Hi Tony, I've heard that there has been a deadline extension (from people that were also behind schedule for submitting their tutorial :-), so I think it's still time to submit an abstract. Cheers, Emmanuelle On Mon, Apr 01, 2013 at 10:26:07PM -0500, Tony Yu wrote:
Emmanuelle, Thanks so much for passing along your proposal... Unfortunately, I got caught up with other things and didn't have time to put together a proposal for SciPy. :( -Tony
On Fri, Mar 29, 2013 at 2:51 AM, Emmanuelle Gouillart <[1]emmanuelle.gouillart@nsup.org> wrote:
Hi Tony,
I'm not going to SciPy 2013, but I've agreed to give a 1h30-long tutorial on image processing with scikit-image at Euroscipy 2013 (August 21-24). I'd happy to share course materials if you're interested.
I copy below the abstract I've given to the organizers.
Cheers, Emmanuelle
Image processing with scikit-image and the SciPy stack ======================================================
Numerical image processing involves the manipulation and transformation of images, often in order to extract information of interest from the images. NumPy nd-arrays provide an efficient container for image data, that can therefore be processed using the SciPy toolstack.
In this tutorial, we will first briefly see how simple operations on images (e.g. cropping, framing) can be performed using NumPy. More complex image processing operations will be handled principally by the scikit-image module (occasionally by the ndimage submodule of SciPy). Compared to other image processing modules for Python, scikit-image is designed to work transparently with numpy nd-arrays, and is written in pure Python and some Cython in order to promote readability and maintainability.
The different subtopics of this tutorial include:
* input and output of images (file formats...) * image enhancing / denoising * image segmentation (separating an image in labeled regions) * extraction of geometrical features (edges, lines, spheres, skeleton...) * extraction of features for image classification
This tutorial will consist mostly of hands-on examples; no mathematical justification of the algorithms will be given during the tutorial. Besides the main image processing tasks, the tutorial will demonstrate how NumPy advanced features (masks, broadcasting, manipulation of subsets of indices) and scikit-image utilities functions make image processing easier. The tutorial will also address the visualization of image processing results (contours, etc.).
On Thu, Mar 28, 2013 at 09:06:04PM -0500, Tony Yu wrote: > � �I was wondering if anyone has plans to submit a [1]tutorial proposal for > � �SciPy 2013. The proposal is due on Monday (Apr. 1st). It'd be great to > � �have scikit-image represented there; especially since medical imaging is > � �one of the mini-symposia topics. > � �If no one else is able, I'll probably submit something, but I have a > � �feeling that many of you have more (i.e. any) experience teaching image > � �processing than I do. > � �Cheers, > � �-Tony
Yes! The new deadline is on Monday 8th, so you are still on time. Francesc Al 06/04/13 13:49, En/na Emmanuelle Gouillart ha escrit:
Hi Tony,
I've heard that there has been a deadline extension (from people that were also behind schedule for submitting their tutorial :-), so I think it's still time to submit an abstract.
Cheers, Emmanuelle
On Mon, Apr 01, 2013 at 10:26:07PM -0500, Tony Yu wrote:
Emmanuelle, Thanks so much for passing along your proposal... Unfortunately, I got caught up with other things and didn't have time to put together a proposal for SciPy. :( -Tony On Fri, Mar 29, 2013 at 2:51 AM, Emmanuelle Gouillart <[1]emmanuelle.gouillart@nsup.org> wrote: Hi Tony, I'm not going to SciPy 2013, but I've agreed to give a 1h30-long tutorial on image processing with scikit-image at Euroscipy 2013 (August 21-24). I'd happy to share course materials if you're interested. I copy below the abstract I've given to the organizers. Cheers, Emmanuelle Image processing with scikit-image and the SciPy stack ====================================================== Numerical image processing involves the manipulation and transformation of images, often in order to extract information of interest from the images. NumPy nd-arrays provide an efficient container for image data, that can therefore be processed using the SciPy toolstack. In this tutorial, we will first briefly see how simple operations on images (e.g. cropping, framing) can be performed using NumPy. More complex image processing operations will be handled principally by the scikit-image module (occasionally by the ndimage submodule of SciPy). Compared to other image processing modules for Python, scikit-image is designed to work transparently with numpy nd-arrays, and is written in pure Python and some Cython in order to promote readability and maintainability. The different subtopics of this tutorial include: * input and output of images (file formats...) * image enhancing / denoising * image segmentation (separating an image in labeled regions) * extraction of geometrical features (edges, lines, spheres, skeleton...) * extraction of features for image classification This tutorial will consist mostly of hands-on examples; no mathematical justification of the algorithms will be given during the tutorial. Besides the main image processing tasks, the tutorial will demonstrate how NumPy advanced features (masks, broadcasting, manipulation of subsets of indices) and scikit-image utilities functions make image processing easier. The tutorial will also address the visualization of image processing results (contours, etc.). On Thu, Mar 28, 2013 at 09:06:04PM -0500, Tony Yu wrote: > � �I was wondering if anyone has plans to submit a [1]tutorial proposal for > � �SciPy 2013. The proposal is due on Monday (Apr. 1st). It'd be great to > � �have scikit-image represented there; especially since medical imaging is > � �one of the mini-symposia topics. > � �If no one else is able, I'll probably submit something, but I have a > � �feeling that many of you have more (i.e. any) experience teaching image > � �processing than I do. > � �Cheers, > � �-Tony
I'll have to give this another try, then. Thanks! -Tony On Sat, Apr 6, 2013 at 6:56 AM, Francesc Alted <francesc@continuum.io>wrote:
Yes! The new deadline is on Monday 8th, so you are still on time.
Francesc
Al 06/04/13 13:49, En/na Emmanuelle Gouillart ha escrit:
Hi Tony,
I've heard that there has been a deadline extension (from people that were also behind schedule for submitting their tutorial :-), so I think it's still time to submit an abstract.
Cheers, Emmanuelle
On Mon, Apr 01, 2013 at 10:26:07PM -0500, Tony Yu wrote:
Emmanuelle, Thanks so much for passing along your proposal... Unfortunately, I got caught up with other things and didn't have time to put together a proposal for SciPy. :( -Tony On Fri, Mar 29, 2013 at 2:51 AM, Emmanuelle Gouillart <[1]emmanuelle.gouillart@nsup.**org <emmanuelle.gouillart@nsup.org>> wrote: Hi Tony, I'm not going to SciPy 2013, but I've agreed to give a 1h30-long tutorial on image processing with scikit-image at Euroscipy 2013 (August 21-24). I'd happy to share course materials if you're interested. I copy below the abstract I've given to the organizers. Cheers, Emmanuelle Image processing with scikit-image and the SciPy stack ==============================**======================== Numerical image processing involves the manipulation and transformation of images, often in order to extract information of interest from the images. NumPy nd-arrays provide an efficient container for image data, that can therefore be processed using the SciPy toolstack. In this tutorial, we will first briefly see how simple operations on images (e.g. cropping, framing) can be performed using NumPy. More complex image processing operations will be handled principally by the scikit-image module (occasionally by the ndimage submodule of SciPy). Compared to other image processing modules for Python, scikit-image is designed to work transparently with numpy nd-arrays, and is written in pure Python and some Cython in order to promote readability and maintainability. The different subtopics of this tutorial include: * input and output of images (file formats...) * image enhancing / denoising * image segmentation (separating an image in labeled regions) * extraction of geometrical features (edges, lines, spheres, skeleton...) * extraction of features for image classification This tutorial will consist mostly of hands-on examples; no mathematical justification of the algorithms will be given during the tutorial. Besides the main image processing tasks, the tutorial will demonstrate how NumPy advanced features (masks, broadcasting, manipulation of subsets of indices) and scikit-image utilities functions make image processing easier. The tutorial will also address the visualization of image processing results (contours, etc.). On Thu, Mar 28, 2013 at 09:06:04PM -0500, Tony Yu wrote: > � �I was wondering if anyone has plans to submit a [1]tutorial proposal for > � �SciPy 2013. The proposal is due on Monday (Apr. 1st). It'd be great to > � �have scikit-image represented there; especially since medical imaging is > � �one of the mini-symposia topics. > � �If no one else is able, I'll probably submit something, but I have a > � �feeling that many of you have more (i.e. any) experience teaching image > � �processing than I do. > � �Cheers, > � �-Tony
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participants (3)
-
Emmanuelle Gouillart -
Francesc Alted -
Tony Yu