On 1/25/19 6:16 PM, Phillip Feldman wrote:

The documentation page (at http://smil.cmm.mines-paristech.fr/wiki/doku.php/doc/start) is currently empty.

Please follow links in the left menu : All links are OK, "Running SMIL under Python", lacks some contents.

On Fri, Jan 25, 2019 at 2:11 AM Jose-Marcio Martins da Cruz <jose-marcio.martins@mines-paristech.fr <mailto:jose-marcio.martins@mines-paristech.fr>> wrote:

Hi all,

I'm the maintainer of SMIL and I'd like to, eventually integrate SMIL into SciPy or Scikit-image.

Announcement: SMIL 0.9.1 ========================

I'm pleased to announce SMIL - Simple Morphological Image Library - v. 0.9.1

SMIL is a library with all basic and some advanced mathematical morphology features which can be extended with plugins and user modules.

Among its features it can handle 2D and 3D images and can handle data from/to NumPy data.

It's been developed in C++ and has a Python interface thanks to Swig.

SMIL is a product of CMM, the research Center of Mathematical Morphology of Mines-Paristech, where the discipline of Mathematical Morphology was created in the 60's by Jean Serra and Georges Matheron.

SMIL is distributed with GPL license.

We use SMIL in our research and teaching activities in the field.

You can find SMIL - binaries and documentation - at our web site :

http://smil.cmm.mines-paristech.fr

or the source code at :

https://github.com/ensmp-cmm/smil

Thanks

Jose-Marcio

--

  ---------------------------------------------------------------   Jose Marcio MARTINS DA CRUZ, Ph.D.   Ecole des Mines de Paris   CMM - Centre de Morphologie Mathématique   ---------------------------------------------------------------       Spam : http://amzn.to/LEscRu ou http://bit.ly/SpamJM   ---------------------------------------------------------------

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On 25/01/2019 21:39, Phillip Feldman wrote:

When I click on the Tutorials link, I get the following "This topic does not exist yet".  It would be good to have 3-4 sentences of top-level explanation about what this package does and why someone would want to use it.

Thanks for the suggestion. The Python part of the documentation is still under construction. The documentation of the C++ is OK, thanks do Doxygen. The python part is being build based on this, with the same structure, but it isn't enough. Hopefully, all this will be OK as soon as possible. The source code is still being improved with more advanced algorithms, like stochastic Watershed, Bilateral Filtering, and so.

On Fri, Jan 25, 2019 at 10:58 AM Jose-Marcio Martins da Cruz <Jose-Marcio.Martins@mines-paristech.fr <mailto:Jose-Marcio.Martins@mines-paristech.fr>> wrote:

On 1/25/19 6:16 PM, Phillip Feldman wrote: > The documentation page (at http://smil.cmm.mines-paristech.fr/wiki/doku.php/doc/start) is currently empty.

Please follow links in the left menu : All links are OK, "Running SMIL under Python", lacks some contents.

> > On Fri, Jan 25, 2019 at 2:11 AM Jose-Marcio Martins da Cruz <jose-marcio.martins@mines-paristech.fr <mailto:jose-marcio.martins@mines-paristech.fr> > <mailto:jose-marcio.martins@mines-paristech.fr <mailto:jose-marcio.martins@mines-paristech.fr>>> wrote: > > >     Hi all, > >     I'm the maintainer of SMIL and I'd like to, eventually integrate SMIL into SciPy or Scikit-image. > >     Announcement: SMIL 0.9.1 >     ======================== > >     I'm pleased to announce SMIL - Simple Morphological Image Library - v. 0.9.1 > >     SMIL is a library with all basic and some advanced mathematical morphology features which can be extended with plugins >     and user modules. > >     Among its features it can handle 2D and 3D images and can handle data from/to NumPy data. > >     It's been developed in C++ and has a Python interface thanks to Swig. > >     SMIL is a product of CMM, the research Center of Mathematical Morphology of Mines-Paristech, where the discipline of >     Mathematical Morphology was created in the 60's by Jean Serra and Georges Matheron. > >     SMIL is distributed with GPL license. > >     We use SMIL in our research and teaching activities in the field. > >     You can find SMIL - binaries and documentation - at our web site : > > http://smil.cmm.mines-paristech.fr > >     or the source code at : > > https://github.com/ensmp-cmm/smil > >     Thanks > >     Jose-Marcio > >     -- > >        --------------------------------------------------------------- >        Jose Marcio MARTINS DA CRUZ, Ph.D. >        Ecole des Mines de Paris >        CMM - Centre de Morphologie Mathématique >        --------------------------------------------------------------- >            Spam : http://amzn.to/LEscRu ou http://bit.ly/SpamJM >        --------------------------------------------------------------- > >     _______________________________________________ >     SciPy-Dev mailing list > SciPy-Dev@python.org <mailto:SciPy-Dev@python.org> <mailto:SciPy-Dev@python.org <mailto:SciPy-Dev@python.org>> > https://mail.python.org/mailman/listinfo/scipy-dev >

-- --------------------------------------------------------------- Jose Marcio MARTINS DA CRUZ, Ph.D. Ecole des Mines de Paris CMM - Centre de Morphologie Mathématique --------------------------------------------------------------- Spam : http://amzn.to/LEscRu ou http://bit.ly/SpamJM ---------------------------------------------------------------

Hi Stefan, On 1/29/19 12:44 AM, Stefan van der Walt wrote:

Hi Jose-Marcio,

On Fri, 25 Jan 2019 11:10:44 +0100, Jose-Marcio Martins da Cruz wrote:

...

I'm pleased to announce SMIL - Simple Morphological Image Library - v. 0.9.1

Neat and compact little library; congratulations on the release!

Thanks,

...

SMIL is distributed with GPL license.

Note that the website currently states BSD.

Sorry, you're right !

Is there any reason you are not using standard NumPy arrays to represent data, or at least return those from the Python API? E.g., the following code would feel very foreign to someone used to Python:

For the moment, you can go back and forth from NumPy. See below. Some internal users are asking for this, but... The library was optimized to have better performance with data in the usual matrix structure. We could surely rewrite all this, as was done by OpenCV, but There will surely have a performance loss. NumPy data structures are very flexible at the cost of some complexity. But we're thinking in how to implement it in some clever way.

...

...

...

im3D = sp.Image(im2.getWidth(), im2.getHeight(), 3) im3D << 0 sp.copy(im1, 0, 256, im3D) sp.copy(im3, im3D, 0, 0, 2)

<rem> Sorry, this part isn't yet documented in the web site. </rem> * to create an image from numpy data : im.fromNumArray(npArr) * to get a numpy pointer from an Image : npArr = im.getNumArray() Related to this, there are floating point images. In Morphology, we don't need this as only ordered sets matter, not the real values. Some people (medical or materials) handling 3D images from scanners convert them to 32 bits before doing Morpho operations on them. But we need to have an answer to this.

Usage of the `lena` image is somewhat frowned upon nowadays, so you may want to consider replacing that with another image. In skimage, we use astronaut Eileen Collins:

https://github.com/scikit-image/scikit-image/blob/v0.14.2/skimage/data/astro...

Thanks. This is an interesting image. I'll add some examples with this. Thanks a lot for your comments. Best regards José-Marcio

Best regards, Stéfan