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Hi, authors,
The parameters of the image encoder and prompt encoder are fixed during training, how are their parameters initialized if I start training from scratch?
According to my understanding, they should be initialized with the parameters of SAM, but I didn't find this part of the code.
Could you help me with this?
The text was updated successfully, but these errors were encountered:
You can use the provided RobustSAM checkpoints for initialization, as those checkpoints retain the original SAM image encoder and prompt encoder parameters.
I noticed that the SAM weights are integrated with the new components of RobustSAM (as seen in the robustsam_checkpoint_l.pth file). I have a question regarding whether it is possible to initialize the original SAM parts with the pre-trained SAM weights while training the new parts of RobustSAM from scratch. My downstream task involves a non-visible light scenario, which differs significantly from the conditions of the pre-trained weights. Therefore, I would like to load SAM's pre-trained weights and simultaneously train the new components of RobustSAM from scratch.
Is this feasible with the current version of the code?
Hi, authors,
The parameters of the image encoder and prompt encoder are fixed during training, how are their parameters initialized if I start training from scratch?
According to my understanding, they should be initialized with the parameters of SAM, but I didn't find this part of the code.
Could you help me with this?
The text was updated successfully, but these errors were encountered: