Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Parameter initialization #14

Open
guangqian-guo opened this issue Aug 24, 2024 · 2 comments
Open

Parameter initialization #14

guangqian-guo opened this issue Aug 24, 2024 · 2 comments

Comments

@guangqian-guo
Copy link

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?

@robustsam
Copy link
Owner

You can use the provided RobustSAM checkpoints for initialization, as those checkpoints retain the original SAM image encoder and prompt encoder parameters.

@ljmkgbkq
Copy link

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?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants