Mailman 3 April 2014 - scikit-image

Master branch missing io/video.py
by Bill Gabella 08 Apr '14

08 Apr '14

Sorry if this is posted somewhere, but I could not find it. The Master branch is missing skimage/io/video.py making the Master unusable (at least for my applications). I see that file in the other branches. Is there a reason it does not show up in the default, Master branch? thanks, bill e.g.

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Lineprofile, how to retrieve data?
by Math Gon 07 Apr '14

07 Apr '14

Hello everybody, I used the tutorial example to open and image and draw the histogram for a line but, unfortunatly, I didn't manage to retrieve the data for this line. image = scipy.misc.imread('myImage.bmp') new_viewer = viewer.ImageViewer(image) new_viewer += lineprofile.LineProfile() new_viewer.show() I tried many things but I don't understand, may someone give me an advice please? Best regards

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Re: watershed algorithm for segmentation
by amit bhatkal 04 Apr '14

04 Apr '14

Thanks a lot for the explanation Juan . I am infact working with FIBSEM image which basically consists of only black pores in grey solid matter. So what would be suitable as an "image" for my case? a *gradient image* or *distance transformed image*? And , I feel I have got a better understanding of the watershed() method thanks to your explanation. With regards, Amit On Fri, Apr 4, 2014 at 11:23 AM, Juan Nunez-Iglesias <jni.soma(a)gmail.com>wrote: > Amit, > > The confusion here is just semantics. A gradient is an image. In our > context, any two-dimensional boolean or numeric array is an image. The > watershed algorithm works by flooding a landscape from the bottom up, so > you want your input to be an image where your regions will have low > intensity and the boundaries between them will have high intensity. In the > example, the distance transformed image satisfies this property, while the > original does not. In other cases, your input image may satisfy the > property without requiring a transform (for example, electron microscopy > data). > > Juan. > > > On Fri, Apr 4, 2014 at 3:09 PM, amit bhatkal <amitbhatkal12(a)gmail.com>wrote: > >> Thank you Tony and Ronnie for your timely inputs. >> I was going through the link provided by Tony >> "http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html<http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html>" . Here in line 16 of the code >> >> # process the watershedlabels = watershed(gradient, markers) >> >> Also I came across this code : http://scikit-image.org/docs/dev/auto_examples/plot_watershed.html >> >> Which uses distance map in the place of image. >> >> >> The actual sytax is : >> watershed(*image*, *markers*, *connectivity=None*, *offset=None*, *mask=None*) >> >> The "image" parameter of the watershed function is fed with "gradient" instead of actual image. This is the point of confusion. So thats what I wanted to clarify. Should I be providing the actual image data or some edge detected or gradient image for the watershed. >> >> >> >> Thank you >> >> Amit >> >> >> >> On Thu, Apr 3, 2014 at 8:04 PM, Tony Yu <tsyu80(a)gmail.com> wrote: >> >>> >>> >>> >>> On Thu, Apr 3, 2014 at 4:46 AM, <amitbhatkal12(a)gmail.com> wrote: >>> >>>> Hi everyone, >>>> I was trying to segment a greyscale 8 bit image using the watershed >>>> algorithm present in skimage.morphology but I am confused as to what should >>>> I provide as inputs to the watershed(). >>>> Can anyone please help me in this regard. >>>> This is what I gathered from the documentation. >>>> >>>> *image: ndarray (2-D, 3-D, ...) of integers* : >>>> >>>> Data array where the lowest value points are labeled first. >>>> >>>> *markers: ndarray of the same shape as `image`* : >>>> >>>> An array marking the basins with the values to be assigned in the label >>>> matrix. Zero means not a marker. This array should be of an integer type. >>>> >>>> Here "image" refers to original image or something else? >>>> How do I obtain the markers ? >>>> >>>> >>> Hi, you should take a look at the gallery examples. Here's a >>> particularly relevant one: >>> >>> http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html >>> >>> >>> Cheers, >>> -Tony >>> >>> -- >>> 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. >>> >> >> -- >> 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. >> > > -- > 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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Re: watershed algorithm for segmentation
by Juan Nunez-Iglesias 04 Apr '14

04 Apr '14

Amit, The confusion here is just semantics. A gradient is an image. In our context, any two-dimensional boolean or numeric array is an image. The watershed algorithm works by flooding a landscape from the bottom up, so you want your input to be an image where your regions will have low intensity and the boundaries between them will have high intensity. In the example, the distance transformed image satisfies this property, while the original does not. In other cases, your input image may satisfy the property without requiring a transform (for example, electron microscopy data). Juan. On Fri, Apr 4, 2014 at 3:09 PM, amit bhatkal <amitbhatkal12(a)gmail.com>wrote: > Thank you Tony and Ronnie for your timely inputs. > I was going through the link provided by Tony > "http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html<http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html>" . Here in line 16 of the code > > # process the watershedlabels = watershed(gradient, markers) > > Also I came across this code : http://scikit-image.org/docs/dev/auto_examples/plot_watershed.html > > Which uses distance map in the place of image. > > > The actual sytax is : > watershed(*image*, *markers*, *connectivity=None*, *offset=None*, *mask=None*) > > The "image" parameter of the watershed function is fed with "gradient" instead of actual image. This is the point of confusion. So thats what I wanted to clarify. Should I be providing the actual image data or some edge detected or gradient image for the watershed. > > > Thank you > > Amit > > > > On Thu, Apr 3, 2014 at 8:04 PM, Tony Yu <tsyu80(a)gmail.com> wrote: > >> >> >> >> On Thu, Apr 3, 2014 at 4:46 AM, <amitbhatkal12(a)gmail.com> wrote: >> >>> Hi everyone, >>> I was trying to segment a greyscale 8 bit image using the watershed >>> algorithm present in skimage.morphology but I am confused as to what should >>> I provide as inputs to the watershed(). >>> Can anyone please help me in this regard. >>> This is what I gathered from the documentation. >>> >>> *image: ndarray (2-D, 3-D, ...) of integers* : >>> >>> Data array where the lowest value points are labeled first. >>> >>> *markers: ndarray of the same shape as `image`* : >>> >>> An array marking the basins with the values to be assigned in the label >>> matrix. Zero means not a marker. This array should be of an integer type. >>> >>> Here "image" refers to original image or something else? >>> How do I obtain the markers ? >>> >>> >> Hi, you should take a look at the gallery examples. Here's a particularly >> relevant one: >> >> http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html >> >> >> Cheers, >> -Tony >> >> -- >> 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. >> > > -- > 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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Re: watershed algorithm for segmentation
by amit bhatkal 04 Apr '14

04 Apr '14

Thank you Tony and Ronnie for your timely inputs. I was going through the link provided by Tony "http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html<http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html>" . Here in line 16 of the code # process the watershedlabels = watershed(gradient, markers) Also I came across this code : http://scikit-image.org/docs/dev/auto_examples/plot_watershed.html Which uses distance map in the place of image. The actual sytax is : watershed(*image*, *markers*, *connectivity=None*, *offset=None*, *mask=None*) The "image" parameter of the watershed function is fed with "gradient" instead of actual image. This is the point of confusion. So thats what I wanted to clarify. Should I be providing the actual image data or some edge detected or gradient image for the watershed. Thank you Amit On Thu, Apr 3, 2014 at 8:04 PM, Tony Yu <tsyu80(a)gmail.com> wrote: > > > > On Thu, Apr 3, 2014 at 4:46 AM, <amitbhatkal12(a)gmail.com> wrote: > >> Hi everyone, >> I was trying to segment a greyscale 8 bit image using the watershed >> algorithm present in skimage.morphology but I am confused as to what should >> I provide as inputs to the watershed(). >> Can anyone please help me in this regard. >> This is what I gathered from the documentation. >> >> *image: ndarray (2-D, 3-D, ...) of integers* : >> >> Data array where the lowest value points are labeled first. >> >> *markers: ndarray of the same shape as `image`* : >> >> An array marking the basins with the values to be assigned in the label >> matrix. Zero means not a marker. This array should be of an integer type. >> >> Here "image" refers to original image or something else? >> How do I obtain the markers ? >> >> > Hi, you should take a look at the gallery examples. Here's a particularly > relevant one: > > http://scikit-image.org/docs/dev/auto_examples/plot_marked_watershed.html > > Cheers, > -Tony > > -- > 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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watershed algorithm for segmentation
by amitbhatkal12＠gmail.com 03 Apr '14

03 Apr '14

Hi everyone, I was trying to segment a greyscale 8 bit image using the watershed algorithm present in skimage.morphology but I am confused as to what should I provide as inputs to the watershed(). Can anyone please help me in this regard. This is what I gathered from the documentation. *image: ndarray (2-D, 3-D, ...) of integers* : Data array where the lowest value points are labeled first. *markers: ndarray of the same shape as `image`* : An array marking the basins with the values to be assigned in the label matrix. Zero means not a marker. This array should be of an integer type. Here "image" refers to original image or something else? How do I obtain the markers ? Thank you

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