kmeans.cpp
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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
* Copyright 2012 The MITRE Corporation *
* *
* Licensed under the Apache License, Version 2.0 (the "License"); *
* you may not use this file except in compliance with the License. *
* You may obtain a copy of the License at *
* *
* http://www.apache.org/licenses/LICENSE-2.0 *
* *
* Unless required by applicable law or agreed to in writing, software *
* distributed under the License is distributed on an "AS IS" BASIS, *
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. *
* See the License for the specific language governing permissions and *
* limitations under the License. *
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
#include <opencv2/flann/flann.hpp>
#include <openbr/plugins/openbr_internal.h>
#include <openbr/core/opencvutils.h>
using namespace cv;
namespace br
{
/*!
* \ingroup transforms
* \brief Wraps OpenCV kmeans and flann.
* \author Josh Klontz \cite jklontz
*/
class KMeansTransform : public Transform
{
Q_OBJECT
Q_PROPERTY(int kTrain READ get_kTrain WRITE set_kTrain RESET reset_kTrain STORED false)
Q_PROPERTY(int kSearch READ get_kSearch WRITE set_kSearch RESET reset_kSearch STORED false)
BR_PROPERTY(int, kTrain, 256)
BR_PROPERTY(int, kSearch, 1)
Mat centers;
mutable QScopedPointer<flann::Index> index;
mutable QMutex mutex;
void reindex()
{
index.reset(new flann::Index(centers, flann::LinearIndexParams()));
}
void train(const TemplateList &data)
{
Mat bestLabels;
const double compactness = kmeans(OpenCVUtils::toMatByRow(data.data()), kTrain, bestLabels, TermCriteria(TermCriteria::MAX_ITER, 10, 0), 3, KMEANS_PP_CENTERS, centers);
qDebug("KMeans compactness = %f", compactness);
reindex();
}
void project(const Template &src, Template &dst) const
{
QMutexLocker locker(&mutex);
Mat dists, indicies;
index->knnSearch(src, indicies, dists, kSearch);
dst = indicies.reshape(1, 1);
}
void load(QDataStream &stream)
{
stream >> centers;
reindex();
}
void store(QDataStream &stream) const
{
stream << centers;
}
};
BR_REGISTER(Transform, KMeansTransform)
} // namespace br
#include "cluster/kmeans.moc"