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图像处理常见的两种拉流方式

news 2025/6/30 10:21:58

传统算法或者深度学习在进行图像处理之前，总是会首先进行图像的采集，也就是所谓的拉流。解决拉流的方式有两种，一个是直接使用opencv进行取流，另一个是使用ffmpeg进行取流，如下分别介绍这两种方式进行拉流处理。

1、opencv直接取流

opencv的取流方式主要是利用VideoCapture类进行处理的。VideoCapture提供了一整套的读取视频流信息的方案，主要的函数如下：
VideoCapture有三个构造函数：

不带任何参数的构造函数
带有一个视频流地址的构造函数
带有一个视频index的构造函数

isOpened()函数主要是判定是否成功打开流地址

read()读取视频数据

release()函数用于释放类对象

具体参考地址：https://docs.opencv.org/4.0.0/d8/dfe/classcv_1_1VideoCapture.html

1.1 python拉流

主要流程为分为以下几步：

通过流的地址实例化VideoCapture类
判断是否成功打开流地址
循环读取每一帧流数据并处理
释放实例化的对象
释放cv

def vedio2Img(vedio_path, save_path):cap = cv2.VideoCapture(vedio_path)fps = int(cap.get(cv2.CAP_PROP_FPS))total_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)count = 0img_idx = 0if not cap.isOpened():returnwhile True:success, frame = cap.read()if success:try:count += 1if count % fps == 0:img_idx += 1name = save_path.split('\\')[-1]save_path1 = os.path.join(save_path, '{}_vedio_{}.jpg'.format(name, str(img_idx)))save_img(save_path1, frame)print('finish number {} img save'.format(img_idx))cv2.waitKey(1)except:print('encounter some wrong')continuecap.release()cv2.destroyAllWindows()

1.2 C++ opencv拉流

c++的使用opencv拉流的方式和opencv基本一致（ps:python的底层应该是C++实现的），因此其实现格式如下所示：

	std::string vedio_path = "rtsp://admin:123456@127.0.0.1/Streaming/Channels/11000";cv::VideoCapture cap;cap.open(vedio_path);if (!cap.isOpened()) {std::cout << "error about cap" << std::endl;}VideoFrameDecode videoframe;cv::Mat frame;while (cap.read(frame)){if (frame.empty()) {break;}int w = frame.size().width;int h = frame.size().height;printf("h=%i,w=%i", h, w);unsigned char* buffer = frame.data;size_t stride = frame.step;cv::Mat img = cv::Mat(h, w, CV_8UC3, (void*)buffer, stride);cv::namedWindow("demo", cv::WINDOW_NORMAL);cv::imshow("demo", img);cv::waitKey(0);}cap.release();cv::destroyAllWindows();

2、ffmpeg拉流（C++实现）

下载ffmpeg包的
ffmpeg包下载地址
博主下载的5.1.2版本
vs2022配置使用
在C/C+±>附加包含目录中添加新下载的ffmpeg包的include路径

在链接器->附加库目录中添加ffmpeg包的lib文件路径

在链接器->输入->附加依赖项中加入所需要的lib库目录，整理如下：
```
avcodec.lib
avdevice.lib
avfilter.lib
avformat.lib
avutil.lib
swresample.lib
swscale.lib
```
如果不想在环境变量中配置ffmpeg中bin文件的目录，可以使用如下方式临时配置：
在调试->环境中使用Path=D:\ffmpeg\bin;%PATH即可临时使用

博主将拉流方式封装为一个类，主要代码如下所示：
ffmpeg.h文件如下：

#ifndef __FFMPEG_DECODE_H__
#define __FFMPEG_DECODE_H__// Opencv
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
extern "C"
{
#include<libavutil/avutil.h>
#include<libavutil/imgutils.h>
#include <libavcodec/avcodec.h>
#include <libavformat/avformat.h>
#include <libswscale/swscale.h>
#include<libavdevice/avdevice.h>
};struct VideoFrameDecode {void* buffer;		//֡帧的buffer指针(仅支持RGB格式)int pitch;			//图像一行的宽度
};class ReadFfmpeg
{
public:ReadFfmpeg(char* rtsppath);~ReadFfmpeg();void processOneFrame(cv::Mat &img);private:AVFormatContext* formatContext = nullptr; int ret = -1;int videoStreamIndex = -1;AVCodecParameters* codecParameters = nullptr;const AVCodec* codec = nullptr; AVCodecContext* codecContext = nullptr; AVPacket packet; AVFrame* pFrameRGB;uint8_t* buffer;SwsContext* sws_ctx; };
#endif

其中具体实现的ffmpeg.cpp文件如下所示

#include "ReadFfmpeg.h"
#include <iostream>
#include<chrono>
#include<thread>
using namespace std;ReadFfmpeg::ReadFfmpeg(char* rtsppath)
{avformat_network_init();AVDictionary* formatOptions = nullptr;av_dict_set_int(&formatOptions, "buffer_size", 2 << 20, 0);av_dict_set(&formatOptions, "rtsp_transport", "tcp", 0); //默认使用udp协议进行传输，会出现max delay reached. need to consume packet av_dict_set_int(&formatOptions, "timeout", 5000000, 0);formatContext = avformat_alloc_context();ret = avformat_open_input(&formatContext, rtsppath, nullptr, &formatOptions);if (ret != 0) {std::cerr << "Failed to open RTSP stream." << std::endl;}ret = avformat_find_stream_info(formatContext, nullptr);if (ret < 0) {std::cerr << "Failed to find stream info." << std::endl;}for (unsigned int i = 0; i < formatContext->nb_streams; ++i) {if (formatContext->streams[i]->codecpar->codec_type == AVMEDIA_TYPE_VIDEO) {videoStreamIndex = i;break;}}if (videoStreamIndex == -1) {std::cerr << "Failed to find video stream." << std::endl;}codecParameters = formatContext->streams[videoStreamIndex]->codecpar;codec = avcodec_find_decoder(codecParameters->codec_id);if (codec == nullptr) {std::cerr << "Failed to find video decoder." << std::endl;}codecContext = avcodec_alloc_context3(codec);if (avcodec_parameters_to_context(codecContext, codecParameters) < 0) {std::cerr << "Failed to allocate codec context." << std::endl;}ret = avcodec_open2(codecContext, codec, nullptr);if (ret < 0) {std::cerr << "Failed to open codec." << std::endl;}pFrameRGB = av_frame_alloc();buffer = (uint8_t*)av_malloc(av_image_get_buffer_size(AV_PIX_FMT_RGB24, codecContext->width, codecContext->height, 1));av_image_fill_arrays(pFrameRGB->data, pFrameRGB->linesize, buffer, AV_PIX_FMT_RGB24, codecContext->width, codecContext->height, 1);sws_ctx = sws_getContext(codecContext->width, codecContext->height, codecContext->pix_fmt,codecContext->width, codecContext->height, AV_PIX_FMT_RGB24,SWS_BILINEAR, nullptr, nullptr, nullptr);ret = av_read_frame(formatContext, &packet);if (ret < 0) {std::cerr << "Failed to open packet." << std::endl;}
}ReadFfmpeg::~ReadFfmpeg()
{avformat_network_deinit();avcodec_free_context(&codecContext);sws_freeContext(sws_ctx);	av_free(pFrameRGB);av_free(buffer);av_free(codecParameters);avformat_close_input(&formatContext);
}void ReadFfmpeg::processOneFrame(cv::Mat& img)
{if (img.empty()){img = cv::Mat(codecContext->height, codecContext->width, CV_8UC3);}int ret = av_read_frame(formatContext, &packet);if (ret >= 0) {if (packet.stream_index == videoStreamIndex) {avcodec_send_packet(codecContext, &packet);AVFrame* avFrame = av_frame_alloc();int res = avcodec_receive_frame(codecContext, avFrame);if (res == 0) {// Convert frame to RGBsws_scale(sws_ctx, avFrame->data, avFrame->linesize, 0, codecContext->height, pFrameRGB->data, pFrameRGB->linesize);img.data = pFrameRGB->data[0];}av_frame_free(&avFrame);}}av_packet_unref(&packet);
}void test() {char* filename = (char*)"rtsp://admin:123456@127.0.0.1:10000/Streaming/Channels/10000";ReadFfmpeg* fmpeg = new ReadFfmpeg(filename);cv::Mat img;int nFrame = 0;auto start = std::chrono::system_clock::now();for (;;){nFrame++;fmpeg->processOneFrame(img);if (nFrame % 100==0) {nFrame = 0;auto end = std::chrono::system_clock::now();auto duration = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);std::cout << "the fps is: " << static_cast<float>(100 / (duration.count() / 1000.0)) << std::endl;start = end;}// Display framecv::namedWindow("RTSP Stream", cv::WINDOW_NORMAL);cv::imshow("RTSP Stream", img);cv::waitKey(1);}delete fmpeg;}