extended Python bindings; not merged into cv.cpp yet; and many of the helper functions, like pyopencv_to_*, pyopencv_from_* etc. are still missing
This commit is contained in:
Vadim Pisarevsky
parent
893fb90b87
commit
00ec555252
@ -3847,10 +3847,21 @@ static int zero = 0;
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#include "generated0.i"
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#include "opencv2x.h"
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static PyMethodDef methods[] = {
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#if PYTHON_USE_NUMPY
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{"fromarray", (PyCFunction)pycvfromarray, METH_KEYWORDS, "fromarray(array) -> cvmatnd"},
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{"fromarray", (PyCFunction)pycvfromarray, METH_KEYWORDS, "fromarray(array) -> cvmatnd"},
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{"absdiff", (PyCFunction)cv::pyopencv_absdiff, METH_KEYWORDS, "absdiff(src1,src2,dst=None) -> dst"},
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{"add", (PyCFunction)cv::pyopencv_add, METH_KEYWORDS, "add(src1,src2,dst=None,mask=None) -> dst"},
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{"bitwise_and", (PyCFunction)cv::pyopencv_and, METH_KEYWORDS, "bitwise_and(src1,src2,dst=None,mask=None) -> dst"},
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{"bitwise_or", (PyCFunction)cv::pyopencv_or, METH_KEYWORDS, "bitwise_or(src1,src2,dst=None,mask=None) -> dst"},
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{"bitwise_xor", (PyCFunction)cv::pyopencv_xor, METH_KEYWORDS, "bitwise_xor(src1,src2,dst=None,mask=None) -> dst"},
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{"max", (PyCFunction)cv::pyopencv_max, METH_KEYWORDS, "max(src1,src2,dst=None) -> dst"},
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{"min", (PyCFunction)cv::pyopencv_min, METH_KEYWORDS, "min(src1,src2,dst=None) -> dst"},
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{"subtract", (PyCFunction)cv::pyopencv_subtract, METH_KEYWORDS, "subtract(src1,src2,dst=None,mask=None) -> dst"},
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#endif
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//{"CalcOpticalFlowFarneback", (PyCFunction)pycvCalcOpticalFlowFarneback, METH_KEYWORDS, "CalcOpticalFlowFarneback(prev, next, flow, pyr_scale=0.5, levels=3, win_size=15, iterations=3, poly_n=7, poly_sigma=1.5, flags=0) -> None"},
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@ -3887,6 +3898,10 @@ __declspec(dllexport)
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void initcv()
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{
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#if PYTHON_USE_NUMPY
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import_array();
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#endif
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PyObject *m, *d;
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cvSetErrMode(CV_ErrModeParent);
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525
modules/python/opencv_api_extra.hpp
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525
modules/python/opencv_api_extra.hpp
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@ -0,0 +1,525 @@
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#ifndef _OPENCV_API_EXTRA_HPP_
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#define _OPENCV_API_EXTRA_HPP_
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#include "opencv2/core/core.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/calib3d/calib3d.hpp"
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namespace cv
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{
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template<typename _Tp>
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static inline void mv2vv(const vector<Mat>& src, vector<vector<_Tp> >& dst)
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{
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size_t i, n = src.size();
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dst.resize(src.size());
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for( i = 0; i < n; i++ )
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src[i].copyTo(dst[i]);
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}
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///////////////////////////// core /////////////////////////////
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CV_WRAP_AS(getTickCount) static inline double getTickCount_()
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{
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return (double)getTickCount();
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}
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CV_WRAP_AS(getCPUTickCount) static inline double getCPUTickCount_()
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{
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return (double)getCPUTickCount();
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}
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CV_WRAP static inline void SVDecomp(const Mat& src, CV_OUT Mat& w, CV_OUT Mat& u, CV_OUT Mat& vt, int flags=0 )
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{
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SVD::compute(src, w, u, vt, flags);
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}
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CV_WRAP static inline void SVDBackSubst( const Mat& w, const Mat& u, const Mat& vt,
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const Mat& rhs, CV_OUT Mat& dst )
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{
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SVD::backSubst(w, u, vt, rhs, dst);
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}
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CV_WRAP static inline void mixChannels(const vector<Mat>& src, vector<Mat>& dst,
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const vector<int>& fromTo)
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{
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if(fromTo.empty())
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return;
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CV_Assert(fromTo.size()%2 == 0);
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mixChannels(&src[0], (int)src.size(), &dst[0], (int)dst.size(), &fromTo[0], (int)(fromTo.size()/2));
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}
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CV_WRAP static inline bool eigen(const Mat& src, bool computeEigenvectors,
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CV_OUT Mat& eigenvalues, CV_OUT Mat& eigenvectors,
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int lowindex=-1, int highindex=-1)
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{
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if(computeEigenvectors)
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eigen(src, eigenvalues, eigenvectors, lowindex, highindex);
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else
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eigen(src, eigenvalues, lowindex, highindex);
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}
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CV_WRAP static inline void fillConvexPoly(Mat& img, const Mat& points,
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const Scalar& color, int lineType=8,
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int shift=0)
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{
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CV_Assert(points.checkVector(2, CV_32S) >= 0);
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fillConvexPoly(img, (const Point*)points.data, points.rows*points.cols*points.channels()/2, color, lineType, shift);
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}
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CV_WRAP static inline void fillPoly(Mat& img, const vector<Mat>& pts,
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const Scalar& color, int lineType=8, int shift=0,
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Point offset=Point() )
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{
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if( pts.empty() )
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return;
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AutoBuffer<Point*> _ptsptr(pts.size());
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AutoBuffer<int> _npts(pts.size());
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Point** ptsptr = _ptsptr;
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int* npts = _npts;
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for( size_t i = 0; i < pts.size(); i++ )
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{
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const Mat& p = pts[i];
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CV_Assert(p.checkVector(2, CV_32S) >= 0);
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ptsptr[i] = (const Point*)p.data;
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npts[i] = p.rows*p.cols*p.channels()/2;
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}
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fillPoly(img, ptsptr, npts, (int)pts.size(), color, lineType, shift, offset);
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}
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CV_WRAP static inline void polylines(Mat& img, const vector<Mat>& pts,
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bool isClosed, const Scalar& color,
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int thickness=1, int lineType=8, int shift=0 )
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{
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if( pts.empty() )
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return;
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AutoBuffer<Point*> _ptsptr(pts.size());
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AutoBuffer<int> _npts(pts.size());
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Point** ptsptr = _ptsptr;
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int* npts = _npts;
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for( size_t i = 0; i < pts.size(); i++ )
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{
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const Mat& p = pts[i];
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CV_Assert(p.checkVector(2, CV_32S) >= 0);
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ptsptr[i] = (const Point*)p.data;
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npts[i] = p.rows*p.cols*p.channels()/2;
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}
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polylines(img, ptsptr, npts, (int)pts.size(), isClosed, color, thickness, lineType, shift);
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}
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/////////////////////////// imgproc /////////////////////////////////
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CV_WRAP static inline void HuMoments(const Moments& m, CV_OUT vector<double>& hu)
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{
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hu.resize(7);
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HuMoments(m, &hu[0]);
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}
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CV_WRAP static inline Mat getPerspectiveTransform(const vector<Point2f>& src, const vector<Point2f>& dst)
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{
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CV_Assert(src.size() == 4 && dst.size() == 4);
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return getPerspectiveTransform(&src[0], &dst[0]);
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}
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CV_WRAP static inline Mat getAffineTransform(const vector<Point2f>& src, const vector<Point2f>& dst)
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{
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CV_Assert(src.size() == 3 && dst.size() == 3);
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return getAffineTransform(&src[0], &dst[0]);
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}
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CV_WRAP static inline void calcHist( const vector<Mat>& images, const vector<int>& channels,
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const Mat& mask, CV_OUT Mat& hist,
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const vector<int>& histSize,
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const vector<float>& ranges,
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bool accumulate=false)
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{
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int i, dims = (int)histSize.size(), rsz = (int)ranges.size(), csz = (int)channels.size();
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CV_Assert(images.size() > 0 && dims > 0);
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CV_Assert(rsz == dims*2 || (rsz == 0 && images[0].depth() == CV_8U));
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CV_Assert(csz == 0 || csz == dims);
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float* _ranges[CV_MAX_DIM];
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if( rsz > 0 )
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{
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_all_ranges = _ranges;
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for( int i = 0; i < rsz/2; i++ )
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_ranges[i] = &ranges[i*2];
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}
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calcHist(&images[0], (int)images.size(), csz ? &channels[0] : 0,
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mask, hist, dims, &histSize[0], rsz ? (const float**)_ranges : 0,
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true, accumulate);
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}
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CV_WRAP void calcBackProject( const vector<Mat>& images, const vector<int>& channels,
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const Mat& hist, CV_OUT Mat& dst,
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const vector<float>& ranges,
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double scale=1 )
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{
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int i, dims = hist.dims, rsz = (int)ranges.size(), csz = (int)channels.size();
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CV_Assert(images.size() > 0);
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CV_Assert(rsz == dims*2 || (rsz == 0 && images[0].depth() == CV_8U));
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CV_Assert(csz == 0 || csz == dims);
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float* _ranges[CV_MAX_DIM];
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if( rsz > 0 )
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{
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_all_ranges = _ranges;
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for( int i = 0; i < rsz/2; i++ )
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_ranges[i] = &ranges[i*2];
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}
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calcHist(&images[0], (int)images.size(), csz ? &channels[0] : 0,
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hist, dst, rsz ? (const float**)_ranges : 0, scale, true);
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}
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static void addChildContour(const vector<Mat>& contours,
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const Mat& hierarchy,
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int i, vector<CvSeq>& seq,
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vector<CvSeqBlock>& block)
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{
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size_t count = contours.size();
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for( ; i >= 0; i = ((const Vec4i*)hierarchy.data)[i][0] )
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{
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const vector<Point>& ci = contours[i];
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cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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!ci.empty() ? (void*)&ci[0] : 0, (int)ci.size(),
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&seq[i], &block[i] );
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const Vec4i h_i = ((const Vec4i*)hierarchy.data)[i];
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int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
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seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
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seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
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seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
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seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
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if( v_next >= 0 )
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addChildContour(contours, hierarchy, v_next, seq, block);
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}
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}
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//! draws contours in the image
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CV_WRAP static inline void drawContours( Mat& image, const vector<Mat>& contours,
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int contourIdx, const Scalar& color,
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int thickness=1, int lineType=8,
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const Mat& hierarchy=Mat(),
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int maxLevel=INT_MAX, Point offset=Point() )
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{
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CvMat _image = image;
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size_t i = 0, first = 0, last = contours.size();
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vector<CvSeq> seq;
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vector<CvSeqBlock> block;
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if( !last )
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return;
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seq.resize(last);
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block.resize(last);
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for( i = first; i < last; i++ )
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seq[i].first = 0;
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if( contourIdx >= 0 )
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{
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CV_Assert( 0 <= contourIdx && contourIdx < (int)last );
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first = contourIdx;
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last = contourIdx + 1;
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}
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for( i = first; i < last; i++ )
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{
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const Mat& ci = contours[i];
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int ci_size = ci.checkVector(2, CV_32S);
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CV_Assert( ci_size >= 0 );
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cvMakeSeqHeaderForArray(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(Point),
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ci_size > 0 ? ci.data : 0, ci_size, &seq[i], &block[i] );
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}
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if( hierarchy.empty() || maxLevel == 0 )
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for( i = first; i < last; i++ )
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{
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seq[i].h_next = i < last-1 ? &seq[i+1] : 0;
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seq[i].h_prev = i > first ? &seq[i-1] : 0;
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}
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else
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{
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int hsz = hierarchy.checkVector(4, CV_32S);
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size_t count = last - first;
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CV_Assert((size_t)hsz == contours.size());
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if( count == contours.size() )
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{
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for( i = first; i < last; i++ )
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{
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const Vec4i& h_i = ((const Vec4i*)hierarchy.data)[i];
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int h_next = h_i[0], h_prev = h_i[1], v_next = h_i[2], v_prev = h_i[3];
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seq[i].h_next = (size_t)h_next < count ? &seq[h_next] : 0;
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seq[i].h_prev = (size_t)h_prev < count ? &seq[h_prev] : 0;
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seq[i].v_next = (size_t)v_next < count ? &seq[v_next] : 0;
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seq[i].v_prev = (size_t)v_prev < count ? &seq[v_prev] : 0;
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}
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}
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else
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{
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int child = ((const Vec4i*)hierarchy.data)[first][2];
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if( child >= 0 )
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{
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addChildContour(contours, hierarchy, child, seq, block);
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seq[first].v_next = &seq[child];
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}
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}
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}
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cvDrawContours( &_image, &seq[first], color, color, contourIdx >= 0 ?
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-maxLevel : maxLevel, thickness, lineType, offset );
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}
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CV_WRAP static inline void approxPolyDP( const Mat& curve,
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CV_OUT Mat& approxCurve,
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double epsilon, bool closed )
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{
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if( curve.depth() == CV_32S )
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{
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vector<Point> result;
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approxyPolyDP(curve, result, epsilon, closed);
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Mat(result).copyTo(approxCurve);
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}
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else if( curve.depth() == CV_32F )
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{
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vector<Point2f> result;
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approxyPolyDP(curve, result, epsilon, closed);
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Mat(result).copyTo(approxCurve);
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}
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else
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CV_Error(CV_StsUnsupportedFormat, "")
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}
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CV_WRAP static inline void convexHull( const Mat& points, CV_OUT Mat& hull, bool returnPoints=true, bool clockwise=false )
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{
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if( !returnPoints )
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{
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vector<int> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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else if( points.depth() == CV_32S )
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{
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vector<Point> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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else if( points.depth() == CV_32F )
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{
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vector<Point2f> h;
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convexHull(points, h, clockwise);
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Mat(h).copyTo(hull);
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}
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}
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CV_WRAP static inline void fitLine( const Mat& points, CV_OUT CV_CUSTOM_CARRAY(points) float* line,
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int distType, double param, double reps, double aeps )
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{
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if(points.channels() == 2 || points.cols == 2)
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fitLine(points, *(Vec4f*)line, distType, param, reps, aeps);
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else
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fitLine(points, *(Vec6f*)line, distType, param, reps, aeps);
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}
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CV_WRAP static inline int estimateAffine3D( const Mat& from, const Mat& to,
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CV_OUT Mat& dst, CV_OUT Mat& outliers,
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double param1 = 3.0, double param2 = 0.99 )
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{
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vector<int> outliers_vec;
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int res = estimateAffine3D(from, to, dst, outliers_vec, param1, param2);
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outliers_vec.copyTo(outliers);
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return res;
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}
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CV_WRAP static inline void cornerSubPix( const Mat& image, Mat& corners,
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Size winSize, Size zeroZone,
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TermCriteria criteria )
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{
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int n = corners.checkVector(2, CV_32F);
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CV_Assert(n >= 0);
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if( n == 0 )
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return;
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CvMat _image = image;
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cvCornerSubPix(&_image, (CvPoint2D32f*)corners.data, n, winSize, zeroZone, criteria);
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}
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CV_WRAP static inline void goodFeaturesToTrack( const Mat& image, CV_OUT Mat& corners,
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int maxCorners, double qualityLevel, double minDistance,
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const Mat& mask=Mat(), int blockSize=3,
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bool useHarrisDetector=false, double k=0.04 )
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{
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vector<Point2f> corners_vec;
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goodFeaturesToTrack(image, corners_vec, maxCorners, qualityLevel,
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minDistance, mask, blockSize, useHarrisDetector, k);
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Mat(corners_vec).copyTo(corners);
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}
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CV_WRAP static inline void HoughLines( const Mat& image, CV_OUT Mat& lines,
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double rho, double theta, int threshold,
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double srn=0, double stn=0 )
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{
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vector<Vec2f>& lines_vec;
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HoughLines(image, lines_vec, rho, theta, threshold, srn, stn);
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Mat(lines_vec).copyTo(lines);
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}
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CV_WRAP static inline void HoughLinesP( Mat& image, CV_OUT Mat& lines,
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double rho, double theta, int threshold,
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double minLineLength=0, double maxLineGap=0 )
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{
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vector<Vec4i>& lines_vec;
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HoughLinesP(image, lines_vec, rho, theta, threshold, minLineLength, maxLineGap);
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Mat(lines_vec).copyTo(lines);
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||||
}
|
||||
|
||||
CV_WRAP static inline void HoughCircles( const Mat& image, CV_OUT vector<Vec3f>& circles,
|
||||
int method, double dp, double minDist,
|
||||
double param1=100, double param2=100,
|
||||
int minRadius=0, int maxRadius=0 )
|
||||
{
|
||||
vector<Vec3f>& circles_vec;
|
||||
HoughCircles(image, circles_vec, method, dp, minDist, param1, param2, minRadius, maxRadius);
|
||||
Mat(circles_vec).copyTo(circles);
|
||||
}
|
||||
|
||||
|
||||
/////////////////////////////// calib3d ///////////////////////////////////////////
|
||||
|
||||
CV_WRAP static inline bool findChessboardCorners( const Mat& image, Size patternSize,
|
||||
CV_OUT Mat& corners,
|
||||
int flags=CALIB_CB_ADAPTIVE_THRESH+
|
||||
CALIB_CB_NORMALIZE_IMAGE )
|
||||
{
|
||||
vector<Point2f> corners_vec;
|
||||
bool res = findChessboardCorners(image, patternSize, corners_vec, flags);
|
||||
corners_vec.copyTo(corners);
|
||||
return res;
|
||||
}
|
||||
|
||||
|
||||
CV_WRAP static inline void projectPoints( const Mat& objectPoints,
|
||||
const Mat& rvec, const Mat& tvec,
|
||||
const Mat& cameraMatrix,
|
||||
const Mat& distCoeffs,
|
||||
CV_OUT Mat& imagePoints )
|
||||
{
|
||||
vector<Point2f> imgpt;
|
||||
projectPoints(objectPoints, rvec, tvec, cameraMatrix, distCoeffs, imgpt);
|
||||
Mat(imgpt).copyTo(imagePoints);
|
||||
}
|
||||
|
||||
CV_WRAP static inline void projectPointsJ( const Mat& objectPoints,
|
||||
const Mat& rvec, const Mat& tvec,
|
||||
const Mat& cameraMatrix,
|
||||
const Mat& distCoeffs,
|
||||
CV_OUT Mat& imagePoints,
|
||||
CV_OUT Mat& dpdrot, CV_OUT Mat& dpdt, CV_OUT Mat& dpdf,
|
||||
CV_OUT Mat& dpdc, CV_OUT Mat& dpddist,
|
||||
double aspectRatio=0 )
|
||||
{
|
||||
vector<Point2f> imgpt;
|
||||
projectPoints(objectPoints, rvec, tvec, cameraMatri, distCoeffs, imgpt,
|
||||
dpdrot, dpdt, dpdf, dpdc, dpddist, aspectRatio);
|
||||
Mat(imgpt).copyTo(imagePoints);
|
||||
}
|
||||
|
||||
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_Assert(CV_StsBadSize, "");
|
||||
CvMat _src = src, _dst = dst;
|
||||
cvConvertHomogeneous(&_src, &_dst);
|
||||
}
|
||||
|
||||
|
||||
//! 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, rvec, 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, cameraMatrix2,
|
||||
imageSize, R, T, E, F, criteria, flags);
|
||||
}
|
||||
|
||||
|
||||
CV_WRAP static 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);
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
Loading…
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Reference in New Issue
Block a user