目标检测之YOLOV11的环境搭建

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已于 2025-06-18 10:12:27 修改 · 760 阅读

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#YOLO

于 2025-06-17 16:12:47 首次发布

该文章已生成可运行项目，

1 创建虚拟环境

conda create -n yolov11 python=3.9
conda activate yolov11

2 安装ultralytics

默认是有cuda的情况下

# Install all packages together using conda
conda install pytorch torchvision

conda 还不能直接安装ultralytics，需要通过pip进行安装

pip install ultralytics

但是可能会因为网络问题报错，根据官网提示可以使用下面的方式：

pip install git+https://github.com/ultralytics/ultralytics.git@main

当然也可以试多几次，或者使用下面的命令添加尝试参数：

pip install --resume-retries 5 ultralytics

安装好后基本上差不多了，可以直接在终端上运行：yolo

(yolov11) xxx@xxx:your path to/yolov11$ yolo
WARNING ⚠️ Ultralytics settings reset to default values. This may be due to a possible problem with your settings or a recent ultralytics package update. 
View Ultralytics Settings with 'yolo settings' or at '/home/a/.config/Ultralytics/settings.json'
Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.

    Arguments received: ['yolo']. Ultralytics 'yolo' commands use the following syntax:

        yolo TASK MODE ARGS

        Where   TASK (optional) is one of ['obb', 'pose', 'detect', 'segment', 'classify']
                MODE (require