From egor.v.panfilov at gmail.com  Fri Sep  1 05:30:17 2017
From: egor.v.panfilov at gmail.com (Egor Panfilov)
Date: Fri, 1 Sep 2017 12:30:17 +0300
Subject: [scikit-image] Release date for 0.14
Message-ID: <CAPBs059fUSrt8A=xa-+=DVMznr=YRLbZMXqTfRROEM5oSayyiQ@mail.gmail.com>

Dear all,

I propose to set a release date for scikit-image 0.14 on the mid of October
(15th should do). Also, I'd volunteer to be a release manager for the
release.
Please, let me know if you agree. If so, I kindly ask you to take a deep
breath and try to review some of the scheduled PRs in the coming month.

Thanks in advance, and have a nice we!

Regards,
Egor Panfilov
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From jni.soma at gmail.com  Fri Sep  1 09:47:02 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Fri, 1 Sep 2017 16:47:02 +0300
Subject: [scikit-image] Release date for 0.14
In-Reply-To: <CAPBs059fUSrt8A=xa-+=DVMznr=YRLbZMXqTfRROEM5oSayyiQ@mail.gmail.com>
References: <CAPBs059fUSrt8A=xa-+=DVMznr=YRLbZMXqTfRROEM5oSayyiQ@mail.gmail.com>
Message-ID: <471ba497-f6ec-4d59-a93d-d87a69734242@Spark>

Hi Egor,

Thanks for your support! I would prefer Nov 15 because I know for a fact that I will struggle to finish some of the major PRs that I need to get in before 0.14, including undoing the speed regression of watershed, and nd moments. (For the first one I don?t even know where to start currently.)

Juan.

On 1 Sep 2017, 12:31 PM +0300, Egor Panfilov <egor.v.panfilov at gmail.com>, wrote:
> Dear all,
>
> I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release.
> Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month.
>
> Thanks in advance, and have a nice we!
>
> Regards,
> Egor Panfilov
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Fri Sep  1 10:18:36 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Fri, 01 Sep 2017 22:18:36 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6UmU6ICBSZWxlYXNlIGRhdGUgZm9yIDAu?=
 =?gbk?q?14?=
Message-ID: <20170901141836.76CB72E00D8@webmail.sinamail.sina.com.cn>

Hi Juan:What do you mean "undoing the speed regression of watershed"?  I found watershed run very slowly with large image,  and I am writting one with numba.           YXDragon
----- ???? -----
????Juan Nunez-Iglesias <jni.soma at gmail.com>
????scikit-image List Mailing <scikit-image at python.org>,  "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image at python.org>
???Re: [scikit-image] Release date for 0.14
???2017?09?01? 21?48?




Hi Egor,


Thanks for your support! I would prefer Nov 15 because I know for a fact that I will struggle to finish some of the major PRs that I need to get in before 0.14, including undoing the speed regression of watershed, and nd moments. (For the first one I don?t even know where to start currently.)


Juan.



On 1 Sep 2017, 12:31 PM +0300, Egor Panfilov <egor.v.panfilov at gmail.com>, wrote:


Dear all,


I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release.
Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month.


Thanks in advance, and have a nice we!



Regards,
Egor Panfilov

_______________________________________________

scikit-image mailing list

scikit-image at python.org

https://mail.python.org/mailman/listinfo/scikit-image






_______________________________________________
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  Fri Sep  1 13:23:01 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Fri, 1 Sep 2017 20:23:01 +0300
Subject: [scikit-image]
 =?utf-8?Q?=E5=9B=9E=E5=A4=8D=EF=BC=9ARe=3A__?=Release date for 0.14
In-Reply-To: <20170901141836.76CB72E00D8@webmail.sinamail.sina.com.cn>
References: <20170901141836.76CB72E00D8@webmail.sinamail.sina.com.cn>
Message-ID: <597ca96b-f397-4f7b-914c-30d4495fdc05@Spark>

Hi Yan,

See here:

https://github.com/scikit-image/scikit-image/issues/2636

Juan.

On 1 Sep 2017, 6:07 PM +0300, imagepy at sina.com, wrote:
> Hi Juan:
> What do you mean "undoing the speed regression of watershed"?? I found watershed run very slowly with large image,? and I am writting one with numba.
> ?????????? YXDragon
>
> ----- ???? -----
> ????Juan Nunez-Iglesias <jni.soma at gmail.com>
> ????scikit-image List Mailing <scikit-image at python.org>, "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image at python.org>
> ???Re: [scikit-image] Release date for 0.14
> ???2017?09?01? 21?48?
>
> Hi Egor,
>
> Thanks for your support! I would prefer Nov 15 because I know for a fact that I will struggle to finish some of the major PRs that I need to get in before 0.14, including undoing the speed regression of watershed, and nd moments. (For the first one I don?t even know where to start currently.)
>
> Juan.
>
> On 1 Sep 2017, 12:31 PM +0300, Egor Panfilov <egor.v.panfilov at gmail.com>, wrote:
> > Dear all,
> >
> > I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release.
> > Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month.
> >
> > Thanks in advance, and have a nice we!
> >
> > Regards,
> > Egor Panfilov
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From stefanv at berkeley.edu  Fri Sep  1 13:31:51 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Fri, 01 Sep 2017 10:31:51 -0700
Subject: [scikit-image] Release date for 0.14
In-Reply-To: <CAPBs059fUSrt8A=xa-+=DVMznr=YRLbZMXqTfRROEM5oSayyiQ@mail.gmail.com>
References: <CAPBs059fUSrt8A=xa-+=DVMznr=YRLbZMXqTfRROEM5oSayyiQ@mail.gmail.com>
Message-ID: <1504287111.3906259.1092490952.18F279A6@webmail.messagingengine.com>

Hi Egor

On Fri, Sep 1, 2017, at 02:30, Egor Panfilov wrote:
> I propose to set a release date for scikit-image 0.14 on the mid of
> October (15th should do). Also, I'd volunteer to be a release manager
> for the release.> Please, let me know if you agree. If so, I kindly ask you to take a
> deep breath and try to review some of the scheduled PRs in the
> coming month.
That's a fantastic offer; we'll take it! :)

October is also difficult to me, so let's aim for mid-November?

St?fan

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From 24dakenlo at gmail.com  Wed Sep  6 21:23:24 2017
From: 24dakenlo at gmail.com (NASAHARA Kenlo)
Date: Thu, 7 Sep 2017 10:23:24 +0900
Subject: [scikit-image] GLCM for non-rectangular image
Message-ID: <20170907102324.2a692758ce56ba98dd9210d8@gmail.com>

Dear scikit-image community:

I am trying GLCM functions in scikit-image. 
http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_glcm.html

I wonder whether they can treat images with irregular 
shapes, such as a circle, an oval, or some more complex 
forms (not only rectagle). 

In the "greycomatrix", function:

    def greycomatrix(image, distances, angles, levels=None, symmetric=False, normed=False):
    
    image : array_like
        Integer typed input image. Only positive valued images are supported.
        If type is other than uint8, the argument `levels` needs to be set.

the "image" seems to be required to be a rectangle. 

If NAN or NULL values are allowed in the "image", and the function skips 
treating those "no-data" pixels assigned with NAN or NULL, then we 
may be able to treat any shapes of image, by filling the pixels outside the
boudary with NAN or NULL.

However, in the source code of "_glcm_loop" function
(https://searchcode.com/codesearch/view/83509141/),  all the pixels 
within the rectangular image are scanned, without permitting "no-data".

My questions:
1. Do you know how to treat GLCM in non-rectangular image with
scikit-image?
2. If not, do you know any other ways to do that instead of scikit-image?
3. Do you think it is a reasonable idea to change GLCM functions in 
  scikit-image so that they can treat no-data (allowing NAN or NULL)?

-- 
Kenlo Nishida Nasahara
Faculty of Life and Environmental Sciences
University of Tsukuba, Japan 305-8572
24dakenlo at gmail.com

From jni.soma at gmail.com  Thu Sep  7 00:29:16 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 7 Sep 2017 14:29:16 +1000
Subject: [scikit-image] GLCM for non-rectangular image
In-Reply-To: <20170907102324.2a692758ce56ba98dd9210d8@gmail.com>
References: <20170907102324.2a692758ce56ba98dd9210d8@gmail.com>
Message-ID: <c0ea3822-96b1-4704-85f1-0d77658da280@Spark>

Hi Kenlo,

Thanks for your email.

`np.nan` is only defined for floating point images, but GLCM only works for non-negative integer images, since the intensity values need to serve as indices to a matrix.

Therefore, in order to ignore NULL values, you just need to create an array with an arbitrary value as NULL. This is actually not too hard. If you start with a uint8 image, make a uint16 image with a mask where values to be ignored are set to 256.

Then, use greycomatrix with levels=257.

Finally, from the documentation:

> ? ? ? ?The grey-level co-occurrence histogram. The value
> ? ? ? ?`P[i,j,d,theta]` is the number of times that grey-level `j`
> ? ? ? ?occurs at a distance `d` and at an angle `theta` from
> ? ? ? ?grey-level `i`.

Thus you can get your odd-shaped GLCM, ignoring values outside your mask, with:

out = greycomatrix(image, [?], levels=257)
result = out[:256, :256]

I hope this helps!

If you have suggestions for making this process easier, please let us know!

Juan.

On 7 Sep 2017, 11:23 AM +1000, NASAHARA Kenlo <24dakenlo at gmail.com>, wrote:
> Dear scikit-image community:
>
> I am trying GLCM functions in scikit-image.
> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_glcm.html
>
> I wonder whether they can treat images with irregular
> shapes, such as a circle, an oval, or some more complex
> forms (not only rectagle).
>
> In the "greycomatrix", function:
>
> def greycomatrix(image, distances, angles, levels=None, symmetric=False, normed=False):
>
> image : array_like
> Integer typed input image. Only positive valued images are supported.
> If type is other than uint8, the argument `levels` needs to be set.
>
> the "image" seems to be required to be a rectangle.
>
> If NAN or NULL values are allowed in the "image", and the function skips
> treating those "no-data" pixels assigned with NAN or NULL, then we
> may be able to treat any shapes of image, by filling the pixels outside the
> boudary with NAN or NULL.
>
> However, in the source code of "_glcm_loop" function
> (https://searchcode.com/codesearch/view/83509141/), all the pixels
> within the rectangular image are scanned, without permitting "no-data".
>
> My questions:
> 1. Do you know how to treat GLCM in non-rectangular image with
> scikit-image?
> 2. If not, do you know any other ways to do that instead of scikit-image?
> 3. Do you think it is a reasonable idea to change GLCM functions in
> scikit-image so that they can treat no-data (allowing NAN or NULL)?
>
> --
> Kenlo Nishida Nasahara
> Faculty of Life and Environmental Sciences
> University of Tsukuba, Japan 305-8572
> 24dakenlo at gmail.com
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From 24dakenlo at gmail.com  Thu Sep  7 00:42:55 2017
From: 24dakenlo at gmail.com (NASAHARA Kenlo)
Date: Thu, 7 Sep 2017 13:42:55 +0900
Subject: [scikit-image] GLCM for non-rectangular image
In-Reply-To: <c0ea3822-96b1-4704-85f1-0d77658da280@Spark>
References: <20170907102324.2a692758ce56ba98dd9210d8@gmail.com>
 <c0ea3822-96b1-4704-85f1-0d77658da280@Spark>
Message-ID: <20170907134255.f0bbb150b0673dfbfe7e51f0@gmail.com>

Thanks, Juan

What a clever idea! 

You mean, we put a dummy number (which is 
larger than the actual maximum) and create the 
GLCM, and then we remove the pairs with the
valid number and the dummy number. (Perhaps the 
normalization should be done after that manually).

I will try it!

Kenlo Nasahara

On Thu, 7 Sep 2017 14:29:16 +1000
Juan Nunez-Iglesias <jni.soma at gmail.com> wrote:

> Hi Kenlo,
> 
> Thanks for your email.
> 
> `np.nan` is only defined for floating point images, but GLCM only works for non-negative integer images, since the intensity values need to serve as indices to a matrix.
> 
> Therefore, in order to ignore NULL values, you just need to create an array with an arbitrary value as NULL. This is actually not too hard. If you start with a uint8 image, make a uint16 image with a mask where values to be ignored are set to 256.
> 
> Then, use greycomatrix with levels=257.
> 
> Finally, from the documentation:
> 
> > ? ? ? ?The grey-level co-occurrence histogram. The value
> > ? ? ? ?`P[i,j,d,theta]` is the number of times that grey-level `j`
> > ? ? ? ?occurs at a distance `d` and at an angle `theta` from
> > ? ? ? ?grey-level `i`.
> 
> Thus you can get your odd-shaped GLCM, ignoring values outside your mask, with:
> 
> out = greycomatrix(image, [?], levels=257)
> result = out[:256, :256]
> 
> I hope this helps!
> 
> If you have suggestions for making this process easier, please let us know!
> 
> Juan.
> 
> On 7 Sep 2017, 11:23 AM +1000, NASAHARA Kenlo <24dakenlo at gmail.com>, wrote:
> > Dear scikit-image community:
> >
> > I am trying GLCM functions in scikit-image.
> > http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_glcm.html
> >
> > I wonder whether they can treat images with irregular
> > shapes, such as a circle, an oval, or some more complex
> > forms (not only rectagle).
> >
> > In the "greycomatrix", function:
> >
> > def greycomatrix(image, distances, angles, levels=None, symmetric=False, normed=False):
> >
> > image : array_like
> > Integer typed input image. Only positive valued images are supported.
> > If type is other than uint8, the argument `levels` needs to be set.
> >
> > the "image" seems to be required to be a rectangle.
> >
> > If NAN or NULL values are allowed in the "image", and the function skips
> > treating those "no-data" pixels assigned with NAN or NULL, then we
> > may be able to treat any shapes of image, by filling the pixels outside the
> > boudary with NAN or NULL.
> >
> > However, in the source code of "_glcm_loop" function
> > (https://searchcode.com/codesearch/view/83509141/), all the pixels
> > within the rectangular image are scanned, without permitting "no-data".
> >
> > My questions:
> > 1. Do you know how to treat GLCM in non-rectangular image with
> > scikit-image?
> > 2. If not, do you know any other ways to do that instead of scikit-image?
> > 3. Do you think it is a reasonable idea to change GLCM functions in
> > scikit-image so that they can treat no-data (allowing NAN or NULL)?
> >
> > --
> > Kenlo Nishida Nasahara
> > Faculty of Life and Environmental Sciences
> > University of Tsukuba, Japan 305-8572
> > 24dakenlo at gmail.com
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image


-- 
Kenlo Nishida Nasahara
Faculty of Life and Environmental Sciences
University of Tsukuba, Japan 305-8572
24dakenlo at gmail.com

From imagepy at sina.com  Fri Sep  8 05:49:33 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Fri, 08 Sep 2017 17:49:33 +0800
Subject: [scikit-image] some question about h_minma (need a paremeter,
 and can run faster)
Message-ID: <20170908094934.0F240C800A9@webmail.sinamail.sina.com.cn>

 Hi every one:    As I mentioned befor, In the official example, use watershed to segment two circle, In this example, use pick_local_max to find the seed. But When I try on other binary images, there always are two local_max nearby, then the segment be too trivial. And I use the h_maxma and h_minma, I have some trouble:
1. when a region has more than one min value(same but not nearby), the result will mark them all. (I want to use them as seed to watershed, So I need any one, else the region will be broken, can we add a parameter to control?)2. h_minma run too slowly, (what more, the watershed run more slowly... so my program crashed! I had heard Juan will improve it in the next version)
So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image:       scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. 
I will attach my code and test image. If any one can have a look, and improve the h_minma function? I will write a issue on github soon.
                                                                            YXDragon
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From imagepy at sina.com  Sat Sep  9 00:25:56 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Sat, 09 Sep 2017 12:25:56 +0800
Subject: [scikit-image] =?gbk?b?16q3oqO6c29tZSBxdWVzdGlvbiBhYm91dCBoX21p?=
 =?gbk?q?nma_=28need_a_paremeter=2C_and_can_run_faster=29?=
Message-ID: <20170909042556.7A3C2C800A9@webmail.sinamail.sina.com.cn>

Sorry, May be I had send one, But I am not sure if I send suceessfully, because of the attachment is too large, so I send again, with a jpg format.

 Hi every one:    As I mentioned befor, In the official example, use watershed to segment two circle, In this example, use pick_local_max to find the seed. But When I try on other binary images, there always are two local_max nearby, then the segment be too trivial. And I use the h_maxma and h_minma, I have some trouble:
1. when a region has more than one min value(same but not nearby), the result will mark them all. (I want to use them as seed to watershed, So I need any one, else the region will be broken, can we add a parameter to control?)2. h_minma run too slowly, (what more, the watershed run more slowly... so my program crashed! I had heard Juan will improve it in the next version)
So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image:       scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. 
I will attach my code and test image. If any one can have a look, and improve the h_minma function? I will write a issue on github soon.
                                                                            YXDragon
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From balazovic.peter at gmail.com  Sat Sep  9 10:28:38 2017
From: balazovic.peter at gmail.com (Peter Balazovic)
Date: Sat, 9 Sep 2017 16:28:38 +0200
Subject: [scikit-image] HOGDescriptor
Message-ID: <CAFq4t4j0prt93KCQKzUAmAXFOsiu7gK44COGEJNAD4ktMPG5Lg@mail.gmail.com>

Hello.

I see there is HOG descriptor implemented within scikit image, I wonder how
can I reused or compare exmples given
http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_hog.html
with OpenCV where I can find
http://docs.opencv.org/3.1.0/d5/d33/structcv_1_1HOGDescriptor.html.
I want to intialize and compute HoG descriptor with both same parametrs.
How and which the hog paramerts from scikit relates to OpenCV one? Anyone
can help?

Thank you very much.
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From stefanv at berkeley.edu  Sat Sep  9 23:16:49 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Sat, 09 Sep 2017 20:16:49 -0700
Subject: [scikit-image] HOGDescriptor
In-Reply-To: <CAFq4t4j0prt93KCQKzUAmAXFOsiu7gK44COGEJNAD4ktMPG5Lg@mail.gmail.com>
References: <CAFq4t4j0prt93KCQKzUAmAXFOsiu7gK44COGEJNAD4ktMPG5Lg@mail.gmail.com>
Message-ID: <1505013409.3401389.1100929616.59B2354E@webmail.messagingengine.com>

Hi Peter

On Sat, Sep 9, 2017, at 07:28, Peter Balazovic wrote:
> I see there is HOG descriptor implemented within scikit image, I
> wonder how can I reused or compare exmples given
> http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_hog.html> with OpenCV where I can find
> http://docs.opencv.org/3.1.0/d5/d33/structcv_1_1HOGDescriptor.html.> I want to intialize and compute HoG descriptor with both same
> parametrs. How and which the hog paramerts from scikit relates to
> OpenCV one? Anyone can help?
The API reference for HoG might help:

http://scikit-image.org/docs/dev/api/skimage.feature.html?highlight=hog#skimage.feature.hog
Best regards
St?fan


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From stefanv at berkeley.edu  Sat Sep  9 23:29:00 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Sat, 09 Sep 2017 20:29:00 -0700
Subject: [scikit-image] =?utf-8?b?6L2s5Y+R77yac29tZSBxdWVzdGlvbiBhYm91?=
 =?utf-8?q?t_h=5Fminma_=28need_a_paremeter=2C_and_can_run_faster=29?=
In-Reply-To: <20170909042556.7A3C2C800A9@webmail.sinamail.sina.com.cn>
References: <20170909042556.7A3C2C800A9@webmail.sinamail.sina.com.cn>
Message-ID: <1505014140.3403275.1100930128.6F560853@webmail.messagingengine.com>

Hi, YXDragon

On Fri, Sep 8, 2017, at 21:25, imagepy at sina.com wrote:
> So I wrote h_minma/maxma and watershed myself (as a sub package of my
> project imagepy). My watershed now only support 2D, But the h_minma
> now is OK, works on nd. I had test one image:>        scikit-image's h_minma runs in 15s, and mine runs in 0.3s,
>        45times.
I tested on my machine and can confirm the slowness.  Would you be
willing to help profile the code, to find out why it is so slow?
Best regards
St?fan

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From imagepy at sina.com  Sun Sep 10 13:18:08 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Mon, 11 Sep 2017 01:18:08 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6UmU6ICDXqreio7pzb21lIHF1ZXN0aW9u?=
 =?gbk?b?IGFib3V0X2hfbWlubWFfKG5lZWRfYV9wYXJlbWV0ZXIsX2FuZF9jYW5fcnVuX2Zh?=
 =?gbk?q?ster=29?=
Message-ID: <20170910171808.D787FAC00D5@webmail.sinamail.sina.com.cn>

sorry! Perhaps I wrote mixed and disorderly, I want to say, I had improve or wrote some function, I want to contribute them when we support numba.
----- ???? -----
????Stefan van der Walt <stefanv at berkeley.edu>
????scikit-image at python.org
???Re: [scikit-image] ???some question about_h_minma_(need_a_paremeter,_and_can_run_faster)
???2017?09?10? 11?29?




Hi, YXDragon



On Fri, Sep 8, 2017, at 21:25, imagepy at sina.com wrote:

So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image:

       scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times.




I tested on my machine and can confirm the slowness.  Would you be willing to help profile the code, to find out why it is so slow?



Best regards

St?fan






_______________________________________________
scikit-image mailing list
scikit-image at python.org
https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Sun Sep 10 13:44:35 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Mon, 11 Sep 2017 01:44:35 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6UmU6ICDXqreio7pzb21lIHF1ZXN0aW9u?=
 =?gbk?b?IGFib3V0X2hfbWlubWFfKG5lZWRfYV9wYXJlbWV0ZXIsX2FuZF9jYW5fcnVuX2Zh?=
 =?gbk?q?ster=29?=
Message-ID: <20170910174435.A6F5EAC00D4@webmail.sinamail.sina.com.cn>

Hi Stefan:OK, I would commen my code,  and try to profile the skimage's code. then start a issue on github.I once tried to contribute to scikit-image. But give up, for I am averse to write cython. I prefer writting in pure C, and importting with ctypes, or writting pure python with numba (JNI recommend to me). So I agree with using numba to extend scikit-image(we discussed before).And I had wrote or improve some other function may be usful. I improved the medal axis, watershed, h_maxma/minma, and writed a ridge algrism(extract the ridge or river valley), and we can use them in imagepy interactively. I will attach some snapshot, please have a look.(I had wrapped many functions of scipy.ndimage and skimage in imagepy, and have built some user base in my country (China), they will feed back some questions to me, I think it's useful to imagepy and skimage)
----- ???? -----
????Stefan van der Walt <stefanv at berkeley.edu>
????scikit-image at python.org
???Re: [scikit-image] ???some question about_h_minma_(need_a_paremeter,_and_can_run_faster)
???2017?09?10? 11?29?




Hi, YXDragon



On Fri, Sep 8, 2017, at 21:25, imagepy at sina.com wrote:

So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image:

       scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times.




I tested on my machine and can confirm the slowness.  Would you be willing to help profile the code, to find out why it is so slow?



Best regards

St?fan






_______________________________________________
scikit-image mailing list
scikit-image at python.org
https://mail.python.org/mailman/listinfo/scikit-image
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From Thomas.Edgar.Walter at googlemail.com  Sun Sep 10 15:12:38 2017
From: Thomas.Edgar.Walter at googlemail.com (Thomas Walter)
Date: Sun, 10 Sep 2017 21:12:38 +0200
Subject: [scikit-image] =?utf-8?b?6L2s5Y+R77yac29tZSBxdWVzdGlvbiBhYm91?=
 =?utf-8?q?t_h=5Fminma_=28need_a_paremeter=2C_and_can_run_faster=29?=
In-Reply-To: <20170909042556.7A3C2C800A9@webmail.sinamail.sina.com.cn>
References: <20170909042556.7A3C2C800A9@webmail.sinamail.sina.com.cn>
Message-ID: <60197079-53c1-0168-8066-ab5b0343ad81@googlemail.com>

Hello,

just to comment on your remarks.

 > 1. when a region has more than one min value(same but not nearby), 
the result will mark them all. (I want to use them as seed to watershed, 
So I need any one, else the region will be broken, can we add a 
parameter to control?)
I think there is a problem in the naming of the operator; I will open an 
issue on this. But this can be easily fixed. There is no parameter to be 
added.

 > 2. h_minma run too slowly, (what more, the watershed run more 
slowly... so my program crashed! I had heard Juan will improve it in the 
next version)
h_minima are based on the grey-scale reconstruction; so I guess that if 
h_minima is too slow, the reconstruction operator and all derived 
operators will have the same issue.

Best,

Thomas.


On 9/9/17 6:25 AM, imagepy at sina.com wrote:
> Sorry, May be I had send one, But I am not sure if I send 
> suceessfully, because of the attachment is too large, so I send again, 
> with a jpg format.
>
>  Hi every one:
>     As I mentioned befor, In the official example, use watershed to 
> segment two circle, In this example, use pick_local_max to find the 
> seed. But When I try on other binary images, there always are two 
> local_max nearby, then the segment be too trivial. And I use the 
> h_maxma and h_minma, I have some trouble:
>
> 1. when a region has more than one min value(same but not nearby), the 
> result will mark them all. (I want to use them as seed to watershed, 
> So I need any one, else the region will be broken, can we add a 
> parameter to control?)
> 2. h_minma run too slowly, (what more, the watershed run more 
> slowly... so my program crashed! I had heard Juan will improve it in 
> the next version)
>
> So I wrote h_minma/maxma and watershed myself (as a sub package of my 
> project imagepy). My watershed now only support 2D, But the h_minma 
> now is OK, works on nd. I had test one image:
>        scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 
> 45times.
>
> I will attach my code and test image. If any one can have a look, and 
> improve the h_minma function? I will write a issue on github soon.
>
> YXDragon
>
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image


-- 
Thomas Walter
27 rue des Acacias
75017 Paris

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From imagepy at sina.com  Mon Sep 11 16:32:02 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Tue, 12 Sep 2017 04:32:02 +0800
Subject: [scikit-image] my watershed
Message-ID: <20170911203202.DE2E24C0095@webmail.sinamail.sina.com.cn>

Hi:Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s.It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast.
YXDragon
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From siqueiraaf at gmail.com  Wed Sep 20 00:25:01 2017
From: siqueiraaf at gmail.com (Alexandre Fioravante de Siqueira)
Date: Wed, 20 Sep 2017 01:25:01 -0300
Subject: [scikit-image] Code for the short course 'Image Processing using
 Python', @ IAMG2017
Message-ID: <CANPz1oZA4YaG9R74hg9y4Uw72WQ4kAOYC0gF4+e60rxUxN=Ujg@mail.gmail.com>

Dear all,
as I said in an old previous e-mail, I presented a short course using
scikit-image for processing microscopy images at IAMG2017 (short course 8
at <http://iamg2017.com/courses/> <http://iamg2017.com/courses/>).
An alpha version of the codes is now available; please feel free to check
it at
<https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>
<https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>.
Since it is still very raw, I'd be glad to receive your comments,
suggestions and ideas!
Thank you in advance. Kind regards,

Alex

-- 
------------------------------------------------------------------------------
Dr. Alexandre 'Jaguar' Fioravante de Siqueira
Grupo de Cronologia - Sala 13
Departamento de Raios C?smicos e Cronologia - DRCC
Instituto de F?sica "Gleb Wataghin" - IFGW
Unicamp - Universidade Estadual de Campinas
Rua S?rgio Buarque de Holanda, 777
Cidade Universit?ria Zeferino Vaz - CEP 13083-859
Campinas - SP - Brazil

Phone: +55(19)3521-5362
Lattes curriculum: 3936721630855880
<http://lattes.cnpq.br/3936721630855880/>
ORCID: 0000-0003-1320-4347 <http://orcid.org/0000-0003-1320-4347>
Personal site: programmingscience.org <http://www.programmingscience.org/>
Github: alexandrejaguar <http://www.github.com/alexandrejaguar/>
Skype: alexandrejaguar
Twitter: alexdesiqueira <http://www.twitter.com/alexdesiqueira/>
------------------------------------------------------------------------------
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From stefanv at berkeley.edu  Wed Sep 20 17:15:48 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Wed, 20 Sep 2017 14:15:48 -0700
Subject: [scikit-image] Code for the short course 'Image Processing
 using Python', @ IAMG2017
In-Reply-To: <CANPz1oZA4YaG9R74hg9y4Uw72WQ4kAOYC0gF4+e60rxUxN=Ujg@mail.gmail.com>
References: <CANPz1oZA4YaG9R74hg9y4Uw72WQ4kAOYC0gF4+e60rxUxN=Ujg@mail.gmail.com>
Message-ID: <1505942148.1198683.1112942264.0FB29A5C@webmail.messagingengine.com>

Hi Alex

On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote:> as I said in an old previous e-mail, I presented a short course using
> scikit-image for processing microscopy images at IAMG2017 (short
> course 8 at <http://iamg2017.com/courses/>).> An alpha version of the codes is now available; please feel free to
> check it at
> <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>
> .
Thanks for sharing these!

>  Since it is still very raw, I'd be glad to receive your comments,
>  suggestions and ideas!
I'd say 1) stick to gray, viridis, and other reliable colormaps and 2)
plot the found features so that they are easier to observe (currently
just pixels inside a big image).
You may also want to take a look at the segmentation lesson from the
skimage_tutorial repo, which has a few sketches to clarify the workings
of watershed.
Best regards
St?fan

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From jni.soma at gmail.com  Thu Sep 21 01:46:54 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 21 Sep 2017 15:46:54 +1000
Subject: [scikit-image] my watershed
In-Reply-To: <20170911203202.DE2E24C0095@webmail.sinamail.sina.com.cn>
References: <20170911203202.DE2E24C0095@webmail.sinamail.sina.com.cn>
Message-ID: <107f1ba4-b698-449f-af63-421fdf5d54f5@Spark>

Hi Yan,

Thanks for this. Simple functions are very good for one?s own images, as well as to understand an algorithm, but for a widely used library like scikit-image, flexibility and robustness are least as important as speed. In skimage, we aim to support floating point input images, for which your code won?t work. There is a lot of thought into edge cases going into the skimage implementation, which unfortunately could have an effect on performance. The question we need to solve isn?t ?can we make a super-fast watershed implementation?, but, ?can we make a flexible and robust implementation that is also fast?? Using Numba is certainly not off-limits, but any candidate implementation should at a minimum pass the skimage test suite.

I once tried a level-by-level implementation of watershed, by the way. It has a fatal flaw, which is that valleys with no markers will never get labeled. Here?s a test case that works with skimage but fails in your implementation. (Note also that your implementation overwrites the seeds image, which is pretty crazy. =)

Thanks again!

Juan.

In [44]: import watershed
In [45]: from skimage import morphology
In [46]: import numpy as np
In [47]: image = np.array([1, 0, 1, 0, 1, 0, 1], dtype=np.uint8)
In [48]: seeds = np.array([0, 1, 0, 0, 0, 2, 0])
In [49]: morphology.watershed(image, seeds)
Out[49]: array([1, 1, 1, 1, 2, 2, 2], dtype=int32)
In [50]: watershed.watershed(image, seeds)
Out[50]: array([0, 0, 0, 0, 0, 0, 0])
In [51]: seeds
Out[51]: array([0, 0, 0, 0, 0, 0, 0])

On 12 Sep 2017, 6:34 AM +1000, imagepy at sina.com, wrote:
> Hi:
> Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s.
> It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast.
>
> YXDragon
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Thu Sep 21 02:19:39 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Thu, 21 Sep 2017 14:19:39 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6UmU6ICBDb2RlIGZvciB0aGUgc2hvcnQg?=
 =?gbk?q?course_=27Image_Processing_using_Python=27=2C_=40_IAMG2017?=
Message-ID: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>

Hi Stefan:  "segmentation lesson from the skimage_tutorial repo" did you means this?(https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/4_segmentation.ipynb), I am writing a simple imageprocessing book, It may be useful for me.
Best regardsYXDragon----- ???? -----
????Stefan van der Walt <stefanv at berkeley.edu>
????Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com>, scikit-image at python.org
???Re: [scikit-image] Code for the short course 'Image Processing using Python', @ IAMG2017
???2017?09?21? 05?16?




Hi Alex



On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote:

as I said in an old previous e-mail, I presented a short course using scikit-image for processing microscopy images at IAMG2017 (short course 8 at <http://iamg2017.com/courses/>).

An alpha version of the codes is now available; please feel free to check it at <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>.




Thanks for sharing these!



 Since it is still very raw, I'd be glad to receive your comments, suggestions and ideas!




I'd say 1) stick to gray, viridis, and other reliable colormaps and 2) plot the found features so that they are easier to observe (currently just pixels inside a big image).



You may also want to take a look at the segmentation lesson from the skimage_tutorial repo, which has a few sketches to clarify the workings of watershed.



Best regards

St?fan






_______________________________________________
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  Thu Sep 21 02:30:19 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 21 Sep 2017 16:30:19 +1000
Subject: [scikit-image]
 =?utf-8?Q?=E5=9B=9E=E5=A4=8D=EF=BC=9ARe=3A__?=Code for the short course
 'Image Processing using Python', @ IAMG2017
In-Reply-To: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>
References: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>
Message-ID: <9373f9f9-2ee5-4b0b-ad73-dd8304aea6ec@Spark>

I just noticed that the tutorials repo has no license. Oops! I suggest CC-BY. Technically we would need to ask all the contributors for their permission to put any new license on it.

In the meantime, though, as the main author of that specific document, I grant Yan permission to use its contents. (St?fan might technically need to step in also, but I think it safe to assume he?ll agree. =) A mention of the source in your book would be appreciated, Yan. =)

Juan.

On 21 Sep 2017, 4:25 PM +1000, imagepy at sina.com, wrote:
> Hi Stefan:
> ? "segmentation lesson from the skimage_tutorial repo" did you means this?(https://github.com/scikit-image/skimage-tutorials/blob/master/lectures/4_segmentation.ipynb), I am writing a simple imageprocessing book, It may be useful for me.
>
> Best regards
> YXDragon
> ----- ???? -----
> ????Stefan van der Walt <stefanv at berkeley.edu>
> ????Alexandre Fioravante de Siqueira <siqueiraaf at gmail.com>, scikit-image at python.org
> ???Re: [scikit-image] Code for the short course 'Image Processing using Python', @ IAMG2017
> ???2017?09?21? 05?16?
>
> Hi Alex
>
> On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote:
> > as I said in an old previous e-mail, I presented a short course using scikit-image for processing microscopy images at IAMG2017 (short course 8 at <http://iamg2017.com/courses/>).
> > An alpha version of the codes is now available; please feel free to check it at <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>.
>
> Thanks for sharing these!
>
> > Since it is still very raw, I'd be glad to receive your?comments, suggestions and ideas!
>
> I'd say 1) stick to gray, viridis, and other reliable colormaps and 2) plot the found features so that they are easier to observe (currently just pixels inside a big image).
>
> You may also want to take a look at the segmentation lesson from the skimage_tutorial repo, which has a few sketches to clarify the workings of watershed.
>
> Best regards
> St?fan
>
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
> _______________________________________________
> scikit-image mailing list
> scikit-image at python.org
> https://mail.python.org/mailman/listinfo/scikit-image
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From imagepy at sina.com  Thu Sep 21 02:33:26 2017
From: imagepy at sina.com (imagepy at sina.com)
Date: Thu, 21 Sep 2017 14:33:26 +0800
Subject: [scikit-image] =?gbk?b?u9i4tKO6UmU6ICBteSB3YXRlcnNoZWQ=?=
Message-ID: <20170921063326.C8F9140157@webmail.sinamail.sina.com.cn>

add one:if scikit-image can implements a ridge filter. just like watershed mixed with the skeleton. make all region a same label, then do level loop, just stop when one pixel left. It's usful in geography and hydrology analysis.
----- ???? -----
????Juan Nunez-Iglesias <jni.soma at gmail.com>
????scikit-image <scikit-image at python.org>, imagepy at sina.com,  "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image at python.org>
???Re: [scikit-image] my watershed
???2017?09?21? 13?48?




Hi Yan,


Thanks for this. Simple functions are very good for one?s own images, as well as to understand an algorithm, but for a widely used library like scikit-image, flexibility and robustness are least as important as speed. In skimage, we aim to support floating point input images, for which your code won?t work. There is a lot of thought into edge cases going into the skimage implementation, which unfortunately could have an effect on performance. The question we need to solve isn?t ?can we make a super-fast watershed implementation?, but, ?can we make a flexible and robust implementation that is also fast?? Using Numba is certainly not off-limits, but any candidate implementation should at a minimum pass the skimage test suite.


I once tried a level-by-level implementation of watershed, by the way. It has a fatal flaw, which is that valleys with no markers will never get labeled. Here?s a test case that works with skimage but fails in your implementation. (Note also that your implementation overwrites the seeds image, which is pretty crazy. =)


Thanks again!


Juan.



In [44]: import watershed
In [45]: from skimage import morphology
In [46]: import numpy as np
In [47]: image = np.array([1, 0, 1, 0, 1, 0, 1], dtype=np.uint8)
In [48]: seeds = np.array([0, 1, 0, 0, 0, 2, 0])
In [49]: morphology.watershed(image, seeds)
Out[49]: array([1, 1, 1, 1, 2, 2, 2], dtype=int32)
In [50]: watershed.watershed(image, seeds)
Out[50]: array([0, 0, 0, 0, 0, 0, 0])
In [51]: seeds
Out[51]: array([0, 0, 0, 0, 0, 0, 0])




On 12 Sep 2017, 6:34 AM +1000, imagepy at sina.com, wrote:


Hi:
Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s.
It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast.


YXDragon
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https://mail.python.org/mailman/listinfo/scikit-image






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From jni.soma at gmail.com  Thu Sep 21 02:34:43 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 21 Sep 2017 16:34:43 +1000
Subject: [scikit-image] =?utf-8?Q?=E5=9B=9E=E5=A4=8D=EF=BC=9ARe=3A_?= my
 watershed
In-Reply-To: <20170921063326.C8F9140157@webmail.sinamail.sina.com.cn>
References: <20170921063326.C8F9140157@webmail.sinamail.sina.com.cn>
Message-ID: <2a789228-ef78-4535-9d0c-7ed2b3240d2f@Spark>

Actually this specific function has been on my mind for some time! Do you have a reference implementation, preferably in nD? =)

On 21 Sep 2017, 4:33 PM +1000, imagepy at sina.com, wrote:
> add one:
> if scikit-image can implements a ridge filter. just like watershed mixed with the skeleton. make all region a same label, then do level loop, just stop when one pixel left. It's usful in geography and hydrology analysis.
>
> ----- ???? -----
> ????Juan Nunez-Iglesias <jni.soma at gmail.com>
> ????scikit-image <scikit-image at python.org>, imagepy at sina.com, "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image at python.org>
> ???Re: [scikit-image] my watershed
> ???2017?09?21? 13?48?
>
> Hi Yan,
>
> Thanks for this. Simple functions are very good for one?s own images, as well as to understand an algorithm, but for a widely used library like scikit-image, flexibility and robustness are least as important as speed. In skimage, we aim to support floating point input images, for which your code won?t work. There is a lot of thought into edge cases going into the skimage implementation, which unfortunately could have an effect on performance. The question we need to solve isn?t ?can we make a super-fast watershed implementation?, but, ?can we make a flexible and robust implementation that is also fast?? Using Numba is certainly not off-limits, but any candidate implementation should at a minimum pass the skimage test suite.
>
> I once tried a level-by-level implementation of watershed, by the way. It has a fatal flaw, which is that valleys with no markers will never get labeled. Here?s a test case that works with skimage but fails in your implementation. (Note also that your implementation overwrites the seeds image, which is pretty crazy. =)
>
> Thanks again!
>
> Juan.
>
> In [44]: import watershed
> In [45]: from skimage import morphology
> In [46]: import numpy as np
> In [47]: image = np.array([1, 0, 1, 0, 1, 0, 1], dtype=np.uint8)
> In [48]: seeds = np.array([0, 1, 0, 0, 0, 2, 0])
> In [49]: morphology.watershed(image, seeds)
> Out[49]: array([1, 1, 1, 1, 2, 2, 2], dtype=int32)
> In [50]: watershed.watershed(image, seeds)
> Out[50]: array([0, 0, 0, 0, 0, 0, 0])
> In [51]: seeds
> Out[51]: array([0, 0, 0, 0, 0, 0, 0])
>
> On 12 Sep 2017, 6:34 AM +1000, imagepy at sina.com, wrote:
> > Hi:
> > Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s.
> > It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast.
> >
> > YXDragon
> > _______________________________________________
> > scikit-image mailing list
> > scikit-image at python.org
> > https://mail.python.org/mailman/listinfo/scikit-image
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From stefanv at berkeley.edu  Thu Sep 21 02:59:40 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Wed, 20 Sep 2017 23:59:40 -0700
Subject: [scikit-image] =?utf-8?b?5Zue5aSN77yaUmU6ICBDb2RlIGZvciB0aGUg?=
 =?utf-8?q?short_course_=27Image_Processing_using_Python=27=2C_=40_IAMG201?=
 =?utf-8?q?7?=
In-Reply-To: <9373f9f9-2ee5-4b0b-ad73-dd8304aea6ec@Spark>
References: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>
 <9373f9f9-2ee5-4b0b-ad73-dd8304aea6ec@Spark>
Message-ID: <1505977180.840036.1113324136.64FB1DB7@webmail.messagingengine.com>

On Wed, Sep 20, 2017, at 23:30, Juan Nunez-Iglesias wrote:
> I just noticed that the tutorials repo has no license. Oops! I suggest
> CC-BY. Technically we would need to ask all the contributors for their
> permission to put any new license on it.
Thanks, I never noticed!  All the lessons were contributed for teaching
purposes, so I don't imagine adding a license now would be a problem.
CC-BY is fine, although we should also consider CC-0.
St?fan

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From jni.soma at gmail.com  Thu Sep 21 03:17:17 2017
From: jni.soma at gmail.com (Juan Nunez-Iglesias)
Date: Thu, 21 Sep 2017 17:17:17 +1000
Subject: [scikit-image]
 =?utf-8?Q?=E5=9B=9E=E5=A4=8D=EF=BC=9ARe=3A__?=Code for the short course
 'Image Processing using Python', @ IAMG2017
In-Reply-To: <1505977180.840036.1113324136.64FB1DB7@webmail.messagingengine.com>
References: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>
 <9373f9f9-2ee5-4b0b-ad73-dd8304aea6ec@Spark>
 <1505977180.840036.1113324136.64FB1DB7@webmail.messagingengine.com>
Message-ID: <8ac1190f-24e1-4636-a1b4-2bc5c1e0e613@Spark>

On 21 Sep 2017, 5:00 PM +1000, Stefan van der Walt <stefanv at berkeley.edu>, wrote:

> Thanks, I never noticed! ?All the lessons were contributed for teaching purposes, so I don't imagine adding a license now would be a problem. ?CC-BY is fine, although we should also consider CC-0.

Sure. How about CC0 + adding a note in the readme, ?if you find these tutorials useful, we appreciate mentioning them in any derivative works.?
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From stefanv at berkeley.edu  Thu Sep 21 12:52:15 2017
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Thu, 21 Sep 2017 09:52:15 -0700
Subject: [scikit-image] =?utf-8?b?5Zue5aSN77yaUmU6ICBDb2RlIGZvciB0aGUg?=
 =?utf-8?q?short_course_=27Image_Processing_using_Python=27=2C_=40_IAMG201?=
 =?utf-8?q?7?=
In-Reply-To: <8ac1190f-24e1-4636-a1b4-2bc5c1e0e613@Spark>
References: <20170921061939.DEABF400FA@webmail.sinamail.sina.com.cn>
 <9373f9f9-2ee5-4b0b-ad73-dd8304aea6ec@Spark>
 <1505977180.840036.1113324136.64FB1DB7@webmail.messagingengine.com>
 <8ac1190f-24e1-4636-a1b4-2bc5c1e0e613@Spark>
Message-ID: <15ea55aa618.2815.acf34a9c767d7bb498a799333be0433e@fastmail.com>

On 21 September 2017 00:18:05 Juan Nunez-Iglesias <jni.soma at gmail.com> wrote:

> On 21 Sep 2017, 5:00 PM +1000, Stefan van der Walt <stefanv at berkeley.edu>, 
> wrote:
>
>> Thanks, I never noticed! ?All the lessons were contributed for teaching 
>> purposes, so I don't imagine adding a license now would be a problem. 
>> ?CC-BY is fine, although we should also consider CC-0.
>
> Sure. How about CC0 + adding a note in the readme, ?if you find these 
> tutorials useful, we appreciate mentioning them in any derivative works.?

That works, thanks!

St?fan
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