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SLAM算法与工程实践——相机篇：传统相机使用（1）

SLAM算法与工程实践系列文章

下面是SLAM算法与工程实践系列文章的总链接，本人发表这个系列的文章链接均收录于此

SLAM算法与工程实践系列文章链接

下面是专栏地址：

SLAM算法与工程实践系列专栏

文章目录

前言

这个系列的文章是分享SLAM相关技术算法的学习和工程实践

SLAM算法与工程实践——相机篇：传统相机使用（1）

相机相关命令

插上USB相机，使用命令查看USB设备

lsusb

在这里插入图片描述

可以识别相机

使用命令查看识别到几个摄像头

ll /dev/video*

在这里插入图片描述

然后改变其权限

sudochmod777 /dev/video0
sudochmod777 /dev/video1

安装 

v4l-utils

工具包

sudoapt-getinstall v4l-utils

使用下列命令查看相机参数

v4l2-ctl -d /dev/video0 --list-formats-ext

在命令行输出为：

ioctl: VIDIOC_ENUM_FMT
        Type: Video Capture

        [0]: 'MJPG'(Motion-JPEG, compressed)
                Size: Discrete 2560x800
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                        Interval: Discrete 0.067s (15.000 fps)
                Size: Discrete 2560x720
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                Size: Discrete 1280x800
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                Size: Discrete 1280x792
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                Size: Discrete 1280x400
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)
                        Interval: Discrete 0.033s (30.000 fps)
                Size: Discrete 640x400
                        Interval: Discrete 0.005s (210.000 fps)
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)
                Size: Discrete 640x392
                        Interval: Discrete 0.005s (210.000 fps)
                        Interval: Discrete 0.008s (120.000 fps)
                        Interval: Discrete 0.017s (60.000 fps)[1]: 'YUYV'(YUYV 4:2:2)
                Size: Discrete 2560x800
                        Interval: Discrete 0.500s (2.000 fps)
                Size: Discrete 2560x720
                        Interval: Discrete 0.500s (2.000 fps)
                Size: Discrete 1280x800
                        Interval: Discrete 0.200s (5.000 fps)
                Size: Discrete 1280x792
                        Interval: Discrete 0.200s (5.000 fps)
                Size: Discrete 1280x400
                        Interval: Discrete 0.067s (15.000 fps)
                        Interval: Discrete 0.100s (10.000 fps)
                Size: Discrete 640x400
                        Interval: Discrete 0.033s (30.000 fps)
                Size: Discrete 640x392
                        Interval: Discrete 0.033s (30.000 fps)

可以看出本相机的参数和对应设置下的帧率，最高为 120 帧，分辨率为 2560x800，我这选用 1280x400

在这里插入图片描述

接下来看看你的USB摄像头支持什么附加属性，只需要执行下面的命令即可

v4l2-ctl -d /dev/video0 --list-ctrls

得到下面的结果

User Controls

                     brightness 0x00980900 (int):min=-64 max=64step=1default=0value=0
                       contrast 0x00980901 (int):min=0max=95step=1default=0value=0
                     saturation 0x00980902 (int):min=0max=100step=1default=64value=64
                            hue 0x00980903 (int):min=-2000 max=2000step=1default=0value=0
        white_balance_automatic 0x0098090c (bool):default=1value=1
                          gamma 0x00980910 (int):min=100max=300step=1default=100value=100

在这里插入图片描述

使用应用程序茄子（cheese）

输入命令：

sudoapt-getinstall cheese

装好后，用命令：

cheese

，即可打开。如果指定打开video1，输入命令：

cheese -d /dev/video1

读取相机配置文件 

HBV-1780-2.yaml

int UseStereoCam::loadCamParam(std::string cfgPath) {
    cv::FileStorage fs(cfgPath, cv::FileStorage::READ);
    if (fs.isOpened()) {
        std::cout << "Stereo Camera Paramter is loading..." << std::endl;

        //内参矩阵
        fs["IntrinsicMatrixLeft"] >> IntrinsicMatrixLeft;      //存放内参矩阵,左相机
        IntrinsicMatrixLeft.at<double>(0, 0) = IntrinsicMatrixLeft.at<double>(0, 0) * resizeScalse;
        IntrinsicMatrixLeft.at<double>(1, 1) = IntrinsicMatrixLeft.at<double>(1, 1) * resizeScalse;
        IntrinsicMatrixLeft.at<double>(0, 2) = IntrinsicMatrixLeft.at<double>(0, 2) * resizeScalse;
        IntrinsicMatrixLeft.at<double>(1, 2) = IntrinsicMatrixLeft.at<double>(1, 2) * resizeScalse;

        fs["IntrinsicMatrixRight"] >> IntrinsicMatrixRight;      //存放内参矩阵,右相机
        IntrinsicMatrixRight.at<double>(0, 0) = IntrinsicMatrixRight.at<double>(0, 0) * resizeScalse;
        IntrinsicMatrixRight.at<double>(1, 1) = IntrinsicMatrixRight.at<double>(1, 1) * resizeScalse;
        IntrinsicMatrixRight.at<double>(0, 2) = IntrinsicMatrixRight.at<double>(0, 2) * resizeScalse;
        IntrinsicMatrixRight.at<double>(1, 2) = IntrinsicMatrixRight.at<double>(1, 2) * resizeScalse;

        //畸变系数
        fs["DistCoeffLeft"] >> DistCoeffLeft;            //畸变矩阵，左相机
        fs["DistCoeffRight"] >> DistCoeffRight;             //畸变矩阵，右相机

        //旋转矩阵 平移向量
        fs["RotationMatrix"] >> R;
        fs["TranslationVector"] >> T;
        T = T * resizeScalse;

        fs.release();

        leftFocalLength =
                (IntrinsicMatrixLeft.at<double>(0, 0) + IntrinsicMatrixLeft.at<double>(1, 1)) / 2.0;
        rightFocalLength =
                (IntrinsicMatrixRight.at<double>(0, 0) + IntrinsicMatrixRight.at<double>(1, 1)) / 2.0;
        // 处理焦距（例如取平均值）
        focalLength = (leftFocalLength + rightFocalLength) / 2.0;

        fx = (IntrinsicMatrixLeft.at<double>(0, 0) + IntrinsicMatrixRight.at<double>(0, 0)) / 2.0;
        fy = (IntrinsicMatrixLeft.at<double>(1, 1) + IntrinsicMatrixRight.at<double>(1, 1)) / 2.0;
        cx = (IntrinsicMatrixLeft.at<double>(0, 2) + IntrinsicMatrixRight.at<double>(0, 2)) / 2.0;
        cy = (IntrinsicMatrixLeft.at<double>(1, 2) + IntrinsicMatrixRight.at<double>(1, 2)) / 2.0;

        baseline = cv::norm(T) / 100;     //基线（baseline）单位设置为分米

        std::cout << "camera parameter loaded successfully!" << std::endl;

        return 0;

    } else {
        std::cout << "Failed to load camera parameter!" << std::endl;
        return -1;
    }

}

出现的问题

参考：

解决OpenCV的GStreamer warning警告

在用opencv调用摄像头时报错

在这里插入图片描述

[ WARN:0] global ../modules/videoio/src/cap_gstreamer.cpp (935)open OpenCV | GStreamer warning: Cannot query video position: status=0, value=-1, duration=-1
[ WARN:0] global ../modules/videoio/src/cap_gstreamer.cpp (1758) handleMessage OpenCV | GStreamer warning: Embedded video playback halted; module v4l2src0 reported: Device '/dev/video0' failed during initialization
[ WARN:0] global ../modules/videoio/src/cap_gstreamer.cpp (515) startPipeline OpenCV | GStreamer warning: unable to start pipeline
[ WARN:0] global ../modules/videoio/src/cap_gstreamer.cpp (1057) setProperty OpenCV | GStreamer warning: no pipeline
[ WARN:0] global ../modules/videoio/src/cap_gstreamer.cpp (480) isPipelinePlaying OpenCV | GStreamer warning: GStreamer: pipeline have not been created
摄像头打开失败!

解决办法：

修改打开摄像头的代码如下：

cap.open(0,CAP_V4L2);

调用相机

在编写多个主函数共用

src

和

include

定义的类的文件时，CMakeLists.txt的编写应该类似下面的写法，然后包含每个子项目的子文件夹

cmake_minimum_required(VERSION 2.8)
project(DEPTH_COMPUTE)

IF (NOT CMAKE_BUILD_TYPE)
    SET(CMAKE_BUILD_TYPE Release)
ENDIF ()

MESSAGE("Build type: " ${CMAKE_BUILD_TYPE})

# set path
set(LIB_PATH ${PROJECT_SOURCE_DIR}/lib)
set(HEAD_PATH ${PROJECT_SOURCE_DIR}/include)
set(EXEC_PATH ${PROJECT_SOURCE_DIR}/bin)

set(DEPTH_LIB calc_depth)   # set libiary name

find_package(OpenCV 4 REQUIRED)
find_package(Eigen3 3.1.0 NO_MODULE)
find_package(Pangolin REQUIRED)

include_directories(${HEAD_PATH})
aux_source_directory(${PROJECT_SOURCE_DIR}/src LIB_SRC)

SET(LIBRARY_OUTPUT_PATH ${LIB_PATH})
add_library(${DEPTH_LIB} SHARED ${LIB_SRC})
TARGET_LINK_LIBRARIES(${DEPTH_LIB}
        ${OpenCV_LIBS}
        ${EIGEN3_LIBS}
        ${Pangolin_LIBRARIES}
)

# add subdirectories 这里是具体的主函数
add_subdirectory(useCamForShot) 
add_subdirectory(openCamera)

子项目的CMakeLists.txt应该如下

cmake_minimum_required(VERSION 2.8)
project(OPENCAM)

find_package(OpenCV 4 REQUIRED)

include_directories(${HEAD_PATH})
link_directories(${LIB_PATH})

set(CMAKE_BUILD_TYPE "Release")
set(CMAKE_CXX_FLAGS "-O3")
set(EXECUTABLE_OUTPUT_PATH  ${EXEC_PATH})

#add_library(${DEPTH_LIB} SHARED  ${SRC_LIST})

add_executable(open_camera open_camera.cpp)
target_link_libraries(open_camera ${DEPTH_LIB} ${OpenCV_LIBS})

以MJPG格式打开相机

参考：

OpenCV+V4L实现MJPG格式拉取USB摄像头

关于openCV VideoCapture获取摄像头MJPG视频的问题

相机支持的视频流格式

在这里插入图片描述

在这里插入图片描述

在打开相机后，设置参数

capture.open(camIndex, cv::CAP_V4L);    // open camera

//设置编码格式，这里只能写在分辨率和帧率后面，否则无效
capture.set(cv::CAP_PROP_FOURCC, cv::VideoWriter::fourcc('M', 'J', 'P', 'G'));//视频流格式
标签： 算法 计算机视觉 机器人
本文转载自: https://blog.csdn.net/qq_37648371/article/details/134984819
版权归原作者 yangtsejin 所有， 如有侵权，请联系我们删除。
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