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I will just freeze the weights in the PipNet model itself, but I'd like to get gradients (to adjust aspects of the input image) from a loss created by the Landmarks vs some target Landmarks.
It looks like the code 'flows through' from input image to Landmark predictions - does this sound right? Or is there some strange discretisation step that would make the gradients nonsense?
The text was updated successfully, but these errors were encountered:
I will just freeze the weights in the PipNet model itself, but I'd like to get gradients (to adjust aspects of the input image) from a loss created by the Landmarks vs some target Landmarks.
It looks like the code 'flows through' from input image to Landmark predictions - does this sound right? Or is there some strange discretisation step that would make the gradients nonsense?
The text was updated successfully, but these errors were encountered: