DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
[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
[X] I have searched the DAMO-YOLO issues and found no similar questions.
Question
Set up:
I have already organize my dataset and configs correctly.
My GPU is a RTX 3090 24GB with cuda 11.7.
Issue:
I have a command like this to train the model:
python -m torch.distributed.launch --nproc_per_node=1 tools/train.py -f configs/damoyolo_tinynasL18_Ns.pyBUT here is what I got:
P/S: I tried the solution that adding python path from issue 11 but it didn't work with my case. Please drop me a message if you think you can help. Thank you in advance!
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
Set up:
Issue:
I have a command like this to train the model:
python -m torch.distributed.launch --nproc_per_node=1 tools/train.py -f configs/damoyolo_tinynasL18_Ns.py
BUT here is what I got:P/S: I tried the solution that adding python path from issue 11 but it didn't work with my case. Please drop me a message if you think you can help. Thank you in advance!
Additional
No response