Ultralytics yolo下载
1. 官方Github仓库
主仓库:https://github.com/ultralytics/ultralytics
模型权重托管仓库:https://github.com/ultralytics/assets/releases
2. 全部.pt预训练权重直链(v8.3.0版本,YOLOv8+YOLO11)
# yolov8l 检测 https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l.pt # yolov8l-seg 实例分割 https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l-seg.pt # yolo11n-cls 图像分类 https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n-cls.pt # yolo11n-pose 姿态估计 https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n-pose.pt # yolov8m-obb 旋转框检测 https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8m-obb.pt3. 一键导出ONNX完整代码(复制运行)
第一步安装依赖
pipinstallultralytics第二步导出脚本
fromultralyticsimportYOLO# 逐个加载pt并导出onnxmodel_list=["yolov8l.pt","yolov8l-seg.pt","yolo11n-cls.pt","yolo11n-pose.pt","yolov8m-obb.pt"]fornameinmodel_list:model=YOLO(name)# format=onnx 导出,默认640分辨率out_path=model.export(format="onnx")print(f"导出完成:{out_path}")运行后,当前目录就会生成你需要的5个onnx文件:yolov8l.onnx、yolov8l-seg.onnx、yolo11n-cls.onnx、yolo11n-pose.onnx、yolov8m-obb.onnx
4. 服务器上一键下载+导出全套(直接粘贴到Linux服务器执行)
# 下载权重wgethttps://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l.ptwgethttps://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l-seg.ptwgethttps://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n-cls.ptwgethttps://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n-pose.ptwgethttps://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8m-obb.pt# 安装依赖pipinstallultralytics# python导出onnxpython-c" from ultralytics import YOLO models = ['yolov8l.pt','yolov8l-seg.pt','yolo11n-cls.pt','yolo11n-pose.pt','yolov8m-obb.pt'] for m in models: p = YOLO(m).export(format='onnx') print('Exported:', p) "5. 国内下载慢解决方案
如果github下载超时,可以使用加速地址:
格式:在原链接前面加https://mirror.ghproxy.com/
示例:
https://mirror.ghproxy.com/https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8l.pt补充说明
- 不要网上随便找别人打包好的onnx,输入尺寸、后处理节点各不相同,容易推理报错;官方pt导出最标准
- 如果你需要固定onnx参数(例如简化op、固定输入shape、启用dynamic),我可以给你加上对应导出参数