Comments (1)
Thanks for the question.
We have conducted on similar scenarios, such as Microsoft internal FaceDetection, and get very promising results. In some issues, people have applied OTO onto some YOLO tasks. We will provide official tutorials upon our bandwidth. The key of applying OTO would be if the backbone of YOLO has not unsupported operators. Some architecture such as resnet101, darknet in https://github.com/dbolya/yolact/ should be definitely fine, but some may need a little bit architecture adjustment. See #5
from only_train_once.
Related Issues (20)
- two problems about algorithm convergence HOT 4
- How to compress the backbone of a model with an auxiliary branch? HOT 1
- How did you design your supernet search space in OTOv3? HOT 3
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- Error when testing yolov5 HOT 6
- When I replaced the model in the tutorial with my own other model, this error occurred HOT 3
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from only_train_once.