scikit-image July 2012

scikit-image@python.org

15 participants
43 discussions

Re: Bundling scikits-image using pyinstaller
by Stéfan van der Walt 31 Jul '12

31 Jul '12

Hi Nicklas On Jul 31, 2012 9:30 AM, "Nicklas Nordenmark" <nordenmark(a)gmail.com> wrote: > > Heya, I'm trying to bundle an application that's using scikits-image and other libraries but I'm running into problems (see this Stackoverflow thread for a more detailed description of the problem: http://stackoverflow.com/questions/11719292/error-when-bundling-application… ). Is there any way of locating files in such a distribution? If so, we can incorporate it in the plugin loader. Regards Stéfan

1 0

Re: Bug in regionprops
by Stéfan van der Walt 31 Jul '12

31 Jul '12

Hi Jeff On Jul 31, 2012 9:07 AM, "jeff witz" <witzjean(a)gmail.com> wrote: > > I must use regionprops in order to identify a lot of el > > Hello, > > I must use regionprops in order to identify a lot of ellipse in a picture. > I have constated a mistake in the implementation of the 'Orientation' > identification. > in skimage/measure/_regionprops.py at line 298 the function atan is used > to recover the angle. In my case I constate that a lot of the ellipse are > correctly identified using atan, but in some cases the 'MinorAxisLength' > and the 'MajorAxisLength' are swapped. You can solve this issue using the > atan2 function that take into account the trigonometric quadrant. > > Best Regards, > > > >

1 0

Qt-MPL image viewer
by Tony Yu 28 Jul '12

28 Jul '12

So I've been hacking on a new implementation of an image-viewer/interactive-image-processor. See PR 229: https://github.com/scikits-image/scikits-image/pull/229 The previous implementation was written purely in Matplotlib, partly for portability. Unfortunately, I found this implementation a bit limiting because Matplotlib doesn't provide quite-enough widget support. In addition, there was no way to add custom toolbars or menus without getting toolkit-specific. So, I've added a new implementation that requires PyQt but also uses Matplotlib because of the wealth of plotting functionality that it provides. There's a lot that I added in my original implementation that needs to be updated for this implementation (an image collection viewer, and Guillaume Gay's contrast setter and line-profile plugins). I'm of the opinion, however, that these should be implemented later in order to reduce the work to review this PR (that's actually why I moved the line profile plugin<https://github.com/tonysyu/scikits-image/blob/qtmpl-lineprofile/skimage/vie…>to a separate branch). Overall, I'm pretty happy with the current implementation. The basic idea is that there's a viewer class (to view images, of course). You can then connect plugins to the viewer, which typically calls some sort of filter function, but that's in no way a requirement (for example, the line-profile plugin measures values in the image). Also, there are widgets that get attached to these plugins (currently, just a slider and a combo box) to adjust filtering or plugin parameters. There are two ways to implement a plugin: The first is by subclassing the base `Plugin` class<https://github.com/tonysyu/scikits-image/blob/qtmpl-viewer/skimage/viewer/p…>. The second (which I shamelessly stole from Bokeh) instantiates a plugin and just adds widgets<https://github.com/tonysyu/scikits-image/blob/qtmpl-viewer/viewer_examples/…>(using the addition operator) to control filter parameters. The first is probably more flexible, while the second is convenient for people who may not be as comfortable with object-oriented programming (plus I think it reads really well). It's a big PR, but I'd really appreciate comments and suggestions. Cheers, -Tony P.S. Stefan: In a separate branch, I've added the Hough Transform plugin you so desired. Right now it's a little hacky, partly because I haven't yet built the infrastructure to support this type of plot (not only does it plot an overlay but also Matplotlib lines; in addition, parameters have to be delegated to two different functions). Nevertheless, the implementation is surprisingly short<https://github.com/tonysyu/scikits-image/blob/qtmpl-houghplugin/viewer_exam…>, despite not adding anything else to support this use case.

1 0

Re: Relation with computer vision and machine learning
by Andreas Mueller 27 Jul '12

27 Jul '12

Hi Wei. > Thanks for your reply! I see your great work in scikits-learn and your > comments are quite useful. > Thanks :) > Many will overlap, I think we can maintain a list. As a quick example > in the following: There is no discussion that machine learning methods are helpful for vision problems and that vision problems are an important application domain for machine learning tools. The question is if there is something you would like in skimage that would require the use of something from sklearn. I.e. what algorithm you want in skimage is only useful together with something from sklearn? I don't think any of your examples are in this category. Which is well enough, since this means it should be easy to keep the two things separate ;) Btw, MRFs in vision are often not learned, so this is no ML, just optimization. And I would rather place that in skimage, as it is quite image specific. When I talked about graph-cuts, that's what I meant. Normalized cuts are of limited use in low level vision since they are very slow for superpixels. I was rather thinking of Boykov-Kolmogorov push-relabel - which is my next project when I get my superpixels done. (Stefan actually mentioned he'd like to have it :) Abour RBMs: I am <http://www.ais.uni-bonn.de/deep_learning/papers/ESANN10_schulz.pdf> no <http://www.ais.uni-bonn.de/deep_learning/papers/IJCNN10_mueller.pdf> stranger <http://www.ais.uni-bonn.de/%7Eschulz/publications/papers/nips10ws_schulz_mu…> to them <http://www.ais.uni-bonn.de/%7Eschulz/publications/papers/neurocomp11_schulz…> but I would rather not include them in sklearn and definitely not in skimage. Cheers, Andy

2 1

Re: Relation with computer vision and machine learning
by Andreas Mueller 25 Jul '12

25 Jul '12

Hi Wei. While I'm not so active in skimage at the moment, I am very interested in how to connect sklearn and skimage. I think at the moment the best approach would be to leave the two packages independent but try not to reimplement to much. Many of the ML methods applied to images can be made much more efficient for images, so reimplementing these is definitely worth it. For example image segmentation algorithms often build on clustering algorithms (like the one you mentioned) but they can be made much faster by only considering local neighborhoods. (which is why I work on #206 <https://github.com/scikits-image/scikits-image/pull/206>) In most cases that I am interested in the "higher level" ML sort of "wraps around" the CV, as for example with descriptors and classification. I would place all descriptors in skimage but skimage doesn't need sklearn as a dependence for me to be able to use an SVM on them. Do you have more examples where sklearn and skimage might overlap? I was actually wondering about doing a grab-cut implementation which needs Gaussian mixture models. But before I get there, we need graph cuts in skimage ;) Cheers, Andy On 07/24/2012 08:09 AM, LI, Wei wrote: > Dear ALL: > > I am new to scikits-image and I am not sure the intended coverage of > this package. Seems digital image processing using a signal processing > view is quite mature but there are also trends where methods from > statistical learning theory and computer vision are adpated into > solving standard digial image processing tasks just like using > learning method to do super resolution, image denoising. There are > also some discussion in this forum that are related to computer vision > like the object detection. As far as I know, there is one scikits > package as the scikits-learn implementing many machine learning > algorithm. When we need some functions to perform some tasks whether > we need to reimplement some functions or just to use another package > as a denepdence? > > As I am a computer vision researcher I find this package by searching > for available implementation for hog features in python. Just > wondering whether some modules I can help to implement for this as I > have already gotten help from package :-). But I have some questions > when picturing whether I can take the tasks in the wiki page > http://scikits-image.org/docs/dev/contribute.html . For example the > graph-cut based segmentation. As we know, the graph cut base algorithm > based mainly on graph-based clustering method. Such method is > implemented in various packages and is in scikits-learn > http://scikit-learn.org/dev/modules/generated/sklearn.cluster.SpectralClust…. > > Then we have two choices, > 1. Write one JUST for image clustering in this package (Pros: self > contained package, Cons: cannot get updated when clustering methods > are updated) > 2. Include the sklearn as a dependence, adapt the mehtods in that > package, and write a routine that just build the graph from the image > ,throw it to sklearn to solve the learning problem and convert the > result back? > > As more and more papers in standard image processing conference like > ICIP, using the statistical learning method, furthuer implementations > may have more functions need the machine learning as subroutines. So > what is the indented choice from the founders of this package? > > Best, > Wei

2 1

Re: error in skimage.feature.hog
by Brian Holt 23 Jul '12

23 Jul '12

Any other comments on this PR? I think its ready to merge. Brian

1 0

Colorspace conversions RGB, XYZ, Lab
by Andreas Mueller 21 Jul '12

21 Jul '12

Hi everybody. I wanted to look into doing a RGB2Lab conversion in skimage but I got a bit confused with the different color spaces. The standard method to go from RGB to Lab seems to be via XYZ. I compared the way that RGB2XYZ is done in scikits-image, vl_feat and the SLIC code, and they seem to be three different ways. As I want to use Lab for the segmentation methods by the vl_feat authors and SLIC, I feel this is a bit unfortunate. The difference between wikipedia, skimage and vl_feat seems to be that vl_feat does a gamma-correction of 2.2. SLIC does something else that I don't really understand. Could someone help me understand the differences so that I can try and reproduce other peoples' results? Cheers, Andy

1 0

Re: Filterbank code
by Andreas Mueller 19 Jul '12

19 Jul '12

Hey Stefan. > No, but I recently saw some activity at: > > https://github.com/nigma/pywt > http://www.pybytes.com/pywavelets/ > > > > Cool, thanks. > >>> By the way, you mentioned you are interested in matting. >>> I'm working on the alphamatting.com dataset this week :) >> Ah, fantastic! Are you implementing their paper? > I'm working with Carsten Rother and we are doing super fancy super > secret things ;) Cool, thanks. >> By the way, you mentioned you are interested in matting. >> I'm working on the alphamatting.com dataset this week :) > Ah, fantastic! Are you implementing their paper? The paper compare a lot of methods, right? Which one do you mean? I'm working with Carsten Rother and we are doing super fancy super secret things ;) Basically it's an extension of an upcoming ECCV paper on Decision Tree Fields. > >> OT: Sorry for not finishing up my segmentation PR. >> It is quite mature but I wanted to compare it to the standard >> implementations. But for that I need Lab color space conversions, >> which I didn't get around doing yet. > I'll add Lab color space conversion to the todo list for Friday's SciPy sprint. Thanks, that would be great. I'll try to do it myself but I'm pretty swamped with work atm. Cheers, Andy

1 0

Re: Filterbank code
by Andreas Mueller 18 Jul '12

18 Jul '12

Hey Stefan. Actually I don't know how these kind of filter banks compare with wavelets. They just seem kind of popular with computer vision people. There is no wavelet filter bank in skimage, is there? I guess it would be easy enough to do with scipy, though. By the way, you mentioned you are interested in matting. I'm working on the alphamatting.com dataset this week :) OT: Sorry for not finishing up my segmentation PR. It is quite mature but I wanted to compare it to the standard implementations. But for that I need Lab color space conversions, which I didn't get around doing yet. Cheers, Andy On 07/17/2012 09:44 PM, StÃ¯Â¿Â½fan van der Walt wrote: > Hey Andy > > On Tue, Jul 17, 2012 at 10:38 AM, Andreas MÃ¯Â¿Â½ller > <amueller(a)ais.uni-bonn.de> wrote: >> I put together some simple filterbank code here: >> http://peekaboo-vision.blogspot.co.uk/2012/07/filterbank-for-low-level-visi… > Interesting! How do those compare with wavelet filter banks? > > (I happened to have dabbled in texture recognition before: > http://mentat.za.net/msc_thesis.html . I didn't know that Zisserman's > lab worked on that--interesting because they also did a lot of > super-resolution, the topic of my PhD). > > StÃ¯Â¿Â½fan > > P.S. Small typo: Andres -> Andrew Zisserman

2 1

Filterbank code
by Andreas Müller 18 Jul '12

18 Jul '12

Hey everybody. I put together some simple filterbank code here: http://peekaboo-vision.blogspot.co.uk/2012/07/filterbank-for-low-level-visi… Do you think that would be interesting for skimage? Cheers, Andy

3 2

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

scikit-image July 2012