运行神经网络框架Darknet报了“Failed to initialize NVML: Driver/library version mismatch”的ERROR,笔者一开始采用了如下两篇博客中的操作Ubuntu中Failed to initialize NVML: Driver/library version mismatch问题的解决、出现“no CUDA-
编译过程会出现gcc版本错误,显示版本太高了(5.4),打开/usr/local/cuda/include/host_config.h 注释掉: error -- unsupported GNU version! gcc versions later than 5.3 are not supported! 在cuda和opencv编译的时候也会报gcc版本太高的错误(主要是cuda引起的,如果opencv不用cuda就没这个错误): 解决: 安装gcc-...
包含目录: D:\library\opencv\build\include;D:\library\opencv\build\include\opencv;D:\library\opencv\build\include\opencv2;$(CUDA_PATH)\include;$(IncludePath) 库目录: D:\library\opencv\build\x64\vc14\lib;$(CUDA_PATH)\lib\x64;$(LibraryPath) 链接器: 附加库目录: D:\library\opencv\build\...
libswscale-dev(7:2.8.11-0ubuntu0.16.04.1) cuda install wget cuda8网址 sudo sh xxxxrun 安装库(注意:已安装nvidia驱动了不要再选择安装Nvidia Graphic Driver那项,其他都可以yes或默认)。 ffmpeg 安装 安装其他依赖库 官方必须包:sudo apt-get install build-essential cmake git libgtk2.0-dev pkg-config ...
OpenCV 安装 检查CUDA版本:首先,需要根据Google Colab上安装的CUDA版本进行编译。可以通过运行以下命令来检查 !nvcc --version 2. 安装依赖项: !sudo apt update !sudo apt install -y build-essential cmake unzip pkg-config !sudo apt install -y libjpeg-dev libpng-dev libtiff-dev ...
pip install opencv-python 可参考:OpenCV with CUDA for Jetson Nano | NVIDIA Developer# 检查你的总内存(RAM + swap),以便快速构建。至少需要: # OpenCV 4.8.0 -> 8.5 GB! # OpenCV 4.7.0 -> 8.5 GB! # OpenCV 4.6.0 -> 8.5 GB! # OpenCV 4.5.5 -> 8.5 GB! # OpenCV 4.5.4 -> 8.5 GB...
pip install opencv-python 可参考:OpenCV with CUDA for Jetson Nano | NVIDIA Developer# 检查你的总内存(RAM + swap),以便快速构建。至少需要: # OpenCV 4.8.0 -> 8.5 GB! # OpenCV 4.7.0 -> 8.5 GB! # OpenCV 4.6.0 -> 8.5 GB! # OpenCV 4.5.5 -> 8.5 GB! # OpenCV 4.5.4 -> 8.5 GB...
安装到默认环境(base)不需要执行此步骤,该步骤步骤的目的是安装cuda版本opencv到用户自定义的虚拟环境中,分别将路径指向自定义虚拟环境的对应位置 : PYTHON3_EXECUTABLE、PYTHON3_INCLUDE_DIR、PYTHON3_LIBRARY、PYTHON3_NUMPY_INCLUDE_DIRS(需要安装numpy)、PYTHON3_PACKAGES_PATH。
1、首先移除nx中已经默认的opencv。 sudo apt-getpurge libopencv*sudo apt autoremove sudo apt-getupdate 2、检查已安装组件 https://blog.csdn.net/beckhans/article/details/89138876 有一步是10.2 export CUDA_HOME=/usr/local/cuda-10.2 export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_...
这是由于opecv3.1与cuda8.0不兼容导致的。解决办法: 修改/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp 文件内容,如图: image.png 在graphcuts.cpp中将 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) 改为 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER) || (CUDART_VERSION >= ...