@Rachel-liuqr I have great news 😃! I've recently added official support for Ultralytics YOLOv8 NCNN export ✅ in PR https://github.com/ultralytics/ultralytics/pull/3529 with the help of @nihui which is part of `ultralytics==8.0.129`. NCNN works for all tasks including Detect, Segment, Pose and Classify.

[xkai66]

          @Rachel-liuqr I have great news 😃! I've recently added official support for Ultralytics YOLOv8 NCNN export ✅ in PR https://github.com/ultralytics/ultralytics/pull/3529 with the help of @nihui which is part of `ultralytics==8.0.129`. NCNN works for all tasks including Detect, Segment, Pose and Classify.

You can now export with CLI:

yolo export model=yolov8n.pt format=ncnn

or Python:

from ultralytics import YOLO

# Create a model
model = YOLO('yolov8n.pt')

# Export the model to NCNN with arguments
model.export(format='ncnn', half=True, imgsz=640)

Output is a yolov8n_ncnn_model/ directory containing model.bin, model.param and metadata.yaml, along with extra PNNX files. For details see https://github.com/pnnx/pnnx README.

To get this update:

• Git – Run git pull from within your ultralytics/ directory or run git clone https://github.com/ultralytics/ultralytics again
• Pip – Update with pip install -U ultralytics
• Notebooks – Check out the updated notebooks
• Docker – Run sudo docker pull ultralytics/ultralytics:latest to update your image

Please let us know if NCNN export is working correctly for you, and don't hesitate to report any other issues you find or feature requests you may have. Happy training with YOLOv8 🚀!

Originally posted by @glenn-jocher in #4649 (comment)

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