Mailman 3 May 2016 - scikit-image

Re: skimage and opencv
by Emmanuelle Gouillart Sept. 22, 2016

Sept. 22, 2016

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,

3 2

Translating Multi-Otsu Threshold from java
by Alexandre Fioravante de Siqueira Aug. 11, 2016

Aug. 11, 2016

Hi everyone, I was thinking about using multi-Otsu thresholding for some research. I am used to use the ImageJ available plugin, http://imagej.net/Multi_Otsu_Threshold. Could you give me a hand on writing such a function which could do this for python? Maybe putting it into scikit-image. Or else, could you point me a better alternative? Thank you very much! Alex

2 5

Re: Dropping support for 2.7 in 2020
by Juan Nunez-Iglesias July 4, 2016

July 4, 2016

I would drop 2.7 sooner. NumPy/SciPy dropping it is the absolute cutoff, but there’s no reason why we can’t jump the gun (and lead rather than follow). Py2.7 users can make do with older releases. As Stéfan mentioned, this is not about erasing Py2.7 support, but not releasing new features on Py2.7. Very different. I envision that we stop producing Py2.7 releases after 0.13, but we call that an “LTS” release which will get bugfix backports until 2020. imho, with Py3.4 and especially Py3.5, Py3-only suddenly became very attractive. My three favourite features are type annotations, keyword-only arguments (these two together make it much easier to produce correct code and debug), and the @ matrix multiplication operator. The latter makes linear algebra code *so* *much* nicer to read and write, and we have our fair share in scikit-image. For my own projects, I am now Py3.5-only, always. Finally, as others have mentioned, but is worth restating: - Conda allows user-space installs of Python versions and packages, so you don’t ever depend on your sysadmin-controlled environment. - It is *absolutely false* that conda packages are only useful on Windows — I have failed to compile scipy both on OSX and Ubuntu boxes. - It is also *not* a requirement to download the monolithic Anaconda distro — with miniconda (which should be the default), you just install precisely what you need. - With conda-forge we now have a community-run repository of binary conda packages. So, in short, the switch to Py3 is easier than ever for *all* users, some might just not realise it yet ;), and switching to a Py3-only programming environment is a boon to all the scikit-image devs… though again some might not realise it yet ;). Juan. On 21 May 2016 at 12:20:38 PM, Nathaniel Smith (njs(a)vorpus.org) wrote: On May 20, 2016 07:30, "Michael Sarahan" <msarahan(a)gmail.com> wrote: > I don't think this is a concern for cython or scikit-image, but many people at bumping into the language support limit in the C++11 sense with Python 2.7 on Windows. Since VS 2008 is the de-facto standard compiler for Python 2.7, people are unable to use C++11 code in modules for Python 2.7. Some people use newer compilers anyway, which sometimes works, but is mixing runtimes, and can lead to bugs or crashes. Many people would like to support Python 2.7 using a different compiler for the whole ecosystem. One example is Ilastik, by folks at HHMI, using VS 2012 to have a custom stack: https://github.com/ilastik/ilastik-build-conda I think getting mingwpy finished and polished is probably an easier solution for this problem than forking the entire py27-on-windows ecosystem :-) -n -- 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. To post to this group, send email to scikit-image(a)googlegroups.com. To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/CAPJVwB%3DjRQtHn9Xj0xwv3hxtD…. For more options, visit https://groups.google.com/d/optout.

3 3

Genetic Algorithms based feature extraction algorithm (by minimizing a metric)
by Hakim Benoudjit June 21, 2016

June 21, 2016

Hello, Is there a pixel-based region growing algorithm implemented with Scikit-image that would be employed for feature extraction on an image? Basically, the kind of algorithms I'm looking for (or just checking if someone came across it, to see if I'm in the right direction) works by adding pixels to the detected feature based on the minimization of a certain metric. Potentially, a pixel can be removed if the metric is not optimized when this pixel is added. I'm thinking of implementing this feature extraction algorithm using Genetic Algorithms (GA), but I can't think of a way to make it possible to backtrack (i.e. remove a pixel). Anyone encountered something similar even if it's not using GAs?

2 1

Re: Thresholding a dark region in an image
by Juan Nunez-Iglesias June 16, 2016

June 16, 2016

Hi Nabil, Have you looked at the skimage.filters.threshold_* functions? I would start by looking at the results from each of those on a few example sunspots to see whether one reliably gives you a reasonable result. Juan. On 20 May 2016 at 12:26:37 AM, Nabil Freij (nabil.freij(a)gmail.com) wrote: Hello, I have been investigating how to threshold a structure in my images. More specifically, a sunspot, that can be seen in Figure 1. The aim has been to isolate and measure the number of pixels that are part of the central part of a sunspot, which is the darkest region of the structure. The method I have been using is to define a region which contains no features that are similar to a sunspot. The size of this region is not fixed but I generally make it as large as the data allows. This region is at the bottom black box in Figure 1 (ignore the slider). The mean and standard deviation of this region is calculated, which allows me to define a threshold limit, which is subtracting the standard deviation multiplied by a user defined constant from the mean. The constant is chosen so that overall, the threshold is selecting the pixels we know that are part of the central region. But this value varies depending the structure and the data source. Another method I have discussed or looked into are related to Figure 2. On the left is a cropped field of view of the sunspot and on the right is a histogram of this image in red and in yellow is the histogram of the background box from Figure 1. By using the histogram, I can work out the numerical gradient and pick the points with the largest shift. I also tried this method on the original image by taking slices along the sunspot, however, due to the non-uniform nature of a sunspot the results were not very good. I was wondering if there were any suggestions to threshold this region that is not as ad hoc as my method? Thanks, Nabil -- 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. To post to this group, send email to scikit-image(a)googlegroups.com. To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/CADwJ0z1Sthz7OW8uu2G2i%2Bm9V…. For more options, visit https://groups.google.com/d/optout.

2 1

Re: Skimage - Getting the transformation from Geometric transformation object
by Shrawan May 27, 2016

May 27, 2016

Thanks a ton, Dr. Walt! On Fri, May 27, 2016 at 1:38 PM, Stéfan van der Walt <stefanv(a)berkeley.edu> wrote: > Hi Shrawan > > On Fri, 27 May 2016 at 12:33 Shrawan Kumar Mageswaran < > m.shrawankumar(a)gmail.com> wrote: > >> I am trying to retrieve and store transformation parameters as a matrix >> after estimating them using the >> "skimage.transform.estimate_transform('Affine',src,dst)" method. I >> understand that the output of >> "skimage.transform.estimate_transform('Affine',src,dst)" is not a >> transformation matrix by itself (I do not know what the properties of such >> a transform object are and I would like to know more) and I would like to >> calculate the matrix from such an object. I would greatly appreciate your >> help on this issue. Thank you. >> > > Take a look at the source here: > > > https://github.com/scikit-image/scikit-image/blob/master/skimage/transform/… > > You are looking for the `params` attribute. > > Stéfan > > -- > You received this message because you are subscribed to a topic in the > Google Groups "scikit-image" group. > To unsubscribe from this topic, visit > https://groups.google.com/d/topic/scikit-image/oKSPYsmF9rw/unsubscribe. > To unsubscribe from this group and all its topics, send an email to > scikit-image+unsubscribe(a)googlegroups.com. > To post to this group, send email to scikit-image(a)googlegroups.com. > To view this discussion on the web, visit > https://groups.google.com/d/msgid/scikit-image/CABDkGQ%3DY1CT1kd8qgWdUPXLi3… > <https://groups.google.com/d/msgid/scikit-image/CABDkGQ%3DY1CT1kd8qgWdUPXLi3…> > . > For more options, visit https://groups.google.com/d/optout. > -- Shrawan Kumar Mageswaran Postdoctoral Scholar Jensen Lab California Institute of Technology

1 0

Skimage - Getting the transformation from Geometric transformation object
by Shrawan Kumar Mageswaran May 27, 2016

May 27, 2016

Dear Skimage users/developers, I am trying to retrieve and store transformation parameters as a matrix after estimating them using the "skimage.transform.estimate_transform('Affine',src,dst)" method. I understand that the output of "skimage.transform.estimate_transform('Affine',src,dst)" is not a transformation matrix by itself (I do not know what the properties of such a transform object are and I would like to know more) and I would like to calculate the matrix from such an object. I would greatly appreciate your help on this issue. Thank you. Best, Shrawan -- Shrawan Kumar Mageswaran Post-doc Jensen Lab California Institute of Technology

2 1

Re: function to measure the (local) density of 1s in a binary image
by Egor Panfilov May 26, 2016

May 26, 2016

By the way :), we do have such filter in `skimage`: http://scikit-image.org/docs/dev/api/skimage.filters.rank.html#mean , but it is selective to input dtype and doesn't support many boundary conditions' alternatives. Cheers, Egor четверг, 26 мая 2016 г., 18:29:59 UTC+3 пользователь Egor Panfilov написал: > > Hi Matteo! > > The function you're looking for is as simple as convolution [1] with a > typical structuring element [2] (we have square, circle and many more). I > suppose, this can also be called as 'mean filter': > > Here is an example: > >> import numpy as np >> import scipy.ndimage as ndi >> from skimage.morphology import square >> >> img = np.random.uniform(size=(5, 5)) >> img = (img > 0.5).astype(np.float) >> sem = square(3)/3**2 # Don't forget to normalize >> out = ndi.convolve(img, sem, mode='wrap') >> > > > print(img) >> print(sem) >> print(out) > > > Results to: > >> [[ 1. 0. 0. 1. 0.] >> [ 1. 0. 0. 0. 0.] >> [ 0. 0. 1. 1. 0.] >> [ 0. 0. 0. 0. 1.] >> [ 1. 0. 1. 0. 0.]] >> [[ 0.11111111 0.11111111 0.11111111] >> [ 0.11111111 0.11111111 0.11111111] >> [ 0.11111111 0.11111111 0.11111111]] >> [[ 0.33333333 0.44444444 0.22222222 0.22222222 0.44444444] >> [ 0.22222222 0.33333333 0.33333333 0.33333333 0.44444444] >> [ 0.22222222 0.22222222 0.22222222 0.33333333 0.33333333] >> [ 0.22222222 0.33333333 0.33333333 0.44444444 0.33333333] >> [ 0.33333333 0.33333333 0.22222222 0.33333333 0.44444444]] > > > Cheers, > Egor > > [1] > http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.convolve.… > > [2] > http://scikit-image.org/docs/dev/api/skimage.morphology.html#module-skimage… > > 2016-05-26 18:11 GMT+03:00 Matteo <matteo.niccoli(a)gmail.com>: > >> Is there a function in scikit-image to calculate the the local density of >> 1s in a binary image? >> >> By local density of 1s I mean: >> 1) count the number of pixels that have value of 1 in a running/sliding >> window (preferrably circular but square would work too) >> 2) divide by the total number of pixels in the running window >> >> Thanks >> Matteo >> >> -- >> 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. >> To post to this group, send email to scikit-image(a)googlegroups.com. >> To view this discussion on the web, visit >> https://groups.google.com/d/msgid/scikit-image/1b36234e-79ed-4eec-9c4a-ea1b… >> <https://groups.google.com/d/msgid/scikit-image/1b36234e-79ed-4eec-9c4a-ea1b…> >> . >> For more options, visit https://groups.google.com/d/optout. >> > >

2 1

function to measure the (local) density of 1s in a binary image
by Matteo May 26, 2016

May 26, 2016

Is there a function in scikit-image to calculate the the local density of 1s in a binary image? By local density of 1s I mean: 1) count the number of pixels that have value of 1 in a running/sliding window (preferrably circular but square would work too) 2) divide by the total number of pixels in the running window Thanks Matteo

2 1

Re: Thresholding a dark region in an image
by François Boulogne May 25, 2016

May 25, 2016

Hi, I'm actually working to add threshold algorithms to scikit-image. We are almost ready to merge the minimum algorithm (see https://github.com/scikit-image/scikit-image/pull/2104), Jeff made the implementation. I believe the histogram could be fruitful in your case and I think that you can study how this algorithm works and generalize it for 3 peaks in the histogram. Then, you will get two minima where you can threshold. Let us know if it works or not. You can probably cut your histogram "by hand" at one minimum to check if the result looks good or not. -- François Boulogne. http://www.sciunto.org GPG: 32D5F22F

1 0