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ml: refactor non-virtual methods

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This commit is contained in:
berak
2018-04-24 12:11:59 +02:00
parent 4d7d630e92
commit fc5bba66af
4 changed files with 39 additions and 76 deletions
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modules/ml/include/opencv2/ml.hpp
+7 -7
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@@ -198,7 +198,7 @@ public:
CV_WRAP virtual Mat getTestSampleWeights() const = 0;
CV_WRAP virtual Mat getVarIdx() const = 0;
CV_WRAP virtual Mat getVarType() const = 0;
CV_WRAP Mat getVarSymbolFlags() const;
CV_WRAP virtual Mat getVarSymbolFlags() const = 0;
CV_WRAP virtual int getResponseType() const = 0;
CV_WRAP virtual Mat getTrainSampleIdx() const = 0;
CV_WRAP virtual Mat getTestSampleIdx() const = 0;
@@ -234,10 +234,10 @@ public:
CV_WRAP virtual void shuffleTrainTest() = 0;
/** @brief Returns matrix of test samples */
CV_WRAP Mat getTestSamples() const;
CV_WRAP virtual Mat getTestSamples() const = 0;
/** @brief Returns vector of symbolic names captured in loadFromCSV() */
CV_WRAP void getNames(std::vector<String>& names) const;
CV_WRAP virtual void getNames(std::vector<String>& names) const = 0;
CV_WRAP static Mat getSubVector(const Mat& vec, const Mat& idx);
@@ -727,7 +727,7 @@ public:
regression (SVM::EPS_SVR or SVM::NU_SVR). If it is SVM::ONE_CLASS, no optimization is made and
the usual %SVM with parameters specified in params is executed.
*/
CV_WRAP bool trainAuto(InputArray samples,
CV_WRAP virtual bool trainAuto(InputArray samples,
int layout,
InputArray responses,
int kFold = 10,
@@ -737,7 +737,7 @@ public:
Ptr<ParamGrid> nuGrid = SVM::getDefaultGridPtr(SVM::NU),
Ptr<ParamGrid> coeffGrid = SVM::getDefaultGridPtr(SVM::COEF),
Ptr<ParamGrid> degreeGrid = SVM::getDefaultGridPtr(SVM::DEGREE),
bool balanced=false);
bool balanced=false) = 0;
/** @brief Retrieves all the support vectors
@@ -752,7 +752,7 @@ public:
support vector, used for prediction, was derived from. They are returned in a floating-point
matrix, where the support vectors are stored as matrix rows.
*/
CV_WRAP Mat getUncompressedSupportVectors() const;
CV_WRAP virtual Mat getUncompressedSupportVectors() const = 0;
/** @brief Retrieves the decision function
@@ -1273,7 +1273,7 @@ public:
@param results Array where the result of the calculation will be written.
@param flags Flags for defining the type of RTrees.
*/
CV_WRAP void getVotes(InputArray samples, OutputArray results, int flags) const;
CV_WRAP virtual void getVotes(InputArray samples, OutputArray results, int flags) const = 0;
/** Creates the empty model.
Use StatModel::train to train the model, StatModel::train to create and train the model,