Lines Matching refs:haar
50 // Anton Obukhov, "Haar Classifiers for Object Detection with CUDA"
184 * Haar features solid array.
190 * Haar classifiers flattened trees container.
942 Ncv32u getStageNumWithNotLessThanNclassifiers(Ncv32u N, HaarClassifierCascadeDescriptor &haar,
946 for (; i<haar.NumStages; i++)
961 HaarClassifierCascadeDescriptor &haar,
997 integral.width() >= anchorsRoi.width + haar.ClassifierSize.width &&
998 integral.height() >= anchorsRoi.height + haar.ClassifierSize.height, NCV_DIMENSIONS_INVALID);
1002 ncvAssertReturn(d_HaarStages.length() >= haar.NumStages &&
1003 d_HaarNodes.length() >= haar.NumClassifierTotalNodes &&
1004 d_HaarFeatures.length() >= haar.NumFeatures &&
1006 haar.NumClassifierRootNodes <= haar.NumClassifierTotalNodes, NCV_DIMENSIONS_INVALID);
1008 ncvAssertReturn(haar.bNeedsTiltedII == false || gpuAllocator.isCounting(), NCV_NOIMPL_HAAR_TILTED_FEATURES);
1084 Ncv32f scaleAreaPixels = scaleArea * ((haar.ClassifierSize.width - 2*HAAR_STDDEV_BORDER) *
1085 (haar.ClassifierSize.height - 2*HAAR_STDDEV_BORDER));
1111 (anchorsRoi.height + haar.ClassifierSize.height) * integral.pitch()), NCV_CUDA_ERROR);
1124 d_HaarFeatures.ptr(), cfdTexHaarFeatures,sizeof(HaarFeature64) * haar.NumFeatures), NCV_CUDA_ERROR);
1127 d_HaarNodes.ptr(), cfdTexHaarClassifierNodes, sizeof(HaarClassifierNode128) * haar.NumClassifierTotalNodes), NCV_CUDA_ERROR);
1133 haar, h_HaarStages);
1134 Ncv32u stageEndClassifierParallel = haar.NumStages;
1414 ncvStat = ncvApplyHaarClassifierCascade_host(h_integralImage, h_weights, h_pixelMask, numDetGold, haar,
1549 HaarClassifierCascadeDescriptor &haar,
1590 ncvAssertReturn(d_HaarStages.length() >= haar.NumStages &&
1591 d_HaarNodes.length() >= haar.NumClassifierTotalNodes &&
1592 d_HaarFeatures.length() >= haar.NumFeatures &&
1594 haar.NumClassifierRootNodes <= haar.NumClassifierTotalNodes, NCV_DIMENSIONS_INVALID);
1596 ncvAssertReturn(haar.bNeedsTiltedII == false, NCV_NOIMPL_HAAR_TILTED_FEATURES);
1670 if (haar.ClassifierSize.width * (Ncv32s)scale < minObjSize.width ||
1671 haar.ClassifierSize.height * (Ncv32s)scale < minObjSize.height)
1687 searchRoi.width = scaledIIRoi.width - haar.ClassifierSize.width;
1688 searchRoi.height = scaledIIRoi.height - haar.ClassifierSize.height;
1721 searchRoi.width = scaledIIRoi.width - haar.ClassifierSize.width;
1722 searchRoi.height = scaledIIRoi.height - haar.ClassifierSize.height;
1741 haar.ClassifierSize.width - 2*HAAR_STDDEV_BORDER,
1742 haar.ClassifierSize.height - 2*HAAR_STDDEV_BORDER);
1757 haar, h_HaarStages, d_HaarStages, d_HaarNodes, d_HaarFeatures, false,
1771 haar.ClassifierSize.width,
1772 haar.ClassifierSize.height,
1908 HaarClassifierCascadeDescriptor &haar,
1930 h_integralImage.width() >= anchorsRoi.width + haar.ClassifierSize.width &&
1931 h_integralImage.height() >= anchorsRoi.height + haar.ClassifierSize.height, NCV_DIMENSIONS_INVALID);
1933 ncvAssertReturn(h_HaarStages.length() >= haar.NumStages &&
1934 h_HaarNodes.length() >= haar.NumClassifierTotalNodes &&
1935 h_HaarFeatures.length() >= haar.NumFeatures &&
1937 haar.NumClassifierRootNodes <= haar.NumClassifierTotalNodes, NCV_DIMENSIONS_INVALID);
1938 ncvAssertReturn(haar.bNeedsTiltedII == false, NCV_NOIMPL_HAAR_TILTED_FEATURES);
1941 Ncv32f scaleAreaPixels = scaleArea * ((haar.ClassifierSize.width - 2*HAAR_STDDEV_BORDER) *
1942 (haar.ClassifierSize.height - 2*HAAR_STDDEV_BORDER));
1954 for (Ncv32u iStage = 0; iStage < haar.NumStages; iStage++)
2110 HaarClassifierCascadeDescriptor &haar,
2117 (void) haar;
2126 haar.NumStages = 0;
2127 haar.NumClassifierRootNodes = 0;
2128 haar.NumClassifierTotalNodes = 0;
2129 haar.NumFeatures = 0;
2130 haar.ClassifierSize.width = 0;
2131 haar.ClassifierSize.height = 0;
2132 haar.bHasStumpsOnly = true;
2133 haar.bNeedsTiltedII = false;
2147 haar.ClassifierSize.width = oldCascade->orig_window_size.width;
2148 haar.ClassifierSize.height = oldCascade->orig_window_size.height;
2187 haar.bHasStumpsOnly = false;
2203 haar.bHasStumpsOnly = false;
2208 haar.bNeedsTiltedII = (tiltedVal != 0);
2224 ncvStat = curFeature.setRect(rectX, rectY, rectWidth, rectHeight, haar.ClassifierSize.width, haar.ClassifierSize.height);
2233 ncvStat = tmpFeatureDesc.create(haar.bNeedsTiltedII, bIsLeftNodeLeaf, bIsRightNodeLeaf,
2260 haar.NumStages = static_cast<Ncv32u>(haarStages.size());
2261 haar.NumClassifierRootNodes = static_cast<Ncv32u>(haarClassifierNodes.size());
2262 haar.NumClassifierTotalNodes = static_cast<Ncv32u>(haar.NumClassifierRootNodes + h_TmpClassifierNotRootNodes.size());
2263 haar.NumFeatures = static_cast<Ncv32u>(haarFeatures.size());
2321 HaarClassifierCascadeDescriptor &haar,
2350 haar.NumStages = *(Ncv32u *)(&fdata[0]+dataOffset);
2352 haar.NumClassifierRootNodes = *(Ncv32u *)(&fdata[0]+dataOffset);
2354 haar.NumClassifierTotalNodes = *(Ncv32u *)(&fdata[0]+dataOffset);
2356 haar.NumFeatures = *(Ncv32u *)(&fdata[0]+dataOffset);
2358 haar.ClassifierSize = *(NcvSize32u *)(&fdata[0]+dataOffset);
2360 haar.bNeedsTiltedII = *(NcvBool *)(&fdata[0]+dataOffset);
2362 haar.bHasStumpsOnly = *(NcvBool *)(&fdata[0]+dataOffset);
2365 haarStages.resize(haar.NumStages);
2366 haarClassifierNodes.resize(haar.NumClassifierTotalNodes);
2367 haarFeatures.resize(haar.NumFeatures);
2369 Ncv32u szStages = haar.NumStages * sizeof(HaarStage64);
2370 Ncv32u szClassifiers = haar.NumClassifierTotalNodes * sizeof(HaarClassifierNode128);
2371 Ncv32u szFeatures = haar.NumFeatures * sizeof(HaarFeature64);
2415 HaarClassifierCascadeDescriptor haar;
2420 ncvStat = loadFromXML(filename, haar, haarStages, haarNodes, haarFeatures);
2423 numStages = haar.NumStages;
2424 numNodes = haar.NumClassifierTotalNodes;
2425 numFeatures = haar.NumFeatures;
2437 HaarClassifierCascadeDescriptor &haar,
2457 ncvStat = loadFromNVBIN(filename, haar, haarStages, haarNodes, haarFeatures);
2462 ncvStat = loadFromXML(filename, haar, haarStages, haarNodes, haarFeatures);
2483 HaarClassifierCascadeDescriptor haar,
2488 ncvAssertReturn(h_HaarStages.length() >= haar.NumStages, NCV_INCONSISTENT_INPUT);
2489 ncvAssertReturn(h_HaarNodes.length() >= haar.NumClassifierTotalNodes, NCV_INCONSISTENT_INPUT);
2490 ncvAssertReturn(h_HaarFeatures.length() >= haar.NumFeatures, NCV_INCONSISTENT_INPUT);
2495 Ncv32u szStages = haar.NumStages * sizeof(HaarStage64);
2496 Ncv32u szClassifiers = haar.NumClassifierTotalNodes * sizeof(HaarClassifierNode128);
2497 Ncv32u szFeatures = haar.NumFeatures * sizeof(HaarFeature64);
2508 *(Ncv32u *)(&fdata[0]+dataOffset) = haar.NumStages;
2510 *(Ncv32u *)(&fdata[0]+dataOffset) = haar.NumClassifierRootNodes;
2512 *(Ncv32u *)(&fdata[0]+dataOffset) = haar.NumClassifierTotalNodes;
2514 *(Ncv32u *)(&fdata[0]+dataOffset) = haar.NumFeatures;
2516 *(NcvSize32u *)(&fdata[0]+dataOffset) = haar.ClassifierSize;
2518 *(NcvBool *)(&fdata[0]+dataOffset) = haar.bNeedsTiltedII;
2520 *(NcvBool *)(&fdata[0]+dataOffset) = haar.bHasStumpsOnly;
