| /external/opencv/ml/src/ |
| D | mlestimate.cpp | 404 const CvMat* sampleIdx)
454 if (sampleIdx)
459 if (!CV_IS_MAT (sampleIdx))
462 if (sampleIdx->rows != 1 && sampleIdx->cols != 1)
465 s_len = sampleIdx->rows + sampleIdx->cols - 1;
466 s_step = sampleIdx->rows == 1 ?
467 1 : sampleIdx->step / CV_ELEM_SIZE(sampleIdx->type);
469 s_type = CV_MAT_TYPE (sampleIdx->type);
476 uchar* s_data = sampleIdx->data.ptr;
510 uchar* s_data = sampleIdx->data.ptr;
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| D | _ml.h | 219 ICV_MAT2VEC( *sampleIdx, sidx, sistep, l ); \
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| /external/opencv3/apps/traincascade/ |
| D | old_ml.hpp | 198 const CvMat* varIdx=0, const CvMat* sampleIdx=0 );
201 const CvMat* varIdx = 0, const CvMat* sampleIdx=0, bool update=false );
207 const cv::Mat& varIdx=cv::Mat(), const cv::Mat& sampleIdx=cv::Mat() );
209 const cv::Mat& varIdx = cv::Mat(), const cv::Mat& sampleIdx=cv::Mat(),
243 const CvMat* sampleIdx=0, bool isRegression=false, int max_k=32 );
246 const CvMat* sampleIdx=0, bool is_regression=false,
253 const cv::Mat& sampleIdx=cv::Mat(), bool isRegression=false, int max_k=32 );
256 const cv::Mat& sampleIdx=cv::Mat(), bool isRegression=false,
473 const CvMat* varIdx=0, const CvMat* sampleIdx=0,
477 const CvMat* varIdx=0, const CvMat* sampleIdx=0,
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| D | haarfeatures.h | 37 virtual float operator()(int featureIdx, int sampleIdx) const;
73 inline float CvHaarEvaluator::operator()(int featureIdx, int sampleIdx) const in operator()
75 float nf = normfactor.at<float>(0, sampleIdx); in operator()
76 return !nf ? 0.0f : (features[featureIdx].calc( sum, tilted, sampleIdx)/nf); in operator()
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| D | HOGfeatures.h | 25 virtual float operator()(int varIdx, int sampleIdx) const;
52 inline float CvHOGEvaluator::operator()(int varIdx, int sampleIdx) const in operator()
57 return features[featureIdx].calc( hist, normSum, sampleIdx, componentIdx); in operator()
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| D | lbpfeatures.h | 20 virtual float operator()(int featureIdx, int sampleIdx) const in operator()
21 { return (float)features[featureIdx].calc( sum, sampleIdx); } in operator()
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| D | boost.h | 56 virtual CvDTreeNode* predict( int sampleIdx ) const;
70 virtual float predict( int sampleIdx, bool returnSum = false ) const;
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| D | boost.cpp | 954 CvDTreeNode* CvCascadeBoostTree::predict( int sampleIdx ) const in predict()
965 float val = ((CvCascadeBoostTrainData*)data)->getVarValue( split->var_idx, sampleIdx ); in predict()
974 int c = (int)((CvCascadeBoostTrainData*)data)->getVarValue( split->var_idx, sampleIdx ); in predict()
1403 float CvCascadeBoost::predict( int sampleIdx, bool returnSum ) const in predict() argument
1414 sum += ((CvCascadeBoostTree*)wtree)->predict(sampleIdx)->value; in predict()
1437 const int* sampleIdx = 0; in update_weights() local
1448 sampleIdx = data->get_sample_indices( data->data_root, sampleIdxBuf ); in update_weights()
1513 fdata[sampleIdx[i]*step] = orig_response->data.i[i] > 0 ? 2.f : -2.f; in update_weights()
1523 fdata[sampleIdx[i]*step] = (float)orig_response->data.i[i]; in update_weights()
1632 fdata[sampleIdx[i]*step] = (float)min(z, lbZMax); in update_weights()
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| D | cascadeclassifier.cpp | 288 int CvCascadeClassifier::predict( int sampleIdx ) in predict() argument
290 CV_DbgAssert( sampleIdx < numPos + numNeg ); in predict()
294 if ( (*it)->predict( sampleIdx ) == 0.f ) in predict()
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| D | cascadeclassifier.h | 100 int predict( int sampleIdx );
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| D | traincascade_features.h | 83 virtual float operator()(int featureIdx, int sampleIdx) const = 0;
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| D | old_ml_precomp.hpp | 215 ICV_MAT2VEC( *sampleIdx, sidx, sistep, l ); \
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| /external/opencv3/modules/ml/src/ |
| D | data.cpp | 131 return !sampleIdx.empty() ? (int)sampleIdx.total() : in getNSamples()
160 Mat getTrainSampleIdx() const { return !trainSampleIdx.empty() ? trainSampleIdx : sampleIdx; } in getTrainSampleIdx()
217 sampleIdx.release(); in clear()
242 sampleIdx = _sampleIdx.getMat(); in setData()
253 if( !sampleIdx.empty() ) in setData()
255 CV_Assert( (sampleIdx.checkVector(1, CV_32S, true) > 0 && in setData()
256 checkRange(sampleIdx, true, 0, 0, nsamples-1)) || in setData()
257 sampleIdx.checkVector(1, CV_8U, true) == nsamples ); in setData()
258 if( sampleIdx.type() == CV_8U ) in setData()
259 sampleIdx = convertMaskToIdx(sampleIdx); in setData()
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| D | gbt.cpp | 1322 const cv::Mat& sampleIdx, const cv::Mat& varType,
1338 train(trainData, tflag, responses, varIdx, sampleIdx, varType, missingDataMask, _params, false);
1343 const cv::Mat& sampleIdx, const cv::Mat& varType,
1349 CvMat _varIdx = varIdx, _sampleIdx = sampleIdx, _varType = varType;
1353 sampleIdx.empty() ? 0 : &_sampleIdx, varType.empty() ? 0 : &_varType,
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| /external/webrtc/webrtc/modules/audio_device/mac/ |
| D | audio_device_mac.cc | 2638 for (uint32_t sampleIdx = 0; sampleIdx < nOutSamples; sampleIdx += 2) { in RenderWorkerThread() local
2639 sampleInt32 = pPlayBuffer[sampleIdx]; in RenderWorkerThread()
2640 sampleInt32 += pPlayBuffer[sampleIdx + 1]; in RenderWorkerThread()
2649 pPlayBuffer[sampleIdx] = 0; in RenderWorkerThread()
2650 pPlayBuffer[sampleIdx + 1] = static_cast<SInt16>(sampleInt32); in RenderWorkerThread()
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| /external/opencv3/modules/ml/include/opencv2/ |
| D | ml.hpp | 284 InputArray varIdx=noArray(), InputArray sampleIdx=noArray(),
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| /external/opencv/ml/include/ |
| D | ml.h | 1508 const CvMat* sampleIdx CV_DEFAULT(0) );
1525 const CvMat* sampleIdx CV_DEFAULT(0),
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