yolov8环境安装cuda11.2版本

1、创建

conda create -n V8 python=3.8

2、下载官方的yolov8.zip文件到服务器
先解压，再进去

unzip ultralytics-main.zip && cd ultralytics-main

再运行：

pip install -e .

3、查看pip list，把带cu12的东西都给卸载了，那一片都是

pip uninstall xxx-cu12

4、这个是我后来导出来的安装过的包，重点就是这些带cu11的东西，因为我是11.2版本的，所以之前默认安装的cu12都不适配。还是torch的版本也要注意一下哦

nvidia-cublas-cu1111.10.3.66
nvidia-cuda-cupti-cu1111.7.101
nvidia-cuda-nvrtc-cu1111.7.99
nvidia-cuda-runtime-cu1111.7.99
nvidia-cudnn-cu118.5.0.96
nvidia-cufft-cu1110.9.0.58
nvidia-curand-cu1110.2.10.91
nvidia-cusolver-cu1111.4.0.1
nvidia-cusparse-cu1111.7.4.91
nvidia-nccl-cu112.14.3
nvidia-nvtx-cu11==11.7.91

certifi==2023.7.22
charset-normalizer==3.3.0
cmake==3.27.7
contourpy==1.1.1
cycler==0.12.1
filelock==3.12.4
fonttools==4.43.1
fsspec==2023.9.2
idna==3.4
importlib-resources==6.1.0
Jinja2==3.1.2
kiwisolver==1.4.5
lit==17.0.2
MarkupSafe==2.1.3
matplotlib==3.7.3
mpmath==1.3.0
networkx==3.1
numpy==1.24.4
nvidia-cublas-cu11==11.10.3.66
nvidia-cuda-cupti-cu11==11.7.101
nvidia-cuda-nvrtc-cu11==11.7.99
nvidia-cuda-runtime-cu11==11.7.99
nvidia-cudnn-cu11==8.5.0.96
nvidia-cufft-cu11==10.9.0.58
nvidia-curand-cu11==10.2.10.91
nvidia-cusolver-cu11==11.4.0.1
nvidia-cusparse-cu11==11.7.4.91
nvidia-nccl-cu11==2.14.3
nvidia-nvtx-cu11==11.7.91
opencv-python==4.8.1.78
packaging==23.2
pandas==2.0.3
Pillow==10.0.1
psutil==5.9.5
py-cpuinfo==9.0.0
pyparsing==3.1.1
python-dateutil==2.8.2
pytz==2023.3.post1
PyYAML==6.0.1
requests==2.31.0
scipy==1.10.1
seaborn==0.13.0
six==1.16.0
sympy==1.12
thop==0.1.1.post2209072238
torch==2.0.1
torchaudio==0.8.0
torchmetrics==0.10.3
torchvision==0.15.2
tqdm==4.66.1
triton==2.0.0
typing_extensions==4.8.0
tzdata==2023.3
# Editable install with no version control (ultralytics==8.0.198)
urllib3==2.0.6
zipp==3.17.0