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There was also a minor issue if the patch size is equal to the image size in a dimension
(missing +1, rand numbers low=a high=b -> sample from [a,b) so b can be the max_size). I corrected this.
This is very helpful to use the patch sampler as a slice sampler (for instance slicing 512x512 from 512x512x156 volumes).
Cheers
Tobias
The text was updated successfully, but these errors were encountered:
Hi fernando,
I recently switched from tf to pytorch and I was really happy to find your library.
Great work! Thanks.
I added a more efficient image sampler to sample random patches which should contain
at least one point of a specific label.
https://github.com/lab-midas/midas-torchio/blob/dev_tobias/torchio/data/sampler/label.py
(code and examples are still a bit messy, I will work on this the next days).
But maybe you can use (parts of) it ;)
There was also a minor issue if the patch size is equal to the image size in a dimension
(missing +1, rand numbers low=a high=b -> sample from [a,b) so b can be the max_size). I corrected this.
This is very helpful to use the patch sampler as a slice sampler (for instance slicing 512x512 from 512x512x156 volumes).
Cheers
Tobias
The text was updated successfully, but these errors were encountered: