/external/libweave/examples/daemon/sample/ |
H A D | sample.cc | 16 "_sample": { 65 CHECK(device->AddComponent(kComponent, {"_sample"}, nullptr)); 67 kComponent, R"({"_sample": {"pingCount": 0}})", nullptr)); 69 device->AddCommandHandler(kComponent, "_sample.hello", 72 device->AddCommandHandler(kComponent, "_sample.ping", 75 device->AddCommandHandler(kComponent, "_sample.countdown", 109 device_->SetStateProperty(kComponent, "_sample.pingCount",
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/external/opencv/ml/src/ |
H A D | mlboost.cpp | 1057 CvMat _sample, _mask; local 1064 _sample = cvMat( 1, data->var_count, CV_32F ); 1071 _sample.data.fl = values; 1073 values += _sample.cols; 1075 weak_eval->data.db[i] = tree->predict( &_sample, &_mask, true )->value; 1262 CvBoost::predict( const CvMat* _sample, const CvMat* _missing, 1287 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || 1288 _sample->cols != 1 && _sample [all...] |
H A D | mlem.cpp | 209 CvEM::predict( const CvMat* _sample, CvMat* _probs ) const argument 229 CV_CALL( cvPreparePredictData( _sample, dims, 0, params.nclusters, _probs, &sample_data )); 293 if( sample_data != _sample->data.fl ) 982 CvMat* cov = covs[k], _mean, _sample; local 987 cvGetRow( samples, &_sample, k ); 1002 _sample.data.db = (double*)(samples->data.ptr + samples->step*i); 1006 cvMulTransposed( &_sample, covs_item, 1, &_mean ); 1012 double val = _sample.data.db[j] - _mean.data.db[j];
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H A D | mltree.cpp | 2881 CvDTreeNode* CvDTree::predict( const CvMat* _sample, argument 2903 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || 2904 _sample->cols != 1 && _sample->rows != 1 || 2905 _sample->cols + _sample->rows - 1 != data->var_all && !preprocessed_input || 2906 _sample->cols + _sample->rows - 1 != data->var_count && preprocessed_input ) 2911 sample = _sample [all...] |
H A D | ml_inner_functions.cpp | 1148 cvPreparePredictData( const CvArr* _sample, int dims_all, argument 1160 const CvMat* sample = (const CvMat*)_sample;
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/external/opencv3/apps/traincascade/ |
H A D | old_ml_boost.cpp | 1271 CvMat _sample, _mask; local 1277 _sample = cvMat( 1, data->var_count, CV_32F ); 1284 _sample.data.fl = values; 1286 values += _sample.cols; 1288 weak_eval->data.db[i] = tree->predict( &_sample, &_mask, true )->value; 1603 CvBoost::predict( const CvMat* _sample, const CvMat* _missing, 1617 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || 1618 (_sample->cols != 1 && _sample [all...] |
H A D | old_ml_tree.cpp | 3618 CvDTreeNode* CvDTree::predict( const CvMat* _sample, argument 3630 if( !CV_IS_MAT(_sample) || CV_MAT_TYPE(_sample->type) != CV_32FC1 || 3631 (_sample->cols != 1 && _sample->rows != 1) || 3632 (_sample->cols + _sample->rows - 1 != data->var_all && !preprocessed_input) || 3633 (_sample->cols + _sample->rows - 1 != data->var_count && preprocessed_input) ) 3638 const float* sample = _sample 3735 predict( const Mat& _sample, const Mat& _missing, bool preprocessed_input ) const argument [all...] |
H A D | old_ml_inner_functions.cpp | 1078 cvPreparePredictData( const CvArr* _sample, int dims_all, argument 1090 const CvMat* sample = (const CvMat*)_sample;
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/external/opencv3/modules/ml/src/ |
H A D | gbt.cpp | 806 float CvGBTrees::predict_serial( const CvMat* _sample, const CvMat* _missing, 841 float p = (float)(tree->predict(_sample, _missing)->value); 905 const CvMat* _sample, const CvMat* _missing, float* _sum ) : 906 weak(_weak), sum(_sum), k(_k), sample(_sample), 955 float CvGBTrees::predict( const CvMat* _sample, const CvMat* _missing, 968 params.shrinkage, _sample, _missing, sum); 1360 CvMat _sample = sample, miss = _missing; 1361 return predict(&_sample, _missing.empty() ? 0 : &miss, 0,
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H A D | em.cpp | 188 Vec2d predict2(InputArray _sample, OutputArray _probs) const argument 191 Mat sample = _sample.getMat();
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/external/opencv/ml/include/ |
H A D | ml.h | 514 virtual float predict( const CvMat* _sample ) const; 845 virtual CvDTreeNode* predict( const CvMat* _sample, const CvMat* _missing_data_mask=0, 1101 virtual float predict( const CvMat* _sample, const CvMat* _missing=0,
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