potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-29 15:23:05 +04:00
Code Packages Releases Wiki Activity

ml: apply CV_OVERRIDE/CV_FINAL

Browse Source
This commit is contained in:
Alexander Alekhin
2018-03-15 16:16:58 +03:00
parent 3314966acb
commit 4d0dd3e509
13 changed files with 370 additions and 301 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/ml/src/knearest.cpp
+28 -25
View File
@@ -134,11 +134,11 @@ public:
Mat responses;
};
class BruteForceImpl : public Impl
class BruteForceImpl CV_FINAL : public Impl
{
public:
String getModelName() const { return NAME_BRUTE_FORCE; }
int getType() const { return ml::KNearest::BRUTE_FORCE; }
String getModelName() const CV_OVERRIDE { return NAME_BRUTE_FORCE; }
int getType() const CV_OVERRIDE { return ml::KNearest::BRUTE_FORCE; }
void findNearestCore( const Mat& _samples, int k0, const Range& range,
Mat* results, Mat* neighbor_responses,
@@ -294,7 +294,7 @@ public:
presult = _presult;
}
void operator()( const Range& range ) const
void operator()(const Range& range) const CV_OVERRIDE
{
int delta = std::min(range.end - range.start, 256);
for( int start = range.start; start < range.end; start += delta )
@@ -316,7 +316,7 @@ public:
float findNearest( InputArray _samples, int k,
OutputArray _results,
OutputArray _neighborResponses,
OutputArray _dists ) const
OutputArray _dists ) const CV_OVERRIDE
{
float result = 0.f;
CV_Assert( 0 < k );
@@ -358,13 +358,13 @@ public:
};
class KDTreeImpl : public Impl
class KDTreeImpl CV_FINAL : public Impl
{
public:
String getModelName() const { return NAME_KDTREE; }
int getType() const { return ml::KNearest::KDTREE; }
String getModelName() const CV_OVERRIDE { return NAME_KDTREE; }
int getType() const CV_OVERRIDE { return ml::KNearest::KDTREE; }
void doTrain(InputArray points)
void doTrain(InputArray points) CV_OVERRIDE
{
tr.build(points);
}
@@ -372,7 +372,7 @@ public:
float findNearest( InputArray _samples, int k,
OutputArray _results,
OutputArray _neighborResponses,
OutputArray _dists ) const
OutputArray _dists ) const CV_OVERRIDE
{
float result = 0.f;
CV_Assert( 0 < k );
@@ -432,18 +432,21 @@ public:
//================================================================
class KNearestImpl : public KNearest
class KNearestImpl CV_FINAL : public KNearest
{
CV_IMPL_PROPERTY(int, DefaultK, impl->defaultK)
CV_IMPL_PROPERTY(bool, IsClassifier, impl->isclassifier)
CV_IMPL_PROPERTY(int, Emax, impl->Emax)
inline int getDefaultK() const CV_OVERRIDE { return impl->defaultK; }
inline void setDefaultK(int val) CV_OVERRIDE { impl->defaultK = val; }
inline bool getIsClassifier() const CV_OVERRIDE { return impl->isclassifier; }
inline void setIsClassifier(bool val) CV_OVERRIDE { impl->isclassifier = val; }
inline int getEmax() const CV_OVERRIDE { return impl->Emax; }
inline void setEmax(int val) CV_OVERRIDE { impl->Emax = val; }
public:
int getAlgorithmType() const
int getAlgorithmType() const CV_OVERRIDE
{
return impl->getType();
}
void setAlgorithmType(int val)
void setAlgorithmType(int val) CV_OVERRIDE
{
if (val != BRUTE_FORCE && val != KDTREE)
val = BRUTE_FORCE;
@@ -459,18 +462,18 @@ public:
{
}
bool isClassifier() const { return impl->isclassifier; }
bool isTrained() const { return !impl->samples.empty(); }
bool isClassifier() const CV_OVERRIDE { return impl->isclassifier; }
bool isTrained() const CV_OVERRIDE { return !impl->samples.empty(); }
int getVarCount() const { return impl->samples.cols; }
int getVarCount() const CV_OVERRIDE { return impl->samples.cols; }
void write( FileStorage& fs ) const
void write( FileStorage& fs ) const CV_OVERRIDE
{
writeFormat(fs);
impl->write(fs);
}
void read( const FileNode& fn )
void read( const FileNode& fn ) CV_OVERRIDE
{
int algorithmType = BRUTE_FORCE;
if (fn.name() == NAME_KDTREE)
@@ -482,22 +485,22 @@ public:
float findNearest( InputArray samples, int k,
OutputArray results,
OutputArray neighborResponses=noArray(),
OutputArray dist=noArray() ) const
OutputArray dist=noArray() ) const CV_OVERRIDE
{
return impl->findNearest(samples, k, results, neighborResponses, dist);
}
float predict(InputArray inputs, OutputArray outputs, int) const
float predict(InputArray inputs, OutputArray outputs, int) const CV_OVERRIDE
{
return impl->findNearest( inputs, impl->defaultK, outputs, noArray(), noArray() );
}
bool train( const Ptr<TrainData>& data, int flags )
bool train( const Ptr<TrainData>& data, int flags ) CV_OVERRIDE
{
return impl->train(data, flags);
}
String getDefaultName() const { return impl->getModelName(); }
String getDefaultName() const CV_OVERRIDE { return impl->getModelName(); }
protected:
void initImpl(int algorithmType)