for the limit for uint8 regardless of what may be routine is 255 ;)
that said, I think a more important question is how should we handle overflow on uint8 images? and should we even bother trying?
The numpy standard is to wrap, the opencv standard is to threshold at 255. I don't see any easy way to make either of these two do it the other way.
2009/10/22 Stéfan van der Walt email@example.com:
2009/10/21 Ralf Gommers firstname.lastname@example.org:
The code I have so far lives here: http://github.com/rgommers/scikits.image/tree/color
Thanks for cleaning up the colour conversion routines! Here are some review comments:
- Add this contribution to CONTRIBUTORS.txt
- Do not check types explicitly against ndarray. A safer route is to
- "float32" is not a valid dtype descriptor -- use np.float32 instead
- Question: why are there NaN's in the output?
A question that pertains to the scikit as a whole: what do we assume the limits of images to be? I think a common convention is 0-255 for type uint8 and 0-1 for type float. These need to be handled in all functions, and we may soon see patterns emerging that can be captured in standard utility functions.