OpenCV
3.3.0
Open Source Computer Vision
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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 } |
enum | cv::KmeansFlags { cv::KMEANS_RANDOM_CENTERS = 0, cv::KMEANS_PP_CENTERS = 2, cv::KMEANS_USE_INITIAL_LABELS = 1 } |
k-Means flags More... | |
enum | cv::LineTypes { cv::FILLED = -1, cv::LINE_4 = 4, cv::LINE_8 = 8, cv::LINE_AA = 16 } |
type of line More... | |
enum | cv::ReduceTypes { cv::REDUCE_SUM = 0, cv::REDUCE_AVG = 1, cv::REDUCE_MAX = 2, cv::REDUCE_MIN = 3 } |
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) |
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 |
typedef Affine3<float> cv::Affine3f |
typedef WImageC<short, 1> cv::WImage1_16s |
typedef WImageC<ushort, 1> cv::WImage1_16u |
typedef WImageC<uchar, 1> cv::WImage1_b |
typedef WImageC<float, 1> cv::WImage1_f |
typedef WImageC<short, 3> cv::WImage3_16s |
typedef WImageC<ushort, 3> cv::WImage3_16u |
typedef WImageC<uchar, 3> cv::WImage3_b |
typedef WImageC<float, 3> cv::WImage3_f |
typedef WImage<short> cv::WImage_16s |
typedef WImage<ushort> cv::WImage_16u |
typedef WImage<uchar> cv::WImage_b |
typedef WImage<float> cv::WImage_f |
typedef WImageBufferC<short, 1> cv::WImageBuffer1_16s |
typedef WImageBufferC<ushort, 1> cv::WImageBuffer1_16u |
typedef WImageBufferC<uchar, 1> cv::WImageBuffer1_b |
typedef WImageBufferC<float, 1> cv::WImageBuffer1_f |
typedef WImageBufferC<short, 3> cv::WImageBuffer3_16s |
typedef WImageBufferC<ushort, 3> cv::WImageBuffer3_16u |
typedef WImageBufferC<uchar, 3> cv::WImageBuffer3_b |
typedef WImageBufferC<float, 3> cv::WImageBuffer3_f |
typedef WImageBuffer<short> cv::WImageBuffer_16s |
typedef WImageBuffer<ushort> cv::WImageBuffer_16u |
typedef WImageBuffer<uchar> cv::WImageBuffer_b |
typedef WImageBuffer<float> cv::WImageBuffer_f |
typedef WImageViewC<short, 1> cv::WImageView1_16s |
typedef WImageViewC<ushort, 1> cv::WImageView1_16u |
typedef WImageViewC<uchar, 1> cv::WImageView1_b |
typedef WImageViewC<float, 1> cv::WImageView1_f |
typedef WImageViewC<short, 3> cv::WImageView3_16s |
typedef WImageViewC<ushort, 3> cv::WImageView3_16u |
typedef WImageViewC<uchar, 3> cv::WImageView3_b |
typedef WImageViewC<float, 3> cv::WImageView3_f |
typedef WImageView<short> cv::WImageView_16s |
typedef WImageView<ushort> cv::WImageView_16u |
typedef WImageView<uchar> cv::WImageView_b |
typedef WImageView<float> cv::WImageView_f |
enum cv::CovarFlags |
Covariation flags.
Enumerator | |
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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 | 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 | 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 | 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 | 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 | 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 |
Only a subset of Hershey fonts http://sources.isc.org/utils/misc/hershey-font.txt are supported
enum cv::KmeansFlags |
k-Means flags
enum cv::LineTypes |
enum cv::ReduceTypes |
cv::WImageView< T >::WImageView | ( | WImage< T > * | img, |
int | c, | ||
int | r, | ||
int | width, | ||
int | height | ||
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cv::WImageView< T >::WImageView | ( | T * | data, |
int | width, | ||
int | height, | ||
int | channels, | ||
int | width_step = -1 |
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cv::WImageViewC< T, C >::WImageViewC | ( | ) |
cv::WImageViewC< T, C >::WImageViewC | ( | WImageC< T, C > * | img, |
int | c, | ||
int | r, | ||
int | width, | ||
int | height | ||
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cv::WImageViewC< T, C >::WImageViewC | ( | T * | data, |
int | width, | ||
int | height, | ||
int | width_step = -1 |
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inlinepure virtual |
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inlinepure virtual |
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inline |
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inline |
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static |
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 | ||
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WImageViewC< T, C > cv::WImageC< T, C >::View | ( | int | c, |
int | r, | ||
int | width, | ||
int | height | ||
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