finetune-anything
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ziqi-jin
Fine-tune SAM (Segment Anything Model) for computer vision tasks such as semantic segmentation, matting, detection ... in specific scenarios
It's not a issue but I want to do a segmentation on point clouds and I have a .laz files for finetuning sam model. So, basically I should create a...
如题，如果sam在某些数据上表现不好，大概率是sam的数据集里面不包含某些场景。微调sam也需要不少资源，单纯的微调sam能解决数据集之间域的差别吗？会比从头训练一个小一点的模型好吗？
An interesting job, but I have some questions. Why set mask_scale=1 with multimask_output=True instead of mask_scale=0 with multimask_output=False here? https://github.com/ziqi-jin/finetune-anything/blob/85a0658cb0011a504aa73f2399cf4ab305cc8a65/extend_sam/mask_decoder_heads.py#L192
Thank you for your warm answer! After finetuning, how do you successfully predict samples?
Hello team, great work. I had one doubt, during fine tuning, What is used as ground truth to calculate the loss against the masks generated by SAM with any prompt?
