release: scikit-image 0.12 is out!
Announcement: scikit-image 0.12 =============================== The scikit-image team is very pleased to announce the release of version 0.12 of scikit-image. scikit-image is an image processing toolbox for Python and SciPy, that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more, for 2-D and 3-D (sometimes n-D) images. For more information, examples, and documentation, please visit our website: http://scikit-image.org and our example gallery http://scikit-image.org/docs/dev/auto_examples/ This release includes new features such as image inpainting, seam carving, image comparison metrics, and a parallelization framework based on dask. The release has also improved the support of 3-D images, with 3-D skeletonization, 3-D phantom data. and partial support of measure.regionprops for 3-D images. Also note that the handling of background pixels by measure.label, a function labeling connected components, has changed to be consistent with scipy.ndimage.label. For this release, we merged over 200 pull requests from 64 contributors, with bug fixes, cleanups, improved documentation and new features. Release notes are available on http://scikit-image.org/docs/0.12.x/release_notes_and_installation.html#rele... and include a more detailed list of changes, and the complete list of contributors to this release. The release can be downloaded on PyPi https://pypi.python.org/pypi/scikit-image or directly installed using pip pip install --upgrade scikit-image Please let us know any issues you might have on the issue tracker https://github.com/scikit-image/scikit-image/issues Many thanks to all the developers who made this release possible, and a warm welcome to our new contributors. Happy image processing! The scikit-image team
hi Emmanuel, I need help with installation of the latest version of scikit image(the version I have is 0.11.3 kindly find attached). I currently run Ubuntu 14.04 LTS and running python 3.4.3. I'm not sure if sudo apt-get build-dep python-scikit-image is the way to go or if pip install --upgrade scikit-image do the necessary upgrade for me. Any guidance will be highly appreciated. Thank you. On Monday, 7 March 2016 13:50:11 UTC-8, Emmanuelle Gouillart wrote:
Announcement: scikit-image 0.12 ===============================
The scikit-image team is very pleased to announce the release of version 0.12 of scikit-image.
scikit-image is an image processing toolbox for Python and SciPy, that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more, for 2-D and 3-D (sometimes n-D) images.
For more information, examples, and documentation, please visit our website:
and our example gallery
http://scikit-image.org/docs/dev/auto_examples/
This release includes new features such as image inpainting, seam carving, image comparison metrics, and a parallelization framework based on dask. The release has also improved the support of 3-D images, with 3-D skeletonization, 3-D phantom data. and partial support of measure.regionprops for 3-D images. Also note that the handling of background pixels by measure.label, a function labeling connected components, has changed to be consistent with scipy.ndimage.label.
For this release, we merged over 200 pull requests from 64 contributors, with bug fixes, cleanups, improved documentation and new features. Release notes are available on
http://scikit-image.org/docs/0.12.x/release_notes_and_installation.html#rele... and include a more detailed list of changes, and the complete list of contributors to this release.
The release can be downloaded on PyPi https://pypi.python.org/pypi/scikit-image or directly installed using pip
pip install --upgrade scikit-image
Please let us know any issues you might have on the issue tracker https://github.com/scikit-image/scikit-image/issues
Many thanks to all the developers who made this release possible, and a warm welcome to our new contributors.
Happy image processing! The scikit-image team
Hi Raphael, I don't think we have an Ubuntu package yet for 0.11. The way to go would be to use pip, with "pip install --upgrade scikit-image". Cheers, Emma On Wed, Apr 27, 2016 at 04:59:41PM -0700, Raphael Okoye wrote:
hi Emmanuel,
Â
 I need help with installation of  the latest version of scikit image(the version I have is 0.11.3 kindly find attached). I currently run Ubuntu 14.04 LTS and running python 3.4.3. I'm not sure if   sudo apt-get build-dep python- scikit-image    is the way to go or ifÂ
pip install --upgrade scikit-image do the necessary upgrade for me.  Any guidance will be highly appreciated.Â
Thank you.
On Monday, 7 March 2016 13:50:11 UTC-8, Emmanuelle Gouillart wrote:
Announcement: scikit-image 0.12 ===============================
The scikit-image team is very pleased to announce the release of version 0.12 of scikit-image.
scikit-image is an image processing toolbox for Python and SciPy, that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more, for 2-D and 3-D (sometimes n-D) images.
For more information, examples, and documentation, please visit our website:
and our example gallery
This release includes new features such as image inpainting, seam carving, image comparison metrics, and a parallelization framework based on dask. The release has also improved the support of 3-D images, with 3-D skeletonization, 3-D phantom data. and partial support of measure.regionprops for 3-D images. Also note that the handling of background pixels by measure.label, a function labeling connected components, has changed to be consistent with scipy.ndimage.label.
For this release, we merged over 200 pull requests from 64 contributors, with bug fixes, cleanups, improved documentation and new features. Release notes are available on http://scikit-image.org/docs/0.12.x/release_notes_and_installation.html# release-notes and include a more detailed list of changes, and the complete list of contributors to this release.
The release can be downloaded on PyPi https://pypi.python.org/pypi/scikit-image or directly installed using pip
pip install --upgrade scikit-image
Please let us know any issues you might have on the issue tracker https://github.com/scikit-image/scikit-image/issues
Many thanks to all the developers who made this release possible, and a warm welcome to our new contributors.
Happy image processing! The scikit-image team
Sorry, I meant for 0.12. Morning answers before coffee are not reliable :-) On Thu, Apr 28, 2016 at 08:43:44AM +0200, Emmanuelle Gouillart wrote:
Hi Raphael,
I don't think we have an Ubuntu package yet for 0.11. The way to go would be to use pip, with "pip install --upgrade scikit-image".
Cheers, Emma
On Wed, Apr 27, 2016 at 04:59:41PM -0700, Raphael Okoye wrote:
hi Emmanuel,
Â
 I need help with installation of  the latest version of scikit image(the version I have is 0.11.3 kindly find attached). I currently run Ubuntu 14.04 LTS and running python 3.4.3. I'm not sure if   sudo apt-get build-dep python- scikit-image    is the way to go or ifÂ
pip install --upgrade scikit-image do the necessary upgrade for me.  Any guidance will be highly appreciated.Â
Thank you.
On Monday, 7 March 2016 13:50:11 UTC-8, Emmanuelle Gouillart wrote:
Announcement: scikit-image 0.12 ===============================
The scikit-image team is very pleased to announce the release of version 0.12 of scikit-image.
scikit-image is an image processing toolbox for Python and SciPy, that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more, for 2-D and 3-D (sometimes n-D) images.
For more information, examples, and documentation, please visit our website:
and our example gallery
This release includes new features such as image inpainting, seam carving, image comparison metrics, and a parallelization framework based on dask. The release has also improved the support of 3-D images, with 3-D skeletonization, 3-D phantom data. and partial support of measure.regionprops for 3-D images. Also note that the handling of background pixels by measure.label, a function labeling connected components, has changed to be consistent with scipy.ndimage.label.
For this release, we merged over 200 pull requests from 64 contributors, with bug fixes, cleanups, improved documentation and new features. Release notes are available on http://scikit-image.org/docs/0.12.x/release_notes_and_installation.html# release-notes and include a more detailed list of changes, and the complete list of contributors to this release.
The release can be downloaded on PyPi https://pypi.python.org/pypi/scikit-image or directly installed using pip
pip install --upgrade scikit-image
Please let us know any issues you might have on the issue tracker https://github.com/scikit-image/scikit-image/issues
Many thanks to all the developers who made this release possible, and a warm welcome to our new contributors.
Happy image processing! The scikit-image team
hi Emmanuelle, hehehe...hope u have your coffee now..Thanks for the reply. So pip install --upgrade scikit-image will land me in which version? 0.12.0? On the announcements on the website http://scikit-image.org/ it seems that's the latest stable version (although the right top corner of the page says 0.12.3 is the latest) . On 27 April 2016 at 23:45, Emmanuelle Gouillart < emmanuelle.gouillart@nsup.org> wrote:
Sorry, I meant for 0.12. Morning answers before coffee are not reliable :-)
On Thu, Apr 28, 2016 at 08:43:44AM +0200, Emmanuelle Gouillart wrote:
Hi Raphael,
I don't think we have an Ubuntu package yet for 0.11. The way to go would be to use pip, with "pip install --upgrade scikit-image".
Cheers, Emma
On Wed, Apr 27, 2016 at 04:59:41PM -0700, Raphael Okoye wrote:
hi Emmanuel,
I need help with installation of the latest version of scikit image(the version I have is 0.11.3 kindly find attached). I currently run Ubuntu 14.04 LTS and running python 3.4.3. I'm not sure if sudo apt-get build-dep python- scikit-image is the way to go or if
pip install --upgrade scikit-image do the necessary upgrade for me. Any guidance will be highly appreciated.
Thank you.
On Monday, 7 March 2016 13:50:11 UTC-8, Emmanuelle Gouillart wrote:
Announcement: scikit-image 0.12 ===============================
The scikit-image team is very pleased to announce the release of
version
0.12 of scikit-image.
scikit-image is an image processing toolbox for Python and SciPy,
that
includes algorithms for segmentation, geometric transformations,
color > > space manipulation, analysis, filtering, morphology, feature detection, > > and more, for 2-D and 3-D (sometimes n-D) images.
For more information, examples, and documentation, please visit our website:
and our example gallery
This release includes new features such as image inpainting, seam carving, image comparison metrics, and a parallelization framework
based
on dask. The release has also improved the support of 3-D images,
with
3-D skeletonization, 3-D phantom data. and partial support of measure.regionprops for 3-D images. Also note that the handling of background pixels by measure.label, a function labeling connected components, has changed to be consistent with scipy.ndimage.label.
For this release, we merged over 200 pull requests from 64
contributors,
with bug fixes, cleanups, improved documentation and new features. Release notes are available on
http://scikit-image.org/docs/0.12.x/release_notes_and_installation.html#
release-notes and include a more detailed list of changes, and the complete list
of
contributors to this release.
The release can be downloaded on PyPi https://pypi.python.org/pypi/scikit-image or directly installed
using pip
pip install --upgrade scikit-image
Please let us know any issues you might have on the issue tracker https://github.com/scikit-image/scikit-image/issues
Many thanks to all the developers who made this release possible,
and a
warm welcome to our new contributors.
Happy image processing! The scikit-image team
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participants (2)
-
Emmanuelle Gouillart -
Raphael Okoye