conda create -n aienv2 python=3.10
激活环境

conda create -n yolo_trt_10 python=3.10 -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/ -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ --override-channels



最后安装tensorrt依赖的whl包，不然gdal 安装不上


conda activate aienv
安装本地环境所需的包
//cuda 版本需要根据本地硬件做适配
同时安装ultralyticsopencv，可以解决opencv 无法读取rtmp的问题

conda install -c pytorch -c nvidia -c conda-forge -c defaults pytorch torchvision pytorch-cuda=12.4  -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/ -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ --override-channels

ultralytics opencv 

conda install  -c conda-forge sanic  minio paho-mqtt sanic-cors -y


conda remove --name aimmseg --all   删除环境

# 执行清理后
conda clean --all


# 20250708 最新最新环境安装命令如下，既要适配sanic的3.9及以上，也要适配mmseg的torch版本

conda create -n aimmseg python=3.10


windows
pip install mmcv==2.0.0 -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.0/index.html -i https://mirrors.aliyun.com/pypi/simple/
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia

试一下torch2.0.1
conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia
mamba install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia

linux
pip install mmcv==2.0.0 -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.0/index.html
conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia


pip install av -i https://mirrors.aliyun.com/pypi/simple/

pip install -U openmim -i https://mirrors.aliyun.com/pypi/simple/

pip install "mmsegmentation>=1.0.0" -i https://mirrors.aliyun.com/pypi/simple/

pip install ftfy -i https://mirrors.aliyun.com/pypi/simple/
pip install opencv-python -i https://mirrors.aliyun.com/pypi/simple/

pip install rasterio einops imageio albumentations opencv-contrib-python  -i https://mirrors.aliyun.com/pypi/simple/

版本问题，需要保证numpy低于 2.0
python -c "import numpy; print(numpy.__version__)"

#torch版本低，需要降级numpy
pip uninstall numpy -y
pip install "numpy<2.0"  # 安装 1.26.4 或更早版本

pip install numpy==1.24.4

pip install --no-deps albumentations==2.0.8  -i https://pypi.tuna.tsinghua.edu.cn/simple

mmsegmentation