yolo8 fun
Tue Sep 19 2023 09:49:22 GMT+0000 (Coordinated Universal Time)
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@cvataicode
import PIL.Image
from ultralytics import YOLO
import cvat_sdk.auto_annotation as cvataa
import cvat_sdk.models as models
_model = YOLO("yolov8n.pt")
spec = cvataa.DetectionFunctionSpec(
labels=[cvataa.label_spec(name, id) for id, name in _model.names.items()],
)
def _yolo_to_cvat(results):
for result in results:
for box, label in zip(result.boxes.xyxy, result.boxes.cls):
yield cvataa.rectangle(int(label.item()), [p.item() for p in box])
def detect(context, image):
return list(_yolo_to_cvat(_model.predict(source=image, verbose=False)))
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