• Java之视频读取IO流解帧实施方案


      获取视频处理对象的方式有很多,读取本地文件、读取url、读取摄像头等,而直接读流解析视频的实施方案却难以寻觅。此处有两种方案处理视频流(此处设定场景为用户上传视频,同时两种方式均需服务端安装ffmpeg+opencv):

      1.io流保存本地再读取

          该方案没有太多技术含量,直接借助java.io+opencv-VideoCapture即可实现视频的解帧等操作。

          1)保存本地

            本地保存为求方便,直接使用 apache.commons.io.FileUtils.copyInputStreamToFile(InputStream,File)方法

    // MultipartFile videoFile
    InputStream videoInputStream = videoFile.getInputStream();
    File file = new File(path + getRandomFileName() + ".mp4");
    FileUtils.copyInputStreamToFile(videoInputStream,file);

          2)  视频解析

            此处视频解析,可以直接使用整合了ffmpeg的opencv中的VideoCapture对象来操作

    VideoCapture = new VideoCapture(file.getPath());

          3) 业务要求

            项目业务要求,取视频前两秒的20帧,转储为Mat矩阵的集合

    // 此处的视频操作常量来自 javacv
    Double rawFps = videoCapture.get(opencv_highgui.CV_CAP_PROP_FPS);// 帧率
    Double validFps = Math.min(10.0,rawFps);// 校验
    Double validTimeGap = 1.0 / validFps;
    List<Mat> frameList = new ArrayList();
    try {
        Double currentTime = 0.0;
        while (currentTime + EPSILON < timeCount) {//EPSILON为浮点数操作修正值
            // 设置视频的位置
            videoCapture.set(opencv_highgui.CV_CAP_PROP_POS_MSEC,currentTime * 1000);
            Mat frame = new Mat();
            capture.read(frame);
            frameList.add(frame);
            currentTime += validTimeGap;
        }  
    } catch .... finally ..

      2.直接读流

        直接读流的依赖支撑来自 Bytedeco - javacv - FFmpegFrameGrabber 类,在此 向Bytedeco团队致敬

        1)读io,转FFmpegFrameGrabber

    InputStream inputStream = videoFile.getInputStream();
    FFmpegFrameGrabber grabber = new FFmpegFrameGrabber(inputStream);

        2)业务要求

        FFmpegFrameGrabber与VideoCapture在开闭时有所不同,VideoCapture如果直接构造来初始化不需手动open()即打开,FFmpegFrameGrabber有一专属方法来打开视频解析 - start() 。

    grabber.start();
    // get each mat
    List<Mat> mats = new ArrayList<>();
    double fps = grabber.getFrameRate();
    double each = Math.ceil(fps / fpsDefine);
    double count = fps * timeCount ;
    for (int i = 0 ; i < count ; i++) {
        double mod = i % each;
        Frame frame = grabber.grabImage();
        if (mod == 0.0) {
            OpenCVFrameConverter.ToMat toMat = new OpenCVFrameConverter.ToMat();
            opencv_core.Mat mat = toMat.convert(frame);
            if (mat != null) {
                Mat matUse = new Mat(mat.clone().address());
                mats.add(matUse);
                mat.release();
            }
        }
    }

      3.两种方式的异同

        1.bytedeco - ffmpeg 包中整合有Frame - Mat - BufferImage的相关转换方法,实际应用中需注意其与opencv - Mat的转换

        2.二者都依赖ffmpeg+opencv本地方法,而pom依赖又有不同:

        VideoCapture:

            <dependency>
                <groupId>org.opencv</groupId>
                <artifactId>opencv</artifactId>
                <version>2.4.13</version>
            </dependency>
            <dependency>
                <groupId>org.bytedeco</groupId>
                <artifactId>javacv</artifactId>
                <version>1.4.3</version>
            </dependency>

        FFmpegFrameGrabber:

            <dependency>
                <groupId>org.opencv</groupId>
                <artifactId>opencv</artifactId>
                <version>2.4.13</version>
            </dependency>
            <dependency>
                <groupId>org.bytedeco</groupId>
                <artifactId>javacv</artifactId>
                <version>1.4.3</version>
            </dependency>
            <dependency>
                <groupId>org.bytedeco.javacpp-presets</groupId>
                <artifactId>opencv</artifactId>
                <version>3.4.3-1.4.3</version>
                <classifier>linux-x86_64</classifier>
            </dependency>
            <dependency>
                <groupId>org.bytedeco.javacpp-presets</groupId>
                <artifactId>ffmpeg</artifactId>
                <version>4.0.2-1.4.3</version>
                <classifier>linux-x86_64</classifier>
            </dependency>
            <dependency>
                <groupId>org.bytedeco</groupId>
                <artifactId>javacpp</artifactId>
                <version>1.4.3</version>
            </dependency>

        3.都需手动对本地资源加以释放:这里包括io流,视频流,Mat矩阵,同时释放的方法又有不同

        VideoCapture:release()

        FFmpegFrameGrabber : stop()

            finally {
                try {
                    inputStream.close();
                } catch (IOException e) {
                    log.error("close InputStream error : " , e);
                }
                try {
                    grabber.stop();
                } catch (FrameGrabber.Exception e) {
                    log.error("stop grabber error : " , e);
                }
                for (Mat mat : mats) {
                    if (mat != null) {
                        mat.release();
                    }
                }
            }
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  • 原文地址:https://www.cnblogs.com/nyatom/p/10213358.html
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