Cv2 Methods

Computes absolute value of each matrix element

Computes absolute value of each matrix element

Calculates the per-element absolute difference between two arrays or between an array and a scalar.

Adds an image to the accumulator.

Adds the per-element product of two input images to the accumulator.

Adds the square of a source image to the accumulator.

Updates a running average.

Applies an adaptive threshold to an array.

Computes the per-element sum of two arrays or an array and a scalar.

computes weighted sum of two arrays (dst = alpha*src1 + beta*src2 + gamma)

Detects corners using the AGAST algorithm

Aligns buffer size by the certain number of bytes This small inline function aligns a buffer size by the certian number of bytes by enlarging it.

Applies a GNU Octave/MATLAB equivalent colormap on a given image.

Approximates contour or a curve using Douglas-Peucker algorithm

Approximates contour or a curve using Douglas-Peucker algorithm

Approximates contour or a curve using Douglas-Peucker algorithm

Calculates a contour perimeter or a curve length.

Calculates a contour perimeter or a curve length.

Calculates a contour perimeter or a curve length.

Draws a arrow segment pointing from the first point to the second one. The function arrowedLine draws an arrow between pt1 and pt2 points in the image. See also cv::line.

naive nearest neighbor finder

Applies bilateral filter to the image

computes bitwise conjunction of the two arrays (dst = src1 & src2)

inverts each bit of array (dst = ~src)

computes bitwise disjunction of the two arrays (dst = src1 | src2)

computes bitwise exclusive-or of the two arrays (dst = src1 ^ src2)

Performs linear blending of two images: dst(i,j) = weights1(i,j)*src1(i,j) + weights2(i,j)*src2(i,j)

Smoothes image using normalized box filter

Computes the source location of an extrapolated pixel.

Calculates the up-right bounding rectangle of a point set.

Calculates the up-right bounding rectangle of a point set.

Calculates the up-right bounding rectangle of a point set.

Smoothes image using box filter

Finds the four vertices of a rotated rect. Useful to draw the rotated rectangle. The function finds the four vertices of a rotated rectangle.This function is useful to draw the rectangle.In C++, instead of using this function, you can directly use RotatedRect::points method. Please visit the @ref tutorial_bounding_rotated_ellipses "tutorial on Creating Bounding rotated boxes and ellipses for contours" for more information.

Finds the four vertices of a rotated rect. Useful to draw the rotated rectangle. The function finds the four vertices of a rotated rectangle.This function is useful to draw the rectangle.In C++, instead of using this function, you can directly use RotatedRect::points method. Please visit the @ref tutorial_bounding_rotated_ellipses "tutorial on Creating Bounding rotated boxes and ellipses for contours" for more information.

Constructs a pyramid which can be used as input for calcOpticalFlowPyrLK

Constructs a pyramid which can be used as input for calcOpticalFlowPyrLK

computes the joint dense histogram for a set of images.

computes covariation matrix of a set of samples

computes covariation matrix of a set of samples

computes the joint dense histogram for a set of images.

computes the joint dense histogram for a set of images.

Computes a dense optical flow using the Gunnar Farneback's algorithm.

computes sparse optical flow using multi-scale Lucas-Kanade algorithm

computes sparse optical flow using multi-scale Lucas-Kanade algorithm

finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.

finds intrinsic and extrinsic camera parameters from several fews of a known calibration pattern.

computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.

computes several useful camera characteristics from the camera matrix, camera frame resolution and the physical sensor size.

Finds an object center, size, and orientation.

Finds edges in an image using the Canny algorithm with custom image gradient.

Finds edges in an image using Canny algorithm.

Calculates the magnitude and angle of 2D vectors.

Checks whether the image contains chessboard of the specific size or not.

Returns true if the specified feature is supported by the host hardware. The function returns true if the host hardware supports the specified feature.When user calls setUseOptimized(false), the subsequent calls to checkHardwareSupport() will return false until setUseOptimized(true) is called.This way user can dynamically switch on and off the optimized code in OpenCV.

checks that each matrix element is within the specified range.

checks that each matrix element is within the specified range.

Draws a circle

Draws a circle

Clips the line against the image rectangle

Clips the line against the image rectangle

Given an original color image, two differently colored versions of this image can be mixed seamlessly. Multiplication factor is between 0.5 to 2.5.

Performs the per-element comparison of two arrays or an array and scalar value.

compares two histograms stored in dense arrays

extends the symmetrical matrix from the lower half or from the upper half

composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments

composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments

composes 2 [R|t] transformations together. Also computes the derivatives of the result w.r.t the arguments

For points in an image of a stereo pair, computes the corresponding epilines in the other image.

For points in an image of a stereo pair, computes the corresponding epilines in the other image.

For points in an image of a stereo pair, computes the corresponding epilines in the other image.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

Computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels[0, N - 1] where 0 represents the background label.ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.ccltype specifies the connected components labeling algorithm to use, currently Grana (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes for details.Note that SAUF algorithm forces a row major ordering of labels while BBDT does not. This function uses parallel version of both Grana and Wu's algorithms if at least one allowed parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

computes the connected components labeled image of boolean image. image with 4 or 8 way connectivity - returns N, the total number of labels [0, N-1] where 0 represents the background label. ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.

computes the connected components labeled image of boolean image and also produces a statistics output for each label. image with 4 or 8 way connectivity - returns N, the total number of labels[0, N - 1] where 0 represents the background label.ltype specifies the output label image type, an important consideration based on the total number of labels or alternatively the total number of pixels in the source image.ccltype specifies the connected components labeling algorithm to use, currently Grana's (BBDT) and Wu's (SAUF) algorithms are supported, see the #ConnectedComponentsAlgorithmsTypes for details.Note that SAUF algorithm forces a row major ordering of labels while BBDT does not. This function uses parallel version of both Grana and Wu's algorithms (statistics included) if at least one allowed parallel framework is enabled and if the rows of the image are at least twice the number returned by #getNumberOfCPUs.

Calculates the contour area

Calculates the contour area

Calculates the contour area

Converts an array to half precision floating number. This function converts FP32(single precision floating point) from/to FP16(half precision floating point). CV_16S format is used to represent FP16 data. There are two use modes(src -> dst) : CV_32F -> CV_16S and CV_16S -> CV_32F.The input array has to have type of CV_32F or CV_16S to represent the bit depth.If the input array is neither of them, the function will raise an error. The format of half precision floating point is defined in IEEE 754-2008.

Converts image transformation maps from one representation to another.

converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))

converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))

converts point coordinates from homogeneous to normal pixel coordinates ((x,y,z)->(x/z, y/z))

Converts points to/from homogeneous coordinates.

converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))

converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))

converts point coordinates from normal pixel coordinates to homogeneous coordinates ((x,y)->(x,y,1))

Scales, computes absolute values and converts the result to 8-bit.

Computes convex hull for a set of 2D points.

Computes convex hull for a set of 2D points.

Computes convex hull for a set of 2D points.

Computes convex hull for a set of 2D points.

Computes convex hull for a set of 2D points.

Computes the contour convexity defects

Computes the contour convexity defects

Computes the contour convexity defects

Forms a border around the image

Copies the matrix to another one. When the operation mask is specified, if the Mat::create call shown above reallocates the matrix, the newly allocated matrix is initialized with all zeros before copying the data.

computes both eigenvalues and the eigenvectors of 2x2 derivative covariation matrix at each pixel. The output is stored as 6-channel matrix.

adjusts the corner locations with sub-pixel accuracy to maximize the certain cornerness criteria

Refines coordinates of corresponding points.

Refines coordinates of corresponding points.

computes the number of nonzero array elements

Creates a predefined CLAHE object

Computes a Hanning window coefficients in two dimensions.

Create Bilateral TV-L1 Super Resolution.

Create Bilateral TV-L1 Super Resolution.

Creates a trackbar and attaches it to the specified window. The function createTrackbar creates a trackbar(a slider or range control) with the specified name and range, assigns a variable value to be a position synchronized with the trackbar and specifies the callback function onChange to be called on the trackbar position change.The created trackbar is displayed in the specified window winName.

Creates a trackbar and attaches it to the specified window. The function createTrackbar creates a trackbar(a slider or range control) with the specified name and range, assigns a variable value to be a position synchronized with the trackbar and specifies the callback function onChange to be called on the trackbar position change.The created trackbar is displayed in the specified window winName.

computes cube root of the argument

Converts image from one color space to another

Converts an image from one color space to another where the source image is stored in two planes. This function only supports YUV420 to RGB conversion as of now.

Performs forward or inverse 1D or 2D Discrete Cosine Transformation

Transforms a color image to a grayscale image. It is a basic tool in digital printing, stylized black-and-white photograph rendering, and in many single channel image processing applications @cite CL12 .

Decompose a homography matrix to rotation(s), translation(s) and plane normal(s).

Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector

Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector

Decomposes the projection matrix into camera matrix and the rotation martix and the translation vector

main function for all demosaicing processes

Primal-dual algorithm is an algorithm for solving special types of variational problems (that is, finding a function to minimize some functional). As the image denoising, in particular, may be seen as the variational problem, primal-dual algorithm then can be used to perform denoising and this is exactly what is implemented.

Destroys all of the HighGUI windows.

Destroys the specified window.

This filter enhances the details of a particular image.

computes determinant of a square matrix

Performs a forward Discrete Fourier transform of 1D or 2D floating-point array.

Dilates an image by using a specific structuring element.

computes the distance transform map

Calculates the distance to the closest zero pixel for each pixel of the source image.

Performs per-element division of two arrays or a scalar by an array.

Performs per-element division of two arrays or a scalar by an array.

Renders the detected chessboard corners.

Renders the detected chessboard corners.

draws contours in the image

draws contours in the image

Draw axes of the world/object coordinate system from pose estimation.

Draw keypoints.

Draws a marker on a predefined position in an image. The function cv::drawMarker draws a marker on a given position in the image.For the moment several marker types are supported, see #MarkerTypes for more information.

Draws the found matches of keypoints from two images.

Draws the found matches of keypoints from two images.

Filtering is the fundamental operation in image and video processing. Edge-preserving smoothing filters are used in many different applications @cite EM11 .

Computes eigenvalues and eigenvectors of a symmetric matrix.

Calculates eigenvalues and eigenvectors of a non-symmetric matrix (real eigenvalues only).

Draws simple or thick elliptic arc or fills ellipse sector

Draws simple or thick elliptic arc or fills ellipse sector

Approximates an elliptic arc with a polyline. The function ellipse2Poly computes the vertices of a polyline that approximates the specified elliptic arc. It is used by cv::ellipse.

Approximates an elliptic arc with a polyline. The function ellipse2Poly computes the vertices of a polyline that approximates the specified elliptic arc. It is used by cv::ellipse.

Computes the "minimal work" distance between two weighted point configurations. The function computes the earth mover distance and/or a lower boundary of the distance between the two weighted point configurations.One of the applications described in @cite RubnerSept98, @cite Rubner2000 is multi-dimensional histogram comparison for image retrieval.EMD is a transportation problem that is solved using some modification of a simplex algorithm, thus the complexity is exponential in the worst case, though, on average it is much faster.In the case of a real metric the lower boundary can be calculated even faster (using linear-time algorithm) and it can be used to determine roughly whether the two signatures are far enough so that they cannot relate to the same object.

Computes the "minimal work" distance between two weighted point configurations. The function computes the earth mover distance and/or a lower boundary of the distance between the two weighted point configurations.One of the applications described in @cite RubnerSept98, @cite Rubner2000 is multi-dimensional histogram comparison for image retrieval.EMD is a transportation problem that is solved using some modification of a simplex algorithm, thus the complexity is exponential in the worst case, though, on average it is much faster.In the case of a real metric the lower boundary can be calculated even faster (using linear-time algorithm) and it can be used to determine roughly whether the two signatures are far enough so that they cannot relate to the same object.

Computes the "minimal work" distance between two weighted point configurations. The function computes the earth mover distance and/or a lower boundary of the distance between the two weighted point configurations.One of the applications described in @cite RubnerSept98, @cite Rubner2000 is multi-dimensional histogram comparison for image retrieval.EMD is a transportation problem that is solved using some modification of a simplex algorithm, thus the complexity is exponential in the worst case, though, on average it is much faster.In the case of a real metric the lower boundary can be calculated even faster (using linear-time algorithm) and it can be used to determine roughly whether the two signatures are far enough so that they cannot relate to the same object.

normalizes the grayscale image brightness and contrast by normalizing its histogram

Erodes an image by using a specific structuring element.

Computes an optimal affine transformation between two 2D point sets.

Computes an optimal affine transformation between two 3D point sets.

Computes an optimal limited affine transformation with 4 degrees of freedom between two 2D point sets.

computes exponent of each matrix element (dst = e**src)

extracts a single channel from src (coi is 0-based index)

Detects corners using the FAST algorithm

Detects corners using the FAST algorithm

computes the angle in degrees (0..360) of the vector (x,y)

Perform image denoising using Non-local Means Denoising algorithm with several computational optimizations. Noise expected to be a gaussian white noise

Modification of fastNlMeansDenoising function for colored images

Modification of fastNlMeansDenoisingMulti function for colored images sequences

Modification of fastNlMeansDenoisingMulti function for colored images sequences

Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces.

Modification of fastNlMeansDenoising function for images sequence where consequtive images have been captured in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces.

Fills a convex polygon.

Fills a convex polygon.

Fills the area bounded by one or more polygons

Fills the area bounded by one or more polygons

Convolves an image with the kernel

Filters homography decompositions based on additional information.

filters off speckles (small regions of incorrectly computed disparity)

finds subpixel-accurate positions of the chessboard corners

finds subpixel-accurate positions of the chessboard corners

Finds the positions of internal corners of the chessboard.

Finds the positions of internal corners of the chessboard.

Finds the positions of internal corners of the chessboard using a sector based approach.

Finds the positions of internal corners of the chessboard using a sector based approach.

Finds centers in the grid of circles.

Finds centers in the grid of circles.

Finds contours in a binary image.

Finds contours in a binary image.

Finds contours in a binary image.

Finds contours in a binary image.

Calculates an essential matrix from the corresponding points in two images.

Calculates an essential matrix from the corresponding points in two images.

Calculates a fundamental matrix from the corresponding points in two images.

Calculates a fundamental matrix from the corresponding points in two images.

computes the best-fit perspective transformation mapping srcPoints to dstPoints.

computes the best-fit perspective transformation mapping srcPoints to dstPoints.

returns the list of locations of non-zero pixels

Fits ellipse to the set of 2D points.

Fits ellipse to the set of 2D points.

Fits ellipse to the set of 2D points.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Approximate Mean Square(AMS) proposed by @cite Taubin1991 is used.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Approximate Mean Square(AMS) proposed by @cite Taubin1991 is used.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Approximate Mean Square(AMS) proposed by @cite Taubin1991 is used.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Direct least square(Direct) method by @cite Fitzgibbon1999 is used.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Direct least square(Direct) method by @cite Fitzgibbon1999 is used.

Fits an ellipse around a set of 2D points. The function calculates the ellipse that fits a set of 2D points. It returns the rotated rectangle in which the ellipse is inscribed. The Direct least square(Direct) method by @cite Fitzgibbon1999 is used.

Fits line to the set of 2D points using M-estimator algorithm

Fits line to the set of 2D points using M-estimator algorithm

Fits line to the set of 3D points using M-estimator algorithm

Fits line to the set of 3D points using M-estimator algorithm

Fits line to the set of 2D points using M-estimator algorithm

reverses the order of the rows, columns or both in a matrix

Fills a connected component with the given color.

Fills a connected component with the given color.

Fills a connected component with the given color.

Fills a connected component with the given color.

Blurs an image using a Gaussian filter.

implements generalized matrix product algorithm GEMM from BLAS

Calculates an affine transform from three pairs of the corresponding points. The function calculates the 2×3 matrix of an affine transform.

Calculates an affine transform from three pairs of the corresponding points. The function calculates the 2×3 matrix of an affine transform.

Returns full configuration time cmake output. Returned value is raw cmake output including version control system revision, compiler version, compiler flags, enabled modules and third party libraries, etc.Output format depends on target architecture.

Returns list of CPU features enabled during compilation. Returned value is a string containing space separated list of CPU features with following markers: - no markers - baseline features - prefix `*` - features enabled in dispatcher - suffix `?` - features enabled but not available in HW

Returns the number of CPU ticks. The function returns the current number of CPU ticks on some architectures(such as x86, x64, PowerPC). On other platforms the function is equivalent to getTickCount.It can also be used for very accurate time measurements, as well as for RNG initialization.Note that in case of multi-CPU systems a thread, from which getCPUTickCount is called, can be suspended and resumed at another CPU with its own counter. So, theoretically (and practically) the subsequent calls to the function do not necessary return the monotonously increasing values. Also, since a modern CPU varies the CPU frequency depending on the load, the number of CPU clocks spent in some code cannot be directly converted to time units.Therefore, getTickCount is generally a preferable solution for measuringexecution time.

returns the default new camera matrix (by default it is the same as cameraMatrix unless centerPricipalPoint=true)

Returns filter coefficients for computing spatial image derivatives.

Calculates the font-specific size to use to achieve a given height in pixels.

Returns Gabor filter coefficients.

Returns Gaussian filter coefficients.

Returns feature name by ID. Returns empty string if feature is not defined

Gets the mouse-wheel motion delta, when handling mouse-wheel events cv::EVENT_MOUSEWHEEL and cv::EVENT_MOUSEHWHEEL. For regular mice with a scroll-wheel, delta will be a multiple of 120. The value 120 corresponds to a one notch rotation of the wheel or the threshold for action to be taken and one such action should occur for each delta.Some high-precision mice with higher-resolution freely-rotating wheels may generate smaller values. For cv::EVENT_MOUSEWHEEL positive and negative values mean forward and backward scrolling, respectively.For cv::EVENT_MOUSEHWHEEL, where available, positive and negative values mean right and left scrolling, respectively.

Returns the number of logical CPUs available for the process.

Returns the number of threads used by OpenCV for parallel regions. Always returns 1 if OpenCV is built without threading support. The exact meaning of return value depends on the threading framework used by OpenCV library: - `TBB` - The number of threads, that OpenCV will try to use for parallel regions. If there is any tbb::thread_scheduler_init in user code conflicting with OpenCV, then function returns default number of threads used by TBB library. - `OpenMP` - An upper bound on the number of threads that could be used to form a new team. - `Concurrency` - The number of threads, that OpenCV will try to use for parallel regions. - `GCD` - Unsupported; returns the GCD thread pool limit(512) for compatibility. - `C=` - The number of threads, that OpenCV will try to use for parallel regions, if before called setNumThreads with threads > 0, otherwise returns the number of logical CPUs, available for the process.

Returns the optimal DFT size for a given vector size.

Returns the new camera matrix based on the free scaling parameter.

Returns the new camera matrix based on the free scaling parameter.

Calculates a perspective transform from four pairs of the corresponding points. The function calculates the 3×3 matrix of a perspective transform.

Calculates a perspective transform from four pairs of the corresponding points. The function calculates the 3×3 matrix of a perspective transform.

Retrieves a pixel rectangle from an image with sub-pixel accuracy.

Calculates an affine matrix of 2D rotation.

Returns a structuring element of the specified size and shape for morphological operations. The function constructs and returns the structuring element that can be further passed to erode, dilate or morphologyEx.But you can also construct an arbitrary binary mask yourself and use it as the structuring element.

Returns a structuring element of the specified size and shape for morphological operations. The function constructs and returns the structuring element that can be further passed to erode, dilate or morphologyEx.But you can also construct an arbitrary binary mask yourself and use it as the structuring element.

returns bounding box of the text string

Returns the thread-local Random number generator

Returns the index of the currently executed thread within the current parallel region. Always returns 0 if called outside of parallel region. @deprecated Current implementation doesn't corresponding to this documentation. The exact meaning of the return value depends on the threading framework used by OpenCV library: - `TBB` - Unsupported with current 4.1 TBB release.Maybe will be supported in future. - `OpenMP` - The thread number, within the current team, of the calling thread. - `Concurrency` - An ID for the virtual processor that the current context is executing on(0 for master thread and unique number for others, but not necessary 1,2,3,...). - `GCD` - System calling thread's ID. Never returns 0 inside parallel region. - `C=` - The index of the current parallel task.

Returns the number of ticks. The function returns the number of ticks after the certain event (for example, when the machine was turned on). It can be used to initialize RNG or to measure a function execution time by reading the tick count before and after the function call.

Returns the number of ticks per second. The function returns the number of ticks per second.That is, the following code computes the execution time in seconds:

Returns the trackbar position.

computes valid disparity ROI from the valid ROIs of the rectified images (that are returned by cv::stereoRectify())

Returns major library version

Returns minor library version

Returns revision field of the library version

Returns library version string. For example "3.4.1-dev".

Provides rectangle of image in the window. The function getWindowImageRect returns the client screen coordinates, width and height of the image rendering area.

Provides parameters of a window.

finds the strong enough corners where the cornerMinEigenVal() or cornerHarris() report the local maxima

Segments the image using GrabCut algorithm

Groups the object candidate rectangles.

Groups the object candidate rectangles.

Groups the object candidate rectangles.

Groups the object candidate rectangles.

Applies horizontal concatenation to given matrices.

Applies horizontal concatenation to given matrices.

Finds circles in a grayscale image using a Hough transform.

Finds lines in a binary image using standard Hough transform.

Finds lines segments in a binary image using probabilistic Hough transform.

Finds lines in a set of points using the standard Hough transform. The function finds lines in a set of points using a modification of the Hough transform.

Performs inverse 1D or 2D Discrete Cosine Transformation

Performs an inverse Discrete Fourier transform of 1D or 2D floating-point array.

Applying an appropriate non-linear transformation to the gradient field inside the selection and then integrating back with a Poisson solver, modifies locally the apparent illumination of an image.

Reads image from the specified buffer in memory.

Reads image from the specified buffer in memory.

Reads image from the specified buffer in memory.

Compresses the image and stores it in the memory buffer

Compresses the image and stores it in the memory buffer

Loads an image from a file.

Loads a multi-page image from a file.

Displays the image in the specified window

Saves an image to a specified file.

Saves an image to a specified file.

Saves an image to a specified file.

Saves an image to a specified file.

initializes camera matrix from a few 3D points and the corresponding projections.

initializes camera matrix from a few 3D points and the corresponding projections.

set up P/Invoke settings only for .NET 2.0/3.0/3.5

initializes maps for cv::remap() to correct lens distortion and optionally rectify the image

initializes maps for cv::remap() for wide-angle

Restores the selected region in an image using the region neighborhood.

set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb)

set mask elements for those array elements which are within the element-specific bounding box (dst = lowerb <= src && src < upperb)

inserts a single channel to dst (coi is 0-based index)

Calculates the integral of an image. The function calculates one or more integral images for the source image.

Calculates the integral of an image. The function calculates one or more integral images for the source image.

Calculates the integral of an image. The function calculates one or more integral images for the source image.

finds intersection of two convex polygons

finds intersection of two convex polygons

finds intersection of two convex polygons

computes inverse or pseudo-inverse matrix

Inverts an affine transformation.

returns true if the contour is convex. Does not support contours with self-intersection

returns true if the contour is convex. Does not support contours with self-intersection

returns true if the contour is convex. D oes not support contours with self-intersection

Finds centers of clusters and groups input samples around the clusters.

Calculates the Laplacian of an image

Draws a line segment connecting two points

Draws a line segment connecting two points

Remaps an image to polar space.

computes natural logarithm of absolute value of each matrix element: dst = log(abs(src))

Remaps an image to log-polar space.

transforms array of numbers using a lookup table: dst(i)=lut(src(i))

transforms array of numbers using a lookup table: dst(i)=lut(src(i))

Calculates the magnitude of 2D vectors.

Calculates the Mahalanobis distance between two vectors.

Compares two shapes.

Compares two shapes.

Computes the proximity map for the raster template and the image where the template is searched for

computes derivatives of the matrix product w.r.t each of the multiplied matrix coefficients

computes per-element maximum of two arrays (dst = max(src1, src2))

computes per-element maximum of two arrays (dst = max(src1, src2))

computes per-element maximum of array and scalar (dst = max(src1, src2))

computes mean value of selected array elements

Finds an object on a back projection image.

computes mean value and standard deviation of all or selected array elements

computes mean value and standard deviation of all or selected array elements

Smoothes image using median filter

makes multi-channel array out of several single-channel arrays

computes per-element minimum of two arrays (dst = min(src1, src2))

computes per-element minimum of two arrays (dst = min(src1, src2))

computes per-element minimum of array and scalar (dst = min(src1, src2))

Finds the minimum area rotated rectangle enclosing a 2D point set.

Finds the minimum area rotated rectangle enclosing a 2D point set.

Finds the minimum area rotated rectangle enclosing a 2D point set.

Finds the minimum area circle enclosing a 2D point set.

Finds the minimum area circle enclosing a 2D point set.

Finds the minimum area circle enclosing a 2D point set.

Finds a triangle of minimum area enclosing a 2D point set and returns its area.

Finds a triangle of minimum area enclosing a 2D point set and returns its area.

Finds a triangle of minimum area enclosing a 2D point set and returns its area.

finds global minimum and maximum array elements and returns their values and their locations

finds global minimum and maximum array elements and returns their values and their locations

finds global minimum and maximum array elements and returns their values and their locations

finds global minimum and maximum array elements and returns their values and their locations

finds global minimum and maximum array elements and returns their values and their locations

finds global minimum and maximum array elements and returns their values and their locations

copies selected channels from the input arrays to the selected channels of the output arrays

Calculates all of the moments up to the third order of a polygon or rasterized shape.

Calculates all of the moments up to the third order of a polygon or rasterized shape.

Calculates all of the moments up to the third order of a polygon or rasterized shape.

Calculates all of the moments up to the third order of a polygon or rasterized shape.

Calculates all of the moments up to the third order of a polygon or rasterized shape.

Default borderValue for Dilate/Erode

Performs advanced morphological transformations

Moves window to the specified position

Performs the per-element multiplication of two Fourier spectrums.

Calculates the per-element scaled product of two arrays

multiplies matrix by its transposition from the left or from the right

Creates a window.

Calculates absolute array norm, absolute difference norm, or relative difference norm.

computes norm of selected part of the difference between two arrays

scales and shifts array elements so that either the specified norm (alpha) or the minimum (alpha) and maximum (beta) array values get the specified values

Splits an element set into equivalency classes. Consider using GroupBy of Linq instead.

converts NaN's to the given number

Reconstructs vectors from their PC projections.

PCA of the supplied dataset.

PCA of the supplied dataset.

PCA of the supplied dataset.

PCA of the supplied dataset.

Projects vector(s) to the principal component subspace.

Pencil-like non-photorealistic line drawing

performs perspective transformation of each element of multi-channel input matrix

performs perspective transformation of each element of multi-channel input matrix

performs perspective transformation of each element of multi-channel input matrix

performs perspective transformation of each element of multi-channel input matrix

performs perspective transformation of each element of multi-channel input matrix

Calculates the rotation angle of 2D vectors.

The function is used to detect translational shifts that occur between two images. The operation takes advantage of the Fourier shift theorem for detecting the translational shift in the frequency domain.It can be used for fast image registration as well as motion estimation. For more information please see http://en.wikipedia.org/wiki/Phase_correlation. Calculates the cross-power spectrum of two supplied source arrays. The arrays are padded if needed with getOptimalDFTSize.

Checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary

Checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary

Checks if the point is inside the contour. Optionally computes the signed distance from the point to the contour boundary.

Calculates x and y coordinates of 2D vectors from their magnitude and angle.

draws one or more polygonal curves

draws one or more polygonal curves

raises the input matrix elements to the specified power (b = a**power)

computes another complex cornerness criteria at each pixel

projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters

projects points from the model coordinate space to the image coordinates. Also computes derivatives of the image coordinates w.r.t the intrinsic and extrinsic camera parameters

Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric. This function calculates the Peak Signal-to-Noise Ratio(PSNR) image quality metric in decibels(dB), between two input arrays src1 and src2.The arrays must have the same type.

renders text string in the image

Blurs an image and downsamples it.

Performs initial step of meanshift segmentation of an image.

Upsamples an image and then blurs it.

fills array with normally-distributed random numbers with the specified mean and the standard deviation

fills array with normally-distributed random numbers with the specified mean and the standard deviation

shuffles the input array elements

shuffles the input array elements

fills array with uniformly-distributed random numbers from the range [low, high)

fills array with uniformly-distributed random numbers from the range [low, high)

Recover relative camera rotation and translation from an estimated essential matrix and the corresponding points in two images, using cheirality check. Returns the number of inliers which pass the check.

Recover relative camera rotation and translation from an estimated essential matrix and the corresponding points in two images, using cheirality check. Returns the number of inliers which pass the check.

Recover relative camera rotation and translation from an estimated essential matrix and the corresponding points in two images, using cheirality check. Returns the number of inliers which pass the check.

Draws simple, thick or filled rectangle

Draws simple, thick or filled rectangle

Draws simple, thick or filled rectangle

Draws simple, thick or filled rectangle

computes the rectification transformations for 3-head camera, where all the heads are on the same line.

transforms 2D matrix to 1D row or column vector by taking sum, minimum, maximum or mean value over all the rows

Applies a generic geometrical transformation to an image.

replicates the input matrix the specified number of times in the horizontal and/or vertical direction

replicates the input matrix the specified number of times in the horizontal and/or vertical direction

reprojects disparity image to 3D: (x,y,d)->(X,Y,Z) using the matrix Q returned by cv::stereoRectify

Resizes an image.

Resizes window to the specified size

Resizes window to the specified size

converts rotation matrix to rotation vector using Rodrigues transformation

converts rotation vector to rotation matrix using Rodrigues transformation

converts rotation vector to rotation matrix or vice versa using Rodrigues transformation

Rotates a 2D array in multiples of 90 degrees.

Finds out if there is any intersection between two rotated rectangles. If there is then the vertices of the interesecting region are returned as well. Below are some examples of intersection configurations. The hatched pattern indicates the intersecting region and the red vertices are returned by the function.

Finds out if there is any intersection between two rotated rectangles. If there is then the vertices of the interesecting region are returned as well. Below are some examples of intersection configurations. The hatched pattern indicates the intersecting region and the red vertices are returned by the function.

Computes RQ decomposition of 3x3 matrix

Computes RQ decomposition of 3x3 matrix

Computes RQ decomposition of 3x3 matrix

Calculates the Sampson Distance between two points.

Calculates the Sampson Distance between two points.

adds scaled array to another one (dst = alpha*src1 + src2)

Calculates the first x- or y- image derivative using Scharr operator

Image editing tasks concern either global changes (color/intensity corrections, filters, deformations) or local changes concerned to a selection. Here we are interested in achieving local changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless manner. The extent of the changes ranges from slight distortions to complete replacement by novel content @cite PM03 .

Selects ROI on the given image. Function creates a window and allows user to select a ROI using mouse. Controls: use `space` or `enter` to finish selection, use key `c` to cancel selection (function will return the zero cv::Rect).

Selects ROI on the given image. Function creates a window and allows user to select a ROI using mouse. Controls: use `space` or `enter` to finish selection, use key `c` to cancel selection (function will return the zero cv::Rect).

Selects ROIs on the given image. Function creates a window and allows user to select a ROIs using mouse. Controls: use `space` or `enter` to finish current selection and start a new one, use `esc` to terminate multiple ROI selection process.

Applies separable linear filter to an image

Sets/resets the break-on-error mode. When the break-on-error mode is set, the default error handler issues a hardware exception, which can make debugging more convenient.

initializes scaled identity matrix

Sets the callback function for mouse events occuring within the specified window.

OpenCV will try to set the number of threads for the next parallel region. If threads == 0, OpenCV will disable threading optimizations and run all it's functions sequentially.Passing threads < 0 will reset threads number to system default. This function must be called outside of parallel region. OpenCV will try to run its functions with specified threads number, but some behaviour differs from framework: - `TBB` - User-defined parallel constructions will run with the same threads number, if another is not specified.If later on user creates his own scheduler, OpenCV will use it. - `OpenMP` - No special defined behaviour. - `Concurrency` - If threads == 1, OpenCV will disable threading optimizations and run its functions sequentially. - `GCD` - Supports only values <= 0. - `C=` - No special defined behaviour.

Sets the thread-local Random number generator

Sets the trackbar maximum position. The function sets the maximum position of the specified trackbar in the specified window.

Sets the trackbar minimum position. The function sets the minimum position of the specified trackbar in the specified window.

Sets the trackbar position.

Turns on/off available optimization. The function turns on or off the optimized code in OpenCV. Some optimization can not be enabled or disabled, but, for example, most of SSE code in OpenCV can be temporarily turned on or off this way.

Changes parameters of a window dynamically.

Updates window title

Calculates the first, second, third or mixed image derivatives using an extended Sobel operator

solves linear system or a least-square problem

finds real roots of a cubic polynomial

Solve given (non-integer) linear programming problem using the Simplex Algorithm (Simplex Method).

Finds an object pose from 3D-2D point correspondences.

Finds an object pose from 3D-2D point correspondences.

computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.

computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.

computes the camera pose from a few 3D points and the corresponding projections. The outliers are possible.

finds real and complex roots of a polynomial

sorts independently each matrix row or each matrix column

sorts independently each matrix row or each matrix column

Calculates the first order image derivative in both x and y using a Sobel operator

Copies each plane of a multi-channel array to a dedicated array

Copies each plane of a multi-channel array to a dedicated array

Calculates the normalized sum of squares of the pixel values overlapping the filter. For every pixel f(x, y) in the source image, the function calculates the sum of squares of those neighboring pixel values which overlap the filter placed over the pixel f(x, y). The unnormalized square box filter can be useful in computing local image statistics such as the the local variance and standard deviation around the neighborhood of a pixel.

computes square root of each matrix element (dst = src**0.5)

finds intrinsic and extrinsic parameters of a stereo camera

finds intrinsic and extrinsic parameters of a stereo camera

computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters

computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters

computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters

computes the rectification transformation for a stereo camera from its intrinsic and extrinsic parameters

computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)

computes the rectification transformation for an uncalibrated stereo camera (zero distortion is assumed)

Stylization aims to produce digital imagery with a wide variety of effects not focused on photorealism. Edge-aware filters are ideal for stylization, as they can abstract regions of low contrast while preserving, or enhancing, high-contrast features.

Calculates per-element difference between two arrays or array and a scalar

Calculates per-element difference between two arrays or array and a scalar

Calculates per-element difference between two arrays or array and a scalar

computes sum of array elements

performs back substitution for the previously computed SVD

decomposes matrix and stores the results to user-provided matrices

By retaining only the gradients at edge locations, before integrating with the Poisson solver, one washes out the texture of the selected region, giving its contents a flat aspect. Here Canny Edge Detector is used.

Applies a fixed-level threshold to each array element.

computes trace of a matrix

performs affine transformation of each element of multi-channel input matrix

transposes the matrix

Reconstructs points by triangulation.

Reconstructs points by triangulation.

corrects lens distortion for the given camera matrix and distortion coefficients

Computes the ideal point coordinates from the observed point coordinates.

Computes the ideal point coordinates from the observed point coordinates.

Returns the current optimization status. The function returns the current optimization status, which is controlled by cv::setUseOptimized().

validates disparity using the left-right check. The matrix "cost" should be computed by the stereo correspondence algorithm

Applies vertical concatenation to given matrices.

Applies vertical concatenation to given matrices.

Waits for a pressed key.

Waits for a pressed key. Similar to #waitKey, but returns full key code. Key code is implementation specific and depends on used backend: QT/GTK/Win32/etc

Applies an affine transformation to an image.

Applies a perspective transformation to an image.

Applies a perspective transformation to an image.

Remaps an image to polar or semilog-polar coordinates space.

Performs a marker-based image segmentation using the watershed algorithm.