How to use C++ for efficient video stream processing and video analysis?

How to use C for efficient video stream processing and video analysis?

Abstract: With the rapid development of video technology, more and more applications require video processing and analysis. This article will introduce how to use C language for efficient video stream processing and video analysis, including video stream acquisition, video decoding, video encoding and video analysis, and provide corresponding code examples.

1. Video stream acquisition
Video stream acquisition is the first step in video processing, which mainly obtains video streams from sources such as cameras, files, or networks. In C, you can use the OpenCV library for video stream acquisition, which is easy to use and powerful.
The following is a code example that uses the OpenCV library to obtain local video files:

#include <opencv2/opencv.hpp>

int main() {
    cv::VideoCapture cap("test.mp4");  // 打开本地视频文件
    if (!cap.isOpened()) {             // 检查文件是否成功打开
        std::cout << "Failed to open video file!" << std::endl;
        return -1;
    }

    cv::Mat frame;
    while (cap.read(frame)) {          // 读取每一帧画面
        cv::imshow("Video", frame);    // 显示视频
        cv::waitKey(1);
    }

    cap.release();                     // 释放资源

    return 0;
}

2. Video decoding
Video decoding is to decode the compressed video stream into the original video frame data for subsequent use processing and analysis. In C, you can use the FFmpeg library for video decoding, with extensive support and efficient decoding performance.
The following is a code example that uses the FFmpeg library to decode a video file and output each frame:

extern "C" {
#include <libavformat/avformat.h>
#include <libswscale/swscale.h>
}

int main() {
    av_register_all();

    AVFormatContext* format_ctx = nullptr;
    if (avformat_open_input(&format_ctx, "test.mp4", nullptr, nullptr) != 0) {
        std::cout << "Failed to open video file!" << std::endl;
        return -1;
    }

    avformat_find_stream_info(format_ctx, nullptr);

    int video_stream_index = -1;
    for (int i = 0; i < format_ctx->nb_streams; i++) {
        if (format_ctx->streams[i]->codecpar->codec_type == AVMEDIA_TYPE_VIDEO) {
            video_stream_index = i;  // 找到视频流索引
            break;
        }
    }

    AVCodecParameters* codec_params = format_ctx->streams[video_stream_index]->codecpar;
    AVCodec* codec = avcodec_find_decoder(codec_params->codec_id);
    if (codec == nullptr) {
        std::cout << "Failed to find decoder!" << std::endl;
        return -1;
    }

    AVCodecContext* codec_ctx = avcodec_alloc_context3(codec);
    avcodec_parameters_to_context(codec_ctx, codec_params);
    avcodec_open2(codec_ctx, codec, nullptr);

    AVFrame* frame = av_frame_alloc();
    AVPacket packet;

    while (av_read_frame(format_ctx, &packet) >= 0) {
        if (packet.stream_index == video_stream_index) {
            avcodec_send_packet(codec_ctx, &packet);
            avcodec_receive_frame(codec_ctx, frame);

            // TODO: 处理每一帧画面
        }
        av_packet_unref(&packet);
    }

    av_frame_free(&frame);
    avcodec_free_context(&codec_ctx);
    avformat_close_input(&format_ctx);

    return 0;
}

3. Video encoding
Video encoding is to compress the processed video frame data for storage and transmission. In C, it is also possible to use the FFmpeg library for video encoding to achieve efficient video compression and encoding.
The following is a code example that uses the FFmpeg library to encode the original video frame data into a video file in H.264 format:

extern "C" {
#include <libavformat/avformat.h>
#include <libswscale/swscale.h>
#include <libavcodec/avcodec.h>
}

int main() {
    av_register_all();

    AVFormatContext* format_ctx = nullptr;
    if (avformat_alloc_output_context2(&format_ctx, nullptr, nullptr, "output.mp4") != 0) {
        std::cout << "Failed to create output format context!" << std::endl;
        return -1;
    }

    AVOutputFormat* output_fmt = format_ctx->oformat;

    AVStream* video_stream = avformat_new_stream(format_ctx, nullptr);
    if (video_stream == nullptr) {
        std::cout << "Failed to create video stream!" << std::endl;
        return -1;
    }

    AVCodec* codec = avcodec_find_encoder(AV_CODEC_ID_H264);
    if (codec == nullptr) {
        std::cout << "Failed to find encoder!" << std::endl;
        return -1;
    }

    AVCodecContext* codec_ctx = avcodec_alloc_context3(codec);
    if (codec_ctx == nullptr) {
        std::cout << "Failed to allocate codec context!" << std::endl;
        return -1;
    }

    codec_ctx->width = 640;
    codec_ctx->height = 480;
    codec_ctx->pix_fmt = AV_PIX_FMT_YUV420P;
    codec_ctx->time_base = (AVRational){1, 30};

    if (format_ctx->oformat->flags & AVFMT_GLOBALHEADER) {
        codec_ctx->flags |= AV_CODEC_FLAG_GLOBAL_HEADER;
    }

    avcodec_open2(codec_ctx, codec, nullptr);

    avcodec_parameters_from_context(video_stream->codecpar, codec_ctx);

    avio_open(&format_ctx->pb, "output.mp4", AVIO_FLAG_WRITE);

    avformat_write_header(format_ctx, nullptr);

    // TODO: 逐帧编码并写入

    av_write_trailer(format_ctx);

    avio_close(format_ctx->pb);
    avcodec_free_context(&codec_ctx);
    avformat_free_context(format_ctx);

    return 0;
}

4. Video analysis
Video analysis is to perform various operations on video data. Algorithms and processing, by extracting key information and features in videos to complete different tasks, such as target detection, action recognition, etc. In C, you can use the OpenCV library for video analysis and combine it with other image processing algorithms for more advanced video analysis.
The following is a code example that uses the OpenCV library to perform target detection on videos:

#include <opencv2/opencv.hpp>

int main() {
    cv::VideoCapture cap("test.mp4");
    if (!cap.isOpened()) {
        std::cout << "Failed to open video file!" << std::endl;
        return -1;
    }

    cv::CascadeClassifier classifier("haarcascade_frontalface_default.xml");

    cv::Mat frame;
    while (cap.read(frame)) {
        cv::Mat gray;
        cv::cvtColor(frame, gray, cv::COLOR_BGR2GRAY);

        std::vector<cv::Rect> faces;
        classifier.detectMultiScale(gray, faces, 1.1, 3);

        for (const auto& rect : faces) {
            cv::rectangle(frame, rect, cv::Scalar(0, 255, 0), 2);
        }

        cv::imshow("Video", frame);
        cv::waitKey(1);
    }

    cap.release();

    return 0;
}

Summary: This article introduces how to use C language for efficient video stream processing and video analysis. Through the OpenCV library for video stream acquisition and video analysis, and through the FFmpeg library for video decoding and video encoding, various video processing and analysis functions can be easily implemented. Through the code examples provided in this article, readers can refer to them during the development process and apply them to actual projects. I hope this article will be helpful to readers in video processing and video analysis.

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