yolov9
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fine-tuning panoptic segmentation
I would like to fine-tune gelan-c-pan.pt
on a custom dataset. However I do not quite understand how to adjust the panoptic head.
If I understand gelan-c-pan.yaml
correctly ([[15, 18, 21], 1, Panoptic, [nc, 93, 32, 256]], # Panoptic(P3, P4, P5)
), nc
refers to the number of thing classes and 93
refers to the number of stuff classes?
Do I need to list thing and stuff classes separately in the data.yaml
file for the training to work?
Thanks for any help!
coco.yaml
updated.
When generating the .txt files for stuff and things, are the class-ids allowed to overlap between stuff and things? Do the class-ids of stuff in the .txt files need to match the indices of stuff_names
?
I also think panoptic/predict.py
is not working correctly with gelan-c-pan.pt
.
How to switch off stuff? My custom data only has class polygon