@DatasetDescription( name = "Tim Cootes's sample appearance modelling data", description = "The sample data (images, points and connections) that come with Tim Cootes's am_tools software.",
@Experiment( author = "Jonathon Hare", dateCreated = "2012-07-26", RunnableExperiment @IndependentVariable protected CrossValidator<GroupedDataset<PERSON, ListDataset<FACE>, FACE>> crossValidator; @IndependentVariable protected GroupedDataset<PERSON, ? extends ListDataset<IMAGE>, IMAGE> dataset; @IndependentVariable protected FaceDetector<FACE, IMAGE> faceDetector; @IndependentVariable protected FaceRecogniserProvider<FACE, PERSON> engine; @DependentVariable protected AggregatedCMResult<PERSON> result;
@Experiment( author = "David Dupplaw <dpd@ecs.soton.ac.uk>", dateCreated = "2013-03-08", @IndependentVariable private final SpeechDetector speechDetector; @IndependentVariable private MapBackedDataset<String, ListDataset<DoubleFV>, DoubleFV> dataset = null; @IndependentVariable private AggregatedCMResult<String> result;
@Time(identifier = "Finish Experiment") protected static void runFinish(RunnableExperiment experiment, ExperimentContext context) { experiment.finish(context); } }
@Override public void transform(String className, CtClass ctclz) throws Exception { final CtMethod[] methods = ctclz.getDeclaredMethods(); for (final CtMethod m : methods) { final Time ann = (Time) m.getAnnotation(Time.class); if (ann != null) { String timerName = ann.identifier(); if (timerName == null || timerName.length() == 0) timerName = String.format("%s#%s", className, m.getLongName()); addTimingInterceptor(ctclz, m, timerName); } } }
@DatasetDescription( name = "Tim Cootes's sample appearance modelling data", description = "The sample data (images, points and connections) that come with Tim Cootes's am_tools software.",
@Time(identifier = "Finish Experiment") protected static void runFinish(RunnableExperiment experiment, ExperimentContext context) { experiment.finish(context); } }
@Experiment( author = "David Dupplaw <dpd@ecs.soton.ac.uk>", dateCreated = "2013-03-08", @IndependentVariable private final SpeechDetector speechDetector; @IndependentVariable private MapBackedDataset<String, ListDataset<DoubleFV>, DoubleFV> dataset = null; @IndependentVariable private AggregatedCMResult<String> result;
@Override public void transform(String className, CtClass ctclz) throws Exception { final CtMethod[] methods = ctclz.getDeclaredMethods(); for (final CtMethod m : methods) { final Time ann = (Time) m.getAnnotation(Time.class); if (ann != null) { String timerName = ann.identifier(); if (timerName == null || timerName.length() == 0) timerName = String.format("%s#%s", className, m.getLongName()); addTimingInterceptor(ctclz, m, timerName); } } }
@DatasetDescription( name = "INRIAPerson", description = "Images of upright people in images and video. " +
@Time(identifier = "Setup Experiment") protected static void runSetup(RunnableExperiment experiment) { experiment.setup(); }
@DatasetDescription( name = "INRIAPerson", description = "Images of upright people in images and video. " +
@Time(identifier = "Perform Experiment") protected static void runPerform(RunnableExperiment experiment) { experiment.perform(); }
@DatasetDescription( name = "Wine Data Set", description = "" +
@Time(identifier = "Setup Experiment") protected static void runSetup(RunnableExperiment experiment) { experiment.setup(); }
@DatasetDescription( name = "The IMM Face Database", description = "A dataset consisting of 240 annotated monocular " +
@Time(identifier = "Perform Experiment") protected static void runPerform(RunnableExperiment experiment) { experiment.perform(); }
@DatasetDescription( name = "The IMM Face Database", description = "A dataset consisting of 240 annotated monocular " +
@Time(identifier = "Train and Evaluate recogniser") @Override public CMResult<PERSON> evaluate( GroupedDataset<PERSON, ListDataset<FACE>, FACE> training, GroupedDataset<PERSON, ListDataset<FACE>, FACE> validation) { final FaceRecogniser<FACE, PERSON> rec = engine.create(training); final ClassificationEvaluator<CMResult<PERSON>, PERSON, FACE> eval = new ClassificationEvaluator<CMResult<PERSON>, PERSON, FACE>( rec, validation, new CMAnalyser<FACE, PERSON>(CMAnalyser.Strategy.SINGLE) ); return eval.analyse(eval.evaluate()); } });
@DatasetDescription( name = "Our Database of Faces/The ORL Face Database/The AT&T Face database", description = "Our Database of Faces, (formerly 'The ORL Database of Faces'), "