1270 lines
61 KiB
C#
1270 lines
61 KiB
C#
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using OpenCVForUnity.CoreModule;
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using OpenCVForUnity.UtilsModule;
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using System;
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using System.Collections.Generic;
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using System.Runtime.InteropServices;
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namespace OpenCVForUnity.ObjdetectModule
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{
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// C++: class HOGDescriptor
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/**
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* Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector.
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*
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* the HOG descriptor algorithm introduced by Navneet Dalal and Bill Triggs CITE: Dalal2005 .
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*
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* useful links:
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*
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* https://hal.inria.fr/inria-00548512/document/
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*
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* https://en.wikipedia.org/wiki/Histogram_of_oriented_gradients
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*
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* https://software.intel.com/en-us/ipp-dev-reference-histogram-of-oriented-gradients-hog-descriptor
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*
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* http://www.learnopencv.com/histogram-of-oriented-gradients
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*
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* http://www.learnopencv.com/handwritten-digits-classification-an-opencv-c-python-tutorial
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*/
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public class HOGDescriptor : DisposableOpenCVObject
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{
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protected override void Dispose(bool disposing)
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{
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try
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{
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if (disposing)
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{
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}
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if (IsEnabledDispose)
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{
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if (nativeObj != IntPtr.Zero)
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objdetect_HOGDescriptor_delete(nativeObj);
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nativeObj = IntPtr.Zero;
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}
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}
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finally
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{
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base.Dispose(disposing);
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}
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}
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protected internal HOGDescriptor(IntPtr addr) : base(addr) { }
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public IntPtr getNativeObjAddr() { return nativeObj; }
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// internal usage only
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public static HOGDescriptor __fromPtr__(IntPtr addr) { return new HOGDescriptor(addr); }
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// C++: enum <unnamed>
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public const int DEFAULT_NLEVELS = 64;
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// C++: enum cv.HOGDescriptor.DescriptorStorageFormat
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public const int DESCR_FORMAT_COL_BY_COL = 0;
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public const int DESCR_FORMAT_ROW_BY_ROW = 1;
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// C++: enum cv.HOGDescriptor.HistogramNormType
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public const int L2Hys = 0;
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//
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// C++: cv::HOGDescriptor::HOGDescriptor()
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//
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/**
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* Creates the HOG descriptor and detector with default parameters.
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*
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* aqual to HOGDescriptor(Size(64,128), Size(16,16), Size(8,8), Size(8,8), 9 )
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*/
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public HOGDescriptor()
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_10());
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}
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//
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// C++: cv::HOGDescriptor::HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture = 1, double _winSigma = -1, HOGDescriptor_HistogramNormType _histogramNormType = HOGDescriptor::L2Hys, double _L2HysThreshold = 0.2, bool _gammaCorrection = false, int _nlevels = HOGDescriptor::DEFAULT_NLEVELS, bool _signedGradient = false)
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//
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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* param _histogramNormType sets histogramNormType with given value.
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* param _L2HysThreshold sets L2HysThreshold with given value.
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* param _gammaCorrection sets gammaCorrection with given value.
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* param _nlevels sets nlevels with given value.
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* param _signedGradient sets signedGradient with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, bool _gammaCorrection, int _nlevels, bool _signedGradient)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_11(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma, _histogramNormType, _L2HysThreshold, _gammaCorrection, _nlevels, _signedGradient));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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* param _histogramNormType sets histogramNormType with given value.
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* param _L2HysThreshold sets L2HysThreshold with given value.
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* param _gammaCorrection sets gammaCorrection with given value.
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* param _nlevels sets nlevels with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, bool _gammaCorrection, int _nlevels)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_12(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma, _histogramNormType, _L2HysThreshold, _gammaCorrection, _nlevels));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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* param _histogramNormType sets histogramNormType with given value.
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* param _L2HysThreshold sets L2HysThreshold with given value.
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* param _gammaCorrection sets gammaCorrection with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, bool _gammaCorrection)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_13(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma, _histogramNormType, _L2HysThreshold, _gammaCorrection));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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* param _histogramNormType sets histogramNormType with given value.
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* param _L2HysThreshold sets L2HysThreshold with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_14(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma, _histogramNormType, _L2HysThreshold));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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* param _histogramNormType sets histogramNormType with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_15(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma, _histogramNormType));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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* param _winSigma sets winSigma with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture, double _winSigma)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_16(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture, _winSigma));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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* param _derivAperture sets derivAperture with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_17(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins, _derivAperture));
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}
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/**
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*
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* param _winSize sets winSize with given value.
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* param _blockSize sets blockSize with given value.
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* param _blockStride sets blockStride with given value.
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* param _cellSize sets cellSize with given value.
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* param _nbins sets nbins with given value.
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*/
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public HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_18(_winSize.width, _winSize.height, _blockSize.width, _blockSize.height, _blockStride.width, _blockStride.height, _cellSize.width, _cellSize.height, _nbins));
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}
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//
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// C++: cv::HOGDescriptor::HOGDescriptor(String filename)
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//
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/**
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*
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*
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* Creates the HOG descriptor and detector and loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file.
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* param filename The file name containing HOGDescriptor properties and coefficients for the linear SVM classifier.
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*/
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public HOGDescriptor(string filename)
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{
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nativeObj = DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_HOGDescriptor_19(filename));
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}
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//
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// C++: size_t cv::HOGDescriptor::getDescriptorSize()
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//
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/**
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* Returns the number of coefficients required for the classification.
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* return automatically generated
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*/
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public long getDescriptorSize()
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{
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ThrowIfDisposed();
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return objdetect_HOGDescriptor_getDescriptorSize_10(nativeObj);
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}
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//
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// C++: bool cv::HOGDescriptor::checkDetectorSize()
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//
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/**
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* Checks if detector size equal to descriptor size.
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* return automatically generated
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*/
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public bool checkDetectorSize()
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{
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ThrowIfDisposed();
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return objdetect_HOGDescriptor_checkDetectorSize_10(nativeObj);
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}
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//
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// C++: double cv::HOGDescriptor::getWinSigma()
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//
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/**
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* Returns winSigma value
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* return automatically generated
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*/
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public double getWinSigma()
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{
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ThrowIfDisposed();
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return objdetect_HOGDescriptor_getWinSigma_10(nativeObj);
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}
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//
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// C++: void cv::HOGDescriptor::setSVMDetector(Mat svmdetector)
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//
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/**
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* Sets coefficients for the linear SVM classifier.
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* param svmdetector coefficients for the linear SVM classifier.
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*/
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public void setSVMDetector(Mat svmdetector)
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{
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ThrowIfDisposed();
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if (svmdetector != null) svmdetector.ThrowIfDisposed();
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objdetect_HOGDescriptor_setSVMDetector_10(nativeObj, svmdetector.nativeObj);
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}
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//
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// C++: bool cv::HOGDescriptor::load(String filename, String objname = String())
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//
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/**
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* loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file
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* param filename Name of the file to read.
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* param objname The optional name of the node to read (if empty, the first top-level node will be used).
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||
|
|
* return automatically generated
|
||
|
|
*/
|
||
|
|
public bool load(string filename, string objname)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_load_10(nativeObj, filename, objname);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* loads HOGDescriptor parameters and coefficients for the linear SVM classifier from a file
|
||
|
|
* param filename Name of the file to read.
|
||
|
|
* return automatically generated
|
||
|
|
*/
|
||
|
|
public bool load(string filename)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_load_11(nativeObj, filename);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: void cv::HOGDescriptor::save(String filename, String objname = String())
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* saves HOGDescriptor parameters and coefficients for the linear SVM classifier to a file
|
||
|
|
* param filename File name
|
||
|
|
* param objname Object name
|
||
|
|
*/
|
||
|
|
public void save(string filename, string objname)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
objdetect_HOGDescriptor_save_10(nativeObj, filename, objname);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* saves HOGDescriptor parameters and coefficients for the linear SVM classifier to a file
|
||
|
|
* param filename File name
|
||
|
|
*/
|
||
|
|
public void save(string filename)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
objdetect_HOGDescriptor_save_11(nativeObj, filename);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: void cv::HOGDescriptor::compute(Mat img, vector_float& descriptors, Size winStride = Size(), Size padding = Size(), vector_Point locations = std::vector<Point>())
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes HOG descriptors of given image.
|
||
|
|
* param img Matrix of the type CV_8U containing an image where HOG features will be calculated.
|
||
|
|
* param descriptors Matrix of the type CV_32F
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* param locations Vector of Point
|
||
|
|
*/
|
||
|
|
public void compute(Mat img, MatOfFloat descriptors, Size winStride, Size padding, MatOfPoint locations)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (descriptors != null) descriptors.ThrowIfDisposed();
|
||
|
|
if (locations != null) locations.ThrowIfDisposed();
|
||
|
|
Mat descriptors_mat = descriptors;
|
||
|
|
Mat locations_mat = locations;
|
||
|
|
objdetect_HOGDescriptor_compute_10(nativeObj, img.nativeObj, descriptors_mat.nativeObj, winStride.width, winStride.height, padding.width, padding.height, locations_mat.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes HOG descriptors of given image.
|
||
|
|
* param img Matrix of the type CV_8U containing an image where HOG features will be calculated.
|
||
|
|
* param descriptors Matrix of the type CV_32F
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
*/
|
||
|
|
public void compute(Mat img, MatOfFloat descriptors, Size winStride, Size padding)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (descriptors != null) descriptors.ThrowIfDisposed();
|
||
|
|
Mat descriptors_mat = descriptors;
|
||
|
|
objdetect_HOGDescriptor_compute_11(nativeObj, img.nativeObj, descriptors_mat.nativeObj, winStride.width, winStride.height, padding.width, padding.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes HOG descriptors of given image.
|
||
|
|
* param img Matrix of the type CV_8U containing an image where HOG features will be calculated.
|
||
|
|
* param descriptors Matrix of the type CV_32F
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
*/
|
||
|
|
public void compute(Mat img, MatOfFloat descriptors, Size winStride)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (descriptors != null) descriptors.ThrowIfDisposed();
|
||
|
|
Mat descriptors_mat = descriptors;
|
||
|
|
objdetect_HOGDescriptor_compute_12(nativeObj, img.nativeObj, descriptors_mat.nativeObj, winStride.width, winStride.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes HOG descriptors of given image.
|
||
|
|
* param img Matrix of the type CV_8U containing an image where HOG features will be calculated.
|
||
|
|
* param descriptors Matrix of the type CV_32F
|
||
|
|
*/
|
||
|
|
public void compute(Mat img, MatOfFloat descriptors)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (descriptors != null) descriptors.ThrowIfDisposed();
|
||
|
|
Mat descriptors_mat = descriptors;
|
||
|
|
objdetect_HOGDescriptor_compute_13(nativeObj, img.nativeObj, descriptors_mat.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: void cv::HOGDescriptor::detect(Mat img, vector_Point& foundLocations, vector_double& weights, double hitThreshold = 0, Size winStride = Size(), Size padding = Size(), vector_Point searchLocations = std::vector<Point>())
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Performs object detection without a multi-scale window.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries.
|
||
|
|
* param weights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* param searchLocations Vector of Point includes set of requested locations to be evaluated.
|
||
|
|
*/
|
||
|
|
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride, Size padding, MatOfPoint searchLocations)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (weights != null) weights.ThrowIfDisposed();
|
||
|
|
if (searchLocations != null) searchLocations.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat weights_mat = weights;
|
||
|
|
Mat searchLocations_mat = searchLocations;
|
||
|
|
objdetect_HOGDescriptor_detect_10(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height, searchLocations_mat.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Performs object detection without a multi-scale window.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries.
|
||
|
|
* param weights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
*/
|
||
|
|
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride, Size padding)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (weights != null) weights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat weights_mat = weights;
|
||
|
|
objdetect_HOGDescriptor_detect_11(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Performs object detection without a multi-scale window.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries.
|
||
|
|
* param weights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
*/
|
||
|
|
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold, Size winStride)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (weights != null) weights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat weights_mat = weights;
|
||
|
|
objdetect_HOGDescriptor_detect_12(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj, hitThreshold, winStride.width, winStride.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Performs object detection without a multi-scale window.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries.
|
||
|
|
* param weights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
*/
|
||
|
|
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights, double hitThreshold)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (weights != null) weights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat weights_mat = weights;
|
||
|
|
objdetect_HOGDescriptor_detect_13(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj, hitThreshold);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Performs object detection without a multi-scale window.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of point where each point contains left-top corner point of detected object boundaries.
|
||
|
|
* param weights Vector that will contain confidence values for each detected object.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
*/
|
||
|
|
public void detect(Mat img, MatOfPoint foundLocations, MatOfDouble weights)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (weights != null) weights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat weights_mat = weights;
|
||
|
|
objdetect_HOGDescriptor_detect_14(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, weights_mat.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: void cv::HOGDescriptor::detectMultiScale(Mat img, vector_Rect& foundLocations, vector_double& foundWeights, double hitThreshold = 0, Size winStride = Size(), Size padding = Size(), double scale = 1.05, double groupThreshold = 2.0, bool useMeanshiftGrouping = false)
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* param scale Coefficient of the detection window increase.
|
||
|
|
* param groupThreshold Coefficient to regulate the similarity threshold. When detected, some objects can be covered
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
* param useMeanshiftGrouping indicates grouping algorithm
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale, double groupThreshold, bool useMeanshiftGrouping)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_10(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height, scale, groupThreshold, useMeanshiftGrouping);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* param scale Coefficient of the detection window increase.
|
||
|
|
* param groupThreshold Coefficient to regulate the similarity threshold. When detected, some objects can be covered
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale, double groupThreshold)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_11(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height, scale, groupThreshold);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* param scale Coefficient of the detection window increase.
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding, double scale)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_12(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height, scale);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* param padding Padding
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride, Size padding)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_13(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height, padding.width, padding.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* param winStride Window stride. It must be a multiple of block stride.
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold, Size winStride)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_14(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold, winStride.width, winStride.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* param hitThreshold Threshold for the distance between features and SVM classifying plane.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights, double hitThreshold)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_15(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj, hitThreshold);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Detects objects of different sizes in the input image. The detected objects are returned as a list
|
||
|
|
* of rectangles.
|
||
|
|
* param img Matrix of the type CV_8U or CV_8UC3 containing an image where objects are detected.
|
||
|
|
* param foundLocations Vector of rectangles where each rectangle contains the detected object.
|
||
|
|
* param foundWeights Vector that will contain confidence values for each detected object.
|
||
|
|
* Usually it is 0 and should be specified in the detector coefficients (as the last free coefficient).
|
||
|
|
* But if the free coefficient is omitted (which is allowed), you can specify it manually here.
|
||
|
|
* by many rectangles. 0 means not to perform grouping.
|
||
|
|
*/
|
||
|
|
public void detectMultiScale(Mat img, MatOfRect foundLocations, MatOfDouble foundWeights)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (foundLocations != null) foundLocations.ThrowIfDisposed();
|
||
|
|
if (foundWeights != null) foundWeights.ThrowIfDisposed();
|
||
|
|
Mat foundLocations_mat = foundLocations;
|
||
|
|
Mat foundWeights_mat = foundWeights;
|
||
|
|
objdetect_HOGDescriptor_detectMultiScale_16(nativeObj, img.nativeObj, foundLocations_mat.nativeObj, foundWeights_mat.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: void cv::HOGDescriptor::computeGradient(Mat img, Mat& grad, Mat& angleOfs, Size paddingTL = Size(), Size paddingBR = Size())
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes gradients and quantized gradient orientations.
|
||
|
|
* param img Matrix contains the image to be computed
|
||
|
|
* param grad Matrix of type CV_32FC2 contains computed gradients
|
||
|
|
* param angleOfs Matrix of type CV_8UC2 contains quantized gradient orientations
|
||
|
|
* param paddingTL Padding from top-left
|
||
|
|
* param paddingBR Padding from bottom-right
|
||
|
|
*/
|
||
|
|
public void computeGradient(Mat img, Mat grad, Mat angleOfs, Size paddingTL, Size paddingBR)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (grad != null) grad.ThrowIfDisposed();
|
||
|
|
if (angleOfs != null) angleOfs.ThrowIfDisposed();
|
||
|
|
|
||
|
|
objdetect_HOGDescriptor_computeGradient_10(nativeObj, img.nativeObj, grad.nativeObj, angleOfs.nativeObj, paddingTL.width, paddingTL.height, paddingBR.width, paddingBR.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes gradients and quantized gradient orientations.
|
||
|
|
* param img Matrix contains the image to be computed
|
||
|
|
* param grad Matrix of type CV_32FC2 contains computed gradients
|
||
|
|
* param angleOfs Matrix of type CV_8UC2 contains quantized gradient orientations
|
||
|
|
* param paddingTL Padding from top-left
|
||
|
|
*/
|
||
|
|
public void computeGradient(Mat img, Mat grad, Mat angleOfs, Size paddingTL)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (grad != null) grad.ThrowIfDisposed();
|
||
|
|
if (angleOfs != null) angleOfs.ThrowIfDisposed();
|
||
|
|
|
||
|
|
objdetect_HOGDescriptor_computeGradient_11(nativeObj, img.nativeObj, grad.nativeObj, angleOfs.nativeObj, paddingTL.width, paddingTL.height);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Computes gradients and quantized gradient orientations.
|
||
|
|
* param img Matrix contains the image to be computed
|
||
|
|
* param grad Matrix of type CV_32FC2 contains computed gradients
|
||
|
|
* param angleOfs Matrix of type CV_8UC2 contains quantized gradient orientations
|
||
|
|
*/
|
||
|
|
public void computeGradient(Mat img, Mat grad, Mat angleOfs)
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
if (img != null) img.ThrowIfDisposed();
|
||
|
|
if (grad != null) grad.ThrowIfDisposed();
|
||
|
|
if (angleOfs != null) angleOfs.ThrowIfDisposed();
|
||
|
|
|
||
|
|
objdetect_HOGDescriptor_computeGradient_12(nativeObj, img.nativeObj, grad.nativeObj, angleOfs.nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: static vector_float cv::HOGDescriptor::getDefaultPeopleDetector()
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns coefficients of the classifier trained for people detection (for 64x128 windows).
|
||
|
|
* return automatically generated
|
||
|
|
*/
|
||
|
|
public static MatOfFloat getDefaultPeopleDetector()
|
||
|
|
{
|
||
|
|
|
||
|
|
|
||
|
|
return MatOfFloat.fromNativeAddr(DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_getDefaultPeopleDetector_10()));
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: static vector_float cv::HOGDescriptor::getDaimlerPeopleDetector()
|
||
|
|
//
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns coefficients of the classifier trained for people detection (for 48x96 windows).
|
||
|
|
* return automatically generated
|
||
|
|
*/
|
||
|
|
public static MatOfFloat getDaimlerPeopleDetector()
|
||
|
|
{
|
||
|
|
|
||
|
|
|
||
|
|
return MatOfFloat.fromNativeAddr(DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_getDaimlerPeopleDetector_10()));
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: Size HOGDescriptor::winSize
|
||
|
|
//
|
||
|
|
|
||
|
|
public Size get_winSize()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
double[] tmpArray = new double[2];
|
||
|
|
objdetect_HOGDescriptor_get_1winSize_10(nativeObj, tmpArray);
|
||
|
|
Size retVal = new Size(tmpArray);
|
||
|
|
|
||
|
|
return retVal;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: Size HOGDescriptor::blockSize
|
||
|
|
//
|
||
|
|
|
||
|
|
public Size get_blockSize()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
double[] tmpArray = new double[2];
|
||
|
|
objdetect_HOGDescriptor_get_1blockSize_10(nativeObj, tmpArray);
|
||
|
|
Size retVal = new Size(tmpArray);
|
||
|
|
|
||
|
|
return retVal;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: Size HOGDescriptor::blockStride
|
||
|
|
//
|
||
|
|
|
||
|
|
public Size get_blockStride()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
double[] tmpArray = new double[2];
|
||
|
|
objdetect_HOGDescriptor_get_1blockStride_10(nativeObj, tmpArray);
|
||
|
|
Size retVal = new Size(tmpArray);
|
||
|
|
|
||
|
|
return retVal;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: Size HOGDescriptor::cellSize
|
||
|
|
//
|
||
|
|
|
||
|
|
public Size get_cellSize()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
double[] tmpArray = new double[2];
|
||
|
|
objdetect_HOGDescriptor_get_1cellSize_10(nativeObj, tmpArray);
|
||
|
|
Size retVal = new Size(tmpArray);
|
||
|
|
|
||
|
|
return retVal;
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: int HOGDescriptor::nbins
|
||
|
|
//
|
||
|
|
|
||
|
|
public int get_nbins()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1nbins_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: int HOGDescriptor::derivAperture
|
||
|
|
//
|
||
|
|
|
||
|
|
public int get_derivAperture()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1derivAperture_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: double HOGDescriptor::winSigma
|
||
|
|
//
|
||
|
|
|
||
|
|
public double get_winSigma()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1winSigma_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: HOGDescriptor_HistogramNormType HOGDescriptor::histogramNormType
|
||
|
|
//
|
||
|
|
|
||
|
|
public int get_histogramNormType()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1histogramNormType_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: double HOGDescriptor::L2HysThreshold
|
||
|
|
//
|
||
|
|
|
||
|
|
public double get_L2HysThreshold()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1L2HysThreshold_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: bool HOGDescriptor::gammaCorrection
|
||
|
|
//
|
||
|
|
|
||
|
|
public bool get_gammaCorrection()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1gammaCorrection_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: vector_float HOGDescriptor::svmDetector
|
||
|
|
//
|
||
|
|
|
||
|
|
public MatOfFloat get_svmDetector()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return MatOfFloat.fromNativeAddr(DisposableObject.ThrowIfNullIntPtr(objdetect_HOGDescriptor_get_1svmDetector_10(nativeObj)));
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: int HOGDescriptor::nlevels
|
||
|
|
//
|
||
|
|
|
||
|
|
public int get_nlevels()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1nlevels_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
//
|
||
|
|
// C++: bool HOGDescriptor::signedGradient
|
||
|
|
//
|
||
|
|
|
||
|
|
public bool get_signedGradient()
|
||
|
|
{
|
||
|
|
ThrowIfDisposed();
|
||
|
|
|
||
|
|
return objdetect_HOGDescriptor_get_1signedGradient_10(nativeObj);
|
||
|
|
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
|
||
|
|
const string LIBNAME = "__Internal";
|
||
|
|
#else
|
||
|
|
const string LIBNAME = "opencvforunity";
|
||
|
|
#endif
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
// C++: cv::HOGDescriptor::HOGDescriptor()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_10();
|
||
|
|
|
||
|
|
// C++: cv::HOGDescriptor::HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride, Size _cellSize, int _nbins, int _derivAperture = 1, double _winSigma = -1, HOGDescriptor_HistogramNormType _histogramNormType = HOGDescriptor::L2Hys, double _L2HysThreshold = 0.2, bool _gammaCorrection = false, int _nlevels = HOGDescriptor::DEFAULT_NLEVELS, bool _signedGradient = false)
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_11(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, [MarshalAs(UnmanagedType.U1)] bool _gammaCorrection, int _nlevels, [MarshalAs(UnmanagedType.U1)] bool _signedGradient);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_12(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, [MarshalAs(UnmanagedType.U1)] bool _gammaCorrection, int _nlevels);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_13(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold, [MarshalAs(UnmanagedType.U1)] bool _gammaCorrection);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_14(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType, double _L2HysThreshold);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_15(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma, int _histogramNormType);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_16(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture, double _winSigma);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_17(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins, int _derivAperture);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_18(double _winSize_width, double _winSize_height, double _blockSize_width, double _blockSize_height, double _blockStride_width, double _blockStride_height, double _cellSize_width, double _cellSize_height, int _nbins);
|
||
|
|
|
||
|
|
// C++: cv::HOGDescriptor::HOGDescriptor(String filename)
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_HOGDescriptor_19(string filename);
|
||
|
|
|
||
|
|
// C++: size_t cv::HOGDescriptor::getDescriptorSize()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern long objdetect_HOGDescriptor_getDescriptorSize_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: bool cv::HOGDescriptor::checkDetectorSize()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
[return: MarshalAs(UnmanagedType.U1)]
|
||
|
|
private static extern bool objdetect_HOGDescriptor_checkDetectorSize_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: double cv::HOGDescriptor::getWinSigma()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern double objdetect_HOGDescriptor_getWinSigma_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::setSVMDetector(Mat svmdetector)
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_setSVMDetector_10(IntPtr nativeObj, IntPtr svmdetector_nativeObj);
|
||
|
|
|
||
|
|
// C++: bool cv::HOGDescriptor::load(String filename, String objname = String())
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
[return: MarshalAs(UnmanagedType.U1)]
|
||
|
|
private static extern bool objdetect_HOGDescriptor_load_10(IntPtr nativeObj, string filename, string objname);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
[return: MarshalAs(UnmanagedType.U1)]
|
||
|
|
private static extern bool objdetect_HOGDescriptor_load_11(IntPtr nativeObj, string filename);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::save(String filename, String objname = String())
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_save_10(IntPtr nativeObj, string filename, string objname);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_save_11(IntPtr nativeObj, string filename);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::compute(Mat img, vector_float& descriptors, Size winStride = Size(), Size padding = Size(), vector_Point locations = std::vector<Point>())
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_compute_10(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr descriptors_mat_nativeObj, double winStride_width, double winStride_height, double padding_width, double padding_height, IntPtr locations_mat_nativeObj);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_compute_11(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr descriptors_mat_nativeObj, double winStride_width, double winStride_height, double padding_width, double padding_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_compute_12(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr descriptors_mat_nativeObj, double winStride_width, double winStride_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_compute_13(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr descriptors_mat_nativeObj);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::detect(Mat img, vector_Point& foundLocations, vector_double& weights, double hitThreshold = 0, Size winStride = Size(), Size padding = Size(), vector_Point searchLocations = std::vector<Point>())
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detect_10(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr weights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height, IntPtr searchLocations_mat_nativeObj);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detect_11(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr weights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detect_12(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr weights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detect_13(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr weights_mat_nativeObj, double hitThreshold);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detect_14(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr weights_mat_nativeObj);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::detectMultiScale(Mat img, vector_Rect& foundLocations, vector_double& foundWeights, double hitThreshold = 0, Size winStride = Size(), Size padding = Size(), double scale = 1.05, double groupThreshold = 2.0, bool useMeanshiftGrouping = false)
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_10(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height, double scale, double groupThreshold, [MarshalAs(UnmanagedType.U1)] bool useMeanshiftGrouping);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_11(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height, double scale, double groupThreshold);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_12(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height, double scale);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_13(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height, double padding_width, double padding_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_14(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold, double winStride_width, double winStride_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_15(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj, double hitThreshold);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_detectMultiScale_16(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr foundLocations_mat_nativeObj, IntPtr foundWeights_mat_nativeObj);
|
||
|
|
|
||
|
|
// C++: void cv::HOGDescriptor::computeGradient(Mat img, Mat& grad, Mat& angleOfs, Size paddingTL = Size(), Size paddingBR = Size())
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_computeGradient_10(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr grad_nativeObj, IntPtr angleOfs_nativeObj, double paddingTL_width, double paddingTL_height, double paddingBR_width, double paddingBR_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_computeGradient_11(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr grad_nativeObj, IntPtr angleOfs_nativeObj, double paddingTL_width, double paddingTL_height);
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_computeGradient_12(IntPtr nativeObj, IntPtr img_nativeObj, IntPtr grad_nativeObj, IntPtr angleOfs_nativeObj);
|
||
|
|
|
||
|
|
// C++: static vector_float cv::HOGDescriptor::getDefaultPeopleDetector()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_getDefaultPeopleDetector_10();
|
||
|
|
|
||
|
|
// C++: static vector_float cv::HOGDescriptor::getDaimlerPeopleDetector()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_getDaimlerPeopleDetector_10();
|
||
|
|
|
||
|
|
// C++: Size HOGDescriptor::winSize
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_get_1winSize_10(IntPtr nativeObj, double[] retVal);
|
||
|
|
|
||
|
|
// C++: Size HOGDescriptor::blockSize
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_get_1blockSize_10(IntPtr nativeObj, double[] retVal);
|
||
|
|
|
||
|
|
// C++: Size HOGDescriptor::blockStride
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_get_1blockStride_10(IntPtr nativeObj, double[] retVal);
|
||
|
|
|
||
|
|
// C++: Size HOGDescriptor::cellSize
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_get_1cellSize_10(IntPtr nativeObj, double[] retVal);
|
||
|
|
|
||
|
|
// C++: int HOGDescriptor::nbins
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern int objdetect_HOGDescriptor_get_1nbins_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: int HOGDescriptor::derivAperture
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern int objdetect_HOGDescriptor_get_1derivAperture_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: double HOGDescriptor::winSigma
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern double objdetect_HOGDescriptor_get_1winSigma_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: HOGDescriptor_HistogramNormType HOGDescriptor::histogramNormType
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern int objdetect_HOGDescriptor_get_1histogramNormType_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: double HOGDescriptor::L2HysThreshold
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern double objdetect_HOGDescriptor_get_1L2HysThreshold_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: bool HOGDescriptor::gammaCorrection
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
[return: MarshalAs(UnmanagedType.U1)]
|
||
|
|
private static extern bool objdetect_HOGDescriptor_get_1gammaCorrection_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: vector_float HOGDescriptor::svmDetector
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern IntPtr objdetect_HOGDescriptor_get_1svmDetector_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: int HOGDescriptor::nlevels
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern int objdetect_HOGDescriptor_get_1nlevels_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// C++: bool HOGDescriptor::signedGradient
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
[return: MarshalAs(UnmanagedType.U1)]
|
||
|
|
private static extern bool objdetect_HOGDescriptor_get_1signedGradient_10(IntPtr nativeObj);
|
||
|
|
|
||
|
|
// native support for java finalize()
|
||
|
|
[DllImport(LIBNAME)]
|
||
|
|
private static extern void objdetect_HOGDescriptor_delete(IntPtr nativeObj);
|
||
|
|
|
||
|
|
}
|
||
|
|
}
|