许可协议: agpl-3.0
标签:

• 目标检测
• 计算机视觉
• yolov10
• pytorch_model_hub_mixin
  数据集:
• detection-datasets/coco
  库名称: yolov10
  推理: false

模型描述

YOLOv10: 实时端到端目标检测

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

安装

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

训练与验证

from ultralytics import YOLOv10  

model = YOLOv10.from_pretrained('jameslahm/yolov10b')  
# 训练  
model.train(...)  
# 训练完成后，可推送至Hub  
model.push_to_hub("your-hf-username/yolov10-finetuned")  

# 验证  
model.val(...)  

推理

以下是一个端到端的示例，展示如何对一张猫的图片进行推理：

from ultralytics import YOLOv10  

model = YOLOv10.from_pretrained('jameslahm/yolov10b')  
source = 'http://images.cocodataset.org/val2017/000000039769.jpg'  
model.predict(source=source, save=True)  

结果如下：

BibTeX条目与引用信息

@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}  
}