查看显卡信息
lspci | grep -i nvidia |
查看系统是否受支持
uname -mhttp://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements |
验证是否有编译环境
gcc -v |
验证系统是否安装了正确的内核头文件和开发包
yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)# kernel、kernel-devel、kernel-headers版本必须保持一致 |
禁用nouveau方法
# 新建一个配置文件vim /etc/modprobe.d/blacklist-nouveau.conf#写入以下内容blacklist nouveauoptions nouveau modeset=0# 保存并退出:wq# 备份当前的镜像sudo mv /boot/initramfs-$(uname -r).img /boot/initramfs-$(uname -r).img.bak#建立新的镜像sudo dracut /boot/initramfs-$(uname -r).img $(uname -r)# 重启sudo reboot# 最后输入上面的命令验证lsmod | grep nouveau没有任何信息输出，则表示已经禁用nouveau |
安装 CUDA 10.1
# 下载安装包wget https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.243_418.87.00_linux.run# 修改权限chmod 755 cuda_10.1.243_418.87.00_linux.run# 执行安装./cuda_10.1.243_418.87.00_linux.run# 验证，查看驱动信息nvidia-smi |
安装 cuDNN 7.6.5
# 下载安装包wget https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.1_20191031/cudnn-10.1-linux-x64-v7.6.5.32.tgz# 解压tar zxvf cudnn-10.1-linux-x64-v7.6.5.32.tgz # 拷贝文件cp cuda/include/cudnn.h /usr/local/cuda/includecp cuda/lib64/libcudnn* /usr/local/cuda/lib64# 修改权限chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*# 添加环境变量vim ~/.bashrc# 添加内容如下export CUDA_HOME=/usr/local/cudaexport PATH=/usr/local/cuda/bin:$PATHexport LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATHexport CUDA_ROOT=/usr/local/cuda# 保存退出:wq# 使新的环境变量生效source ~/.bashrc# 验证，查看版本信息nvcc -V |
创建python3.7运行环境
安装miniconda
# 下载安装文件wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh# 修改权限chmod 755 Miniconda3-latest-Linux-x86_64.sh # 执行安装./Miniconda3-latest-Linux-x86_64.sh# 查看环境变量信息vim /root/.bashrc# 以下内容为安装minicoda时，自动写入的环境变量信息# >>> conda initialize >>># !! Contents within this block are managed by 'conda init' !!__conda_setup="$('/root/miniconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"if [ $? -eq 0 ]; theneval "$__conda_setup"elseif [ -f "/root/miniconda3/etc/profile.d/conda.sh" ]; then. "/root/miniconda3/etc/profile.d/conda.sh"elseexport PATH="/root/miniconda3/bin:$PATH"fifiunset __conda_setup# <<< conda initialize <<<# 使环境变量生效source /root/.bashrc# 配置国内源conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/freeconda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/mainconda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forgeconda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/biocondaconda config --set show_channel_urls yes# 验证，查看版本信息conda -V |
创建 tr-ocr python3.7运行环境
# 创建 python3.7 环境conda create --name tr-ocr python=3.7# 切换环境验证conda activate tr-ocr |
安装 TrWebOCR 环境依赖
# 切换环境conda activate tr-ocr# 安装 TrWebOCR 依赖包pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple# requirements内容如下libtorch==1.2.0.1numpy==1.14.6opencv-python==3.4.4.19Pillow==7.1.0tornado==6.0.4 |
安装 cudatoolkit
pip install cudatoolkit==10.1 -i https://pypi.tuna.tsinghua.edu.cn/simple |
使用GPU运行程序
启动TrWebOCR程序并验证
#下载代码https://github.com/alisen39/TrWebOCR#进入目录cd TrWebOCR-master/#启动程序python backend/main.py --open_gpu=1 --port=8089 |
启动Tr程序并验证
#下载代码https://github.com/myhub/tr#进入目录cd tr-master/#验证程序python test.py |
参考：