Mailman 3 May 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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Re: Contribution: circles and hough transform
by François 18 Jun '14

18 Jun '14

Hi, FYI, I plan to work on the detection of ellipses quite soon. Stefan indicated to me a reference which seems fairly simple to implement. Cheers, François.

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Re: "Cythonize" not working on OSX?
by Stéfan van der Walt 06 Jun '14

06 Jun '14

On Mon, 03 Feb 2014 16:44:07 +1100, Juan Nunez-Iglesias wrote: > I didn't know this was a possible course of action! =) I have no idea how > many people are affected, or how quick a fix can be... Is it worth > exploring a bit more before reversing it? I actually have very little idea > about the entire build process so I can't offer much insight here... It broke the build on my system too (perhaps it does not check correctly for old versions), so my preference is to revert and have another look at it. StÃ©fan

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ANN: scikit-image 0.10.0
by Johannes Schönberger 01 Jun '14

01 Jun '14

Announcement: scikit-image 0.10.0 ================================= We're happy to announce the release of scikit-image v0.10.0! scikit-image is an image processing toolbox for SciPy that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. For more information, examples, and documentation, please visit our website: http://scikit-image.org New Features ------------ In addition to many bug fixes, (speed) improvements and new examples, the 118 pull requests (1112 commits) merged for this release include the following new features (PR number in brackets): - Viewer returns overlays (#810) - Luv colorspace conversion (#798) - Phase unwrapping (#644) - Add Wiener deconvolution (#800) - Sum filter to rank filters (#844) - Updates to MCP algorithm. (#854) - Add ISODATA thresholding (#859) - Add `imread_collection` automatically if plugin provides `imread` (#862) - Enforce SLIC superpixels connectivity (#857) - Estimator class parameters now public (#840) - BRIEF, ORB and CENSURE features (#834) - SLIC-zero capabilities for SLIC segmentation. (#864) - Shaded Polygon for LineProfile Plugin Output (#875) - Add string inputs for range parameters of `rescale_intensity` (#897) - Blob Detection (#903) - `peak_local_max` support for N-d images (#906) - Add loading from URL in novice module (#916) - Correct mesh orientation in marching cubes algorithm (#882) - Added alpha channel support to novice (#946) - Equality for regionprops (#956) - IPython notebook export for examples (#1000) API changes ----------- The following backward-incompatible API changes were made between 0.9 and 0.10: - Removed deprecated functions in `skimage.filter.rank.*` - Removed deprecated parameter `epsilon` of `skimage.viewer.LineProfile` - Removed backwards-compatability of `skimage.measure.regionprops` - Removed {`ratio`, `sigma`} deprecation warnings of `skimage.segmentation.slic` and also remove explicit `sigma` parameter from doc-string example - Changed default mode of random_walker segmentation to 'cg_mg' > 'cg' > 'bf', depending on which optional dependencies are available. - Removed deprecated `out` parameter of `skimage.morphology.binary_*` - Removed deprecated parameter `depth` in `skimage.segmentation.random_walker` - Removed deprecated logger function in `skimage/__init__.py` - Removed deprecated function `filter.median_filter` - Removed deprecated `skimage.color.is_gray` and `skimage.color.is_rgb` functions - Removed deprecated `skimage.segmentation.visualize_boundaries` - Removed deprecated `skimage.morphology.greyscale_*` - Removed deprecated `skimage.exposure.equalize` Contributors to this release ---------------------------- This release was made possible by the collaborative efforts of many contributors, both new and old. They are listed in alphabetical order by surname: - Raphael Ackermann - Ankit Agrawal - Maximilian Albert - Pietro Berkes - Vighnesh Birodkar - François Boulogne - Olivier Debeir - Christoph Deil - Jaidev Deshpande - Jostein Bø Fløystad - Neeraj Gangwar - Michael Hansen - Almar Klein - Jeremy Metz - Juan Nunez-Iglesias - François Orieux - Guillem Palou - Rishabh Raj - Thomas Robitaille - Michal Romaniuk - Johannes L. Schönberger - Julian Taylor - Gregor Thalhammer - Matthew Trentacoste - Siva Prasad Varma - Guillem Palou Visa - Stefan van der Walt - Josh Warner - Tony S Yu - blink1073 - cgohlke - jaimefrio - radioxoma - sharky93

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Consistent equalization on set of images
by jim＠rybarski.com 28 May '14

28 May '14

I want to use exposure.equalize_adapthist() on a set of images, but a defined part of each image occasionally will have a very bright object in it, which I would like to ignore when calculating the equalization. Currently, the images with the very bright object are much darker than the images without it. Really, one of two solutions would work, but I don't know how to do either with scikit-image: 1) Calculate a histogram equalization for the entire set of images and apply the same equalization to each one 2) Mask the area with the bright object, calculate the equalization of the rest of the image, and apply that equalization to the original image. Are either possible? Thanks!

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Re: generic non-linear filtering that support selem and boundary handling
by Johannes Schönberger 27 May '14

27 May '14

Since this is a feature for 1.0 and my main system is OSX, I am happy to look into it when I'm back... > On May 27, 2014, at 1:41 AM, "Stéfan van der Walt" <stefan(a)sun.ac.za> wrote: > >> On Tue, May 27, 2014 at 7:27 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com> wrote: >> Stéfan, I thought I saw some message recently about access to some OSX >> machines for scikit-image testing? > > Yes, Christoph Deil made available a machine for us to test on, so if > you'd like access please get in touch off-list. > > Regards > Stéfan > > -- > 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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Updating LinePorofile on image changed
by Nadav Horesh 27 May '14

27 May '14

Hi, I built an application based on skimage viewer some image filter plugins and a LineProfile. In this application I want to investigate the influence of the filters (tuned by some attached sliders) via the LineProfile tool. My problem is that the tool sees only the original image, and not those generated (and displayed in viewer window) by the filters. How can I make the LineProfile tool relate to the modified image? Thanks, Nadav.

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Re: generic non-linear filtering that support selem and boundary handling
by Stéfan van der Walt 27 May '14

27 May '14

On Tue, May 27, 2014 at 7:27 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com> wrote: > Stéfan, I thought I saw some message recently about access to some OSX > machines for scikit-image testing? Yes, Christoph Deil made available a machine for us to test on, so if you'd like access please get in touch off-list. Regards Stéfan

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Re: generic non-linear filtering that support selem and boundary handling
by Josh Warner 27 May '14

27 May '14

Basically OSX uses Clang, and Clang doesn't (yet) support OpenMP. Some people are working toward this, but it's not in there yet. OSX is the only architecture for which this is a problem. There are a lot of places in skimage where relatively simple optimizations (release the GIL, use prange) would reap very large performance benefits. I'd asked about this before, and it was viewed as not feasible due to Clang's limitations. However, I looked at this again just now and it *might *be that Cython simply ignores OpenMP features under Clang, compiling as if they didn't exist (i.e. basically substitution range for prange). If that is true, I could submit these without much issue... and we could expose pretty dramatic improvements to some existing Cython loops. Sadly, I don't have a Clang platform to test this behavior. Josh On Monday, May 26, 2014 10:48:15 PM UTC-5, Juan Nunez-Iglesias wrote: > > Josh, why the parallel stripping out? Is it a Cython version requirement? > We can always have this as a "dormant" PR for 1.0, for which we might bump > up the version required. It might also be possible to wrap the import > around a try-catch clause so that it fails gracefully on an earlier Cython > version. > > Juan. > > > On Tue, May 27, 2014 at 1:07 PM, Josh Warner <silvertrumpet999(a)gmail.com>wrote: > >> Funny you should request this. I built a Cython framework do exactly what >> you want (arbitrary selem, boundary handling [padding], and even arbitrary >> weighting of the selem in 2D and 3D) for local *weighted *variance. >> >> The framework is about as useful as the actual calculation. Replace the >> innermost loop, change the name, and you get an entirely different >> non-linear weighted local feature. This requires a somewhat skilled user, >> but the framework is already done so it isn't as hard as it sounds. >> >> Trouble is, I used some features from cython.parallel so those would have >> to be stripped out, losing over an order of magnitude in speed. I've been >> kicking around submitting them, but going back and ripping out the parallel >> features is painful. >> >> If interested I can clean up and put them in a Gist or two. >> >> Josh >> >> >> On Monday, May 26, 2014 1:50:10 AM UTC-5, Chencan QIAN wrote: >>> >>> Essentially, this is something similar to scipy.ndimage.filters.generic_filter >>> (which is too slow because of its internal python for-loop), but >>> implemented in cython as with skimage.filter.rank family. >>> >>> Given the diversity within skimage.filter.rank, a generic function would >>> be very useful. For example, I'd like to calculate local variance, which is >>> conceptually similar to skimage.filter.rank.mean, but not supported >>> currently. >>> >>> I guess the absence of such a function must be due to some unresolved >>> technical obstacle? >>> >>> Thanks~ >>> >>> Chencan >>> >> -- >> 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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generic non-linear filtering that support selem and boundary handling
by Chencan QIAN 27 May '14

27 May '14

Essentially, this is something similar to scipy.ndimage.filters.generic_filter (which is too slow because of its internal python for-loop), but implemented in cython as with skimage.filter.rank family. Given the diversity within skimage.filter.rank, a generic function would be very useful. For example, I'd like to calculate local variance, which is conceptually similar to skimage.filter.rank.mean, but not supported currently. I guess the absence of such a function must be due to some unresolved technical obstacle? Thanks~ Chencan

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scikit-image May 2014