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Merge pull request #645 from taka-no-me:bump_headers

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This commit is contained in:
Andrey Kamaev
2013-03-14 11:42:22 +04:00
committed by OpenCV Buildbot
parent b076b69e68 a42a0f5fca
commit d9cd753835
281 changed files with 22107 additions and 21404 deletions
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2
modules/CMakeLists.txt
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@@ -1,3 +1,5 @@
add_definitions(-D__OPENCV_BUILD=1)
if(NOT OPENCV_MODULES_PATH)
set(OPENCV_MODULES_PATH "${CMAKE_CURRENT_SOURCE_DIR}")
endif()

1
modules/androidcamera/include/camera_activity.hpp
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@@ -2,7 +2,6 @@
#define _CAMERAACTIVITY_H_
#include <camera_properties.h>
//#include <opencv2/core/core.hpp>
class CameraActivity
{

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modules/calib3d/include/opencv2/calib3d.hpp Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CALIB3D_HPP__
#define __OPENCV_CALIB3D_HPP__
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#ifdef __cplusplus
extern "C" {
#endif
/****************************************************************************************\
* Camera Calibration, Pose Estimation and Stereo *
\****************************************************************************************/
typedef struct CvPOSITObject CvPOSITObject;
/* Allocates and initializes CvPOSITObject structure before doing cvPOSIT */
CVAPI(CvPOSITObject*) cvCreatePOSITObject( CvPoint3D32f* points, int point_count );
/* Runs POSIT (POSe from ITeration) algorithm for determining 3d position of
an object given its model and projection in a weak-perspective case */
CVAPI(void) cvPOSIT( CvPOSITObject* posit_object, CvPoint2D32f* image_points,
double focal_length, CvTermCriteria criteria,
float* rotation_matrix, float* translation_vector);
/* Releases CvPOSITObject structure */
CVAPI(void) cvReleasePOSITObject( CvPOSITObject** posit_object );
/* updates the number of RANSAC iterations */
CVAPI(int) cvRANSACUpdateNumIters( double p, double err_prob,
int model_points, int max_iters );
CVAPI(void) cvConvertPointsHomogeneous( const CvMat* src, CvMat* dst );
/* Calculates fundamental matrix given a set of corresponding points */
#define CV_FM_7POINT 1
#define CV_FM_8POINT 2
#define CV_LMEDS 4
#define CV_RANSAC 8
#define CV_FM_LMEDS_ONLY CV_LMEDS
#define CV_FM_RANSAC_ONLY CV_RANSAC
#define CV_FM_LMEDS CV_LMEDS
#define CV_FM_RANSAC CV_RANSAC
enum
{
CV_ITERATIVE = 0,
CV_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
CV_P3P = 2 // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
};
CVAPI(int) cvFindFundamentalMat( const CvMat* points1, const CvMat* points2,
CvMat* fundamental_matrix,
int method CV_DEFAULT(CV_FM_RANSAC),
double param1 CV_DEFAULT(3.), double param2 CV_DEFAULT(0.99),
CvMat* status CV_DEFAULT(NULL) );
/* For each input point on one of images
computes parameters of the corresponding
epipolar line on the other image */
CVAPI(void) cvComputeCorrespondEpilines( const CvMat* points,
int which_image,
const CvMat* fundamental_matrix,
CvMat* correspondent_lines );
/* Triangulation functions */
CVAPI(void) cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2,
CvMat* projPoints1, CvMat* projPoints2,
CvMat* points4D);
CVAPI(void) cvCorrectMatches(CvMat* F, CvMat* points1, CvMat* points2,
CvMat* new_points1, CvMat* new_points2);
/* Computes the optimal new camera matrix according to the free scaling parameter alpha:
alpha=0 - only valid pixels will be retained in the undistorted image
alpha=1 - all the source image pixels will be retained in the undistorted image
*/
CVAPI(void) cvGetOptimalNewCameraMatrix( const CvMat* camera_matrix,
const CvMat* dist_coeffs,
CvSize image_size, double alpha,
CvMat* new_camera_matrix,
CvSize new_imag_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pixel_ROI CV_DEFAULT(0),
int center_principal_point CV_DEFAULT(0));
/* Converts rotation vector to rotation matrix or vice versa */
CVAPI(int) cvRodrigues2( const CvMat* src, CvMat* dst,
CvMat* jacobian CV_DEFAULT(0) );
/* Finds perspective transformation between the object plane and image (view) plane */
CVAPI(int) cvFindHomography( const CvMat* src_points,
const CvMat* dst_points,
CvMat* homography,
int method CV_DEFAULT(0),
double ransacReprojThreshold CV_DEFAULT(3),
CvMat* mask CV_DEFAULT(0));
/* Computes RQ decomposition for 3x3 matrices */
CVAPI(void) cvRQDecomp3x3( const CvMat *matrixM, CvMat *matrixR, CvMat *matrixQ,
CvMat *matrixQx CV_DEFAULT(NULL),
CvMat *matrixQy CV_DEFAULT(NULL),
CvMat *matrixQz CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes projection matrix decomposition */
CVAPI(void) cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr,
CvMat *rotMatr, CvMat *posVect,
CvMat *rotMatrX CV_DEFAULT(NULL),
CvMat *rotMatrY CV_DEFAULT(NULL),
CvMat *rotMatrZ CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes d(AB)/dA and d(AB)/dB */
CVAPI(void) cvCalcMatMulDeriv( const CvMat* A, const CvMat* B, CvMat* dABdA, CvMat* dABdB );
/* Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)),
t3 = rodrigues(r2)*t1 + t2 and the respective derivatives */
CVAPI(void) cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1,
const CvMat* _rvec2, const CvMat* _tvec2,
CvMat* _rvec3, CvMat* _tvec3,
CvMat* dr3dr1 CV_DEFAULT(0), CvMat* dr3dt1 CV_DEFAULT(0),
CvMat* dr3dr2 CV_DEFAULT(0), CvMat* dr3dt2 CV_DEFAULT(0),
CvMat* dt3dr1 CV_DEFAULT(0), CvMat* dt3dt1 CV_DEFAULT(0),
CvMat* dt3dr2 CV_DEFAULT(0), CvMat* dt3dt2 CV_DEFAULT(0) );
/* Projects object points to the view plane using
the specified extrinsic and intrinsic camera parameters */
CVAPI(void) cvProjectPoints2( const CvMat* object_points, const CvMat* rotation_vector,
const CvMat* translation_vector, const CvMat* camera_matrix,
const CvMat* distortion_coeffs, CvMat* image_points,
CvMat* dpdrot CV_DEFAULT(NULL), CvMat* dpdt CV_DEFAULT(NULL),
CvMat* dpdf CV_DEFAULT(NULL), CvMat* dpdc CV_DEFAULT(NULL),
CvMat* dpddist CV_DEFAULT(NULL),
double aspect_ratio CV_DEFAULT(0));
/* Finds extrinsic camera parameters from
a few known corresponding point pairs and intrinsic parameters */
CVAPI(void) cvFindExtrinsicCameraParams2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
CvMat* rotation_vector,
CvMat* translation_vector,
int use_extrinsic_guess CV_DEFAULT(0) );
/* Computes initial estimate of the intrinsic camera parameters
in case of planar calibration target (e.g. chessboard) */
CVAPI(void) cvInitIntrinsicParams2D( const CvMat* object_points,
const CvMat* image_points,
const CvMat* npoints, CvSize image_size,
CvMat* camera_matrix,
double aspect_ratio CV_DEFAULT(1.) );
#define CV_CALIB_CB_ADAPTIVE_THRESH 1
#define CV_CALIB_CB_NORMALIZE_IMAGE 2
#define CV_CALIB_CB_FILTER_QUADS 4
#define CV_CALIB_CB_FAST_CHECK 8
// Performs a fast check if a chessboard is in the input image. This is a workaround to
// a problem of cvFindChessboardCorners being slow on images with no chessboard
// - src: input image
// - size: chessboard size
// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
// 0 if there is no chessboard, -1 in case of error
CVAPI(int) cvCheckChessboard(IplImage* src, CvSize size);
/* Detects corners on a chessboard calibration pattern */
CVAPI(int) cvFindChessboardCorners( const void* image, CvSize pattern_size,
CvPoint2D32f* corners,
int* corner_count CV_DEFAULT(NULL),
int flags CV_DEFAULT(CV_CALIB_CB_ADAPTIVE_THRESH+CV_CALIB_CB_NORMALIZE_IMAGE) );
/* Draws individual chessboard corners or the whole chessboard detected */
CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size,
CvPoint2D32f* corners,
int count, int pattern_was_found );
#define CV_CALIB_USE_INTRINSIC_GUESS 1
#define CV_CALIB_FIX_ASPECT_RATIO 2
#define CV_CALIB_FIX_PRINCIPAL_POINT 4
#define CV_CALIB_ZERO_TANGENT_DIST 8
#define CV_CALIB_FIX_FOCAL_LENGTH 16
#define CV_CALIB_FIX_K1 32
#define CV_CALIB_FIX_K2 64
#define CV_CALIB_FIX_K3 128
#define CV_CALIB_FIX_K4 2048
#define CV_CALIB_FIX_K5 4096
#define CV_CALIB_FIX_K6 8192
#define CV_CALIB_RATIONAL_MODEL 16384
#define CV_CALIB_THIN_PRISM_MODEL 32768
#define CV_CALIB_FIX_S1_S2_S3_S4 65536
/* Finds intrinsic and extrinsic camera parameters
from a few views of known calibration pattern */
CVAPI(double) cvCalibrateCamera2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* point_counts,
CvSize image_size,
CvMat* camera_matrix,
CvMat* distortion_coeffs,
CvMat* rotation_vectors CV_DEFAULT(NULL),
CvMat* translation_vectors CV_DEFAULT(NULL),
int flags CV_DEFAULT(0),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON)) );
/* Computes various useful characteristics of the camera from the data computed by
cvCalibrateCamera2 */
CVAPI(void) cvCalibrationMatrixValues( const CvMat *camera_matrix,
CvSize image_size,
double aperture_width CV_DEFAULT(0),
double aperture_height CV_DEFAULT(0),
double *fovx CV_DEFAULT(NULL),
double *fovy CV_DEFAULT(NULL),
double *focal_length CV_DEFAULT(NULL),
CvPoint2D64f *principal_point CV_DEFAULT(NULL),
double *pixel_aspect_ratio CV_DEFAULT(NULL));
#define CV_CALIB_FIX_INTRINSIC 256
#define CV_CALIB_SAME_FOCAL_LENGTH 512
/* Computes the transformation from one camera coordinate system to another one
from a few correspondent views of the same calibration target. Optionally, calibrates
both cameras */
CVAPI(double) cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1,
const CvMat* image_points2, const CvMat* npoints,
CvMat* camera_matrix1, CvMat* dist_coeffs1,
CvMat* camera_matrix2, CvMat* dist_coeffs2,
CvSize image_size, CvMat* R, CvMat* T,
CvMat* E CV_DEFAULT(0), CvMat* F CV_DEFAULT(0),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6)),
int flags CV_DEFAULT(CV_CALIB_FIX_INTRINSIC));
#define CV_CALIB_ZERO_DISPARITY 1024
/* Computes 3D rotations (+ optional shift) for each camera coordinate system to make both
views parallel (=> to make all the epipolar lines horizontal or vertical) */
CVAPI(void) cvStereoRectify( const CvMat* camera_matrix1, const CvMat* camera_matrix2,
const CvMat* dist_coeffs1, const CvMat* dist_coeffs2,
CvSize image_size, const CvMat* R, const CvMat* T,
CvMat* R1, CvMat* R2, CvMat* P1, CvMat* P2,
CvMat* Q CV_DEFAULT(0),
int flags CV_DEFAULT(CV_CALIB_ZERO_DISPARITY),
double alpha CV_DEFAULT(-1),
CvSize new_image_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pix_ROI1 CV_DEFAULT(0),
CvRect* valid_pix_ROI2 CV_DEFAULT(0));
/* Computes rectification transformations for uncalibrated pair of images using a set
of point correspondences */
CVAPI(int) cvStereoRectifyUncalibrated( const CvMat* points1, const CvMat* points2,
const CvMat* F, CvSize img_size,
CvMat* H1, CvMat* H2,
double threshold CV_DEFAULT(5));
/* stereo correspondence parameters and functions */
#define CV_STEREO_BM_NORMALIZED_RESPONSE 0
#define CV_STEREO_BM_XSOBEL 1
/* Block matching algorithm structure */
typedef struct CvStereoBMState
{
// pre-filtering (normalization of input images)
int preFilterType; // =CV_STEREO_BM_NORMALIZED_RESPONSE now
int preFilterSize; // averaging window size: ~5x5..21x21
int preFilterCap; // the output of pre-filtering is clipped by [-preFilterCap,preFilterCap]
// correspondence using Sum of Absolute Difference (SAD)
int SADWindowSize; // ~5x5..21x21
int minDisparity; // minimum disparity (can be negative)
int numberOfDisparities; // maximum disparity - minimum disparity (> 0)
// post-filtering
int textureThreshold; // the disparity is only computed for pixels
// with textured enough neighborhood
int uniquenessRatio; // accept the computed disparity d* only if
// SAD(d) >= SAD(d*)*(1 + uniquenessRatio/100.)
// for any d != d*+/-1 within the search range.
int speckleWindowSize; // disparity variation window
int speckleRange; // acceptable range of variation in window
int trySmallerWindows; // if 1, the results may be more accurate,
// at the expense of slower processing
CvRect roi1, roi2;
int disp12MaxDiff;
// temporary buffers
CvMat* preFilteredImg0;
CvMat* preFilteredImg1;
CvMat* slidingSumBuf;
CvMat* cost;
CvMat* disp;
} CvStereoBMState;
#define CV_STEREO_BM_BASIC 0
#define CV_STEREO_BM_FISH_EYE 1
#define CV_STEREO_BM_NARROW 2
CVAPI(CvStereoBMState*) cvCreateStereoBMState(int preset CV_DEFAULT(CV_STEREO_BM_BASIC),
int numberOfDisparities CV_DEFAULT(0));
CVAPI(void) cvReleaseStereoBMState( CvStereoBMState** state );
CVAPI(void) cvFindStereoCorrespondenceBM( const CvArr* left, const CvArr* right,
CvArr* disparity, CvStereoBMState* state );
CVAPI(CvRect) cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
int numberOfDisparities, int SADWindowSize );
CVAPI(void) cvValidateDisparity( CvArr* disparity, const CvArr* cost,
int minDisparity, int numberOfDisparities,
int disp12MaxDiff CV_DEFAULT(1) );
/* Reprojects the computed disparity image to the 3D space using the specified 4x4 matrix */
CVAPI(void) cvReprojectImageTo3D( const CvArr* disparityImage,
CvArr* _3dImage, const CvMat* Q,
int handleMissingValues CV_DEFAULT(0) );
#ifdef __cplusplus
}
//////////////////////////////////////////////////////////////////////////////////////////
class CV_EXPORTS CvLevMarq
{
public:
CvLevMarq();
CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
~CvLevMarq();
void init( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
bool update( const CvMat*& param, CvMat*& J, CvMat*& err );
bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm );
void clear();
void step();
enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 };
cv::Ptr<CvMat> mask;
cv::Ptr<CvMat> prevParam;
cv::Ptr<CvMat> param;
cv::Ptr<CvMat> J;
cv::Ptr<CvMat> err;
cv::Ptr<CvMat> JtJ;
cv::Ptr<CvMat> JtJN;
cv::Ptr<CvMat> JtErr;
cv::Ptr<CvMat> JtJV;
cv::Ptr<CvMat> JtJW;
double prevErrNorm, errNorm;
int lambdaLg10;
CvTermCriteria criteria;
int state;
int iters;
bool completeSymmFlag;
};
namespace cv
{
//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation
CV_EXPORTS_W void Rodrigues(InputArray src, OutputArray dst, OutputArray jacobian=noArray());
//! type of the robust estimation algorithm
enum
{
LMEDS=CV_LMEDS, //!< least-median algorithm
RANSAC=CV_RANSAC //!< RANSAC algorithm
};
//! 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());
//! 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.
enum
{
ITERATIVE=CV_ITERATIVE,
EPNP=CV_EPNP,
P3P=CV_P3P
};
CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
InputArray cameraMatrix, InputArray distCoeffs,
OutputArray rvec, OutputArray tvec,
bool useExtrinsicGuess=false, int flags=ITERATIVE);
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.
CV_EXPORTS_W void solvePnPRansac( InputArray objectPoints,
InputArray imagePoints,
InputArray cameraMatrix,
InputArray distCoeffs,
OutputArray rvec,
OutputArray tvec,
bool useExtrinsicGuess = false,
int iterationsCount = 100,
float reprojectionError = 8.0,
int minInliersCount = 100,
OutputArray inliers = noArray(),
int flags = 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. );
enum { CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2,
CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8 };
//! 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 );
enum { CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2,
CALIB_CB_CLUSTERING = 4 };
//! 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 = new SimpleBlobDetector());
//! the deprecated function. Use findCirclesGrid() instead of it.
CV_EXPORTS_W bool findCirclesGridDefault( InputArray image, Size patternSize,
OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID );
enum
{
CALIB_USE_INTRINSIC_GUESS = CV_CALIB_USE_INTRINSIC_GUESS,
CALIB_FIX_ASPECT_RATIO = CV_CALIB_FIX_ASPECT_RATIO,
CALIB_FIX_PRINCIPAL_POINT = CV_CALIB_FIX_PRINCIPAL_POINT,
CALIB_ZERO_TANGENT_DIST = CV_CALIB_ZERO_TANGENT_DIST,
CALIB_FIX_FOCAL_LENGTH = CV_CALIB_FIX_FOCAL_LENGTH,
CALIB_FIX_K1 = CV_CALIB_FIX_K1,
CALIB_FIX_K2 = CV_CALIB_FIX_K2,
CALIB_FIX_K3 = CV_CALIB_FIX_K3,
CALIB_FIX_K4 = CV_CALIB_FIX_K4,
CALIB_FIX_K5 = CV_CALIB_FIX_K5,
CALIB_FIX_K6 = CV_CALIB_FIX_K6,
CALIB_RATIONAL_MODEL = CV_CALIB_RATIONAL_MODEL,
CALIB_THIN_PRISM_MODEL = CV_CALIB_THIN_PRISM_MODEL,
CALIB_FIX_S1_S2_S3_S4=CV_CALIB_FIX_S1_S2_S3_S4,
// only for stereo
CALIB_FIX_INTRINSIC = CV_CALIB_FIX_INTRINSIC,
CALIB_SAME_FOCAL_LENGTH = CV_CALIB_SAME_FOCAL_LENGTH,
// for stereo rectification
CALIB_ZERO_DISPARITY = CV_CALIB_ZERO_DISPARITY
};
//! 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,
CV_OUT InputOutputArray cameraMatrix,
CV_OUT 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,
CV_OUT InputOutputArray cameraMatrix1,
CV_OUT InputOutputArray distCoeffs1,
CV_OUT InputOutputArray cameraMatrix2,
CV_OUT InputOutputArray distCoeffs2,
Size imageSize, OutputArray R,
OutputArray T, OutputArray E, OutputArray F,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6),
int flags=CALIB_FIX_INTRINSIC );
//! 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 );
//! the algorithm for finding fundamental matrix
enum
{
FM_7POINT = CV_FM_7POINT, //!< 7-point algorithm
FM_8POINT = CV_FM_8POINT, //!< 8-point algorithm
FM_LMEDS = CV_FM_LMEDS, //!< least-median algorithm
FM_RANSAC = CV_FM_RANSAC //!< RANSAC algorithm
};
//! 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 Mat findEssentialMat( InputArray points1, InputArray points2, double focal = 1.0, Point2d pp = Point2d(0, 0),
int method = CV_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 void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
//! recover relative camera pose from a set of corresponding 2D points
CV_EXPORTS 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 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 );
class CV_EXPORTS_W StereoMatcher : public Algorithm
{
public:
CV_WRAP virtual void compute( InputArray left, InputArray right,
OutputArray disparity ) = 0;
};
enum { STEREO_DISP_SCALE=16, STEREO_PREFILTER_NORMALIZED_RESPONSE = 0, STEREO_PREFILTER_XSOBEL = 1 };
CV_EXPORTS Ptr<StereoMatcher> createStereoBM(int numDisparities=0, int SADWindowSize=21);
CV_EXPORTS Ptr<StereoMatcher> createStereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
int P1=0, int P2=0, int disp12MaxDiff=0,
int preFilterCap=0, int uniquenessRatio=0,
int speckleWindowSize=0, int speckleRange=0,
bool fullDP=false);
template<> CV_EXPORTS void Ptr<CvStereoBMState>::delete_obj();
// to be moved to "compat" module
class CV_EXPORTS_W StereoBM
{
public:
enum { PREFILTER_NORMALIZED_RESPONSE = 0, PREFILTER_XSOBEL = 1,
BASIC_PRESET=0, FISH_EYE_PRESET=1, NARROW_PRESET=2 };
//! the default constructor
CV_WRAP StereoBM();
//! the full constructor taking the camera-specific preset, number of disparities and the SAD window size
CV_WRAP StereoBM(int preset, int ndisparities=0, int SADWindowSize=21);
//! the method that reinitializes the state. The previous content is destroyed
void init(int preset, int ndisparities=0, int SADWindowSize=21);
//! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
CV_WRAP_AS(compute) void operator()( InputArray left, InputArray right,
OutputArray disparity, int disptype=CV_16S );
//! pointer to the underlying CvStereoBMState
Ptr<CvStereoBMState> state;
};
// to be moved to "compat" module
class CV_EXPORTS_W StereoSGBM
{
public:
enum { DISP_SHIFT=4, DISP_SCALE = (1<<DISP_SHIFT) };
//! the default constructor
CV_WRAP StereoSGBM();
//! the full constructor taking all the necessary algorithm parameters
CV_WRAP StereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
int P1=0, int P2=0, int disp12MaxDiff=0,
int preFilterCap=0, int uniquenessRatio=0,
int speckleWindowSize=0, int speckleRange=0,
bool fullDP=false);
//! the destructor
virtual ~StereoSGBM();
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(InputArray left, InputArray right,
OutputArray disp);
CV_PROP_RW int minDisparity;
CV_PROP_RW int numberOfDisparities;
CV_PROP_RW int SADWindowSize;
CV_PROP_RW int preFilterCap;
CV_PROP_RW int uniquenessRatio;
CV_PROP_RW int P1;
CV_PROP_RW int P2;
CV_PROP_RW int speckleWindowSize;
CV_PROP_RW int speckleRange;
CV_PROP_RW int disp12MaxDiff;
CV_PROP_RW bool fullDP;
protected:
Ptr<StereoMatcher> sm;
};
//! 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);
}
#endif
#endif

742
modules/calib3d/include/opencv2/calib3d/calib3d.hpp
View File

@@ -7,11 +7,12 @@
// copy or use the software.
//
//
// License Agreement
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
@@ -40,741 +41,8 @@
//
//M*/
#ifndef __OPENCV_CALIB3D_HPP__
#define __OPENCV_CALIB3D_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#ifdef __cplusplus
extern "C" {
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
/****************************************************************************************\
* Camera Calibration, Pose Estimation and Stereo *
\****************************************************************************************/
typedef struct CvPOSITObject CvPOSITObject;
/* Allocates and initializes CvPOSITObject structure before doing cvPOSIT */
CVAPI(CvPOSITObject*) cvCreatePOSITObject( CvPoint3D32f* points, int point_count );
/* Runs POSIT (POSe from ITeration) algorithm for determining 3d position of
an object given its model and projection in a weak-perspective case */
CVAPI(void) cvPOSIT( CvPOSITObject* posit_object, CvPoint2D32f* image_points,
double focal_length, CvTermCriteria criteria,
float* rotation_matrix, float* translation_vector);
/* Releases CvPOSITObject structure */
CVAPI(void) cvReleasePOSITObject( CvPOSITObject** posit_object );
/* updates the number of RANSAC iterations */
CVAPI(int) cvRANSACUpdateNumIters( double p, double err_prob,
int model_points, int max_iters );
CVAPI(void) cvConvertPointsHomogeneous( const CvMat* src, CvMat* dst );
/* Calculates fundamental matrix given a set of corresponding points */
#define CV_FM_7POINT 1
#define CV_FM_8POINT 2
#define CV_LMEDS 4
#define CV_RANSAC 8
#define CV_FM_LMEDS_ONLY CV_LMEDS
#define CV_FM_RANSAC_ONLY CV_RANSAC
#define CV_FM_LMEDS CV_LMEDS
#define CV_FM_RANSAC CV_RANSAC
enum
{
CV_ITERATIVE = 0,
CV_EPNP = 1, // F.Moreno-Noguer, V.Lepetit and P.Fua "EPnP: Efficient Perspective-n-Point Camera Pose Estimation"
CV_P3P = 2 // X.S. Gao, X.-R. Hou, J. Tang, H.-F. Chang; "Complete Solution Classification for the Perspective-Three-Point Problem"
};
CVAPI(int) cvFindFundamentalMat( const CvMat* points1, const CvMat* points2,
CvMat* fundamental_matrix,
int method CV_DEFAULT(CV_FM_RANSAC),
double param1 CV_DEFAULT(3.), double param2 CV_DEFAULT(0.99),
CvMat* status CV_DEFAULT(NULL) );
/* For each input point on one of images
computes parameters of the corresponding
epipolar line on the other image */
CVAPI(void) cvComputeCorrespondEpilines( const CvMat* points,
int which_image,
const CvMat* fundamental_matrix,
CvMat* correspondent_lines );
/* Triangulation functions */
CVAPI(void) cvTriangulatePoints(CvMat* projMatr1, CvMat* projMatr2,
CvMat* projPoints1, CvMat* projPoints2,
CvMat* points4D);
CVAPI(void) cvCorrectMatches(CvMat* F, CvMat* points1, CvMat* points2,
CvMat* new_points1, CvMat* new_points2);
/* Computes the optimal new camera matrix according to the free scaling parameter alpha:
alpha=0 - only valid pixels will be retained in the undistorted image
alpha=1 - all the source image pixels will be retained in the undistorted image
*/
CVAPI(void) cvGetOptimalNewCameraMatrix( const CvMat* camera_matrix,
const CvMat* dist_coeffs,
CvSize image_size, double alpha,
CvMat* new_camera_matrix,
CvSize new_imag_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pixel_ROI CV_DEFAULT(0),
int center_principal_point CV_DEFAULT(0));
/* Converts rotation vector to rotation matrix or vice versa */
CVAPI(int) cvRodrigues2( const CvMat* src, CvMat* dst,
CvMat* jacobian CV_DEFAULT(0) );
/* Finds perspective transformation between the object plane and image (view) plane */
CVAPI(int) cvFindHomography( const CvMat* src_points,
const CvMat* dst_points,
CvMat* homography,
int method CV_DEFAULT(0),
double ransacReprojThreshold CV_DEFAULT(3),
CvMat* mask CV_DEFAULT(0));
/* Computes RQ decomposition for 3x3 matrices */
CVAPI(void) cvRQDecomp3x3( const CvMat *matrixM, CvMat *matrixR, CvMat *matrixQ,
CvMat *matrixQx CV_DEFAULT(NULL),
CvMat *matrixQy CV_DEFAULT(NULL),
CvMat *matrixQz CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes projection matrix decomposition */
CVAPI(void) cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr,
CvMat *rotMatr, CvMat *posVect,
CvMat *rotMatrX CV_DEFAULT(NULL),
CvMat *rotMatrY CV_DEFAULT(NULL),
CvMat *rotMatrZ CV_DEFAULT(NULL),
CvPoint3D64f *eulerAngles CV_DEFAULT(NULL));
/* Computes d(AB)/dA and d(AB)/dB */
CVAPI(void) cvCalcMatMulDeriv( const CvMat* A, const CvMat* B, CvMat* dABdA, CvMat* dABdB );
/* Computes r3 = rodrigues(rodrigues(r2)*rodrigues(r1)),
t3 = rodrigues(r2)*t1 + t2 and the respective derivatives */
CVAPI(void) cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1,
const CvMat* _rvec2, const CvMat* _tvec2,
CvMat* _rvec3, CvMat* _tvec3,
CvMat* dr3dr1 CV_DEFAULT(0), CvMat* dr3dt1 CV_DEFAULT(0),
CvMat* dr3dr2 CV_DEFAULT(0), CvMat* dr3dt2 CV_DEFAULT(0),
CvMat* dt3dr1 CV_DEFAULT(0), CvMat* dt3dt1 CV_DEFAULT(0),
CvMat* dt3dr2 CV_DEFAULT(0), CvMat* dt3dt2 CV_DEFAULT(0) );
/* Projects object points to the view plane using
the specified extrinsic and intrinsic camera parameters */
CVAPI(void) cvProjectPoints2( const CvMat* object_points, const CvMat* rotation_vector,
const CvMat* translation_vector, const CvMat* camera_matrix,
const CvMat* distortion_coeffs, CvMat* image_points,
CvMat* dpdrot CV_DEFAULT(NULL), CvMat* dpdt CV_DEFAULT(NULL),
CvMat* dpdf CV_DEFAULT(NULL), CvMat* dpdc CV_DEFAULT(NULL),
CvMat* dpddist CV_DEFAULT(NULL),
double aspect_ratio CV_DEFAULT(0));
/* Finds extrinsic camera parameters from
a few known corresponding point pairs and intrinsic parameters */
CVAPI(void) cvFindExtrinsicCameraParams2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* camera_matrix,
const CvMat* distortion_coeffs,
CvMat* rotation_vector,
CvMat* translation_vector,
int use_extrinsic_guess CV_DEFAULT(0) );
/* Computes initial estimate of the intrinsic camera parameters
in case of planar calibration target (e.g. chessboard) */
CVAPI(void) cvInitIntrinsicParams2D( const CvMat* object_points,
const CvMat* image_points,
const CvMat* npoints, CvSize image_size,
CvMat* camera_matrix,
double aspect_ratio CV_DEFAULT(1.) );
#define CV_CALIB_CB_ADAPTIVE_THRESH 1
#define CV_CALIB_CB_NORMALIZE_IMAGE 2
#define CV_CALIB_CB_FILTER_QUADS 4
#define CV_CALIB_CB_FAST_CHECK 8
// Performs a fast check if a chessboard is in the input image. This is a workaround to
// a problem of cvFindChessboardCorners being slow on images with no chessboard
// - src: input image
// - size: chessboard size
// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
// 0 if there is no chessboard, -1 in case of error
CVAPI(int) cvCheckChessboard(IplImage* src, CvSize size);
/* Detects corners on a chessboard calibration pattern */
CVAPI(int) cvFindChessboardCorners( const void* image, CvSize pattern_size,
CvPoint2D32f* corners,
int* corner_count CV_DEFAULT(NULL),
int flags CV_DEFAULT(CV_CALIB_CB_ADAPTIVE_THRESH+CV_CALIB_CB_NORMALIZE_IMAGE) );
/* Draws individual chessboard corners or the whole chessboard detected */
CVAPI(void) cvDrawChessboardCorners( CvArr* image, CvSize pattern_size,
CvPoint2D32f* corners,
int count, int pattern_was_found );
#define CV_CALIB_USE_INTRINSIC_GUESS 1
#define CV_CALIB_FIX_ASPECT_RATIO 2
#define CV_CALIB_FIX_PRINCIPAL_POINT 4
#define CV_CALIB_ZERO_TANGENT_DIST 8
#define CV_CALIB_FIX_FOCAL_LENGTH 16
#define CV_CALIB_FIX_K1 32
#define CV_CALIB_FIX_K2 64
#define CV_CALIB_FIX_K3 128
#define CV_CALIB_FIX_K4 2048
#define CV_CALIB_FIX_K5 4096
#define CV_CALIB_FIX_K6 8192
#define CV_CALIB_RATIONAL_MODEL 16384
#define CV_CALIB_THIN_PRISM_MODEL 32768
#define CV_CALIB_FIX_S1_S2_S3_S4 65536
/* Finds intrinsic and extrinsic camera parameters
from a few views of known calibration pattern */
CVAPI(double) cvCalibrateCamera2( const CvMat* object_points,
const CvMat* image_points,
const CvMat* point_counts,
CvSize image_size,
CvMat* camera_matrix,
CvMat* distortion_coeffs,
CvMat* rotation_vectors CV_DEFAULT(NULL),
CvMat* translation_vectors CV_DEFAULT(NULL),
int flags CV_DEFAULT(0),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON)) );
/* Computes various useful characteristics of the camera from the data computed by
cvCalibrateCamera2 */
CVAPI(void) cvCalibrationMatrixValues( const CvMat *camera_matrix,
CvSize image_size,
double aperture_width CV_DEFAULT(0),
double aperture_height CV_DEFAULT(0),
double *fovx CV_DEFAULT(NULL),
double *fovy CV_DEFAULT(NULL),
double *focal_length CV_DEFAULT(NULL),
CvPoint2D64f *principal_point CV_DEFAULT(NULL),
double *pixel_aspect_ratio CV_DEFAULT(NULL));
#define CV_CALIB_FIX_INTRINSIC 256
#define CV_CALIB_SAME_FOCAL_LENGTH 512
/* Computes the transformation from one camera coordinate system to another one
from a few correspondent views of the same calibration target. Optionally, calibrates
both cameras */
CVAPI(double) cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1,
const CvMat* image_points2, const CvMat* npoints,
CvMat* camera_matrix1, CvMat* dist_coeffs1,
CvMat* camera_matrix2, CvMat* dist_coeffs2,
CvSize image_size, CvMat* R, CvMat* T,
CvMat* E CV_DEFAULT(0), CvMat* F CV_DEFAULT(0),
CvTermCriteria term_crit CV_DEFAULT(cvTermCriteria(
CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6)),
int flags CV_DEFAULT(CV_CALIB_FIX_INTRINSIC));
#define CV_CALIB_ZERO_DISPARITY 1024
/* Computes 3D rotations (+ optional shift) for each camera coordinate system to make both
views parallel (=> to make all the epipolar lines horizontal or vertical) */
CVAPI(void) cvStereoRectify( const CvMat* camera_matrix1, const CvMat* camera_matrix2,
const CvMat* dist_coeffs1, const CvMat* dist_coeffs2,
CvSize image_size, const CvMat* R, const CvMat* T,
CvMat* R1, CvMat* R2, CvMat* P1, CvMat* P2,
CvMat* Q CV_DEFAULT(0),
int flags CV_DEFAULT(CV_CALIB_ZERO_DISPARITY),
double alpha CV_DEFAULT(-1),
CvSize new_image_size CV_DEFAULT(cvSize(0,0)),
CvRect* valid_pix_ROI1 CV_DEFAULT(0),
CvRect* valid_pix_ROI2 CV_DEFAULT(0));
/* Computes rectification transformations for uncalibrated pair of images using a set
of point correspondences */
CVAPI(int) cvStereoRectifyUncalibrated( const CvMat* points1, const CvMat* points2,
const CvMat* F, CvSize img_size,
CvMat* H1, CvMat* H2,
double threshold CV_DEFAULT(5));
/* stereo correspondence parameters and functions */
#define CV_STEREO_BM_NORMALIZED_RESPONSE 0
#define CV_STEREO_BM_XSOBEL 1
/* Block matching algorithm structure */
typedef struct CvStereoBMState
{
// pre-filtering (normalization of input images)
int preFilterType; // =CV_STEREO_BM_NORMALIZED_RESPONSE now
int preFilterSize; // averaging window size: ~5x5..21x21
int preFilterCap; // the output of pre-filtering is clipped by [-preFilterCap,preFilterCap]
// correspondence using Sum of Absolute Difference (SAD)
int SADWindowSize; // ~5x5..21x21
int minDisparity; // minimum disparity (can be negative)
int numberOfDisparities; // maximum disparity - minimum disparity (> 0)
// post-filtering
int textureThreshold; // the disparity is only computed for pixels
// with textured enough neighborhood
int uniquenessRatio; // accept the computed disparity d* only if
// SAD(d) >= SAD(d*)*(1 + uniquenessRatio/100.)
// for any d != d*+/-1 within the search range.
int speckleWindowSize; // disparity variation window
int speckleRange; // acceptable range of variation in window
int trySmallerWindows; // if 1, the results may be more accurate,
// at the expense of slower processing
CvRect roi1, roi2;
int disp12MaxDiff;
// temporary buffers
CvMat* preFilteredImg0;
CvMat* preFilteredImg1;
CvMat* slidingSumBuf;
CvMat* cost;
CvMat* disp;
} CvStereoBMState;
#define CV_STEREO_BM_BASIC 0
#define CV_STEREO_BM_FISH_EYE 1
#define CV_STEREO_BM_NARROW 2
CVAPI(CvStereoBMState*) cvCreateStereoBMState(int preset CV_DEFAULT(CV_STEREO_BM_BASIC),
int numberOfDisparities CV_DEFAULT(0));
CVAPI(void) cvReleaseStereoBMState( CvStereoBMState** state );
CVAPI(void) cvFindStereoCorrespondenceBM( const CvArr* left, const CvArr* right,
CvArr* disparity, CvStereoBMState* state );
CVAPI(CvRect) cvGetValidDisparityROI( CvRect roi1, CvRect roi2, int minDisparity,
int numberOfDisparities, int SADWindowSize );
CVAPI(void) cvValidateDisparity( CvArr* disparity, const CvArr* cost,
int minDisparity, int numberOfDisparities,
int disp12MaxDiff CV_DEFAULT(1) );
/* Reprojects the computed disparity image to the 3D space using the specified 4x4 matrix */
CVAPI(void) cvReprojectImageTo3D( const CvArr* disparityImage,
CvArr* _3dImage, const CvMat* Q,
int handleMissingValues CV_DEFAULT(0) );
#ifdef __cplusplus
}
//////////////////////////////////////////////////////////////////////////////////////////
class CV_EXPORTS CvLevMarq
{
public:
CvLevMarq();
CvLevMarq( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
~CvLevMarq();
void init( int nparams, int nerrs, CvTermCriteria criteria=
cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,30,DBL_EPSILON),
bool completeSymmFlag=false );
bool update( const CvMat*& param, CvMat*& J, CvMat*& err );
bool updateAlt( const CvMat*& param, CvMat*& JtJ, CvMat*& JtErr, double*& errNorm );
void clear();
void step();
enum { DONE=0, STARTED=1, CALC_J=2, CHECK_ERR=3 };
cv::Ptr<CvMat> mask;
cv::Ptr<CvMat> prevParam;
cv::Ptr<CvMat> param;
cv::Ptr<CvMat> J;
cv::Ptr<CvMat> err;
cv::Ptr<CvMat> JtJ;
cv::Ptr<CvMat> JtJN;
cv::Ptr<CvMat> JtErr;
cv::Ptr<CvMat> JtJV;
cv::Ptr<CvMat> JtJW;
double prevErrNorm, errNorm;
int lambdaLg10;
CvTermCriteria criteria;
int state;
int iters;
bool completeSymmFlag;
};
namespace cv
{
//! converts rotation vector to rotation matrix or vice versa using Rodrigues transformation
CV_EXPORTS_W void Rodrigues(InputArray src, OutputArray dst, OutputArray jacobian=noArray());
//! type of the robust estimation algorithm
enum
{
LMEDS=CV_LMEDS, //!< least-median algorithm
RANSAC=CV_RANSAC //!< RANSAC algorithm
};
//! 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());
//! 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.
enum
{
ITERATIVE=CV_ITERATIVE,
EPNP=CV_EPNP,
P3P=CV_P3P
};
CV_EXPORTS_W bool solvePnP( InputArray objectPoints, InputArray imagePoints,
InputArray cameraMatrix, InputArray distCoeffs,
OutputArray rvec, OutputArray tvec,
bool useExtrinsicGuess=false, int flags=ITERATIVE);
//! computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.
CV_EXPORTS_W void solvePnPRansac( InputArray objectPoints,
InputArray imagePoints,
InputArray cameraMatrix,
InputArray distCoeffs,
OutputArray rvec,
OutputArray tvec,
bool useExtrinsicGuess = false,
int iterationsCount = 100,
float reprojectionError = 8.0,
int minInliersCount = 100,
OutputArray inliers = noArray(),
int flags = 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. );
enum { CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2,
CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8 };
//! 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 );
enum { CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2,
CALIB_CB_CLUSTERING = 4 };
//! 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 = new SimpleBlobDetector());
//! the deprecated function. Use findCirclesGrid() instead of it.
CV_EXPORTS_W bool findCirclesGridDefault( InputArray image, Size patternSize,
OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID );
enum
{
CALIB_USE_INTRINSIC_GUESS = CV_CALIB_USE_INTRINSIC_GUESS,
CALIB_FIX_ASPECT_RATIO = CV_CALIB_FIX_ASPECT_RATIO,
CALIB_FIX_PRINCIPAL_POINT = CV_CALIB_FIX_PRINCIPAL_POINT,
CALIB_ZERO_TANGENT_DIST = CV_CALIB_ZERO_TANGENT_DIST,
CALIB_FIX_FOCAL_LENGTH = CV_CALIB_FIX_FOCAL_LENGTH,
CALIB_FIX_K1 = CV_CALIB_FIX_K1,
CALIB_FIX_K2 = CV_CALIB_FIX_K2,
CALIB_FIX_K3 = CV_CALIB_FIX_K3,
CALIB_FIX_K4 = CV_CALIB_FIX_K4,
CALIB_FIX_K5 = CV_CALIB_FIX_K5,
CALIB_FIX_K6 = CV_CALIB_FIX_K6,
CALIB_RATIONAL_MODEL = CV_CALIB_RATIONAL_MODEL,
CALIB_THIN_PRISM_MODEL = CV_CALIB_THIN_PRISM_MODEL,
CALIB_FIX_S1_S2_S3_S4=CV_CALIB_FIX_S1_S2_S3_S4,
// only for stereo
CALIB_FIX_INTRINSIC = CV_CALIB_FIX_INTRINSIC,
CALIB_SAME_FOCAL_LENGTH = CV_CALIB_SAME_FOCAL_LENGTH,
// for stereo rectification
CALIB_ZERO_DISPARITY = CV_CALIB_ZERO_DISPARITY
};
//! 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,
CV_OUT InputOutputArray cameraMatrix,
CV_OUT 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,
CV_OUT InputOutputArray cameraMatrix1,
CV_OUT InputOutputArray distCoeffs1,
CV_OUT InputOutputArray cameraMatrix2,
CV_OUT InputOutputArray distCoeffs2,
Size imageSize, OutputArray R,
OutputArray T, OutputArray E, OutputArray F,
TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6),
int flags=CALIB_FIX_INTRINSIC );
//! 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 );
//! the algorithm for finding fundamental matrix
enum
{
FM_7POINT = CV_FM_7POINT, //!< 7-point algorithm
FM_8POINT = CV_FM_8POINT, //!< 8-point algorithm
FM_LMEDS = CV_FM_LMEDS, //!< least-median algorithm
FM_RANSAC = CV_FM_RANSAC //!< RANSAC algorithm
};
//! 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 Mat findEssentialMat( InputArray points1, InputArray points2, double focal = 1.0, Point2d pp = Point2d(0, 0),
int method = CV_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 void decomposeEssentialMat( InputArray E, OutputArray R1, OutputArray R2, OutputArray t );
//! recover relative camera pose from a set of corresponding 2D points
CV_EXPORTS 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 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 );
class CV_EXPORTS_W StereoMatcher : public Algorithm
{
public:
CV_WRAP virtual void compute( InputArray left, InputArray right,
OutputArray disparity ) = 0;
};
enum { STEREO_DISP_SCALE=16, STEREO_PREFILTER_NORMALIZED_RESPONSE = 0, STEREO_PREFILTER_XSOBEL = 1 };
CV_EXPORTS Ptr<StereoMatcher> createStereoBM(int numDisparities=0, int SADWindowSize=21);
CV_EXPORTS Ptr<StereoMatcher> createStereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
int P1=0, int P2=0, int disp12MaxDiff=0,
int preFilterCap=0, int uniquenessRatio=0,
int speckleWindowSize=0, int speckleRange=0,
bool fullDP=false);
template<> CV_EXPORTS void Ptr<CvStereoBMState>::delete_obj();
// to be moved to "compat" module
class CV_EXPORTS_W StereoBM
{
public:
enum { PREFILTER_NORMALIZED_RESPONSE = 0, PREFILTER_XSOBEL = 1,
BASIC_PRESET=0, FISH_EYE_PRESET=1, NARROW_PRESET=2 };
//! the default constructor
CV_WRAP StereoBM();
//! the full constructor taking the camera-specific preset, number of disparities and the SAD window size
CV_WRAP StereoBM(int preset, int ndisparities=0, int SADWindowSize=21);
//! the method that reinitializes the state. The previous content is destroyed
void init(int preset, int ndisparities=0, int SADWindowSize=21);
//! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
CV_WRAP_AS(compute) void operator()( InputArray left, InputArray right,
OutputArray disparity, int disptype=CV_16S );
//! pointer to the underlying CvStereoBMState
Ptr<CvStereoBMState> state;
};
// to be moved to "compat" module
class CV_EXPORTS_W StereoSGBM
{
public:
enum { DISP_SHIFT=4, DISP_SCALE = (1<<DISP_SHIFT) };
//! the default constructor
CV_WRAP StereoSGBM();
//! the full constructor taking all the necessary algorithm parameters
CV_WRAP StereoSGBM(int minDisparity, int numDisparities, int SADWindowSize,
int P1=0, int P2=0, int disp12MaxDiff=0,
int preFilterCap=0, int uniquenessRatio=0,
int speckleWindowSize=0, int speckleRange=0,
bool fullDP=false);
//! the destructor
virtual ~StereoSGBM();
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(InputArray left, InputArray right,
OutputArray disp);
CV_PROP_RW int minDisparity;
CV_PROP_RW int numberOfDisparities;
CV_PROP_RW int SADWindowSize;
CV_PROP_RW int preFilterCap;
CV_PROP_RW int uniquenessRatio;
CV_PROP_RW int P1;
CV_PROP_RW int P2;
CV_PROP_RW int speckleWindowSize;
CV_PROP_RW int speckleRange;
CV_PROP_RW int disp12MaxDiff;
CV_PROP_RW bool fullDP;
protected:
Ptr<StereoMatcher> sm;
};
//! 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);
}
#endif
#endif
#include "opencv2/calib3d.hpp"

8
modules/calib3d/perf/perf_precomp.hpp
View File

@@ -9,10 +9,10 @@
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined

2
modules/calib3d/src/calibinit.cpp
View File

@@ -69,7 +69,7 @@
#ifdef DEBUG_CHESSBOARD
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_CHESSBOARD
# endif

2
modules/calib3d/src/checkchessboard.cpp
View File

@@ -49,7 +49,7 @@
#if defined(DEBUG_WINDOWS)
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_WINDOWS
# endif

2
modules/calib3d/src/circlesgrid.cpp
View File

@@ -46,7 +46,7 @@
#ifdef DEBUG_CIRCLES
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_CIRCLES
# endif

6
modules/calib3d/src/precomp.hpp
View File

@@ -46,11 +46,11 @@
#include "cvconfig.h"
#endif
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/core/internal.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/features2d.hpp"
#include <vector>
#ifdef HAVE_TEGRA_OPTIMIZATION

2
modules/calib3d/test/test_chessboardgenerator.hpp
View File

@@ -1,7 +1,7 @@
#ifndef CV_CHESSBOARDGENERATOR_H143KJTVYM389YTNHKFDHJ89NYVMO3VLMEJNTBGUEIYVCM203P
#define CV_CHESSBOARDGENERATOR_H143KJTVYM389YTNHKFDHJ89NYVMO3VLMEJNTBGUEIYVCM203P
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/calib3d.hpp"
namespace cv
{

8
modules/calib3d/test/test_precomp.hpp
View File

@@ -9,11 +9,11 @@
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
namespace cvtest

6
modules/contrib/doc/facerec/colormaps.rst
View File

@@ -42,9 +42,9 @@ In OpenCV 2.4 you only need :ocv:func:`applyColorMap` to apply a colormap on a g
.. code-block:: cpp
#include <opencv2/contrib/contrib.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/contrib.hpp>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
using namespace cv;

6
modules/contrib/doc/facerec/src/facerec_demo.cpp
View File

@@ -16,9 +16,9 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>

6
modules/contrib/doc/facerec/src/facerec_eigenfaces.cpp
View File

@@ -16,9 +16,9 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <fstream>

6
modules/contrib/doc/facerec/src/facerec_fisherfaces.cpp
View File

@@ -16,9 +16,9 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <fstream>

6
modules/contrib/doc/facerec/src/facerec_lbph.cpp
View File

@@ -16,9 +16,9 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/core.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <fstream>

6
modules/contrib/doc/facerec/src/facerec_save_load.cpp
View File

@@ -16,9 +16,9 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <fstream>

10
modules/contrib/doc/facerec/src/facerec_video.cpp
View File

@@ -16,11 +16,11 @@
* See <http://www.opensource.org/licenses/bsd-license>
*/
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/core.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include <iostream>
#include <fstream>

974
modules/contrib/include/opencv2/contrib.hpp Normal file
View File

@@ -0,0 +1,974 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_CONTRIB_HPP__
#define __OPENCV_CONTRIB_HPP__
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/objdetect.hpp"
#ifdef __cplusplus
/****************************************************************************************\
* Adaptive Skin Detector *
\****************************************************************************************/
class CV_EXPORTS CvAdaptiveSkinDetector
{
private:
enum {
GSD_HUE_LT = 3,
GSD_HUE_UT = 33,
GSD_INTENSITY_LT = 15,
GSD_INTENSITY_UT = 250
};
class CV_EXPORTS Histogram
{
private:
enum {
HistogramSize = (GSD_HUE_UT - GSD_HUE_LT + 1)
};
protected:
int findCoverageIndex(double surfaceToCover, int defaultValue = 0);
public:
CvHistogram *fHistogram;
Histogram();
virtual ~Histogram();
void findCurveThresholds(int &x1, int &x2, double percent = 0.05);
void mergeWith(Histogram *source, double weight);
};
int nStartCounter, nFrameCount, nSkinHueLowerBound, nSkinHueUpperBound, nMorphingMethod, nSamplingDivider;
double fHistogramMergeFactor, fHuePercentCovered;
Histogram histogramHueMotion, skinHueHistogram;
IplImage *imgHueFrame, *imgSaturationFrame, *imgLastGrayFrame, *imgMotionFrame, *imgFilteredFrame;
IplImage *imgShrinked, *imgTemp, *imgGrayFrame, *imgHSVFrame;
protected:
void initData(IplImage *src, int widthDivider, int heightDivider);
void adaptiveFilter();
public:
enum {
MORPHING_METHOD_NONE = 0,
MORPHING_METHOD_ERODE = 1,
MORPHING_METHOD_ERODE_ERODE = 2,
MORPHING_METHOD_ERODE_DILATE = 3
};
CvAdaptiveSkinDetector(int samplingDivider = 1, int morphingMethod = MORPHING_METHOD_NONE);
virtual ~CvAdaptiveSkinDetector();
virtual void process(IplImage *inputBGRImage, IplImage *outputHueMask);
};
/****************************************************************************************\
* Fuzzy MeanShift Tracker *
\****************************************************************************************/
class CV_EXPORTS CvFuzzyPoint {
public:
double x, y, value;
CvFuzzyPoint(double _x, double _y);
};
class CV_EXPORTS CvFuzzyCurve {
private:
std::vector<CvFuzzyPoint> points;
double value, centre;
bool between(double x, double x1, double x2);
public:
CvFuzzyCurve();
~CvFuzzyCurve();
void setCentre(double _centre);
double getCentre();
void clear();
void addPoint(double x, double y);
double calcValue(double param);
double getValue();
void setValue(double _value);
};
class CV_EXPORTS CvFuzzyFunction {
public:
std::vector<CvFuzzyCurve> curves;
CvFuzzyFunction();
~CvFuzzyFunction();
void addCurve(CvFuzzyCurve *curve, double value = 0);
void resetValues();
double calcValue();
CvFuzzyCurve *newCurve();
};
class CV_EXPORTS CvFuzzyRule {
private:
CvFuzzyCurve *fuzzyInput1, *fuzzyInput2;
CvFuzzyCurve *fuzzyOutput;
public:
CvFuzzyRule();
~CvFuzzyRule();
void setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
double calcValue(double param1, double param2);
CvFuzzyCurve *getOutputCurve();
};
class CV_EXPORTS CvFuzzyController {
private:
std::vector<CvFuzzyRule*> rules;
public:
CvFuzzyController();
~CvFuzzyController();
void addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
double calcOutput(double param1, double param2);
};
class CV_EXPORTS CvFuzzyMeanShiftTracker
{
private:
class FuzzyResizer
{
private:
CvFuzzyFunction iInput, iOutput;
CvFuzzyController fuzzyController;
public:
FuzzyResizer();
int calcOutput(double edgeDensity, double density);
};
class SearchWindow
{
public:
FuzzyResizer *fuzzyResizer;
int x, y;
int width, height, maxWidth, maxHeight, ellipseHeight, ellipseWidth;
int ldx, ldy, ldw, ldh, numShifts, numIters;
int xGc, yGc;
long m00, m01, m10, m11, m02, m20;
double ellipseAngle;
double density;
unsigned int depthLow, depthHigh;
int verticalEdgeLeft, verticalEdgeRight, horizontalEdgeTop, horizontalEdgeBottom;
SearchWindow();
~SearchWindow();
void setSize(int _x, int _y, int _width, int _height);
void initDepthValues(IplImage *maskImage, IplImage *depthMap);
bool shift();
void extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth);
void getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
void getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
void getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
bool meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth);
};
public:
enum TrackingState
{
tsNone = 0,
tsSearching = 1,
tsTracking = 2,
tsSetWindow = 3,
tsDisabled = 10
};
enum ResizeMethod {
rmEdgeDensityLinear = 0,
rmEdgeDensityFuzzy = 1,
rmInnerDensity = 2
};
enum {
MinKernelMass = 1000
};
SearchWindow kernel;
int searchMode;
private:
enum
{
MaxMeanShiftIteration = 5,
MaxSetSizeIteration = 5
};
void findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth);
public:
CvFuzzyMeanShiftTracker();
~CvFuzzyMeanShiftTracker();
void track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass = MinKernelMass);
};
namespace cv
{
class CV_EXPORTS Octree
{
public:
struct Node
{
Node() {}
int begin, end;
float x_min, x_max, y_min, y_max, z_min, z_max;
int maxLevels;
bool isLeaf;
int children[8];
};
Octree();
Octree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
virtual ~Octree();
virtual void buildTree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
virtual void getPointsWithinSphere( const Point3f& center, float radius,
std::vector<Point3f>& points ) const;
const std::vector<Node>& getNodes() const { return nodes; }
private:
int minPoints;
std::vector<Point3f> points;
std::vector<Node> nodes;
virtual void buildNext(size_t node_ind);
};
class CV_EXPORTS Mesh3D
{
public:
struct EmptyMeshException {};
Mesh3D();
Mesh3D(const std::vector<Point3f>& vtx);
~Mesh3D();
void buildOctree();
void clearOctree();
float estimateResolution(float tryRatio = 0.1f);
void computeNormals(float normalRadius, int minNeighbors = 20);
void computeNormals(const std::vector<int>& subset, float normalRadius, int minNeighbors = 20);
void writeAsVrml(const std::string& file, const std::vector<Scalar>& colors = std::vector<Scalar>()) const;
std::vector<Point3f> vtx;
std::vector<Point3f> normals;
float resolution;
Octree octree;
const static Point3f allzero;
};
class CV_EXPORTS SpinImageModel
{
public:
/* model parameters, leave unset for default or auto estimate */
float normalRadius;
int minNeighbors;
float binSize;
int imageWidth;
float lambda;
float gamma;
float T_GeometriccConsistency;
float T_GroupingCorespondances;
/* public interface */
SpinImageModel();
explicit SpinImageModel(const Mesh3D& mesh);
~SpinImageModel();
void setLogger(std::ostream* log);
void selectRandomSubset(float ratio);
void setSubset(const std::vector<int>& subset);
void compute();
void match(const SpinImageModel& scene, std::vector< std::vector<Vec2i> >& result);
Mat packRandomScaledSpins(bool separateScale = false, size_t xCount = 10, size_t yCount = 10) const;
size_t getSpinCount() const { return spinImages.rows; }
Mat getSpinImage(size_t index) const { return spinImages.row((int)index); }
const Point3f& getSpinVertex(size_t index) const { return mesh.vtx[subset[index]]; }
const Point3f& getSpinNormal(size_t index) const { return mesh.normals[subset[index]]; }
const Mesh3D& getMesh() const { return mesh; }
Mesh3D& getMesh() { return mesh; }
/* static utility functions */
static bool spinCorrelation(const Mat& spin1, const Mat& spin2, float lambda, float& result);
static Point2f calcSpinMapCoo(const Point3f& point, const Point3f& vertex, const Point3f& normal);
static float geometricConsistency(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2);
static float groupingCreteria(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2,
float gamma);
protected:
void defaultParams();
void matchSpinToModel(const Mat& spin, std::vector<int>& indeces,
std::vector<float>& corrCoeffs, bool useExtremeOutliers = true) const;
void repackSpinImages(const std::vector<uchar>& mask, Mat& spinImages, bool reAlloc = true) const;
std::vector<int> subset;
Mesh3D mesh;
Mat spinImages;
std::ostream* out;
};
class CV_EXPORTS TickMeter
{
public:
TickMeter();
void start();
void stop();
int64 getTimeTicks() const;
double getTimeMicro() const;
double getTimeMilli() const;
double getTimeSec() const;
int64 getCounter() const;
void reset();
private:
int64 counter;
int64 sumTime;
int64 startTime;
};
CV_EXPORTS std::ostream& operator<<(std::ostream& out, const TickMeter& tm);
class CV_EXPORTS SelfSimDescriptor
{
public:
SelfSimDescriptor();
SelfSimDescriptor(int _ssize, int _lsize,
int _startDistanceBucket=DEFAULT_START_DISTANCE_BUCKET,
int _numberOfDistanceBuckets=DEFAULT_NUM_DISTANCE_BUCKETS,
int _nangles=DEFAULT_NUM_ANGLES);
SelfSimDescriptor(const SelfSimDescriptor& ss);
virtual ~SelfSimDescriptor();
SelfSimDescriptor& operator = (const SelfSimDescriptor& ss);
size_t getDescriptorSize() const;
Size getGridSize( Size imgsize, Size winStride ) const;
virtual void compute(const Mat& img, std::vector<float>& descriptors, Size winStride=Size(),
const std::vector<Point>& locations=std::vector<Point>()) const;
virtual void computeLogPolarMapping(Mat& mappingMask) const;
virtual void SSD(const Mat& img, Point pt, Mat& ssd) const;
int smallSize;
int largeSize;
int startDistanceBucket;
int numberOfDistanceBuckets;
int numberOfAngles;
enum { DEFAULT_SMALL_SIZE = 5, DEFAULT_LARGE_SIZE = 41,
DEFAULT_NUM_ANGLES = 20, DEFAULT_START_DISTANCE_BUCKET = 3,
DEFAULT_NUM_DISTANCE_BUCKETS = 7 };
};
typedef bool (*BundleAdjustCallback)(int iteration, double norm_error, void* user_data);
class CV_EXPORTS LevMarqSparse {
public:
LevMarqSparse();
LevMarqSparse(int npoints, // number of points
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X, // measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* data, // user-specific data passed to the callbacks
BundleAdjustCallback cb, void* user_data
);
virtual ~LevMarqSparse();
virtual void run( int npoints, // number of points
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X, // measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* data // user-specific data passed to the callbacks
);
virtual void clear();
// useful function to do simple bundle adjustment tasks
static void bundleAdjust(std::vector<Point3d>& points, // positions of points in global coordinate system (input and output)
const std::vector<std::vector<Point2d> >& imagePoints, // projections of 3d points for every camera
const std::vector<std::vector<int> >& visibility, // visibility of 3d points for every camera
std::vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
std::vector<Mat>& R, // rotation matrices of all cameras (input and output)
std::vector<Mat>& T, // translation vector of all cameras (input and output)
std::vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
const TermCriteria& criteria=
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON),
BundleAdjustCallback cb = 0, void* user_data = 0);
public:
virtual void optimize(CvMat &_vis); //main function that runs minimization
//iteratively asks for measurement for visible camera-point pairs
void ask_for_proj(CvMat &_vis,bool once=false);
//iteratively asks for Jacobians for every camera_point pair
void ask_for_projac(CvMat &_vis);
CvMat* err; //error X-hX
double prevErrNorm, errNorm;
double lambda;
CvTermCriteria criteria;
int iters;
CvMat** U; //size of array is equal to number of cameras
CvMat** V; //size of array is equal to number of points
CvMat** inv_V_star; //inverse of V*
CvMat** A;
CvMat** B;
CvMat** W;
CvMat* X; //measurement
CvMat* hX; //current measurement extimation given new parameter vector
CvMat* prevP; //current already accepted parameter.
CvMat* P; // parameters used to evaluate function with new params
// this parameters may be rejected
CvMat* deltaP; //computed increase of parameters (result of normal system solution )
CvMat** ea; // sum_i AijT * e_ij , used as right part of normal equation
// length of array is j = number of cameras
CvMat** eb; // sum_j BijT * e_ij , used as right part of normal equation
// length of array is i = number of points
CvMat** Yj; //length of array is i = num_points
CvMat* S; //big matrix of block Sjk , each block has size num_cam_params x num_cam_params
CvMat* JtJ_diag; //diagonal of JtJ, used to backup diagonal elements before augmentation
CvMat* Vis_index; // matrix which element is index of measurement for point i and camera j
int num_cams;
int num_points;
int num_err_param;
int num_cam_param;
int num_point_param;
//target function and jacobian pointers, which needs to be initialized
void (*fjac)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data);
void (*func)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data);
void* data;
BundleAdjustCallback cb;
void* user_data;
};
CV_EXPORTS_W int chamerMatching( Mat& img, Mat& templ,
CV_OUT std::vector<std::vector<Point> >& results, CV_OUT std::vector<float>& cost,
double templScale=1, int maxMatches = 20,
double minMatchDistance = 1.0, int padX = 3,
int padY = 3, int scales = 5, double minScale = 0.6, double maxScale = 1.6,
double orientationWeight = 0.5, double truncate = 20);
class CV_EXPORTS_W StereoVar
{
public:
// Flags
enum {USE_INITIAL_DISPARITY = 1, USE_EQUALIZE_HIST = 2, USE_SMART_ID = 4, USE_AUTO_PARAMS = 8, USE_MEDIAN_FILTERING = 16};
enum {CYCLE_O, CYCLE_V};
enum {PENALIZATION_TICHONOV, PENALIZATION_CHARBONNIER, PENALIZATION_PERONA_MALIK};
//! the default constructor
CV_WRAP StereoVar();
//! the full constructor taking all the necessary algorithm parameters
CV_WRAP StereoVar(int levels, double pyrScale, int nIt, int minDisp, int maxDisp, int poly_n, double poly_sigma, float fi, float lambda, int penalization, int cycle, int flags);
//! the destructor
virtual ~StereoVar();
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(const Mat& left, const Mat& right, CV_OUT Mat& disp);
CV_PROP_RW int levels;
CV_PROP_RW double pyrScale;
CV_PROP_RW int nIt;
CV_PROP_RW int minDisp;
CV_PROP_RW int maxDisp;
CV_PROP_RW int poly_n;
CV_PROP_RW double poly_sigma;
CV_PROP_RW float fi;
CV_PROP_RW float lambda;
CV_PROP_RW int penalization;
CV_PROP_RW int cycle;
CV_PROP_RW int flags;
private:
void autoParams();
void FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level);
void VCycle_MyFAS(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
void VariationalSolver(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
};
CV_EXPORTS void polyfit(const Mat& srcx, const Mat& srcy, Mat& dst, int order);
class CV_EXPORTS Directory
{
public:
static std::vector<std::string> GetListFiles ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFilesR ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFolders( const std::string& path, const std::string & exten = "*", bool addPath = true );
};
/*
* Generation of a set of different colors by the following way:
* 1) generate more then need colors (in "factor" times) in RGB,
* 2) convert them to Lab,
* 3) choose the needed count of colors from the set that are more different from
* each other,
* 4) convert the colors back to RGB
*/
CV_EXPORTS void generateColors( std::vector<Scalar>& colors, size_t count, size_t factor=100 );
/*
* Estimate the rigid body motion from frame0 to frame1. The method is based on the paper
* "Real-Time Visual Odometry from Dense RGB-D Images", F. Steinbucker, J. Strum, D. Cremers, ICCV, 2011.
*/
enum { ROTATION = 1,
TRANSLATION = 2,
RIGID_BODY_MOTION = 4
};
CV_EXPORTS bool RGBDOdometry( Mat& Rt, const Mat& initRt,
const Mat& image0, const Mat& depth0, const Mat& mask0,
const Mat& image1, const Mat& depth1, const Mat& mask1,
const Mat& cameraMatrix, float minDepth=0.f, float maxDepth=4.f, float maxDepthDiff=0.07f,
const std::vector<int>& iterCounts=std::vector<int>(),
const std::vector<float>& minGradientMagnitudes=std::vector<float>(),
int transformType=RIGID_BODY_MOTION );
/**
*Bilinear interpolation technique.
*
*The value of a desired cortical pixel is obtained through a bilinear interpolation of the values
*of the four nearest neighbouring Cartesian pixels to the center of the RF.
*The same principle is applied to the inverse transformation.
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Interp
{
public:
LogPolar_Interp() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Interp(int w, int h, Point2i center, int R=70, double ro0=3.0,
int interp=INTER_LINEAR, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Interp();
protected:
Mat Rsri;
Mat Csri;
int S, R, M, N;
int top, bottom,left,right;
double ro0, romax, a, q;
int interp;
Mat ETAyx;
Mat CSIyx;
void create_map(int M, int N, int R, int S, double ro0);
};
/**
*Overlapping circular receptive fields technique
*
*The Cartesian plane is divided in two regions: the fovea and the periphery.
*The fovea (oversampling) is handled by using the bilinear interpolation technique described above, whereas in
*the periphery we use the overlapping Gaussian circular RFs.
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Overlapping
{
public:
LogPolar_Overlapping() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Overlapping(int w, int h, Point2i center, int R=70,
double ro0=3.0, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Overlapping();
protected:
Mat Rsri;
Mat Csri;
std::vector<int> Rsr;
std::vector<int> Csr;
std::vector<double> Wsr;
int S, R, M, N, ind1;
int top, bottom,left,right;
double ro0, romax, a, q;
struct kernel
{
kernel() { w = 0; }
std::vector<double> weights;
int w;
};
Mat ETAyx;
Mat CSIyx;
std::vector<kernel> w_ker_2D;
void create_map(int M, int N, int R, int S, double ro0);
};
/**
* Adjacent receptive fields technique
*
*All the Cartesian pixels, whose coordinates in the cortical domain share the same integer part, are assigned to the same RF.
*The precision of the boundaries of the RF can be improved by breaking each pixel into subpixels and assigning each of them to the correct RF.
*This technique is implemented from: Traver, V., Pla, F.: Log-polar mapping template design: From task-level requirements
*to geometry parameters. Image Vision Comput. 26(10) (2008) 1354-1370
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Adjacent
{
public:
LogPolar_Adjacent() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param smin the size of the subpixel (default value 0.25 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Adjacent(int w, int h, Point2i center, int R=70, double ro0=3.0, double smin=0.25, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Adjacent();
protected:
struct pixel
{
pixel() { u = v = 0; a = 0.; }
int u;
int v;
double a;
};
int S, R, M, N;
int top, bottom,left,right;
double ro0, romax, a, q;
std::vector<std::vector<pixel> > L;
std::vector<double> A;
void subdivide_recursively(double x, double y, int i, int j, double length, double smin);
bool get_uv(double x, double y, int&u, int&v);
void create_map(int M, int N, int R, int S, double ro0, double smin);
};
CV_EXPORTS Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
CV_EXPORTS Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
class CV_EXPORTS LDA
{
public:
// Initializes a LDA with num_components (default 0) and specifies how
// samples are aligned (default dataAsRow=true).
LDA(int num_components = 0) :
_num_components(num_components) {};
// Initializes and performs a Discriminant Analysis with Fisher's
// Optimization Criterion on given data in src and corresponding labels
// in labels. If 0 (or less) number of components are given, they are
// automatically determined for given data in computation.
LDA(InputArrayOfArrays src, InputArray labels,
int num_components = 0) :
_num_components(num_components)
{
this->compute(src, labels); //! compute eigenvectors and eigenvalues
}
// Serializes this object to a given filename.
void save(const std::string& filename) const;
// Deserializes this object from a given filename.
void load(const std::string& filename);
// Serializes this object to a given cv::FileStorage.
void save(FileStorage& fs) const;
// Deserializes this object from a given cv::FileStorage.
void load(const FileStorage& node);
// Destructor.
~LDA() {}
//! Compute the discriminants for data in src and labels.
void compute(InputArrayOfArrays src, InputArray labels);
// Projects samples into the LDA subspace.
Mat project(InputArray src);
// Reconstructs projections from the LDA subspace.
Mat reconstruct(InputArray src);
// Returns the eigenvectors of this LDA.
Mat eigenvectors() const { return _eigenvectors; };
// Returns the eigenvalues of this LDA.
Mat eigenvalues() const { return _eigenvalues; }
protected:
bool _dataAsRow;
int _num_components;
Mat _eigenvectors;
Mat _eigenvalues;
void lda(InputArrayOfArrays src, InputArray labels);
};
class CV_EXPORTS_W FaceRecognizer : public Algorithm
{
public:
//! virtual destructor
virtual ~FaceRecognizer() {}
// Trains a FaceRecognizer.
CV_WRAP virtual void train(InputArrayOfArrays src, InputArray labels) = 0;
// Updates a FaceRecognizer.
CV_WRAP virtual void update(InputArrayOfArrays src, InputArray labels);
// Gets a prediction from a FaceRecognizer.
virtual int predict(InputArray src) const = 0;
// Predicts the label and confidence for a given sample.
CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const = 0;
// Serializes this object to a given filename.
CV_WRAP virtual void save(const std::string& filename) const;
// Deserializes this object from a given filename.
CV_WRAP virtual void load(const std::string& filename);
// Serializes this object to a given cv::FileStorage.
virtual void save(FileStorage& fs) const = 0;
// Deserializes this object from a given cv::FileStorage.
virtual void load(const FileStorage& fs) = 0;
};
CV_EXPORTS_W Ptr<FaceRecognizer> createEigenFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
CV_EXPORTS_W Ptr<FaceRecognizer> createFisherFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
CV_EXPORTS_W Ptr<FaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8,
int grid_x=8, int grid_y=8, double threshold = DBL_MAX);
enum
{
COLORMAP_AUTUMN = 0,
COLORMAP_BONE = 1,
COLORMAP_JET = 2,
COLORMAP_WINTER = 3,
COLORMAP_RAINBOW = 4,
COLORMAP_OCEAN = 5,
COLORMAP_SUMMER = 6,
COLORMAP_SPRING = 7,
COLORMAP_COOL = 8,
COLORMAP_HSV = 9,
COLORMAP_PINK = 10,
COLORMAP_HOT = 11
};
CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
CV_EXPORTS bool initModule_contrib();
}
#include "opencv2/contrib/retina.hpp"
#include "opencv2/contrib/openfabmap.hpp"
#endif
#endif

937
modules/contrib/include/opencv2/contrib/contrib.hpp
View File

@@ -7,11 +7,12 @@
// copy or use the software.
//
//
// License Agreement
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
@@ -40,936 +41,8 @@
//
//M*/
#ifndef __OPENCV_CONTRIB_HPP__
#define __OPENCV_CONTRIB_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#ifdef __cplusplus
/****************************************************************************************\
* Adaptive Skin Detector *
\****************************************************************************************/
class CV_EXPORTS CvAdaptiveSkinDetector
{
private:
enum {
GSD_HUE_LT = 3,
GSD_HUE_UT = 33,
GSD_INTENSITY_LT = 15,
GSD_INTENSITY_UT = 250
};
class CV_EXPORTS Histogram
{
private:
enum {
HistogramSize = (GSD_HUE_UT - GSD_HUE_LT + 1)
};
protected:
int findCoverageIndex(double surfaceToCover, int defaultValue = 0);
public:
CvHistogram *fHistogram;
Histogram();
virtual ~Histogram();
void findCurveThresholds(int &x1, int &x2, double percent = 0.05);
void mergeWith(Histogram *source, double weight);
};
int nStartCounter, nFrameCount, nSkinHueLowerBound, nSkinHueUpperBound, nMorphingMethod, nSamplingDivider;
double fHistogramMergeFactor, fHuePercentCovered;
Histogram histogramHueMotion, skinHueHistogram;
IplImage *imgHueFrame, *imgSaturationFrame, *imgLastGrayFrame, *imgMotionFrame, *imgFilteredFrame;
IplImage *imgShrinked, *imgTemp, *imgGrayFrame, *imgHSVFrame;
protected:
void initData(IplImage *src, int widthDivider, int heightDivider);
void adaptiveFilter();
public:
enum {
MORPHING_METHOD_NONE = 0,
MORPHING_METHOD_ERODE = 1,
MORPHING_METHOD_ERODE_ERODE = 2,
MORPHING_METHOD_ERODE_DILATE = 3
};
CvAdaptiveSkinDetector(int samplingDivider = 1, int morphingMethod = MORPHING_METHOD_NONE);
virtual ~CvAdaptiveSkinDetector();
virtual void process(IplImage *inputBGRImage, IplImage *outputHueMask);
};
/****************************************************************************************\
* Fuzzy MeanShift Tracker *
\****************************************************************************************/
class CV_EXPORTS CvFuzzyPoint {
public:
double x, y, value;
CvFuzzyPoint(double _x, double _y);
};
class CV_EXPORTS CvFuzzyCurve {
private:
std::vector<CvFuzzyPoint> points;
double value, centre;
bool between(double x, double x1, double x2);
public:
CvFuzzyCurve();
~CvFuzzyCurve();
void setCentre(double _centre);
double getCentre();
void clear();
void addPoint(double x, double y);
double calcValue(double param);
double getValue();
void setValue(double _value);
};
class CV_EXPORTS CvFuzzyFunction {
public:
std::vector<CvFuzzyCurve> curves;
CvFuzzyFunction();
~CvFuzzyFunction();
void addCurve(CvFuzzyCurve *curve, double value = 0);
void resetValues();
double calcValue();
CvFuzzyCurve *newCurve();
};
class CV_EXPORTS CvFuzzyRule {
private:
CvFuzzyCurve *fuzzyInput1, *fuzzyInput2;
CvFuzzyCurve *fuzzyOutput;
public:
CvFuzzyRule();
~CvFuzzyRule();
void setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
double calcValue(double param1, double param2);
CvFuzzyCurve *getOutputCurve();
};
class CV_EXPORTS CvFuzzyController {
private:
std::vector<CvFuzzyRule*> rules;
public:
CvFuzzyController();
~CvFuzzyController();
void addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1);
double calcOutput(double param1, double param2);
};
class CV_EXPORTS CvFuzzyMeanShiftTracker
{
private:
class FuzzyResizer
{
private:
CvFuzzyFunction iInput, iOutput;
CvFuzzyController fuzzyController;
public:
FuzzyResizer();
int calcOutput(double edgeDensity, double density);
};
class SearchWindow
{
public:
FuzzyResizer *fuzzyResizer;
int x, y;
int width, height, maxWidth, maxHeight, ellipseHeight, ellipseWidth;
int ldx, ldy, ldw, ldh, numShifts, numIters;
int xGc, yGc;
long m00, m01, m10, m11, m02, m20;
double ellipseAngle;
double density;
unsigned int depthLow, depthHigh;
int verticalEdgeLeft, verticalEdgeRight, horizontalEdgeTop, horizontalEdgeBottom;
SearchWindow();
~SearchWindow();
void setSize(int _x, int _y, int _width, int _height);
void initDepthValues(IplImage *maskImage, IplImage *depthMap);
bool shift();
void extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth);
void getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
void getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
void getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh);
bool meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth);
};
public:
enum TrackingState
{
tsNone = 0,
tsSearching = 1,
tsTracking = 2,
tsSetWindow = 3,
tsDisabled = 10
};
enum ResizeMethod {
rmEdgeDensityLinear = 0,
rmEdgeDensityFuzzy = 1,
rmInnerDensity = 2
};
enum {
MinKernelMass = 1000
};
SearchWindow kernel;
int searchMode;
private:
enum
{
MaxMeanShiftIteration = 5,
MaxSetSizeIteration = 5
};
void findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth);
public:
CvFuzzyMeanShiftTracker();
~CvFuzzyMeanShiftTracker();
void track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass = MinKernelMass);
};
namespace cv
{
class CV_EXPORTS Octree
{
public:
struct Node
{
Node() {}
int begin, end;
float x_min, x_max, y_min, y_max, z_min, z_max;
int maxLevels;
bool isLeaf;
int children[8];
};
Octree();
Octree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
virtual ~Octree();
virtual void buildTree( const std::vector<Point3f>& points, int maxLevels = 10, int minPoints = 20 );
virtual void getPointsWithinSphere( const Point3f& center, float radius,
std::vector<Point3f>& points ) const;
const std::vector<Node>& getNodes() const { return nodes; }
private:
int minPoints;
std::vector<Point3f> points;
std::vector<Node> nodes;
virtual void buildNext(size_t node_ind);
};
class CV_EXPORTS Mesh3D
{
public:
struct EmptyMeshException {};
Mesh3D();
Mesh3D(const std::vector<Point3f>& vtx);
~Mesh3D();
void buildOctree();
void clearOctree();
float estimateResolution(float tryRatio = 0.1f);
void computeNormals(float normalRadius, int minNeighbors = 20);
void computeNormals(const std::vector<int>& subset, float normalRadius, int minNeighbors = 20);
void writeAsVrml(const std::string& file, const std::vector<Scalar>& colors = std::vector<Scalar>()) const;
std::vector<Point3f> vtx;
std::vector<Point3f> normals;
float resolution;
Octree octree;
const static Point3f allzero;
};
class CV_EXPORTS SpinImageModel
{
public:
/* model parameters, leave unset for default or auto estimate */
float normalRadius;
int minNeighbors;
float binSize;
int imageWidth;
float lambda;
float gamma;
float T_GeometriccConsistency;
float T_GroupingCorespondances;
/* public interface */
SpinImageModel();
explicit SpinImageModel(const Mesh3D& mesh);
~SpinImageModel();
void setLogger(std::ostream* log);
void selectRandomSubset(float ratio);
void setSubset(const std::vector<int>& subset);
void compute();
void match(const SpinImageModel& scene, std::vector< std::vector<Vec2i> >& result);
Mat packRandomScaledSpins(bool separateScale = false, size_t xCount = 10, size_t yCount = 10) const;
size_t getSpinCount() const { return spinImages.rows; }
Mat getSpinImage(size_t index) const { return spinImages.row((int)index); }
const Point3f& getSpinVertex(size_t index) const { return mesh.vtx[subset[index]]; }
const Point3f& getSpinNormal(size_t index) const { return mesh.normals[subset[index]]; }
const Mesh3D& getMesh() const { return mesh; }
Mesh3D& getMesh() { return mesh; }
/* static utility functions */
static bool spinCorrelation(const Mat& spin1, const Mat& spin2, float lambda, float& result);
static Point2f calcSpinMapCoo(const Point3f& point, const Point3f& vertex, const Point3f& normal);
static float geometricConsistency(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2);
static float groupingCreteria(const Point3f& pointScene1, const Point3f& normalScene1,
const Point3f& pointModel1, const Point3f& normalModel1,
const Point3f& pointScene2, const Point3f& normalScene2,
const Point3f& pointModel2, const Point3f& normalModel2,
float gamma);
protected:
void defaultParams();
void matchSpinToModel(const Mat& spin, std::vector<int>& indeces,
std::vector<float>& corrCoeffs, bool useExtremeOutliers = true) const;
void repackSpinImages(const std::vector<uchar>& mask, Mat& spinImages, bool reAlloc = true) const;
std::vector<int> subset;
Mesh3D mesh;
Mat spinImages;
std::ostream* out;
};
class CV_EXPORTS TickMeter
{
public:
TickMeter();
void start();
void stop();
int64 getTimeTicks() const;
double getTimeMicro() const;
double getTimeMilli() const;
double getTimeSec() const;
int64 getCounter() const;
void reset();
private:
int64 counter;
int64 sumTime;
int64 startTime;
};
CV_EXPORTS std::ostream& operator<<(std::ostream& out, const TickMeter& tm);
class CV_EXPORTS SelfSimDescriptor
{
public:
SelfSimDescriptor();
SelfSimDescriptor(int _ssize, int _lsize,
int _startDistanceBucket=DEFAULT_START_DISTANCE_BUCKET,
int _numberOfDistanceBuckets=DEFAULT_NUM_DISTANCE_BUCKETS,
int _nangles=DEFAULT_NUM_ANGLES);
SelfSimDescriptor(const SelfSimDescriptor& ss);
virtual ~SelfSimDescriptor();
SelfSimDescriptor& operator = (const SelfSimDescriptor& ss);
size_t getDescriptorSize() const;
Size getGridSize( Size imgsize, Size winStride ) const;
virtual void compute(const Mat& img, std::vector<float>& descriptors, Size winStride=Size(),
const std::vector<Point>& locations=std::vector<Point>()) const;
virtual void computeLogPolarMapping(Mat& mappingMask) const;
virtual void SSD(const Mat& img, Point pt, Mat& ssd) const;
int smallSize;
int largeSize;
int startDistanceBucket;
int numberOfDistanceBuckets;
int numberOfAngles;
enum { DEFAULT_SMALL_SIZE = 5, DEFAULT_LARGE_SIZE = 41,
DEFAULT_NUM_ANGLES = 20, DEFAULT_START_DISTANCE_BUCKET = 3,
DEFAULT_NUM_DISTANCE_BUCKETS = 7 };
};
typedef bool (*BundleAdjustCallback)(int iteration, double norm_error, void* user_data);
class CV_EXPORTS LevMarqSparse {
public:
LevMarqSparse();
LevMarqSparse(int npoints, // number of points
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X, // measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* data, // user-specific data passed to the callbacks
BundleAdjustCallback cb, void* user_data
);
virtual ~LevMarqSparse();
virtual void run( int npoints, // number of points
int ncameras, // number of cameras
int nPointParams, // number of params per one point (3 in case of 3D points)
int nCameraParams, // number of parameters per one camera
int nErrParams, // number of parameters in measurement vector
// for 1 point at one camera (2 in case of 2D projections)
Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
// 1 - point is visible for the camera, 0 - invisible
Mat& P0, // starting vector of parameters, first cameras then points
Mat& X, // measurements, in order of visibility. non visible cases are skipped
TermCriteria criteria, // termination criteria
// callback for estimation of Jacobian matrices
void (CV_CDECL * fjac)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& A, Mat& B, void* data),
// callback for estimation of backprojection errors
void (CV_CDECL * func)(int i, int j, Mat& point_params,
Mat& cam_params, Mat& estim, void* data),
void* data // user-specific data passed to the callbacks
);
virtual void clear();
// useful function to do simple bundle adjustment tasks
static void bundleAdjust(std::vector<Point3d>& points, // positions of points in global coordinate system (input and output)
const std::vector<std::vector<Point2d> >& imagePoints, // projections of 3d points for every camera
const std::vector<std::vector<int> >& visibility, // visibility of 3d points for every camera
std::vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
std::vector<Mat>& R, // rotation matrices of all cameras (input and output)
std::vector<Mat>& T, // translation vector of all cameras (input and output)
std::vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
const TermCriteria& criteria=
TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON),
BundleAdjustCallback cb = 0, void* user_data = 0);
public:
virtual void optimize(CvMat &_vis); //main function that runs minimization
//iteratively asks for measurement for visible camera-point pairs
void ask_for_proj(CvMat &_vis,bool once=false);
//iteratively asks for Jacobians for every camera_point pair
void ask_for_projac(CvMat &_vis);
CvMat* err; //error X-hX
double prevErrNorm, errNorm;
double lambda;
CvTermCriteria criteria;
int iters;
CvMat** U; //size of array is equal to number of cameras
CvMat** V; //size of array is equal to number of points
CvMat** inv_V_star; //inverse of V*
CvMat** A;
CvMat** B;
CvMat** W;
CvMat* X; //measurement
CvMat* hX; //current measurement extimation given new parameter vector
CvMat* prevP; //current already accepted parameter.
CvMat* P; // parameters used to evaluate function with new params
// this parameters may be rejected
CvMat* deltaP; //computed increase of parameters (result of normal system solution )
CvMat** ea; // sum_i AijT * e_ij , used as right part of normal equation
// length of array is j = number of cameras
CvMat** eb; // sum_j BijT * e_ij , used as right part of normal equation
// length of array is i = number of points
CvMat** Yj; //length of array is i = num_points
CvMat* S; //big matrix of block Sjk , each block has size num_cam_params x num_cam_params
CvMat* JtJ_diag; //diagonal of JtJ, used to backup diagonal elements before augmentation
CvMat* Vis_index; // matrix which element is index of measurement for point i and camera j
int num_cams;
int num_points;
int num_err_param;
int num_cam_param;
int num_point_param;
//target function and jacobian pointers, which needs to be initialized
void (*fjac)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data);
void (*func)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data);
void* data;
BundleAdjustCallback cb;
void* user_data;
};
CV_EXPORTS_W int chamerMatching( Mat& img, Mat& templ,
CV_OUT std::vector<std::vector<Point> >& results, CV_OUT std::vector<float>& cost,
double templScale=1, int maxMatches = 20,
double minMatchDistance = 1.0, int padX = 3,
int padY = 3, int scales = 5, double minScale = 0.6, double maxScale = 1.6,
double orientationWeight = 0.5, double truncate = 20);
class CV_EXPORTS_W StereoVar
{
public:
// Flags
enum {USE_INITIAL_DISPARITY = 1, USE_EQUALIZE_HIST = 2, USE_SMART_ID = 4, USE_AUTO_PARAMS = 8, USE_MEDIAN_FILTERING = 16};
enum {CYCLE_O, CYCLE_V};
enum {PENALIZATION_TICHONOV, PENALIZATION_CHARBONNIER, PENALIZATION_PERONA_MALIK};
//! the default constructor
CV_WRAP StereoVar();
//! the full constructor taking all the necessary algorithm parameters
CV_WRAP StereoVar(int levels, double pyrScale, int nIt, int minDisp, int maxDisp, int poly_n, double poly_sigma, float fi, float lambda, int penalization, int cycle, int flags);
//! the destructor
virtual ~StereoVar();
//! the stereo correspondence operator that computes disparity map for the specified rectified stereo pair
CV_WRAP_AS(compute) virtual void operator()(const Mat& left, const Mat& right, CV_OUT Mat& disp);
CV_PROP_RW int levels;
CV_PROP_RW double pyrScale;
CV_PROP_RW int nIt;
CV_PROP_RW int minDisp;
CV_PROP_RW int maxDisp;
CV_PROP_RW int poly_n;
CV_PROP_RW double poly_sigma;
CV_PROP_RW float fi;
CV_PROP_RW float lambda;
CV_PROP_RW int penalization;
CV_PROP_RW int cycle;
CV_PROP_RW int flags;
private:
void autoParams();
void FMG(Mat &I1, Mat &I2, Mat &I2x, Mat &u, int level);
void VCycle_MyFAS(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
void VariationalSolver(Mat &I1_h, Mat &I2_h, Mat &I2x_h, Mat &u_h, int level);
};
CV_EXPORTS void polyfit(const Mat& srcx, const Mat& srcy, Mat& dst, int order);
class CV_EXPORTS Directory
{
public:
static std::vector<std::string> GetListFiles ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFilesR ( const std::string& path, const std::string & exten = "*", bool addPath = true );
static std::vector<std::string> GetListFolders( const std::string& path, const std::string & exten = "*", bool addPath = true );
};
/*
* Generation of a set of different colors by the following way:
* 1) generate more then need colors (in "factor" times) in RGB,
* 2) convert them to Lab,
* 3) choose the needed count of colors from the set that are more different from
* each other,
* 4) convert the colors back to RGB
*/
CV_EXPORTS void generateColors( std::vector<Scalar>& colors, size_t count, size_t factor=100 );
/*
* Estimate the rigid body motion from frame0 to frame1. The method is based on the paper
* "Real-Time Visual Odometry from Dense RGB-D Images", F. Steinbucker, J. Strum, D. Cremers, ICCV, 2011.
*/
enum { ROTATION = 1,
TRANSLATION = 2,
RIGID_BODY_MOTION = 4
};
CV_EXPORTS bool RGBDOdometry( Mat& Rt, const Mat& initRt,
const Mat& image0, const Mat& depth0, const Mat& mask0,
const Mat& image1, const Mat& depth1, const Mat& mask1,
const Mat& cameraMatrix, float minDepth=0.f, float maxDepth=4.f, float maxDepthDiff=0.07f,
const std::vector<int>& iterCounts=std::vector<int>(),
const std::vector<float>& minGradientMagnitudes=std::vector<float>(),
int transformType=RIGID_BODY_MOTION );
/**
*Bilinear interpolation technique.
*
*The value of a desired cortical pixel is obtained through a bilinear interpolation of the values
*of the four nearest neighbouring Cartesian pixels to the center of the RF.
*The same principle is applied to the inverse transformation.
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Interp
{
public:
LogPolar_Interp() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Interp(int w, int h, Point2i center, int R=70, double ro0=3.0,
int interp=INTER_LINEAR, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Interp();
protected:
Mat Rsri;
Mat Csri;
int S, R, M, N;
int top, bottom,left,right;
double ro0, romax, a, q;
int interp;
Mat ETAyx;
Mat CSIyx;
void create_map(int M, int N, int R, int S, double ro0);
};
/**
*Overlapping circular receptive fields technique
*
*The Cartesian plane is divided in two regions: the fovea and the periphery.
*The fovea (oversampling) is handled by using the bilinear interpolation technique described above, whereas in
*the periphery we use the overlapping Gaussian circular RFs.
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Overlapping
{
public:
LogPolar_Overlapping() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Overlapping(int w, int h, Point2i center, int R=70,
double ro0=3.0, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Overlapping();
protected:
Mat Rsri;
Mat Csri;
std::vector<int> Rsr;
std::vector<int> Csr;
std::vector<double> Wsr;
int S, R, M, N, ind1;
int top, bottom,left,right;
double ro0, romax, a, q;
struct kernel
{
kernel() { w = 0; }
std::vector<double> weights;
int w;
};
Mat ETAyx;
Mat CSIyx;
std::vector<kernel> w_ker_2D;
void create_map(int M, int N, int R, int S, double ro0);
};
/**
* Adjacent receptive fields technique
*
*All the Cartesian pixels, whose coordinates in the cortical domain share the same integer part, are assigned to the same RF.
*The precision of the boundaries of the RF can be improved by breaking each pixel into subpixels and assigning each of them to the correct RF.
*This technique is implemented from: Traver, V., Pla, F.: Log-polar mapping template design: From task-level requirements
*to geometry parameters. Image Vision Comput. 26(10) (2008) 1354-1370
*
*More details can be found in http://dx.doi.org/10.1007/978-3-642-23968-7_5
*/
class CV_EXPORTS LogPolar_Adjacent
{
public:
LogPolar_Adjacent() {}
/**
*Constructor
*\param w the width of the input image
*\param h the height of the input image
*\param center the transformation center: where the output precision is maximal
*\param R the number of rings of the cortical image (default value 70 pixel)
*\param ro0 the radius of the blind spot (default value 3 pixel)
*\param smin the size of the subpixel (default value 0.25 pixel)
*\param full \a 1 (default value) means that the retinal image (the inverse transform) is computed within the circumscribing circle.
* \a 0 means that the retinal image is computed within the inscribed circle.
*\param S the number of sectors of the cortical image (default value 70 pixel).
* Its value is usually internally computed to obtain a pixel aspect ratio equals to 1.
*\param sp \a 1 (default value) means that the parameter \a S is internally computed.
* \a 0 means that the parameter \a S is provided by the user.
*/
LogPolar_Adjacent(int w, int h, Point2i center, int R=70, double ro0=3.0, double smin=0.25, int full=1, int S=117, int sp=1);
/**
*Transformation from Cartesian image to cortical (log-polar) image.
*\param source the Cartesian image
*\return the transformed image (cortical image)
*/
const Mat to_cortical(const Mat &source);
/**
*Transformation from cortical image to retinal (inverse log-polar) image.
*\param source the cortical image
*\return the transformed image (retinal image)
*/
const Mat to_cartesian(const Mat &source);
/**
*Destructor
*/
~LogPolar_Adjacent();
protected:
struct pixel
{
pixel() { u = v = 0; a = 0.; }
int u;
int v;
double a;
};
int S, R, M, N;
int top, bottom,left,right;
double ro0, romax, a, q;
std::vector<std::vector<pixel> > L;
std::vector<double> A;
void subdivide_recursively(double x, double y, int i, int j, double length, double smin);
bool get_uv(double x, double y, int&u, int&v);
void create_map(int M, int N, int R, int S, double ro0, double smin);
};
CV_EXPORTS Mat subspaceProject(InputArray W, InputArray mean, InputArray src);
CV_EXPORTS Mat subspaceReconstruct(InputArray W, InputArray mean, InputArray src);
class CV_EXPORTS LDA
{
public:
// Initializes a LDA with num_components (default 0) and specifies how
// samples are aligned (default dataAsRow=true).
LDA(int num_components = 0) :
_num_components(num_components) {};
// Initializes and performs a Discriminant Analysis with Fisher's
// Optimization Criterion on given data in src and corresponding labels
// in labels. If 0 (or less) number of components are given, they are
// automatically determined for given data in computation.
LDA(InputArrayOfArrays src, InputArray labels,
int num_components = 0) :
_num_components(num_components)
{
this->compute(src, labels); //! compute eigenvectors and eigenvalues
}
// Serializes this object to a given filename.
void save(const std::string& filename) const;
// Deserializes this object from a given filename.
void load(const std::string& filename);
// Serializes this object to a given cv::FileStorage.
void save(FileStorage& fs) const;
// Deserializes this object from a given cv::FileStorage.
void load(const FileStorage& node);
// Destructor.
~LDA() {}
//! Compute the discriminants for data in src and labels.
void compute(InputArrayOfArrays src, InputArray labels);
// Projects samples into the LDA subspace.
Mat project(InputArray src);
// Reconstructs projections from the LDA subspace.
Mat reconstruct(InputArray src);
// Returns the eigenvectors of this LDA.
Mat eigenvectors() const { return _eigenvectors; };
// Returns the eigenvalues of this LDA.
Mat eigenvalues() const { return _eigenvalues; }
protected:
bool _dataAsRow;
int _num_components;
Mat _eigenvectors;
Mat _eigenvalues;
void lda(InputArrayOfArrays src, InputArray labels);
};
class CV_EXPORTS_W FaceRecognizer : public Algorithm
{
public:
//! virtual destructor
virtual ~FaceRecognizer() {}
// Trains a FaceRecognizer.
CV_WRAP virtual void train(InputArrayOfArrays src, InputArray labels) = 0;
// Updates a FaceRecognizer.
CV_WRAP virtual void update(InputArrayOfArrays src, InputArray labels);
// Gets a prediction from a FaceRecognizer.
virtual int predict(InputArray src) const = 0;
// Predicts the label and confidence for a given sample.
CV_WRAP virtual void predict(InputArray src, CV_OUT int &label, CV_OUT double &confidence) const = 0;
// Serializes this object to a given filename.
CV_WRAP virtual void save(const std::string& filename) const;
// Deserializes this object from a given filename.
CV_WRAP virtual void load(const std::string& filename);
// Serializes this object to a given cv::FileStorage.
virtual void save(FileStorage& fs) const = 0;
// Deserializes this object from a given cv::FileStorage.
virtual void load(const FileStorage& fs) = 0;
};
CV_EXPORTS_W Ptr<FaceRecognizer> createEigenFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
CV_EXPORTS_W Ptr<FaceRecognizer> createFisherFaceRecognizer(int num_components = 0, double threshold = DBL_MAX);
CV_EXPORTS_W Ptr<FaceRecognizer> createLBPHFaceRecognizer(int radius=1, int neighbors=8,
int grid_x=8, int grid_y=8, double threshold = DBL_MAX);
enum
{
COLORMAP_AUTUMN = 0,
COLORMAP_BONE = 1,
COLORMAP_JET = 2,
COLORMAP_WINTER = 3,
COLORMAP_RAINBOW = 4,
COLORMAP_OCEAN = 5,
COLORMAP_SUMMER = 6,
COLORMAP_SPRING = 7,
COLORMAP_COOL = 8,
COLORMAP_HSV = 9,
COLORMAP_PINK = 10,
COLORMAP_HOT = 11
};
CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
CV_EXPORTS bool initModule_contrib();
}
#include "opencv2/contrib/retina.hpp"
#include "opencv2/contrib/openfabmap.hpp"
#endif
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
#include "opencv2/contrib.hpp"

4
modules/contrib/include/opencv2/contrib/detection_based_tracker.hpp
View File

@@ -2,8 +2,8 @@
#if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
#include <opencv2/core/core.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/core.hpp>
#include <opencv2/objdetect.hpp>
#include <vector>

9
modules/contrib/include/opencv2/contrib/hybridtracker.hpp
View File

@@ -43,12 +43,11 @@
#ifndef __OPENCV_HYBRIDTRACKER_H_
#define __OPENCV_HYBRIDTRACKER_H_
#include "opencv2/core/core.hpp"
#include "opencv2/core/operations.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/video/tracking.hpp"
#include "opencv2/ml/ml.hpp"
#include "opencv2/ml.hpp"
#ifdef __cplusplus

4
modules/contrib/include/opencv2/contrib/openfabmap.hpp
View File

@@ -52,8 +52,8 @@
#ifndef __OPENCV_OPENFABMAP_H_
#define __OPENCV_OPENFABMAP_H_
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/core.hpp"
#include "opencv2/features2d.hpp"
#include <vector>
#include <list>

2
modules/contrib/include/opencv2/contrib/retina.hpp
View File

@@ -72,7 +72,7 @@
* Author: Alexandre Benoit
*/
#include "opencv2/core/core.hpp" // for all OpenCV core functionalities access, including cv::Exception support
#include "opencv2/core.hpp" // for all OpenCV core functionalities access, including cv::Exception support
#include <valarray>
namespace cv

2
modules/contrib/src/ba.cpp
View File

@@ -40,7 +40,7 @@
//M*/
#include "precomp.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/calib3d.hpp"
#include <iostream>
using namespace cv;

2
modules/contrib/src/chamfermatching.cpp
View File

@@ -46,7 +46,7 @@
#include "precomp.hpp"
#include "opencv2/opencv_modules.hpp"
#ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
#endif
#include <iostream>
#include <queue>

2
modules/contrib/src/featuretracker.cpp
View File

@@ -42,7 +42,7 @@
#include "precomp.hpp"
#include <stdio.h>
#include <iostream>
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/contrib/hybridtracker.hpp"
using namespace cv;

1
modules/contrib/src/gencolors.cpp
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@@ -39,7 +39,6 @@
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "opencv2/core/core.hpp"
#include "precomp.hpp"
#include <iostream>

2
modules/contrib/src/inputoutput.cpp
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@@ -1,5 +1,5 @@
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/contrib.hpp"
#ifdef WIN32
#include <windows.h>

8
modules/contrib/src/precomp.hpp
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@@ -47,10 +47,10 @@
#include "cvconfig.h"
#endif
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/core/internal.hpp"

6
modules/contrib/src/rgbdodometry.cpp
View File

@@ -44,11 +44,11 @@
#define SHOW_DEBUG_IMAGES 0
#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/core.hpp"
#include "opencv2/calib3d.hpp"
#if SHOW_DEBUG_IMAGES
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
#endif
#include <iostream>

4
modules/contrib/test/test_precomp.hpp
View File

@@ -9,8 +9,8 @@
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/contrib.hpp"
#include <iostream>
#endif

2
modules/core/doc/basic_structures.rst
View File

@@ -2425,7 +2425,7 @@ The class provides the following features for all derived classes:
Here is example of SIFT use in your application via Algorithm interface: ::
#include "opencv2/opencv.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/nonfree.hpp"
...

4
modules/core/doc/intro.rst
View File

@@ -30,14 +30,14 @@ All the OpenCV classes and functions are placed into the ``cv`` namespace. There
.. code-block:: c
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
...
cv::Mat H = cv::findHomography(points1, points2, CV_RANSAC, 5);
...
or ::
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
using namespace cv;
...
Mat H = findHomography(points1, points2, CV_RANSAC, 5 );

4726
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4690
modules/core/include/opencv2/core/core.hpp
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2
modules/core/include/opencv2/core/eigen.hpp
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@@ -46,7 +46,7 @@
#ifdef __cplusplus
#include "opencv2/core/core_c.h"
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#if defined _MSC_VER && _MSC_VER >= 1200
#pragma warning( disable: 4714 ) //__forceinline is not inlined

2
modules/core/include/opencv2/core/gpumat.hpp
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@@ -45,7 +45,7 @@
#ifdef __cplusplus
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "opencv2/core/cuda_devptrs.hpp"
namespace cv { namespace gpu

2
modules/core/include/opencv2/core/opengl_interop.hpp → modules/core/include/opencv2/core/opengl.hpp
View File

@@ -45,7 +45,7 @@
#ifdef __cplusplus
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
namespace cv { namespace ogl {

2
modules/core/perf/perf_precomp.hpp
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@@ -9,7 +9,7 @@
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined

2
modules/core/src/gl_core_3_1.cpp
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@@ -1,7 +1,7 @@
#include <string>
#include <sstream>
#include "cvconfig.h"
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "gl_core_3_1.hpp"
#ifdef HAVE_OPENGL

2
modules/core/src/matrix.cpp
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@@ -42,7 +42,7 @@
#include "precomp.hpp"
#include "opencv2/core/gpumat.hpp"
#include "opencv2/core/opengl_interop.hpp"
#include "opencv2/core/opengl.hpp"
/****************************************************************************************\
* [scaled] Identity matrix initialization *

2
modules/core/src/opengl_interop.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "precomp.hpp"
#include "opencv2/core/opengl_interop.hpp"
#include "opencv2/core/opengl.hpp"
#include "opencv2/core/gpumat.hpp"
#ifdef HAVE_OPENGL

2
modules/core/src/precomp.hpp
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@@ -47,7 +47,7 @@
#include "cvconfig.h"
#endif
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "opencv2/core/core_c.h"
#include "opencv2/core/internal.hpp"

2
modules/core/test/test_precomp.hpp
View File

@@ -9,7 +9,7 @@
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/core/core_c.h"
#include <iostream>

1610
modules/features2d/include/opencv2/features2d.hpp Normal file
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1572
modules/features2d/include/opencv2/features2d/features2d.hpp
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6
modules/features2d/perf/perf_precomp.hpp
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@@ -9,9 +9,9 @@
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/features2d.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined

2
modules/features2d/src/blobdetector.cpp
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@@ -48,7 +48,7 @@
#ifdef DEBUG_BLOB_DETECTOR
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui/highgui.hpp"
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_BLOB_DETECTOR
# endif

6
modules/features2d/src/brisk.cpp
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@@ -42,9 +42,9 @@
the IEEE International Conference on Computer Vision (ICCV2011).
*/
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <fstream>
#include <stdlib.h>

4
modules/features2d/src/precomp.hpp
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@@ -47,8 +47,8 @@
#include "cvconfig.h"
#endif
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/core/internal.hpp"

2
modules/features2d/test/test_descriptors_regression.cpp
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@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

2
modules/features2d/test/test_detectors_regression.cpp
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@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

2
modules/features2d/test/test_keypoints.cpp
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@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

2
modules/features2d/test/test_matchers_algorithmic.cpp
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@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

2
modules/features2d/test/test_orb.cpp
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@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

8
modules/features2d/test/test_precomp.hpp
View File

@@ -9,11 +9,11 @@
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#endif

2
modules/features2d/test/test_rotation_and_scale_invariance.cpp
View File

@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

427
modules/flann/include/opencv2/flann.hpp Normal file
View File

@@ -0,0 +1,427 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef _OPENCV_FLANN_HPP_
#define _OPENCV_FLANN_HPP_
#ifdef __cplusplus
#include "opencv2/core/types_c.h"
#include "opencv2/core.hpp"
#include "opencv2/flann/flann_base.hpp"
#include "opencv2/flann/miniflann.hpp"
namespace cvflann
{
CV_EXPORTS flann_distance_t flann_distance_type();
FLANN_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order);
}
namespace cv
{
namespace flann
{
template <typename T> struct CvType {};
template <> struct CvType<unsigned char> { static int type() { return CV_8U; } };
template <> struct CvType<char> { static int type() { return CV_8S; } };
template <> struct CvType<unsigned short> { static int type() { return CV_16U; } };
template <> struct CvType<short> { static int type() { return CV_16S; } };
template <> struct CvType<int> { static int type() { return CV_32S; } };
template <> struct CvType<float> { static int type() { return CV_32F; } };
template <> struct CvType<double> { static int type() { return CV_64F; } };
// bring the flann parameters into this namespace
using ::cvflann::get_param;
using ::cvflann::print_params;
// bring the flann distances into this namespace
using ::cvflann::L2_Simple;
using ::cvflann::L2;
using ::cvflann::L1;
using ::cvflann::MinkowskiDistance;
using ::cvflann::MaxDistance;
using ::cvflann::HammingLUT;
using ::cvflann::Hamming;
using ::cvflann::Hamming2;
using ::cvflann::HistIntersectionDistance;
using ::cvflann::HellingerDistance;
using ::cvflann::ChiSquareDistance;
using ::cvflann::KL_Divergence;
template <typename Distance>
class GenericIndex
{
public:
typedef typename Distance::ElementType ElementType;
typedef typename Distance::ResultType DistanceType;
GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance());
~GenericIndex();
void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
DistanceType radius, const ::cvflann::SearchParams& params);
void save(std::string filename) { nnIndex->save(filename); }
int veclen() const { return nnIndex->veclen(); }
int size() const { return nnIndex->size(); }
::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); }
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); }
private:
::cvflann::Index<Distance>* nnIndex;
};
#define FLANN_DISTANCE_CHECK \
if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \
printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\
"the distance using cvflann::set_distance_type. This is no longer working as expected "\
"(cv::flann::Index always uses L2). You should create the index templated on the distance, "\
"for example for L1 distance use: GenericIndex< L1<float> > \n"); \
}
template <typename Distance>
GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance)
{
CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
nnIndex = new ::cvflann::Index<Distance>(m_dataset, params, distance);
FLANN_DISTANCE_CHECK
nnIndex->buildIndex();
}
template <typename Distance>
GenericIndex<Distance>::~GenericIndex()
{
delete nnIndex;
}
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
FLANN_DISTANCE_CHECK
nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
FLANN_DISTANCE_CHECK
nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
FLANN_DISTANCE_CHECK
return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
FLANN_DISTANCE_CHECK
return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
/**
* @deprecated Use GenericIndex class instead
*/
template <typename T>
class
#ifndef _MSC_VER
FLANN_DEPRECATED
#endif
Index_ {
public:
typedef typename L2<T>::ElementType ElementType;
typedef typename L2<T>::ResultType DistanceType;
Index_(const Mat& features, const ::cvflann::IndexParams& params);
~Index_();
void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);
void save(std::string filename)
{
if (nnIndex_L1) nnIndex_L1->save(filename);
if (nnIndex_L2) nnIndex_L2->save(filename);
}
int veclen() const
{
if (nnIndex_L1) return nnIndex_L1->veclen();
if (nnIndex_L2) return nnIndex_L2->veclen();
}
int size() const
{
if (nnIndex_L1) return nnIndex_L1->size();
if (nnIndex_L2) return nnIndex_L2->size();
}
::cvflann::IndexParams getParameters()
{
if (nnIndex_L1) return nnIndex_L1->getParameters();
if (nnIndex_L2) return nnIndex_L2->getParameters();
}
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
{
if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
}
private:
// providing backwards compatibility for L2 and L1 distances (most common)
::cvflann::Index< L2<ElementType> >* nnIndex_L2;
::cvflann::Index< L1<ElementType> >* nnIndex_L1;
};
#ifdef _MSC_VER
template <typename T>
class FLANN_DEPRECATED Index_;
#endif
template <typename T>
Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
{
printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
nnIndex_L1 = NULL;
nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
nnIndex_L2 = NULL;
}
else {
printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
CV_Assert(0);
}
if (nnIndex_L1) nnIndex_L1->buildIndex();
if (nnIndex_L2) nnIndex_L2->buildIndex();
}
template <typename T>
Index_<T>::~Index_()
{
if (nnIndex_L1) delete nnIndex_L1;
if (nnIndex_L2) delete nnIndex_L2;
}
template <typename T>
void Index_<T>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
template <typename T>
void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename Distance>
int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
Distance d = Distance())
{
typedef typename Distance::ElementType ElementType;
typedef typename Distance::ResultType DistanceType;
CV_Assert(features.type() == CvType<ElementType>::type());
CV_Assert(features.isContinuous());
::cvflann::Matrix<ElementType> m_features((ElementType*)features.ptr<ElementType>(0), features.rows, features.cols);
CV_Assert(centers.type() == CvType<DistanceType>::type());
CV_Assert(centers.isContinuous());
::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols);
return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d);
}
template <typename ELEM_TYPE, typename DIST_TYPE>
FLANN_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
{
printf("[WARNING] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> is deprecated, use "
"cv::flann::hierarchicalClustering<Distance> instead\n");
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
return hierarchicalClustering< L1<ELEM_TYPE> >(features, centers, params);
}
else {
printf("[ERROR] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> only provides backwards "
"compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::hierarchicalClustering<Distance>\n");
CV_Assert(0);
}
}
} } // namespace cv::flann
#endif // __cplusplus
#endif

389
modules/flann/include/opencv2/flann/flann.hpp
View File

@@ -7,11 +7,12 @@
// copy or use the software.
//
//
// License Agreement
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
@@ -40,388 +41,8 @@
//
//M*/
#ifndef _OPENCV_FLANN_HPP_
#define _OPENCV_FLANN_HPP_
#ifdef __cplusplus
#include "opencv2/core/types_c.h"
#include "opencv2/core/core.hpp"
#include "opencv2/flann/flann_base.hpp"
#include "opencv2/flann/miniflann.hpp"
namespace cvflann
{
CV_EXPORTS flann_distance_t flann_distance_type();
FLANN_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order);
}
namespace cv
{
namespace flann
{
template <typename T> struct CvType {};
template <> struct CvType<unsigned char> { static int type() { return CV_8U; } };
template <> struct CvType<char> { static int type() { return CV_8S; } };
template <> struct CvType<unsigned short> { static int type() { return CV_16U; } };
template <> struct CvType<short> { static int type() { return CV_16S; } };
template <> struct CvType<int> { static int type() { return CV_32S; } };
template <> struct CvType<float> { static int type() { return CV_32F; } };
template <> struct CvType<double> { static int type() { return CV_64F; } };
// bring the flann parameters into this namespace
using ::cvflann::get_param;
using ::cvflann::print_params;
// bring the flann distances into this namespace
using ::cvflann::L2_Simple;
using ::cvflann::L2;
using ::cvflann::L1;
using ::cvflann::MinkowskiDistance;
using ::cvflann::MaxDistance;
using ::cvflann::HammingLUT;
using ::cvflann::Hamming;
using ::cvflann::Hamming2;
using ::cvflann::HistIntersectionDistance;
using ::cvflann::HellingerDistance;
using ::cvflann::ChiSquareDistance;
using ::cvflann::KL_Divergence;
template <typename Distance>
class GenericIndex
{
public:
typedef typename Distance::ElementType ElementType;
typedef typename Distance::ResultType DistanceType;
GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance());
~GenericIndex();
void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
DistanceType radius, const ::cvflann::SearchParams& params);
void save(std::string filename) { nnIndex->save(filename); }
int veclen() const { return nnIndex->veclen(); }
int size() const { return nnIndex->size(); }
::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); }
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); }
private:
::cvflann::Index<Distance>* nnIndex;
};
#define FLANN_DISTANCE_CHECK \
if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \
printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\
"the distance using cvflann::set_distance_type. This is no longer working as expected "\
"(cv::flann::Index always uses L2). You should create the index templated on the distance, "\
"for example for L1 distance use: GenericIndex< L1<float> > \n"); \
}
template <typename Distance>
GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance)
{
CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
nnIndex = new ::cvflann::Index<Distance>(m_dataset, params, distance);
FLANN_DISTANCE_CHECK
nnIndex->buildIndex();
}
template <typename Distance>
GenericIndex<Distance>::~GenericIndex()
{
delete nnIndex;
}
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
FLANN_DISTANCE_CHECK
nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
FLANN_DISTANCE_CHECK
nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
FLANN_DISTANCE_CHECK
return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
FLANN_DISTANCE_CHECK
return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
/**
* @deprecated Use GenericIndex class instead
*/
template <typename T>
class
#ifndef _MSC_VER
FLANN_DEPRECATED
#endif
Index_ {
public:
typedef typename L2<T>::ElementType ElementType;
typedef typename L2<T>::ResultType DistanceType;
Index_(const Mat& features, const ::cvflann::IndexParams& params);
~Index_();
void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);
void save(std::string filename)
{
if (nnIndex_L1) nnIndex_L1->save(filename);
if (nnIndex_L2) nnIndex_L2->save(filename);
}
int veclen() const
{
if (nnIndex_L1) return nnIndex_L1->veclen();
if (nnIndex_L2) return nnIndex_L2->veclen();
}
int size() const
{
if (nnIndex_L1) return nnIndex_L1->size();
if (nnIndex_L2) return nnIndex_L2->size();
}
::cvflann::IndexParams getParameters()
{
if (nnIndex_L1) return nnIndex_L1->getParameters();
if (nnIndex_L2) return nnIndex_L2->getParameters();
}
FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
{
if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
}
private:
// providing backwards compatibility for L2 and L1 distances (most common)
::cvflann::Index< L2<ElementType> >* nnIndex_L2;
::cvflann::Index< L1<ElementType> >* nnIndex_L1;
};
#ifdef _MSC_VER
template <typename T>
class FLANN_DEPRECATED Index_;
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
template <typename T>
Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
{
printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
CV_Assert(dataset.type() == CvType<ElementType>::type());
CV_Assert(dataset.isContinuous());
::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
nnIndex_L1 = NULL;
nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
nnIndex_L2 = NULL;
}
else {
printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
CV_Assert(0);
}
if (nnIndex_L1) nnIndex_L1->buildIndex();
if (nnIndex_L2) nnIndex_L2->buildIndex();
}
template <typename T>
Index_<T>::~Index_()
{
if (nnIndex_L1) delete nnIndex_L1;
if (nnIndex_L2) delete nnIndex_L2;
}
template <typename T>
void Index_<T>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
template <typename T>
void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(queries.type() == CvType<ElementType>::type());
CV_Assert(queries.isContinuous());
::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename T>
int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
CV_Assert(query.type() == CvType<ElementType>::type());
CV_Assert(query.isContinuous());
::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
CV_Assert(indices.type() == CV_32S);
CV_Assert(indices.isContinuous());
::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
CV_Assert(dists.type() == CvType<DistanceType>::type());
CV_Assert(dists.isContinuous());
::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
template <typename Distance>
int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
Distance d = Distance())
{
typedef typename Distance::ElementType ElementType;
typedef typename Distance::ResultType DistanceType;
CV_Assert(features.type() == CvType<ElementType>::type());
CV_Assert(features.isContinuous());
::cvflann::Matrix<ElementType> m_features((ElementType*)features.ptr<ElementType>(0), features.rows, features.cols);
CV_Assert(centers.type() == CvType<DistanceType>::type());
CV_Assert(centers.isContinuous());
::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols);
return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d);
}
template <typename ELEM_TYPE, typename DIST_TYPE>
FLANN_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
{
printf("[WARNING] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> is deprecated, use "
"cv::flann::hierarchicalClustering<Distance> instead\n");
if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params);
}
else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
return hierarchicalClustering< L1<ELEM_TYPE> >(features, centers, params);
}
else {
printf("[ERROR] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> only provides backwards "
"compatibility for the L1 and L2 distances. "
"For other distance types you must use cv::flann::hierarchicalClustering<Distance>\n");
CV_Assert(0);
}
}
} } // namespace cv::flann
#endif // __cplusplus
#endif
#include "opencv2/flann.hpp"

2
modules/flann/include/opencv2/flann/miniflann.hpp
View File

@@ -45,7 +45,7 @@
#ifdef __cplusplus
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "opencv2/flann/defines.h"
namespace cv

2
modules/flann/include/opencv2/flann/timer.h
View File

@@ -32,7 +32,7 @@
#define OPENCV_FLANN_TIMER_H
#include <time.h>
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
namespace cvflann
{

2
modules/flann/src/flann.cpp
View File

@@ -27,7 +27,7 @@
*************************************************************************/
#include "precomp.hpp"
#include "opencv2/flann/flann.hpp"
#include "opencv2/flann.hpp"
namespace cvflann
{

2
modules/flann/src/precomp.hpp
View File

@@ -8,7 +8,7 @@
#ifdef HAVE_CVCONFIG_H
# include "cvconfig.h"
#endif
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "opencv2/core/internal.hpp"
#include "opencv2/flann/miniflann.hpp"

6
modules/flann/test/test_precomp.hpp
View File

@@ -9,9 +9,9 @@
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/flann/flann.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/core.hpp"
#include "opencv2/flann.hpp"
#include <iostream>
#endif

2
modules/gpu/CMakeLists.txt
View File

@@ -7,7 +7,7 @@ ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video o
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda")
file(GLOB lib_hdrs "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB lib_hdrs "include/opencv2/*.hpp" "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB lib_device_hdrs "include/opencv2/${name}/device/*.hpp" "include/opencv2/${name}/device/*.h")
file(GLOB lib_device_hdrs_detail "include/opencv2/${name}/device/detail/*.hpp" "include/opencv2/${name}/device/detail/*.h")
file(GLOB lib_int_hdrs "src/*.hpp" "src/*.h")

13
modules/gpu/app/nv_perf_test/main.cpp
View File

@@ -1,12 +1,11 @@
#include <cstdio>
#define HAVE_CUDA 1
#include <opencv2/core/core.hpp>
#include <opencv2/gpu/gpu.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/video.hpp>
#include <opencv2/legacy/legacy.hpp>
#include <opencv2/ts/ts.hpp>
#include <opencv2/ts/ts_perf.hpp>
#include <opencv2/core.hpp>
#include <opencv2/gpu.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/video.hpp>
#include <opencv2/legacy.hpp>
#include <opencv2/ts.hpp>
static void printOsInfo()
{

2681
modules/gpu/include/opencv2/gpu.hpp Normal file
View File

File diff suppressed because it is too large Load Diff

2645
modules/gpu/include/opencv2/gpu/gpu.hpp
View File

File diff suppressed because it is too large Load Diff

2
modules/gpu/include/opencv2/gpu/stream_accessor.hpp
View File

@@ -43,7 +43,7 @@
#ifndef __OPENCV_GPU_STREAM_ACCESSOR_HPP__
#define __OPENCV_GPU_STREAM_ACCESSOR_HPP__
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/gpu.hpp"
#include "cuda_runtime_api.h"
namespace cv

21
modules/gpu/perf/perf_precomp.hpp
View File

@@ -18,18 +18,17 @@
#include <cuda_runtime.h>
#endif
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "opencv2/photo/photo.hpp"
#include "opencv2/core.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/video.hpp"
#include "opencv2/nonfree.hpp"
#include "opencv2/legacy.hpp"
#include "opencv2/photo.hpp"
#include "utility.hpp"

4
modules/gpu/perf/utility.hpp
View File

@@ -1,8 +1,8 @@
#ifndef __OPENCV_PERF_GPU_UTILITY_HPP__
#define __OPENCV_PERF_GPU_UTILITY_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/ts/ts_perf.hpp"
cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);

13
modules/gpu/perf4au/main.cpp
View File

@@ -2,13 +2,12 @@
#ifdef HAVE_CVCONFIG_H
#include "cvconfig.h"
#endif
#include "opencv2/core/core.hpp"
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/core.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/video.hpp"
#include "opencv2/legacy.hpp"
#include "opencv2/ts.hpp"
static void printOsInfo()
{

8
modules/gpu/src/precomp.hpp
View File

@@ -66,12 +66,12 @@
#include <memory>
#include <string>
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/core/internal.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/video.hpp"
#if defined WIN32 || defined WINCE
#include <windows.h>

4
modules/gpu/test/interpolation.hpp
View File

@@ -42,8 +42,8 @@
#ifndef __OPENCV_TEST_INTERPOLATION_HPP__
#define __OPENCV_TEST_INTERPOLATION_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
{

2
modules/gpu/test/nvidia/NCVTestSourceProvider.hpp
View File

@@ -14,7 +14,7 @@
#include <memory>
#include "NCV.hpp"
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui.hpp>
template <class T>

21
modules/gpu/test/test_precomp.hpp
View File

@@ -69,17 +69,16 @@
#include <cuda.h>
#include <cuda_runtime.h>
#include "opencv2/core/core.hpp"
#include "opencv2/core/opengl_interop.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/video/video.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/gpu/gpu.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "opencv2/core.hpp"
#include "opencv2/core/opengl.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/video.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/nonfree.hpp"
#include "opencv2/legacy.hpp"
#include "utility.hpp"
#include "interpolation.hpp"

7
modules/gpu/test/utility.hpp
View File

@@ -42,11 +42,10 @@
#ifndef __OPENCV_GPU_TEST_UTILITY_HPP__
#define __OPENCV_GPU_TEST_UTILITY_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
#include "opencv2/core/gpumat.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ts/ts.hpp"
#include "opencv2/ts/ts_perf.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/ts.hpp"
//////////////////////////////////////////////////////////////////////
// random generators

2
modules/highgui/CMakeLists.txt
View File

@@ -74,7 +74,7 @@ set(highgui_srcs
src/window.cpp
)
file(GLOB highgui_ext_hdrs "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
file(GLOB highgui_ext_hdrs "include/opencv2/*.hpp" "include/opencv2/${name}/*.hpp" "include/opencv2/${name}/*.h")
if(HAVE_QT)
if (HAVE_QT_OPENGL)

250
modules/highgui/include/opencv2/highgui.hpp Normal file
View File

@@ -0,0 +1,250 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __OPENCV_HIGHGUI_HPP__
#define __OPENCV_HIGHGUI_HPP__
#include "opencv2/core.hpp"
#include "opencv2/highgui/highgui_c.h"
#ifdef __cplusplus
struct CvCapture;
struct CvVideoWriter;
namespace cv
{
enum {
// Flags for namedWindow
WINDOW_NORMAL = CV_WINDOW_NORMAL, // the user can resize the window (no constraint) / also use to switch a fullscreen window to a normal size
WINDOW_AUTOSIZE = CV_WINDOW_AUTOSIZE, // the user cannot resize the window, the size is constrainted by the image displayed
WINDOW_OPENGL = CV_WINDOW_OPENGL, // window with opengl support
// Flags for set / getWindowProperty
WND_PROP_FULLSCREEN = CV_WND_PROP_FULLSCREEN, // fullscreen property
WND_PROP_AUTOSIZE = CV_WND_PROP_AUTOSIZE, // autosize property
WND_PROP_ASPECT_RATIO = CV_WND_PROP_ASPECTRATIO, // window's aspect ration
WND_PROP_OPENGL = CV_WND_PROP_OPENGL // opengl support
};
CV_EXPORTS_W void namedWindow(const std::string& winname, int flags = WINDOW_AUTOSIZE);
CV_EXPORTS_W void destroyWindow(const std::string& winname);
CV_EXPORTS_W void destroyAllWindows();
CV_EXPORTS_W int startWindowThread();
CV_EXPORTS_W int waitKey(int delay = 0);
CV_EXPORTS_W void imshow(const std::string& winname, InputArray mat);
CV_EXPORTS_W void resizeWindow(const std::string& winname, int width, int height);
CV_EXPORTS_W void moveWindow(const std::string& winname, int x, int y);
CV_EXPORTS_W void setWindowProperty(const std::string& winname, int prop_id, double prop_value);//YV
CV_EXPORTS_W double getWindowProperty(const std::string& winname, int prop_id);//YV
enum
{
EVENT_MOUSEMOVE =0,
EVENT_LBUTTONDOWN =1,
EVENT_RBUTTONDOWN =2,
EVENT_MBUTTONDOWN =3,
EVENT_LBUTTONUP =4,
EVENT_RBUTTONUP =5,
EVENT_MBUTTONUP =6,
EVENT_LBUTTONDBLCLK =7,
EVENT_RBUTTONDBLCLK =8,
EVENT_MBUTTONDBLCLK =9
};
enum
{
EVENT_FLAG_LBUTTON =1,
EVENT_FLAG_RBUTTON =2,
EVENT_FLAG_MBUTTON =4,
EVENT_FLAG_CTRLKEY =8,
EVENT_FLAG_SHIFTKEY =16,
EVENT_FLAG_ALTKEY =32
};
typedef void (*MouseCallback)(int event, int x, int y, int flags, void* userdata);
//! assigns callback for mouse events
CV_EXPORTS void setMouseCallback(const std::string& winname, MouseCallback onMouse, void* userdata = 0);
typedef void (CV_CDECL *TrackbarCallback)(int pos, void* userdata);
CV_EXPORTS int createTrackbar(const std::string& trackbarname, const std::string& winname,
int* value, int count,
TrackbarCallback onChange = 0,
void* userdata = 0);
CV_EXPORTS_W int getTrackbarPos(const std::string& trackbarname, const std::string& winname);
CV_EXPORTS_W void setTrackbarPos(const std::string& trackbarname, const std::string& winname, int pos);
// OpenGL support
typedef void (*OpenGlDrawCallback)(void* userdata);
CV_EXPORTS void setOpenGlDrawCallback(const std::string& winname, OpenGlDrawCallback onOpenGlDraw, void* userdata = 0);
CV_EXPORTS void setOpenGlContext(const std::string& winname);
CV_EXPORTS void updateWindow(const std::string& winname);
//Only for Qt
CV_EXPORTS CvFont fontQt(const std::string& nameFont, int pointSize=-1,
Scalar color=Scalar::all(0), int weight=CV_FONT_NORMAL,
int style=CV_STYLE_NORMAL, int spacing=0);
CV_EXPORTS void addText( const Mat& img, const std::string& text, Point org, CvFont font);
CV_EXPORTS void displayOverlay(const std::string& winname, const std::string& text, int delayms CV_DEFAULT(0));
CV_EXPORTS void displayStatusBar(const std::string& winname, const std::string& text, int delayms CV_DEFAULT(0));
CV_EXPORTS void saveWindowParameters(const std::string& windowName);
CV_EXPORTS void loadWindowParameters(const std::string& windowName);
CV_EXPORTS int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]);
CV_EXPORTS void stopLoop();
typedef void (CV_CDECL *ButtonCallback)(int state, void* userdata);
CV_EXPORTS int createButton( const std::string& bar_name, ButtonCallback on_change,
void* userdata=NULL, int type=CV_PUSH_BUTTON,
bool initial_button_state=0);
//-------------------------
enum
{
// 8bit, color or not
IMREAD_UNCHANGED =-1,
// 8bit, gray
IMREAD_GRAYSCALE =0,
// ?, color
IMREAD_COLOR =1,
// any depth, ?
IMREAD_ANYDEPTH =2,
// ?, any color
IMREAD_ANYCOLOR =4
};
enum
{
IMWRITE_JPEG_QUALITY =1,
IMWRITE_PNG_COMPRESSION =16,
IMWRITE_PNG_STRATEGY =17,
IMWRITE_PNG_BILEVEL =18,
IMWRITE_PNG_STRATEGY_DEFAULT =0,
IMWRITE_PNG_STRATEGY_FILTERED =1,
IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY =2,
IMWRITE_PNG_STRATEGY_RLE =3,
IMWRITE_PNG_STRATEGY_FIXED =4,
IMWRITE_PXM_BINARY =32
};
CV_EXPORTS_W Mat imread( const std::string& filename, int flags=1 );
CV_EXPORTS_W bool imwrite( const std::string& filename, InputArray img,
const std::vector<int>& params=std::vector<int>());
CV_EXPORTS_W Mat imdecode( InputArray buf, int flags );
CV_EXPORTS Mat imdecode( InputArray buf, int flags, Mat* dst );
CV_EXPORTS_W bool imencode( const std::string& ext, InputArray img,
CV_OUT std::vector<uchar>& buf,
const std::vector<int>& params=std::vector<int>());
#ifndef CV_NO_VIDEO_CAPTURE_CPP_API
template<> void CV_EXPORTS Ptr<CvCapture>::delete_obj();
template<> void CV_EXPORTS Ptr<CvVideoWriter>::delete_obj();
class CV_EXPORTS_W VideoCapture
{
public:
CV_WRAP VideoCapture();
CV_WRAP VideoCapture(const std::string& filename);
CV_WRAP VideoCapture(int device);
virtual ~VideoCapture();
CV_WRAP virtual bool open(const std::string& filename);
CV_WRAP virtual bool open(int device);
CV_WRAP virtual bool isOpened() const;
CV_WRAP virtual void release();
CV_WRAP virtual bool grab();
CV_WRAP virtual bool retrieve(CV_OUT Mat& image, int channel=0);
virtual VideoCapture& operator >> (CV_OUT Mat& image);
CV_WRAP virtual bool read(CV_OUT Mat& image);
CV_WRAP virtual bool set(int propId, double value);
CV_WRAP virtual double get(int propId);
protected:
Ptr<CvCapture> cap;
};
class CV_EXPORTS_W VideoWriter
{
public:
CV_WRAP VideoWriter();
CV_WRAP VideoWriter(const std::string& filename, int fourcc, double fps,
Size frameSize, bool isColor=true);
virtual ~VideoWriter();
CV_WRAP virtual bool open(const std::string& filename, int fourcc, double fps,
Size frameSize, bool isColor=true);
CV_WRAP virtual bool isOpened() const;
CV_WRAP virtual void release();
virtual VideoWriter& operator << (const Mat& image);
CV_WRAP virtual void write(const Mat& image);
protected:
Ptr<CvVideoWriter> writer;
};
#endif
}
#endif
#endif

2
modules/highgui/include/opencv2/highgui/cap_ios.h
View File

@@ -32,7 +32,7 @@
#import <Accelerate/Accelerate.h>
#import <AVFoundation/AVFoundation.h>
#import <ImageIO/ImageIO.h>
#include "opencv2/core/core.hpp"
#include "opencv2/core.hpp"
/////////////////////////////////////// CvAbstractCamera /////////////////////////////////////

210
modules/highgui/include/opencv2/highgui/highgui.hpp
View File

@@ -12,6 +12,7 @@
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
@@ -40,211 +41,8 @@
//
//M*/
#ifndef __OPENCV_HIGHGUI_HPP__
#define __OPENCV_HIGHGUI_HPP__
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui_c.h"
#ifdef __cplusplus
struct CvCapture;
struct CvVideoWriter;
namespace cv
{
enum {
// Flags for namedWindow
WINDOW_NORMAL = CV_WINDOW_NORMAL, // the user can resize the window (no constraint) / also use to switch a fullscreen window to a normal size
WINDOW_AUTOSIZE = CV_WINDOW_AUTOSIZE, // the user cannot resize the window, the size is constrainted by the image displayed
WINDOW_OPENGL = CV_WINDOW_OPENGL, // window with opengl support
// Flags for set / getWindowProperty
WND_PROP_FULLSCREEN = CV_WND_PROP_FULLSCREEN, // fullscreen property
WND_PROP_AUTOSIZE = CV_WND_PROP_AUTOSIZE, // autosize property
WND_PROP_ASPECT_RATIO = CV_WND_PROP_ASPECTRATIO, // window's aspect ration
WND_PROP_OPENGL = CV_WND_PROP_OPENGL // opengl support
};
CV_EXPORTS_W void namedWindow(const std::string& winname, int flags = WINDOW_AUTOSIZE);
CV_EXPORTS_W void destroyWindow(const std::string& winname);
CV_EXPORTS_W void destroyAllWindows();
CV_EXPORTS_W int startWindowThread();
CV_EXPORTS_W int waitKey(int delay = 0);
CV_EXPORTS_W void imshow(const std::string& winname, InputArray mat);
CV_EXPORTS_W void resizeWindow(const std::string& winname, int width, int height);
CV_EXPORTS_W void moveWindow(const std::string& winname, int x, int y);
CV_EXPORTS_W void setWindowProperty(const std::string& winname, int prop_id, double prop_value);//YV
CV_EXPORTS_W double getWindowProperty(const std::string& winname, int prop_id);//YV
enum
{
EVENT_MOUSEMOVE =0,
EVENT_LBUTTONDOWN =1,
EVENT_RBUTTONDOWN =2,
EVENT_MBUTTONDOWN =3,
EVENT_LBUTTONUP =4,
EVENT_RBUTTONUP =5,
EVENT_MBUTTONUP =6,
EVENT_LBUTTONDBLCLK =7,
EVENT_RBUTTONDBLCLK =8,
EVENT_MBUTTONDBLCLK =9
};
enum
{
EVENT_FLAG_LBUTTON =1,
EVENT_FLAG_RBUTTON =2,
EVENT_FLAG_MBUTTON =4,
EVENT_FLAG_CTRLKEY =8,
EVENT_FLAG_SHIFTKEY =16,
EVENT_FLAG_ALTKEY =32
};
typedef void (*MouseCallback)(int event, int x, int y, int flags, void* userdata);
//! assigns callback for mouse events
CV_EXPORTS void setMouseCallback(const std::string& winname, MouseCallback onMouse, void* userdata = 0);
typedef void (CV_CDECL *TrackbarCallback)(int pos, void* userdata);
CV_EXPORTS int createTrackbar(const std::string& trackbarname, const std::string& winname,
int* value, int count,
TrackbarCallback onChange = 0,
void* userdata = 0);
CV_EXPORTS_W int getTrackbarPos(const std::string& trackbarname, const std::string& winname);
CV_EXPORTS_W void setTrackbarPos(const std::string& trackbarname, const std::string& winname, int pos);
// OpenGL support
typedef void (*OpenGlDrawCallback)(void* userdata);
CV_EXPORTS void setOpenGlDrawCallback(const std::string& winname, OpenGlDrawCallback onOpenGlDraw, void* userdata = 0);
CV_EXPORTS void setOpenGlContext(const std::string& winname);
CV_EXPORTS void updateWindow(const std::string& winname);
//Only for Qt
CV_EXPORTS CvFont fontQt(const std::string& nameFont, int pointSize=-1,
Scalar color=Scalar::all(0), int weight=CV_FONT_NORMAL,
int style=CV_STYLE_NORMAL, int spacing=0);
CV_EXPORTS void addText( const Mat& img, const std::string& text, Point org, CvFont font);
CV_EXPORTS void displayOverlay(const std::string& winname, const std::string& text, int delayms CV_DEFAULT(0));
CV_EXPORTS void displayStatusBar(const std::string& winname, const std::string& text, int delayms CV_DEFAULT(0));
CV_EXPORTS void saveWindowParameters(const std::string& windowName);
CV_EXPORTS void loadWindowParameters(const std::string& windowName);
CV_EXPORTS int startLoop(int (*pt2Func)(int argc, char *argv[]), int argc, char* argv[]);
CV_EXPORTS void stopLoop();
typedef void (CV_CDECL *ButtonCallback)(int state, void* userdata);
CV_EXPORTS int createButton( const std::string& bar_name, ButtonCallback on_change,
void* userdata=NULL, int type=CV_PUSH_BUTTON,
bool initial_button_state=0);
//-------------------------
enum
{
// 8bit, color or not
IMREAD_UNCHANGED =-1,
// 8bit, gray
IMREAD_GRAYSCALE =0,
// ?, color
IMREAD_COLOR =1,
// any depth, ?
IMREAD_ANYDEPTH =2,
// ?, any color
IMREAD_ANYCOLOR =4
};
enum
{
IMWRITE_JPEG_QUALITY =1,
IMWRITE_PNG_COMPRESSION =16,
IMWRITE_PNG_STRATEGY =17,
IMWRITE_PNG_BILEVEL =18,
IMWRITE_PNG_STRATEGY_DEFAULT =0,
IMWRITE_PNG_STRATEGY_FILTERED =1,
IMWRITE_PNG_STRATEGY_HUFFMAN_ONLY =2,
IMWRITE_PNG_STRATEGY_RLE =3,
IMWRITE_PNG_STRATEGY_FIXED =4,
IMWRITE_PXM_BINARY =32
};
CV_EXPORTS_W Mat imread( const std::string& filename, int flags=1 );
CV_EXPORTS_W bool imwrite( const std::string& filename, InputArray img,
const std::vector<int>& params=std::vector<int>());
CV_EXPORTS_W Mat imdecode( InputArray buf, int flags );
CV_EXPORTS Mat imdecode( InputArray buf, int flags, Mat* dst );
CV_EXPORTS_W bool imencode( const std::string& ext, InputArray img,
CV_OUT std::vector<uchar>& buf,
const std::vector<int>& params=std::vector<int>());
#ifndef CV_NO_VIDEO_CAPTURE_CPP_API
template<> void CV_EXPORTS Ptr<CvCapture>::delete_obj();
template<> void CV_EXPORTS Ptr<CvVideoWriter>::delete_obj();
class CV_EXPORTS_W VideoCapture
{
public:
CV_WRAP VideoCapture();
CV_WRAP VideoCapture(const std::string& filename);
CV_WRAP VideoCapture(int device);
virtual ~VideoCapture();
CV_WRAP virtual bool open(const std::string& filename);
CV_WRAP virtual bool open(int device);
CV_WRAP virtual bool isOpened() const;
CV_WRAP virtual void release();
CV_WRAP virtual bool grab();
CV_WRAP virtual bool retrieve(CV_OUT Mat& image, int channel=0);
virtual VideoCapture& operator >> (CV_OUT Mat& image);
CV_WRAP virtual bool read(CV_OUT Mat& image);
CV_WRAP virtual bool set(int propId, double value);
CV_WRAP virtual double get(int propId);
protected:
Ptr<CvCapture> cap;
};
class CV_EXPORTS_W VideoWriter
{
public:
CV_WRAP VideoWriter();
CV_WRAP VideoWriter(const std::string& filename, int fourcc, double fps,
Size frameSize, bool isColor=true);
virtual ~VideoWriter();
CV_WRAP virtual bool open(const std::string& filename, int fourcc, double fps,
Size frameSize, bool isColor=true);
CV_WRAP virtual bool isOpened() const;
CV_WRAP virtual void release();
virtual VideoWriter& operator << (const Mat& image);
CV_WRAP virtual void write(const Mat& image);
protected:
Ptr<CvVideoWriter> writer;
};
#ifdef __OPENCV_BUILD
#error this is a compatibility header which should not be used inside the OpenCV library
#endif
}
#endif
#endif
#include "opencv2/highgui.hpp"

4
modules/highgui/perf/perf_precomp.hpp
View File

@@ -9,8 +9,8 @@
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts/ts.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/highgui.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined

2
modules/highgui/src/cap_android.cpp
View File

@@ -43,7 +43,7 @@
#ifdef HAVE_ANDROID_NATIVE_CAMERA
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/imgproc.hpp>
#include <pthread.h>
#include <android/log.h>
#include <camera_activity.hpp>

2
modules/highgui/src/cap_avfoundation.mm
View File

@@ -30,7 +30,7 @@
*/
#include "precomp.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#import <AVFoundation/AVFoundation.h>
#import <Foundation/NSException.h>

2
modules/highgui/src/cap_ffmpeg_impl.hpp
View File

@@ -59,11 +59,11 @@ extern "C" {
#include "ffmpeg_codecs.hpp"
#include <libavutil/opt.h>
#include <libavutil/mathematics.h>
#ifdef WIN32
#define HAVE_FFMPEG_SWSCALE 1
#include <libavutil/opt.h>
#include <libavcodec/avcodec.h>
#include <libswscale/swscale.h>
#else

4
modules/highgui/src/cap_openni.cpp
View File

@@ -39,8 +39,8 @@
//
//M*/
#include "precomp.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#ifdef HAVE_OPENNI

2
modules/highgui/src/cap_qtkit.mm
View File

@@ -29,7 +29,7 @@
*/
#include "precomp.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#import <QTKit/QTKit.h>

2
modules/highgui/src/grfmt_webp.cpp
View File

@@ -51,7 +51,7 @@
#include "grfmt_webp.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/imgproc.hpp"
namespace cv
{

2
modules/highgui/src/precomp.hpp
View File

@@ -44,7 +44,7 @@
#include "cvconfig.h"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/core/internal.hpp"

2
modules/highgui/src/window.cpp
View File

@@ -41,7 +41,7 @@
#include "precomp.hpp"
#include <map>
#include "opencv2/core/opengl_interop.hpp"
#include "opencv2/core/opengl.hpp"
// in later times, use this file as a dispatcher to implementations like cvcap.cpp

2
modules/highgui/src/window_w32.cpp
View File

@@ -75,7 +75,7 @@
#include <algorithm>
#include <vector>
#include <functional>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#include <GL\gl.h>
#endif

2
modules/highgui/test/test_drawing.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace std;
using namespace cv;

2
modules/highgui/test/test_ffmpeg.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;

2
modules/highgui/test/test_fourcc.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#undef DEFINE_GUID
#define DEFINE_GUID(n, fourcc, a1, a2, a3, a4, a5, a6, a7, a8, a9, a10) fourcc,

2
modules/highgui/test/test_framecount.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#include <stdio.h>
using namespace cv;

2
modules/highgui/test/test_grfmt.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;
using namespace std;

2
modules/highgui/test/test_gui.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#if defined HAVE_GTK || defined HAVE_QT || defined WIN32 || defined _WIN32 || defined HAVE_CARBON || defined HAVE_COCOA

2
modules/highgui/test/test_positioning.cpp
View File

@@ -41,7 +41,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/highgui.hpp"
#include <stdio.h>
using namespace cv;

4
modules/highgui/test/test_precomp.hpp
View File

@@ -13,8 +13,8 @@
# include "cvconfig.h"
#endif
#include "opencv2/ts/ts.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/ts.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include <iostream>

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