unit.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 <openbr/plugins/openbr_internal.h>
namespace br
{
/*!
* \ingroup distances
* \brief Linear normalizes of a distance so the mean impostor score is 0 and the mean genuine score is 1.
* \author Josh Klontz \cite jklontz
*/
class UnitDistance : public Distance
{
Q_OBJECT
Q_PROPERTY(br::Distance *distance READ get_distance WRITE set_distance RESET reset_distance)
Q_PROPERTY(float a READ get_a WRITE set_a RESET reset_a)
Q_PROPERTY(float b READ get_b WRITE set_b RESET reset_b)
Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
BR_PROPERTY(br::Distance*, distance, make("Dist(L2)"))
BR_PROPERTY(float, a, 1)
BR_PROPERTY(float, b, 0)
BR_PROPERTY(QString, inputVariable, "Label")
void train(const TemplateList &templates)
{
const TemplateList samples = templates.mid(0, 2000);
const QList<int> sampleLabels = samples.indexProperty(inputVariable);
QScopedPointer<MatrixOutput> matrixOutput(MatrixOutput::make(FileList(samples.size()), FileList(samples.size())));
Distance::compare(samples, samples, matrixOutput.data());
double genuineAccumulator, impostorAccumulator;
int genuineCount, impostorCount;
genuineAccumulator = impostorAccumulator = genuineCount = impostorCount = 0;
for (int i=0; i<samples.size(); i++) {
for (int j=0; j<i; j++) {
const float val = matrixOutput.data()->data.at<float>(i, j);
if (sampleLabels[i] == sampleLabels[j]) {
genuineAccumulator += val;
genuineCount++;
} else {
impostorAccumulator += val;
impostorCount++;
}
}
}
if (genuineCount == 0) { qWarning("No genuine matches."); return; }
if (impostorCount == 0) { qWarning("No impostor matches."); return; }
double genuineMean = genuineAccumulator / genuineCount;
double impostorMean = impostorAccumulator / impostorCount;
if (genuineMean == impostorMean) { qWarning("Genuines and impostors are indistinguishable."); return; }
a = 1.0/(genuineMean-impostorMean);
b = impostorMean;
qDebug("a = %f, b = %f", a, b);
}
float compare(const Template &target, const Template &query) const
{
return a * (distance->compare(target, query) - b);
}
};
BR_REGISTER(Distance, UnitDistance)
} // namespace br
#include "distance/unit.moc"