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Firstly, thank u a lot. It looks like the best mask-rcnn implementation. (cause it does not use this magic from config import cfg)
Nevertheless, something is a bit strange for me. In the model init you define self.mask_head (cause it needed for segmentation task), but in the forward pass you dont use it at all. How is that?
Thanks!
The text was updated successfully, but these errors were encountered:
Please see the demo notebooks for the usage of the mask head. Essentially there is a results postprocess stage between the forward pass and running the mask head.
Ideally this post-processing stage (which involves NMS and other things) should also be converted into a torch.nn.Module, but this is not the case for now.
Hi!
Firstly, thank u a lot. It looks like the best mask-rcnn implementation. (cause it does not use this magic
from config import cfg
)Nevertheless, something is a bit strange for me. In the model
init
you defineself.mask_head
(cause it needed for segmentation task), but in theforward
pass you dont use it at all. How is that?Thanks!
The text was updated successfully, but these errors were encountered: