使用ffmepg实现多路视频流合并

2024-08-29 05:58

本文主要是介绍使用ffmepg实现多路视频流合并,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

做视频会议系统的时候,有时需要实现多路视频画面合并后推流功能,要直接底层实现这样的功能还是不太容易的,如果借助ffmpeg就方便多了,使用ffmpeg的滤镜功能就能实现多路合并的效果。

首先说明需要用到的ffmpeg对象,以及一些必要的字段。

ffmpeg版本:

version 4.3

所用到的头文件:

#include <libavutil/avassert.h>
#include <libavutil/opt.h>
#include <libavfilter/avfilter.h>

需要的数据结构如下:

每一条输入流需要如下的字段

typedef struct Stream{int x;int y;int width;int height;int format;//参考AVPixelFormatAVFilterContext* buffersrc_ctx;AVFilter* buffersrc;AVFilterInOut* output;AVFrame* inputFrame;
} Stream;

输出流需要如下字段

typedef struct Merge {AVFilterGraph* filter_graph;AVFilterContext* buffersink_ctx;AVFilter* buffersink;AVFilterInOut* input;const char* filters_descr;AVFrame* outputFrame;unsigned char* outputBuffer;int outputWidth;int outputHeight;int outputFormat;//参考AVPixelFormatStream *streams[128];int streamCount;
} Merge;

主要流程如下:

1、构造输出流及输入流

构造输出流,输出流需要设置分辨率以及输出的像素格式

Merge* Merge_Create(int outputWidth, int outputHeight, int outputFormat) {Merge* merge = malloc(sizeof(Merge));memset(merge, 0, sizeof(Merge));merge->outputWidth = outputWidth;merge->outputHeight = outputHeight;merge->outputFormat = outputFormat;return merge;
}

添加输入流,输入流需要设置在输出流中的位置和大小,以及输入流像素格式 

Stream* Merge_AddStream(Merge* merge, int x, int y, int width, int height, int format) {Stream* stream = malloc(sizeof(Stream));memset(merge, 0, sizeof(Stream));stream->x = x;stream->y = y;stream->width = width;stream->height = height;stream->format = format;merge->streams[merge->streamCount++] = stream;return stream;
}

2、初始化滤镜

主要用到的滤镜是filters_descr = "[in0]pad=1280:640:0:0:black[x0];[x0][in1]overlay=640:0[x1];[x1][in2]overlay=600:0[x2];[x2]null[out]";

//初始化Merge
int Merge_Init(Merge* merge) {char args[512];char name[8];char* filters_descr = NULL;int ret;//avfilter_register_all();//旧版可能用到此行merge->buffersink = avfilter_get_by_name("buffersink");av_assert0(merge->buffersink);merge->input = avfilter_inout_alloc();if (merge->input == NULL){printf("alloc inout  fail\n");goto fail;}merge->filter_graph = avfilter_graph_alloc();if (merge->input == NULL){printf("alloc graph  fail\n");goto fail;}ret = avfilter_graph_create_filter(&merge->buffersink_ctx, merge->buffersink, "out", NULL, NULL, merge->filter_graph);if (ret < 0){printf("graph create  fail\n");goto fail;}merge->input->name = av_strdup("out");merge->input->filter_ctx = merge->buffersink_ctx;merge->input->pad_idx = 0;merge->input->next = NULL;merge->outputFrame = av_frame_alloc();if (merge->outputFrame == NULL){printf("alloc frame  fail\n");goto fail;}merge->outputBuffer = (unsigned char*)av_malloc(av_image_get_buffer_size(merge->outputFormat, merge->outputWidth, merge->outputHeight, 1));if (merge->outputBuffer == NULL){printf("alloc buffer  fail\n");goto fail;}enum AVPixelFormat pix_fmts[2] = { 0, AV_PIX_FMT_NONE };pix_fmts[0] = merge->outputFormat;ret = av_opt_set_int_list(merge->buffersink_ctx, "pix_fmts", pix_fmts, AV_PIX_FMT_NONE, AV_OPT_SEARCH_CHILDREN);if (ret < 0) {printf("set opt fail\n");goto fail;}Stream** streams = merge->streams;for (int i = 0; i < merge->streamCount; i++){streams[i]->buffersrc = avfilter_get_by_name("buffer");av_assert0(streams[i]->buffersrc);snprintf(args, sizeof(args), "video_size=%dx%d:pix_fmt=%d:time_base=%d/%d:pixel_aspect=%d/%d", streams[i]->width, streams[i]->height, streams[i]->format, 1, 90000, 1, 1);snprintf(name, sizeof(name), "in%d", i);ret = avfilter_graph_create_filter(&streams[i]->buffersrc_ctx, streams[i]->buffersrc, name, args, NULL, merge->filter_graph);if (ret < 0){printf("stream graph create fail\n");goto fail;}streams[i]->output = avfilter_inout_alloc();streams[i]->output->name = av_strdup(name);streams[i]->output->filter_ctx = streams[i]->buffersrc_ctx;streams[i]->output->pad_idx = 0;streams[i]->output->next = NULL;streams[i]->inputFrame = av_frame_alloc();if (streams[i]->inputFrame == NULL){printf("alloc frame  fail\n");goto fail;}streams[i]->inputFrame->format = streams[i]->format;streams[i]->inputFrame->width = streams[i]->width;streams[i]->inputFrame->height = streams[i]->height;if (i > 0){streams[i - 1]->output->next = streams[i]->output;}}/*filters_descr = "[in0]pad=1280:640:0:0:black[x0];[x0][in1]overlay=640:0[x1];[x1][in2]overlay=600:0[x2];[x2]null[out]";*/filters_descr = malloc(sizeof(char) * merge->streamCount * 128);if (filters_descr == NULL){printf("alloc string  fail\n");goto fail;}char sigle_descr[128];snprintf(sigle_descr, sizeof(sigle_descr), "[in0]pad=%d:%d:%d:%d:black[x0];", merge->outputWidth, merge->outputHeight, streams[0]->x, streams[0]->y);strcpy(filters_descr, sigle_descr);int i = 1;for (; i < merge->streamCount; i++){snprintf(sigle_descr, sizeof(sigle_descr), "[x%d][in%d]overlay=%d:%d[x%d];", i - 1, i, streams[i]->x, streams[i]->y, i);strcat(filters_descr, sigle_descr);}snprintf(sigle_descr, sizeof(sigle_descr), "[x%d]null[out]", i - 1);strcat(filters_descr, sigle_descr);ret = avfilter_graph_parse_ptr(merge->filter_graph, filters_descr, &merge->input, &streams[0]->output, NULL);if (ret < 0){printf("graph parse fail\n");goto fail;}// 过滤配置初始化ret = avfilter_graph_config(merge->filter_graph, NULL);if (ret < 0){printf("graph config fail\n");goto fail;}if (filters_descr != NULL)free(filters_descr);return 0;
fail:if (filters_descr != NULL)free(filters_descr);Merge_Deinit(merge); //执行反初始化return -1;
}

3、写输入流

void Merge_WriteStream(Merge* merge, Stream* stream, const unsigned char* buffer, int timestamp) {av_image_fill_arrays(stream->inputFrame->data, stream->inputFrame->linesize, buffer, stream->format, stream->width, stream->height, 1);stream->inputFrame->pts = timestamp;if (av_buffersrc_write_frame(stream->buffersrc_ctx, stream->inputFrame) < 0) {printf("Error while add frame.\n");}
}

4、合并流

调用下列方法,即可得到合并后的一帧的数据。可以按照一定帧率调用3、4方法。

const unsigned char* Merge_Merge(Merge* merge) {int	ret = av_buffersink_get_frame(merge->buffersink_ctx, merge->outputFrame);if (ret < 0) {printf("Error while get frame.\n");return NULL;}av_image_copy_to_buffer(merge->outputBuffer,av_image_get_buffer_size(merge->outputFormat, merge->outputWidth, merge->outputHeight, 1),merge->outputFrame->data, merge->outputFrame->linesize, merge->outputFrame->format, merge->outputFrame->width, merge->outputFrame->height, 1);av_frame_unref(merge->outputFrame);return  merge->outputBuffer;
}

5、结束,反初始化,销毁对象

static void Merge_Deinit(Merge* merge)
{if (merge->input != NULL)avfilter_inout_free(&merge->input);if (merge->filter_graph != NULL)avfilter_graph_free(&merge->filter_graph);if (merge->outputFrame != NULL)av_frame_free(&merge->outputFrame);if (merge->outputBuffer != NULL)av_free(merge->outputBuffer);for (int i = 0; i < merge->streamCount; i++){Stream* stream = merge->streams[i]; if (stream->inputFrame != NULL)av_frame_free(&stream->inputFrame);free(stream);}merge->streamCount = 0;
}
void Merge_Destroy(Merge* merge) {Merge_Deinit(merge);free(merge);
}

调用流程示例:

int main() {int flag = 1;Merge* merge = Merge_Create(1920, 1080, 0);Stream* stream1 = Merge_AddStream(merge, 0, 0, 960, 540, 0);Stream* stream2 = Merge_AddStream(merge, 960, 540, 960, 540, 0);Stream* stream3 = Merge_AddStream(merge, 0, 540, 960, 540, 0);if (Merge_Init(merge) != 0){Merge_Destroy(merge);return -1;}while (flag){clock_t time = clock();unsigned char* buffer1;unsigned char* buffer2;unsigned char* buffer3;//获取每路流的数据...//获取每路流的数据-endMerge_WriteStream(merge, stream1, buffer1, time);Merge_WriteStream(merge, stream2, buffer2, time);Merge_WriteStream(merge, stream3, buffer3, time);unsigned char* mergedBuffer = Merge_Merge(merge);//显示或编码推流...//显示或编码推流-end}Merge_Destroy(merge);
}

需要注意的是上述方法最好在单线程中使用,多线程使用可能需要另外做修改,或者参考:

https://download.csdn.net/download/u013113678/32899063

效果如下

这篇关于使用ffmepg实现多路视频流合并的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!


原文地址:
本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.chinasem.cn/article/1117038

相关文章

C/C++中OpenCV 矩阵运算的实现

《C/C++中OpenCV矩阵运算的实现》本文主要介绍了C/C++中OpenCV矩阵运算的实现,包括基本算术运算(标量与矩阵)、矩阵乘法、转置、逆矩阵、行列式、迹、范数等操作,感兴趣的可以了解一下... 目录矩阵的创建与初始化创建矩阵访问矩阵元素基本的算术运算 ➕➖✖️➗矩阵与标量运算矩阵与矩阵运算 (逐元

C/C++的OpenCV 进行图像梯度提取的几种实现

《C/C++的OpenCV进行图像梯度提取的几种实现》本文主要介绍了C/C++的OpenCV进行图像梯度提取的实现,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的... 目录预www.chinasem.cn备知识1. 图像加载与预处理2. Sobel 算子计算 X 和 Y

C/C++和OpenCV实现调用摄像头

《C/C++和OpenCV实现调用摄像头》本文主要介绍了C/C++和OpenCV实现调用摄像头,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一... 目录准备工作1. 打开摄像头2. 读取视频帧3. 显示视频帧4. 释放资源5. 获取和设置摄像头属性

c/c++的opencv图像金字塔缩放实现

《c/c++的opencv图像金字塔缩放实现》本文主要介绍了c/c++的opencv图像金字塔缩放实现,通过对原始图像进行连续的下采样或上采样操作,生成一系列不同分辨率的图像,具有一定的参考价值,感兴... 目录图像金字塔简介图像下采样 (cv::pyrDown)图像上采样 (cv::pyrUp)C++ O

MySQL的ALTER TABLE命令的使用解读

《MySQL的ALTERTABLE命令的使用解读》:本文主要介绍MySQL的ALTERTABLE命令的使用,具有很好的参考价值,希望对大家有所帮助,如有错误或未考虑完全的地方,望不吝赐教... 目录1、查看所建表的编China编程码格式2、修改表的编码格式3、修改列队数据类型4、添加列5、修改列的位置5.1、把列

c/c++的opencv实现图片膨胀

《c/c++的opencv实现图片膨胀》图像膨胀是形态学操作,通过结构元素扩张亮区填充孔洞、连接断开部分、加粗物体,OpenCV的cv::dilate函数实现该操作,本文就来介绍一下opencv图片... 目录什么是图像膨胀?结构元素 (KerChina编程nel)OpenCV 中的 cv::dilate() 函

Python使用FFmpeg实现高效音频格式转换工具

《Python使用FFmpeg实现高效音频格式转换工具》在数字音频处理领域,音频格式转换是一项基础但至关重要的功能,本文主要为大家介绍了Python如何使用FFmpeg实现强大功能的图形化音频转换工具... 目录概述功能详解软件效果展示主界面布局转换过程截图完成提示开发步骤详解1. 环境准备2. 项目功能结

SpringBoot使用ffmpeg实现视频压缩

《SpringBoot使用ffmpeg实现视频压缩》FFmpeg是一个开源的跨平台多媒体处理工具集,用于录制,转换,编辑和流式传输音频和视频,本文将使用ffmpeg实现视频压缩功能,有需要的可以参考... 目录核心功能1.格式转换2.编解码3.音视频处理4.流媒体支持5.滤镜(Filter)安装配置linu

Redis中的Lettuce使用详解

《Redis中的Lettuce使用详解》Lettuce是一个高级的、线程安全的Redis客户端,用于与Redis数据库交互,Lettuce是一个功能强大、使用方便的Redis客户端,适用于各种规模的J... 目录简介特点连接池连接池特点连接池管理连接池优势连接池配置参数监控常用监控工具通过JMX监控通过Pr

apache的commons-pool2原理与使用实践记录

《apache的commons-pool2原理与使用实践记录》ApacheCommonsPool2是一个高效的对象池化框架,通过复用昂贵资源(如数据库连接、线程、网络连接)优化系统性能,这篇文章主... 目录一、核心原理与组件二、使用步骤详解(以数据库连接池为例)三、高级配置与优化四、典型应用场景五、注意事