I tried to find a way to do this without having to post an issue, but I couldn't get any hint so far. I really hope someone can help.
So I'm trying to use Alexey repository to train YOLOR_p6 on my custom dataset, but there hasn't been any update concerning yolor over there (the latest enhancement was regarding yolo_csp). So I tried on my own, and while the cfg file is available here, I can only find the weights as .pt files.
Is there a way to convert the .pt file into a weight file that I can use with the cfg file to train using darknet? (Since I assume darknet cannot use pytorch weights), or is it preferable to avoid training with darknet and just use pytorch to train?
If Pytorch is the best (or only) way, will I need to reorganize my dataset and labels (already organized to match darknet format) ?
Thanks a lot for any help or advice !!
Edit: It seems like even the cfg file needs to be converted to darknet format according to a post I came across. Can anyone please confirm that as well?
I tried to find a way to do this without having to post an issue, but I couldn't get any hint so far. I really hope someone can help.
So I'm trying to use Alexey repository to train YOLOR_p6 on my custom dataset, but there hasn't been any update concerning yolor over there (the latest enhancement was regarding yolo_csp). So I tried on my own, and while the cfg file is available here, I can only find the weights as .pt files.
Is there a way to convert the .pt file into a weight file that I can use with the cfg file to train using darknet? (Since I assume darknet cannot use pytorch weights), or is it preferable to avoid training with darknet and just use pytorch to train?
If Pytorch is the best (or only) way, will I need to reorganize my dataset and labels (already organized to match darknet format) ?
Thanks a lot for any help or advice !!
Edit: It seems like even the cfg file needs to be converted to darknet format according to a post I came across. Can anyone please confirm that as well?