Ubuntu18.04——源码编译CUDA版本OpenCV-4.1.1

文章目录

• ​​1.拉取源码 / 下载压缩包​​
• ​​2.Cmake​​

• ​​报错解决：`CUDA_nppicom_LIBRARY` \ `CUDA_CUDA_LIBRARY` (ADVANCED) 未定义​​

• ​​解决方法​​

• ​​3.Make​​
• ​​4. 测试程序​​
• ​​`CMakeLists.txt`模板​​

• ​​OpenCV程序​​
• ​​ROS-OpenCV程序​​

• ​​其他报错汇总​​

• ​​报错解决：Unsupported gpu architecture 'compute_30'​​

• ​​解决方法​​

• ​​报错解决：对‘TIFFReadRGBAStrip@LIBTIFF_4.0’未定义的引​​

• ​​解决方法​​

前提条件：可以自由S网。

参考文章：

• ​​ubuntu1804编译opencv4.4 +cuda​​

1.拉取源码 / 下载压缩包

• 源码方式：

git clone https://github.com/opencv/opencv.git
cd opencv && git checkout 4.1.1
git clone https://github.com/opencv/opencv_contrib.git
cd opencv_contrib && git checkout 4.1.1
cd ..

• 压缩包方式：

链接：https://pan.baidu.com/s/1teLFkpuhb7yjiTtbRfTQ3A 
提取码：elkg

2.Cmake

mkdir build && cd build

cmake -DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=/usr/local \
-DOPENCV_GENERATE_PKGCONFIG=ON \
-DOPENCV_EXTRA_MODULES_PATH=~/opencv/opencv_contrib/modules \
-DBUILD_EXAMPLES=ON \
-DWITH_GSTREAMER=ON \
-DVIDEOIO_PLUGIN_LIST=gstreamer \
-DBUILD_opencv_python2=OFF \
-DBUILD_opencv_python3=OFF \
-DWITH_EIGEN=ON \
-DWITH_OPENGL=ON \
-DCUDA_nppicom_LIBRARY=stdc++ \
-DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs \
-DCUDA_GENERATION=Auto \
-DWITH_CUDA=ON \
-DWITH_CUBLAS=ON \
-DWITH_CUDNN=ON .. 
# 参数解析
# 如果要使用CUDA，务必加入该参数
# -DCUDA_nppicom_LIBRARY=stdc++ \
# 需要根据自己的GPU架构进行修改
# -D CUDA_GENERATION="Ampere" \

报错解决：​​CUDA_nppicom_LIBRARY​​​ \ ​​CUDA_CUDA_LIBRARY​​ (ADVANCED) 未定义

解决方法

• ​​Opencv-GPU 编译错误 CUDA_nppicom_LIBRARY (ADVANCED)​​

在编译参数中加入：

-DCUDA_nppicom_LIBRARY=stdc++ \

• ​​编译opencv时遇到问题：CUDA_CUDA_LIBRARY (ADVANCED)​​

-DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs

3.Make

make -j12
sudo make install

cd /etc/ld.so.conf.d/
sudo touch opencv4.conf
sudo sh -c 'echo "/usr/local/lib" > opencv4.conf

sudo ldconfig

sudo gedit /etc/bash.bashrc
PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
export PKG_CONFIG_PATH
source /etc/bash.bashrc

• 使用下面的命令可以查看opencv的版本：

opencv_version

• 需要注意的是：OpenCV4在安装好后，所有的头文件一般都会生成在​​/usr/local/include/opencv4​​​路径下，而不是系统默认的头文件目录​​/usr/include/​​，因此需要进行软链接：

sudo ln -s /usr/local/include/opencv4 /usr/include/

软连接后即可在程序中直接使用等头文件：

#include <opencv2/opencv.hpp>

4. 测试程序

• 参考：​​ubuntu 系统 OpenCV 4 安装教程​​

​​CMakeLists.txt​​模板

OpenCV程序

cmake_minimum_required(VERSION 3.0.2)
project(XXXX)

# 0.set opencv dir(where you build)
set(OpenCV_DIR /home/innox/opencv/build)

# 1.find package
# OpenCV 
find_package(OpenCV REQUIRED)

# 2.include directories
include_directories(
  include
  
  ${OpenCV_INCLUDE_DIRS}
)

# 3.link opencv lib
add_executable(image_sub  src/image_sub.cpp)
target_link_libraries(image_sub  ${OpenCV_LIBS})

ROS-OpenCV程序

cmake_minimum_required(VERSION 3.0.2)
project(XXXX)

# 0.set opencv dir(where you build)
set(OpenCV_DIR /home/innox/opencv/build)

# 1.find package
# Catkin 
find_package(catkin REQUIRED COMPONENTS
  roscpp
  rosmsg
  rospy
  message_filters # message_filters
  cv_bridge # ros cv_bridge
  OpenCV # ros cv
  image_transport # ros cv
)
# Boost 
find_package(Boost REQUIRED)
# OpenCV 
find_package(OpenCV REQUIRED)

# 2.catkin package
catkin_package()

# 3.include directories
include_directories(
  include

  ${catkin_INCLUDE_DIRS}
  ${Boost_INCLUDE_DIRS}
  ${OpenCV_INCLUDE_DIRS}
)

# 4.link opencv lib
add_executable(image_sub  src/image_sub.cpp)
target_link_libraries(image_sub  ${OpenCV_LIBS})

其他报错汇总

报错解决：Unsupported gpu architecture ‘compute_30’

解决方法

• 参考文章：​​Unsupported gpu architecture 'compute_11’解决方法​​

在编译选项中加入：

-DCUDA_GENERATION=Auto \

报错解决：对‘TIFFReadRGBAStrip@LIBTIFF_4.0’未定义的引

解决方法

• 参考文章：​​对‘TIFFReadRGBAStrip@LIBTIFF_4.0’未定义的引​​ 在编译选项中加入：

-DBUILD_TIFF=ON \