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6ca893be23
-cv::findHomography added a parameter for RANSAC iterations -cv::findHomography added a parameter for RANSAC confidence
484 lines
25 KiB
C++
484 lines
25 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_CALIB3D_HPP__
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#define __OPENCV_CALIB3D_HPP__
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#include "opencv2/core.hpp"
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#include "opencv2/features2d.hpp"
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#include "opencv2/core/affine.hpp"
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namespace cv
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{
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//! type of the robust estimation algorithm
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enum { LMEDS = 4, //!< least-median algorithm
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RANSAC = 8 //!< RANSAC algorithm
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};
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enum { ITERATIVE = 0,
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EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
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P3P = 2 // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
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};
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enum { CALIB_CB_ADAPTIVE_THRESH = 1,
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CALIB_CB_NORMALIZE_IMAGE = 2,
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CALIB_CB_FILTER_QUADS = 4,
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CALIB_CB_FAST_CHECK = 8
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};
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enum { CALIB_CB_SYMMETRIC_GRID = 1,
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CALIB_CB_ASYMMETRIC_GRID = 2,
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CALIB_CB_CLUSTERING = 4
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};
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enum { CALIB_USE_INTRINSIC_GUESS = 0x00001,
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CALIB_FIX_ASPECT_RATIO = 0x00002,
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CALIB_FIX_PRINCIPAL_POINT = 0x00004,
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CALIB_ZERO_TANGENT_DIST = 0x00008,
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CALIB_FIX_FOCAL_LENGTH = 0x00010,
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CALIB_FIX_K1 = 0x00020,
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CALIB_FIX_K2 = 0x00040,
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CALIB_FIX_K3 = 0x00080,
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CALIB_FIX_K4 = 0x00800,
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CALIB_FIX_K5 = 0x01000,
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CALIB_FIX_K6 = 0x02000,
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CALIB_RATIONAL_MODEL = 0x04000,
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CALIB_THIN_PRISM_MODEL = 0x08000,
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CALIB_FIX_S1_S2_S3_S4 = 0x10000,
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// only for stereo
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CALIB_FIX_INTRINSIC = 0x00100,
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CALIB_SAME_FOCAL_LENGTH = 0x00200,
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// for stereo rectification
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CALIB_ZERO_DISPARITY = 0x00400
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};
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//! the algorithm for finding fundamental matrix
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enum { FM_7POINT = 1, //!< 7-point algorithm
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FM_8POINT = 2, //!< 8-point algorithm
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FM_LMEDS = 4, //!< least-median algorithm
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FM_RANSAC = 8 //!< RANSAC algorithm
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};
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//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation
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CV_EXPORTS_W void Rodrigues( InputArray src, OutputArray dst, OutputArray jacobian = noArray() );
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//! computes the best-fit perspective transformation mapping srcPoints to dstPoints.
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CV_EXPORTS_W Mat findHomography( InputArray srcPoints, InputArray dstPoints,
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int method = 0, double ransacReprojThreshold = 3,
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OutputArray mask=noArray(), const int maxIters = 2000,
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const double confidence = 0.995);
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//! variant of findHomography for backward compatibility
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CV_EXPORTS Mat findHomography( InputArray srcPoints, InputArray dstPoints,
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OutputArray mask, int method = 0, double ransacReprojThreshold = 3 );
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//! Computes RQ decomposition of 3x3 matrix
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CV_EXPORTS_W Vec3d RQDecomp3x3( InputArray src, OutputArray mtxR, OutputArray mtxQ,
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OutputArray Qx = noArray(),
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OutputArray Qy = noArray(),
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OutputArray Qz = noArray());
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//! Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector
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CV_EXPORTS_W void decomposeProjectionMatrix( InputArray projMatrix, OutputArray cameraMatrix,
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OutputArray rotMatrix, OutputArray transVect,
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OutputArray rotMatrixX = noArray(),
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OutputArray rotMatrixY = noArray(),
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OutputArray rotMatrixZ = noArray(),
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OutputArray eulerAngles =noArray() );
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//! computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients
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CV_EXPORTS_W void matMulDeriv( InputArray A, InputArray B, OutputArray dABdA, OutputArray dABdB );
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//! composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments
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CV_EXPORTS_W void composeRT( InputArray rvec1, InputArray tvec1,
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InputArray rvec2, InputArray tvec2,
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OutputArray rvec3, OutputArray tvec3,
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OutputArray dr3dr1 = noArray(), OutputArray dr3dt1 = noArray(),
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OutputArray dr3dr2 = noArray(), OutputArray dr3dt2 = noArray(),
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OutputArray dt3dr1 = noArray(), OutputArray dt3dt1 = noArray(),
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OutputArray dt3dr2 = noArray(), OutputArray dt3dt2 = noArray() );
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//! 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
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CV_EXPORTS_W void projectPoints( InputArray objectPoints,
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InputArray rvec, InputArray tvec,
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InputArray cameraMatrix, InputArray distCoeffs,
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OutputArray imagePoints,
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OutputArray jacobian = noArray(),
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double aspectRatio = 0 );
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//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are not handled.
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CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
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InputArray cameraMatrix, InputArray distCoeffs,
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OutputArray rvec, OutputArray tvec,
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bool useExtrinsicGuess = false, int flags = ITERATIVE );
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//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.
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CV_EXPORTS_W void solvePnPRansac( InputArray objectPoints, InputArray imagePoints,
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InputArray cameraMatrix, InputArray distCoeffs,
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OutputArray rvec, OutputArray tvec,
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bool useExtrinsicGuess = false, int iterationsCount = 100,
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float reprojectionError = 8.0, int minInliersCount = 100,
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OutputArray inliers = noArray(), int flags = ITERATIVE );
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//! initializes camera matrix from a few 3D points and the corresponding projections.
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CV_EXPORTS_W Mat initCameraMatrix2D( InputArrayOfArrays objectPoints,
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InputArrayOfArrays imagePoints,
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Size imageSize, double aspectRatio = 1.0 );
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//! finds checkerboard pattern of the specified size in the image
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CV_EXPORTS_W bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners,
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int flags = CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE );
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//! finds subpixel-accurate positions of the chessboard corners
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CV_EXPORTS bool find4QuadCornerSubpix( InputArray img, InputOutputArray corners, Size region_size );
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//! draws the checkerboard pattern (found or partly found) in the image
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CV_EXPORTS_W void drawChessboardCorners( InputOutputArray image, Size patternSize,
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InputArray corners, bool patternWasFound );
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//! finds circles' grid pattern of the specified size in the image
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CV_EXPORTS_W bool findCirclesGrid( InputArray image, Size patternSize,
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OutputArray centers, int flags = CALIB_CB_SYMMETRIC_GRID,
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const Ptr<FeatureDetector> &blobDetector = makePtr<SimpleBlobDetector>());
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//! finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.
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CV_EXPORTS_W double calibrateCamera( InputArrayOfArrays objectPoints,
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InputArrayOfArrays imagePoints, Size imageSize,
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InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
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OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
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int flags = 0, TermCriteria criteria = TermCriteria(
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TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) );
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//! computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.
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CV_EXPORTS_W void calibrationMatrixValues( InputArray cameraMatrix, Size imageSize,
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double apertureWidth, double apertureHeight,
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CV_OUT double& fovx, CV_OUT double& fovy,
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CV_OUT double& focalLength, CV_OUT Point2d& principalPoint,
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CV_OUT double& aspectRatio );
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//! finds intrinsic and extrinsic parameters of a stereo camera
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CV_EXPORTS_W double stereoCalibrate( InputArrayOfArrays objectPoints,
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InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
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InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1,
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InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2,
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Size imageSize, OutputArray R,OutputArray T, OutputArray E, OutputArray F,
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int flags = CALIB_FIX_INTRINSIC,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6) );
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//! computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters
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CV_EXPORTS_W void stereoRectify( InputArray cameraMatrix1, InputArray distCoeffs1,
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InputArray cameraMatrix2, InputArray distCoeffs2,
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Size imageSize, InputArray R, InputArray T,
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OutputArray R1, OutputArray R2,
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OutputArray P1, OutputArray P2,
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OutputArray Q, int flags = CALIB_ZERO_DISPARITY,
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double alpha = -1, Size newImageSize = Size(),
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CV_OUT Rect* validPixROI1 = 0, CV_OUT Rect* validPixROI2 = 0 );
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//! computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)
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CV_EXPORTS_W bool stereoRectifyUncalibrated( InputArray points1, InputArray points2,
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InputArray F, Size imgSize,
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OutputArray H1, OutputArray H2,
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double threshold = 5 );
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//! computes the rectification transformations for 3-head camera, where all the heads are on the same line.
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CV_EXPORTS_W float rectify3Collinear( InputArray cameraMatrix1, InputArray distCoeffs1,
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InputArray cameraMatrix2, InputArray distCoeffs2,
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InputArray cameraMatrix3, InputArray distCoeffs3,
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InputArrayOfArrays imgpt1, InputArrayOfArrays imgpt3,
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Size imageSize, InputArray R12, InputArray T12,
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InputArray R13, InputArray T13,
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OutputArray R1, OutputArray R2, OutputArray R3,
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OutputArray P1, OutputArray P2, OutputArray P3,
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OutputArray Q, double alpha, Size newImgSize,
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CV_OUT Rect* roi1, CV_OUT Rect* roi2, int flags );
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//! returns the optimal new camera matrix
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CV_EXPORTS_W Mat getOptimalNewCameraMatrix( InputArray cameraMatrix, InputArray distCoeffs,
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Size imageSize, double alpha, Size newImgSize = Size(),
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CV_OUT Rect* validPixROI = 0,
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bool centerPrincipalPoint = false);
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//! converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))
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CV_EXPORTS_W void convertPointsToHomogeneous( InputArray src, OutputArray dst );
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//! converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))
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CV_EXPORTS_W void convertPointsFromHomogeneous( InputArray src, OutputArray dst );
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//! for backward compatibility
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CV_EXPORTS void convertPointsHomogeneous( InputArray src, OutputArray dst );
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//! finds fundamental matrix from a set of corresponding 2D points
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CV_EXPORTS_W Mat findFundamentalMat( InputArray points1, InputArray points2,
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int method = FM_RANSAC,
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double param1 = 3., double param2 = 0.99,
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OutputArray mask = noArray() );
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//! variant of findFundamentalMat for backward compatibility
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CV_EXPORTS Mat findFundamentalMat( InputArray points1, InputArray points2,
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OutputArray mask, int method = FM_RANSAC,
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double param1 = 3., double param2 = 0.99 );
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//! finds essential matrix from a set of corresponding 2D points using five-point algorithm
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CV_EXPORTS_W Mat findEssentialMat( InputArray points1, InputArray points2,
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double focal = 1.0, Point2d pp = Point2d(0, 0),
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int method = RANSAC, double prob = 0.999,
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double threshold = 1.0, OutputArray mask = noArray() );
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//! decompose essential matrix to possible rotation matrix and one translation vector
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CV_EXPORTS_W void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
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//! recover relative camera pose from a set of corresponding 2D points
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CV_EXPORTS_W int recoverPose( InputArray E, InputArray points1, InputArray points2,
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OutputArray R, OutputArray t,
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double focal = 1.0, Point2d pp = Point2d(0, 0),
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InputOutputArray mask = noArray() );
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//! finds coordinates of epipolar lines corresponding the specified points
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CV_EXPORTS_W void computeCorrespondEpilines( InputArray points, int whichImage,
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InputArray F, OutputArray lines );
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CV_EXPORTS_W void triangulatePoints( InputArray projMatr1, InputArray projMatr2,
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InputArray projPoints1, InputArray projPoints2,
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OutputArray points4D );
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CV_EXPORTS_W void correctMatches( InputArray F, InputArray points1, InputArray points2,
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OutputArray newPoints1, OutputArray newPoints2 );
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//! filters off speckles (small regions of incorrectly computed disparity)
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CV_EXPORTS_W void filterSpeckles( InputOutputArray img, double newVal,
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int maxSpeckleSize, double maxDiff,
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InputOutputArray buf = noArray() );
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//! computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify())
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CV_EXPORTS_W Rect getValidDisparityROI( Rect roi1, Rect roi2,
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int minDisparity, int numberOfDisparities,
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int SADWindowSize );
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//! validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm
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CV_EXPORTS_W void validateDisparity( InputOutputArray disparity, InputArray cost,
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int minDisparity, int numberOfDisparities,
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int disp12MaxDisp = 1 );
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//! reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify
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CV_EXPORTS_W void reprojectImageTo3D( InputArray disparity,
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OutputArray _3dImage, InputArray Q,
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bool handleMissingValues = false,
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int ddepth = -1 );
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CV_EXPORTS_W int estimateAffine3D(InputArray src, InputArray dst,
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OutputArray out, OutputArray inliers,
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double ransacThreshold = 3, double confidence = 0.99);
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CV_EXPORTS_W int decomposeHomographyMat(InputArray H,
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InputArray K,
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OutputArrayOfArrays rotations,
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OutputArrayOfArrays translations,
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OutputArrayOfArrays normals);
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class CV_EXPORTS_W StereoMatcher : public Algorithm
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{
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public:
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enum { DISP_SHIFT = 4,
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DISP_SCALE = (1 << DISP_SHIFT)
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};
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CV_WRAP virtual void compute( InputArray left, InputArray right,
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OutputArray disparity ) = 0;
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CV_WRAP virtual int getMinDisparity() const = 0;
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CV_WRAP virtual void setMinDisparity(int minDisparity) = 0;
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CV_WRAP virtual int getNumDisparities() const = 0;
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CV_WRAP virtual void setNumDisparities(int numDisparities) = 0;
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CV_WRAP virtual int getBlockSize() const = 0;
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CV_WRAP virtual void setBlockSize(int blockSize) = 0;
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CV_WRAP virtual int getSpeckleWindowSize() const = 0;
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CV_WRAP virtual void setSpeckleWindowSize(int speckleWindowSize) = 0;
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CV_WRAP virtual int getSpeckleRange() const = 0;
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CV_WRAP virtual void setSpeckleRange(int speckleRange) = 0;
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CV_WRAP virtual int getDisp12MaxDiff() const = 0;
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CV_WRAP virtual void setDisp12MaxDiff(int disp12MaxDiff) = 0;
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};
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class CV_EXPORTS_W StereoBM : public StereoMatcher
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{
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public:
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enum { PREFILTER_NORMALIZED_RESPONSE = 0,
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PREFILTER_XSOBEL = 1
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};
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CV_WRAP virtual int getPreFilterType() const = 0;
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CV_WRAP virtual void setPreFilterType(int preFilterType) = 0;
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CV_WRAP virtual int getPreFilterSize() const = 0;
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CV_WRAP virtual void setPreFilterSize(int preFilterSize) = 0;
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CV_WRAP virtual int getPreFilterCap() const = 0;
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CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
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CV_WRAP virtual int getTextureThreshold() const = 0;
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CV_WRAP virtual void setTextureThreshold(int textureThreshold) = 0;
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CV_WRAP virtual int getUniquenessRatio() const = 0;
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CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
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CV_WRAP virtual int getSmallerBlockSize() const = 0;
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CV_WRAP virtual void setSmallerBlockSize(int blockSize) = 0;
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CV_WRAP virtual Rect getROI1() const = 0;
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CV_WRAP virtual void setROI1(Rect roi1) = 0;
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CV_WRAP virtual Rect getROI2() const = 0;
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CV_WRAP virtual void setROI2(Rect roi2) = 0;
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};
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CV_EXPORTS_W Ptr<StereoBM> createStereoBM(int numDisparities = 0, int blockSize = 21);
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class CV_EXPORTS_W StereoSGBM : public StereoMatcher
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{
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public:
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enum { MODE_SGBM = 0,
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MODE_HH = 1
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};
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CV_WRAP virtual int getPreFilterCap() const = 0;
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CV_WRAP virtual void setPreFilterCap(int preFilterCap) = 0;
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CV_WRAP virtual int getUniquenessRatio() const = 0;
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CV_WRAP virtual void setUniquenessRatio(int uniquenessRatio) = 0;
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CV_WRAP virtual int getP1() const = 0;
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CV_WRAP virtual void setP1(int P1) = 0;
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CV_WRAP virtual int getP2() const = 0;
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CV_WRAP virtual void setP2(int P2) = 0;
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CV_WRAP virtual int getMode() const = 0;
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CV_WRAP virtual void setMode(int mode) = 0;
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};
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CV_EXPORTS_W Ptr<StereoSGBM> createStereoSGBM(int minDisparity, int numDisparities, int blockSize,
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int P1 = 0, int P2 = 0, int disp12MaxDiff = 0,
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int preFilterCap = 0, int uniquenessRatio = 0,
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int speckleWindowSize = 0, int speckleRange = 0,
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int mode = StereoSGBM::MODE_SGBM);
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namespace fisheye
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{
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enum{
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CALIB_USE_INTRINSIC_GUESS = 1,
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CALIB_RECOMPUTE_EXTRINSIC = 2,
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CALIB_CHECK_COND = 4,
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CALIB_FIX_SKEW = 8,
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CALIB_FIX_K1 = 16,
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CALIB_FIX_K2 = 32,
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CALIB_FIX_K3 = 64,
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CALIB_FIX_K4 = 128,
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CALIB_FIX_INTRINSIC = 256
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};
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//! projects 3D points using fisheye model
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CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, const Affine3d& affine,
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InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
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//! projects points using fisheye model
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CV_EXPORTS void projectPoints(InputArray objectPoints, OutputArray imagePoints, InputArray rvec, InputArray tvec,
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InputArray K, InputArray D, double alpha = 0, OutputArray jacobian = noArray());
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//! distorts 2D points using fisheye model
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CV_EXPORTS void distortPoints(InputArray undistorted, OutputArray distorted, InputArray K, InputArray D, double alpha = 0);
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//! undistorts 2D points using fisheye model
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CV_EXPORTS void undistortPoints(InputArray distorted, OutputArray undistorted,
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InputArray K, InputArray D, InputArray R = noArray(), InputArray P = noArray());
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//! computing undistortion and rectification maps for image transform by cv::remap()
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//! If D is empty zero distortion is used, if R or P is empty identity matrixes are used
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CV_EXPORTS void initUndistortRectifyMap(InputArray K, InputArray D, InputArray R, InputArray P,
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const cv::Size& size, int m1type, OutputArray map1, OutputArray map2);
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//! undistorts image, optionally changes resolution and camera matrix. If Knew zero identity matrix is used
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CV_EXPORTS void undistortImage(InputArray distorted, OutputArray undistorted,
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InputArray K, InputArray D, InputArray Knew = cv::noArray(), const Size& new_size = Size());
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//! estimates new camera matrix for undistortion or rectification
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CV_EXPORTS void estimateNewCameraMatrixForUndistortRectify(InputArray K, InputArray D, const Size &image_size, InputArray R,
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OutputArray P, double balance = 0.0, const Size& new_size = Size(), double fov_scale = 1.0);
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//! performs camera calibaration
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CV_EXPORTS double calibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, const Size& image_size,
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InputOutputArray K, InputOutputArray D, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags = 0,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
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//! stereo rectification estimation
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CV_EXPORTS void stereoRectify(InputArray K1, InputArray D1, InputArray K2, InputArray D2, const Size &imageSize, InputArray R, InputArray tvec,
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OutputArray R1, OutputArray R2, OutputArray P1, OutputArray P2, OutputArray Q, int flags, const Size &newImageSize = Size(),
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double balance = 0.0, double fov_scale = 1.0);
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//! performs stereo calibaration
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CV_EXPORTS double stereoCalibrate(InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2,
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InputOutputArray K1, InputOutputArray D1, InputOutputArray K2, InputOutputArray D2, Size imageSize,
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OutputArray R, OutputArray T, int flags = CALIB_FIX_INTRINSIC,
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 100, DBL_EPSILON));
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}
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} // cv
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#endif
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