README.md

metadata

datasets:
  - detection-datasets/coco
library_name: ultralytics
license: agpl-3.0
tags:
  - object-detection
  - computer-vision
  - yolov10
repo_url: https://github.com/THU-MIG/yolov10
inference: false

Model Description

YOLOv10: Real-Time End-to-End Object Detection

• arXiv: https://arxiv.org/abs/2405.14458v1
• github: https://github.com/THU-MIG/yolov10

Installation

pip install git+https://github.com/THU-MIG/yolov10.git

Training and validation

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:

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}
}