On 10/26/2011 08:22 PM, StÃ¯Â¿Â½fan van der Walt wrote:
Sorry for the late reply.
No problem. As you might have noticed I haven't really had the time to do anything on scikits-image lately :(
Usually, this will require you to write code that can only be run on an opencv system, but with the plugin system you can easily share that code with colleagues who do not have opencv installed:
use_backend('my_opencv_routines') output = sobel(input)
If the opencv backend is not found, the backend gracefully falls back to the NumPy / Cython implementation.
I do see your point. On the other hand, if someone found code that was "way better" than the one in scikits-image, I would rather hope people would integrate it. Making the backends easy to substitute might encourage bad scikits-image code.. or rather encourage not changing it.
The above obviously does not apply to OpenCL and Cuda implementations. Then again, it _might_ be a good idea to include OpenCL or Cuda functions in directly into scikits-image. I, personally, would love to have a library with gpu based vision algorithms (except opencv). If scikits-image is a good place for this is certainly debatable.