| /external/opencv3/modules/features2d/test/ocl/ |
| test_brute_force_matcher.cpp | 67 Mat query, train; local
75 queryDescCount = 300; // must be even number because we split train data in some cases in two
86 // Generate train decriptors as follows:
87 // copy each query descriptor to train set countFactor times
108 trainBuf.convertTo(train, CV_32F);
110 train.copyTo(utrain);
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| /external/opencv3/modules/java/src/ |
| ml+StatModel.java | 81 // C++: bool train(Ptr_TrainData trainData, int flags = 0)
88 // C++: bool train(Mat samples, int layout, Mat responses)
91 //javadoc: StatModel::train(samples, layout, responses)
92 public boolean train(Mat samples, int layout, Mat responses) method in class:StatModel
150 // C++: bool train(Mat samples, int layout, Mat responses)
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| features2d+DescriptorMatcher.java | 102 // C++: void train()
105 //javadoc: javaDescriptorMatcher::train()
106 public void train() method in class:DescriptorMatcher
351 // C++: void train()
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| /external/opencv3/samples/python2/ |
| letter_recog.py | 4 The sample demonstrates how to train Random Trees classifier
63 def train(self, samples, responses): member in class:RTrees
68 self.model.train(samples, cv2.CV_ROW_SAMPLE, responses, varType = var_types, params = params)
78 def train(self, samples, responses): member in class:KNearest
79 self.model.train(samples, responses)
90 def train(self, samples, responses): member in class:Boost
97 self.model.train(new_samples, cv2.CV_ROW_SAMPLE, new_responses, varType = var_types, params=params)
110 def train(self, samples, responses): member in class:SVM
114 self.model.train(samples, responses, params = params)
124 def train(self, samples, responses) member in class:MLP
[all...] |
| digits.py | 79 def train(self, samples, responses): member in class:KNearest
81 self.model.train(samples, cv2.ml.ROW_SAMPLE, responses)
95 def train(self, samples, responses): member in class:SVM
97 self.model.train(samples, cv2.ml.ROW_SAMPLE, responses)
172 model.train(samples_train, labels_train)
178 model.train(samples_train, labels_train)
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| /external/opencv3/apps/traincascade/ |
| cascadeclassifier.cpp | 129 bool CvCascadeClassifier::train( const string _cascadeDirName, function in class:CvCascadeClassifier
211 cout << "Train dataset for temp stage can not be filled. "
228 bool isStageTrained = tempStage->train( featureEvaluator,
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| /external/opencv3/modules/ml/src/ |
| inner_functions.cpp | 57 bool StatModel::train( const Ptr<TrainData>&, int ) function in class:cv::ml::StatModel
63 bool StatModel::train( InputArray samples, int layout, InputArray responses ) function in class:cv::ml::StatModel
65 return train(TrainData::create(samples, layout, responses));
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| boost.cpp | 185 bool train( const Ptr<TrainData>& trainData, int flags ) function in class:cv::ml::DTreesImplForBoost
470 bool train( const Ptr<TrainData>& trainData, int flags ) function in class:cv::BoostImpl
472 return impl.train(trainData, flags);
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| lr.cpp | 98 virtual bool train( const Ptr<TrainData>& trainData, int=0 );
129 bool LogisticRegressionImpl::train(const Ptr<TrainData>& trainData, int) function in class:cv::ml::LogisticRegressionImpl
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| rtrees.cpp | 126 bool train( const Ptr<TrainData>& trainData, int flags ) function in class:cv::ml::DTreesImplForRTrees
380 bool train( const Ptr<TrainData>& trainData, int flags ) function in class:cv::ml::RTreesImpl
382 return impl.train(trainData, flags);
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| em.cpp | 112 bool train(const Ptr<TrainData>& data, int) function in class:cv::ml::EMImpl
478 // Precompute the empty initial train data in the cases of START_E_STEP and START_AUTO_STEP
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| knearest.cpp | 74 bool train( const Ptr<TrainData>& data, int flags ) function in class:cv::ml::Impl
494 bool train( const Ptr<TrainData>& data, int flags ) function in class:cv::ml::KNearestImpl
496 return impl->train(data, flags);
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| nbayes.cpp | 55 bool train( const Ptr<TrainData>& trainData, int flags ) function in class:cv::ml::NormalBayesClassifierImpl
110 // process train data (count, sum , productsum)
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| /external/opencv3/modules/cudafeatures2d/test/ |
| test_features2d.cpp | 236 cv::Mat query, train; local
247 queryDescCount = 300; // must be even number because we split train data in some cases in two
260 // Generate train decriptors as follows:
261 // copy each query descriptor to train set countFactor times
282 trainBuf.convertTo(train, CV_32F);
294 mask.create(query.rows, train.rows, CV_8UC1);
299 matcher->match(loadMat(query), loadMat(train), matches, mask);
319 cv::cuda::GpuMat d_train(train);
322 matcher->add(std::vector<cv::cuda::GpuMat>(1, d_train.rowRange(0, train.rows / 2)));
323 matcher->add(std::vector<cv::cuda::GpuMat>(1, d_train.rowRange(train.rows / 2, train.rows)))
[all...] |
| /external/opencv3/modules/features2d/test/ |
| test_matchers_algorithmic.cpp | 62 static const int queryDescCount = 300; // must be even number because we split train data in some cases in two
67 void generateData( Mat& query, Mat& train );
70 void matchTest( const Mat& query, const Mat& train );
71 void knnMatchTest( const Mat& query, const Mat& train );
72 void radiusMatchTest( const Mat& query, const Mat& train );
161 void CV_DescriptorMatcherTest::generateData( Mat& query, Mat& train )
171 // Generate train decriptors as follows:
172 // copy each query descriptor to train set countFactor times
176 train.create( query.rows*countFactor, query.cols, CV_32FC1 );
184 Mat trainDescriptor = train.row(tIdx)
519 Mat query, train; local
[all...] |
| /external/opencv/ml/src/ |
| mlknearest.cpp | 65 train( _train_data, _responses, _sample_idx, _is_regression, _max_k, false );
92 bool CvKNearest::train( const CvMat* _train_data, const CvMat* _responses, function in class:CvKNearest
99 CV_FUNCNAME( "CvKNearest::train" );
113 CV_CALL( cvPrepareTrainData( "CvKNearest::train", _train_data, CV_ROW_SAMPLE,
320 CV_ERROR( CV_StsError, "The search tree must be constructed first using train method" );
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| mlnbayes.cpp | 103 train( _train_data, _responses, _var_idx, _sample_idx );
107 bool CvNormalBayesClassifier::train( const CvMat* _train_data, const CvMat* _responses, function in class:CvNormalBayesClassifier
118 CV_FUNCNAME( "CvNormalBayesClassifier::train" );
195 /* process train data (count, sum , productsum) */
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| mlrtrees.cpp | 55 bool CvForestTree::train( CvDTreeTrainData* _data, function in class:CvForestTree
61 CV_FUNCNAME( "CvForestTree::train" );
80 CvForestTree::train( const CvMat*, int, const CvMat*, const CvMat*, function in class:CvForestTree
89 CvForestTree::train( CvDTreeTrainData*, const CvMat* ) function in class:CvForestTree
231 bool CvRTrees::train( const CvMat* _train_data, int _tflag, function in class:CvRTrees
238 CV_FUNCNAME("CvRTrees::train");
374 CV_CALL(tree->train( data, sample_idx_for_tree, this ));
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| mlem.cpp | 84 // just invoke the train() method
85 train(samples, sample_idx, params, labels);
303 bool CvEM::train( const CvMat* _samples, const CvMat* _sample_idx, function in class:CvEM
[all...] |
| mlann_mlp.cpp | 816 int CvANN_MLP::train( const CvMat* _inputs, const CvMat* _outputs, function in class:CvANN_MLP
829 CV_FUNCNAME( "CvANN_MLP::train" );
1059 CV_FUNCNAME( "CvANN_MLP::train" );
[all...] |
| /external/opencv3/modules/ml/test/ |
| test_mltests2.cpp | 84 CV_Error( CV_StsBadArg, "incorrect ann train method string" );
313 int CV_MLBaseTest::train( int testCaseIdx ) function in class:CV_MLBaseTest
440 is_trained = model->train(data, 0);
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| /external/opencv3/modules/features2d/misc/java/src/cpp/ |
| features2d_manual.hpp | 199 CV_WRAP void train() function
200 { return wrapped->train(); }
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| /external/opencv3/modules/features2d/src/ |
| matchers.cpp | 63 static bool ocl_matchSingle(InputArray query, InputArray train,
66 if (query.empty() || train.empty())
77 UMat uquery = query.getUMat(), utrain = train.getUMat();
161 static bool ocl_knnMatchSingle(InputArray query, InputArray train, UMat &trainIdx,
164 if (query.empty() || train.empty())
177 UMat uquery = query.getUMat(), utrain = train.getUMat();
273 static bool ocl_radiusMatchSingle(InputArray query, InputArray train,
276 if (query.empty() || train.empty())
280 const int train_rows = train.rows();
293 UMat uquery = query.getUMat(), utrain = train.getUMat()
1044 void FlannBasedMatcher::train() function in class:cv::FlannBasedMatcher
[all...] |
| /external/opencv3/modules/ml/include/opencv2/ |
| ml.hpp | 133 of this class into StatModel::train.
154 /** @brief Returns matrix of train samples
318 CV_WRAP virtual bool train( const Ptr<TrainData>& trainData, int flags=0 );
326 CV_WRAP virtual bool train( InputArray samples, int layout, InputArray responses );
351 /** @brief Create and train model with default parameters
355 template<typename _Tp> static Ptr<_Tp> train(const Ptr<TrainData>& data, int flags=0) function in class:cv::ml::StatModel
358 return !model.empty() && model->train(data, flags) ? model : Ptr<_Tp>();
385 Use StatModel::train to train the model after creation. */
466 The static method creates empty %KNearest classifier. It should be then trained using StatModel::train method
[all...] |
| /external/opencv3/samples/gpu/performance/ |
| tests.cpp | 377 Mat train; local
378 gen(train, 3000, desc_len, CV_32F, 0, 1);
385 cuda::GpuMat d_train(train);
393 matcher.match(query, train, matches[0]);
396 matcher.match(query, train, matches[0]);
407 matcher.knnMatch(query, train, matches, 2);
410 matcher.knnMatch(query, train, matches, 2);
423 matcher.radiusMatch(query, train, matches, max_distance);
426 matcher.radiusMatch(query, train, matches, max_distance);
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