Fine-tuning Segment Anything Model: Call up a saved model
Hi all,I have successfully trained my SAM model with the good guidance from the following blog post.Blog Post:Fine tune Segment Anything (SAM) for images with multiple masksI saved the weights of the trained model using the following code:torch.save(model.state_dict(), ‘model_weights.pth’).However, I am now faced with the question of how to use this saved model for my code. The original version of SAM is loaded via the following code:from segment_anything import SamAutomaticMaskGenerator, sam_model_registrysam = sam_model_registry(vit_h)(checkpoint=“/content/drive/MyDrive/…/SAMFineTune/sam_vit_h_4b8939.pth”)Note: I had to replace the square brackets at vit_h with round ones to post it here.Can anyone help me how to use the trained model now in my code to create masks? Unfortunately, I haven’t found anything yet to solve the problem.
2024-05-27T13:47:54Z
.(torch.load(model_save_path)) is the function to load it. Forward passes should be weighed according to your trained model now, in case this helps anybody!