当前位置: 首页 > article >正文

奥比中光opencv显示可见光图片

在奥比中光提供的sdk中没有直接使用opencv读取显示视频流的功能,参照案例与代码写了一个opencv显示奥比中光可见光流的cpp代码

代码:


#include "libobsensor/hpp/Pipeline.hpp"
#include "libobsensor/hpp/Error.hpp"

const char *metaDataTypes[] = { "TIMESTAMP",
                                "SENSOR_TIMESTAMP",
                                "FRAME_NUMBER",
                                "AUTO_EXPOSURE",
                                "EXPOSURE",
                                "GAIN",
                                "AUTO_WHITE_BALANCE",
                                "WHITE_BALANCE",
                                "BRIGHTNESS",
                                "CONTRAST",
                                "SATURATION",
                                "SHARPNESS",
                                "BACKLIGHT_COMPENSATION",
                                "HUE",
                                "GAMMA",
                                "POWER_LINE_FREQUENCY",
                                "LOW_LIGHT_COMPENSATION",
                                "MANUAL_WHITE_BALANCE",
                                "ACTUAL_FRAME_RATE",
                                "FRAME_RATE",
                                "AE_ROI_LEFT",
                                "AE_ROI_TOP",
                                "AE_ROI_RIGHT",
                                "AE_ROI_BOTTOM",
                                "EXPOSURE_PRIORITY",
                                "HDR_SEQUENCE_NAME",
                                "HDR_SEQUENCE_SIZE",
                                "HDR_SEQUENCE_INDEX",
                                "LASER_POWER",
                                "LASER_POWER_LEVEL",
                                "LASER_STATUS",
                                "GPIO_INPUT_DATA" };

int main(int argc, char **argv) try {
    // Create a pipeline with default device
    ob::Pipeline pipe;

    // Configure which streams to enable or disable for the Pipeline by creating a Config
    std::shared_ptr<ob::Config> config = std::make_shared<ob::Config>();
    config->enableVideoStream(OB_STREAM_COLOR);

    // Start the pipeline with config
    pipe.start(config);
    auto currentProfile = pipe.getEnabledStreamProfileList()->getProfile(0)->as<ob::VideoStreamProfile>();
    cv::Mat                                 rstMat;
    // Create a window for rendering, and set the resolution of the window

    while(1) {
        // Wait for up to 100ms for a frameset in blocking mode.
        auto frameSet = pipe.waitForFrames(1000);
        if(frameSet == nullptr) {
            continue;
        }

        // get color frame from frameset
        auto colorFrame = frameSet->colorFrame();
        if(colorFrame == nullptr) {
            continue;
        }

        if(colorFrame->type() == OB_FRAME_COLOR) {
            auto videoFrame = colorFrame->as<ob::VideoFrame>();
            switch(videoFrame->format()) {
            case OB_FORMAT_MJPG: {
                cv::Mat rawMat(1, videoFrame->dataSize(), CV_8UC1, videoFrame->data());
                rstMat = cv::imdecode(rawMat, 1);
            } break;
            case OB_FORMAT_NV21: {
                cv::Mat rawMat(videoFrame->height() * 3 / 2, videoFrame->width(), CV_8UC1, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_YUV2BGR_NV21);
            } break;
            case OB_FORMAT_YUYV:
            case OB_FORMAT_YUY2: {
                cv::Mat rawMat(videoFrame->height(), videoFrame->width(), CV_8UC2, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_YUV2BGR_YUY2);
            } break;
            case OB_FORMAT_RGB: {
                cv::Mat rawMat(videoFrame->height(), videoFrame->width(), CV_8UC3, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_RGB2BGR);
            } break;
            case OB_FORMAT_RGBA: {
                cv::Mat rawMat(videoFrame->height(), videoFrame->width(), CV_8UC4, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_RGBA2BGRA);
            } break;
            case OB_FORMAT_BGRA: {
                rstMat = cv::Mat(videoFrame->height(), videoFrame->width(), CV_8UC4, videoFrame->data());
            } break;
            case OB_FORMAT_UYVY: {
                cv::Mat rawMat(videoFrame->height(), videoFrame->width(), CV_8UC2, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_YUV2BGR_UYVY);
            } break;
            case OB_FORMAT_I420: {
                cv::Mat rawMat(videoFrame->height() * 3 / 2, videoFrame->width(), CV_8UC1, videoFrame->data());
                cv::cvtColor(rawMat, rstMat, cv::COLOR_YUV2BGR_I420);
            } break;
            default:
                break;
                }

        }

        cv::imshow("ccc",rstMat);
        cv::waitKey(100);



        // Render frameset in the window, only color frames are rendered here.

    }

    // Stop the Pipeline, no frame data will be generated
    pipe.stop();

    return 0;
}
catch(ob::Error &e) {
    std::cerr << "function:" << e.getName() << "\nargs:" << e.getArgs() << "\nmessage:" << e.getMessage() << "\ntype:" << e.getExceptionType() << std::endl;
    exit(EXIT_FAILURE);
}


http://www.kler.cn/news/355462.html

相关文章:

  • [论文笔记] llama-factory 微调qwen2.5、llama3踩坑
  • php strtr 函数的坑
  • Android二代抽取壳简易实现和踩坑记录
  • <Linux> 线程池
  • vue项目中使用websocket
  • MAC地址漂移实验
  • 【ShuQiHere】智慧城市(Smart City)全面指南:AI如何重塑城市生活 ️
  • [图形学]蒙特卡洛积分方法介绍及其方差计算
  • AcWing 3817:数组 ← 贪心算法
  • JavaWeb 23.NPM配置和使用
  • HTML5教程(四) - 结构标签
  • git+cmake将Open3D配置到visual studio
  • Android中 tools:text 和 android:text区别
  • Java JDK的面试题
  • Redis基础篇(含redis在linux环境下的安装教程,以及用docker安装redis的教程)
  • 【Linux驱动开发】嵌入式Linux驱动开发基本步骤,字符设备开发入门,点亮LED
  • Python知识梳理总结思维导图
  • SpringBoot实现的物流优化策略
  • 笔记整理—linux网络部分(2)Linux网络框架
  • 如何成为 Rust 核心贡献者?Rust 开发的核​​心是什么?Rust 重要技术专家揭秘