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Merge pull request #22754 from mshabunin:c-cleanup

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C-API cleanup for OpenCV 5.x (imgproc, highgui)

* imgproc: C-API cleanup

* imgproc: increase cvtColor test diff threshold

* imgproc: C-API cleanup pt.2

* imgproc: C-API cleanup pt.3

* imgproc: C-API cleanup pt.4

* imgproc: C-API cleanup pt.5

* imgproc: C-API cleanup pt.5

* imgproc: C-API cleanup pt.6

* highgui: C-API cleanup

* highgui: C-API cleanup pt.2

* highgui: C-API cleanup pt.3

* highgui: C-API cleanup pt.3

* imgproc: C-API cleanup pt.7

* fixup! highgui: C-API cleanup pt.3

* fixup! imgproc: C-API cleanup pt.6

* imgproc: C-API cleanup pt.8

* imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9

* fixup! imgproc: C-API cleanup pt.9
This commit is contained in:
Maksim Shabunin
2022-12-14 21:57:08 +03:00
committed by GitHub
parent d49958141e
commit 8a62b03761
87 changed files with 1374 additions and 12887 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/imgproc/include/opencv2/imgproc.hpp
+6 -3
View File
@@ -190,7 +190,6 @@ location of points on the plane, building special graphs (such as NNG,RNG), and
@defgroup imgproc_feature Feature Detection
@defgroup imgproc_object Object Detection
@defgroup imgproc_segmentation Image Segmentation
@defgroup imgproc_c C API
@defgroup imgproc_hal Hardware Acceleration Layer
@{
@defgroup imgproc_hal_functions Functions
@@ -437,6 +436,8 @@ enum RetrievalModes {
//! the contour approximation algorithm
enum ContourApproximationModes {
/** TBD */
CHAIN_CODE = 0,
/** stores absolutely all the contour points. That is, any 2 subsequent points (x1,y1) and
(x2,y2) of the contour will be either horizontal, vertical or diagonal neighbors, that is,
max(abs(x1-x2),abs(y2-y1))==1. */
@@ -447,7 +448,9 @@ enum ContourApproximationModes {
/** applies one of the flavors of the Teh-Chin chain approximation algorithm @cite TehChin89 */
CHAIN_APPROX_TC89_L1 = 3,
/** applies one of the flavors of the Teh-Chin chain approximation algorithm @cite TehChin89 */
CHAIN_APPROX_TC89_KCOS = 4
CHAIN_APPROX_TC89_KCOS = 4,
/** TBD */
LINK_RUNS = 5
};
/** @brief Shape matching methods
@@ -722,7 +725,7 @@ enum ColorConversionCodes {
COLOR_YUV2GRAY_UYVY = 123,
COLOR_YUV2GRAY_YUY2 = 124,
//CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY,
//COLOR_YUV2GRAY_VYUY = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
modules/imgproc/include/opencv2/imgproc/imgproc_c.h
-861
View File
@@ -45,865 +45,4 @@
#include "opencv2/imgproc/types_c.h"
#ifdef __cplusplus
extern "C" {
#endif
/** @addtogroup imgproc_c
@{
*/
/*********************** Background statistics accumulation *****************************/
/** @brief Adds image to accumulator
@see cv::accumulate
*/
CVAPI(void) cvAcc( const CvArr* image, CvArr* sum,
const CvArr* mask CV_DEFAULT(NULL) );
/** @brief Adds squared image to accumulator
@see cv::accumulateSquare
*/
CVAPI(void) cvSquareAcc( const CvArr* image, CvArr* sqsum,
const CvArr* mask CV_DEFAULT(NULL) );
/** @brief Adds a product of two images to accumulator
@see cv::accumulateProduct
*/
CVAPI(void) cvMultiplyAcc( const CvArr* image1, const CvArr* image2, CvArr* acc,
const CvArr* mask CV_DEFAULT(NULL) );
/** @brief Adds image to accumulator with weights: acc = acc*(1-alpha) + image*alpha
@see cv::accumulateWeighted
*/
CVAPI(void) cvRunningAvg( const CvArr* image, CvArr* acc, double alpha,
const CvArr* mask CV_DEFAULT(NULL) );
/****************************************************************************************\
* Image Processing *
\****************************************************************************************/
/** @brief Smooths the image in one of several ways.
@param src The source image
@param dst The destination image
@param smoothtype Type of the smoothing, see SmoothMethod_c
@param size1 The first parameter of the smoothing operation, the aperture width. Must be a
positive odd number (1, 3, 5, ...)
@param size2 The second parameter of the smoothing operation, the aperture height. Ignored by
CV_MEDIAN and CV_BILATERAL methods. In the case of simple scaled/non-scaled and Gaussian blur if
size2 is zero, it is set to size1. Otherwise it must be a positive odd number.
@param sigma1 In the case of a Gaussian parameter this parameter may specify Gaussian \f$\sigma\f$
(standard deviation). If it is zero, it is calculated from the kernel size:
\f[\sigma = 0.3 (n/2 - 1) + 0.8 \quad \text{where} \quad n= \begin{array}{l l} \mbox{\texttt{size1} for horizontal kernel} \\ \mbox{\texttt{size2} for vertical kernel} \end{array}\f]
Using standard sigma for small kernels ( \f$3\times 3\f$ to \f$7\times 7\f$ ) gives better speed. If
sigma1 is not zero, while size1 and size2 are zeros, the kernel size is calculated from the
sigma (to provide accurate enough operation).
@param sigma2 additional parameter for bilateral filtering
@see cv::GaussianBlur, cv::blur, cv::medianBlur, cv::bilateralFilter.
*/
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));
/** @brief Convolves an image with the kernel.
@param src input image.
@param dst output image of the same size and the same number of channels as src.
@param kernel convolution kernel (or rather a correlation kernel), a single-channel floating point
matrix; if you want to apply different kernels to different channels, split the image into
separate color planes using split and process them individually.
@param anchor anchor of the kernel that indicates the relative position of a filtered point within
the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor
is at the kernel center.
@see cv::filter2D
*/
CVAPI(void) cvFilter2D( const CvArr* src, CvArr* dst, const CvMat* kernel,
CvPoint anchor CV_DEFAULT(cvPoint(-1,-1)));
/** @brief Finds integral image: SUM(X,Y) = sum(x<X,y<Y)I(x,y)
@see cv::integral
*/
CVAPI(void) cvIntegral( const CvArr* image, CvArr* sum,
CvArr* sqsum CV_DEFAULT(NULL),
CvArr* tilted_sum CV_DEFAULT(NULL));
/** @brief Smoothes the input image with gaussian kernel and then down-samples it.
dst_width = floor(src_width/2)[+1],
dst_height = floor(src_height/2)[+1]
@see cv::pyrDown
*/
CVAPI(void) cvPyrDown( const CvArr* src, CvArr* dst,
int filter CV_DEFAULT(CV_GAUSSIAN_5x5) );
/** @brief Up-samples image and smoothes the result with gaussian kernel.
dst_width = src_width*2,
dst_height = src_height*2
@see cv::pyrUp
*/
CVAPI(void) cvPyrUp( const CvArr* src, CvArr* dst,
int filter CV_DEFAULT(CV_GAUSSIAN_5x5) );
/** @brief Converts input array pixels from one color space to another
@see cv::cvtColor
*/
CVAPI(void) cvCvtColor( const CvArr* src, CvArr* dst, int code );
/** @brief Resizes image (input array is resized to fit the destination array)
@see cv::resize
*/
CVAPI(void) cvResize( const CvArr* src, CvArr* dst,
int interpolation CV_DEFAULT( CV_INTER_LINEAR ));
/** @brief Warps image with affine transform
@note ::cvGetQuadrangleSubPix is similar to ::cvWarpAffine, but the outliers are extrapolated using
replication border mode.
@see cv::warpAffine
*/
CVAPI(void) cvWarpAffine( const CvArr* src, CvArr* dst, const CvMat* map_matrix,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) );
/** @brief Computes rotation_matrix matrix
@see cv::getRotationMatrix2D
*/
CVAPI(CvMat*) cv2DRotationMatrix( CvPoint2D32f center, double angle,
double scale, CvMat* map_matrix );
/** @brief Warps image with perspective (projective) transform
@see cv::warpPerspective
*/
CVAPI(void) cvWarpPerspective( const CvArr* src, CvArr* dst, const CvMat* map_matrix,
int flags CV_DEFAULT(CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS),
CvScalar fillval CV_DEFAULT(cvScalarAll(0)) );
/** @brief Computes perspective transform matrix for mapping src[i] to dst[i] (i=0,1,2,3)
@see cv::getPerspectiveTransform
*/
CVAPI(CvMat*) cvGetPerspectiveTransform( const CvPoint2D32f* src,
const CvPoint2D32f* dst,
CvMat* map_matrix );
/** @brief Returns a structuring element of the specified size and shape for morphological operations.
@note the created structuring element IplConvKernel\* element must be released in the end using
`cvReleaseStructuringElement(&element)`.
@param cols Width of the structuring element
@param rows Height of the structuring element
@param anchor_x x-coordinate of the anchor
@param anchor_y y-coordinate of the anchor
@param shape element shape that could be one of the cv::MorphShapes_c
@param values integer array of cols*rows elements that specifies the custom shape of the
structuring element, when shape=CV_SHAPE_CUSTOM.
@see cv::getStructuringElement
*/
CVAPI(IplConvKernel*) cvCreateStructuringElementEx(
int cols, int rows, int anchor_x, int anchor_y,
int shape, int* values CV_DEFAULT(NULL) );
/** @brief releases structuring element
@see cvCreateStructuringElementEx
*/
CVAPI(void) cvReleaseStructuringElement( IplConvKernel** element );
/** @brief erodes input image (applies minimum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used
@see cv::erode
*/
CVAPI(void) cvErode( const CvArr* src, CvArr* dst,
IplConvKernel* element CV_DEFAULT(NULL),
int iterations CV_DEFAULT(1) );
/** @brief dilates input image (applies maximum filter) one or more times.
If element pointer is NULL, 3x3 rectangular element is used
@see cv::dilate
*/
CVAPI(void) cvDilate( const CvArr* src, CvArr* dst,
IplConvKernel* element CV_DEFAULT(NULL),
int iterations CV_DEFAULT(1) );
/** @brief Performs complex morphological transformation
@see cv::morphologyEx
*/
CVAPI(void) cvMorphologyEx( const CvArr* src, CvArr* dst,
CvArr* temp, IplConvKernel* element,
int operation, int iterations CV_DEFAULT(1) );
/** @brief Calculates all spatial and central moments up to the 3rd order
@see cv::moments
*/
CVAPI(void) cvMoments( const CvArr* arr, CvMoments* moments, int binary CV_DEFAULT(0));
/** @brief Retrieve spatial moments */
CVAPI(double) cvGetSpatialMoment( CvMoments* moments, int x_order, int y_order );
/** @brief Retrieve central moments */
CVAPI(double) cvGetCentralMoment( CvMoments* moments, int x_order, int y_order );
/** @brief Retrieve normalized central moments */
CVAPI(double) cvGetNormalizedCentralMoment( CvMoments* moments,
int x_order, int y_order );
/** @brief Calculates 7 Hu's invariants from precalculated spatial and central moments
@see cv::HuMoments
*/
CVAPI(void) cvGetHuMoments( CvMoments* moments, CvHuMoments* hu_moments );
/*********************************** data sampling **************************************/
/** @brief Retrieves quadrangle from the input array.
matrixarr = ( a11 a12 | b1 ) dst(x,y) <- src(A[x y]' + b)
( a21 a22 | b2 ) (bilinear interpolation is used to retrieve pixels
with fractional coordinates)
@see cvWarpAffine
*/
CVAPI(void) cvGetQuadrangleSubPix( const CvArr* src, CvArr* dst,
const CvMat* map_matrix );
/** @brief Computes earth mover distance between
two weighted point sets (called signatures)
@see cv::EMD
*/
CVAPI(float) cvCalcEMD2( const CvArr* signature1,
const CvArr* signature2,
int distance_type,
CvDistanceFunction distance_func CV_DEFAULT(NULL),
const CvArr* cost_matrix CV_DEFAULT(NULL),
CvArr* flow CV_DEFAULT(NULL),
float* lower_bound CV_DEFAULT(NULL),
void* userdata CV_DEFAULT(NULL));
/****************************************************************************************\
* Contours retrieving *
\****************************************************************************************/
/** @brief Retrieves outer and optionally inner boundaries of white (non-zero) connected
components in the black (zero) background
@see cv::findContours, cvStartFindContours, cvFindNextContour, cvSubstituteContour, cvEndFindContours
*/
CVAPI(int) cvFindContours( CvArr* image, CvMemStorage* storage, CvSeq** first_contour,
int header_size CV_DEFAULT(sizeof(CvContour)),
int mode CV_DEFAULT(CV_RETR_LIST),
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0)));
/** @brief Initializes contour retrieving process.
Calls cvStartFindContours.
Calls cvFindNextContour until null pointer is returned
or some other condition becomes true.
Calls cvEndFindContours at the end.
@see cvFindContours
*/
CVAPI(CvContourScanner) cvStartFindContours( CvArr* image, CvMemStorage* storage,
int header_size CV_DEFAULT(sizeof(CvContour)),
int mode CV_DEFAULT(CV_RETR_LIST),
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
CvPoint offset CV_DEFAULT(cvPoint(0,0)));
/** @brief Retrieves next contour
@see cvFindContours
*/
CVAPI(CvSeq*) cvFindNextContour( CvContourScanner scanner );
/** @brief Substitutes the last retrieved contour with the new one
(if the substitutor is null, the last retrieved contour is removed from the tree)
@see cvFindContours
*/
CVAPI(void) cvSubstituteContour( CvContourScanner scanner, CvSeq* new_contour );
/** @brief Releases contour scanner and returns pointer to the first outer contour
@see cvFindContours
*/
CVAPI(CvSeq*) cvEndFindContours( CvContourScanner* scanner );
/** @brief Approximates Freeman chain(s) with a polygonal curve.
This is a standalone contour approximation routine, not represented in the new interface. When
cvFindContours retrieves contours as Freeman chains, it calls the function to get approximated
contours, represented as polygons.
@param src_seq Pointer to the approximated Freeman chain that can refer to other chains.
@param storage Storage location for the resulting polylines.
@param method Approximation method (see the description of the function :ocvFindContours ).
@param parameter Method parameter (not used now).
@param minimal_perimeter Approximates only those contours whose perimeters are not less than
minimal_perimeter . Other chains are removed from the resulting structure.
@param recursive Recursion flag. If it is non-zero, the function approximates all chains that can
be obtained from chain by using the h_next or v_next links. Otherwise, the single input chain is
approximated.
@see cvStartReadChainPoints, cvReadChainPoint
*/
CVAPI(CvSeq*) cvApproxChains( CvSeq* src_seq, CvMemStorage* storage,
int method CV_DEFAULT(CV_CHAIN_APPROX_SIMPLE),
double parameter CV_DEFAULT(0),
int minimal_perimeter CV_DEFAULT(0),
int recursive CV_DEFAULT(0));
/** @brief Initializes Freeman chain reader.
The reader is used to iteratively get coordinates of all the chain points.
If the Freeman codes should be read as is, a simple sequence reader should be used
@see cvApproxChains
*/
CVAPI(void) cvStartReadChainPoints( CvChain* chain, CvChainPtReader* reader );
/** @brief Retrieves the next chain point
@see cvApproxChains
*/
CVAPI(CvPoint) cvReadChainPoint( CvChainPtReader* reader );
/****************************************************************************************\
* Contour Processing and Shape Analysis *
\****************************************************************************************/
/** @brief Approximates a single polygonal curve (contour) or
a tree of polygonal curves (contours)
@see cv::approxPolyDP
*/
CVAPI(CvSeq*) cvApproxPoly( const void* src_seq,
int header_size, CvMemStorage* storage,
int method, double eps,
int recursive CV_DEFAULT(0));
/** @brief Calculates perimeter of a contour or length of a part of contour
@see cv::arcLength
*/
CVAPI(double) cvArcLength( const void* curve,
CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
int is_closed CV_DEFAULT(-1));
/** same as cvArcLength for closed contour
*/
CV_INLINE double cvContourPerimeter( const void* contour )
{
return cvArcLength( contour, CV_WHOLE_SEQ, 1 );
}
/** @brief Calculates contour bounding rectangle (update=1) or
just retrieves pre-calculated rectangle (update=0)
@see cv::boundingRect
*/
CVAPI(CvRect) cvBoundingRect( CvArr* points, int update CV_DEFAULT(0) );
/** @brief Calculates area of a contour or contour segment
@see cv::contourArea
*/
CVAPI(double) cvContourArea( const CvArr* contour,
CvSlice slice CV_DEFAULT(CV_WHOLE_SEQ),
int oriented CV_DEFAULT(0));
/** @brief Calculates exact convex hull of 2d point set
@see cv::convexHull
*/
CVAPI(CvSeq*) cvConvexHull2( const CvArr* input,
void* hull_storage CV_DEFAULT(NULL),
int orientation CV_DEFAULT(CV_CLOCKWISE),
int return_points CV_DEFAULT(0));
/** @brief Checks whether the contour is convex or not (returns 1 if convex, 0 if not)
@see cv::isContourConvex
*/
CVAPI(int) cvCheckContourConvexity( const CvArr* contour );
/** @brief 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 );
/****************************************************************************************\
* Histogram functions *
\****************************************************************************************/
/** @brief Creates a histogram.
The function creates a histogram of the specified size and returns a pointer to the created
histogram. If the array ranges is 0, the histogram bin ranges must be specified later via the
function cvSetHistBinRanges. Though cvCalcHist and cvCalcBackProject may process 8-bit images
without setting bin ranges, they assume they are equally spaced in 0 to 255 bins.
@param dims Number of histogram dimensions.
@param sizes Array of the histogram dimension sizes.
@param type Histogram representation format. CV_HIST_ARRAY means that the histogram data is
represented as a multi-dimensional dense array CvMatND. CV_HIST_SPARSE means that histogram data
is represented as a multi-dimensional sparse array CvSparseMat.
@param ranges Array of ranges for the histogram bins. Its meaning depends on the uniform parameter
value. The ranges are used when the histogram is calculated or backprojected to determine which
histogram bin corresponds to which value/tuple of values from the input image(s).
@param uniform Uniformity flag. If not zero, the histogram has evenly spaced bins and for every
\f$0<=i<cDims\f$ ranges[i] is an array of two numbers: lower and upper boundaries for the i-th
histogram dimension. The whole range [lower,upper] is then split into dims[i] equal parts to
determine the i-th input tuple value ranges for every histogram bin. And if uniform=0 , then the
i-th element of the ranges array contains dims[i]+1 elements: \f$\texttt{lower}_0,
\texttt{upper}_0, \texttt{lower}_1, \texttt{upper}_1 = \texttt{lower}_2,
...
\texttt{upper}_{dims[i]-1}\f$ where \f$\texttt{lower}_j\f$ and \f$\texttt{upper}_j\f$ are lower
and upper boundaries of the i-th input tuple value for the j-th bin, respectively. In either
case, the input values that are beyond the specified range for a histogram bin are not counted
by cvCalcHist and filled with 0 by cvCalcBackProject.
*/
CVAPI(CvHistogram*) cvCreateHist( int dims, int* sizes, int type,
float** ranges CV_DEFAULT(NULL),
int uniform CV_DEFAULT(1));
/** @brief Sets the bounds of the histogram bins.
This is a standalone function for setting bin ranges in the histogram. For a more detailed
description of the parameters ranges and uniform, see the :ocvCalcHist function that can initialize
the ranges as well. Ranges for the histogram bins must be set before the histogram is calculated or
the backproject of the histogram is calculated.
@param hist Histogram.
@param ranges Array of bin ranges arrays. See :ocvCreateHist for details.
@param uniform Uniformity flag. See :ocvCreateHist for details.
*/
CVAPI(void) cvSetHistBinRanges( CvHistogram* hist, float** ranges,
int uniform CV_DEFAULT(1));
/** @brief Makes a histogram out of an array.
The function initializes the histogram, whose header and bins are allocated by the user.
cvReleaseHist does not need to be called afterwards. Only dense histograms can be initialized this
way. The function returns hist.
@param dims Number of the histogram dimensions.
@param sizes Array of the histogram dimension sizes.
@param hist Histogram header initialized by the function.
@param data Array used to store histogram bins.
@param ranges Histogram bin ranges. See cvCreateHist for details.
@param uniform Uniformity flag. See cvCreateHist for details.
*/
CVAPI(CvHistogram*) cvMakeHistHeaderForArray(
int dims, int* sizes, CvHistogram* hist,
float* data, float** ranges CV_DEFAULT(NULL),
int uniform CV_DEFAULT(1));
/** @brief Releases the histogram.
The function releases the histogram (header and the data). The pointer to the histogram is cleared
by the function. If \*hist pointer is already NULL, the function does nothing.
@param hist Double pointer to the released histogram.
*/
CVAPI(void) cvReleaseHist( CvHistogram** hist );
/** @brief Clears the histogram.
The function sets all of the histogram bins to 0 in case of a dense histogram and removes all
histogram bins in case of a sparse array.
@param hist Histogram.
*/
CVAPI(void) cvClearHist( CvHistogram* hist );
/** @brief Finds the minimum and maximum histogram bins.
The function finds the minimum and maximum histogram bins and their positions. All of output
arguments are optional. Among several extremas with the same value the ones with the minimum index
(in the lexicographical order) are returned. In case of several maximums or minimums, the earliest
in the lexicographical order (extrema locations) is returned.
@param hist Histogram.
@param min_value Pointer to the minimum value of the histogram.
@param max_value Pointer to the maximum value of the histogram.
@param min_idx Pointer to the array of coordinates for the minimum.
@param max_idx Pointer to the array of coordinates for the maximum.
*/
CVAPI(void) cvGetMinMaxHistValue( const CvHistogram* hist,
float* min_value, float* max_value,
int* min_idx CV_DEFAULT(NULL),
int* max_idx CV_DEFAULT(NULL));
/** @brief Normalizes the histogram.
The function normalizes the histogram bins by scaling them so that the sum of the bins becomes equal
to factor.
@param hist Pointer to the histogram.
@param factor Normalization factor.
*/
CVAPI(void) cvNormalizeHist( CvHistogram* hist, double factor );
/** @brief Thresholds the histogram.
The function clears histogram bins that are below the specified threshold.
@param hist Pointer to the histogram.
@param threshold Threshold level.
*/
CVAPI(void) cvThreshHist( CvHistogram* hist, double threshold );
/** Compares two histogram */
CVAPI(double) cvCompareHist( const CvHistogram* hist1,
const CvHistogram* hist2,
int method);
/** @brief Copies a histogram.
The function makes a copy of the histogram. If the second histogram pointer \*dst is NULL, a new
histogram of the same size as src is created. Otherwise, both histograms must have equal types and
sizes. Then the function copies the bin values of the source histogram to the destination histogram
and sets the same bin value ranges as in src.
@param src Source histogram.
@param dst Pointer to the destination histogram.
*/
CVAPI(void) cvCopyHist( const CvHistogram* src, CvHistogram** dst );
/** @brief Calculates bayesian probabilistic histograms
(each or src and dst is an array of _number_ histograms */
CVAPI(void) cvCalcBayesianProb( CvHistogram** src, int number,
CvHistogram** dst);
/** @brief Calculates array histogram
@see cv::calcHist
*/
CVAPI(void) cvCalcArrHist( CvArr** arr, CvHistogram* hist,
int accumulate CV_DEFAULT(0),
const CvArr* mask CV_DEFAULT(NULL) );
/** @overload */
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 );
}
/** @brief Calculates back project
@see cvCalcBackProject, cv::calcBackProject
*/
CVAPI(void) cvCalcArrBackProject( CvArr** image, CvArr* dst,
const CvHistogram* hist );
#define cvCalcBackProject(image, dst, hist) cvCalcArrBackProject((CvArr**)image, dst, hist)
/** @brief Locates a template within an image by using a histogram comparison.
The function calculates the back projection by comparing histograms of the source image patches with
the given histogram. The function is similar to matchTemplate, but instead of comparing the raster
patch with all its possible positions within the search window, the function CalcBackProjectPatch
compares histograms. See the algorithm diagram below:
![image](pics/backprojectpatch.png)
@param image Source images (though, you may pass CvMat\*\* as well).
@param dst Destination image.
@param range
@param hist Histogram.
@param method Comparison method passed to cvCompareHist (see the function description).
@param factor Normalization factor for histograms that affects the normalization scale of the
destination image. Pass 1 if not sure.
@see cvCalcBackProjectPatch
*/
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 )
/** @brief equalizes histogram of 8-bit single-channel image
@see cv::equalizeHist
*/
CVAPI(void) cvEqualizeHist( const CvArr* src, CvArr* dst );
/** @brief Applies distance transform to binary image
@see cv::distanceTransform
*/
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),
int labelType CV_DEFAULT(CV_DIST_LABEL_CCOMP));
/** @brief Applies fixed-level threshold to grayscale image.
This is a basic operation applied before retrieving contours
@see cv::threshold
*/
CVAPI(double) cvThreshold( const CvArr* src, CvArr* dst,
double threshold, double max_value,
int threshold_type );
/** @brief Fills the connected component until the color difference gets large enough
@see cv::floodFill
*/
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 *
\****************************************************************************************/
/** @brief Calculates eigen values and vectors of 2x2
gradient covariation matrix at every image pixel
@see cv::cornerEigenValsAndVecs
*/
CVAPI(void) cvCornerEigenValsAndVecs( const CvArr* image, CvArr* eigenvv,
int block_size, int aperture_size CV_DEFAULT(3) );
/** @brief Calculates minimal eigenvalue for 2x2 gradient covariation matrix at
every image pixel
@see cv::cornerMinEigenVal
*/
CVAPI(void) cvCornerMinEigenVal( const CvArr* image, CvArr* eigenval,
int block_size, int aperture_size CV_DEFAULT(3) );
/** @brief Finds lines on binary image using one of several methods.
line_storage is either memory storage or 1 x _max number of lines_ 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
@see cv::HoughLines
*/
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),
double min_theta CV_DEFAULT(0), double max_theta CV_DEFAULT(CV_PI));
/** @brief Finds circles in the image
@see cv::HoughCircles
*/
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));
/****************************************************************************************\
* Drawing *
\****************************************************************************************/
/****************************************************************************************\
* Drawing functions work with images/matrices of arbitrary type. *
* For color images the channel order is BGR[A] *
* Antialiasing is supported only for 8-bit image now. *
* All the functions include parameter color that means rgb value (that may be *
* constructed with CV_RGB macro) for color images and brightness *
* for grayscale images. *
* If a drawn figure is partially or completely outside of the image, it is clipped.*
\****************************************************************************************/
#define CV_FILLED -1
#define CV_AA 16
/** @brief Draws 4-connected, 8-connected or antialiased line segment connecting two points
@see cv::line
*/
CVAPI(void) cvLine( CvArr* img, CvPoint pt1, CvPoint pt2,
CvScalar color, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) );
/** @brief Draws a rectangle given two opposite corners of the rectangle (pt1 & pt2)
if thickness<0 (e.g. thickness == CV_FILLED), the filled box is drawn
@see cv::rectangle
*/
CVAPI(void) cvRectangle( CvArr* img, CvPoint pt1, CvPoint pt2,
CvScalar color, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8),
int shift CV_DEFAULT(0));
/** @brief Draws a circle with specified center and radius.
Thickness works in the same way as with cvRectangle
@see cv::circle
*/
CVAPI(void) cvCircle( CvArr* img, CvPoint center, int radius,
CvScalar color, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0));
/** @brief Draws ellipse outline, filled ellipse, elliptic arc or filled elliptic sector
depending on _thickness_, _start_angle_ and _end_angle_ parameters. The resultant figure
is rotated by _angle_. All the angles are in degrees
@see cv::ellipse
*/
CVAPI(void) cvEllipse( CvArr* img, CvPoint center, CvSize axes,
double angle, double start_angle, double end_angle,
CvScalar color, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0));
/** @brief Fills an area bounded by one or more arbitrary polygons
@see cv::fillPoly
*/
CVAPI(void) cvFillPoly( CvArr* img, CvPoint** pts, const int* npts,
int contours, CvScalar color,
int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) );
/** @brief Draws one or more polygonal curves
@see cv::polylines
*/
CVAPI(void) cvPolyLine( CvArr* img, CvPoint** pts, const int* npts, int contours,
int is_closed, CvScalar color, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8), int shift CV_DEFAULT(0) );
/** @brief Initializes line iterator.
Initially, line_iterator->ptr will point to pt1 (or pt2, see left_to_right description) location in
the image. Returns the number of pixels on the line between the ending points.
@see cv::LineIterator
*/
CVAPI(int) cvInitLineIterator( const CvArr* image, CvPoint pt1, CvPoint pt2,
CvLineIterator* line_iterator,
int connectivity CV_DEFAULT(8),
int left_to_right CV_DEFAULT(0));
#define CV_NEXT_LINE_POINT( line_iterator ) \
{ \
int _line_iterator_mask = (line_iterator).err < 0 ? -1 : 0; \
(line_iterator).err += (line_iterator).minus_delta + \
((line_iterator).plus_delta & _line_iterator_mask); \
(line_iterator).ptr += (line_iterator).minus_step + \
((line_iterator).plus_step & _line_iterator_mask); \
}
#define CV_FONT_HERSHEY_SIMPLEX 0
#define CV_FONT_HERSHEY_PLAIN 1
#define CV_FONT_HERSHEY_DUPLEX 2
#define CV_FONT_HERSHEY_COMPLEX 3
#define CV_FONT_HERSHEY_TRIPLEX 4
#define CV_FONT_HERSHEY_COMPLEX_SMALL 5
#define CV_FONT_HERSHEY_SCRIPT_SIMPLEX 6
#define CV_FONT_HERSHEY_SCRIPT_COMPLEX 7
#define CV_FONT_ITALIC 16
#define CV_FONT_VECTOR0 CV_FONT_HERSHEY_SIMPLEX
/** Font structure */
typedef struct CvFont
{
const char* nameFont; //Qt:nameFont
CvScalar color; //Qt:ColorFont -> cvScalar(blue_component, green_component, red_component[, alpha_component])
int font_face; //Qt: bool italic /** =CV_FONT_* */
const int* ascii; //!< font data and metrics
const int* greek;
const int* cyrillic;
float hscale, vscale;
float shear; //!< slope coefficient: 0 - normal, >0 - italic
int thickness; //!< Qt: weight /** letters thickness */
float dx; //!< horizontal interval between letters
int line_type; //!< Qt: PointSize
}
CvFont;
/** @brief Initializes font structure (OpenCV 1.x API).
The function initializes the font structure that can be passed to text rendering functions.
@param font Pointer to the font structure initialized by the function
@param font_face Font name identifier. See cv::HersheyFonts and corresponding old CV_* identifiers.
@param hscale Horizontal scale. If equal to 1.0f , the characters have the original width
depending on the font type. If equal to 0.5f , the characters are of half the original width.
@param vscale Vertical scale. If equal to 1.0f , the characters have the original height depending
on the font type. If equal to 0.5f , the characters are of half the original height.
@param shear Approximate tangent of the character slope relative to the vertical line. A zero
value means a non-italic font, 1.0f means about a 45 degree slope, etc.
@param thickness Thickness of the text strokes
@param line_type Type of the strokes, see line description
@sa cvPutText
*/
CVAPI(void) cvInitFont( CvFont* font, int font_face,
double hscale, double vscale,
double shear CV_DEFAULT(0),
int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8));
CV_INLINE CvFont cvFont( double scale, int thickness CV_DEFAULT(1) )
{
CvFont font;
cvInitFont( &font, CV_FONT_HERSHEY_PLAIN, scale, scale, 0, thickness, CV_AA );
return font;
}
/** @brief Renders text stroke with specified font and color at specified location.
CvFont should be initialized with cvInitFont
@see cvInitFont, cvGetTextSize, cvFont, cv::putText
*/
CVAPI(void) cvPutText( CvArr* img, const char* text, CvPoint org,
const CvFont* font, CvScalar color );
/** @brief Unpacks color value
if arrtype is CV_8UC?, _color_ is treated as packed color value, otherwise the first channels
(depending on arrtype) of destination scalar are set to the same value = _color_
*/
CVAPI(CvScalar) cvColorToScalar( double packed_color, int arrtype );
/** @brief Returns the polygon points which make up the given ellipse.
The ellipse is define by the box of size 'axes' rotated 'angle' around the 'center'. A partial
sweep of the ellipse arc can be done by specifying arc_start and arc_end to be something other than
0 and 360, respectively. The input array 'pts' must be large enough to hold the result. The total
number of points stored into 'pts' is returned by this function.
@see cv::ellipse2Poly
*/
CVAPI(int) cvEllipse2Poly( CvPoint center, CvSize axes,
int angle, int arc_start, int arc_end, CvPoint * pts, int delta );
/** @brief Draws contour outlines or filled interiors on the image
@see cv::drawContours
*/
CVAPI(void) cvDrawContours( CvArr *img, CvSeq* contour,
CvScalar external_color, CvScalar hole_color,
int max_level, int thickness CV_DEFAULT(1),
int line_type CV_DEFAULT(8),
CvPoint offset CV_DEFAULT(cvPoint(0,0)));
/** @} */
#ifdef __cplusplus
}
#endif
#endif
modules/imgproc/include/opencv2/imgproc/types_c.h
-611
View File
@@ -45,615 +45,4 @@
#include "opencv2/core/core_c.h"
#ifdef __cplusplus
extern "C" {
#endif
/** @addtogroup imgproc_c
@{
*/
/** Connected component structure */
typedef struct CvConnectedComp
{
double area; /**<area of the connected component */
CvScalar value; /**<average color of the connected component */
CvRect rect; /**<ROI of the component */
CvSeq* contour; /**<optional component boundary
(the contour might have child contours corresponding to the holes)*/
}
CvConnectedComp;
/** Image smooth methods */
enum SmoothMethod_c
{
/** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all 1's). If
you want to smooth different pixels with different-size box kernels, you can use the integral
image that is computed using integral */
CV_BLUR_NO_SCALE =0,
/** linear convolution with \f$\texttt{size1}\times\texttt{size2}\f$ box kernel (all
1's) with subsequent scaling by \f$1/(\texttt{size1}\cdot\texttt{size2})\f$ */
CV_BLUR =1,
/** linear convolution with a \f$\texttt{size1}\times\texttt{size2}\f$ Gaussian kernel */
CV_GAUSSIAN =2,
/** median filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture */
CV_MEDIAN =3,
/** bilateral filter with a \f$\texttt{size1}\times\texttt{size1}\f$ square aperture, color
sigma= sigma1 and spatial sigma= sigma2. If size1=0, the aperture square side is set to
cvRound(sigma2\*1.5)\*2+1. See cv::bilateralFilter */
CV_BILATERAL =4
};
/** Filters used in pyramid decomposition */
enum
{
CV_GAUSSIAN_5x5 = 7
};
/** Special filters */
enum
{
CV_SCHARR =-1,
CV_MAX_SOBEL_KSIZE =7
};
/** Constants for color conversion */
enum
{
CV_BGR2BGRA =0,
CV_RGB2RGBA =CV_BGR2BGRA,
CV_BGRA2BGR =1,
CV_RGBA2RGB =CV_BGRA2BGR,
CV_BGR2RGBA =2,
CV_RGB2BGRA =CV_BGR2RGBA,
CV_RGBA2BGR =3,
CV_BGRA2RGB =CV_RGBA2BGR,
CV_BGR2RGB =4,
CV_RGB2BGR =CV_BGR2RGB,
CV_BGRA2RGBA =5,
CV_RGBA2BGRA =CV_BGRA2RGBA,
CV_BGR2GRAY =6,
CV_RGB2GRAY =7,
CV_GRAY2BGR =8,
CV_GRAY2RGB =CV_GRAY2BGR,
CV_GRAY2BGRA =9,
CV_GRAY2RGBA =CV_GRAY2BGRA,
CV_BGRA2GRAY =10,
CV_RGBA2GRAY =11,
CV_BGR2BGR565 =12,
CV_RGB2BGR565 =13,
CV_BGR5652BGR =14,
CV_BGR5652RGB =15,
CV_BGRA2BGR565 =16,
CV_RGBA2BGR565 =17,
CV_BGR5652BGRA =18,
CV_BGR5652RGBA =19,
CV_GRAY2BGR565 =20,
CV_BGR5652GRAY =21,
CV_BGR2BGR555 =22,
CV_RGB2BGR555 =23,
CV_BGR5552BGR =24,
CV_BGR5552RGB =25,
CV_BGRA2BGR555 =26,
CV_RGBA2BGR555 =27,
CV_BGR5552BGRA =28,
CV_BGR5552RGBA =29,
CV_GRAY2BGR555 =30,
CV_BGR5552GRAY =31,
CV_BGR2XYZ =32,
CV_RGB2XYZ =33,
CV_XYZ2BGR =34,
CV_XYZ2RGB =35,
CV_BGR2YCrCb =36,
CV_RGB2YCrCb =37,
CV_YCrCb2BGR =38,
CV_YCrCb2RGB =39,
CV_BGR2HSV =40,
CV_RGB2HSV =41,
CV_BGR2Lab =44,
CV_RGB2Lab =45,
CV_BayerBG2BGR =46,
CV_BayerGB2BGR =47,
CV_BayerRG2BGR =48,
CV_BayerGR2BGR =49,
CV_BayerBG2RGB =CV_BayerRG2BGR,
CV_BayerGB2RGB =CV_BayerGR2BGR,
CV_BayerRG2RGB =CV_BayerBG2BGR,
CV_BayerGR2RGB =CV_BayerGB2BGR,
CV_BGR2Luv =50,
CV_RGB2Luv =51,
CV_BGR2HLS =52,
CV_RGB2HLS =53,
CV_HSV2BGR =54,
CV_HSV2RGB =55,
CV_Lab2BGR =56,
CV_Lab2RGB =57,
CV_Luv2BGR =58,
CV_Luv2RGB =59,
CV_HLS2BGR =60,
CV_HLS2RGB =61,
CV_BayerBG2BGR_VNG =62,
CV_BayerGB2BGR_VNG =63,
CV_BayerRG2BGR_VNG =64,
CV_BayerGR2BGR_VNG =65,
CV_BayerBG2RGB_VNG =CV_BayerRG2BGR_VNG,
CV_BayerGB2RGB_VNG =CV_BayerGR2BGR_VNG,
CV_BayerRG2RGB_VNG =CV_BayerBG2BGR_VNG,
CV_BayerGR2RGB_VNG =CV_BayerGB2BGR_VNG,
CV_BGR2HSV_FULL = 66,
CV_RGB2HSV_FULL = 67,
CV_BGR2HLS_FULL = 68,
CV_RGB2HLS_FULL = 69,
CV_HSV2BGR_FULL = 70,
CV_HSV2RGB_FULL = 71,
CV_HLS2BGR_FULL = 72,
CV_HLS2RGB_FULL = 73,
CV_LBGR2Lab = 74,
CV_LRGB2Lab = 75,
CV_LBGR2Luv = 76,
CV_LRGB2Luv = 77,
CV_Lab2LBGR = 78,
CV_Lab2LRGB = 79,
CV_Luv2LBGR = 80,
CV_Luv2LRGB = 81,
CV_BGR2YUV = 82,
CV_RGB2YUV = 83,
CV_YUV2BGR = 84,
CV_YUV2RGB = 85,
CV_BayerBG2GRAY = 86,
CV_BayerGB2GRAY = 87,
CV_BayerRG2GRAY = 88,
CV_BayerGR2GRAY = 89,
//YUV 4:2:0 formats family
CV_YUV2RGB_NV12 = 90,
CV_YUV2BGR_NV12 = 91,
CV_YUV2RGB_NV21 = 92,
CV_YUV2BGR_NV21 = 93,
CV_YUV420sp2RGB = CV_YUV2RGB_NV21,
CV_YUV420sp2BGR = CV_YUV2BGR_NV21,
CV_YUV2RGBA_NV12 = 94,
CV_YUV2BGRA_NV12 = 95,
CV_YUV2RGBA_NV21 = 96,
CV_YUV2BGRA_NV21 = 97,
CV_YUV420sp2RGBA = CV_YUV2RGBA_NV21,
CV_YUV420sp2BGRA = CV_YUV2BGRA_NV21,
CV_YUV2RGB_YV12 = 98,
CV_YUV2BGR_YV12 = 99,
CV_YUV2RGB_IYUV = 100,
CV_YUV2BGR_IYUV = 101,
CV_YUV2RGB_I420 = CV_YUV2RGB_IYUV,
CV_YUV2BGR_I420 = CV_YUV2BGR_IYUV,
CV_YUV420p2RGB = CV_YUV2RGB_YV12,
CV_YUV420p2BGR = CV_YUV2BGR_YV12,
CV_YUV2RGBA_YV12 = 102,
CV_YUV2BGRA_YV12 = 103,
CV_YUV2RGBA_IYUV = 104,
CV_YUV2BGRA_IYUV = 105,
CV_YUV2RGBA_I420 = CV_YUV2RGBA_IYUV,
CV_YUV2BGRA_I420 = CV_YUV2BGRA_IYUV,
CV_YUV420p2RGBA = CV_YUV2RGBA_YV12,
CV_YUV420p2BGRA = CV_YUV2BGRA_YV12,
CV_YUV2GRAY_420 = 106,
CV_YUV2GRAY_NV21 = CV_YUV2GRAY_420,
CV_YUV2GRAY_NV12 = CV_YUV2GRAY_420,
CV_YUV2GRAY_YV12 = CV_YUV2GRAY_420,
CV_YUV2GRAY_IYUV = CV_YUV2GRAY_420,
CV_YUV2GRAY_I420 = CV_YUV2GRAY_420,
CV_YUV420sp2GRAY = CV_YUV2GRAY_420,
CV_YUV420p2GRAY = CV_YUV2GRAY_420,
//YUV 4:2:2 formats family
CV_YUV2RGB_UYVY = 107,
CV_YUV2BGR_UYVY = 108,
//CV_YUV2RGB_VYUY = 109,
//CV_YUV2BGR_VYUY = 110,
CV_YUV2RGB_Y422 = CV_YUV2RGB_UYVY,
CV_YUV2BGR_Y422 = CV_YUV2BGR_UYVY,
CV_YUV2RGB_UYNV = CV_YUV2RGB_UYVY,
CV_YUV2BGR_UYNV = CV_YUV2BGR_UYVY,
CV_YUV2RGBA_UYVY = 111,
CV_YUV2BGRA_UYVY = 112,
//CV_YUV2RGBA_VYUY = 113,
//CV_YUV2BGRA_VYUY = 114,
CV_YUV2RGBA_Y422 = CV_YUV2RGBA_UYVY,
CV_YUV2BGRA_Y422 = CV_YUV2BGRA_UYVY,
CV_YUV2RGBA_UYNV = CV_YUV2RGBA_UYVY,
CV_YUV2BGRA_UYNV = CV_YUV2BGRA_UYVY,
CV_YUV2RGB_YUY2 = 115,
CV_YUV2BGR_YUY2 = 116,
CV_YUV2RGB_YVYU = 117,
CV_YUV2BGR_YVYU = 118,
CV_YUV2RGB_YUYV = CV_YUV2RGB_YUY2,
CV_YUV2BGR_YUYV = CV_YUV2BGR_YUY2,
CV_YUV2RGB_YUNV = CV_YUV2RGB_YUY2,
CV_YUV2BGR_YUNV = CV_YUV2BGR_YUY2,
CV_YUV2RGBA_YUY2 = 119,
CV_YUV2BGRA_YUY2 = 120,
CV_YUV2RGBA_YVYU = 121,
CV_YUV2BGRA_YVYU = 122,
CV_YUV2RGBA_YUYV = CV_YUV2RGBA_YUY2,
CV_YUV2BGRA_YUYV = CV_YUV2BGRA_YUY2,
CV_YUV2RGBA_YUNV = CV_YUV2RGBA_YUY2,
CV_YUV2BGRA_YUNV = CV_YUV2BGRA_YUY2,
CV_YUV2GRAY_UYVY = 123,
CV_YUV2GRAY_YUY2 = 124,
//CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY,
CV_YUV2GRAY_Y422 = CV_YUV2GRAY_UYVY,
CV_YUV2GRAY_UYNV = CV_YUV2GRAY_UYVY,
CV_YUV2GRAY_YVYU = CV_YUV2GRAY_YUY2,
CV_YUV2GRAY_YUYV = CV_YUV2GRAY_YUY2,
CV_YUV2GRAY_YUNV = CV_YUV2GRAY_YUY2,
// alpha premultiplication
CV_RGBA2mRGBA = 125,
CV_mRGBA2RGBA = 126,
CV_RGB2YUV_I420 = 127,
CV_BGR2YUV_I420 = 128,
CV_RGB2YUV_IYUV = CV_RGB2YUV_I420,
CV_BGR2YUV_IYUV = CV_BGR2YUV_I420,
CV_RGBA2YUV_I420 = 129,
CV_BGRA2YUV_I420 = 130,
CV_RGBA2YUV_IYUV = CV_RGBA2YUV_I420,
CV_BGRA2YUV_IYUV = CV_BGRA2YUV_I420,
CV_RGB2YUV_YV12 = 131,
CV_BGR2YUV_YV12 = 132,
CV_RGBA2YUV_YV12 = 133,
CV_BGRA2YUV_YV12 = 134,
// Edge-Aware Demosaicing
CV_BayerBG2BGR_EA = 135,
CV_BayerGB2BGR_EA = 136,
CV_BayerRG2BGR_EA = 137,
CV_BayerGR2BGR_EA = 138,
CV_BayerBG2RGB_EA = CV_BayerRG2BGR_EA,
CV_BayerGB2RGB_EA = CV_BayerGR2BGR_EA,
CV_BayerRG2RGB_EA = CV_BayerBG2BGR_EA,
CV_BayerGR2RGB_EA = CV_BayerGB2BGR_EA,
CV_BayerBG2BGRA =139,
CV_BayerGB2BGRA =140,
CV_BayerRG2BGRA =141,
CV_BayerGR2BGRA =142,
CV_BayerBG2RGBA =CV_BayerRG2BGRA,
CV_BayerGB2RGBA =CV_BayerGR2BGRA,
CV_BayerRG2RGBA =CV_BayerBG2BGRA,
CV_BayerGR2RGBA =CV_BayerGB2BGRA,
CV_COLORCVT_MAX = 143
};
/** Sub-pixel interpolation methods */
enum
{
CV_INTER_NN =0,
CV_INTER_LINEAR =1,
CV_INTER_CUBIC =2,
CV_INTER_AREA =3,
CV_INTER_LANCZOS4 =4
};
/** ... and other image warping flags */
enum
{
CV_WARP_FILL_OUTLIERS =8,
CV_WARP_INVERSE_MAP =16
};
/** Shapes of a structuring element for morphological operations
@see cv::MorphShapes, cv::getStructuringElement
*/
enum MorphShapes_c
{
CV_SHAPE_RECT =0,
CV_SHAPE_CROSS =1,
CV_SHAPE_ELLIPSE =2,
CV_SHAPE_CUSTOM =100 //!< custom structuring element
};
/** Morphological operations */
enum
{
CV_MOP_ERODE =0,
CV_MOP_DILATE =1,
CV_MOP_OPEN =2,
CV_MOP_CLOSE =3,
CV_MOP_GRADIENT =4,
CV_MOP_TOPHAT =5,
CV_MOP_BLACKHAT =6
};
/** Spatial and central moments */
typedef struct CvMoments
{
double m00, m10, m01, m20, m11, m02, m30, m21, m12, m03; /**< spatial moments */
double mu20, mu11, mu02, mu30, mu21, mu12, mu03; /**< central moments */
double inv_sqrt_m00; /**< m00 != 0 ? 1/sqrt(m00) : 0 */
#if defined(CV__ENABLE_C_API_CTORS) && defined(__cplusplus)
CvMoments(){}
CvMoments(const cv::Moments& m)
{
m00 = m.m00; m10 = m.m10; m01 = m.m01;
m20 = m.m20; m11 = m.m11; m02 = m.m02;
m30 = m.m30; m21 = m.m21; m12 = m.m12; m03 = m.m03;
mu20 = m.mu20; mu11 = m.mu11; mu02 = m.mu02;
mu30 = m.mu30; mu21 = m.mu21; mu12 = m.mu12; mu03 = m.mu03;
double am00 = std::abs(m.m00);
inv_sqrt_m00 = am00 > DBL_EPSILON ? 1./std::sqrt(am00) : 0;
}
operator cv::Moments() const
{
return cv::Moments(m00, m10, m01, m20, m11, m02, m30, m21, m12, m03);
}
#endif
}
CvMoments;
#ifdef __cplusplus
} // extern "C"
CV_INLINE CvMoments cvMoments()
{
#if !defined(CV__ENABLE_C_API_CTORS)
CvMoments self = CV_STRUCT_INITIALIZER; return self;
#else
return CvMoments();
#endif
}
CV_INLINE CvMoments cvMoments(const cv::Moments& m)
{
#if !defined(CV__ENABLE_C_API_CTORS)
double am00 = std::abs(m.m00);
CvMoments self = {
m.m00, m.m10, m.m01, m.m20, m.m11, m.m02, m.m30, m.m21, m.m12, m.m03,
m.mu20, m.mu11, m.mu02, m.mu30, m.mu21, m.mu12, m.mu03,
am00 > DBL_EPSILON ? 1./std::sqrt(am00) : 0
};
return self;
#else
return CvMoments(m);
#endif
}
extern "C" {
#endif // __cplusplus
/** Hu invariants */
typedef struct CvHuMoments
{
double hu1, hu2, hu3, hu4, hu5, hu6, hu7; /**< Hu invariants */
}
CvHuMoments;
/** Template matching methods */
enum
{
CV_TM_SQDIFF =0,
CV_TM_SQDIFF_NORMED =1,
CV_TM_CCORR =2,
CV_TM_CCORR_NORMED =3,
CV_TM_CCOEFF =4,
CV_TM_CCOEFF_NORMED =5
};
typedef float (CV_CDECL * CvDistanceFunction)( const float* a, const float* b, void* user_param );
/** Contour retrieval modes */
enum
{
CV_RETR_EXTERNAL=0,
CV_RETR_LIST=1,
CV_RETR_CCOMP=2,
CV_RETR_TREE=3,
CV_RETR_FLOODFILL=4
};
/** Contour approximation methods */
enum
{
CV_CHAIN_CODE=0,
CV_CHAIN_APPROX_NONE=1,
CV_CHAIN_APPROX_SIMPLE=2,
CV_CHAIN_APPROX_TC89_L1=3,
CV_CHAIN_APPROX_TC89_KCOS=4,
CV_LINK_RUNS=5
};
/*
Internal structure that is used for sequential retrieving contours from the image.
It supports both hierarchical and plane variants of Suzuki algorithm.
*/
typedef struct _CvContourScanner* CvContourScanner;
/** Freeman chain reader state */
typedef struct CvChainPtReader
{
CV_SEQ_READER_FIELDS()
char code;
CvPoint pt;
schar deltas[8][2];
}
CvChainPtReader;
/** initializes 8-element array for fast access to 3x3 neighborhood of a pixel */
#define CV_INIT_3X3_DELTAS( deltas, step, nch ) \
((deltas)[0] = (nch), (deltas)[1] = -(step) + (nch), \
(deltas)[2] = -(step), (deltas)[3] = -(step) - (nch), \
(deltas)[4] = -(nch), (deltas)[5] = (step) - (nch), \
(deltas)[6] = (step), (deltas)[7] = (step) + (nch))
/** Contour approximation algorithms */
enum
{
CV_POLY_APPROX_DP = 0
};
/** Shape matching methods */
enum
{
CV_CONTOURS_MATCH_I1 =1, //!< \f[I_1(A,B) = \sum _{i=1...7} \left | \frac{1}{m^A_i} - \frac{1}{m^B_i} \right |\f]
CV_CONTOURS_MATCH_I2 =2, //!< \f[I_2(A,B) = \sum _{i=1...7} \left | m^A_i - m^B_i \right |\f]
CV_CONTOURS_MATCH_I3 =3 //!< \f[I_3(A,B) = \max _{i=1...7} \frac{ \left| m^A_i - m^B_i \right| }{ \left| m^A_i \right| }\f]
};
/** Shape orientation */
enum
{
CV_CLOCKWISE =1,
CV_COUNTER_CLOCKWISE =2
};
/** Convexity defect */
typedef struct CvConvexityDefect
{
CvPoint* start; /**< point of the contour where the defect begins */
CvPoint* end; /**< point of the contour where the defect ends */
CvPoint* depth_point; /**< the farthest from the convex hull point within the defect */
float depth; /**< distance between the farthest point and the convex hull */
} CvConvexityDefect;
/** Histogram comparison methods */
enum
{
CV_COMP_CORREL =0,
CV_COMP_CHISQR =1,
CV_COMP_INTERSECT =2,
CV_COMP_BHATTACHARYYA =3,
CV_COMP_HELLINGER =CV_COMP_BHATTACHARYYA,
CV_COMP_CHISQR_ALT =4,
CV_COMP_KL_DIV =5
};
/** Mask size for distance transform */
enum
{
CV_DIST_MASK_3 =3,
CV_DIST_MASK_5 =5,
CV_DIST_MASK_PRECISE =0
};
/** Content of output label array: connected components or pixels */
enum
{
CV_DIST_LABEL_CCOMP = 0,
CV_DIST_LABEL_PIXEL = 1
};
/** Distance types for Distance Transform and M-estimators */
enum
{
CV_DIST_USER =-1, /**< User defined distance */
CV_DIST_L1 =1, /**< distance = |x1-x2| + |y1-y2| */
CV_DIST_L2 =2, /**< the simple euclidean distance */
CV_DIST_C =3, /**< distance = max(|x1-x2|,|y1-y2|) */
CV_DIST_L12 =4, /**< L1-L2 metric: distance = 2(sqrt(1+x*x/2) - 1)) */
CV_DIST_FAIR =5, /**< distance = c^2(|x|/c-log(1+|x|/c)), c = 1.3998 */
CV_DIST_WELSCH =6, /**< distance = c^2/2(1-exp(-(x/c)^2)), c = 2.9846 */
CV_DIST_HUBER =7 /**< distance = |x|<c ? x^2/2 : c(|x|-c/2), c=1.345 */
};
/** Threshold types */
enum
{
CV_THRESH_BINARY =0, /**< value = value > threshold ? max_value : 0 */
CV_THRESH_BINARY_INV =1, /**< value = value > threshold ? 0 : max_value */
CV_THRESH_TRUNC =2, /**< value = value > threshold ? threshold : value */
CV_THRESH_TOZERO =3, /**< value = value > threshold ? value : 0 */
CV_THRESH_TOZERO_INV =4, /**< value = value > threshold ? 0 : value */
CV_THRESH_MASK =7,
CV_THRESH_OTSU =8, /**< use Otsu algorithm to choose the optimal threshold value;
combine the flag with one of the above CV_THRESH_* values */
CV_THRESH_TRIANGLE =16 /**< use Triangle algorithm to choose the optimal threshold value;
combine the flag with one of the above CV_THRESH_* values, but not
with CV_THRESH_OTSU */
};
/** Adaptive threshold methods */
enum
{
CV_ADAPTIVE_THRESH_MEAN_C =0,
CV_ADAPTIVE_THRESH_GAUSSIAN_C =1
};
/** FloodFill flags */
enum
{
CV_FLOODFILL_FIXED_RANGE =(1 << 16),
CV_FLOODFILL_MASK_ONLY =(1 << 17)
};
/** Canny edge detector flags */
enum
{
CV_CANNY_L2_GRADIENT =(1 << 31)
};
/** Variants of a Hough transform */
enum
{
CV_HOUGH_STANDARD =0,
CV_HOUGH_PROBABILISTIC =1,
CV_HOUGH_MULTI_SCALE =2,
CV_HOUGH_GRADIENT =3
};
/* Fast search data structures */
struct CvFeatureTree;
struct CvLSH;
struct CvLSHOperations;
/** @} */
#ifdef __cplusplus
}
#endif
#endif