Mailman 3 April 2015 - scikit-image

Re: problem with io.imread
by Emmanuelle Gouillart 29 Apr '15

29 Apr '15

Hi Julien, how did you install scikit-image? Are you using a scientific Python distribution such as Anaconda or Canopy? Did you try re-installing scikit-image after installing pillow? Which version of scikit-image did you install? Emma On Wed, Apr 29, 2015 at 06:21:00PM +0200, Julien Derr wrote: > Hi everyone, > I have a very basic problem, but I have no idea how to solve it ! > I installed scikitimage on a new computer, and I cannot manage to load an image > with the io module > from skimage import io,Â works fine : > VariableÂ Â TypeÂ Â Â Â Â Data/Info > ------------------------------ > filenameÂ Â strÂ Â Â Â Â Â ./small.jpg > ioÂ Â Â Â Â Â Â Â moduleÂ Â Â <module 'skimage.io' from<...>skimage/io/__init__.pyc'> > but when I want to load my image: I get the error > In [5]: camera = io.imread(filename) > ValueError: Could not load "./small.jpg" > Please see documentation at: http://pillow.readthedocs.org/en/latest/ > installation.html#external-libraries > I went on the website where they ask to unistall PIL before installing pillow, > this is what I did, and still I get the error ... > any ideas ? > thanks a lot! > Julien

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problem with io.imread
by Julien Derr 29 Apr '15

29 Apr '15

Hi everyone, I have a very basic problem, but I have no idea how to solve it ! I installed scikitimage on a new computer, and I cannot manage to load an image with the io module from skimage import io, works fine : Variable Type Data/Info ------------------------------ filename str ./small.jpg io module <module 'skimage.io' from<...>skimage/io/__init__.pyc'> but when I want to load my image: I get the error In [5]: camera = io.imread(filename) ValueError: Could not load "./small.jpg" Please see documentation at: http://pillow.readthedocs.org/en/latest/installation.html#external-libraries I went on the website where they ask to unistall PIL before installing pillow, this is what I did, and still I get the error ... any ideas ? thanks a lot! Julien

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Scikit-image installation in Quantum GIS
by Forest Applied Remote Sensing RG (FARS) 29 Apr '15

29 Apr '15

Hello everyone, I am trying to use scikit-image in QGIS's Python console. I manage to install many other packages with pip in OSGeo4W Shell but with scikit-image the same error always come (attached). Can anybody help me with this issue? Thank you <https://lh3.googleusercontent.com/-d6JHijl_5bM/VUCokgR8RTI/AAAAAAAAAFA/VbHd…>

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Re: Blog post on scikit-image by Eric Chiang
by Viral Parikh 29 Apr '15

29 Apr '15

hi all, the blog post is good! but its unclear how he is using pd.DataFrame() in step 10 - ggplot(pd.DataFrame(),aes(fill=True,alpha=0.5)) + \ geom_density(aes(x=gray_image.flatten()),color='green') + \ geom_density(aes(x=equalized_image.flatten()),color='orange') + \ ggtitle("Histogram Equalization Process\n(From Green to Orange)") + \ xlab("pixel intensity") + \ ylab("density") what should be contained in the dataframe is unclear to me? would appreciate your response, thank you! On Monday, February 3, 2014 at 9:19:26 AM UTC-6, Ankit Agrawal wrote: > > Cool blog post!! +1 for inclusion of feature detection, extraction and > matching example in future post. > > Regards, > Ankit Agrawal, > Communication and Signal Processing, > IIT Bombay. > > > On Mon, Feb 3, 2014 at 8:30 PM, Johannes Schönberger <js...(a)demuc.de > <javascript:>> wrote: > >> Really nice, the blog post should definitely get a follow up with the >> new feature detection, extraction and matching capabilities. >> >> On Sun, Feb 2, 2014 at 1:41 PM, Stéfan van der Walt <ste...(a)sun.ac.za >> <javascript:>> wrote: >> > Have a look at this great blog post: >> > >> > http://blog.yhathq.com/posts/image-processing-with-scikit-image.html >> > >> > -- >> > 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...(a)googlegroups.com <javascript:>. >> > For more options, visit https://groups.google.com/groups/opt_out. >> >> -- >> 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...(a)googlegroups.com <javascript:>. >> For more options, visit https://groups.google.com/groups/opt_out. >> > >

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Re: Blog post on scikit-image by Eric Chiang
by Viral Parikh 29 Apr '15

29 Apr '15

Hi All, Has anyone run the below part of the code mentioned in the blog - ggplot(pd.DataFrame(),aes(fill=True,alpha=0.5)) + \ geom_density(aes(x=gray_image.flatten()),color='green') + \ geom_density(aes(x=equalized_image.flatten()),color='orange') + \ ggtitle("Histogram Equalization Process\n(From Green to Orange)") + \ xlab("pixel intensity") + \ ylab("density") I run and I keep getting errors. Can anyone tell me what - pd.DataFrame() mean over here? Thank you in advance! Best, Viral On Monday, February 3, 2014 at 9:19:26 AM UTC-6, Ankit Agrawal wrote: > > Cool blog post!! +1 for inclusion of feature detection, extraction and > matching example in future post. > > Regards, > Ankit Agrawal, > Communication and Signal Processing, > IIT Bombay. > > > On Mon, Feb 3, 2014 at 8:30 PM, Johannes Schönberger <js...(a)demuc.de > <javascript:>> wrote: > >> Really nice, the blog post should definitely get a follow up with the >> new feature detection, extraction and matching capabilities. >> >> On Sun, Feb 2, 2014 at 1:41 PM, Stéfan van der Walt <ste...(a)sun.ac.za >> <javascript:>> wrote: >> > Have a look at this great blog post: >> > >> > http://blog.yhathq.com/posts/image-processing-with-scikit-image.html >> > >> > -- >> > 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...(a)googlegroups.com <javascript:>. >> > For more options, visit https://groups.google.com/groups/opt_out. >> >> -- >> 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...(a)googlegroups.com <javascript:>. >> For more options, visit https://groups.google.com/groups/opt_out. >> > >

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A DataFrame-like container for image data
by Yotam Doron 28 Apr '15

28 Apr '15

Hi all, I wrote the beginnings of a DataFrame-like container for image processing. It's an experiment for the moment, a small wrapper around a dictionary of arrays, and I'd be interested in any kind of feedback https://github.com/yotam/pictureframe https://pypi.python.org/pypi/pictureframe/0.1.0 https://github.com/yotam/pictureframe/blob/master/examples/quickstart.py I wrote this because in my work I either end up with - procedural code where I pass around lots of image-shaped arrays, or - classes that have lots of image-shaped arrays as member variables I wanted to avoid having to write repeated indexing code whenever I work on a subset, and to have some guarantees about the shape of the data. I also wanted to be able to quickly generate a scaled-down version of all my arrays and to leave the door open for higher dimensional data like vxel grids. Main differences from Pandas DataFrame - Arrays can have varying dimensions, only the first `fixed_dim` dimensions must match. So you can keep together data such as RGB, depth, label distributions, weight maps and so on. - Higher dimensional data, not just a tabular structure. Main differences from scikit-image ImageCollection and MultiImage - Slicing and indexing operate on the underlying array data rather than selecting a subset of the images. - Images are constrained to match on first dimensions. - Not constrained to image data, e.g. indexing can return a PictureFrame with fewer constrained dimensions. Any thoughts, suggestions or "aren't you just reimplementing library X?" are very welcome. This is the first time I've tried to release a package so if anything seems unusual please let me know. Thanks, Yotam

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Python count crystals (total and by color)
by Oscar J. Delgado 28 Apr '15

28 Apr '15

Good morning to all, I have pictures from a microscope and I am trying to count the total number of crystal as well as those with specific colors (red, blue or yellow). In principle it looks possible to do it just by looking at the picture but considering I have to do it for over 200, I believe a script would be more effective. My first approach was to follow the examples in the "skimage" gallery, but I have a big issue as the crystals color and the background color (an alcohol solution) are almost the same (transparent). So far I have successfully segmented the particles using the following code: import matplotlib.pyplot as plt import numpy as np from skimage.morphology import disk from skimage.filters import rank, threshold_adaptive from skimage.util import img_as_ubyte from skimage.measure import label from skimage.color import label2rgb import pylab from PIL import Image path = r".../11-3.jpg" img = pylab.array(Image.open(path).convert('L')) image = img_as_ubyte(img) # denoise image denoised = rank.median(image, disk(10)) #local gradient gradient = rank.gradient(denoised, disk(2)) #threshold_adaptive filter threshold = threshold_adaptive(gradient, 15000) # label image regions label_image = label(threshold) image_label_overlay = label2rgb(label_image, image=image) # display results fig, axe = plt.subplots(ncols=1, figsize=(10,5)) axe.imshow(image, cmap=plt.cm.gray, interpolation='nearest') axe.imshow(gradient, interpolation='nearest', cmap=plt.cm.spectral, alpha= 0.2) axe.imshow(threshold, interpolation='nearest', cmap=plt.cm.binary_r, alpha= 0.2) axe.imshow(label_image, alpha=0.2) axe.axis('off') fig.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right =1) plt.show() Please note I had to increase the threshold_adaptive to more than 10,000 in order to get the crystals, but this is really slow. I am still working on how identify if the particles segmented are blue tinted (nothing yet!). I really really will appreciate if anyone can give me a hand with this. I have tried even modifying the way I take the pictures but nothing. Again, I have two objectives: count the total number of particles and then count those particles that have a tint (red, blue or yellow) Please find below one typical picture: [image: Cell Image] Best!

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Euroscipy tutorial on scikit-image
by Emmanuelle Gouillart 28 Apr '15

28 Apr '15

Dear all, I'm thinking of submitting an abstract for a tutorial on scikit-image for the next Euroscipy in Cambridge (24-28 August). I know there was already an excellent tutorial by StÃ©fan last year :-), but as new people keep on joining the community, it still might be interesting for a wide audience. There is also the possibility to focus on a more specific or more advanced aspect of image processing, such as image segmentation, 3D images, etc. Would anybody be interested in giving a joint tutorial with me on scikit-image at Euroscipy 2015? Ideas on subjects important to cover on such a tutorial are also very welcome. Cheers, Emmanuelle

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Google Summer of Code 2015
by Stefan van der Walt 27 Apr '15

27 Apr '15

Hi all, scikit-image is again participating in Google's Summer of Code under the umbrella of the PSF. Google today announced the accepted students, and we'd like to congratulate Daniil Pakhomov (project: "Implementing a patent-free Face Detection algorithm") and Aman Singh (project: "rewriting scipy.ndimage in cython")! We are now in the community bonding period [0], so please join us on Gitter (https://gitter.im/scikit-image/scikit-image) and let's have some fun coding together before the projects officially kick off! To the students who did not get accepted this year: thank you for all the hard work you put into your proposals, and please stay involved and in touch. We look forward to working with you! Here's to a great few months ahead! Stéfan [0] http://googlesummerofcode.blogspot.nl/2007/04/so-what-is-this-community-bon…

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How can I resample an Image in Scikit?
by Claiborne Morton 24 Apr '15

24 Apr '15

Hey guys, I was wondering if there is a way to resample images in Scikit Image. Im not even sure that is the correct terminology for what I am trying to do? Basically my goal is to increase the size of images by a factor of 4. My goal is to smooth the edges of shapes within my images, by increasing the number of pixels. I have tried doing this using the resize function but I end up with the same rough edges, just on a larger scale. Also the images I am working with are binary, and I would like this to remain when the image is expanded. I have tried doing this using resize, but the result is an image with grayscale pixels, and the rough edges are only magnified. Some time in the past I was able to get these result using Fiji and Preview (mac), but am not exactly sure how. I have attached both a zoomed image of the resize function as well as a zoom on the results I have made in the past. Also attached is the images that I am trying to multiply by a factor of 4 (binary_filled_bp). Sorry for the confusing post. Please let me know if I can clear anything up! Thanks Clay

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