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#ifndef __OPENCV_CALIB3D_HPP__
#define __OPENCV_CALIB3D_HPP__
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/core/affine.hpp"
namespace cv
{
//! type of the robust estimation algorithm
enum { LMEDS = 4, //!< least-median algorithm
RANSAC = 8 //!< RANSAC algorithm
};
enum { SOLVEPNP_ITERATIVE = 0,
SOLVEPNP_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
SOLVEPNP_P3P = 2, // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
SOLVEPNP_DLS = 3, // Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP"
SOLVEPNP_UPNP = 4 // A.Penate-Sanchez, J.Andrade-Cetto, F.Moreno-Noguer. "Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation"
};
enum { CALIB_CB_ADAPTIVE_THRESH = 1,
CALIB_CB_NORMALIZE_IMAGE = 2,
CALIB_CB_FILTER_QUADS = 4,
CALIB_CB_FAST_CHECK = 8
};
enum { CALIB_CB_SYMMETRIC_GRID = 1,
CALIB_CB_ASYMMETRIC_GRID = 2,
CALIB_CB_CLUSTERING = 4
};
enum { CALIB_USE_INTRINSIC_GUESS = 0x00001,
CALIB_FIX_ASPECT_RATIO = 0x00002,
CALIB_FIX_PRINCIPAL_POINT = 0x00004,
CALIB_ZERO_TANGENT_DIST = 0x00008,
CALIB_FIX_FOCAL_LENGTH = 0x00010,
CALIB_FIX_K1 = 0x00020,
CALIB_FIX_K2 = 0x00040,
CALIB_FIX_K3 = 0x00080,
CALIB_FIX_K4 = 0x00800,
CALIB_FIX_K5 = 0x01000,
CALIB_FIX_K6 = 0x02000,
CALIB_RATIONAL_MODEL = 0x04000,
CALIB_THIN_PRISM_MODEL = 0x08000,
CALIB_FIX_S1_S2_S3_S4 = 0x10000,
// only for stereo
CALIB_FIX_INTRINSIC = 0x00100,
CALIB_SAME_FOCAL_LENGTH = 0x00200,
// for stereo rectification
CALIB_ZERO_DISPARITY = 0x00400
};
//! the algorithm for finding fundamental matrix
enum { FM_7POINT = 1, //!< 7-point algorithm
FM_8POINT = 2, //!< 8-point algorithm
FM_LMEDS = 4, //!< least-median algorithm
FM_RANSAC = 8 //!< RANSAC algorithm
};
//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation
CV_EXPORTS_W void Rodrigues( InputArray src, OutputArray dst, OutputArray jacobian = noArray() );
//! computes the best-fit perspective transformation mapping srcPoints to dstPoints.
CV_EXPORTS_W Mat findHomography( InputArray srcPoints, InputArray dstPoints,
int method = 0, double ransacReprojThreshold = 3,
OutputArray mask=noArray(), const int maxIters = 2000,
const double confidence = 0.995);
//! variant of findHomography for backward compatibility
CV_EXPORTS Mat findHomography( InputArray srcPoints, InputArray dstPoints,
OutputArray mask, int method = 0, double ransacReprojThreshold = 3 );
//! Computes RQ decomposition of 3x3 matrix
CV_EXPORTS_W Vec3d RQDecomp3x3( InputArray src, OutputArray mtxR, OutputArray mtxQ,
OutputArray Qx = noArray(),
OutputArray Qy = noArray(),
OutputArray Qz = noArray());
//! Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector
CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray cameraMatrix,
OutputArray rotMatrix, OutputArray transVect,
OutputArray rotMatrixX = noArray(),
OutputArray rotMatrixY = noArray(),
OutputArray rotMatrixZ = noArray(),
OutputArray eulerAngles =noArray() );
//! computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients
CV_EXPORTS_W void matMulDeriv( InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB );
//! composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments
CV_EXPORTS_W void composeRT( InputArray rvec1, InputArray tvec1,
InputArray rvec2, InputArray tvec2,
OutputArray rvec3, OutputArray tvec3,
OutputArray dr3dr1 = noArray(), OutputArray dr3dt1 = noArray(),
OutputArray dr3dr2 = noArray(), OutputArray dr3dt2 = noArray(),
OutputArray dt3dr1 = noArray(), OutputArray dt3dt1 = noArray(),
OutputArray dt3dr2 = noArray(), OutputArray dt3dt2 = noArray() );
//! projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters
CV_EXPORTS_W void projectPoints( InputArray objectPoints,
InputArray rvec, InputArray tvec,
InputArray cameraMatrix, InputArray distCoeffs,
OutputArray imagePoints,
OutputArray jacobian = noArray(),
double aspectRatio = 0 );
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled.
CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
InputArray cameraMatrix, InputArray distCoeffs,
OutputArray rvec, OutputArray tvec,
bool useExtrinsicGuess = false, int flags = SOLVEPNP_ITERATIVE );
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.
CV_EXPORTS_W bool solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
InputArray cameraMatrix, InputArray distCoeffs,
OutputArray rvec, OutputArray tvec,
bool useExtrinsicGuess = false, int iterationsCount = 100,
float reprojectionError = 8.0, double confidence = 0.99,
OutputArray inliers = noArray(), int flags = SOLVEPNP_ITERATIVE );
//! initializes camera matrix from a few 3D points and the corresponding projections.
CV_EXPORTS_W Mat initCameraMatrix2D( InputArrayOfArrays objectPoints,
InputArrayOfArrays imagePoints,
Size imageSize, double aspectRatio = 1.0 );
//! finds checkerboard pattern of the specified size in the image
CV_EXPORTS_W bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners,
int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE );
//! finds subpixel-accurate positions of the chessboard corners
CV_EXPORTS bool find4QuadCornerSubpix( InputArray img, InputOutputArray corners, Size region_size );
//! draws the checkerboard pattern (found or partly found) in the image
CV_EXPORTS_W void drawChessboardCorners( InputOutputArray image, Size patternSize,
InputArray corners, bool patternWasFound );
//! finds circles' grid pattern of the specified size in the image
CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize,
OutputArray centers, int flags = CALIB_CB_SYMMETRIC_GRID,
const Ptr<FeatureDetector> &blobDetector = makePtr<SimpleBlobDetector>());
//! finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.
CV_EXPORTS_W double calibrateCamera( InputArrayOfArrays objectPoints,
InputArrayOfArrays imagePoints, Size imageSize,
InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
int flags = 0, TermCriteria criteria = TermCriteria(
TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
//! computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.
CV_EXPORTS_W void calibrationMatrixValues( InputArray cameraMatrix, Size imageSize,
double apertureWidth, double apertureHeight,
CV_OUT double& fovx, CV_OUT double& fovy,
CV_OUT double& focalLength, CV_OUT Point2d& principalPoint,
CV_OUT double& aspectRatio );
//! finds intrinsic and extrinsic parameters of a stereo camera
CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
Size imageSize, OutputArray R,OutputArray T, OutputArray E, OutputArray F,
int flags = CALIB_FIX_INTRINSIC,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
//! computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters
CV_EXPORTS_W void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs1,
InputArray cameraMatrix2, InputArray distCoeffs2,
Size imageSize, InputArray R, InputArray T,
OutputArray R1, OutputArray R2,
OutputArray P1, OutputArray P2,
OutputArray Q, int flags = CALIB_ZERO_DISPARITY,
double alpha = -1, Size newImageSize = Size(),
CV_OUT Rect* validPixROI1 = 0, CV_OUT Rect* validPixROI2 = 0 );
//! computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)
CV_EXPORTS_W bool stereoRectifyUncalibrated( InputArray points1, InputArray points2,
InputArray F, Size imgSize,
OutputArray H1, OutputArray H2,
double threshold = 5 );
//! computes the rectification transformations for 3-head camera, where all the heads are on the same line.
CV_EXPORTS_W float rectify3Collinear( InputArray cameraMatrix1, InputArray distCoeffs1,
InputArray cameraMatrix2, InputArray distCoeffs2,
InputArray cameraMatrix3, InputArray distCoeffs3,
InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3,
Size imageSize, InputArray R12, InputArray T12,
InputArray R13, InputArray T13,
OutputArray R1, OutputArray R2, OutputArray R3,
OutputArray P1, OutputArray P2, OutputArray P3,
OutputArray Q, double alpha, Size newImgSize,
CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags );
//! returns the optimal new camera matrix
CV_EXPORTS_W Mat getOptimalNewCameraMatrix( InputArray cameraMatrix, InputArray distCoeffs,
Size imageSize, double alpha, Size newImgSize = Size(),
CV_OUT Rect* validPixROI = 0,
bool centerPrincipalPoint = false);
//! converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))
CV_EXPORTS_W void convertPointsToHomogeneous( InputArray src, OutputArray dst );
//! converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))
CV_EXPORTS_W void convertPointsFromHomogeneous( InputArray src, OutputArray dst );
//! for backward compatibility
CV_EXPORTS void convertPointsHomogeneous( InputArray src, OutputArray dst );
//! finds fundamental matrix from a set of corresponding 2D points
CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
int method = FM_RANSAC,
double param1 = 3., double param2 = 0.99,
OutputArray mask = noArray() );
//! variant of findFundamentalMat for backward compatibility
CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2,
OutputArray mask, int method = FM_RANSAC,
double param1 = 3., double param2 = 0.99 );
//! finds essential matrix from a set of corresponding 2D points using five-point algorithm
CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2,
double focal = 1.0, Point2d pp = Point2d(0, 0),
int method = RANSAC, double prob = 0.999,
double threshold = 1.0, OutputArray mask = noArray() );
//! decompose essential matrix to possible rotation matrix and one translation vector
CV_EXPORTS_W void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
//! recover relative camera pose from a set of corresponding 2D points
CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
OutputArray R, OutputArray t,
double focal = 1.0, Point2d pp = Point2d(0, 0),
InputOutputArray mask = noArray() );
//! finds coordinates of epipolar lines corresponding the specified points
CV_EXPORTS_W void computeCorrespondEpilines( InputArray points, int whichImage,
InputArray F, OutputArray lines );
CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
InputArray projPoints1, InputArray projPoints2,
OutputArray points4D );
CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2,
OutputArray newPoints1, OutputArray newPoints2 );
//! filters off speckles (small regions of incorrectly computed disparity)
CV_EXPORTS_W void filterSpeckles( InputOutputArray img, double newVal,
int maxSpeckleSize, double maxDiff,
InputOutputArray buf = noArray() );
//! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify())
CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2,
int minDisparity, int numberOfDisparities,
int SADWindowSize );
//! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm
CV_EXPORTS_W void validateDisparity( InputOutputArray disparity, InputArray cost,
int minDisparity, int numberOfDisparities,
int disp12MaxDisp = 1 );
//! reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify
CV_EXPORTS_W void reprojectImageTo3D( InputArray disparity,
OutputArray _3dImage, InputArray Q,
bool handleMissingValues = false,
int ddepth = -1 );
CV_EXPORTS_W int estimateAffine3D(InputArray src, InputArray dst,
OutputArray out, OutputArray inliers,
double ransacThreshold = 3, double confidence = 0.99);
CV_EXPORTS_W int decomposeHomographyMat(InputArray H,
InputArray K,
OutputArrayOfArrays rotations,
OutputArrayOfArrays translations,
OutputArrayOfArrays normals);
class CV_EXPORTS_W StereoMatcher : public Algorithm
{
public:
enum { DISP_SHIFT = 4,
DISP_SCALE = (1 << DISP_SHIFT)
};
CV_WRAP virtual void compute( InputArray left, InputArray right,
OutputArray disparity ) = 0;
CV_WRAP virtual int getMinDisparity() const = 0;
CV_WRAP virtual void setMinDisparity(int minDisparity) = 0;
CV_WRAP virtual int getNumDisparities() const = 0;
CV_WRAP virtual void setNumDisparities(int numDisparities) = 0;
CV_WRAP virtual int getBlockSize() const = 0;
CV_WRAP virtual void setBlockSize(int blockSize) = 0;
CV_WRAP virtual int getSpeckleWindowSize() const = 0;
CV_WRAP virtual void setSpeckleWindowSize(int speckleWindowSize) = 0;
CV_WRAP virtual int getSpeckleRange() const = 0;
CV_WRAP virtual void setSpeckleRange(int speckleRange) = 0;
CV_WRAP virtual int getDisp12MaxDiff() const = 0;
CV_WRAP virtual void setDisp12MaxDiff(int disp12MaxDiff) = 0;
};
class CV_EXPORTS_W StereoBM : public StereoMatcher
{
public:
enum { PREFILTER_NORMALIZED_RESPONSE = 0,
PREFILTER_XSOBEL = 1
};
CV_WRAP virtual int getPreFilterType() const = 0;
CV_WRAP virtual void setPreFilterType(int preFilterType) = 0;
CV_WRAP virtual int getPreFilterSize() const = 0;
CV_WRAP virtual void setPreFilterSize(int preFilterSize) = 0;
CV_WRAP virtual int getPreFilterCap() const = 0;
CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
CV_WRAP virtual int getTextureThreshold() const = 0;
CV_WRAP virtual void setTextureThreshold(int textureThreshold) = 0;
CV_WRAP virtual int getUniquenessRatio() const = 0;
CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
CV_WRAP virtual int getSmallerBlockSize() const = 0;
CV_WRAP virtual void setSmallerBlockSize(int blockSize) = 0;
CV_WRAP virtual Rect getROI1() const = 0;
CV_WRAP virtual void setROI1(Rect roi1) = 0;
CV_WRAP virtual Rect getROI2() const = 0;
CV_WRAP virtual void setROI2(Rect roi2) = 0;
};
CV_EXPORTS_W Ptr<StereoBM> createStereoBM(int numDisparities = 0, int blockSize = 21);
class CV_EXPORTS_W StereoSGBM : public StereoMatcher
{
public:
enum { MODE_SGBM = 0,
MODE_HH = 1
};
CV_WRAP virtual int getPreFilterCap() const = 0;
CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
CV_WRAP virtual int getUniquenessRatio() const = 0;
CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
CV_WRAP virtual int getP1() const = 0;
CV_WRAP virtual void setP1(int P1) = 0;
CV_WRAP virtual int getP2() const = 0;
CV_WRAP virtual void setP2(int P2) = 0;
CV_WRAP virtual int getMode() const = 0;
CV_WRAP virtual void setMode(int mode) = 0;
};
CV_EXPORTS_W Ptr<StereoSGBM> createStereoSGBM(int minDisparity, int numDisparities, int blockSize,
int P1 = 0, int P2 = 0, int disp12MaxDiff = 0,
int preFilterCap = 0, int uniquenessRatio = 0,
int speckleWindowSize = 0, int speckleRange = 0,
int mode = StereoSGBM::MODE_SGBM);
namespace fisheye
{
enum{
CALIB_USE_INTRINSIC_GUESS = 1,
CALIB_RECOMPUTE_EXTRINSIC = 2,
CALIB_CHECK_COND = 4,
CALIB_FIX_SKEW = 8,
CALIB_FIX_K1 = 16,
CALIB_FIX_K2 = 32,
CALIB_FIX_K3 = 64,
CALIB_FIX_K4 = 128,
CALIB_FIX_INTRINSIC = 256
};
//! projects 3D points using fisheye model
CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! projects points using fisheye model
CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec,
InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
//! distorts 2D points using fisheye model
CV_EXPORTS void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0);
//! undistorts 2D points using fisheye model
CV_EXPORTS void undistortPoints(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray());
//! computing undistortion and rectification maps for image transform by cv::remap()
//! If D is empty zero distortion is used, if R or P is empty identity matrixes are used
CV_EXPORTS void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P,
const cv::Size& size, int m1type, OutputArray map1, OutputArray map2);
//! undistorts image, optionally changes resolution and camera matrix. If Knew zero identity matrix is used
CV_EXPORTS void undistortImage(InputArray distorted, OutputArray undistorted,
InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size());
//! estimates new camera matrix for undistortion or rectification
CV_EXPORTS void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R,
OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0);
//! performs camera calibaration
CV_EXPORTS double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
//! stereo rectification estimation
CV_EXPORTS void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec,
OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(),
double balance = 0.0, double fov_scale = 1.0);
//! performs stereo calibaration
CV_EXPORTS double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
OutputArray R, OutputArray T, int flags = CALIB_FIX_INTRINSIC,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
}
} // cv
#endif