ESDK中的ai识别推流后卡顿

我们用esdk进行ai识别然后再sample_liveview_main.cc中添加了推流功能来进行测试 显示推流还行但是播放就很卡 想问一下是为什么   以及我把推送mqtt也放在这个文件中 发送mqtt时ai会卡顿 是否应该单独写出     以下是代码          

#include <iostream>

#include <vector>

#include <unistd.h>

#include <cstdio>

#include <cstring>

#include <opencv2/opencv.hpp>  // 确保包含 OpenCV 头文件




#include "error_code.h"

#include "image_processor.h"

#include "logger.h"

#include "sample_liveview.h"

#include "cloud_api.h"

#include <unordered_set>

#include "image_processor_yolovfastest.h"




using namespace edge_sdk;

using namespace edge_app;




ErrorCode ESDKInit();




// Global pipe for FFmpeg

FILE* ffmpeg_pipe = nullptr;




// Function to initialize FFmpeg

void initFFmpeg() {

    if (ffmpeg_pipe) return; // FFmpeg process already started




    // 修改 FFmpeg 命令以匹配新的分辨率、帧率和其他参数

    std::string command = "ffmpeg -loglevel debug -f rawvideo -pix_fmt bgr24 -s 1440x1080 -framerate 15 -i - "

                          "-b:v 2000k -bufsize 3000k -c:v libx264 -preset fast -tune zerolatency -pix_fmt yuv420p "

                          "-f flv rtmp://39.104.204.208:1935/live/stream";

    ffmpeg_pipe = popen(command.c_str(), "w");

    if (!ffmpeg_pipe) {

        ERROR("Failed to open pipe to FFmpeg");

    }

}




// Function to close FFmpeg

void closeFFmpeg() {

    if (ffmpeg_pipe) {

        pclose(ffmpeg_pipe);

        ffmpeg_pipe = nullptr;

    }

}




// Function to send detection results to cloud

void SendDetectionResultToCloud(const std::unordered_set<std::string>& detections) {

    std::string combined_result;

    for (const auto& detection : detections) {

        if (!combined_result.empty()) {

            combined_result += ", ";  // 添加分隔符

        }

        combined_result += detection;

    }




    // 确保结果字符串是 UTF-8 编码

    INFO("send message to cloud: %s", combined_result.c_str());

    CloudAPI_SendCustomEventsMessage(reinterpret_cast<const uint8_t*>(combined_result.c_str()), combined_result.size());

}










// Function to process image and send it to FFmpeg

void processImage(const std::shared_ptr<cv::Mat>& image) {

    if (image) {

        size_t img_size = image->total() * image->elemSize();

        if (ffmpeg_pipe) {

            size_t written = fwrite(image->data, 1, img_size, ffmpeg_pipe);

            if (written != img_size) {

                ERROR("Failed to write full frame to FFmpeg");

            }

            fflush(ffmpeg_pipe); // Ensure data is flushed to FFmpeg

        } else {

            ERROR("FFmpeg pipe is not open");

        }

    } else {

        ERROR("Image is null");

    }

}




int main(int argc, char** argv) {

    auto rc = ESDKInit();

    if (rc != kOk) {

        ERROR("pre init failed");

        return -1;

    }




    // Initialize FFmpeg process

    initFFmpeg();




    // 创建 payload liveview

    auto payload_liveview = std::make_shared<LiveviewSample>("Payload");




    StreamDecoder::Options decoder_option = {.name = std::string("ffmpeg")};

    // 创建 payload 解码器

    auto payload_decoder = CreateStreamDecoder(decoder_option);




    // 创建 payload 图像处理器并添加回调函数

    ImageProcessor::Options image_processor_option = {

        .name = std::string("yolovfastest"),

        .alias = std::string("PlayloadCamera: Yolovfastest"),

        .callback = [](const std::shared_ptr<cv::Mat>& image) {

            processImage(image);

        }

    };

    auto payload_image_processor = CreateImageProcessor(image_processor_option);




    if (0 != InitLiveviewSample(

        payload_liveview, Liveview::kCameraTypePayload, Liveview::kStreamQuality1080pHigh,

        payload_decoder, payload_image_processor)) {

        ERROR("Init payload liveview sample failed");

    } else {

        // 启动 payload liveview

        payload_liveview->Start();

    }




    // 创建 fpv liveview

    auto fpv_liveview = std::make_shared<LiveviewSample>("Fpv");




    // 创建 fpv 解码器

    auto fpv_decoder = CreateStreamDecoder(decoder_option);




    // 创建 fpv 图像处理器

    ImageProcessor::Options fpv_image_processor_option = {

        .name = std::string("display"),

        .alias = std::string("FPVCamera"),

        .userdata = fpv_liveview

    };

    auto fpv_image_processor = CreateImageProcessor(fpv_image_processor_option);




    if (0 != InitLiveviewSample(

        fpv_liveview, Liveview::kCameraTypeFpv, Liveview::kStreamQuality720p,

        fpv_decoder, fpv_image_processor)) {

        ERROR("Init fpv liveview sample failed");

    } else {

        // 启动 fpv liveview

        fpv_liveview->Start();

    }




    // 运行主循环

    while (true) {

    sleep(3);




    // 使用互斥锁保护 detected_objects

    {

        std::lock_guard<std::mutex> lock(detected_objects_mutex);




        // 处理检测到的物品并发送到云端

        if (detected_objects.empty()) {

            SendDetectionResultToCloud({"null"});

        } else {

            SendDetectionResultToCloud(detected_objects);

        }







        // 清空 detected_objects 以准备处理下一帧

        detected_objects.clear();

}

}







    // 退出时关闭 FFmpeg 进程

    closeFFmpeg();




    return 0;

}