Java Code Examples for org.bytedeco.javacpp.Loader#load()

public static void tryLoad() throws Exception {
    if (loadingException != null) {
        throw loadingException;
    } else {
        try {
            Loader.load(org.bytedeco.javacpp.avutil.class);
            Loader.load(org.bytedeco.javacpp.avcodec.class);
            Loader.load(org.bytedeco.javacpp.avformat.class);
            Loader.load(org.bytedeco.javacpp.postproc.class);
            Loader.load(org.bytedeco.javacpp.swresample.class);
            Loader.load(org.bytedeco.javacpp.swscale.class);
            Loader.load(org.bytedeco.javacpp.avfilter.class);

            av_register_all();
            avfilter_register_all();
        } catch (Throwable t) {
            if (t instanceof Exception) {
                throw loadingException = (Exception)t;
            } else {
                throw loadingException = new Exception("Failed to load " + FFmpegFrameRecorder.class, t);
            }
        }
    }
}
 

public static void tryLoad() throws Exception {
    if (loadingException != null) {
        throw loadingException;
    } else {
        try {
            Loader.load(org.bytedeco.javacpp.avutil.class);
            Loader.load(org.bytedeco.javacpp.swresample.class);
            Loader.load(org.bytedeco.javacpp.avcodec.class);
            Loader.load(org.bytedeco.javacpp.avformat.class);
            Loader.load(org.bytedeco.javacpp.swscale.class);

            /* initialize libavcodec, and register all codecs and formats */
            av_register_all();
            avformat_network_init();
        } catch (Throwable t) {
            if (t instanceof Exception) {
                throw loadingException = (Exception)t;
            } else {
                throw loadingException = new Exception("Failed to load " + FFmpegFrameRecorder.class, t);
            }
        }
    }
}
 

public void run() {
	Loader.load(opencv_objdetect.class);

	try {
		grabber = FFmpegFrameGrabber.createDefault(url);
		grabber.start();
	} catch (Exception e) {
		try {
			grabber.restart();
		} catch (Exception e1) {
		}
	}
	while (true) {
		// try {
		getBufferedImage();
		// sleep(1);
		// } catch (InterruptedException e) {
		// e.printStackTrace();
		// }
	}
}
 

public void setClassifierFullBody(String name) {

		try {

			setClassiferName(name);
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierFullBody = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

@Override
public boolean canRun() {
    int[] count = { 0 };
    org.bytedeco.cuda.global.cudart.cudaGetDeviceCount(count);
    if (count[0] <= 0) {
        throw new RuntimeException("No CUDA devices were found in system");
    }
    Loader.load(org.bytedeco.cuda.global.cublas.class);

    return true;
}
 

org.opencv.core.Mat makeRandomOrgOpenCvCoreMatImage(int height, int width, int channels) {
    Mat img = makeRandomImage(height, width, channels);

    Loader.load(org.bytedeco.opencv.opencv_java.class);
    OpenCVFrameConverter.ToOrgOpenCvCoreMat c = new OpenCVFrameConverter.ToOrgOpenCvCoreMat();

    return c.convert(c.convert(img));
}
 

@Override
public boolean canRun() {
    int[] count = { 0 };
    cuda.cudaGetDeviceCount(count);
    if (count[0] <= 0) {
        throw new RuntimeException("No CUDA devices were found in system");
    }
    Loader.load(cublas.class);
    return true;
}
 

public void setClassifierUpperBody(String name) {

		try {

			classiferName = name;
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierUpperBody = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public void setClassifierEyeGlass(String name) {

		try {

			setClassiferName(name);
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierEyeglass = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public void setClassifierSideFace(String name) {

		try {

			classiferName = name;
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierSideFace = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public void setClassifierSmile(String name) {

		try {

			setClassiferName(name);
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierSmile = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public void setClassifierEye(String name) {

		try {

			classiferName = name;
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifierEye = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public void setClassifier(String name) {

		try {

			setClassiferName(name);
			classifierFile = Loader.extractResource(classiferName, null, "classifier", ".xml");

			if (classifierFile == null || classifierFile.length() <= 0) {
				throw new IOException("Could not extract \"" + classiferName + "\" from Java resources.");
			}

			// Preload the opencv_objdetect module to work around a known bug.
			Loader.load(opencv_objdetect.class);
			classifier = new CvHaarClassifierCascade(cvLoad(classifierFile.getAbsolutePath()));
			classifierFile.delete();
			if (classifier.isNull()) {
				throw new IOException("Could not load the classifier file.");
			}

		} catch (Exception e) {
			if (exception == null) {
				exception = e;

			}
		}

	}
 

public static void tryLoad() throws Exception {
    if (loadingException != null) {
        throw loadingException;
    } else {
        try {
            Loader.load(org.bytedeco.javacpp.avutil.class);
            Loader.load(org.bytedeco.javacpp.swresample.class);
            Loader.load(org.bytedeco.javacpp.avcodec.class);
            Loader.load(org.bytedeco.javacpp.avformat.class);
            Loader.load(org.bytedeco.javacpp.swscale.class);

            /* initialize libavcodec, and register all codecs and formats */
            av_jni_set_java_vm(Loader.getJavaVM(), null);
            avcodec_register_all();
            av_register_all();
            avformat_network_init();

            Loader.load(org.bytedeco.javacpp.avdevice.class);
            avdevice_register_all();
        } catch (Throwable t) {
            if (t instanceof Exception) {
                throw loadingException = (Exception)t;
            } else {
                throw loadingException = new Exception("Failed to load " + FFmpegFrameRecorder.class, t);
            }
        }
    }
}
 

public static void main(String[] args) {

        // Learning constants defined in the DeepMind Nature paper
        // (http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html)
        int experienceMemoryLength = 1000000;
        int maxHistoryLength = 4;
        int staleUpdateFreq = 10000;
        double gamma = 0.99;
        int frameSkip = 4;
        int updateFreq = 4;
        double rewardClip = 1.0;
        float gradientClip = 1.0f;
        double epsilonStart = 1;
        double epsilonEnd = 0.1;
        int epsilonAnnealDuration = 1000000;
        int replayStartSize = 50000;
        int noopMax = 30;
        int totalTrainingSteps = 50000000;
        double testEpsilon = 0.05;

        // Testing and recording constants
        int testInterval = 250000;
        int totalTestSteps = 125000;
        int maxEpisodeSteps = 100000;
        int snapshotInterval = 1000000;
        String snapshotPrefix = "snapshots/experiment1";
        String resultsDirectory = "results/experiment1";

        // ALE Paths
        // TODO: Set to appropriate paths for your machine
        String alePath = "/path/to/atari/executable";
        String romPath = "/path/to/atari/rom/file";

        // Caffe solver file
        String solverFile = "example_models/atari_dqn_solver.prototxt";

        // Load Caffe
        Loader.load(Caffe.class);

        // Create the domain
        ALEDomainGenerator domGen = new ALEDomainGenerator(ALEDomainGenerator.saActionSet());
        SADomain domain = domGen.generateDomain();

        // Create the ALEEnvironment and visualizer
        ALEEnvironment env = new ALEEnvironment(alePath, romPath, frameSkip, PoolingMethod.POOLING_METHOD_MAX);
        env.setRandomNoopMax(noopMax);
        ALEVisualExplorer exp = new ALEVisualExplorer(domain, env, ALEVisualizer.create());
        exp.initGUI();
        exp.startLiveStatePolling(1000/60);

        // Setup the ActionSet from the ALEDomain to use the ALEActions
        ActionSet actionSet = new ActionSet(domain);

        // Setup the training and test memory
        FrameExperienceMemory trainingExperienceMemory =
                new FrameExperienceMemory(experienceMemoryLength, maxHistoryLength, new ALEPreProcessor(), actionSet);
        // The size of the test memory is arbitrary but should be significantly greater than 1 to minimize copying
        FrameExperienceMemory testExperienceMemory =
                new FrameExperienceMemory(10000, maxHistoryLength, new ALEPreProcessor(), actionSet);


        // Initialize the DQN with the solver file.
        // NOTE: this Caffe architecture is made for 3 actions (the number of actions in Pong)
        DQN dqn = new DQN(solverFile, actionSet, trainingExperienceMemory, gamma);
        dqn.setRewardClip(rewardClip);
        dqn.setGradientClip(gradientClip);

        // Create the policies
        SolverDerivedPolicy learningPolicy =
                new AnnealedEpsilonGreedy(dqn, epsilonStart, epsilonEnd, epsilonAnnealDuration);
        SolverDerivedPolicy testPolicy = new EpsilonGreedy(dqn, testEpsilon);

        // Setup the learner
        DeepQLearner deepQLearner = new DeepQLearner(domain, gamma, replayStartSize, learningPolicy, dqn, trainingExperienceMemory);
        deepQLearner.setExperienceReplay(trainingExperienceMemory, dqn.batchSize);
        deepQLearner.useStaleTarget(staleUpdateFreq);
        deepQLearner.setUpdateFreq(updateFreq);

        // Setup the tester
        DeepQTester tester = new DeepQTester(testPolicy, testExperienceMemory, testExperienceMemory);

        // Setup helper
        TrainingHelper helper =
                new AtariDQN(deepQLearner, tester, dqn, actionSet, env, trainingExperienceMemory, testExperienceMemory);
        helper.setTotalTrainingSteps(totalTrainingSteps);
        helper.setTestInterval(testInterval);
        helper.setTotalTestSteps(totalTestSteps);
        helper.setMaxEpisodeSteps(maxEpisodeSteps);
        helper.enableSnapshots(snapshotPrefix, snapshotInterval);
        helper.recordResultsTo(resultsDirectory);
        //helper.verbose = true;

        // Uncomment this line to load learning state if resuming
        //helper.loadLearningState(snapshotDirectory);

        // Run helper
        helper.run();
    }
 

public static void main(String args[]) {

        // Learning constants
        double gamma = 0.99;
        int replayStartSize = 50000;
        int memorySize = 1000000;
        double epsilonStart = 1;
        double epsilonEnd = 0.1;
        double testEpsilon = 0.05;
        int epsilonAnnealDuration = 1000000;
        int staleUpdateFreq = 10000;

        // Caffe solver file
        String solverFile = "example_models/grid_world_dqn_solver.prototxt";

        // Load Caffe
        Loader.load(caffe.Caffe.class);

        // Setup the network
        GridWorldDQN gridWorldDQN = new GridWorldDQN(solverFile, gamma);

        // Create the policies
        SolverDerivedPolicy learningPolicy =
                new AnnealedEpsilonGreedy(epsilonStart, epsilonEnd, epsilonAnnealDuration);
        SolverDerivedPolicy testPolicy = new EpsilonGreedy(testEpsilon);

        // Setup the learner
        DeepQLearner deepQLearner =
                new DeepQLearner(gridWorldDQN.domain, gamma, replayStartSize, learningPolicy, gridWorldDQN.dqn);
        deepQLearner.setExperienceReplay(new FixedSizeMemory(memorySize), gridWorldDQN.dqn.batchSize);
        deepQLearner.useStaleTarget(staleUpdateFreq);

        // Setup the tester
        Tester tester = new SimpleTester(testPolicy);

        // Set the QProvider for the policies
        learningPolicy.setSolver(deepQLearner);
        testPolicy.setSolver(deepQLearner);

        // Setup the visualizer
        VisualExplorer exp = new VisualExplorer(
                gridWorldDQN.domain, gridWorldDQN.env, GridWorldVisualizer.getVisualizer(gridWorldDQN.gwdg.getMap()));
        exp.initGUI();
        exp.startLiveStatePolling(33);

        // Setup helper
        TrainingHelper helper = new TrainingHelper(
                deepQLearner, tester, gridWorldDQN.dqn, actionSet, gridWorldDQN.env);
        helper.setTotalTrainingSteps(50000000);
        helper.setTestInterval(500000);
        helper.setTotalTestSteps(125000);
        helper.setMaxEpisodeSteps(10000);

        // Run helper
        helper.run();
    }
 

@Before
public void setup() {
    Loader.load(opencv_core.class);
}
 

/**
 * 转流器
 * 
 * @param inputFile
 * @param outputFile
 * @throws Exception
 * @throws org.bytedeco.javacv.FrameRecorder.Exception
 * @throws InterruptedException
 */
public static void recordPush(String inputFile, int v_rs) throws Exception, org.bytedeco.javacv.FrameRecorder.Exception, InterruptedException {
	Loader.load(opencv_objdetect.class);
	long startTime = 0;
	FrameGrabber grabber = FFmpegFrameGrabber.createDefault(inputFile);
	try {
		grabber.start();
	} catch (Exception e) {
		try {
			grabber.restart();
		} catch (Exception e1) {
			throw e;
		}
	}

	OpenCVFrameConverter.ToIplImage converter = new OpenCVFrameConverter.ToIplImage();
	Frame grabframe = grabber.grab();
	IplImage grabbedImage = null;
	if (grabframe != null) {
		System.out.println("取到第一帧");
		grabbedImage = converter.convert(grabframe);
	} else {
		System.out.println("没有取到第一帧");
	}

	System.out.println("开始推流");
	CanvasFrame frame = new CanvasFrame("camera", CanvasFrame.getDefaultGamma() / grabber.getGamma());
	frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
	frame.setAlwaysOnTop(true);
	while (frame.isVisible() && (grabframe = grabber.grab()) != null) {
		System.out.println("推流...");
		frame.showImage(grabframe);
		grabbedImage = converter.convert(grabframe);
		Frame rotatedFrame = converter.convert(grabbedImage);

		if (startTime == 0) {
			startTime = System.currentTimeMillis();
		}

		Thread.sleep(40);
	}
	frame.dispose();

	grabber.stop();
	System.exit(2);
}