Mailman 3 November 2014 - scikit-image

Re: skimage and opencv
by Emmanuelle Gouillart 22 Sep '16

22 Sep '16

Hi FranÃ¯Â¿Â½ois, that's an excellent question, and not a troll :-). Opencv is a very powerful library, but it focuses primarily on computer vision (feature detection and extraction, classification, ...), as opposed to image processing in general (with other tasks such as denoising, segmentation, ...). The other big difference is that skimage builds on numpy ndarrays, and uses the full power of the numpy API (including of course the basic facilities for processing arrays as images that come with numpy), as well as some of scipy functions (you could have added scipy.ndimage to your list -- a few functions in skimage are wrappers around scipy.ndimage, that exist for the sake of completeneness). One important consequence is that algorithms working for 3-d or even n-d images can be easily implemented in 3-d/n-d in skimage, whereas opencv is restricted to 2-D images (as far as I know). Thanks to the use of numpy arrays, the API of skimage is also quite pleasant for a numpy user, more than the API of opencv. A related difference is that skimage is written in python and cython, whereas opencv is a C++ library. The two libraries attract a different crowd of developers, and a Python/Cython toolkit based on numpy arrays is easier to develop and maintain inside the Scientific Python ecosystem. I'm sure that other devs/users will have things to add to this discussion! Cheers, Emmanuelle On Thu, Dec 27, 2012 at 02:06:08PM -0800, FranÃ¯Â¿Â½ois wrote: > Hi users and devs, > It came to my knowledge that another python library (based on C++ and C > codes) for image processing exists too : opencv > I understand that numpy intregrates some basic features and we need some > advanced features but I have the feeling that skimages is redoundant with > opencv in some ways. > What's the position of skimage about that? (Don't read this question as a > troll but like a real question). > I mean that similar features exist in both. Would not be possible to > reuse/integrate opencv or merge? what's the reason for keeping them apart? > My observation is there is 4 libraries to manipulate images: > * PIL > * numpy > * skimages > * opencv > That's a lot. > Cheers,

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Problems with coordinate ranges when doing conversion from LCH to LAB to RGB
by Matteo 16 Nov '15

16 Nov '15

A while ago I wrote a post on my blog with code on how to import in Python a colour palette in an ASCII file and convert it to a Matplotlib colormap: mycarta.wordpress.com/2014/04/25/convert-color-palettes-to-python-matplotli… Following that post I wrote a tutorial on a geoscience magazine on how to evaluate and compare colormaps using Python: wiki.seg.org/wiki/How_to_evaluate_and_compare_color_maps In the accompanying notebook I show how to convert a 256x3 RGB colormap to a 256x256x3 RGB image, then convert it to CIELAB using scikit-image's rgb2lab, then plot the 256x1 lightness (L) array to evaluate the colormaps perceptually. You can read the relevant extract of the notebook using this nbviewer link: http://nbviewer.ipython.org/urls/dl.dropbox.com/s/54zoax2qesb71wn/evaluate_… In that case scikit-image worked really well for me. Now I am trying to follow up with a new tutorial and I run into problems with the color space conversions. You can follow what I am trying to do in this other notebook extract: http://nbviewer.ipython.org/urls/dl.dropbox.com/s/noli66nzrlk0676/make_colo… The goal of this new tutorial is to show how to build colormaps from scratch using perceptual principles. I design a color palette in LCH (polar version of CIELAB) by keeping Chroma and Lightness fixed and interpolating Hue around the circle, then convert to LAB, then to RGB. As far as I know the code I wrote should work, but the result is a black colormap. I am thinking I got wrong one or more of the ranges for the LCH coordinates. I assumed L between (0,1), Ch between (0,1), and H between (0, 2*pi). Is that wrong, and if that's the case, what are the ranges? Many of them are not stated clearly in the documentation in here: http://scikit-image.org/docs/dev/api/skimage.color.html Is it possible to update the documentation to clearly state all ranges for all colour spaces. Thanks for your help. Matteo

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ANN: imageio v1.0
by Almar Klein 03 Jul '15

03 Jul '15

Hi all, I'm pleased to announce version 1.0 of imageio - a library for reading and writing images. This library started as a spin-off of the freeimage plugin in skimage, and is now a fully-fledged library with unit tests and all. Imageio provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 2.x and 3.x, and is easy to install. Imageio is plugin-based, making it easy to extend. It could probably use more scientific formats. I welcome anyone who's interested to contribute! install: pip install imageio website: http://imageio.github.io release notes: http://imageio.readthedocs.org/en/latest/releasenotes.html Regards, Almar

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Example: Scikit-image and trackpy (bubble tracking in foams)
by François Boulogne 25 Mar '15

25 Mar '15

Hi, Just for your information, I wrote an example based on my research to show the use of scikit-image with trackpy for feature detection and tracking. http://nbviewer.ipython.org/github/soft-matter/trackpy-examples/blob/master… Hopefully, this might be helpful for future workshops or presentations. Best, -- François Boulogne. http://www.sciunto.org GPG: 32D5F22F

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Image warping using transform.PolynomialTransform: crazy results
by Herve Bouy 04 Dec '14

04 Dec '14

Hi, I found very few examples for transform.PolynomialTransform on the internet so I hope someone in this group can help me understand what I am doing wrong. If it's not the right place to ask for help, please forgive me! Here is my problem. I have a greyscale image with some curved lines. I want to transform it so the lines become straight. <https://lh3.googleusercontent.com/-l7PV-L6ZCek/VGsf6aKWYpI/AAAAAAAABSk/Pae2…> So I measure the position of the lines at regular intervals (in the attached file source_test2.csv) And compute the desired positions after transformation (in the attached file destination_test2.csv) So i have a nice set of input points and their correspondences as in the figure below (red = input points, and blue = desired positions after transformation): <https://lh4.googleusercontent.com/-2SjXbAQwJHU/VGsi-bqv8OI/AAAAAAAABSw/Jsni…> Next I compute the transformation using skimage.transform.PolynomialTransform and a polynomial of order 2, and apply the transformation to get the warped image using skimage.transform.warp But the warped image is completely crazy! See below: <https://lh3.googleusercontent.com/-VZmvMqQjNTo/VGsjdSpuklI/AAAAAAAABS4/OsAH…> It seems the transformation found by PolynomialTransform is completely wrong... *Note that I managed to get a good transformation in some cases for sub-images (e.g using the first 400 columns only).* What am I doing wrong? Are PolynomialTransform too unstable? Do I need a regular grid? I attach the code I use (warp.py) Thanks for your help! Hervé

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Sobel
by Johannes Schoenberger 29 Nov '14

29 Nov '14

Hi, Why are we returning the absolute values in the hsobel and vsobel functions? I do not see the benefit. Johannes

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Rotation with scpecification of the center ?
by Julien Derr 28 Nov '14

28 Nov '14

Hi everyone, this is my first post here, so I am really a newbie... I haev seen on the doc that it is possible to specify the center of rotation (http://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transfo…) with rotate(image2,90 , resize=False, order=1, mode='constant', cval=0.0, center=(1140,1383)) but my computer doesn't seem very happy with this parameter center : rotate() got an unexpected keyword argument 'center' how can I specify the center of rotation ? thanks a lot, Julien

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Re: Sobel
by Johannes Schoenberger 27 Nov '14

27 Nov '14

I note this and hopefully I will be able to submit a PR over the next days. > On Nov 20, 2014, at 5:21 AM, Stéfan van der Walt <stefan(a)sun.ac.za> wrote: > > Nice suggestion, Tony. > > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/d/optout.

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Re: OK to upload OSX wheels for 10.10?
by Stéfan van der Walt 27 Nov '14

27 Nov '14

Hi Matthew On Nov 27, 2014 2:41 AM, "Matthew Brett" <matthew.brett(a)gmail.com> wrote: > > I'd like to upload new wheeels to pypi (which are just rebuilt copies > of the old one) with the longer filenames, as in: > > scikit_image-0.10.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > > etc. I propose to leave the old ones there in case anyone is > depending on them. Is that OK with y'all? Thanks very much! Please go ahead. Stéfan

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OK to upload OSX wheels for 10.10?
by Matthew Brett 27 Nov '14

27 Nov '14

Hi, OSX is now at 10.10, and the current wheels won't get installed by system python, homebrew or macports on 10.10, because they lack the relevant bits to their filenames. Specifically the wheel files need to have the text "macosx_10_10_intel.macosx_10_10_x86_64" in their filename. I'd like to upload new wheeels to pypi (which are just rebuilt copies of the old one) with the longer filenames, as in: scikit_image-0.10.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl etc. I propose to leave the old ones there in case anyone is depending on them. Is that OK with y'all? Cheers, Matthew

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