Mailman 3 April 2013 - scikit-image

Re: Making algorithms at least 3D, preferably nD
by jeff witz April 26, 2013

April 26, 2013

Hello, I think you must all pay attention to standards if you want to act on nD images. For structured data files there is a library that hab been used for decade and which is very efficient, it's netcdf (http://www.unidata.ucar.edu/software/netcdf/), there is already tools in python to deal with it. This library allows one to deal with data in // which is important when one deals with big datas. The last version is based on hdf wich is the tools used on HPC. If your data are not stored in a standard format, the library ITK has provide a binding called SimpleITK that allows one to read every format ITK konws. It is important to take into account the fact that the operation on pixel depend on the grid spacing, as for exampe the finite difference gradient which is wrong when one chooses a step of one because the file as not been read correctly. As the 3D datas often comes from the measurement X-Ray Tomography, MRI, Echography, it is important to consider the device information. The format dicom as been made in this specific purpose there is a python binding called pydicom. I know that scikit team does'nt want to have to much dependances, but for nD case I think it is important to use existing libraries. Best regards Le vendredi 30 novembre 2012 05:45:49 UTC+1, Juan Nunez-Iglesias a écrit : > > Hey Guys, > > I mentioned this briefly at SciPy, but I would like to reiterate: a lot of > data is 3D images these days, and more and more data is being generated > that is multi-channel, 3D+t. Therefore, it would be awesome if scikit-image > started making more of an effort to support these. In the best case, the > dimension of the underlying array can be abstracted away — see here<https://github.com/jni/ray/blob/develop/ray/morpho.py#L328>for example, the functions juicy_center (which extracts the centre of an > array, along all dimensions), surfaces (grabs the "border" arrays along > each dimension), hollowed (zeroes-out the centre), and more. Otherwise, > writing a 3D function that gracefully degrades to 2D when one of the > dimensions is 1 is also possible. > > In general, the amount of additional effort to make code 3-, 4- or n- > dimensional is relatively low when you write the algorithm initially, > relative to refactoring a whole bunch of functions later. I'll try to > fiddle with whichever code I need, but in the meantime, what do you think > about adding a paragraph or a sentence about this issue in the scikit-image > contribute <http://scikit-image.org/docs/dev/contribute.html> section, so > that people at least have this in mind when they are thinking of writing > something new? > > Thanks, > > Juan. >

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problems with cmorph / reconstruction
by thomash April 25, 2013

April 25, 2013

I don't know if this is the correct place to post a bug-message: Using scikit image 0.8.1, with Python 2.7.3 and on a Win64 system, I have difficulties with importing "reconstruction". The problems seem to stem from "cmorph": from skimage.morphology import reconstruction --------------------------------------------------------------------------- ImportError Traceback (most recent call last) <ipython-input-1-5fc8bff47c48> in <module>() ----> 1 from skimage.morphology import reconstruction C:\Python27\lib\site-packages\skimage\morphology\__init__.py in <module>() 1 from .binary import (binary_erosion, binary_dilation, binary_opening, 2 binary_closing) ----> 3 from .grey import * 4 from .selem import * 5 from .ccomp import label C:\Python27\lib\site-packages\skimage\morphology\grey.py in <module>() 2 from skimage import img_as_ubyte 3 ----> 4 from . import cmorph 5 6 ImportError: cannot import name cmorph

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Re: Mean of Least Variance filter
by Chintak Sheth April 25, 2013

April 25, 2013

Hi, Would an implementation of a complete as outlined by the paper provided by Stefan be counted as a GSOC proposal ? Chintak On Thu, Apr 25, 2013 at 5:23 PM, Stéfan van der Walt <stefan(a)sun.ac.za>wrote: > On Thu, Apr 25, 2013 at 1:41 PM, Chintak Sheth <chintaksheth(a)gmail.com> > wrote: > > I think such implementations would be pretty nice for the community. > > Thoughts ? > > I don't know much about these, so I'll let other chime in. > > 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/groups/opt_out. > > >

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Re: Mean of Least Variance filter
by Stéfan van der Walt April 25, 2013

April 25, 2013

On Thu, Apr 25, 2013 at 1:41 PM, Chintak Sheth <chintaksheth(a)gmail.com> wrote: > I think such implementations would be pretty nice for the community. > Thoughts ? I don't know much about these, so I'll let other chime in. Stéfan

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Re: Mean of Least Variance filter
by Chintak Sheth April 25, 2013

April 25, 2013

Hi Stefan, On Wed, Apr 24, 2013 at 7:22 PM, Stéfan van der Walt <stefan(a)sun.ac.za>wrote: > > Petkov has a copy on his website: > http://www.cs.rug.nl/~petkov/publications/2011ivc-contour_survey.pdf > > Yeah, it surely looks like they have described edge and line based contour detectors in detail. I'm not done reading this paper yet, but just out of curiosity how many such contour detector implementations do we currently have in skimage ? More specifically, also the preprocessing edge preserving smoothers, like value-and-criterion operator ? I know rank order filters is one. Any else ? I think such implementations would be pretty nice for the community. Thoughts ? Chintak

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Re: Cython 0.18 installation + skimage package - error
by Emmanuelle Gouillart April 25, 2013

April 25, 2013

Hello Lakshmi, git is not a Python package, but a standalone version control software. If you're starting using Python, I recommend that you install a distribution of Scientific Python with all the Python packages that you need, this will save you some trouble! Canopy Express is a good pick, but I don't think that skimage is shipped with the free edition. On Windows, you might want to try instead Anaconda from Continuum, which comes with the scikit-image and the scikit-learn (AFAIK, SVMs are found in the scikit-learn). If you install another distribution, you should first remove the Python-related directories that you had installed, otherwise there might be conflicts. Hope this helps, Emmanuelle On Wed, Apr 24, 2013 at 10:32:36PM -0700, Lakshmi wrote: > Hello Members, > Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½ Ã¯Â¿Â½Ã¯Â¿Â½ > Ã¯Â¿Â½I am using Python 2.7. (OS - Windows 7, 64 bit). I am newbie to Python. > Ã¯Â¿Â½I would like to use SVM for 2 D image segmentation. > I have installed "git hub" (in C:/Users/Viji/Documents/GitHub) > I have chosen "Clone in Windows" option in - > [1]https://github.com/scikit-image/scikit-image , > to use skimage package. Am I right by following the above steps? > Should I install GitHub in C:/Python27? I have this doubt since I am > getting an error as "The specified module > could not be found". > I have installed numpy and scipy packages in > C:/Python27/Lib/site-packages. > When I tried to install Cython 0.18, I have got an error as "Unable to > find vcvarsall.bat". > I have installed Canopy Express (free edition). > I do not know why I could not use skimage. Please help me to solve this > issue. > Regards > Lakshmi

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Frei-Chen Edge Detector
by Umesh Sharma April 25, 2013

April 25, 2013

Hi, I am working on implementation of Frei-Chen Edge detector ( http://rastergrid.com/blog/2011/01/frei-chen-edge-detector/ ) , i have almost completed it but i have one doubt regarding the last mask it is using for computing average . I don't know why it is using this mask and after applying this mask i am getting an image which looks like original image and the difference can't be detected and if that mask is not used then edges are clearly visible . so can you please tell me where is problem ? Thanks, Umesh

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Re: functions of ndimage
by Josh Warner April 25, 2013

April 25, 2013

Regarding the `scipy.ndimage.label` changes coming in 0.13, see the discussion in Issue #495<https://github.com/scikit-image/scikit-image/issues/495> and the partial fix in merged Issue #498<https://github.com/scikit-image/scikit-image/issues/498>; I think there are still ~4 or so outstanding cases from #495. On Wednesday, April 24, 2013 1:33:21 AM UTC-5, Juan Nunez-Iglesias wrote: > > On Wed, Apr 24, 2013 at 4:16 PM, Josh Warner <silvertr...(a)gmail.com<javascript:> > > wrote: > >> (like the change of `scipy.ndimage.label` coming in 0.13) > > > Huh? For the less-informed among us, could you elaborate? A quick Googling > was not informative... And I have (approximately) 5 bajillion functions > that depend on `nd.label`. =) > > If this were to be implemented, would our policy then be to use relative >> imports for the wrapped versions of these functions internally, rather than >> importing from SciPy? >> > > I hadn't considered this but it makes a lot of sense, as it potentially > slowly decouples scikit-image from its scipy dependency. >

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Re: Frei-Chen Edge Detector
by Michael Aye April 24, 2013

April 24, 2013

Concerning removal of whitespace noise, one could setup pre-commit git hooks to do that: http://stackoverflow.com/questions/591923/make-git-automatically-remove-tra… On Wednesday, April 24, 2013 3:48:52 AM UTC-7, Chintak Sheth wrote: > > Hi Umesh, > > As stated in the subject I'm presuming you want to implement an edge > detector, right ? As it says on the blog : > >> When we are using the Frei-Chen masks for edge detection we are searching >> for the cosine defined above and we use the first four masks as the >> elements of importance so the first sum above goes from one to four. >> > > But in your implementation you are summing all the elements including the > 4 line masks. As can be seen from the function definition, M is the sum of > square of the convolution of relevant masks and S is the sum of square of > the convolution of all the masks. If you take all the masks as "relevant", > the ratio essentially works out to be 1. > > In short, you have to return the sqrt((mask1 + mask2 + mask3 + mask4) / ( > mask1 + mask2 + mask3 + mask4 + mask5 + mask6 + mask7 + mask8 + mask9)) > Where, mask : refers to the square of the convolution between the > corresponding mask and the image > > Also just one more note, before you submit a PR, clean up the whitespace > noise. You can use Sublime Text 2, with 4 white spaces for indentation as > Josh suggested. This is something I learned the hard way. To cross check if > the noise is actually cleared out, you can view it on the GitHub editor. > > I hope this sorts out the issue. > > This is the link you should provide : > https://github.com/umesh563/scikit-image/blob/master/skimage/filter/edges.py. Always > assume people are lazy. ;) > Thanks, > Chintak >

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Re: Mean of Least Variance filter
by Dan Farmer April 24, 2013

April 24, 2013

Just to jump on the citation count, etc. Microsoft Academic is actually quite cool in this regard: http://academic.research.microsoft.com/Publication/526623/a-morphology-base… Looks like it's been cited about 17 times. I actually prefer Microsoft Academic to Google Scholar for digging up papers to read, but Google Scholar is better at finding copies of the papers outside of paywalls. -Dan On Wed, Apr 24, 2013 at 5:43 AM, Stéfan van der Walt <stefan(a)sun.ac.za> wrote: > Hi Chintak > > On Wed, Apr 24, 2013 at 2:34 PM, Chintak Sheth <chintaksheth(a)gmail.com> wrote: >> So I was reading a paper on implementation of MLV filters which belongs to a >> broder class of value-and-criterion filters. I read this paper "A >> morphology-based filter structure for edge-enhancing smoothing" > > This looks like an interesting approach (paper available for download > at: http://www.markschulze.net/docs/pdf/icip94.pdf), but I can't find > much more written on it, or a citation count--so it's hard to see what > its effect has been in practice. It'd be good to also look at > > http://dl.acm.org/citation.cfm?id=1897509 > > and compare with other algorithms. > > 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/groups/opt_out. > >

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