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实战小项目之ffmpeg推流yolo视频实时检测

     之前实现了yolo图像的在线检测,这次主要完成远程视频的检测。主要包括推流--収流--检测显示三大部分

  首先说一下推流,主要使用ffmpeg命令进行本地摄像头的推流,为了实现首屏秒开使用-g设置gop大小,同时使用-b降低网络负载,保证流畅度。

ffmpeg -r 30  -i /dev/video0 -vcodec h264 -max_delay 100 -f flv -g 5 -b 700000 rtmp://219.216.87.170/live/test1

 

  其次是収流,収流最开始的时候,有很大的延迟,大约5秒,后来通过优化,现在延时保证在1s以内,还是可以接收的,直接上収流的程序

AVFormatContext *pFormatCtx;    int i, videoindex;    AVCodecContext *pCodecCtx;    AVCodec *pCodec;    AVFrame *pFrame, *pFrameRGB;    uint8_t *out_buffer;    AVPacket *packet;    //int y_size;    int ret, got_picture;    struct SwsContext *img_convert_ctx;    //输入文件路径//    char filepath[] = "rtmp://219.216.87.170/vod/test.flv";    char filepath[] = "rtmp://219.216.87.170/live/test1";    int frame_cnt;    printf("wait for playing %s\n", filepath);    av_register_all();    avformat_network_init();    pFormatCtx = avformat_alloc_context();    printf("size %ld\tduration %ld\n", pFormatCtx->probesize,            pFormatCtx->max_analyze_duration);    pFormatCtx->probesize = 20000000;    pFormatCtx->max_analyze_duration = 2000;//    pFormatCtx->interrupt_callback.callback = timout_callback;//    pFormatCtx->interrupt_callback.opaque = pFormatCtx;//    pFormatCtx->flags |= AVFMT_FLAG_NONBLOCK;    AVDictionary* options = NULL;    av_dict_set(&options, "fflags", "nobuffer", 0);//    av_dict_set(&options, "max_delay", "100000", 0);//    av_dict_set(&options, "rtmp_transport", "tcp", 0);//    av_dict_set(&options, "stimeout", "6", 0);    printf("wating for opening file\n");    if (avformat_open_input(&pFormatCtx, filepath, NULL, &options) != 0) {        printf("Couldn‘t open input stream.\n");        return -1;    }    av_dict_free(&options);    printf("wating for finding stream\n");    if (avformat_find_stream_info(pFormatCtx, NULL) < 0) {        printf("Couldn‘t find stream information.\n");        return -1;    }    videoindex = -1;    for (i = 0; i < pFormatCtx->nb_streams; i++)        if (pFormatCtx->streams[i]->codec->codec_type == AVMEDIA_TYPE_VIDEO) {            videoindex = i;            break;        }    if (videoindex == -1) {        printf("Didn‘t find a video stream.\n");        return -1;        }    pCodecCtx = pFormatCtx->streams[videoindex]->codec;    pCodec = avcodec_find_decoder(pCodecCtx->codec_id);    if (pCodec == NULL) {        printf("Codec not found.\n");        return -1;        }    if (avcodec_open2(pCodecCtx, pCodec, NULL) < 0) {        printf("Could not open codec.\n");        return -1;        }    /*     * 在此处添加输出视频信息的代码     * 取自于pFormatCtx,使用fprintf()     */    pFrame = av_frame_alloc();    pFrameRGB = av_frame_alloc();    out_buffer = (uint8_t *) av_malloc(            avpicture_get_size(AV_PIX_FMT_BGR24, pCodecCtx->width,                    pCodecCtx->height));    avpicture_fill((AVPicture *) pFrameRGB, out_buffer, AV_PIX_FMT_BGR24,            pCodecCtx->width, pCodecCtx->height);    packet = (AVPacket *) av_malloc(sizeof(AVPacket));    //Output Info-----------------------------    printf("--------------- File Information ----------------\n");    av_dump_format(pFormatCtx, 0, filepath, 0);    printf("-------------------------------------------------\n");    img_convert_ctx = sws_getContext(pCodecCtx->width, pCodecCtx->height,            pCodecCtx->pix_fmt, pCodecCtx->width, pCodecCtx->height,            AV_PIX_FMT_BGR24, SWS_BICUBIC, NULL, NULL, NULL);    CvSize imagesize;    imagesize.width = pCodecCtx->width;    imagesize.height = pCodecCtx->height;    IplImage *image = cvCreateImageHeader(imagesize, IPL_DEPTH_8U, 3);    cvSetData(image, out_buffer, imagesize.width * 3);    cvNamedWindow(filepath, CV_WINDOW_AUTOSIZE);    frame_cnt = 0;    int num = 0;    while (av_read_frame(pFormatCtx, packet) >= 0) {        if (packet->stream_index == videoindex) {            /*             * 在此处添加输出H264码流的代码             * 取自于packet,使用fwrite()             */            ret = avcodec_decode_video2(pCodecCtx, pFrame, &got_picture,                    packet);            if (ret < 0) {                printf("Decode Error.\n");                return -1;            }            if (got_picture) {                sws_scale(img_convert_ctx,                        (const uint8_t* const *) pFrame->data, pFrame->linesize,                        0, pCodecCtx->height, pFrameRGB->data,                        pFrameRGB->linesize);                printf("Decoded frame index: %d\n", frame_cnt);                /*                 * 在此处添加输出YUV的代码                 * 取自于pFrameYUV,使用fwrite()                 */                frame_cnt++;                cvShowImage(filepath, image);                cvWaitKey(30);            }        }        av_free_packet(packet);        }    sws_freeContext(img_convert_ctx);    av_frame_free(&pFrameRGB);    av_frame_free(&pFrame);    avcodec_close(pCodecCtx);    avformat_close_input(&pFormatCtx);    return 0;

  将解压后的数据区与opencv的IplImage的数据区映射,实现opencv显示。

  

  检测部分,主要使用IplImage与yolo中的图像进行对接,在图像转换方面,进行了部分优化,缩减一些不必要的步骤。然后使用线程区接收ffmepg流,主循环里区做检测并显示。需要做线程同步处理,只有当收到新流时,才去检测。

实战小项目之ffmpeg推流yolo视频实时检测