sample 174 3rdparty/libtiff/tif_read.c TIFFSeek(TIFF* tif, uint32 row, uint16 sample ) sample 192 3rdparty/libtiff/tif_read.c if (sample >= td->td_samplesperpixel) { sample 195 3rdparty/libtiff/tif_read.c (unsigned long) sample, (unsigned long) td->td_samplesperpixel); sample 198 3rdparty/libtiff/tif_read.c strip = (uint32)sample*td->td_stripsperimage + row/td->td_rowsperstrip; sample 289 3rdparty/libtiff/tif_read.c TIFFReadScanline(TIFF* tif, void* buf, uint32 row, uint16 sample) sample 295 3rdparty/libtiff/tif_read.c if( (e = TIFFSeek(tif, row, sample)) != 0) { sample 300 3rdparty/libtiff/tif_read.c (tif, (uint8*) buf, tif->tif_scanlinesize, sample); sample 38 3rdparty/libtiff/tif_strip.c TIFFComputeStrip(TIFF* tif, uint32 row, uint16 sample) sample 46 3rdparty/libtiff/tif_strip.c if (sample >= td->td_samplesperpixel) { sample 49 3rdparty/libtiff/tif_strip.c (unsigned long) sample, (unsigned long) td->td_samplesperpixel); sample 52 3rdparty/libtiff/tif_strip.c strip += (uint32)sample*td->td_stripsperimage; sample 49 3rdparty/libtiff/tif_write.c TIFFWriteScanline(TIFF* tif, void* buf, uint32 row, uint16 sample) sample 85 3rdparty/libtiff/tif_write.c if (sample >= td->td_samplesperpixel) { sample 88 3rdparty/libtiff/tif_write.c (unsigned long) sample, (unsigned long) td->td_samplesperpixel); sample 91 3rdparty/libtiff/tif_write.c strip = sample*td->td_stripsperimage + row/td->td_rowsperstrip; sample 138 3rdparty/libtiff/tif_write.c if (!(*tif->tif_preencode)(tif, sample)) sample 170 3rdparty/libtiff/tif_write.c tif->tif_scanlinesize, sample); sample 188 3rdparty/libtiff/tif_write.c uint16 sample; sample 241 3rdparty/libtiff/tif_write.c sample = (uint16)(strip / td->td_stripsperimage); sample 242 3rdparty/libtiff/tif_write.c if (!(*tif->tif_preencode)(tif, sample)) sample 248 3rdparty/libtiff/tif_write.c if (!(*tif->tif_encodestrip)(tif, (uint8*) data, cc, sample)) sample 344 3rdparty/libtiff/tif_write.c uint16 sample; sample 390 3rdparty/libtiff/tif_write.c sample = (uint16)(tile/td->td_stripsperimage); sample 391 3rdparty/libtiff/tif_write.c if (!(*tif->tif_preencode)(tif, sample)) sample 404 3rdparty/libtiff/tif_write.c if (!(*tif->tif_encodetile)(tif, (uint8*) data, cc, sample)) sample 411 3rdparty/libtiff/tiffio.h extern int TIFFReadScanline(TIFF* tif, void* buf, uint32 row, uint16 sample = 0); sample 412 3rdparty/libtiff/tiffio.h extern int TIFFWriteScanline(TIFF* tif, void* buf, uint32 row, uint16 sample = 0); sample 418 3rdparty/libtiff/tiffio.h extern int TIFFReadScanline(TIFF* tif, void* buf, uint32 row, uint16 sample); sample 419 3rdparty/libtiff/tiffio.h extern int TIFFWriteScanline(TIFF* tif, void* buf, uint32 row, uint16 sample); sample 91 3rdparty/libtiff/tiffiop.h typedef int (*TIFFCodeMethod)(TIFF* tif, uint8* buf, tmsize_t size, uint16 sample); sample 57 3rdparty/libwebp/dec/io.c const WebPSampleLinePairFunc sample = WebPSamplers[output->colorspace]; sample 62 3rdparty/libwebp/dec/io.c sample(y_src, y_src + io->y_stride, u_src, v_src, sample 70 3rdparty/libwebp/dec/io.c sample(y_src, y_src, u_src, v_src, dst, dst, mb_w); sample 134 apps/createsamples/utility.cpp static void icvWriteVecSample( FILE* file, CvArr* sample ) sample 141 apps/createsamples/utility.cpp mat = cvGetMat( sample, &stub ); sample 1231 apps/createsamples/utility.cpp CvMat sample; sample 1238 apps/createsamples/utility.cpp sample = cvMat( winheight, winwidth, CV_8UC1, cvAlloc( sizeof( uchar ) * sample 1241 apps/createsamples/utility.cpp icvWriteVecHeader( output, count, sample.cols, sample.rows ); sample 1253 apps/createsamples/utility.cpp icvGetBackgroundImage( cvbgdata, cvbgreader, &sample ); sample 1257 apps/createsamples/utility.cpp cvSet( &sample, cvScalar( bgcolor ) ); sample 1264 apps/createsamples/utility.cpp icvPlaceDistortedSample( &sample, inverse, maxintensitydev, sample 1273 apps/createsamples/utility.cpp cvShowImage( "Sample", &sample ); sample 1280 apps/createsamples/utility.cpp icvWriteVecSample( output, &sample ); sample 1290 apps/createsamples/utility.cpp cvFree( &(sample.data.ptr) ); sample 1428 apps/createsamples/utility.cpp IplImage* sample; sample 1473 apps/createsamples/utility.cpp sample = cvCreateImage( cvSize( winwidth, winheight ), IPL_DEPTH_8U, 1 ); sample 1475 apps/createsamples/utility.cpp icvWriteVecHeader( vec, num, sample->width, sample->height ); sample 1520 apps/createsamples/utility.cpp cvResize( src, sample, width >= sample->width && sample 1521 apps/createsamples/utility.cpp height >= sample->height ? CV_INTER_AREA : CV_INTER_LINEAR ); sample 1525 apps/createsamples/utility.cpp cvShowImage( "Sample", sample ); sample 1531 apps/createsamples/utility.cpp icvWriteVecSample( vec, sample ); sample 1550 apps/createsamples/utility.cpp if( sample ) sample 1552 apps/createsamples/utility.cpp cvReleaseImage( &sample ); sample 1608 apps/createsamples/utility.cpp CvMat* sample; sample 1660 apps/createsamples/utility.cpp sample = scaled_sample = cvCreateMat( winheight, winwidth, CV_8UC1 ); sample 1670 apps/createsamples/utility.cpp icvGetTraininDataFromVec( sample, &file ); sample 1671 apps/createsamples/utility.cpp if( scale != 1.0 ) cvResize( sample, scaled_sample, CV_INTER_LINEAR); sample 1675 apps/createsamples/utility.cpp if( scaled_sample && scaled_sample != sample ) cvReleaseMat( &scaled_sample ); sample 1676 apps/createsamples/utility.cpp cvReleaseMat( &sample ); sample 491 apps/traincascade/old_ml.hpp virtual float predict( const CvMat* sample, bool returnDFVal=false ) const; sample 512 apps/traincascade/old_ml.hpp CV_WRAP virtual float predict( const cv::Mat& sample, bool returnDFVal=false ) const; sample 787 apps/traincascade/old_ml.hpp virtual CvDTreeNode* predict( const CvMat* sample, const CvMat* missingDataMask=0, sample 796 apps/traincascade/old_ml.hpp CV_WRAP virtual CvDTreeNode* predict( const cv::Mat& sample, const cv::Mat& missingDataMask=cv::Mat(), sample 930 apps/traincascade/old_ml.hpp virtual float predict( const CvMat* sample, const CvMat* missing = 0 ) const; sample 931 apps/traincascade/old_ml.hpp virtual float predict_prob( const CvMat* sample, const CvMat* missing = 0 ) const; sample 938 apps/traincascade/old_ml.hpp CV_WRAP virtual float predict( const cv::Mat& sample, const cv::Mat& missing = cv::Mat() ) const; sample 939 apps/traincascade/old_ml.hpp CV_WRAP virtual float predict_prob( const cv::Mat& sample, const cv::Mat& missing = cv::Mat() ) const; sample 1136 apps/traincascade/old_ml.hpp virtual float predict( const CvMat* sample, const CvMat* missing=0, sample 1153 apps/traincascade/old_ml.hpp CV_WRAP virtual float predict( const cv::Mat& sample, const cv::Mat& missing=cv::Mat(), sample 1475 apps/traincascade/old_ml.hpp virtual float predict_serial( const CvMat* sample, const CvMat* missing=0, sample 1507 apps/traincascade/old_ml.hpp virtual float predict( const CvMat* sample, const CvMat* missing=0, sample 1592 apps/traincascade/old_ml.hpp CV_WRAP virtual float predict( const cv::Mat& sample, const cv::Mat& missing=cv::Mat(), sample 1904 apps/traincascade/old_ml.hpp CVAPI(void) cvRandMVNormal( CvMat* mean, CvMat* cov, CvMat* sample, sample 1912 apps/traincascade/old_ml.hpp CvMat* sample, sample 1658 apps/traincascade/old_ml_boost.cpp cv::Mat sample = cv::cvarrToMat(_sample); sample 1675 apps/traincascade/old_ml_boost.cpp sample = cv::Mat(1, var_count, CV_32FC1); sample 1678 apps/traincascade/old_ml_boost.cpp dst_sample = sample.ptr<float>(); sample 1744 apps/traincascade/old_ml_boost.cpp sample_data = sample.ptr<float>(); sample 1854 apps/traincascade/old_ml_boost.cpp CvMat sample, miss; sample 1856 apps/traincascade/old_ml_boost.cpp cvGetRow( values, &sample, si ); sample 1859 apps/traincascade/old_ml_boost.cpp float r = (float)predict( &sample, missing ? &miss : 0 ); sample 1871 apps/traincascade/old_ml_boost.cpp CvMat sample, miss; sample 1873 apps/traincascade/old_ml_boost.cpp cvGetRow( values, &sample, si ); sample 1876 apps/traincascade/old_ml_boost.cpp float r = (float)predict( &sample, missing ? &miss : 0 ); sample 2141 apps/traincascade/old_ml_boost.cpp CvMat sample = _sample, mmask = _missing; sample 2157 apps/traincascade/old_ml_boost.cpp return predict(&sample, _missing.empty() ? 0 : &mmask, 0, sample 158 apps/traincascade/old_ml_inner_functions.cpp CV_IMPL void cvRandMVNormal( CvMat* mean, CvMat* cov, CvMat* sample, CvRNG* rng ) sample 160 apps/traincascade/old_ml_inner_functions.cpp int dim = sample->cols; sample 161 apps/traincascade/old_ml_inner_functions.cpp int amount = sample->rows; sample 164 apps/traincascade/old_ml_inner_functions.cpp cvRandArr(&state, sample, CV_RAND_NORMAL, cvScalarAll(0), cvScalarAll(1) ); sample 166 apps/traincascade/old_ml_inner_functions.cpp CvMat* utmat = cvCreateMat(dim, dim, sample->type); sample 167 apps/traincascade/old_ml_inner_functions.cpp CvMat* vect = cvCreateMatHeader(1, dim, sample->type); sample 174 apps/traincascade/old_ml_inner_functions.cpp cvGetRow(sample, vect, i); sample 185 apps/traincascade/old_ml_inner_functions.cpp static void cvRandSeries( float probs[], int len, int sample[], int amount ) sample 204 apps/traincascade/old_ml_inner_functions.cpp sample[i] = j; sample 217 apps/traincascade/old_ml_inner_functions.cpp CvMat* sample, sample 220 apps/traincascade/old_ml_inner_functions.cpp int dim = sample->cols; sample 221 apps/traincascade/old_ml_inner_functions.cpp int amount = sample->rows; sample 236 apps/traincascade/old_ml_inner_functions.cpp cvRandArr(&state, sample, CV_RAND_NORMAL, cvScalarAll(0), cvScalarAll(1)); sample 249 apps/traincascade/old_ml_inner_functions.cpp cvGetRow(sample, vect, i); sample 1006 apps/traincascade/old_ml_inner_functions.cpp const float* sample; sample 1049 apps/traincascade/old_ml_inner_functions.cpp pairs[i].sample = samples[i]; sample 1062 apps/traincascade/old_ml_inner_functions.cpp samples[i] = pairs[i].sample; sample 1090 apps/traincascade/old_ml_inner_functions.cpp const CvMat* sample = (const CvMat*)_sample; sample 1093 apps/traincascade/old_ml_inner_functions.cpp int is_sparse = CV_IS_SPARSE_MAT(sample); sample 1098 apps/traincascade/old_ml_inner_functions.cpp if( !is_sparse && !CV_IS_MAT(sample) ) sample 1099 apps/traincascade/old_ml_inner_functions.cpp CV_ERROR( !sample ? CV_StsNullPtr : CV_StsBadArg, "The sample is not a valid vector" ); sample 1101 apps/traincascade/old_ml_inner_functions.cpp if( cvGetElemType( sample ) != CV_32FC1 ) sample 1104 apps/traincascade/old_ml_inner_functions.cpp CV_CALL( d = cvGetDims( sample, sizes )); sample 1106 apps/traincascade/old_ml_inner_functions.cpp if( !((is_sparse && d == 1) || (!is_sparse && d == 2 && (sample->rows == 1 || sample->cols == 1))) ) sample 1145 apps/traincascade/old_ml_inner_functions.cpp if( CV_IS_MAT(sample) ) sample 1147 apps/traincascade/old_ml_inner_functions.cpp sample_data = sample->data.fl; sample 1148 apps/traincascade/old_ml_inner_functions.cpp sample_step = CV_IS_MAT_CONT(sample->type) ? 1 : sample->step/sizeof(row_sample[0]); sample 1150 apps/traincascade/old_ml_inner_functions.cpp if( !comp_idx && CV_IS_MAT_CONT(sample->type) && !as_sparse ) sample 1186 apps/traincascade/old_ml_inner_functions.cpp const CvSparseMat* sparse = (const CvSparseMat*)sample; sample 1466 apps/traincascade/old_ml_inner_functions.cpp CvArr* sample = &predict_input_part; sample 1629 apps/traincascade/old_ml_inner_functions.cpp sample = sparse_rows[idx]; sample 1634 apps/traincascade/old_ml_inner_functions.cpp CV_CALL( response = stat_model->predict( stat_model, (CvMat*)sample, probs1 )); sample 309 apps/traincascade/old_ml_precomp.hpp cvPreparePredictData( const CvArr* sample, int dims_all, const CvMat* comp_idx, sample 3342 apps/traincascade/old_ml_tree.cpp CvMat sample, miss; sample 3344 apps/traincascade/old_ml_tree.cpp cvGetRow( values, &sample, si ); sample 3347 apps/traincascade/old_ml_tree.cpp float r = (float)predict( &sample, missing ? &miss : 0 )->value; sample 3359 apps/traincascade/old_ml_tree.cpp CvMat sample, miss; sample 3361 apps/traincascade/old_ml_tree.cpp cvGetRow( values, &sample, si ); sample 3364 apps/traincascade/old_ml_tree.cpp float r = (float)predict( &sample, missing ? &miss : 0 )->value; sample 3638 apps/traincascade/old_ml_tree.cpp const float* sample = _sample->data.fl; sample 3639 apps/traincascade/old_ml_tree.cpp int step = CV_IS_MAT_CONT(_sample->type) ? 1 : _sample->step/sizeof(sample[0]); sample 3673 apps/traincascade/old_ml_tree.cpp float val = sample[(size_t)i*step]; sample 3737 apps/traincascade/old_ml_tree.cpp CvMat sample = _sample, mmask = _missing; sample 3738 apps/traincascade/old_ml_tree.cpp return predict(&sample, mmask.data.ptr ? &mmask : 0, preprocessed_input); sample 185 modules/core/src/kmeans.cpp const float *sample = data.ptr<float>(i); sample 192 modules/core/src/kmeans.cpp const double dist = normL2Sqr(sample, center, dims); sample 282 modules/core/src/kmeans.cpp const float* sample = data.ptr<float>(0); sample 284 modules/core/src/kmeans.cpp box[j] = Vec2f(sample[j], sample[j]); sample 288 modules/core/src/kmeans.cpp sample = data.ptr<float>(i); sample 291 modules/core/src/kmeans.cpp float v = sample[j]; sample 329 modules/core/src/kmeans.cpp sample = data.ptr<float>(i); sample 336 modules/core/src/kmeans.cpp float t0 = center[j] + sample[j]; sample 337 modules/core/src/kmeans.cpp float t1 = center[j+1] + sample[j+1]; sample 342 modules/core/src/kmeans.cpp t0 = center[j+2] + sample[j+2]; sample 343 modules/core/src/kmeans.cpp t1 = center[j+3] + sample[j+3]; sample 350 modules/core/src/kmeans.cpp center[j] += sample[j]; sample 386 modules/core/src/kmeans.cpp sample = data.ptr<float>(i); sample 387 modules/core/src/kmeans.cpp double dist = normL2Sqr(sample, _old_center, dims); sample 399 modules/core/src/kmeans.cpp sample = data.ptr<float>(farthest_i); sample 403 modules/core/src/kmeans.cpp old_center[j] -= sample[j]; sample 404 modules/core/src/kmeans.cpp new_center[j] += sample[j]; sample 807 modules/ml/include/opencv2/ml.hpp CV_WRAP CV_WRAP virtual Vec2d predict2(InputArray sample, OutputArray probs) const = 0; sample 210 modules/ml/src/boost.cpp Mat sample(1, nvars, CV_32F, sbuf); sample 217 modules/ml/src/boost.cpp result[i] = predictTrees(Range(treeidx, treeidx+1), sample, predictFlags); sample 359 modules/ml/src/boost.cpp float predictTrees( const Range& range, const Mat& sample, int flags0 ) const sample 362 modules/ml/src/boost.cpp float val = DTreesImpl::predictTrees(range, sample, flags); sample 191 modules/ml/src/em.cpp Mat sample = _sample.getMat(); sample 194 modules/ml/src/em.cpp CV_Assert(!sample.empty()); sample 195 modules/ml/src/em.cpp if(sample.type() != CV_64FC1) sample 198 modules/ml/src/em.cpp sample.convertTo(tmp, CV_64FC1); sample 199 modules/ml/src/em.cpp sample = tmp; sample 201 modules/ml/src/em.cpp sample.reshape(1, 1); sample 212 modules/ml/src/em.cpp return computeProbabilities(sample, !probs.empty() ? &probs : 0, ptype); sample 439 modules/ml/src/em.cpp const Mat sample = trainSamples.row(sampleIndex); sample 440 modules/ml/src/em.cpp clusterSamples.push_back(sample); sample 557 modules/ml/src/em.cpp Vec2d computeProbabilities(const Mat& sample, Mat* probs, int ptype) const sample 565 modules/ml/src/em.cpp int stype = sample.type(); sample 568 modules/ml/src/em.cpp CV_Assert(sample.size() == Size(means.cols, 1)); sample 570 modules/ml/src/em.cpp int dim = sample.cols; sample 580 modules/ml/src/em.cpp const float* sptr = sample.ptr<float>(); sample 586 modules/ml/src/em.cpp const double* sptr = sample.ptr<double>(); sample 895 modules/ml/src/gbt.cpp const CvMat* sample; sample 903 modules/ml/src/gbt.cpp Tree_predictor() : weak(0), sum(0), k(0), sample(0), missing(0), shrinkage(1.0f) {} sample 906 modules/ml/src/gbt.cpp weak(_weak), sum(_sum), k(_k), sample(_sample), sample 911 modules/ml/src/gbt.cpp weak(p.weak), sum(p.sum), k(p.k), sample(p.sample), sample 937 modules/ml/src/gbt.cpp tmp_sum += shrinkage*(float)(tree->predict(sample, missing)->value); sample 1357 modules/ml/src/gbt.cpp float CvGBTrees::predict( const cv::Mat& sample, const cv::Mat& _missing, sample 1360 modules/ml/src/gbt.cpp CvMat _sample = sample, miss = _missing; sample 92 modules/ml/src/inner_functions.cpp Mat sample = layout == ROW_SAMPLE ? samples.row(si) : samples.col(si); sample 93 modules/ml/src/inner_functions.cpp float val = predict(sample); sample 167 modules/ml/src/inner_functions.cpp Mat sample = samples.row(i); sample 168 modules/ml/src/inner_functions.cpp gemm(sample, utmat, 1, mean, 1, sample, flags); sample 326 modules/ml/src/precomp.hpp virtual float predictTrees( const Range& range, const Mat& sample, int flags ) const; sample 149 modules/ml/src/rtrees.cpp Mat sample0, sample(nallvars, 1, CV_32F, &samplebuf[0]); sample 204 modules/ml/src/rtrees.cpp sample = Mat( nallvars, 1, CV_32F, psamples + sstep0*w->sidx[j], sstep1*sizeof(psamples[0]) ); sample 206 modules/ml/src/rtrees.cpp double val = predictTrees(Range(treeidx, treeidx+1), sample, predictFlags); sample 256 modules/ml/src/rtrees.cpp sample.at<float>(k) = sample0.at<float>(k); sample 257 modules/ml/src/rtrees.cpp sample.at<float>(vi) = psamples[sstep0*w->sidx[vj] + sstep1*vi]; sample 259 modules/ml/src/rtrees.cpp double val = predictTrees(Range(treeidx, treeidx+1), sample, predictFlags); sample 172 modules/ml/src/svm.cpp const float* sample = &vecs[j*var_count]; sample 175 modules/ml/src/svm.cpp s += sample[k]*another[k] + sample[k+1]*another[k+1] + sample 176 modules/ml/src/svm.cpp sample[k+2]*another[k+2] + sample[k+3]*another[k+3]; sample 178 modules/ml/src/svm.cpp s += sample[k]*another[k]; sample 225 modules/ml/src/svm.cpp const float* sample = &vecs[j*var_count]; sample 230 modules/ml/src/svm.cpp double t0 = sample[k] - another[k]; sample 231 modules/ml/src/svm.cpp double t1 = sample[k+1] - another[k+1]; sample 235 modules/ml/src/svm.cpp t0 = sample[k+2] - another[k+2]; sample 236 modules/ml/src/svm.cpp t1 = sample[k+3] - another[k+3]; sample 243 modules/ml/src/svm.cpp double t0 = sample[k] - another[k]; sample 263 modules/ml/src/svm.cpp const float* sample = &vecs[j*var_count]; sample 266 modules/ml/src/svm.cpp s += std::min(sample[k],another[k]) + std::min(sample[k+1],another[k+1]) + sample 267 modules/ml/src/svm.cpp std::min(sample[k+2],another[k+2]) + std::min(sample[k+3],another[k+3]); sample 269 modules/ml/src/svm.cpp s += std::min(sample[k],another[k]); sample 283 modules/ml/src/svm.cpp const float* sample = &vecs[j*var_count]; sample 287 modules/ml/src/svm.cpp double d = sample[k]-another[k]; sample 288 modules/ml/src/svm.cpp double devisor = sample[k]+another[k]; sample 1363 modules/ml/src/tree.cpp float DTreesImpl::predictTrees( const Range& range, const Mat& sample, int flags ) const sample 1365 modules/ml/src/tree.cpp CV_Assert( sample.type() == CV_32F ); sample 1380 modules/ml/src/tree.cpp const float* psample = sample.ptr<float>(); sample 1382 modules/ml/src/tree.cpp size_t sstep = sample.isContinuous() ? 1 : sample.step/sizeof(float); sample 427 modules/ml/test/test_emknearestkmeans.cpp Mat sample = testData.row(i); sample 429 modules/ml/test/test_emknearestkmeans.cpp labels.at<int>(i) = static_cast<int>(em->predict2( sample, probs )[1]); sample 644 modules/ml/test/test_emknearestkmeans.cpp Mat sample = samples.row(i); sample 647 modules/ml/test/test_emknearestkmeans.cpp samples0.push_back(sample); sample 649 modules/ml/test/test_emknearestkmeans.cpp samples1.push_back(sample); sample 665 modules/ml/test/test_emknearestkmeans.cpp Mat sample = samples.row(i); sample 666 modules/ml/test/test_emknearestkmeans.cpp double sampleLogLikelihoods0 = model0->predict2(sample, noArray())[0]; sample 667 modules/ml/test/test_emknearestkmeans.cpp double sampleLogLikelihoods1 = model1->predict2(sample, noArray())[0]; sample 162 modules/ml/test/test_mltests2.cpp Mat sample = samples.row(si); sample 163 modules/ml/test/test_mltests2.cpp ann->predict( sample, output ); sample 148 modules/videoio/src/cap_gstreamer.cpp GstSample* sample; sample 171 modules/videoio/src/cap_gstreamer.cpp sample = NULL; sample 229 modules/videoio/src/cap_gstreamer.cpp if(sample) sample 230 modules/videoio/src/cap_gstreamer.cpp gst_sample_unref(sample); sample 232 modules/videoio/src/cap_gstreamer.cpp sample = gst_app_sink_pull_sample(GST_APP_SINK(sink)); sample 234 modules/videoio/src/cap_gstreamer.cpp if(!sample) sample 237 modules/videoio/src/cap_gstreamer.cpp buffer = gst_sample_get_buffer(sample); sample 262 modules/videoio/src/cap_gstreamer.cpp GstCaps* buffer_caps = gst_sample_get_caps(sample); sample 4343 modules/videoio/src/cap_msmf.cpp _ComPtr<IMFSample> sample; sample 4397 modules/videoio/src/cap_msmf.cpp hr = MFCreateSample(&sample); sample 4401 modules/videoio/src/cap_msmf.cpp hr = sample->AddBuffer(buffer.Get()); sample 4407 modules/videoio/src/cap_msmf.cpp hr = sample->SetSampleTime(Start); sample 4411 modules/videoio/src/cap_msmf.cpp hr = sample->SetSampleDuration(Duration); sample 4417 modules/videoio/src/cap_msmf.cpp hr = sinkWriter->WriteSample(streamIndex, sample.Get()); sample 157 modules/videoio/src/cap_winrt/CaptureFrameGrabber.cpp void Media::CaptureFrameGrabber::ProcessSample(_In_ MediaSample^ sample) sample 169 modules/videoio/src/cap_winrt/CaptureFrameGrabber.cpp CHK(sample->Sample->ConvertToContiguousBuffer(&buffer)); sample 63 modules/videoio/src/cap_winrt/CaptureFrameGrabber.hpp void ProcessSample(_In_ MediaSample^ sample); sample 172 modules/videoio/src/cap_winrt/MFIncludes.hpp delegate void MediaSampleHandler(MediaSample^ sample); sample 107 modules/videoio/src/cap_winrt/MediaStreamSink.cpp HRESULT MediaStreamSink::ProcessSample(__in_opt IMFSample *sample) sample 109 modules/videoio/src/cap_winrt/MediaStreamSink.cpp return ExceptionBoundary([this, sample]() sample 119 modules/videoio/src/cap_winrt/MediaStreamSink.cpp if (sample == nullptr) sample 124 modules/videoio/src/cap_winrt/MediaStreamSink.cpp mediaSample->Sample = sample; sample 53 modules/videoio/src/cap_winrt/MediaStreamSink.hpp IFACEMETHODIMP ProcessSample(__in_opt IMFSample *sample); sample 23 samples/cpp/em.cpp Mat sample( 1, 2, CV_32FC1 ); sample 50 samples/cpp/em.cpp sample.at<float>(0) = (float)j; sample 51 samples/cpp/em.cpp sample.at<float>(1) = (float)i; sample 52 samples/cpp/em.cpp int response = cvRound(em_model->predict2( sample, noArray() )[1]); sample 129 samples/cpp/letter_recog.cpp Mat sample = data.row(i); sample 131 samples/cpp/letter_recog.cpp float r = model->predict( sample );