Users want to be able to easily train DETR via fine tuning for their own datasets.
Each user dataset will have it's own num_classes.
Currently the detr.py::build(args) function determines the num_classes by defaulting to 20 or 91 (coco) or 250 (coco_panoptic), based on the args.dataset_file param:
Thus, request:
is there an addition to support an args.num_classes to be passed in that can be easily adjusted, and have that be used for model creation instead of the defaults based on dataset_file arg?
I could make a quick PR for this if that helps?
NOTE:
Only general answers are provided.
If you want to ask about "why X did not work", please use the
Unexpected behaviors issue template.
About how to implement new models / new dataloader / new training logic, etc., check documentation first.
We do not answer general machine learning / computer vision questions that are not specific to DETR, such as how a model works, how to improve your training/make it converge, or what algorithm/methods can be used to achieve X.
❓ How to do something using DETR
Describe what you want to do, including:
Users want to be able to easily train DETR via fine tuning for their own datasets. Each user dataset will have it's own num_classes.
Currently the detr.py::build(args) function determines the num_classes by defaulting to 20 or 91 (coco) or 250 (coco_panoptic), based on the args.dataset_file param:
https://github.com/facebookresearch/detr/blob/master/models/detr.py#L304
Thus, request: is there an addition to support an args.num_classes to be passed in that can be easily adjusted, and have that be used for model creation instead of the defaults based on dataset_file arg?
I could make a quick PR for this if that helps?
NOTE:
Only general answers are provided. If you want to ask about "why X did not work", please use the Unexpected behaviors issue template.
About how to implement new models / new dataloader / new training logic, etc., check documentation first.
We do not answer general machine learning / computer vision questions that are not specific to DETR, such as how a model works, how to improve your training/make it converge, or what algorithm/methods can be used to achieve X.