default package怎么删除

时间: 2023-05-31 13:18:43 浏览: 1272
### 回答1: 默认包(default package)是Java中没有指定包名的类所属的包,通常情况下不建议使用默认包。如果需要删除默认包,可以将类移动到一个新的包中,或者在类文件的开头添加包名声明。具体操作如下: 1. 将类移动到新的包中: 将类文件从默认包中移动到新的包中,可以使用IDE(如Eclipse、IntelliJ IDEA)的重构功能,右键点击类文件,选择“Refactor” -> “Move”,然后选择目标包名即可。 2. 添加包名声明: 在类文件的开头添加包名声明,格式为“package 包名;”,例如“package com.example;”。注意,包名声明必须放在类文件的第一行,否则会编译错误。 完成以上操作后,就可以删除默认包了。 ### 回答2: 首先,我们需要明确一个概念,default package是在Java中的一种特殊情况,它表示一个类被定义在一个没有指定包名的源文件中,也就是没有package语句的文件。不过,通常我们建议不要使用default package,因为它会带来很多不可预测的问题,比如冲突、命名空间不够明确等等。 如果你使用Eclipse这样的IDE,那么删除default package非常简单,只需要将你的所有类放在一个指定的package中即可。具体操作如下: 1.右击项目,选择New -> Package,创建一个新的包。 2.将你的所有类文件拖拽到这个新的包中。 3.右击default package,选择Delete,然后就可以将default package删除了。 如果你是手动编辑Java源文件,那么也可以通过修改源文件的package语句来删除default package。具体方法如下: 1.编辑源文件,在文件开头加上一个package语句,指定需要将这个类归属到哪个包中。 2.将源文件保存到指定的包目录下,以类名作为文件名。 3.删除原始的源文件,只保留新的位于指定包中的源文件。 需要注意的是,如果你在default package中使用了其他类的引用,那么在删除default package之前,你需要修改这些类的引用路径,以便它们可以正确地引用新的包中的类。 ### 回答3: 默认包(default package)是Java中所有未指定包名的类所属的包。在Java开发中,一个类必须被打包加入一个包中。 如果默认包中出现重名类,则会出现编译错误甚至运行错误。因此,通常不建议使用默认包。 若需要删除默认包: 1.将该文件移动到指定的包名中。即,在文件的开头增加所属包名的声明。 例如,将DefaultClass.java移动到com.example包中,则需要在文件开头增加声明: package com.example; 编译器会自动将DefaultClass所属包名更改为com.example,从而删除默认包。 2. 在IDE工具中进行配置更改。一些IDE工具,例如Eclipse、IntelliJ IDEA等,可以直接改变类所处的包即可删除默认包。 方法如下: -在工程目录中创建一个新的包。 - 将类拖放到新的包里。 - IDE会自动将该类的包名更改为新的包名。 无论采用哪种方式,重要的是将类放置到明确的包中,以避免因为默认包的使用而造成错误。
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package com.test; import java.awt.image.BufferedImage; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.IOException; public class B { public static void main(String[] args) { File file = new File("c:\\a.jpg"); FileInputStream is = null; try { is = new FileInputStream(file); } catch (FileNotFoundException e2) { e2.printStackTrace(); // return rect; } BufferedImage sourceImg = null; try { sourceImg = javax.imageio.ImageIO.read(is); } catch (IOException e1) { e1.printStackTrace(); // return rect; } System.out.println("width = " + sourceImg.getWidth() + "height = " + sourceImg.getHeight()); } } package com.test; import java.awt.image.BufferedImage; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.IOException; public class B { public static void main(String[] args) { File file = new File("c:\\a.jpg"); FileInputStream is = null; try { is = new FileInputStream(file); } catch (FileNotFoundException e2) { e2.printStackTrace(); // return rect; } BufferedImage sourceImg = null; try { sourceImg = javax.imageio.ImageIO.read(is); } catch (IOException e1) { e1.printStackTrace(); // return rect; } System.out.println("width = " + sourceImg.getWidth() + "height = " + sourceImg.getHeight()); } } package com.test; import java.awt.image.BufferedImage; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.IOException; public class B { public static void main(String[] args) { File file = new File("c:\\a.jpg"); FileInputStream is = null; try { is = new FileInputStream(file); } catch (FileNotFoundException e2) { e2.printStackTrace(); // return rect; } BufferedImage sourceImg = null; try { sourceImg = javax.imageio.ImageIO.read(is); } catch (IOException e1) { e1.printStackTrace(); // return rect; } System.out.println("width = " + sourceImg.getWidth() + "height = " + sourceImg.getHeight()); } } package com.test; import java.awt.image.BufferedImage; import java.io.File; import java.io.FileInputStream; import java.io.FileNotFoundException; import java.io.IOException; public class B { public static void main(String[] args) { File file = new File("c:\\a.jpg"); FileInputStream is = null; try { is = new FileInputStream(file); } catch (FileNotFoundException e2) { e2.printStackTrace(); // return rect; } BufferedImage sourceImg = null; try { sourceImg = javax.imageio.ImageIO.read(is); } catch (IOException e1) { e1.printStackTrace(); // return rect; } System.out.println("width = " + sourceImg.getWidth() + "height = " + sourceImg.getHeight()); } }
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视频人脸识别,取代jmf。。。 Introduction JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, PGR FlyCapture, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, and flandmark), and provides utility classes to make their functionality easier to use on the Java platform, including Android. JavaCV also comes with hardware accelerated full-screen image display (CanvasFrame and GLCanvasFrame), easy-to-use methods to execute code in parallel on multiple cores (Parallel), user-friendly geometric and color calibration of cameras and projectors (GeometricCalibrator, ProCamGeometricCalibrator, ProCamColorCalibrator), detection and matching of feature points (ObjectFinder), a set of classes that implement direct image alignment of projector-camera systems (mainly GNImageAligner, ProjectiveTransformer, ProjectiveColorTransformer, ProCamTransformer, and ReflectanceInitializer), a blob analysis package (Blobs), as well as miscellaneous functionality in the JavaCV class. Some of these classes also have an OpenCL and OpenGL counterpart, their names ending with CL or starting with GL, i.e.: JavaCVCL, GLCanvasFrame, etc. To learn how to use the API, since documentation currently lacks, please refer to the Sample Usage section below as well as the sample programs, including two for Android (FacePreview.java and RecordActivity.java), also found in the samples directory. You may also find it useful to refer to the source code of ProCamCalib and ProCamTracker as well as examples ported from OpenCV2 Cookbook and the associated wiki pages. Please keep me informed of any updates or fixes you make to the code so that I may integrate them into the next release. Thank you! And feel free to ask questions on the mailing list if you encounter any problems with the software! I am sure it is far from perfect... Downloads To install manually the JAR files, obtain the following archives and follow the instructions in the Manual Installation section below. JavaCV 1.3.3 binary archive javacv-platform-1.3.3-bin.zip (212 MB) JavaCV 1.3.3 source archive javacv-platform-1.3.3-src.zip (456 KB) The binary archive contains builds for Android, Linux, Mac OS X, and Windows. The JAR files for specific child modules or platforms can also be obtained individually from the Maven Central Repository. We can also have everything downloaded and installed automatically with: Maven (inside the pom.xml file) <dependency> <groupId>org.bytedeco</groupId> <artifactId>javacv-platform</artifactId> <version>1.3.3</version> </dependency> Gradle (inside the build.gradle file) dependencies { compile group: 'org.bytedeco', name: 'javacv-platform', version: '1.3.3' } sbt (inside the build.sbt file) libraryDependencies += "org.bytedeco" % "javacv-platform" % "1.3.3" This downloads binaries for all platforms, but to get binaries for only one platform we can set the javacpp.platform system property (via the -D command line option) to something like android-arm, linux-x86_64, macosx-x86_64, windows-x86_64, etc. Please refer to the README.md file of the JavaCPP Presets for details. Another option available for Scala users is sbt-javacv. Required Software To use JavaCV, you will first need to download and install the following software: An implementation of Java SE 7 or newer: OpenJDK http://openjdk.java.net/install/ or Sun JDK http://www.oracle.com/technetwork/java/javase/downloads/ or IBM JDK http://www.ibm.com/developerworks/java/jdk/ Further, although not always required, some functionality of JavaCV also relies on: CL Eye Platform SDK (Windows only) http://codelaboratories.com/downloads/ Android SDK API 14 or newer http://developer.android.com/sdk/ JOCL and JOGL from JogAmp http://jogamp.org/ Finally, please make sure everything has the same bitness: 32-bit and 64-bit modules do not mix under any circumstances. Manual Installation Simply put all the desired JAR files (opencv*.jar, ffmpeg*.jar, etc.), in addition to javacpp.jar and javacv.jar, somewhere in your class path. Here are some more specific instructions for common cases: NetBeans (Java SE 7 or newer): In the Projects window, right-click the Libraries node of your project, and select "Add JAR/Folder...". Locate the JAR files, select them, and click OK. Eclipse (Java SE 7 or newer): Navigate to Project > Properties > Java Build Path > Libraries and click "Add External JARs...". Locate the JAR files, select them, and click OK. IntelliJ IDEA (Android 4.0 or newer): Follow the instructions on this page: http://developer.android.com/training/basics/firstapp/ Copy all the JAR files into the app/libs subdirectory. Navigate to File > Project Structure > app > Dependencies, click +, and select "2 File dependency". Select all the JAR files from the libs subdirectory. After that, the wrapper classes for OpenCV and FFmpeg, for example, can automatically access all of their C/C++ APIs: OpenCV documentation FFmpeg documentation Sample Usage The class definitions are basically ports to Java of the original header files in C/C++, and I deliberately decided to keep as much of the original syntax as possible. For example, here is a method that tries to load an image file, smooth it, and save it back to disk: import static org.bytedeco.javacpp.opencv_core.*; import static org.bytedeco.javacpp.opencv_imgproc.*; import static org.bytedeco.javacpp.opencv_imgcodecs.*; public class Smoother { public static void smooth(String filename) { IplImage image = cvLoadImage(filename); if (image != null) { cvSmooth(image, image); cvSaveImage(filename, image); cvReleaseImage(image); } } } JavaCV also comes with helper classes and methods on top of OpenCV and FFmpeg to facilitate their integration to the Java platform. Here is a small demo program demonstrating the most frequently useful parts: import java.io.File; import java.net.URL; import org.bytedeco.javacv.*; import org.bytedeco.javacpp.*; import org.bytedeco.javacpp.indexer.*; import static org.bytedeco.javacpp.opencv_core.*; import static org.bytedeco.javacpp.opencv_imgproc.*; import static org.bytedeco.javacpp.opencv_calib3d.*; import static org.bytedeco.javacpp.opencv_objdetect.*; public class Demo { public static void main(String[] args) throws Exception { String classifierName = null; if (args.length > 0) { classifierName = args[0]; } else { URL url = new URL("https://raw.github.com/Itseez/opencv/2.4.0/data/haarcascades/haarcascade_frontalface_alt.xml"); File file = Loader.extractResource(url, null, "classifier", ".xml"); file.deleteOnExit(); classifierName = file.getAbsolutePath(); } // Preload the opencv_objdetect module to work around a known bug. Loader.load(opencv_objdetect.class); // We can "cast" Pointer objects by instantiating a new object of the desired class. CvHaarClassifierCascade classifier = new CvHaarClassifierCascade(cvLoad(classifierName)); if (classifier.isNull()) { System.err.println("Error loading classifier file \"" + classifierName + "\"."); System.exit(1); } // The available FrameGrabber classes include OpenCVFrameGrabber (opencv_videoio), // DC1394FrameGrabber, FlyCaptureFrameGrabber, OpenKinectFrameGrabber, OpenKinect2FrameGrabber, // RealSenseFrameGrabber, PS3EyeFrameGrabber, VideoInputFrameGrabber, and FFmpegFrameGrabber. FrameGrabber grabber = FrameGrabber.createDefault(0); grabber.start(); // CanvasFrame, FrameGrabber, and FrameRecorder use Frame objects to communicate image data. // We need a FrameConverter to interface with other APIs (Android, Java 2D, or OpenCV). OpenCVFrameConverter.ToIplImage converter = new OpenCVFrameConverter.ToIplImage(); // FAQ about IplImage and Mat objects from OpenCV: // - For custom raw processing of data, createBuffer() returns an NIO direct // buffer wrapped around the memory pointed by imageData, and under Android we can // also use that Buffer with Bitmap.copyPixelsFromBuffer() and copyPixelsToBuffer(). // - To get a BufferedImage from an IplImage, or vice versa, we can chain calls to // Java2DFrameConverter and OpenCVFrameConverter, one after the other. // - Java2DFrameConverter also has static copy() methods that we can use to transfer // data more directly between BufferedImage and IplImage or Mat via Frame objects. IplImage grabbedImage = converter.convert(grabber.grab()); int width = grabbedImage.width(); int height = grabbedImage.height(); IplImage grayImage = IplImage.create(width, height, IPL_DEPTH_8U, 1); IplImage rotatedImage = grabbedImage.clone(); // Objects allocated with a create*() or clone() factory method are automatically released // by the garbage collector, but may still be explicitly released by calling release(). // You shall NOT call cvReleaseImage(), cvReleaseMemStorage(), etc. on objects allocated this way. CvMemStorage storage = CvMemStorage.create(); // The OpenCVFrameRecorder class simply uses the CvVideoWriter of opencv_videoio, // but FFmpegFrameRecorder also exists as a more versatile alternative. FrameRecorder recorder = FrameRecorder.createDefault("output.avi", width, height); recorder.start(); // CanvasFrame is a JFrame containing a Canvas component, which is hardware accelerated. // It can also switch into full-screen mode when called with a screenNumber. // We should also specify the relative monitor/camera response for proper gamma correction. CanvasFrame frame = new CanvasFrame("Some Title", CanvasFrame.getDefaultGamma()/grabber.getGamma()); // Let's create some random 3D rotation... CvMat randomR = CvMat.create(3, 3), randomAxis = CvMat.create(3, 1); // We can easily and efficiently access the elements of matrices and images // through an Indexer object with the set of get() and put() methods. DoubleIndexer Ridx = randomR.createIndexer(), axisIdx = randomAxis.createIndexer(); axisIdx.put(0, (Math.random()-0.5)/4, (Math.random()-0.5)/4, (Math.random()-0.5)/4); cvRodrigues2(randomAxis, randomR, null); double f = (width + height)/2.0; Ridx.put(0, 2, Ridx.get(0, 2)*f); Ridx.put(1, 2, Ridx.get(1, 2)*f); Ridx.put(2, 0, Ridx.get(2, 0)/f); Ridx.put(2, 1, Ridx.get(2, 1)/f); System.out.println(Ridx); // We can allocate native arrays using constructors taking an integer as argument. CvPoint hatPoints = new CvPoint(3); while (frame.isVisible() && (grabbedImage = converter.convert(grabber.grab())) != null) { cvClearMemStorage(storage); // Let's try to detect some faces! but we need a grayscale image... cvCvtColor(grabbedImage, grayImage, CV_BGR2GRAY); CvSeq faces = cvHaarDetectObjects(grayImage, classifier, storage, 1.1, 3, CV_HAAR_FIND_BIGGEST_OBJECT | CV_HAAR_DO_ROUGH_SEARCH); int total = faces.total(); for (int i = 0; i < total; i++) { CvRect r = new CvRect(cvGetSeqElem(faces, i)); int x = r.x(), y = r.y(), w = r.width(), h = r.height(); cvRectangle(grabbedImage, cvPoint(x, y), cvPoint(x+w, y+h), CvScalar.RED, 1, CV_AA, 0); // To access or pass as argument the elements of a native array, call position() before. hatPoints.position(0).x(x-w/10) .y(y-h/10); hatPoints.position(1).x(x+w*11/10).y(y-h/10); hatPoints.position(2).x(x+w/2) .y(y-h/2); cvFillConvexPoly(grabbedImage, hatPoints.position(0), 3, CvScalar.GREEN, CV_AA, 0); } // Let's find some contours! but first some thresholding... cvThreshold(grayImage, grayImage, 64, 255, CV_THRESH_BINARY); // To check if an output argument is null we may call either isNull() or equals(null). CvSeq contour = new CvSeq(null); cvFindContours(grayImage, storage, contour, Loader.sizeof(CvContour.class), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE); while (contour != null && !contour.isNull()) { if (contour.elem_size() > 0) { CvSeq points = cvApproxPoly(contour, Loader.sizeof(CvContour.class), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contour)*0.02, 0); cvDrawContours(grabbedImage, points, CvScalar.BLUE, CvScalar.BLUE, -1, 1, CV_AA); } contour = contour.h_next(); } cvWarpPerspective(grabbedImage, rotatedImage, randomR); Frame rotatedFrame = converter.convert(rotatedImage); frame.showImage(rotatedFrame); recorder.record(rotatedFrame); } frame.dispose(); recorder.stop(); grabber.stop(); } } Furthermore, after creating a pom.xml file with the following content: <modelVersion>4.0.0</modelVersion> <groupId>org.bytedeco.javacv</groupId> <artifactId>demo</artifactId> <version>1.3.3</version> <dependencies> <dependency> <groupId>org.bytedeco</groupId> <artifactId>javacv-platform</artifactId> <version>1.3.3</version> </dependency> </dependencies> And by placing the source code above in src/main/java/Demo.java, we can use the following command to have everything first installed automatically and then executed by Maven: $ mvn compile exec:java -Dexec.mainClass=Demo Build Instructions If the binary files available above are not enough for your needs, you might need to rebuild them from the source code. To this end, the project files were created for: Maven 3.x http://maven.apache.org/download.html JavaCPP 1.3 https://github.com/bytedeco/javacpp JavaCPP Presets 1.3 https://github.com/bytedeco/javacpp-presets Once installed, simply call the usual mvn install command for JavaCPP, its Presets, and JavaCV. By default, no other dependencies than a C++ compiler for JavaCPP are required. Please refer to the comments inside the pom.xml files for further details. Project lead: Samuel Audet [samuel.audet at gmail.com](mailto:samuel.audet at gmail.com) Developer site: https://github.com/bytedeco/javacv Discussion group: http://groups.google.com/group/javacv

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