from ultralytics import YOLOv10

model = YOLOv10.from_pretrained('jameslahm/yolov10n')
# Training
model.train(...)
# after training, one can push to the hub
model.push_to_hub("your-hf-username/yolov10-finetuned")

# Validation
model.val(...)

Inference

Here's an end-to-end example showcasing inference on a cats image:

python

from ultralytics import YOLOv10

model = YOLOv10.from_pretrained('jameslahm/yolov10n')
source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
model.predict(source=source, save=True)

which shows:

BibTeX Entry and Citation Info

@article{wang2024yolov10,
 title={YOLOv10: Real-Time End-to-End Object Detection},
 author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang},
 journal={arXiv preprint arXiv:2405.14458},
 year={2024}
}