OpenCV
3.4.19
Open Source Computer Vision
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Namespaces | |
cv::traits | |
Classes | |
class | cv::Affine3< T > |
Affine transform. More... | |
class | cv::BufferPoolController |
class | cv::WImage< T > |
Image class which provides a thin layer around an IplImage. More... | |
class | cv::WImageBuffer< T > |
class | cv::WImageBufferC< T, C > |
class | cv::WImageC< T, C > |
class | cv::WImageView< T > |
class | cv::WImageViewC< T, C > |
Enumerations | |
enum | cv::CovarFlags { cv::COVAR_SCRAMBLED = 0, cv::COVAR_NORMAL = 1, cv::COVAR_USE_AVG = 2, cv::COVAR_SCALE = 4, cv::COVAR_ROWS = 8, cv::COVAR_COLS = 16 } |
Covariation flags. More... | |
enum | cv::HersheyFonts { cv::FONT_HERSHEY_SIMPLEX = 0, cv::FONT_HERSHEY_PLAIN = 1, cv::FONT_HERSHEY_DUPLEX = 2, cv::FONT_HERSHEY_COMPLEX = 3, cv::FONT_HERSHEY_TRIPLEX = 4, cv::FONT_HERSHEY_COMPLEX_SMALL = 5, cv::FONT_HERSHEY_SCRIPT_SIMPLEX = 6, cv::FONT_HERSHEY_SCRIPT_COMPLEX = 7, cv::FONT_ITALIC = 16 } |
Only a subset of Hershey fonts https://en.wikipedia.org/wiki/Hershey_fonts are supported. More... | |
enum | cv::LineTypes { cv::FILLED = -1, cv::LINE_4 = 4, cv::LINE_8 = 8, cv::LINE_AA = 16 } |
type of line More... | |
Functions | |
cv::WImageView< T >::WImageView (WImage< T > *img, int c, int r, int width, int height) | |
cv::WImageView< T >::WImageView (T *data, int width, int height, int channels, int width_step=-1) | |
cv::WImageViewC< T, C >::WImageViewC () | |
cv::WImageViewC< T, C >::WImageViewC (WImageC< T, C > *img, int c, int r, int width, int height) | |
cv::WImageViewC< T, C >::WImageViewC (T *data, int width, int height, int width_step=-1) | |
virtual | cv::WImage< T >::~WImage ()=0 |
virtual | cv::WImageC< T, C >::~WImageC ()=0 |
void | cv::WImageBuffer< T >::Allocate (int width, int height, int nchannels) |
void | cv::WImageBufferC< T, C >::Allocate (int width, int height) |
template<typename T > | |
static Affine3< T > | cv::operator* (const Affine3< T > &affine1, const Affine3< T > &affine2) |
template<typename T , typename V > | |
static V | cv::operator* (const Affine3< T > &affine, const V &vector) |
V is a 3-element vector with member fields x, y and z. More... | |
static Vec3f | cv::operator* (const Affine3f &affine, const Vec3f &vector) |
static Vec3d | cv::operator* (const Affine3d &affine, const Vec3d &vector) |
void | cv::swap (Mat &a, Mat &b) |
Swaps two matrices. More... | |
void | cv::swap (UMat &a, UMat &b) |
WImageView< T > | cv::WImage< T >::View (int c, int r, int width, int height) |
WImageViewC< T, C > | cv::WImageC< T, C >::View (int c, int r, int width, int height) |
typedef Affine3<double> cv::Affine3d |
#include <opencv2/core/affine.hpp>
typedef Affine3<float> cv::Affine3f |
#include <opencv2/core/affine.hpp>
typedef WImageC<short, 1> cv::WImage1_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageC<ushort, 1> cv::WImage1_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageC<uchar, 1> cv::WImage1_b |
#include <opencv2/core/wimage.hpp>
typedef WImageC<float, 1> cv::WImage1_f |
#include <opencv2/core/wimage.hpp>
typedef WImageC<short, 3> cv::WImage3_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageC<ushort, 3> cv::WImage3_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageC<uchar, 3> cv::WImage3_b |
#include <opencv2/core/wimage.hpp>
typedef WImageC<float, 3> cv::WImage3_f |
#include <opencv2/core/wimage.hpp>
typedef WImage<short> cv::WImage_16s |
#include <opencv2/core/wimage.hpp>
typedef WImage<ushort> cv::WImage_16u |
#include <opencv2/core/wimage.hpp>
typedef WImage<uchar> cv::WImage_b |
#include <opencv2/core/wimage.hpp>
typedef WImage<float> cv::WImage_f |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<short, 1> cv::WImageBuffer1_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<ushort, 1> cv::WImageBuffer1_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<uchar, 1> cv::WImageBuffer1_b |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<float, 1> cv::WImageBuffer1_f |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<short, 3> cv::WImageBuffer3_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<ushort, 3> cv::WImageBuffer3_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<uchar, 3> cv::WImageBuffer3_b |
#include <opencv2/core/wimage.hpp>
typedef WImageBufferC<float, 3> cv::WImageBuffer3_f |
#include <opencv2/core/wimage.hpp>
typedef WImageBuffer<short> cv::WImageBuffer_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageBuffer<ushort> cv::WImageBuffer_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageBuffer<uchar> cv::WImageBuffer_b |
#include <opencv2/core/wimage.hpp>
typedef WImageBuffer<float> cv::WImageBuffer_f |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<short, 1> cv::WImageView1_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<ushort, 1> cv::WImageView1_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<uchar, 1> cv::WImageView1_b |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<float, 1> cv::WImageView1_f |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<short, 3> cv::WImageView3_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<ushort, 3> cv::WImageView3_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<uchar, 3> cv::WImageView3_b |
#include <opencv2/core/wimage.hpp>
typedef WImageViewC<float, 3> cv::WImageView3_f |
#include <opencv2/core/wimage.hpp>
typedef WImageView<short> cv::WImageView_16s |
#include <opencv2/core/wimage.hpp>
typedef WImageView<ushort> cv::WImageView_16u |
#include <opencv2/core/wimage.hpp>
typedef WImageView<uchar> cv::WImageView_b |
#include <opencv2/core/wimage.hpp>
typedef WImageView<float> cv::WImageView_f |
#include <opencv2/core/wimage.hpp>
enum cv::CovarFlags |
#include <opencv2/core.hpp>
Covariation flags.
Enumerator | |
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COVAR_SCRAMBLED Python: cv.COVAR_SCRAMBLED | The output covariance matrix is calculated as: \[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...],\] The covariance matrix will be nsamples x nsamples. Such an unusual covariance matrix is used for fast PCA of a set of very large vectors (see, for example, the EigenFaces technique for face recognition). Eigenvalues of this "scrambled" matrix match the eigenvalues of the true covariance matrix. The "true" eigenvectors can be easily calculated from the eigenvectors of the "scrambled" covariance matrix. |
COVAR_NORMAL Python: cv.COVAR_NORMAL | The output covariance matrix is calculated as: \[\texttt{scale} \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...] \cdot [ \texttt{vects} [0]- \texttt{mean} , \texttt{vects} [1]- \texttt{mean} ,...]^T,\] covar will be a square matrix of the same size as the total number of elements in each input vector. One and only one of COVAR_SCRAMBLED and COVAR_NORMAL must be specified. |
COVAR_USE_AVG Python: cv.COVAR_USE_AVG | If the flag is specified, the function does not calculate mean from the input vectors but, instead, uses the passed mean vector. This is useful if mean has been pre-calculated or known in advance, or if the covariance matrix is calculated by parts. In this case, mean is not a mean vector of the input sub-set of vectors but rather the mean vector of the whole set. |
COVAR_SCALE Python: cv.COVAR_SCALE | If the flag is specified, the covariance matrix is scaled. In the "normal" mode, scale is 1./nsamples . In the "scrambled" mode, scale is the reciprocal of the total number of elements in each input vector. By default (if the flag is not specified), the covariance matrix is not scaled ( scale=1 ). |
COVAR_ROWS Python: cv.COVAR_ROWS | If the flag is specified, all the input vectors are stored as rows of the samples matrix. mean should be a single-row vector in this case. |
COVAR_COLS Python: cv.COVAR_COLS | If the flag is specified, all the input vectors are stored as columns of the samples matrix. mean should be a single-column vector in this case. |
enum cv::HersheyFonts |
#include <opencv2/core.hpp>
Only a subset of Hershey fonts https://en.wikipedia.org/wiki/Hershey_fonts are supported.
enum cv::LineTypes |
#include <opencv2/core.hpp>
type of line
Enumerator | |
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FILLED Python: cv.FILLED | |
LINE_4 Python: cv.LINE_4 | 4-connected line |
LINE_8 Python: cv.LINE_8 | 8-connected line |
LINE_AA Python: cv.LINE_AA | antialiased line |
cv::WImageView< T >::WImageView | ( | WImage< T > * | img, |
int | c, | ||
int | r, | ||
int | width, | ||
int | height | ||
) |
#include <opencv2/core/wimage.hpp>
cv::WImageView< T >::WImageView | ( | T * | data, |
int | width, | ||
int | height, | ||
int | channels, | ||
int | width_step = -1 |
||
) |
#include <opencv2/core/wimage.hpp>
cv::WImageViewC< T, C >::WImageViewC | ( | ) |
#include <opencv2/core/wimage.hpp>
cv::WImageViewC< T, C >::WImageViewC | ( | WImageC< T, C > * | img, |
int | c, | ||
int | r, | ||
int | width, | ||
int | height | ||
) |
#include <opencv2/core/wimage.hpp>
cv::WImageViewC< T, C >::WImageViewC | ( | T * | data, |
int | width, | ||
int | height, | ||
int | width_step = -1 |
||
) |
#include <opencv2/core/wimage.hpp>
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inlinepure virtual |
#include <opencv2/core/wimage.hpp>
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inlinepure virtual |
#include <opencv2/core/wimage.hpp>
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inline |
#include <opencv2/core/wimage.hpp>
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inline |
#include <opencv2/core/wimage.hpp>
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static |
#include <opencv2/core/affine.hpp>
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static |
#include <opencv2/core/affine.hpp>
V is a 3-element vector with member fields x, y and z.
#include <opencv2/core/affine.hpp>
#include <opencv2/core/affine.hpp>
#include <opencv2/core.hpp>
Swaps two matrices.
#include <opencv2/core.hpp>
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
WImageView< T > cv::WImage< T >::View | ( | int | c, |
int | r, | ||
int | width, | ||
int | height | ||
) |
#include <opencv2/core/wimage.hpp>
WImageViewC< T, C > cv::WImageC< T, C >::View | ( | int | c, |
int | r, | ||
int | width, | ||
int | height | ||
) |
#include <opencv2/core/wimage.hpp>