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Deleted functions makeTrainData() and makeTestData() in test_svmsgd.cpp.

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Added function makeData() in test_svmsgd.cpp.
This commit is contained in:
Marina Noskova
2016-02-25 16:57:03 +03:00
parent 74c87a26a5
commit d484893839
3 changed files with 33 additions and 48 deletions
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modules/ml/src/svmsgd.cpp
+7 -5
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@@ -142,6 +142,7 @@ void SVMSGDImpl::normalizeSamples(Mat &samples, Mat &average, float &multiplier)
int samplesCount = samples.rows;
average = Mat(1, featuresCount, samples.type());
CV_Assert(average.type() == CV_32FC1);
for (int featureIndex = 0; featureIndex < featuresCount; featureIndex++)
{
average.at<float>(featureIndex) = static_cast<float>(mean(samples.col(featureIndex))[0]);
@@ -170,11 +171,11 @@ void SVMSGDImpl::makeExtendedTrainSamples(const Mat &trainSamples, Mat &extended
cv::hconcat(normalizedTrainSamples, onesCol, extendedTrainSamples);
}
void SVMSGDImpl::updateWeights(InputArray _sample, bool firstClass, float stepSize, Mat& weights)
void SVMSGDImpl::updateWeights(InputArray _sample, bool positive, float stepSize, Mat& weights)
{
Mat sample = _sample.getMat();
int response = firstClass ? 1 : -1; // ensure that trainResponses are -1 or 1
int response = positive ? 1 : -1; // ensure that trainResponses are -1 or 1
if ( sample.dot(weights) * response > 1)
{
@@ -197,6 +198,7 @@ float SVMSGDImpl::calcShift(InputArray _samples, InputArray _responses) const
Mat trainResponses = _responses.getMat();
CV_Assert(trainResponses.type() == CV_32FC1);
for (int samplesIndex = 0; samplesIndex < trainSamplesCount; samplesIndex++)
{
Mat currentSample = trainSamples.row(samplesIndex);
@@ -261,7 +263,7 @@ bool SVMSGDImpl::train(const Ptr<TrainData>& data, int)
RNG rng(0);
CV_Assert (params.termCrit.type & TermCriteria::COUNT || params.termCrit.type & TermCriteria::EPS);
CV_Assert ((params.termCrit.type & TermCriteria::COUNT || params.termCrit.type & TermCriteria::EPS) && (trainResponses.type() == CV_32FC1));
int maxCount = (params.termCrit.type & TermCriteria::COUNT) ? params.termCrit.maxCount : INT_MAX;
double epsilon = (params.termCrit.type & TermCriteria::EPS) ? params.termCrit.epsilon : 0;
@@ -300,7 +302,7 @@ bool SVMSGDImpl::train(const Ptr<TrainData>& data, int)
weights_ = extendedWeights(roi);
weights_ *= multiplier;
CV_Assert(params.marginType == SOFT_MARGIN || params.marginType == HARD_MARGIN);
CV_Assert((params.marginType == SOFT_MARGIN || params.marginType == HARD_MARGIN) && (extendedWeights.type() == CV_32FC1));
if (params.marginType == SOFT_MARGIN)
{
@@ -332,7 +334,7 @@ float SVMSGDImpl::predict( InputArray _samples, OutputArray _results, int ) cons
else
{
CV_Assert( nSamples == 1 );
results = Mat(1, 1, CV_32F, &result);
results = Mat(1, 1, CV_32FC1, &result);
}
for (int sampleIndex = 0; sampleIndex < nSamples; sampleIndex++)