Are you planning to support Yolo11 anytime soon?
YOLO11
Hi @Iqbalalwi,
I apologize, but I am not sure at what exactly you are referring. Do you mean that you compared the latency of YOLOv11 against YOLOv10 and that YOLOv10 was much faster?
Best,
Jan
- Edited
I was experimenting with the pre-trained YOLO11n detection model from Ultralytics, and I found that if I convert it into a Blob like this:
$ python3 -c 'from ultralytics import YOLO ; model = YOLO("yolo11n.pt") ; model.export(format="onnx")'
$ python3 -m blobconverter --onnx-model yolo11n.onnx --shaves 3
...and then try to run the model using the YOLOv8 example code, I get the following error over and over again:
[1944301041162F1200] [1.3] [3.861] [DetectionNetwork(1)] [error] Mask is not defined for output layer with width '8400'. Define at pipeline build time using: 'setAnchorMasks' for 'side8400'.
If however I use the online model exporter to convert the weights file yolo11n.pt
into a blob, then it works.
Why is that? Is there some missing blobconverter
option that the online tool applies automatically behind the scenes?
- Edited
Hi @xperroni,
yes, that's a good question. Tools (our online exporter tailored for YOLO conversion) actually uses a slightly edited Detection head, which removes some of the final processing operations from the original head. That is because these steps are done inside the YoloDetectionNetwork
node from DepthAI library, so that is why it didn't work.
Kind regards,
Jan