Hey guys,
I finally got around to writing a draft of the proposed plugin system.
You'll find this work in the 'io' branch at
http://github.com/stefanv/scikits.image
It's still a work in progress, but I welcome all comments. Example plugins are
http://github.com/stefanv/scikits.image/blob/io/scikits/image/io/matplotlib…http://github.com/stefanv/scikits.image/blob/io/scikits/image/io/pil_plugin…
I've merged Ralf's colour space conversions, as well as his code
coverage enhancements. Ralf is now documenting the coverage process
and will also look at improving the execution time of the slow filter
tests.
For OpenCV, Chris wrote a docs-decorator that now provides us with
links to the OpenCV online reference:
http://stefanv.github.com/scikits.image/api/scikits.image.opencv.html#cvlap…
He added more functions to the cv module, and is busy implementing
some checks to make sure that even slices out of ndarray's may be
passed to OpenCV, whenever possible.
Tony Yu (welcome!) did some work on loading paletted images. I'll be
sure to review those changes tomorrow.
Have yourselves a splendid weekend!
Cheers
Stéfan
Hi,
Currently, imread doesn't properly handle palette images since PIL
palette images can't be converted directly to numpy arrays. Well, you
can convert it, but the output is garbage since the array values
correspond to the image palette, which you don't have access.
Flattening the image seems to be an OK work around, but if the image
had a color palette, this information is lost. Also, this work around
requires you to know that an image is in palette mode before calling
imread.
Below is a short patch that checks if an image is in palette mode; if
it is, grayscale images are converted to luminance mode and color
images are converted to RGB. I'm not sure if these conversions are
appropriate, but at least it's an improvement.
I hope this is helpful to somebody. Cheers,
-Tony
P.S. `palette_is_grayscale` is a convoluted function to check whether
the palette is grayscale. PIL may provide a simpler check; if so, I
couldn't find it.
P.P.S. The following link has examples of palette images if you want
to test:
http://homepages.inf.ed.ac.uk/rbf/HIPR2/libfce.htm
(NOTE: the thumbnails are actually not palette images, but the linked
images are)
~~~~~~~
diff --git a/scikits/image/io/pil_imread.py b/scikits/image/io/
pil_imread.py
index 421f45c..946d00c 100644
--- a/scikits/image/io/pil_imread.py
+++ b/scikits/image/io/pil_imread.py
@@ -34,6 +34,34 @@ def imread(fname, flatten=False, dtype=None):
" instructions.")
im = Image.open(fname)
+ if im.mode == 'P':
+ if palette_is_grayscale(im):
+ im = im.convert('L')
+ else:
+ im = im.convert('RGB')
if flatten and not im.mode in ('1', 'L', 'I', 'F', 'I;16', 'I;
16L', 'I;16B'):
im = im.convert('F')
return np.array(im, dtype=dtype)
+
+
+def palette_is_grayscale(pil_image):
+ """Return True if PIL image is grayscale.
+
+ Parameters
+ ----------
+ pil_image : PIL image
+ PIL Image that is in Palette mode.
+
+ Returns
+ -------
+ is_grayscale : bool
+ True if all colors in image palette are gray.
+ """
+ assert pil_image.mode == 'P'
+ # get palette as an array with R, G, B columns
+ palette = np.asarray(pil_image.getpalette()).reshape((256, 3))
+ # Not all palette colors are used; unused colors have junk values.
+ start, stop = pil_image.getextrema()
+ valid_palette = palette[start:stop]
+ # Image is grayscale if channel differences (R - G and G - B) are
all zero.
+ return np.allclose(np.diff(valid_palette), 0)
