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(); } } }