Nvidia jetson 关于OpenCv、pytorch、torchvision等python开发环境安装

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Miniconda的安装

docs.anaconda.com/miniconda/

image.png 下载成功之后

bash Miniconda3-latest-Linux-aarch64.sh

安装完成

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之后创建相应虚拟环境

# 创建虚拟环境,其中pytorch3.8是环境名
conda create -n pytorch3.8 python=3.8

# 打开虚拟环境
conda activate pytorch3.8

OpenCv的安装

pip3 install opencv-python 

numpy安装

# 注意安装完坚持版本号,确保版本号小于1.4
pip3 install numpy

pytorch安装

# pytorch版本不能随意安装,必须安装英伟达编译的好的库文件,可通过以下命令查看Jetpack版本号
sudo apt-cache show nvidia-jetpack

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Jetpack5.1.2,选择v2.1.0版本的pytorch,pytorch下载的官网地址

下载成功之后确保在home目录中

接着进行升级和安装相应组件

sudo apt-get -y update
sudo apt-get -y install autoconf bc build-essential g++-8 gcc-8 clang-8 lld-8 gettext-base gfortran-8 iputils-ping libbz2-dev libc++-dev libcgal-dev libffi-dev libfreetype6-dev libhdf5-dev libjpeg-dev liblzma-dev libncurses5-dev libncursesw5-dev libpng-dev libreadline-dev libssl-dev libsqlite3-dev libxml2-dev libxslt-dev locales moreutils openssl python-openssl rsync scons python3-pip libopenblas-dev

然后进行pythorch安装

pip install torch-2.1.0a0+41361538.nv23.06-cp38-cp38-linux_aarch64.whl

torchvision安装

sudo apt-get update
sudo apt-get install libjpeg-dev zlib1g-dev libpython3-dev libavcodec-dev libavformat-dev libswscale-dev
git clone --branch v0.16.0 https://github.com/pytorch/vision torchvision
cd torchvision
export BUILD_VERSION=0.16.0
python3 setup.py install --user

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测试

import torch
import torchvision

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如果没有任何报错安装成功