/* Converted to D from cv.h by */ module opencv.c.cv; /*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*/ private import opencv.c.cxtypes; private import opencv.c.cvtypes; /+ #ifndef _CV_H_ #define _CV_H_ #ifdef __IPL_H__ #define HAVE_IPL #endif #ifndef SKIP_INCLUDES #if defined(_CH_) #pragma package #include LOAD_CHDL(cv) #endif #endif #include "cxcore.h" #include "cvtypes.h" //C #ifdef __cplusplus //C extern "C" { //C #endif +/ extern(C) { /+ /****************************************************************************************\ * Image Processing * \****************************************************************************************/ /* Copies source 2D array inside of the larger destination array and makes a border of the specified type (IPL_BORDER_*) around the copied area. */ CVAPI(void) cvCopyMakeBorder( const CvArr* src, CvArr* dst, CvPoint offset, int bordertype, CvScalar value CV_DEFAULT(cvScalarAll(0))); #define CV_BLUR_NO_SCALE 0 #define CV_BLUR 1 #define CV_GAUSSIAN 2 #define CV_MEDIAN 3 #define CV_BILATERAL 4 /* Smoothes array (removes noise) */ CVAPI(void) cvSmooth( const CvArr* src, CvArr* dst, int smoothtype CV_DEFAULT(CV_GAUSSIAN), int size1 CV_DEFAULT(3), int size2 CV_DEFAULT(0), double sigma1 CV_DEFAULT(0), double sigma2 CV_DEFAULT(0)); /* Convolves the image with the kernel */ CVAPI(void) cvFilter2D( const CvArr* src, CvArr* dst, const CvMat* kernel, CvPoint anchor CV_DEFAULT(cvPoint(-1,-1))); /* Finds integral image: SUM(X,Y) = sum(xnext[(edge + (int)type) & 3]; return (edge & ~3) + ((edge + ((int)type >> 4)) & 3); } CV_INLINE CvSubdiv2DPoint* cvSubdiv2DEdgeOrg( CvSubdiv2DEdge edge ) { CvQuadEdge2D* e = (CvQuadEdge2D*)(edge & ~3); return (CvSubdiv2DPoint*)e->pt[edge & 3]; } CV_INLINE CvSubdiv2DPoint* cvSubdiv2DEdgeDst( CvSubdiv2DEdge edge ) { CvQuadEdge2D* e = (CvQuadEdge2D*)(edge & ~3); return (CvSubdiv2DPoint*)e->pt[(edge + 2) & 3]; } CV_INLINE double cvTriangleArea( CvPoint2D32f a, CvPoint2D32f b, CvPoint2D32f c ) { return (b.x - a.x) * (c.y - a.y) - (b.y - a.y) * (c.x - a.x); } /****************************************************************************************\ * Contour Processing and Shape Analysis * \****************************************************************************************/ #define CV_POLY_APPROX_DP 0 /* Approximates a single polygonal curve (contour) or a tree of polygonal curves (contours) */ CVAPI(CvSeq*) cvApproxPoly( const void* src_seq, int header_size, CvMemStorage* storage, int method, double parameter, int parameter2 CV_DEFAULT(0)); #define CV_DOMINANT_IPAN 1 /* Finds high-curvature points of the contour */ CVAPI(CvSeq*) cvFindDominantPoints( CvSeq* contour, CvMemStorage* storage, int method CV_DEFAULT(CV_DOMINANT_IPAN), double parameter1 CV_DEFAULT(0), double parameter2 CV_DEFAULT(0), double parameter3 CV_DEFAULT(0), double parameter4 CV_DEFAULT(0)); /* Calculates perimeter of a contour or length of a part of contour */ CVAPI(double) cvArcLength( const void* curve, CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ), int is_closed CV_DEFAULT(-1)); #define cvContourPerimeter( contour ) cvArcLength( contour, CV_WHOLE_SEQ, 1 ) /* Calculates contour boundning rectangle (update=1) or just retrieves pre-calculated rectangle (update=0) */ CVAPI(CvRect) cvBoundingRect( CvArr* points, int update CV_DEFAULT(0) ); /* Calculates area of a contour or contour segment */ CVAPI(double) cvContourArea( const CvArr* contour, CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ)); /* Finds minimum area rotated rectangle bounding a set of points */ CVAPI(CvBox2D) cvMinAreaRect2( const CvArr* points, CvMemStorage* storage CV_DEFAULT(NULL)); /* Finds minimum enclosing circle for a set of points */ CVAPI(int) cvMinEnclosingCircle( const CvArr* points, CvPoint2D32f* center, float* radius ); #define CV_CONTOURS_MATCH_I1 1 #define CV_CONTOURS_MATCH_I2 2 #define CV_CONTOURS_MATCH_I3 3 /* Compares two contours by matching their moments */ CVAPI(double) cvMatchShapes( const void* object1, const void* object2, int method, double parameter CV_DEFAULT(0)); /* Builds hierarhical representation of a contour */ CVAPI(CvContourTree*) cvCreateContourTree( const CvSeq* contour, CvMemStorage* storage, double threshold ); /* Reconstruct (completelly or partially) contour a from contour tree */ CVAPI(CvSeq*) cvContourFromContourTree( const CvContourTree* tree, CvMemStorage* storage, CvTermCriteria criteria ); /* Compares two contour trees */ #define CV_CONTOUR_TREES_MATCH_I1 1 CVAPI(double) cvMatchContourTrees( const CvContourTree* tree1, const CvContourTree* tree2, int method, double threshold ); /* Calculates histogram of a contour */ CVAPI(void) cvCalcPGH( const CvSeq* contour, CvHistogram* hist ); #define CV_CLOCKWISE 1 #define CV_COUNTER_CLOCKWISE 2 /* Calculates exact convex hull of 2d point set */ CVAPI(CvSeq*) cvConvexHull2( const CvArr* input, void* hull_storage CV_DEFAULT(NULL), int orientation CV_DEFAULT(CV_CLOCKWISE), int return_points CV_DEFAULT(0)); /* Checks whether the contour is convex or not (returns 1 if convex, 0 if not) */ CVAPI(int) cvCheckContourConvexity( const CvArr* contour ); /* Finds convexity defects for the contour */ CVAPI(CvSeq*) cvConvexityDefects( const CvArr* contour, const CvArr* convexhull, CvMemStorage* storage CV_DEFAULT(NULL)); /* Fits ellipse into a set of 2d points */ CVAPI(CvBox2D) cvFitEllipse2( const CvArr* points ); /* Finds minimum rectangle containing two given rectangles */ CVAPI(CvRect) cvMaxRect( const CvRect* rect1, const CvRect* rect2 ); /* Finds coordinates of the box vertices */ CVAPI(void) cvBoxPoints( CvBox2D box, CvPoint2D32f pt[4] ); /* Initializes sequence header for a matrix (column or row vector) of points - a wrapper for cvMakeSeqHeaderForArray (it does not initialize bounding rectangle!!!) */ CVAPI(CvSeq*) cvPointSeqFromMat( int seq_kind, const CvArr* mat, CvContour* contour_header, CvSeqBlock* block ); /* Checks whether the point is inside polygon, outside, on an edge (at a vertex). Returns positive, negative or zero value, correspondingly. Optionally, measures a signed distance between the point and the nearest polygon edge (measure_dist=1) */ CVAPI(double) cvPointPolygonTest( const CvArr* contour, CvPoint2D32f pt, int measure_dist ); /****************************************************************************************\ * Histogram functions * \****************************************************************************************/ /* Creates new histogram */ CVAPI(CvHistogram*) cvCreateHist( int dims, int* sizes, int type, float** ranges CV_DEFAULT(NULL), int uniform CV_DEFAULT(1)); /* Assignes histogram bin ranges */ CVAPI(void) cvSetHistBinRanges( CvHistogram* hist, float** ranges, int uniform CV_DEFAULT(1)); /* Creates histogram header for array */ CVAPI(CvHistogram*) cvMakeHistHeaderForArray( int dims, int* sizes, CvHistogram* hist, float* data, float** ranges CV_DEFAULT(NULL), int uniform CV_DEFAULT(1)); /* Releases histogram */ CVAPI(void) cvReleaseHist( CvHistogram** hist ); /* Clears all the histogram bins */ CVAPI(void) cvClearHist( CvHistogram* hist ); /* Finds indices and values of minimum and maximum histogram bins */ CVAPI(void) cvGetMinMaxHistValue( const CvHistogram* hist, float* min_value, float* max_value, int* min_idx CV_DEFAULT(NULL), int* max_idx CV_DEFAULT(NULL)); /* Normalizes histogram by dividing all bins by sum of the bins, multiplied by . After that sum of histogram bins is equal to */ CVAPI(void) cvNormalizeHist( CvHistogram* hist, double factor ); /* Clear all histogram bins that are below the threshold */ CVAPI(void) cvThreshHist( CvHistogram* hist, double threshold ); #define CV_COMP_CORREL 0 #define CV_COMP_CHISQR 1 #define CV_COMP_INTERSECT 2 #define CV_COMP_BHATTACHARYYA 3 /* Compares two histogram */ CVAPI(double) cvCompareHist( const CvHistogram* hist1, const CvHistogram* hist2, int method); /* Copies one histogram to another. Destination histogram is created if the destination pointer is NULL */ CVAPI(void) cvCopyHist( const CvHistogram* src, CvHistogram** dst ); /* Calculates bayesian probabilistic histograms (each or src and dst is an array of histograms */ CVAPI(void) cvCalcBayesianProb( CvHistogram** src, int number, CvHistogram** dst); /* Calculates array histogram */ CVAPI(void) cvCalcArrHist( CvArr** arr, CvHistogram* hist, int accumulate CV_DEFAULT(0), const CvArr* mask CV_DEFAULT(NULL) ); CV_INLINE void cvCalcHist( IplImage** image, CvHistogram* hist, int accumulate CV_DEFAULT(0), const CvArr* mask CV_DEFAULT(NULL) ) { cvCalcArrHist( (CvArr**)image, hist, accumulate, mask ); } /* Calculates back project */ CVAPI(void) cvCalcArrBackProject( CvArr** image, CvArr* dst, const CvHistogram* hist ); #define cvCalcBackProject(image, dst, hist) cvCalcArrBackProject((CvArr**)image, dst, hist) /* Does some sort of template matching but compares histograms of template and each window location */ CVAPI(void) cvCalcArrBackProjectPatch( CvArr** image, CvArr* dst, CvSize range, CvHistogram* hist, int method, double factor ); #define cvCalcBackProjectPatch( image, dst, range, hist, method, factor ) \ cvCalcArrBackProjectPatch( (CvArr**)image, dst, range, hist, method, factor ) /* calculates probabilistic density (divides one histogram by another) */ CVAPI(void) cvCalcProbDensity( const CvHistogram* hist1, const CvHistogram* hist2, CvHistogram* dst_hist, double scale CV_DEFAULT(255) ); /* equalizes histogram of 8-bit single-channel image */ CVAPI(void) cvEqualizeHist( const CvArr* src, CvArr* dst ); #define CV_VALUE 1 #define CV_ARRAY 2 /* Updates active contour in order to minimize its cummulative (internal and external) energy. */ CVAPI(void) cvSnakeImage( const IplImage* image, CvPoint* points, int length, float* alpha, float* beta, float* gamma, int coeff_usage, CvSize win, CvTermCriteria criteria, int calc_gradient CV_DEFAULT(1)); /* Calculates the cooficients of the homography matrix */ CVAPI(void) cvCalcImageHomography( float* line, CvPoint3D32f* center, float* intrinsic, float* homography ); #define CV_DIST_MASK_3 3 #define CV_DIST_MASK_5 5 #define CV_DIST_MASK_PRECISE 0 /* Applies distance transform to binary image */ CVAPI(void) cvDistTransform( const CvArr* src, CvArr* dst, int distance_type CV_DEFAULT(CV_DIST_L2), int mask_size CV_DEFAULT(3), const float* mask CV_DEFAULT(NULL), CvArr* labels CV_DEFAULT(NULL)); /* Types of thresholding */ #define CV_THRESH_BINARY 0 /* value = value > threshold ? max_value : 0 */ #define CV_THRESH_BINARY_INV 1 /* value = value > threshold ? 0 : max_value */ #define CV_THRESH_TRUNC 2 /* value = value > threshold ? threshold : value */ #define CV_THRESH_TOZERO 3 /* value = value > threshold ? value : 0 */ #define CV_THRESH_TOZERO_INV 4 /* value = value > threshold ? 0 : value */ #define CV_THRESH_MASK 7 #define CV_THRESH_OTSU 8 /* use Otsu algorithm to choose the optimal threshold value; combine the flag with one of the above CV_THRESH_* values */ /* Applies fixed-level threshold to grayscale image. This is a basic operation applied before retrieving contours */ CVAPI(double) cvThreshold( const CvArr* src, CvArr* dst, double threshold, double max_value, int threshold_type ); #define CV_ADAPTIVE_THRESH_MEAN_C 0 #define CV_ADAPTIVE_THRESH_GAUSSIAN_C 1 /* Applies adaptive threshold to grayscale image. The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and CV_ADAPTIVE_THRESH_GAUSSIAN_C are: neighborhood size (3, 5, 7 etc.), and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...) */ CVAPI(void) cvAdaptiveThreshold( const CvArr* src, CvArr* dst, double max_value, int adaptive_method CV_DEFAULT(CV_ADAPTIVE_THRESH_MEAN_C), int threshold_type CV_DEFAULT(CV_THRESH_BINARY), int block_size CV_DEFAULT(3), double param1 CV_DEFAULT(5)); #define CV_FLOODFILL_FIXED_RANGE (1 << 16) #define CV_FLOODFILL_MASK_ONLY (1 << 17) /* Fills the connected component until the color difference gets large enough */ CVAPI(void) cvFloodFill( CvArr* image, CvPoint seed_point, CvScalar new_val, CvScalar lo_diff CV_DEFAULT(cvScalarAll(0)), CvScalar up_diff CV_DEFAULT(cvScalarAll(0)), CvConnectedComp* comp CV_DEFAULT(NULL), int flags CV_DEFAULT(4), CvArr* mask CV_DEFAULT(NULL)); /****************************************************************************************\ * Feature detection * \****************************************************************************************/ #define CV_CANNY_L2_GRADIENT (1 << 31) /* Runs canny edge detector */ CVAPI(void) cvCanny( const CvArr* image, CvArr* edges, double threshold1, double threshold2, int aperture_size CV_DEFAULT(3) ); /* Calculates constraint image for corner detection Dx^2 * Dyy + Dxx * Dy^2 - 2 * Dx * Dy * Dxy. Applying threshold to the result gives coordinates of corners */ CVAPI(void) cvPreCornerDetect( const CvArr* image, CvArr* corners, int aperture_size CV_DEFAULT(3) ); /* Calculates eigen values and vectors of 2x2 gradient covariation matrix at every image pixel */ CVAPI(void) cvCornerEigenValsAndVecs( const CvArr* image, CvArr* eigenvv, int block_size, int aperture_size CV_DEFAULT(3) ); /* Calculates minimal eigenvalue for 2x2 gradient covariation matrix at every image pixel */ CVAPI(void) cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval, int block_size, int aperture_size CV_DEFAULT(3) ); /* Harris corner detector: Calculates det(M) - k*(trace(M)^2), where M is 2x2 gradient covariation matrix for each pixel */ CVAPI(void) cvCornerHarris( const CvArr* image, CvArr* harris_responce, int block_size, int aperture_size CV_DEFAULT(3), double k CV_DEFAULT(0.04) ); /* Adjust corner position using some sort of gradient search */ CVAPI(void) cvFindCornerSubPix( const CvArr* image, CvPoint2D32f* corners, int count, CvSize win, CvSize zero_zone, CvTermCriteria criteria ); /* Finds a sparse set of points within the selected region that seem to be easy to track */ CVAPI(void) cvGoodFeaturesToTrack( const CvArr* image, CvArr* eig_image, CvArr* temp_image, CvPoint2D32f* corners, int* corner_count, double quality_level, double min_distance, const CvArr* mask CV_DEFAULT(NULL), int block_size CV_DEFAULT(3), int use_harris CV_DEFAULT(0), double k CV_DEFAULT(0.04) ); #define CV_HOUGH_STANDARD 0 #define CV_HOUGH_PROBABILISTIC 1 #define CV_HOUGH_MULTI_SCALE 2 #define CV_HOUGH_GRADIENT 3 /* Finds lines on binary image using one of several methods. line_storage is either memory storage or 1 x CvMat, its number of columns is changed by the function. method is one of CV_HOUGH_*; rho, theta and threshold are used for each of those methods; param1 ~ line length, param2 ~ line gap - for probabilistic, param1 ~ srn, param2 ~ stn - for multi-scale */ CVAPI(CvSeq*) cvHoughLines2( CvArr* image, void* line_storage, int method, double rho, double theta, int threshold, double param1 CV_DEFAULT(0), double param2 CV_DEFAULT(0)); /* Finds circles in the image */ CVAPI(CvSeq*) cvHoughCircles( CvArr* image, void* circle_storage, int method, double dp, double min_dist, double param1 CV_DEFAULT(100), double param2 CV_DEFAULT(100), int min_radius CV_DEFAULT(0), int max_radius CV_DEFAULT(0)); /* Fits a line into set of 2d or 3d points in a robust way (M-estimator technique) */ CVAPI(void) cvFitLine( const CvArr* points, int dist_type, double param, double reps, double aeps, float* line ); struct CvFeatureTree; /* Constructs kd-tree from set of feature descriptors */ CVAPI(struct CvFeatureTree*) cvCreateKDTree(CvMat* desc); /* Constructs spill-tree from set of feature descriptors */ CVAPI(struct CvFeatureTree*) cvCreateSpillTree( const CvMat* raw_data, const int naive CV_DEFAULT(50), const double rho CV_DEFAULT(.7), const double tau CV_DEFAULT(.1) ); /* Release feature tree */ CVAPI(void) cvReleaseFeatureTree(struct CvFeatureTree* tr); /* Searches feature tree for k nearest neighbors of given reference points, searching (in case of kd-tree/bbf) at most emax leaves. */ CVAPI(void) cvFindFeatures(struct CvFeatureTree* tr, const CvMat* query_points, CvMat* indices, CvMat* dist, int k, int emax CV_DEFAULT(20)); /* Search feature tree for all points that are inlier to given rect region. Only implemented for kd trees */ CVAPI(int) cvFindFeaturesBoxed(struct CvFeatureTree* tr, CvMat* bounds_min, CvMat* bounds_max, CvMat* out_indices); struct CvLSH; struct CvLSHOperations; /* Construct a Locality Sensitive Hash (LSH) table, for indexing d-dimensional vectors of given type. Vectors will be hashed L times with k-dimensional p-stable (p=2) functions. */ CVAPI(struct CvLSH*) cvCreateLSH(struct CvLSHOperations* ops, int d, int L CV_DEFAULT(10), int k CV_DEFAULT(10), int type CV_DEFAULT(CV_64FC1), double r CV_DEFAULT(4), int64 seed CV_DEFAULT(-1)); /* Construct in-memory LSH table, with n bins. */ CVAPI(struct CvLSH*) cvCreateMemoryLSH(int d, int n, int L CV_DEFAULT(10), int k CV_DEFAULT(10), int type CV_DEFAULT(CV_64FC1), double r CV_DEFAULT(4), int64 seed CV_DEFAULT(-1)); /* Free the given LSH structure. */ CVAPI(void) cvReleaseLSH(struct CvLSH** lsh); /* Return the number of vectors in the LSH. */ CVAPI(unsigned int) LSHSize(struct CvLSH* lsh); /* Add vectors to the LSH structure, optionally returning indices. */ CVAPI(void) cvLSHAdd(struct CvLSH* lsh, const CvMat* data, CvMat* indices CV_DEFAULT(0)); /* Remove vectors from LSH, as addressed by given indices. */ CVAPI(void) cvLSHRemove(struct CvLSH* lsh, const CvMat* indices); /* Query the LSH n times for at most k nearest points; data is n x d, indices and dist are n x k. At most emax stored points will be accessed. */ CVAPI(void) cvLSHQuery(struct CvLSH* lsh, const CvMat* query_points, CvMat* indices, CvMat* dist, int k, int emax); typedef struct CvSURFPoint { CvPoint2D32f pt; int laplacian; int size; float dir; float hessian; } CvSURFPoint; CV_INLINE CvSURFPoint cvSURFPoint( CvPoint2D32f pt, int laplacian, int size, float dir CV_DEFAULT(0), float hessian CV_DEFAULT(0)) { CvSURFPoint kp; kp.pt = pt; kp.laplacian = laplacian; kp.size = size; kp.dir = dir; kp.hessian = hessian; return kp; } typedef struct CvSURFParams { int extended; double hessianThreshold; int nOctaves; int nOctaveLayers; } CvSURFParams; CVAPI(CvSURFParams) cvSURFParams( double hessianThreshold, int extended CV_DEFAULT(0) ); // If useProvidedKeyPts!=0, keypoints are not detected, but descriptors are computed // at the locations provided in keypoints (a CvSeq of CvSURFPoint). CVAPI(void) cvExtractSURF( const CvArr* img, const CvArr* mask, CvSeq** keypoints, CvSeq** descriptors, CvMemStorage* storage, CvSURFParams params, int useProvidedKeyPts CV_DEFAULT(0) ); typedef struct CvMSERParams { // delta, in the code, it compares (size_{i}-size_{i-delta})/size_{i-delta} int delta; // prune the area which bigger/smaller than max_area/min_area int maxArea; int minArea; // prune the area have simliar size to its children float maxVariation; // trace back to cut off mser with diversity < min_diversity float minDiversity; /* the next few params for MSER of color image */ // for color image, the evolution steps int maxEvolution; // the area threshold to cause re-initialize double areaThreshold; // ignore too small margin double minMargin; // the aperture size for edge blur int edgeBlurSize; } CvMSERParams; CVAPI(CvMSERParams) cvMSERParams( int delta CV_DEFAULT(5), int min_area CV_DEFAULT(60), int max_area CV_DEFAULT(14400), float max_variation CV_DEFAULT(.25f), float min_diversity CV_DEFAULT(.2f), int max_evolution CV_DEFAULT(200), double area_threshold CV_DEFAULT(1.01), double min_margin CV_DEFAULT(.003), int edge_blur_size CV_DEFAULT(5) ); // Extracts the contours of Maximally Stable Extremal Regions CVAPI(void) cvExtractMSER( CvArr* _img, CvArr* _mask, CvSeq** contours, CvMemStorage* storage, CvMSERParams params ); typedef struct CvStarKeypoint { CvPoint pt; int size; float response; } CvStarKeypoint; CV_INLINE CvStarKeypoint cvStarKeypoint(CvPoint pt, int size, float response) { CvStarKeypoint kpt; kpt.pt = pt; kpt.size = size; kpt.response = response; return kpt; } typedef struct CvStarDetectorParams { int maxSize; int responseThreshold; int lineThresholdProjected; int lineThresholdBinarized; int suppressNonmaxSize; } CvStarDetectorParams; CV_INLINE CvStarDetectorParams cvStarDetectorParams( int maxSize CV_DEFAULT(45), int responseThreshold CV_DEFAULT(30), int lineThresholdProjected CV_DEFAULT(10), int lineThresholdBinarized CV_DEFAULT(8), int suppressNonmaxSize CV_DEFAULT(5)) { CvStarDetectorParams params; params.maxSize = maxSize; params.responseThreshold = responseThreshold; params.lineThresholdProjected = lineThresholdProjected; params.lineThresholdBinarized = lineThresholdBinarized; params.suppressNonmaxSize = suppressNonmaxSize; return params; } CVAPI(CvSeq*) cvGetStarKeypoints( const CvArr* img, CvMemStorage* storage, CvStarDetectorParams params CV_DEFAULT(cvStarDetectorParams())); /****************************************************************************************\ * Haar-like Object Detection functions * \****************************************************************************************/ /* Loads haar classifier cascade from a directory. It is obsolete: convert your cascade to xml and use cvLoad instead */ CVAPI(CvHaarClassifierCascade*) cvLoadHaarClassifierCascade( const char* directory, CvSize orig_window_size); +/ //C CVAPI(void) cvReleaseHaarClassifierCascade( CvHaarClassifierCascade** cascade ); void cvReleaseHaarClassifierCascade( CvHaarClassifierCascade** cascade ); /+ #define CV_HAAR_DO_CANNY_PRUNING 1 #define CV_HAAR_SCALE_IMAGE 2 #define CV_HAAR_FIND_BIGGEST_OBJECT 4 #define CV_HAAR_DO_ROUGH_SEARCH 8 +/ //C CVAPI(CvSeq*) cvHaarDetectObjects( const CvArr* image, //C CvHaarClassifierCascade* cascade, //C CvMemStorage* storage, double scale_factor CV_DEFAULT(1.1), //C int min_neighbors CV_DEFAULT(3), int flags CV_DEFAULT(0), //C CvSize min_size CV_DEFAULT(cvSize(0,0))); CvSeq* cvHaarDetectObjects( const(CvArr)* image, CvHaarClassifierCascade* cascade, CvMemStorage* storage, double scale_factor = 1.1, int min_neighbors = 3, int flags = 0, CvSize min_size = cvSize(0,0)); /+ /* sets images for haar classifier cascade */ CVAPI(void) cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* cascade, const CvArr* sum, const CvArr* sqsum, const CvArr* tilted_sum, double scale ); /* runs the cascade on the specified window */ CVAPI(int) cvRunHaarClassifierCascade( const CvHaarClassifierCascade* cascade, CvPoint pt, int start_stage CV_DEFAULT(0)); /****************************************************************************************\ * Camera Calibration, Pose Estimation and Stereo * \****************************************************************************************/ /* Transforms the input image to compensate lens distortion */ CVAPI(void) cvUndistort2( const CvArr* src, CvArr* dst, const CvMat* camera_matrix, const CvMat* distortion_coeffs ); /* Computes transformation map from intrinsic camera parameters that can used by cvRemap */ CVAPI(void) cvInitUndistortMap( const CvMat* camera_matrix, const CvMat* distortion_coeffs, CvArr* mapx, CvArr* mapy ); /* Computes undistortion+rectification map for a head of stereo camera */ CVAPI(void) cvInitUndistortRectifyMap( const CvMat* camera_matrix, const CvMat* dist_coeffs, const CvMat *R, const CvMat* new_camera_matrix, CvArr* mapx, CvArr* mapy ); /* Computes the original (undistorted) feature coordinates from the observed (distorted) coordinates */ CVAPI(void) cvUndistortPoints( const CvMat* src, CvMat* dst, const CvMat* camera_matrix, const CvMat* dist_coeffs, const CvMat* R CV_DEFAULT(0), const CvMat* P 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) ); #define CV_LMEDS 4 #define CV_RANSAC 8 /* 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(0), 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 /* 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 /* Finds intrinsic and extrinsic camera parameters from a few views of known calibration pattern */ CVAPI(void) 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) ); /* 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(void) 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) ); /* 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)); 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, CvMatr32f rotation_matrix, CvVect32f 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_FM_LMEDS_ONLY CV_LMEDS #define CV_FM_RANSAC_ONLY CV_RANSAC #define CV_FM_LMEDS CV_LMEDS #define CV_FM_RANSAC CV_RANSAC 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); /* stereo correspondence parameters and functions */ #define CV_STEREO_BM_NORMALIZED_RESPONSE 0 /* 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 // temporary buffers CvMat* preFilteredImg0; CvMat* preFilteredImg1; CvMat* slidingSumBuf; CvMat* dbmin; CvMat* dbmax; } 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 ); /* Kolmogorov-Zabin stereo-correspondence algorithm (a.k.a. KZ1) */ #define CV_STEREO_GC_OCCLUDED SHRT_MAX typedef struct CvStereoGCState { int Ithreshold; int interactionRadius; float K, lambda, lambda1, lambda2; int occlusionCost; int minDisparity; int numberOfDisparities; int maxIters; CvMat* left; CvMat* right; CvMat* dispLeft; CvMat* dispRight; CvMat* ptrLeft; CvMat* ptrRight; CvMat* vtxBuf; CvMat* edgeBuf; } CvStereoGCState; CVAPI(CvStereoGCState*) cvCreateStereoGCState( int numberOfDisparities, int maxIters ); CVAPI(void) cvReleaseStereoGCState( CvStereoGCState** state ); CVAPI(void) cvFindStereoCorrespondenceGC( const CvArr* left, const CvArr* right, CvArr* disparityLeft, CvArr* disparityRight, CvStereoGCState* state, int useDisparityGuess CV_DEFAULT(0) ); /* 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) ); //C #ifdef __cplusplus //C } //C #endif } #ifdef __cplusplus #ifndef SKIP_INCLUDES // for now only expose old interface to swig #include "cv.hpp" #endif // SKIP_INCLUDES #endif /****************************************************************************************\ * Backward compatibility * \****************************************************************************************/ #ifndef CV_NO_BACKWARD_COMPATIBILITY #include "cvcompat.h" #endif #endif /*_CV_H_*/ +/ }