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486 lines
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486 lines
25 KiB
/*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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// indirect, incidental, special, exemplary, or consequential damages |
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// loss of use, data, or profits; or business interruption) however caused |
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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 { SOLVEPNP_ITERATIVE = 0, |
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SOLVEPNP_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation" |
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SOLVEPNP_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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SOLVEPNP_DLS = 3, // Joel A. Hesch and Stergios I. Roumeliotis. "A Direct Least-Squares (DLS) Method for PnP" |
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SOLVEPNP_UPNP = 4 // A.Penate-Sanchez, J.Andrade-Cetto, F.Moreno-Noguer. "Exhaustive Linearization for Robust Camera Pose and Focal Length Estimation" |
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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 = SOLVEPNP_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 bool 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, double confidence = 0.99, |
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OutputArray inliers = noArray(), int flags = SOLVEPNP_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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