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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