DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
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How to freeze backbone when finetune on custom dataset #126
[X] I have read the README carefully. 我已经仔细阅读了README上的操作指引。
[X] I want to train my custom dataset, and I have read the tutorials for finetune on your data carefully and organize my dataset correctly; 我想训练自定义数据集,我已经仔细阅读了训练自定义数据的教程,以及按照正确的目录结构存放数据集。
[X] I have pulled the latest code of main branch to run again and the problem still existed. 我已经拉取了主分支上最新的代码,重新运行之后,问题仍不能解决。
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[X] I have searched the DAMO-YOLO issues and found no similar questions.
Question
Hi, I would like to know if there is an option to freeze backbone when finetuning on custom dataset. Because according to the the tutorial, there is only a line to add "self.train.finetune_path" which points to the pretrained .pth weights. However, if I run the train.py file without freezing the backbone, isn't that equal to training from scratch?
Before Asking
[X] I have read the README carefully. 我已经仔细阅读了README上的操作指引。
[X] I want to train my custom dataset, and I have read the tutorials for finetune on your data carefully and organize my dataset correctly; 我想训练自定义数据集,我已经仔细阅读了训练自定义数据的教程,以及按照正确的目录结构存放数据集。
[X] I have pulled the latest code of main branch to run again and the problem still existed. 我已经拉取了主分支上最新的代码,重新运行之后,问题仍不能解决。
Search before asking
Question
Hi, I would like to know if there is an option to freeze backbone when finetuning on custom dataset. Because according to the the tutorial, there is only a line to add "self.train.finetune_path" which points to the pretrained .pth weights. However, if I run the train.py file without freezing the backbone, isn't that equal to training from scratch?
Thank you.
Additional
No response