Produce overlay between original image and labelled objects
pennekampster at googlemail.com
Fri Nov 9 03:34:16 EST 2012
Hi Tony and Johannes,
in fact visualize_boundaries works fine and fulfills all I want, so I will
stick with it. The bounding box approach seems fine too!
Thanks to both of you for the quick response and the helpful hints!
On Thursday, November 8, 2012 6:38:56 PM UTC+1, Tony S Yu wrote:
> > wrote:
>> I want to use Python and scikit image for detection, counting and
>> measuring cells from digital pictures. So far most of the things I want to
>> do work fine: I just use a global threshold which separates my cells well
>> from the background. After labelling the thresholded objects the
>> regionprops function provides many of the features I am interested in
>> (area, centroid *etc*).
>> To be completely satisfied, I would like to produce an overlay between
>> the original image and the identified objects after thresholding for error
>> checking. I searched a while to find the proper function to do so and then
>> encountered the mark_boundaries function. However, that one is not working,
>> because the function is not found after importing the skimage.segmentation
>> module (ImportError: cannot import name mark_boundaries). Do you have any
>> suggestions, why it is not working? Or maybe you know a better way to
>> achieve my goal?
>> Many thanks,
> Hi Frank,
> Are you using the latest release (0.7) or the development version on
> github? It's a bit unfortunate, but the documentation link on the website
> goes directly to the dev docs instead of the latest release.
> I believe `mark_boundaries` is only in the development version of
> scikit-image, but really that was just a slight modification of
> `visualize_boundaries`, which should be available in 0.7. Note:
> `visualize_boundaries` doesn't work with grayscale images, so you may need
> to call `skimage.color.gray2rgb`.
> Hope that helps.
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