安装JDK的时候报错java platform SE binary
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java7帮助文档
Java Platform Standard Edition 7 Documentation What's New Documentation Release Notes Tutorials and Training The Java Tutorials Java Training More Information Java SE 7 Names and Versions Java SE White Papers Documentation Accessibility Specifications Installation Instructions Supported Systems Configurations Java SE 7 and JDK 7 Compatibility JDK 7 Adoption Guide Troubleshooting Java SE About Test / Sample Applications and Code Resources Oracle Java SE Advanced and Oracle Java SE Suite Open JDK Bugs Database Downloads Java SE Downloads Community Forums Blogs User Groups Wikis Newsletters Events Other Technologies Java EE Java ME Java FX GlassFish NetBeans Oracle has two products that implement Java Platform Standard Edition (Java SE) 7: Java SE Development Kit (JDK) 7 and Java SE Runtime Environment (JRE) 7. JDK 7 is a superset of JRE 7, and contains everything that is in JRE 7, plus tools such as the compilers and debuggers necessary for developing applets and applications. JRE 7 provides the libraries, the Java Virtual Machine (JVM), and other components to run applets and applications written in the Java programming language. The following conceptual diagram illustrates Java component technologies: JDK Java Language Java Language ` Tools & Tool APIs java javac javadoc jar javap JPDA JConsole Java VisualVM Java DB Security Int'l RMI IDL Deploy Monitoring Troubleshoot Scripting JVM TI JRE RIAs Java Web Start Applet / Java Plug-in User Interface Toolkits AWT Swing Java 2D Accessibility Drag n Drop Input Methods Image I/O Print Service Sound Java SE API Integration Libraries IDL JDBC JNDI RMI RMI-IIOP Scripting Other Base Libraries Beans Int'l Support Input/Output JMX JNI Math Networking Override Mechanism Security Serialization Extension Mechanism XML JAXP lang and util Base Libraries lang and util Collections Concurrency Utilities JAR Logging Management Preferences API Ref Objects Reflection Regular Expressions Versioning Zip Instrumentation Java Virtual Machine Java HotSpot Client and Server VM Description of Java Conceptual Diagram What's New in Documentation Documentation is regularly updated to provide developers with in-depth information about new features in the Java platform. Some recent updates include: Swing The JLayer class has been added, which is a flexible and powerful decorator for Swing components; see How to Decorate Components with JLayer. The Nimbus Look and Feel has been moved from the com.sun.java.swing package to the javax.swing package; see the javax.swing.plaf.nimbus package. Mixing Heavyweight and Lightweight Components is easier to accomplish. Windows with transparency and non-rectangular shape are supported; see How to Create Translucent and Shaped Windows An HSV tab has been added to the JColorChooser class. Java I/O The java.nio.file package and its related package, java.nio.file.attribute, provide comprehensive support for file I/O and for accessing the file system; see File I/O (featuring NIO.2). NIO stands for non-blocking I/O. The directory <Java home>/sample/nio/chatserver/ contains samples that demonstrate the new APIs contained in the java.nio.file package. The directory <Java home>/demo/nio/zipfs/ contains samples that demonstrate the NIO.2 NFS (Network File System) file system. Networking The URLClassLoader.close method has been added; see Closing a URLClassLoader. The Sockets Direct Protocol (SDP) provides access to high performance network connections; see Understanding the Sockets Direct Protocol. Security A new native provider has been added that provides several ECC-based algorithms (ECDSA/ECDH); see Sun PKCS#11 Provider's Supported Algorithms in Java PKCS#11 Reference Guide. Weak cryptographic algorithms can now be disabled; see Appendix D: Disabling Cryptographic Algorithms in Java PKI Programmer's Guide and Disabled Cryptographic Algorithms in Java Secure Socket Extension (JSSE) Reference Guide. Various enhancements related to SSL/TLS have been added to Java Secure Socket Extension. Collections The TransferQueue interface has been added, which is a refinement of the BlockingQueue interface. The class LinkedTransferQueue implements the TransferQueue interface. Concurrency The fork/join framework, which is based on the ForkJoinPool class, is an implementation of the Executor interface. It is designed to efficiently run a large number of tasks using a pool of worker threads. A work-stealing technique is used to keep all the worker threads busy, to take full advantage of multiple processors. See Fork/Join in The Java Tutorials. The directory <Java home>/sample/forkjoin/ contains samples that demonstrate the fork/join framework. The ThreadLocalRandom class eliminates contention among threads using pseudo-random numbers; see Concurrent Random Numbers. The Phaser class is a new synchronization barrier, similar to CyclicBarrier. Rich Internet Applications (RIA) and Deployment The window of a dragged applet can be decorated with a default or custom title; see Requesting and Customizing Applet Decoration in Draggable Applets. The following enhancements have been made to the syntax of JNLP files; see JNLP File Syntax: The os attribute in the information and resources elements can now contain specific versions of Windows, such as Windows Vista or Windows 7. Applications can use the install attribute in the shortcut element to specify their desire to be installed. Installed applications are not removed when the Java Web Start cache is cleared, but can be explicitly removed using the Java Control Panel. Java Web Start applications can be deployed without specifying the codebase attribute; see Deploying Without Codebase A JNLP file can be embedded into an HTML page; see Embedding JNLP File in Applet Tag. You can check the status variable of the applet while it is loading to determine if the applet is ready to handle requests from JavaScript code; see Handling Initialization Status With Event Handlers. You now have control of the window decoration style and title of an applet launched from a shortcut or dragged out of the browser; see Requesting and Customizing Applet Decoration in Developing Draggable Applets. Java 2D A new XRender-based Java 2D rendering pipeline is supported for modern X11-based desktops, offering improved graphics performance; see the xrender flag in System Properties for Java 2D Technology. The JDK now enumerates and displays installed OpenType/CFF fonts through methods such as GraphicsEnvironment.getAvailableFontFamilyNames; these fonts are also recognized by the Font.createFont method. See Selecting a Font. The TextLayout class supports Tibetan script. libfontconfig, a font configuration API, is used to select fonts to use for the logical fonts for some implementations of Linux; see Fontconfig. Java XML This release contains Java API for XML Processing (JAXP) 1.4.5, supports Java Architecture for XML Binding (JAXB) 2.2.3, and supports Java API for XML Web Services (JAX-WS) 2.2.4. Internationalization Unicode 6.0.0 is supported; see Unicode in The Java Tutorials. The directory <Java home>/demo/jfc/Font2DTest/ contains samples that demonstrate Java support for Unicode 6.0. Java SE 7 can accommodate new currencies that are identified by their ISO 4217 codes; see the Currency class. java.lang Package Potential deadlocks were eliminated for multithreaded, non-hierarchically delegating custom class loaders; see Multithreaded Custom Class Loaders in Java SE 7. Java Programming Language The following enhancements have been added to the Java language: Binary Literals Underscores in Numeric Literals Strings in switch Statements Type Inference for Generic Instance Creation Improved Compiler Warnings and Errors When Using Non-Reifiable Formal Parameters with Varargs Methods The try-with-resources Statement Catching Multiple Exception Types and Rethrowing Exceptions with Improved Type Checking Java Virtual Machine Java Virtual Machine Support for Non-Java Languages: Java SE 7 introduces a new JVM instruction that simplifies the implementation of dynamically typed programming languages on the JVM. Garbage-First Collector is a server-style garbage collector that replaces the Concurrent Mark-Sweep Collector (CMS). 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javacv-platform-1.3.3-src
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: <project> <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> </project> 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
微信dat工具.rar
很小的工具,转换不受限制,免费.转换微信dat的小工具,需要安装java,打开方式使用Java(TM)Platform SE binary
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