Alasdair McAndrew <amc...@gmail.com> on Thu, 29 Nov 2012 wrote:
> Probably the combinations of OpenCV, Scipy.ndimage and scikits-image
> would cover pretty much all of my needs.
Hi,
All of those (+ mahotas, which is the package I wrote & imread which
might be useful for microscopy file formats) will work on numpy arrays
(openCV requires a bit of conversion back and forth, but it will work).
Therefore, it is not much of a bother to mix&match functions from one or
the other library::
import mahotas as mah
import imread
import skimage
import pylab
image = imread.imread("my-fancy-image.jpeg")
filtered = mah.gaussian_filter(image, 4.)
segmented = skimage.segmentation.quickshift(filtered)
pylab.imshow(segmented)
...
I just mixed 4 different packages seamlessly in this example. This will
work flawlessly.
mahotas & skimage are both under very active development, but neither is
unstable (i.e., we keep adding new features, but the existing code is
very reliable). scipy.ndimage is sort of dead: I scavenged its code for
good bits and pieces for mahotas, but nobody is developing ndimage.
If you run into specific issues, the mailing list pythonvision at
https://groups.google.com/forum/#!forum/pythonvision
is a good forum. Plenty of people from different projects lurk there.
HTH,
Luis
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