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opencv/modules/python/src2/opencv_extra_api.hpp

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#ifndef _OPENCV_API_EXTRA_HPP_
#define _OPENCV_API_EXTRA_HPP_
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d.hpp"
namespace cv
{
template<typename _Tp>
static inline void mv2vv(const vector<Mat>& src, vector<vector<_Tp> >& dst)
{
size_t i, n = src.size();
dst.resize(src.size());
for( i = 0; i < n; i++ )
src[i].copyTo(dst[i]);
}
///////////////////////////// core /////////////////////////////
CV_WRAP_AS(getTickCount) static inline double getTickCount_()
{
return (double)getTickCount();
}
CV_WRAP_AS(getCPUTickCount) static inline double getCPUTickCount_()
{
return (double)getCPUTickCount();
}
CV_WRAP void randShuffle(const Mat& src, CV_OUT Mat& dst, double iterFactor=1.)
{
src.copyTo(dst);
randShuffle(dst, iterFactor, 0);
}
CV_WRAP static inline void SVDecomp(const Mat& src, CV_OUT Mat& w, CV_OUT Mat& u, CV_OUT Mat& vt, int flags=0 )
{
SVD::compute(src, w, u, vt, flags);
}
CV_WRAP static inline void SVBackSubst( const Mat& w, const Mat& u, const Mat& vt,
const Mat& rhs, CV_OUT Mat& dst )
{
SVD::backSubst(w, u, vt, rhs, dst);
}
CV_WRAP static inline void mixChannels(const vector<Mat>& src, vector<Mat>& dst,
const vector<int>& fromTo)
{
if(fromTo.empty())
return;
CV_Assert(fromTo.size()%2 == 0);
mixChannels(&src[0], (int)src.size(), &dst[0], (int)dst.size(), &fromTo[0], (int)(fromTo.size()/2));
}
CV_WRAP static inline bool eigen(const Mat& src, bool computeEigenvectors,
CV_OUT Mat& eigenvalues, CV_OUT Mat& eigenvectors,
int lowindex=-1, int highindex=-1)
{
return computeEigenvectors ? eigen(src, eigenvalues, eigenvectors, lowindex, highindex) :
eigen(src, eigenvalues, lowindex, highindex);
}
CV_WRAP static inline void fillConvexPoly(Mat& img, const Mat& points,
const Scalar& color, int lineType=8,
int shift=0)
{
CV_Assert(points.checkVector(2, CV_32S) >= 0);
fillConvexPoly(img, (const Point*)points.data, points.rows*points.cols*points.channels()/2, color, lineType, shift);
}
CV_WRAP static inline void fillPoly(Mat& img, const vector<Mat>& pts,
const Scalar& color, int lineType=8, int shift=0,
Point offset=Point() )
{
if( pts.empty() )
return;
AutoBuffer<Point*> _ptsptr(pts.size());
AutoBuffer<int> _npts(pts.size());
Point** ptsptr = _ptsptr;
int* npts = _npts;
for( size_t i = 0; i < pts.size(); i++ )
{
const Mat& p = pts[i];
CV_Assert(p.checkVector(2, CV_32S) >= 0);
ptsptr[i] = (Point*)p.data;
npts[i] = p.rows*p.cols*p.channels()/2;
}
fillPoly(img, (const Point**)ptsptr, npts, (int)pts.size(), color, lineType, shift, offset);
}
CV_WRAP static inline void polylines(Mat& img, const vector<Mat>& pts,
bool isClosed, const Scalar& color,
int thickness=1, int lineType=8, int shift=0 )
{
if( pts.empty() )
return;
AutoBuffer<Point*> _ptsptr(pts.size());
AutoBuffer<int> _npts(pts.size());
Point** ptsptr = _ptsptr;
int* npts = _npts;
for( size_t i = 0; i < pts.size(); i++ )
{
const Mat& p = pts[i];
CV_Assert(p.checkVector(2, CV_32S) >= 0);
ptsptr[i] = (Point*)p.data;
npts[i] = p.rows*p.cols*p.channels()/2;
}
polylines(img, (const Point**)ptsptr, npts, (int)pts.size(), isClosed, color, thickness, lineType, shift);
}
CV_WRAP static inline void PCACompute(const Mat& data, CV_OUT Mat& mean,
CV_OUT Mat& eigenvectors, int maxComponents=0)
{
PCA pca;
pca.mean = mean;
pca.eigenvectors = eigenvectors;
pca(data, Mat(), 0, maxComponents);
pca.mean.copyTo(mean);
pca.eigenvectors.copyTo(eigenvectors);
}
CV_WRAP static inline void PCAProject(const Mat& data, const Mat& mean,
const Mat& eigenvectors, CV_OUT Mat& result)
{
PCA pca;
pca.mean = mean;
pca.eigenvectors = eigenvectors;
pca.project(data, result);
}
CV_WRAP static inline void PCABackProject(const Mat& data, const Mat& mean,
const Mat& eigenvectors, CV_OUT Mat& result)
{
PCA pca;
pca.mean = mean;
pca.eigenvectors = eigenvectors;
pca.backProject(data, result);
}
/////////////////////////// imgproc /////////////////////////////////
CV_WRAP static inline void HuMoments(const Moments& m, CV_OUT vector<double>& hu)
{
hu.resize(7);
HuMoments(m, &hu[0]);
}
CV_WRAP static inline Mat getPerspectiveTransform(const vector<Point2f>& src, const vector<Point2f>& dst)
{
CV_Assert(src.size() == 4 && dst.size() == 4);
return getPerspectiveTransform(&src[0], &dst[0]);
}
CV_WRAP static inline Mat getAffineTransform(const vector<Point2f>& src, const vector<Point2f>& dst)
{
CV_Assert(src.size() == 3 && dst.size() == 3);
return getAffineTransform(&src[0], &dst[0]);
}
CV_WRAP static inline void calcHist( const vector<Mat>& images, const vector<int>& channels,
const Mat& mask, CV_OUT Mat& hist,
const vector<int>& histSize,
const vector<float>& ranges,
bool accumulate=false)
{
int i, dims = (int)histSize.size(), rsz = (int)ranges.size(), csz = (int)channels.size();
CV_Assert(images.size() > 0 && dims > 0);
CV_Assert(rsz == dims*2 || (rsz == 0 && images[0].depth() == CV_8U));
CV_Assert(csz == 0 || csz == dims);
float* _ranges[CV_MAX_DIM];
if( rsz > 0 )
{
for( i = 0; i < rsz/2; i++ )
_ranges[i] = (float*)&ranges[i*2];
}
calcHist(&images[0], (int)images.size(), csz ? &channels[0] : 0,
mask, hist, dims, &histSize[0], rsz ? (const float**)_ranges : 0,
true, accumulate);
}
CV_WRAP void calcBackProject( const vector<Mat>& images, const vector<int>& channels,
const Mat& hist, CV_OUT Mat& dst,
const vector<float>& ranges,
double scale=1 )
{
int i, dims = hist.dims, rsz = (int)ranges.size(), csz = (int)channels.size();
CV_Assert(images.size() > 0);
CV_Assert(rsz == dims*2 || (rsz == 0 && images[0].depth() == CV_8U));
CV_Assert(csz == 0 || csz == dims);
float* _ranges[CV_MAX_DIM];
if( rsz > 0 )
{
for( i = 0; i < rsz/2; i++ )
_ranges[i] = (float*)&ranges[i*2];
}
calcBackProject(&images[0], (int)images.size(), csz ? &channels[0] : 0,
hist, dst, rsz ? (const float**)_ranges : 0, scale, true);
}
static void addChildContour(const vector<Mat>& contours,
const Mat& hierarchy,
int i, vector<CvSeq>& seq,
vector<CvSeqBlock>& block)
{
size_t count = contours.size();
for( ; i >= 0; i = ((const Vec4i*)hierarchy.data)[i][0] )
{
const vector<Point>& ci = contours[i];
cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
!ci.empty() ? (void*)&ci[0] : 0, (int)ci.size(),
&seq[i], &block[i] );
const Vec4i h_i = ((const Vec4i*)hierarchy.data)[i];
int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
if( v_next >= 0 )
addChildContour(contours, hierarchy, v_next, seq, block);
}
}
//! draws contours in the image
CV_WRAP static inline void drawContours( Mat& image, const vector<Mat>& contours,
int contourIdx, const Scalar& color,
int thickness=1, int lineType=8,
const Mat& hierarchy=Mat(),
int maxLevel=INT_MAX, Point offset=Point() )
{
CvMat _image = image;
size_t i = 0, first = 0, last = contours.size();
vector<CvSeq> seq;
vector<CvSeqBlock> block;
if( !last )
return;
seq.resize(last);
block.resize(last);
for( i = first; i < last; i++ )
seq[i].first = 0;
if( contourIdx >= 0 )
{
CV_Assert( 0 <= contourIdx && contourIdx < (int)last );
first = contourIdx;
last = contourIdx + 1;
}
for( i = first; i < last; i++ )
{
const Mat& ci = contours[i];
int ci_size = ci.checkVector(2, CV_32S);
CV_Assert( ci_size >= 0 );
cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
ci_size > 0 ? ci.data : 0, ci_size, &seq[i], &block[i] );
}
if( hierarchy.empty() || maxLevel == 0 )
for( i = first; i < last; i++ )
{
seq[i].h_next = i < last-1 ? &seq[i+1] : 0;
seq[i].h_prev = i > first ? &seq[i-1] : 0;
}
else
{
int hsz = hierarchy.checkVector(4, CV_32S);
size_t count = last - first;
CV_Assert((size_t)hsz == contours.size());
if( count == contours.size() )
{
for( i = first; i < last; i++ )
{
const Vec4i& h_i = ((const Vec4i*)hierarchy.data)[i];
int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
}
}
else
{
int child = ((const Vec4i*)hierarchy.data)[first][2];
if( child >= 0 )
{
addChildContour(contours, hierarchy, child, seq, block);
seq[first].v_next = &seq[child];
}
}
}
cvDrawContours( &_image, &seq[first], color, color, contourIdx >= 0 ?
-maxLevel : maxLevel, thickness, lineType, offset );
}
CV_WRAP static inline void approxPolyDP( const Mat& curve,
CV_OUT Mat& approxCurve,
double epsilon, bool closed )
{
if( curve.depth() == CV_32S )
{
vector<Point> result;
approxPolyDP(curve, result, epsilon, closed);
Mat(result).copyTo(approxCurve);
}
else if( curve.depth() == CV_32F )
{
vector<Point2f> result;
approxPolyDP(curve, result, epsilon, closed);
Mat(result).copyTo(approxCurve);
}
else
CV_Error(CV_StsUnsupportedFormat, "");
}
CV_WRAP static inline void convexHull( const Mat& points, CV_OUT Mat& hull, bool returnPoints=true, bool clockwise=false )
{
if( !returnPoints )
{
vector<int> h;
convexHull(points, h, clockwise);
Mat(h).copyTo(hull);
}
else if( points.depth() == CV_32S )
{
vector<Point> h;
convexHull(points, h, clockwise);
Mat(h).copyTo(hull);
}
else if( points.depth() == CV_32F )
{
vector<Point2f> h;
convexHull(points, h, clockwise);
Mat(h).copyTo(hull);
}
}
CV_WRAP static inline void fitLine( const Mat& points, CV_OUT vector<float>& line,
int distType, double param, double reps, double aeps )
{
if(points.channels() == 2 || points.cols == 2)
{
line.resize(4);
fitLine(points, *(Vec4f*)&line[0], distType, param, reps, aeps);
}
else
{
line.resize(6);
fitLine(points, *(Vec6f*)&line[0], distType, param, reps, aeps);
}
}
CV_WRAP static inline int estimateAffine3D( const Mat& from, const Mat& to,
CV_OUT Mat& dst, CV_OUT Mat& outliers,
double param1 = 3.0, double param2 = 0.99 )
{
vector<uchar> outliers_vec;
int res = estimateAffine3D(from, to, dst, outliers_vec, param1, param2);
Mat(outliers_vec).copyTo(outliers);
return res;
}
CV_WRAP static inline void cornerSubPix( const Mat& image, Mat& corners,
Size winSize, Size zeroZone,
TermCriteria criteria )
{
int n = corners.checkVector(2, CV_32F);
CV_Assert(n >= 0);
if( n == 0 )
return;
CvMat _image = image;
cvFindCornerSubPix(&_image, (CvPoint2D32f*)corners.data, n, winSize, zeroZone, criteria);
}
/////////////////////////////// calib3d ///////////////////////////////////////////
CV_WRAP static inline void convertPointsHomogeneous( const Mat& src, CV_OUT Mat& dst )
{
int n;
if( (n = src.checkVector(2)) >= 0 )
dst.create(n, 2, src.depth());
else if( (n = src.checkVector(3)) >= 0 )
dst.create(n, 3, src.depth());
else
CV_Error(CV_StsBadSize, "");
CvMat _src = src, _dst = dst;
cvConvertPointsHomogeneous(&_src, &_dst);
}
//! finds circles' grid pattern of the specified size in the image
CV_WRAP static inline void findCirclesGridDefault( InputArray image, Size patternSize,
OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID )
{
findCirclesGrid(image, patternSize, centers, flags);
}
/*
//! initializes camera matrix from a few 3D points and the corresponding projections.
CV_WRAP static inline Mat initCameraMatrix2D( const vector<Mat>& objectPoints,
const vector<Mat>& imagePoints,
Size imageSize, double aspectRatio=1. )
{
vector<vector<Point3f> > _objectPoints;
vector<vector<Point2f> > _imagePoints;
mv2vv(objectPoints, _objectPoints);
mv2vv(imagePoints, _imagePoints);
return initCameraMatrix2D(_objectPoints, _imagePoints, imageSize, aspectRatio);
}
CV_WRAP static inline double calibrateCamera( const vector<Mat>& objectPoints,
const vector<Mat>& imagePoints,
Size imageSize,
CV_IN_OUT Mat& cameraMatrix,
CV_IN_OUT Mat& distCoeffs,
vector<Mat>& rvecs, vector<Mat>& tvecs,
int flags=0 )
{
vector<vector<Point3f> > _objectPoints;
vector<vector<Point2f> > _imagePoints;
mv2vv(objectPoints, _objectPoints);
mv2vv(imagePoints, _imagePoints);
return calibrateCamera(_objectPoints, _imagePoints, imageSize, cameraMatrix, distCoeffs, rvecs, tvecs, flags);
}
CV_WRAP static inline double stereoCalibrate( const vector<Mat>& objectPoints,
const vector<Mat>& imagePoints1,
const vector<Mat>& imagePoints2,
CV_IN_OUT Mat& cameraMatrix1, CV_IN_OUT Mat& distCoeffs1,
CV_IN_OUT Mat& cameraMatrix2, CV_IN_OUT Mat& distCoeffs2,
Size imageSize, CV_OUT Mat& R, CV_OUT Mat& T,
CV_OUT Mat& E, CV_OUT Mat& F,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+
TermCriteria::EPS, 30, 1e-6),
int flags=CALIB_FIX_INTRINSIC )
{
vector<vector<Point3f> > _objectPoints;
vector<vector<Point2f> > _imagePoints1;
vector<vector<Point2f> > _imagePoints2;
mv2vv(objectPoints, _objectPoints);
mv2vv(imagePoints1, _imagePoints1);
mv2vv(imagePoints2, _imagePoints2);
return stereoCalibrate(_objectPoints, _imagePoints1, _imagePoints2, cameraMatrix1, distCoeffs1,
cameraMatrix2, distCoeffs2, imageSize, R, T, E, F, criteria, flags);
}
CV_WRAP static inline float rectify3Collinear( const Mat& cameraMatrix1, const Mat& distCoeffs1,
const Mat& cameraMatrix2, const Mat& distCoeffs2,
const Mat& cameraMatrix3, const Mat& distCoeffs3,
const vector<Mat>& imgpt1, const vector<Mat>& imgpt3,
Size imageSize, const Mat& R12, const Mat& T12,
const Mat& R13, const Mat& T13,
CV_OUT Mat& R1, CV_OUT Mat& R2, CV_OUT Mat& R3,
CV_OUT Mat& P1, CV_OUT Mat& P2, CV_OUT Mat& P3, CV_OUT Mat& Q,
double alpha, Size newImgSize,
CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags )
{
vector<vector<Point2f> > _imagePoints1;
vector<vector<Point2f> > _imagePoints3;
mv2vv(imgpt1, _imagePoints1);
mv2vv(imgpt3, _imagePoints3);
return rectify3Collinear(cameraMatrix1, distCoeffs1,
cameraMatrix2, distCoeffs2,
cameraMatrix3, distCoeffs3,
_imagePoints1, _imagePoints3, imageSize,
R12, T12, R13, T13, R1, R2, R3, P1, P2, P3,
Q, alpha, newImgSize, roi1, roi2, flags);
}
*/
}
#endif
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