Mailman 3 September 2013 - scikit-image

Re: ndarray subclasses
by Juan Nunez-Iglesias Sept. 22, 2013

Sept. 22, 2013

On Sun, Sep 22, 2013 at 1:20 PM, Jaime Fernández del Río < jaime.frio(a)gmail.com> wrote: > So a pixel replicated TIFF image has twice the resolution, as per the > above official definition, not the same resolution with twice the sampling. > Even in this case, what we call sampling/spacing is the *inverse* of that definition of resolution.

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Re: ndarray subclasses
by Jaime Fernández del Río Sept. 22, 2013

Sept. 22, 2013

On Sat, Sep 21, 2013 at 7:37 PM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > On Sat, Sep 21, 2013 at 11:55 PM, Jaime Fernández del Río < > jaime.frio(a)gmail.com> wrote: > >> I called it "spacing"... We should probably agree on a terminology >>> library-wide. Incidentally, Josh, I called it "spacing" because of your >>> SciPy talk. ;) >>> >> >> I know the real world is just a particular case we shouldn't be too >> concerned about, but isn't "sampling" or "spacing" basically what everyone >> else calls "resolution"? >> > > Not exactly. The resolution is the minimum distance at which you can > distinguish two points. If you upscale your image just by doubling up each > pixel along each dimension, your pixel spacing/sampling is half but your > resolution hasn't changed. > > Similarly, stick a crappy lens in front of a sensor with very tiny pixel > spacing, and your image resolution is limited by the lens, but your pixel > spacing is unchanged. > Ah, interesting distinction, hadn't thought of it like that. Nevertheless, the term "resolution" is very often used to have a different meaning from what you describe, virtually indistinguishable from "sampling" or "spacing", e.g. in the TIFF standard ( http://partners.adobe.com/public/developer/en/tiff/TIFF6.pdf, page 19): XResolution Tag = 282 (11A.H) Type = RATIONAL The number of pixels per ResolutionUnit in the ImageWidth (typically, horizontal - see Orientation) direction. So a pixel replicated TIFF image has twice the resolution, as per the above official definition, not the same resolution with twice the sampling.

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Re: ndarray subclasses
by Juan Nunez-Iglesias Sept. 22, 2013

Sept. 22, 2013

On Sat, Sep 21, 2013 at 11:55 PM, Jaime Fernández del Río < jaime.frio(a)gmail.com> wrote: > I called it "spacing"... We should probably agree on a terminology >> library-wide. Incidentally, Josh, I called it "spacing" because of your >> SciPy talk. ;) >> > > I know the real world is just a particular case we shouldn't be too > concerned about, but isn't "sampling" or "spacing" basically what everyone > else calls "resolution"? > Not exactly. The resolution is the minimum distance at which you can distinguish two points. If you upscale your image just by doubling up each pixel along each dimension, your pixel spacing/sampling is half but your resolution hasn't changed. Similarly, stick a crappy lens in front of a sensor with very tiny pixel spacing, and your image resolution is limited by the lens, but your pixel spacing is unchanged. Often, the sensor is the limiting factor, which is why we confuse the two. =)

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Postprocessing Book Scans/Photos
by Danilo Sept. 21, 2013

Sept. 21, 2013

Hi all Recently I stumbled upon http://www.booksorber.com/, a project that postprocesses photos taken of books, so that they can be exported as nice PDFs. It's really a great idea, and it probably works nicely using high quality photos with nice lighting, but there are some quirks (especially the UI!). And as it's not open source, I cannot improve upon it. That got me thinking on how hard it would be to implement the same thing using Python. Then I found scikit-image... Therefore, my questions: - Do you know of similar attempts to solve the book scanning problem, preferrably using Python? - Can scikit-image already do such tasks? This includes book border detection, text border detection, color balance correction, de-skewing, finger removal and other things to make the text as readable as possible. Unfortunately I don't know too much about image processing algorithms, so I'd be happy about any pointers and suggestions. Would be great if such a software could be created as an open source effort. In the end, open source always wins :) Danilo

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Re: ndarray subclasses
by Jaime Fernández del Río Sept. 21, 2013

Sept. 21, 2013

On Sat, Sep 21, 2013 at 1:04 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > On Sat, Sep 21, 2013 at 11:07 AM, Josh Warner <silvertrumpet999(a)gmail.com>wrote: > >> I believe the most recent SLIC improvements also added a `sampling` >> parameter. >> > > I called it "spacing"... We should probably agree on a terminology > library-wide. Incidentally, Josh, I called it "spacing" because of your > SciPy talk. ;) > I know the real world is just a particular case we shouldn't be too concerned about, but isn't "sampling" or "spacing" basically what everyone else calls "resolution"? -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.

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binary_fill_holes, but creating separate regions inside each other
by Robin Wilson Sept. 21, 2013

Sept. 21, 2013

Hi, I am currently using various skimage functions to perform a customised edge-based image segmentation. Once I've got the outlines of my segments, I am using binary_fill_holes to fill them so I get a binary 'blobs' image, which I can then label, and use for processing. However, when I have an image like this 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0 0 0 0 1 0 1 0 1 1 1 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 1 1 1 1 0 1 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 1 1 1 binary_fill_holes simply fills the entire, outer shape - and thus the shape in the middle gets lost. Is there any simple way to do a fill so that I get two regions: the outer ('donut-shaped') region and the inner region? Or will I have to develop and implement my own algorithm to do this? Any advice would be great, Thanks, Robin

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Re: ndarray subclasses
by Josh Warner Sept. 21, 2013

Sept. 21, 2013

Indeed, marching cubes has anisotropic support presently. `random_walker` also does, though I think my original API for it is poor (only supports anisotropic `depth`, rather than true arbitrary anisotropy via `sampling`). I have an improvement/generalization PR for that in the works. I believe the most recent SLIC improvements also added a `sampling` parameter. On Friday, September 20, 2013 6:55:58 AM UTC-5, Almar Klein wrote: > > On Thu, Sep 19, 2013 at 12:03 PM, Almar Klein <almar...(a)gmail.com<javascript:>> >> wrote: >> > I suppose that the most important bit is that functions that support >> > anisotropy should look whether a "sampling" attribute is present in the >> > given array. >> >> I don't think we currently have any of these, but for now we can >> probably include a `sampling` argument to functions that support it. >> > > Mmm, you seem to be right, but you're *going* to :) The new marching > cubes algorithm has a sampling argument, and I think Josh spoke about > adding it so some morphological operators. I hope to do a PR on the MCP > algorithm soon, which will add support for anisotropy as well. > > > > I do not necessarily mean that a PointSet represents an image (although >> it >> > could), but more generally to for instance store the locations of >> detected >> > feature points. >> >> How do you think this would fit into the scope of image processing? >> (Asked out of curiosity, not at all to put the idea down.) >> > > That's a good point. I think a PointSet class fits image processing > because many image processing algorithms either accept or produce some form > of locations or vectors. I would still call it "image processing" when you > process the resulting locations/vectors. However, such algorithms probably > fall out the scope of scikit-image. > > So probably a better place for a PointSet class would be Scipy, but I have > a feeling they would not be interested in including it. > > > I am not related to the development of scikit-image but I guess its goal >> is to work on images in general and not get too specialised, for instance >> in Medical images. >> > > I agree with that. I think that the only parameter of interest to scikit > image is the "sampling" to deal with anisotropic arrays. So in that sense, > it should be sufficient that sciki-image provides an Image class to which > arbitrary attributes can be attached. Functions in scikit-image can the > check if the array has a "sampling" attribute, and use it. If it returns an > array with the same shape, it would be nice to also set the sampling on > that. > > > May I ask: if you were to add sampling information and spatial >> coordinates, such as an origin for the top-left pixel, how would you input >> that information into scikit-image, could you read it directly from the >> input files or would you need some user input? >> > > I am not sure I understand. In most cases the attributes are added to the > image (i.e. numpy array) when it is read. > >

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Re: ndarray subclasses
by Kevin Keraudren Sept. 20, 2013

Sept. 20, 2013

Le 19/09/2013 10:36, Almar Klein a Ã¯Â¿Â½crit : > > 1) Allowing extra attributes for the Image class, like "sampling" that > specifies the distance between the pixels. This attribute can then be > used by algorithms to take anisotropy into account, and visualization > toolkits could use it to scale the image in the correct way > automatically. This may not seem a very common use case for 2D images, > but 3D data is usually not isotropic. > > Other attributes that I think may be of use for the Image class are > "origin" that specifies the location of the topleft pixel relative to > an arbitrary coordinate frame, and "meta" for the meta data (e.g. EXIF > tags). Hi, I am not related to the development of scikit-image but I guess its goal is to work on images in general and not get too specialised, for instance in Medical images. I am working on a Python interface for a C++ medical imaging library, and I chose to subclass np.ndarray, images keeping a header information ( 'dim', 'orientation', 'origin' and 'pixelSize'), the main feature is to keep track of those spatial coordinate when we slice or resample the array. As StÃ¯Â¿Â½fan pointed out " when you slice out a scalar, or sum, you get an Image object out!", but this has not been an issue so far, I just hide it by overriding: def __str__(self): if len(self.shape) == 0: return str(self.view(np.ndarray)) else: return self.__repr__() The documentation I placed online might give you more ideas on what could be done with a subclass of np.ndarray dedicated to images: http://www.doc.ic.ac.uk/~kpk09/irtk/#irtk.imread May I ask: if you were to add sampling information and spatial coordinates, such as an origin for the top-left pixel, how would you input that information into scikit-image, could you read it directly from the input files or would you need some user input? Kind regards, Kevin

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Re: ndarray subclasses
by Stéfan van der Walt Sept. 19, 2013

Sept. 19, 2013

On Thu, Sep 19, 2013 at 12:03 PM, Almar Klein <almar.klein(a)gmail.com> wrote: > I suppose that the most important bit is that functions that support > anisotropy should look whether a "sampling" attribute is present in the > given array. I don't think we currently have any of these, but for now we can probably include a `sampling` argument to functions that support it. > I do not necessarily mean that a PointSet represents an image (although it > could), but more generally to for instance store the locations of detected > feature points. How do you think this would fit into the scope of image processing? (Asked out of curiosity, not at all to put the idea down.) Stéfan

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Re: ndarray subclasses
by Almar Klein Sept. 19, 2013

Sept. 19, 2013

On 19 September 2013 11:41, Stéfan van der Walt <stefan(a)sun.ac.za> wrote: > Hi Almar > > On Thu, Sep 19, 2013 at 11:36 AM, Almar Klein <almar.klein(a)gmail.com> > wrote: > > Skimage also has the Image class (that inherits from np.ndarray), which I > > believe is mostly there to make the image be shown as an image in IPython > > notebook. What about taking this idea a bit further? In particular, I am > > thinking about two things: > > > > 1) Allowing extra attributes for the Image class, like "sampling" that > > specifies the distance between the pixels. This attribute can then be > used > > by algorithms to take anisotropy into account, and visualization toolkits > > could use it to scale the image in the correct way automatically. This > may > > not seem a very common use case for 2D images, but 3D data is usually not > > isotropic. > > We tried making this the default output of imread, but it caused some > problems (e.g. when you slice out a scalar, or sum, you get an Image > object out!), so we're back to vanilla arrays. I've had the same problem with my own "Image" class. You can solve this pretty well by overloading __getitem__ and __array_wrap__. A small example: https://gist.github.com/almarklein/6621363 That said, the Image > object is still quite useful. The Image class has a dictionary > container for adding any type of meta-data you want (e.g., origin, > sampling distance, etc.) so I don't know if it is necessary to > explicitly specify what those fields should be. > I suppose that the most important bit is that functions that support anisotropy should look whether a "sampling" attribute is present in the given array. > 2) Using a PointSet class to represent numpy arrays that are point sets or > > vector sets. Also such a class can make working with point data much > easier, > > both in internal algorithms, and for the end-user. > > > > An example class can be seen here: > > https://gist.github.com/almarklein/6620956 it allow things like > > appending/removing/inserting/ > popping individual points, and calculating > > things like normals, angles, distances, etc. > > In this case, I see an argument for having such a class, since it > behaves differently from a traditional image, and may need to be > resampled to a regular grid, etc. > I do not necessarily mean that a PointSet represents an image (although it could), but more generally to for instance store the locations of detected feature points. The computation of normals, angles, > etc. could be be utility functions outside the class (I guess I'm a > minimalist when it comes to class design). > You're probably be right about that. The most important bit is the manipulation of individual points inside the pointset.

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Re: ndarray subclasses
by Stéfan van der Walt Sept. 19, 2013

Sept. 19, 2013

Hi Almar On Thu, Sep 19, 2013 at 11:36 AM, Almar Klein <almar.klein(a)gmail.com> wrote: > Skimage also has the Image class (that inherits from np.ndarray), which I > believe is mostly there to make the image be shown as an image in IPython > notebook. What about taking this idea a bit further? In particular, I am > thinking about two things: > > 1) Allowing extra attributes for the Image class, like "sampling" that > specifies the distance between the pixels. This attribute can then be used > by algorithms to take anisotropy into account, and visualization toolkits > could use it to scale the image in the correct way automatically. This may > not seem a very common use case for 2D images, but 3D data is usually not > isotropic. We tried making this the default output of imread, but it caused some problems (e.g. when you slice out a scalar, or sum, you get an Image object out!), so we're back to vanilla arrays. That said, the Image object is still quite useful. The Image class has a dictionary container for adding any type of meta-data you want (e.g., origin, sampling distance, etc.) so I don't know if it is necessary to explicitly specify what those fields should be. > 2) Using a PointSet class to represent numpy arrays that are point sets or > vector sets. Also such a class can make working with point data much easier, > both in internal algorithms, and for the end-user. > > An example class can be seen here: > https://gist.github.com/almarklein/6620956 it allow things like > appending/removing/inserting/popping individual points, and calculating > things like normals, angles, distances, etc. In this case, I see an argument for having such a class, since it behaves differently from a traditional image, and may need to be resampled to a regular grid, etc. The computation of normals, angles, etc. could be be utility functions outside the class (I guess I'm a minimalist when it comes to class design). Regards Stéfan

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ndarray subclasses
by Almar Klein Sept. 19, 2013

Sept. 19, 2013

Hi, Many functions in skimage return a numpy array, but the meaning of that array can differ significantly: sometimes it represents an image, sometimes a set of locations or vectors, etc. Skimage also has the Image class (that inherits from np.ndarray), which I believe is mostly there to make the image be shown as an image in IPython notebook. What about taking this idea a bit further? In particular, I am thinking about two things: 1) Allowing extra attributes for the Image class, like "sampling" that specifies the distance between the pixels. This attribute can then be used by algorithms to take anisotropy into account, and visualization toolkits could use it to scale the image in the correct way automatically. This may not seem a very common use case for 2D images, but 3D data is usually not isotropic. Other attributes that I think may be of use for the Image class are "origin" that specifies the location of the topleft pixel relative to an arbitrary coordinate frame, and "meta" for the meta data (e.g. EXIF tags). 2) Using a PointSet class to represent numpy arrays that are point sets or vector sets. Also such a class can make working with point data much easier, both in internal algorithms, and for the end-user. An example class can be seen here: https://gist.github.com/almarklein/6620956 it allow things like appending/removing/inserting/popping individual points, and calculating things like normals, angles, distances, etc. I would like to stress that both Image and PointSet class do (and should) inherit from np.ndarray, such that they are completely compatible with existing code in skimage and other packages. I am interested to learn whether these ideas can find their way into skimage or not, Almar

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Re: Keypoint matching and ORSA like algorithm
by Jérôme Kieffer Sept. 19, 2013

Sept. 19, 2013

Hello Séfan, On Wed, 18 Sep 2013 23:36:59 +0200 Stéfan van der Walt <stefan(a)sun.ac.za> wrote: > > Do you know an algorithm using those informations as well ? > > Using RANSAC (included in skimage as well), you can define any > criterium you choose for inliers. Wonderful, I will have a look. Cheers, -- Jérôme Kieffer <google(a)terre-adelie.org>

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Keypoint matching and ORSA like algorithm
by Jérôme Kieffer Sept. 18, 2013

Sept. 18, 2013

Hi all, I am working on image alignment using SIFT algorithm; but this also applies to SURF. Sometimes one needs to "refine" matching because of a few wrong match in the list. The ORSA algorithm looks adapted (Moisan-Stival ORSA (Optimized Random Sampling Algorithm) algorithm to filter out the false matches using the epipolar geometry constraint) but it uses only the X and Y coordinate of the keypoint and not the angle + orientation. Maybe using those informations it would be easier to spot those outliers, no ? Do you know an algorithm using those informations as well ? Thanks, -- Jérôme Kieffer <google(a)terre-adelie.org>

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Re: Any plans for 0.9 release?
by Pierre Villeneuve Sept. 14, 2013

Sept. 14, 2013

Stefan, Thanks for the reply. I was in fact hoping the solution would be this simple. Don't rush the release then just for me :) It looks like I'll be all set! Thanks again. On Friday, September 13, 2013 3:53:28 PM UTC-7, Stefan van der Walt wrote: > > Dear Pierre > > We are certainly due for a release, and while the next week is very > busy, I'm hoping to work on that in the two weeks following. I think > we're looking at around 15 October. In the mean time, you may use the > RANSAC tools without compiling by simply adding the appropriate Python > files into the correct locations. > > Regards > Stéfan > > On Sat, Sep 14, 2013 at 12:21 AM, Pierre Villeneuve > <pierre.v...(a)gmail.com <javascript:>> wrote: > > I am eagerly awaiting the new RANSAC model fitting tools in the current > dev > > version. I am working on Windows 8 x64 and it turns into a total mess > when > > I try to compile skimage myself. I normally rely on the binaries at > Chris > > Gohlke's site, but he only has the current stable version 0.8.2. I am > just > > curious to know if there is a planned timeframe for releasing 0.9? > Thanks! > > > > -- > > 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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Any plans for 0.9 release?
by Pierre Villeneuve Sept. 13, 2013

Sept. 13, 2013

I am eagerly awaiting the new RANSAC model fitting tools in the current dev version. I am working on Windows 8 x64 and it turns into a total mess when I try to compile skimage myself. I normally rely on the binaries at Chris Gohlke's site, but he only has the current stable version 0.8.2. I am just curious to know if there is a planned timeframe for releasing 0.9? Thanks!

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Re: Intensity plot of along the line
by Guillaume Gay Sept. 13, 2013

Sept. 13, 2013

There's a line profile tool in the Tony Yu's ImageViewer.. On 12/09/2013 18:29, Thomas A Caswell wrote: > scipy.ndimage.interpolation.map_coordinates > (http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.interpola…) > + matplotlib will do what you want. > > Tom > > > On Thu, Sep 12, 2013 at 11:19 AM, Dan <dkin(a)walla.co.il > <mailto:dkin@walla.co.il>> wrote: > > Hi, > > Is there a way to generate an intensity plot of along the line > using scikit-image (like Plot Profile option in imageJ) (example: > http://imagej.1557.x6.nabble.com/file/n3682337/cracks.png). > > Thanks. > -- > 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 > <mailto:scikit-image%2Bunsubscribe@googlegroups.com>. > For more options, visit https://groups.google.com/groups/opt_out. > > > > > -- > Thomas A Caswell > PhD Candidate University of Chicago > Nagel and Gardel labs > tcaswell(a)uchicago.edu <mailto:tcaswell@uchicago.edu> > jfi.uchicago.edu/~tcaswell <http://jfi.uchicago.edu/%7Etcaswell> > o: 773.702.7204 > -- > 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: Intensity plot of along the line
by Stéfan van der Walt Sept. 13, 2013

Sept. 13, 2013

On Thu, Sep 12, 2013 at 6:29 PM, Thomas A Caswell <tcaswell(a)uchicago.edu> wrote: > scipy.ndimage.interpolation.map_coordinates > (http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.interpola…) > + matplotlib will do what you want. For the record, map_coordinates is quite hard to use--have a look at skimage.transform.warp as well. Stéfan

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Re: Get border pixels of labelled region
by Juan Nunez-Iglesias Sept. 13, 2013

Sept. 13, 2013

The input is a grayscale image, not a binary image. It finds contours of a given intensity threshold. The output is a list of arrays. Each array has shape (Q, 2), and it is a set of x, y coordinates of the points in the contour. If you want to look at the contours, you need to convert this to an image somehow. This example uses matplotlib's `plot` function to draw the contours on the image: http://scikit-image.org/docs/dev/auto_examples/plot_contours.html#example-p… Alternately, you can round the contour coordinates to int and use those to make a new image: conts = find_contours(image, threshold) contour_image = zeros_like(image) for c in conts: c = np.round(c).astype(int) coords = (c[:, 0], c[:, 1]) contour_image[coords] = 1 imshow(contour_image) On Fri, Sep 13, 2013 at 5:26 PM, Payal Gupta <erpayal2010(a)gmail.com> wrote: > hi juan.... > > i can't understand array after using find_contour which return a ndarray. > it is main prob i wanna find out contour array. > > > On Fri, Sep 13, 2013 at 6:07 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > >> Hi Payal, >> >> I think we're getting somewhere. =) Thanks for the image. >> >> Questions: >> 1) Are you looking to segment out different cars? That is, do you want >> each car to have its own contour? With your current thresholding, you can >> see that the four cars on the right are all connected, so you would get a >> single contour of the whole blob, rather than a contour of each car. >> 2) I just saw the doc<http://www.mathworks.com.au/help/images/ref/bwboundaries.html>for bwboundaries. Do you want the interior holes of the objects to have its >> own contour, or do you want just a contour *around* each object and don't >> care about the interior? Also, do you care about parent/child object >> relationships? My guess is no to both these questions. For example, do you >> want a contour around the windshield of each car? >> >> Comments: >> >> Note that when you do rgb2gray on a thresholded RGB image, you no longer >> have a binary image, but a grayscale image with levels 0, 0.333, 0.667, and >> 1.0. I think you probably mean to do rgb2gray followed by threshold. >> >> Either way, my suspicion is that you want to segment the cars first (get >> one binary blob object per car), then find their contours. Am I right? >> >> Juan. >> >> >> On Thu, Sep 12, 2013 at 8:24 PM, Payal Gupta <erpayal2010(a)gmail.com>wrote: >> >>> hi Juan... >>> i have done it.... :) :) >>> plz solve the contour problem. :( :( >>> reply me >>> >>> On Thursday, September 12, 2013 9:19:36 AM UTC+5:30, Juan Nunez-Iglesias >>> wrote: >>> >>>> On Thu, Sep 12, 2013 at 2:58 AM, Payal Gupta <erpay...(a)gmail.com>wrote: >>>> >>>>> hello... >>>>> i m also use this prog to count white pixel and black pixel bt i cant >>>>> save an image and cant count the pixel. >>>>> can you help me. >>>>> >>>> >>>> "white pixels" and "black pixels" will mean different things with >>>> different images. Can you send us a sample image? >>>> >>> -- >>> 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. >>> >> >> -- >> 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/rXRS0KT2PdU/unsubscribe. >> To unsubscribe from this group and all of its topics, send an email to >> scikit-image+unsubscribe(a)googlegroups.com. >> >> 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+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. >

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Re: Get border pixels of labelled region
by Payal Gupta Sept. 13, 2013

Sept. 13, 2013

hi juan.... i can't understand array after using find_contour which return a ndarray. it is main prob i wanna find out contour array. On Fri, Sep 13, 2013 at 6:07 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > Hi Payal, > > I think we're getting somewhere. =) Thanks for the image. > > Questions: > 1) Are you looking to segment out different cars? That is, do you want > each car to have its own contour? With your current thresholding, you can > see that the four cars on the right are all connected, so you would get a > single contour of the whole blob, rather than a contour of each car. > 2) I just saw the doc<http://www.mathworks.com.au/help/images/ref/bwboundaries.html>for bwboundaries. Do you want the interior holes of the objects to have its > own contour, or do you want just a contour *around* each object and don't > care about the interior? Also, do you care about parent/child object > relationships? My guess is no to both these questions. For example, do you > want a contour around the windshield of each car? > > Comments: > > Note that when you do rgb2gray on a thresholded RGB image, you no longer > have a binary image, but a grayscale image with levels 0, 0.333, 0.667, and > 1.0. I think you probably mean to do rgb2gray followed by threshold. > > Either way, my suspicion is that you want to segment the cars first (get > one binary blob object per car), then find their contours. Am I right? > > Juan. > > > On Thu, Sep 12, 2013 at 8:24 PM, Payal Gupta <erpayal2010(a)gmail.com>wrote: > >> hi Juan... >> i have done it.... :) :) >> plz solve the contour problem. :( :( >> reply me >> >> On Thursday, September 12, 2013 9:19:36 AM UTC+5:30, Juan Nunez-Iglesias >> wrote: >> >>> On Thu, Sep 12, 2013 at 2:58 AM, Payal Gupta <erpay...(a)gmail.com> wrote: >>> >>>> hello... >>>> i m also use this prog to count white pixel and black pixel bt i cant >>>> save an image and cant count the pixel. >>>> can you help me. >>>> >>> >>> "white pixels" and "black pixels" will mean different things with >>> different images. Can you send us a sample image? >>> >> -- >> 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. >> > > -- > 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/rXRS0KT2PdU/unsubscribe. > To unsubscribe from this group and all of its topics, send an email to > scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/groups/opt_out. >

1 0

Re: Get border pixels of labelled region
by Payal Gupta Sept. 13, 2013

Sept. 13, 2013

hi Juan... i have done it.... :) :) plz solve the contour problem. :( :( reply me On Thursday, September 12, 2013 9:19:36 AM UTC+5:30, Juan Nunez-Iglesias wrote: > > On Thu, Sep 12, 2013 at 2:58 AM, Payal Gupta <erpay...(a)gmail.com<javascript:> > > wrote: > >> hello... >> i m also use this prog to count white pixel and black pixel bt i cant >> save an image and cant count the pixel. >> can you help me. >> > > "white pixels" and "black pixels" will mean different things with > different images. Can you send us a sample image? >

2 1

Intensity plot of along the line
by Dan Sept. 12, 2013

Sept. 12, 2013

Hi, Is there a way to generate an intensity plot of along the line using scikit-image (like Plot Profile option in imageJ) (example: http://imagej.1557.x6.nabble.com/file/n3682337/cracks.png). Thanks.

2 1

Get border pixels of labelled region
by Robin Wilson Sept. 12, 2013

Sept. 12, 2013

Hi all, Is there a way to get the pixels on the border of a labelled region in an image using skimage? I've done edge detection, and then filled the resulting shapes (after some edge linking), and would now like to be able to get the pixels on the border of each of these shapes. I would have thought that getting borders would be an option in regionprops, but it doesn't seem to be. Any ideas? Cheers, Robin

3 4

Re: Get border pixels of labelled region
by Juan Nunez-Iglesias Sept. 12, 2013

Sept. 12, 2013

On Thu, Sep 12, 2013 at 2:58 AM, Payal Gupta <erpayal2010(a)gmail.com> wrote: > hello... > i m also use this prog to count white pixel and black pixel bt i cant save > an image and cant count the pixel. > can you help me. > "white pixels" and "black pixels" will mean different things with different images. Can you send us a sample image?

1 0

Re: Get border pixels of labelled region
by Payal Gupta Sept. 11, 2013

Sept. 11, 2013

hello... i m also use this prog to count white pixel and black pixel bt i cant save an image and cant count the pixel. can you help me. from skimage import measure from numpy import array import skimage.io as io from skimage import data_dir from skimage.data import coins,camera import matplotlib.pyplot as plt import skimage.color as color from skimage.data import camera from skimage.filter import canny, sobel import Image from skimage import data,filter image = io.imread("IMG_1.jpg") thresh = filter.threshold_otsu(image) binary = image > thresh imag= color.colorconv.rgb2grey(binary) img = array(imag) print img x = np.array((255, 255)) x = np.array((255, 255), dtype=np.uint8) #x[:] = np.arange(255) io.imsave('imag.png', x) #im = Image.open() white_points = 0 black_points=0 for row in range(0,244): for col in range(0, 461): if(img(row,col)==1): white_points = white_points+1 else: black_points = black_points+1 print white_points On Wed, Sep 11, 2013 at 1:49 PM, Payal Gupta <erpayal2010(a)gmail.com> wrote: > hello everyone... > i used find_contour function which returns a 2D ndarray . i can't > understand the return array so any body help me. > *program :* > > image = io.imread("IMG_2.jpg") > > thresh = filter.threshold_otsu(image) > > binary = image > thresh > > imag= color.colorconv.rgb2grey(binary) > > img = array(imag) > > edge_canny = canny(img) > > edge_sobel = sobel(img) > > contours = measure.find_contours(imag,0.9,'high') > > print contours > > fig, (ax0, ax1) = plt.subplots(ncols=2) > > ax0.imshow(imag ,cmap=plt.cm.gray) > > ax0.set_title('Roberts Edge Detection') > > ax0.axis('off') > > ax1.imshow(edge_canny, cmap=plt.cm.gray) > > ax1.set_title('Sobel Edge Detection') > > ax1.axis('off') > > > *returns array:* > > > [array([[ 135. , 72.9 ], > [ 134. , 72.9 ], > [ 133. , 72.9 ], > ..., > [ 1. , 21.52941176], > [ 0.47058824, 21. ], > [ 0. , 20.9 ]]), array([[ 0. , > 104.35137034], > [ 1. , 104.35137034], > [ 1.64862966, 105. ], > [ 2. , 105.1 ], 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[ 135. , 50.1 ]])] > >>> > Click here to Reply or Forward > Why this ad?Ads – > Best CTET Coaching Delhi<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CXWpUwCYwUq__JrOoiga6x4…> > Classroom Coaching by Experts with Study Material & Mock Tests. 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Free Shipping, COD, Shop Now! > jabong.com/Sandals/Fastest_Delivery<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CsfKtwCYwUq__JrOoiga6x4…> > ICICI™ Car Insurance<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CenrHwCYwUq__JrOoiga6x4…> > Free Quick Quotes In 30 secs .Now, Also Use Fb to login & Insure > ICICILombard.com/Car_Insurance<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CenrHwCYwUq__JrOoiga6x4…> > Jobs In TCS<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CqOzuwCYwUq__JrOoiga6x4…> > Apply today - Upload your profile A Unique 4th Generation Job Portal > www.wisdomjobs.com<http://www.googleadservices.com/pagead/aclk?sa=L&ai=CqOzuwCYwUq__JrOoiga6x4…> > > <http://www.googleadservices.com/pagead/aclk?sa=L&ai=CXWpUwCYwUq__JrOoiga6x4…> > > > On Thu, Sep 5, 2013 at 12:19 PM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > >> Hi Payal, >> >> I think you're misunderstanding the purpose of "find_boundaries"... Not >> quite your fault since the documentation is pretty sparse there. >> >> I'll use my favourite fuzzball as an example: >> >> [image: Inline image 1] >> >> "find_boundaries" is meant to take in a segmentation, which is an image >> in which each region has a different integer label, like this one: >> >> [image: Inline image 2] >> >> Then, find_boundaries merely looks for pixels where the neighbouring >> labels are different: >> >> [image: Inline image 3] >> >> It's not doing any edge detection per se, it's just a tool for displaying >> segmentations when it is easier to look at edges than at regions (above). I >> think what you are after is edge detection? Maybe an image like this one: >> >> [image: Inline image 4] >> ? >> >> For that, you should directly use the edge detection algorithms, such as >> Sobel or Canny, without previously thresholding your image. Have a close >> look at the examples gallery to figure out if any are close to what you are >> after, and try to apply the code there to your own image: >> >> http://scikit-image.org/docs/dev/auto_examples/ >> >> Some of the more pertinent ones, I think: >> http://scikit-image.org/docs/dev/auto_examples/plot_canny.html >> http://scikit-image.org/docs/dev/auto_examples/plot_edge_filter.html >> >> http://scikit-image.org/docs/dev/auto_examples/plot_join_segmentations.html >> http://scikit-image.org/docs/dev/auto_examples/plot_label.html >> http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html >> >> http://scikit-image.org/docs/dev/auto_examples/plot_random_walker_segmentat… >> http://scikit-image.org/docs/dev/auto_examples/plot_watershed.html >> >> http://scikit-image.org/docs/dev/auto_examples/applications/plot_coins_segm… >> >> Note that in the edge detection examples, Canny/Sobel is applied to the >> image *before* any thresholding — unlike the example code you provided. >> >> Juan. >> >> >> On Wed, Sep 4, 2013 at 5:31 PM, Payal Gupta <erpayal2010(a)gmail.com>wrote: >> >>> hello everyone... >>> i will try this code,in this i want to do read a image then do edge >>> detection after that find the boundaries of image object. but >>> find_boundaries return me a bool array but i need a integer array. is it >>> any solution of this. >>> >>> >>> code:: >>> >>> import Image >>> >>> from skimage import segmentation as seg,io,filter >>> >>> imge = io.imread("IMG_1.jpg") >>> >>> thresh = filter.threshold_otsu(imge) >>> >>> binary = imge> thresh >>> >>> edge_canny = filter.canny(binary) >>> >>> bimg =seg.find_boundaries(binary) >>> >>> print(bimg) >>> >>> fig, (ax0, ax1) = plt.subplots(ncols=2) >>> >>> ax0.imshow(bimg,cmap=plt.cm.gray) >>> ax1.imshow(binary,cmap=plt.cm.gray) >>> >>> >>> On Tue, Sep 3, 2013 at 7:42 PM, Stéfan van der Walt <stefan(a)sun.ac.za>wrote: >>> >>>> >>>> On 3 Sep 2013 11:45, "Payal Gupta" <erpayal2010(a)gmail.com> wrote: >>>> > >>>> > thanks it working but i confused when i use function of skimage >>>> library. i want to change rgb image to a graylevel image but inbuilt >>>> function rgb2gray not convert gray level image. >>>> > reply. >>>> >>>> If you want help on this list, please provide code examples of what you >>>> are attempting. >>>> >>>> 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/rXRS0KT2PdU/unsubscribe. >>>> To unsubscribe from this group and all of its topics, send an email to >>>> scikit-image+unsubscribe(a)googlegroups.com. >>>> 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+unsubscribe(a)googlegroups.com. >>> >>> For more options, visit https://groups.google.com/groups/opt_out. >>> >> >> -- >> 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/rXRS0KT2PdU/unsubscribe. >> To unsubscribe from this group and all of its topics, 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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