxA@mail.gmail.com>
 <CA+JHcKQrU34h_Nbr--CfJUduFVMw9hLeNmamaTDHpkw_PcKGdQ@mail.gmail.com>
Message-ID: <CAHvaZnbVF0cJ88Y3Du9oZoODP3_o=zzEcsERWnSLRY-00u7JJA@mail.gmail.com>

Dear all,

sorry about the worse problem description! I tried this example
<http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_mean_color.html#sphx-glr-auto-examples-segmentation-plot-rag-mean-color-py>
with
different parameters for SLIC and graph.cut_threshold  but none of them
gave me satisfying results.

I attached the original image, the ImageJ SRM (Q=25) output and the RAG
output (segmentation.slic(img, compactness=20;
n_segments=400), graph.cut_threshold(labels1, g, 10))

The results are quite different, obviously I am doing something wrong. My
aim is to segment each leaf separately. At the moment I am
using felzenszwalb, which gives me quite reasonable results. However I
would like to try everything possible and therefore I would appreciate some
tips.

Thank you for the explanation of the algorithm, that was helpful.

Best regards,
Stefanie





2016-11-15 1:51 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:

> Hi Stefanie,
>
> Sorry, these responses should all be CCd to the list, so that others can
> benefit from the discussion ? my bad for dropping that thread. Could you
> please:
>
> - provide an example segmentation where skimage is doing worse than Fiji
> - provide the script and parameter settings for both
>
> Then we can help troubleshoot. I don?t know what you mean by the results
> ?were very strange?, for example, so it?s hard to diagnose the problem. =)
>
> Starting to merge directly from pixels, as the Fiji plugin does, is
> expensive and can be error prone. SLIC is a fast, initial pixel merging
> step, from which we can merge regions according to various criteria.  With
> the right parameters, SLIC + RAG mean color agglomeration should give quite
> similar results to Fiji?s approach?
>
> Juan.
>
> On 15 November 2016 at 2:39:45 am, Stefanie L?ck (luecks at gmail.com) wrote:
>
> Hi Juan,
>
> thank you for your reply! I have seen and tested the RAG examples but I
> did not understand the SLIC step and the results were very strange... Is
> there any advantage? I am using SLIC anyway at the moment but
> the statistical region merging of ImageJ gives me better results.
>
> Thanks
> Stefanie
>
>
>
> 2016-11-14 13:44 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:
>
>> Hi Stefanie!
>>
>> Have a look at skimage.future.graph! There are some relevant examples in
>> the gallery, too:
>>
>> http://scikit-image.org/docs/dev/auto_examples/#segmentation-of-objects
>>
>> The future.graph API is still experimental (that?s why it?s in ?future?),
>> so we really appreciate any feedback you have about it!
>>
>> Juan.
>>
>>
>>
>> On 14 November 2016 at 8:21:12 pm, Stefanie L?ck (luecks at gmail.com)
>> wrote:
>>
>> Hi!
>>
>> I am looking for a statistical region merging segmentation. Is there
>> anything like this in skimage?
>>
>> Thanks in advance,
>> Stefanie
>> _______________________________________________
>> scikit-image mailing list
>> scikit-image at python.org
>> https://mail.python.org/mailman/listinfo/scikit-image
>>
>>
>
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From jni.soma at gmail.com  Tue Nov 15 17:55:16 2016
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Tue, 15 Nov 2016 16:55:16 -0600
Subject: [scikit-image] statistical region merging
In-Reply-To: <CAHvaZnbVF0cJ88Y3Du9oZoODP3_o=zzEcsERWnSLRY-00u7JJA@mail.gmail.com>
References: <CAHvaZnbMfMeWHgM30dkABoGMePOcLGK_BLZ_66Qxu_JS1cvqjg@mail.gmail.com>
 <CA+JHcKQNBq1T60-ea_4t_CLN=s79kByeRu+GjPjcQ3GUPq5ffg@mail.gmail.com>
 <CAHvaZnb2QhUc7NaAWN7-0vU1HNRizoeYfcMy3+ia3SGqzPnUxA@mail.gmail.com>
 <CA+JHcKQrU34h_Nbr--CfJUduFVMw9hLeNmamaTDHpkw_PcKGdQ@mail.gmail.com>
 <CAHvaZnbVF0cJ88Y3Du9oZoODP3_o=zzEcsERWnSLRY-00u7JJA@mail.gmail.com>
Message-ID: <CA+JHcKQsvmo0YRVqCYeux8q6rE95C3+r7LY0=t9p+wZOFnnF+g@mail.gmail.com>

Hi Stefanie,

Wow, those results *do* look weird! =) Why are they not the same shape as
the image? Could you send us the complete code you used?

In the meantime, there's a few things to change. `cut_threshold` is
probably the single most fragile algorithm you can use with a RAG. You want
to be using merge_hierarchical. You can do this either on a "color graph",
which merges regions according to color similarity (and is most similar to
the statistical region merging of Fiji):
http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_merge.html#sphx-glr-auto-examples-segmentation-plot-rag-merge-py

or on a *boundary graph*, which first detects "edges" in the image and then
merges regions progressively according to the mean edge value:
http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_boundary.html#sphx-glr-auto-examples-segmentation-plot-rag-boundary-py

http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_boundary_merge.html#sphx-glr-auto-examples-segmentation-plot-boundary-merge-py

My intuition about this image is that your best choice is to use a sobel
filter:
http://scikit-image.org/docs/dev/auto_examples/edges/plot_edge_filter.html#sphx-glr-auto-examples-edges-plot-edge-filter-py
followed by compact watershed:
http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_compact_watershed.html#sphx-glr-auto-examples-segmentation-plot-compact-watershed-py
then by region boundary merging:
http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_boundary_merge.html#sphx-glr-auto-examples-segmentation-plot-boundary-merge-py

The edges look pretty sharp, too. You might even get good results with
Canny:
http://scikit-image.org/docs/dev/auto_examples/edges/plot_canny.html#sphx-glr-auto-examples-edges-plot-canny-py

I hope all this helps!

Juan.

On 15 November 2016 at 7:11:14 pm, Stefanie L?ck (luecks at gmail.com) wrote:

Dear all,

sorry about the worse problem description! I tried this example
<http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_mean_color.html#sphx-glr-auto-examples-segmentation-plot-rag-mean-color-py>
with
different parameters for SLIC and graph.cut_threshold  but none of them
gave me satisfying results.

I attached the original image, the ImageJ SRM (Q=25) output and the RAG
output (segmentation.slic(img, compactness=20;
n_segments=400), graph.cut_threshold(labels1, g, 10))

The results are quite different, obviously I am doing something wrong. My
aim is to segment each leaf separately. At the moment I am
using felzenszwalb, which gives me quite reasonable results. However I
would like to try everything possible and therefore I would appreciate some
tips.

Thank you for the explanation of the algorithm, that was helpful.

Best regards,
Stefanie





2016-11-15 1:51 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:

> Hi Stefanie,
>
> Sorry, these responses should all be CCd to the list, so that others can
> benefit from the discussion ? my bad for dropping that thread. Could you
> please:
>
> - provide an example segmentation where skimage is doing worse than Fiji
> - provide the script and parameter settings for both
>
> Then we can help troubleshoot. I don?t know what you mean by the results
> ?were very strange?, for example, so it?s hard to diagnose the problem. =)
>
> Starting to merge directly from pixels, as the Fiji plugin does, is
> expensive and can be error prone. SLIC is a fast, initial pixel merging
> step, from which we can merge regions according to various criteria.  With
> the right parameters, SLIC + RAG mean color agglomeration should give quite
> similar results to Fiji?s approach?
>
> Juan.
>
> On 15 November 2016 at 2:39:45 am, Stefanie L?ck (luecks at gmail.com) wrote:
>
> Hi Juan,
>
> thank you for your reply! I have seen and tested the RAG examples but I
> did not understand the SLIC step and the results were very strange... Is
> there any advantage? I am using SLIC anyway at the moment but
> the statistical region merging of ImageJ gives me better results.
>
> Thanks
> Stefanie
>
>
>
> 2016-11-14 13:44 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:
>
>> Hi Stefanie!
>>
>> Have a look at skimage.future.graph! There are some relevant examples in
>> the gallery, too:
>>
>> http://scikit-image.org/docs/dev/auto_examples/#segmentation-of-objects
>>
>> The future.graph API is still experimental (that?s why it?s in ?future?),
>> so we really appreciate any feedback you have about it!
>>
>> Juan.
>>
>>
>>
>> On 14 November 2016 at 8:21:12 pm, Stefanie L?ck (luecks at gmail.com)
>> wrote:
>>
>> Hi!
>>
>> I am looking for a statistical region merging segmentation. Is there
>> anything like this in skimage?
>>
>> Thanks in advance,
>> Stefanie
>> _______________________________________________
>> scikit-image mailing list
>> scikit-image at python.org
>> https://mail.python.org/mailman/listinfo/scikit-image
>>
>>
>
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From luecks at gmail.com  Wed Nov 16 11:06:00 2016
From: luecks at gmail.com (=?UTF-8?Q?Stefanie_L=C3=BCck?=)
Date: Wed, 16 Nov 2016 17:06:00 +0100
Subject: [scikit-image] statistical region merging
In-Reply-To: <CA+JHcKQsvmo0YRVqCYeux8q6rE95C3+r7LY0=t9p+wZOFnnF+g@mail.gmail.com>
References: <CAHvaZnbMfMeWHgM30dkABoGMePOcLGK_BLZ_66Qxu_JS1cvqjg@mail.gmail.com>
 <CA+JHcKQNBq1T60-ea_4t_CLN=s79kByeRu+GjPjcQ3GUPq5ffg@mail.gmail.com>
 <CAHvaZnb2QhUc7NaAWN7-0vU1HNRizoeYfcMy3+ia3SGqzPnUxA@mail.gmail.com>
 <CA+JHcKQrU34h_Nbr--CfJUduFVMw9hLeNmamaTDHpkw_PcKGdQ@mail.gmail.com>
 <CAHvaZnbVF0cJ88Y3Du9oZoODP3_o=zzEcsERWnSLRY-00u7JJA@mail.gmail.com>
 <CA+JHcKQsvmo0YRVqCYeux8q6rE95C3+r7LY0=t9p+wZOFnnF+g@mail.gmail.com>
Message-ID: <CAHvaZnZBO=znMM8Hzx7+wBrJzSPMV0Sjw3RsZUSnVVDggnppuQ@mail.gmail.com>

Hi Juan,

thank you very much for this detailed explanation and your suggestions. I
just had a quick try with the merge_hierarchical example. If I use the code
which I attached the results look more like expected. In addition, I will
test your others suggestions also in terms of speed (I have to segment many
images).

Thanks again for your effort!
Stefanie


2016-11-15 23:55 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:

> Hi Stefanie,
>
> Wow, those results *do* look weird! =) Why are they not the same shape as
> the image? Could you send us the complete code you used?
>
> In the meantime, there's a few things to change. `cut_threshold` is
> probably the single most fragile algorithm you can use with a RAG. You want
> to be using merge_hierarchical. You can do this either on a "color graph",
> which merges regions according to color similarity (and is most similar to
> the statistical region merging of Fiji):
> http://scikit-image.org/docs/dev/auto_examples/
> segmentation/plot_rag_merge.html#sphx-glr-auto-examples-
> segmentation-plot-rag-merge-py
>
> or on a *boundary graph*, which first detects "edges" in the image and
> then merges regions progressively according to the mean edge value:
> http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_
> boundary.html#sphx-glr-auto-examples-segmentation-plot-rag-boundary-py
>
> http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_boundary_
> merge.html#sphx-glr-auto-examples-segmentation-plot-boundary-merge-py
>
> My intuition about this image is that your best choice is to use a sobel
> filter:
> http://scikit-image.org/docs/dev/auto_examples/edges/plot_
> edge_filter.html#sphx-glr-auto-examples-edges-plot-edge-filter-py
> followed by compact watershed:
> http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_compact_
> watershed.html#sphx-glr-auto-examples-segmentation-plot-
> compact-watershed-py
> then by region boundary merging:
> http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_boundary_
> merge.html#sphx-glr-auto-examples-segmentation-plot-boundary-merge-py
>
> The edges look pretty sharp, too. You might even get good results with
> Canny:
> http://scikit-image.org/docs/dev/auto_examples/edges/plot_
> canny.html#sphx-glr-auto-examples-edges-plot-canny-py
>
> I hope all this helps!
>
> Juan.
>
> On 15 November 2016 at 7:11:14 pm, Stefanie L?ck (luecks at gmail.com) wrote:
>
> Dear all,
>
> sorry about the worse problem description! I tried this example
> <http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_rag_mean_color.html#sphx-glr-auto-examples-segmentation-plot-rag-mean-color-py> with
> different parameters for SLIC and graph.cut_threshold  but none of them
> gave me satisfying results.
>
> I attached the original image, the ImageJ SRM (Q=25) output and the RAG
> output (segmentation.slic(img, compactness=20; n_segments=400), graph.cut_threshold(labels1,
> g, 10))
>
> The results are quite different, obviously I am doing something wrong. My
> aim is to segment each leaf separately. At the moment I am
> using felzenszwalb, which gives me quite reasonable results. However I
> would like to try everything possible and therefore I would appreciate some
> tips.
>
> Thank you for the explanation of the algorithm, that was helpful.
>
> Best regards,
> Stefanie
>
>
>
>
>
> 2016-11-15 1:51 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:
>
>> Hi Stefanie,
>>
>> Sorry, these responses should all be CCd to the list, so that others can
>> benefit from the discussion ? my bad for dropping that thread. Could you
>> please:
>>
>> - provide an example segmentation where skimage is doing worse than Fiji
>> - provide the script and parameter settings for both
>>
>> Then we can help troubleshoot. I don?t know what you mean by the results
>> ?were very strange?, for example, so it?s hard to diagnose the problem. =)
>>
>> Starting to merge directly from pixels, as the Fiji plugin does, is
>> expensive and can be error prone. SLIC is a fast, initial pixel merging
>> step, from which we can merge regions according to various criteria.  With
>> the right parameters, SLIC + RAG mean color agglomeration should give quite
>> similar results to Fiji?s approach?
>>
>> Juan.
>>
>> On 15 November 2016 at 2:39:45 am, Stefanie L?ck (luecks at gmail.com)
>> wrote:
>>
>> Hi Juan,
>>
>> thank you for your reply! I have seen and tested the RAG examples but I
>> did not understand the SLIC step and the results were very strange... Is
>> there any advantage? I am using SLIC anyway at the moment but
>> the statistical region merging of ImageJ gives me better results.
>>
>> Thanks
>> Stefanie
>>
>>
>>
>> 2016-11-14 13:44 GMT+01:00 Juan Nunez-Iglesias <jni.soma at gmail.com>:
>>
>>> Hi Stefanie!
>>>
>>> Have a look at skimage.future.graph! There are some relevant examples in
>>> the gallery, too:
>>>
>>> http://scikit-image.org/docs/dev/auto_examples/#segmentation-of-objects
>>>
>>> The future.graph API is still experimental (that?s why it?s in
>>> ?future?), so we really appreciate any feedback you have about it!
>>>
>>> Juan.
>>>
>>>
>>>
>>> On 14 November 2016 at 8:21:12 pm, Stefanie L?ck (luecks at gmail.com)
>>> wrote:
>>>
>>> Hi!
>>>
>>> I am looking for a statistical region merging segmentation. Is there
>>> anything like this in skimage?
>>>
>>> Thanks in advance,
>>> Stefanie
>>> _______________________________________________
>>> scikit-image mailing list
>>> scikit-image at python.org
>>> https://mail.python.org/mailman/listinfo/scikit-image
>>>
>>>
>>
>
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import numpy as np
import matplotlib.pyplot as plt
from skimage import data, util, filters, color
from skimage.filters import roberts, sobel, scharr, prewitt
from skimage import io
from skimage.morphology import watershed
from skimage import data, segmentation, filters, color
from skimage.future import graph
from skimage.filters import threshold_otsu



def _weight_mean_color(graph, src, dst, n):
    """Callback to handle merging nodes by recomputing mean color.

    The method expects that the mean color of `dst` is already computed.

    Parameters
    ----------
    graph : RAG
        The graph under consideration.
    src, dst : int
        The vertices in `graph` to be merged.
    n : int
        A neighbor of `src` or `dst` or both.

    Returns
    -------
    data : dict
        A dictionary with the `"weight"` attribute set as the absolute
        difference of the mean color between node `dst` and `n`.
    """

    diff = graph.node[dst]['mean color'] - graph.node[n]['mean color']
    diff = np.linalg.norm(diff)
    return {'weight': diff}


def merge_mean_color(graph, src, dst):
    """Callback called before merging two nodes of a mean color distance graph.

    This method computes the mean color of `dst`.

    Parameters
    ----------
    graph : RAG
        The graph under consideration.
    src, dst : int
        The vertices in `graph` to be merged.
    """
    graph.node[dst]['total color'] += graph.node[src]['total color']
    graph.node[dst]['pixel count'] += graph.node[src]['pixel count']
    graph.node[dst]['mean color'] = (graph.node[dst]['total color'] /
                                     graph.node[dst]['pixel count'])

img = io.imread("test4.png", as_grey=True)

edges = filters.sobel(color.rgb2gray(img))



labels = segmentation.slic(img, compactness=10, n_segments=10000)
g = graph.rag_mean_color(img, labels)

labels2 = graph.merge_hierarchical(labels, g, thresh=20, rag_copy=False,
                                   in_place_merge=True,
                                   merge_func=merge_mean_color,
                                   weight_func=_weight_mean_color)

g2 = graph.rag_mean_color(img, labels2)

out = color.label2rgb(labels2, img, kind='avg')

#thresh = threshold_otsu(out)
#binary = out > thresh


#out = segmentation.mark_boundaries(out, labels2, (0, 0, 0))
io.imshow(out)
io.show()

#
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From ssouravsingh12 at gmail.com  Wed Nov 16 13:57:29 2016
From: ssouravsingh12 at gmail.com (Sourav Singh)
Date: Thu, 17 Nov 2016 00:27:29 +0530
Subject: [scikit-image] Contributing to scikit-image
In-Reply-To: <CALpy4prVWDZpMDfDcXEGiLO90rkAauqhmUO7_n5-qkK8CqpORQ@mail.gmail.com>
References: <CALpy4prVWDZpMDfDcXEGiLO90rkAauqhmUO7_n5-qkK8CqpORQ@mail.gmail.com>
Message-ID: <CALpy4pqpefoxwJwtmjfN264xi=ZgFS98Um-RYA9i_O_4A7BdMw@mail.gmail.com>

Hello,

I am a student from India who is interested in scikit-image project. I
would like to contribute to scikit-image by adding COSFIRE and merging
CellProfiler code.

If possible, I would also like to become a long-term maintainer of the
project.

Regards,

Sourav
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From winecoding at gmail.com  Mon Nov 21 22:49:41 2016
From: winecoding at gmail.com (wine lover)
Date: Mon, 21 Nov 2016 21:49:41 -0600
Subject: [scikit-image] filtering image entry values based on a threshold
Message-ID: <CAFyUc2DOzLonpBAyn8c4RL9pqHPVZWKO16ithRAji_Aa3MYEYg@mail.gmail.com>

Dear All,

In one code segment, I once saw an approach of filtering image values as
follows using cv2.  In Scikit image, if I want to realize the same
functionality, how to do it?

import cv2
img = cv2.threshold(img, 0.5, 1., cv2.THRESH_BINARY)[1].astype(np.uint8


Thanks,

huaiyang
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From stefanv at berkeley.edu  Tue Nov 22 20:25:48 2016
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Tue, 22 Nov 2016 17:25:48 -0800
Subject: [scikit-image] Model PRs
Message-ID: <1479864348.1798838.796498617.7D9771AA@webmail.messagingengine.com>

Hi everyone

I've started a new page on the wiki to track "Model PRs" (thanks, Juan,
for the suggestion).

These PRs are meant to illustrate how to perform certain common
refactoring operations.  I've added one example already, of how to
deprecate modules that return XY formatted outputs to row-column format.

If you have similar examples, please feel free to add them:

https://github.com/scikit-image/scikit-image/wiki/Model-PRs

Thanks
St?fan

From stefanv at berkeley.edu  Tue Nov 22 20:30:02 2016
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Tue, 22 Nov 2016 17:30:02 -0800
Subject: [scikit-image] filtering image entry values based on a threshold
In-Reply-To: <CAFyUc2DOzLonpBAyn8c4RL9pqHPVZWKO16ithRAji_Aa3MYEYg@mail.gmail.com>
References: <CAFyUc2DOzLonpBAyn8c4RL9pqHPVZWKO16ithRAji_Aa3MYEYg@mail.gmail.com>
Message-ID: <1479864602.1799613.796499057.14C1D0D7@webmail.messagingengine.com>

On Mon, Nov 21, 2016, at 19:49, wine lover wrote:

> In one code segment, I once saw an approach of filtering image values
> as follows using cv2.  In Scikit image, if I want to realize the same
> functionality, how to do it?
> 

> import cv2 img = cv2.threshold(img, 0.5, 1.,
> cv2.THRESH_BINARY)[1].astype(np.uint8


How about:



from skimage import img_as_float, img_as_ubyte

img = img_as_float(img)

img_thresholded = img_as_ubyte(img < 0.5)



St?fan
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