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Since Bonsai affords the ability to create custom centroid and instance cropping image processing routines, it would be nice to have the ability to run identification and pose estimation without the first centroid tracking step. This would be implemented through a custom single labeled instance network model. Similarly to the current single instance, it would be great if this first model always guarantees a single output per input image (even if full of NaNs).
As a side note, while certainly not necessary, is it possible to have a model wherein, from a cropped image, outputs only ClassID?
The text was updated successfully, but these errors were encountered:
Following Sleap structure, there are currently four model types supported in Bonsai:
- Multi-instance:
centroid
top-down-model
(Centroid + CenteredInstance)top-down-id-model
(Centroid + CenteredInstance + ClassID)- Single Instance:
single instance
(CenteredInstance)Since Bonsai affords the ability to create custom centroid and instance cropping image processing routines, it would be nice to have the ability to run identification and pose estimation without the first centroid tracking step. This would be implemented through a custom
single labeled instance
network model. Similarly to the currentsingle instance,
it would be great if this first model always guarantees a single output per input image (even if full ofNaN
s).As a side note, while certainly not necessary, is it possible to have a model wherein, from a cropped image, outputs only ClassID?
The text was updated successfully, but these errors were encountered: