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Added yolov9 compatibility
Added Yolov9 compatibility:
- Yolov9 model download for E & C
- Yolov9 process ( same as yolov8 )
Other model size and demo predict will be added with time.
Amazing contribution @Hamzalopode! 🚀
Please fix the errors raised in tests by:
- Install required development packages:
pip install -e ."[dev]"
- Reformat with black and isort:
python -m scripts.run_code_style format
- Commit and push 💯
Thanks @fcakyon !
I think everything looks good now. Let me know if there is anything else.
🚀
@Hamzalopode for some reason, you updated all the prior notebook files. Can you please revert these changes?
Other than that all seems OK 🚀
Done.
Sorry I thought that applying the styling format for the notebooks was a good idea.
@Hamzalopode Can we add one level of abstraction to integrate common features between yolov8 and yolov9 (see e.g. PR #988) As far as I know there is full compatibility between the two models.
getting the following error when trying to use
TypeError: ERROR ❌️ ../weights/best.pt appears to be an Ultralytics YOLOv5 model originally trained with https://github.com/ultralytics/yolov5. This model is NOT forwards compatible with YOLOv8 at https://github.com/ultralytics/ultralytics. Recommend fixes are to train a new model using the latest 'ultralytics' package or to run a command with an official Ultralytics model, i.e. 'yolo predict model=yolov8n.pt'
The training was like
train_dual.py --sync-bn ---img 640 --cfg models/detect/yolov9-c.yaml --weights '' --name yolov9-c --hyp hyp.scratch-high.yaml
Interested in using yolov9 but cannot figure out how to get this to work. I have a custom yolov9-e model and its yaml but I cannot find any documentation on how to use it with SAHI. I've been butting my head against this for a bit and wondering if this has had any progress.
