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replace Mats to Input/OutputArrays for Octave's public interface

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This commit is contained in:
marina.kolpakova 2013-01-09 17:07:24 +04:00
parent e7bab669fa
commit e47f58f4ce
2 changed files with 24 additions and 12 deletions
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12
modules/ml/include/opencv2/ml/ml.hpp
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@ -2171,15 +2171,17 @@ public:
};
Octave(cv::Rect boundingBox, int npositives, int nnegatives, int logScale, int shrinkage);
virtual bool train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth);
virtual void setRejectThresholds(OutputArray thresholds);
virtual void write( CvFileStorage* fs, string name) const;
virtual void write( cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const;
virtual ~Octave();
virtual bool train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth);
virtual float predict( const Mat& _sample, Mat& _votes, bool raw_mode, bool return_sum ) const;
virtual void setRejectThresholds(cv::Mat& thresholds);
virtual void write( CvFileStorage* fs, string name) const;
virtual float predict( InputArray _sample, InputArray _votes, bool raw_mode, bool return_sum ) const;
virtual void write( cv::FileStorage &fs, const FeaturePool* pool, const Mat& thresholds) const;
int logScale;

24
modules/ml/src/octave.cpp
View File

@ -167,7 +167,7 @@ bool cv::Octave::train( const cv::Mat& _trainData, const cv::Mat& _responses, co
update);
}
void cv::Octave::setRejectThresholds(cv::Mat& thresholds)
void cv::Octave::setRejectThresholds(cv::OutputArray _thresholds)
{
dprintf("set thresholds according to DBP strategy\n");
@ -190,7 +190,8 @@ void cv::Octave::setRejectThresholds(cv::Mat& thresholds)
}
int weaks = weak->total;
thresholds.create(1, weaks, CV_64FC1);
_thresholds.create(1, weaks, CV_64FC1);
cv::Mat& thresholds = _thresholds.getMatRef();
double* thptr = thresholds.ptr<double>(0);
cv::Mat traces(weaks, nsamples, CV_64FC1, cv::Scalar::all(FLT_MAX));
@ -346,12 +347,13 @@ void cv::Octave::traverse(const CvBoostTree* tree, cv::FileStorage& fs, int& nfe
fs << "}";
}
void cv::Octave::write( cv::FileStorage &fso, const FeaturePool* pool, const Mat& thresholds) const
void cv::Octave::write( cv::FileStorage &fso, const FeaturePool* pool, InputArray _thresholds) const
{
CV_Assert(!thresholds.empty());
CV_Assert(!_thresholds.empty());
cv::Mat used( 1, weak->total * (pow(2, params.max_depth) - 1), CV_32SC1);
int* usedPtr = used.ptr<int>(0);
int nfeatures = 0;
cv::Mat thresholds = _thresholds.getMat();
fso << "{"
<< "scale" << logScale
<< "weaks" << weak->total
@ -438,10 +440,18 @@ bool cv::Octave::train(const Dataset* dataset, const FeaturePool* pool, int weak
}
float cv::Octave::predict( const Mat& _sample, Mat& _votes, bool raw_mode, bool return_sum ) const
float cv::Octave::predict( cv::InputArray _sample, cv::InputArray _votes, bool raw_mode, bool return_sum ) const
{
CvMat sample = _sample, votes = _votes;
return CvBoost::predict(&sample, 0, (_votes.empty())? 0 : &votes, CV_WHOLE_SEQ, raw_mode, return_sum);
cv::Mat sample = _sample.getMat();
CvMat csample = sample;
if (_votes.empty())
return CvBoost::predict(&csample, 0, 0, CV_WHOLE_SEQ, raw_mode, return_sum);
else
{
cv::Mat votes = _votes.getMat();
CvMat cvotes = votes;
return CvBoost::predict(&csample, 0, &cvotes, CV_WHOLE_SEQ, raw_mode, return_sum);
}
}
float cv::Octave::predict( const Mat& _sample, const cv::Range range) const