_d      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                                  ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~                                                                                                                                                                   ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I JKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!""""""""""""""""########$$$$$$$$$$$%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&''''''''''''()))))))))) ) ) ) ) )))))))****++++++++ +!+"+#+$+%+&+'+(+)+*,+,,---.-/-0-1-2-3-4-5-6-7-8-9-:-;-<-=->-?-@-A-B-C-D-E-F-G-H-I-J-K-L-M-N-O-P-Q-R-S-T-U-V-W-X-Y-Z-[-\-]-^-_-`-a-b-c-9 Safe-InferedStream of monadic values Attaching side effects Repeating stream .Create a stream by iterating a monadic action )Pure and monadic left fold over a stream Merge two (time)streams NDrop elements from the stream. Due to stream structure, this operation cannot O fail gracefully when dropping more elements than what is found in the stream dMap over a stream %  !"ed#  !"#  !"   !"ed Safe-Infered#+Group list into indevidual pairs: [1,2,3,4] => [(1,2),(3,4)]. + Works only with even number of elements $Undo pairs function &Group list into pairs: [1,2,3] => [(1,2),(2,3)].  Works with non null lists 'Undo pairs1 function ?#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`a?#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`a?#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`a?#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`a Safe-Inferedbcdefghibcdefghibcdefghibcdefghi. Safe-Infered)fghijklmnopqrstuvwxyz{|}~(fghijklmnopqrstuvwxyz{|}~f ghijklmnopqrstuvwxyz{|}~ Safe-Inferedjjjj Safe-Inferedklklklkl Safe-Inferedmnopmnopmnopmnop Safe-Infered$Create rectangle around point (x,y) 7Return rectangle r2 in coordinate system defined by r1 1Return a point in coordinates of given rectangle :Adjust the size of the rectangle to be divisible by 2^n. !Create a tiling of a rectangles. Scale a rectangle 'qrstuvwxyz{|}~%qrstuvwxyz{|}~%qrstuvwxyz{|}~&qrstuvwxyz{|}~ Safe-Infered   Safe-InferedHu invariants spatial moments central moments  m00 != 0 ? 1/ sqrt(m00) : 0D<Convert a CvSeq object into list of its contents. Note that Q since CvSeq can be approximately anything, including a crazy man from the moon, 3 this is pretty unsafe and you must make sure that a is actually the element W in the seq, and the seq is something that remotely represents a sequence of elements. /Spatial and central moments /      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~89:;<=>?@AB,-*+()&'$% !"#     7536C42DEbFGHUIVJWKXLYMZN[Oc\Pd]Qe^Rf_S`Taghijklmnopsqtruvwxyz{|}~1/0.      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~/ Safe-Infered,* 0 Safe-Infered1 Safe-Infered  2 Safe-Infered     Safe-InferedClass for images that exist. Create an image from size ATypeclass for elements with a size, such as images and matrices. PTypeclass for CV items that can be read from file. Mainly images at this point. The type for Images rType family for expressing which channels a colorspace contains. This needs to be fixed wrt. the BGR color space. Single channel grayscale image "Remove typing info from an image PPerform (a destructive) inplace map of the image. This should be wrapped inside ! withClone or an image operation Allocate a new empty image RAllocate a new image that of the same size and type as the exemplar image given. 3Tile images by overlapping them on a black canvas.  Blit image2 onto image1. [ This uses an alpha channel bitmap for determining the regions where the image should be blended with  the base image.  Create a copy of an image UCreate a montage form given images (u,v) determines the layout and space the spacing Y between images. Images are assumed to be the same size (determined by the first image)            !"#$%&'()*+,-.Y     Y     u           !"#$%&'()*+,-.  Safe-InferedZA wrapper for allowing functor and applicative instances for non-polymorphic image types.  &Re-arrange pixel positions and values !IConvert image to a function, which returns pixel values in the domain of  the image and zero elsewhere #(Convert a pixelwise construct to image. $(Convert a pixelwise construct to image. (=Convert a function into construct into a Pixelwise construct *Shorthand for `a  $ fromImage b` +Shorthand for `a  * fromImage b`  !"#$%&'()*+/012345 !"#$%&'()*+"($# %'&)!*+ !"#$%&'()*+/012345  Safe-Infered12Copy the contents of a CArray into CV.Image type. 22Copy the contents of a CArray into CV.Image type. 3Copy CArray of floats to image 4#Copy D32 grayscale image to CArray 5(Copy the real part of an array to image 6/Copy the contents of a CV.Image into a CArray. 7:Copy the contents of CV.Image into a pre-existing CArray. 8.Copy image as a real part of a complex CArray ,-./012345678 ,-./012345678 21634587/0-., ,-./0123456783 Safe-Infered66  Safe-Infered =+Create an empty matrix of given dimensions >Create an identity matrix ?ITranspose a matrix. Does not do complex conjugation for complex matrices @<Convert a rotation vector to a rotation matrix (1x3 -> 3x3) A Ordinary matrix multiplication C(Generate a matrix from a index function E1Convert a matrix to flat list (row major order) F3Convert matrix to rows represented as nested lists G3Convert matrix to cols represented as nested lists HGet an element of the matrix IWrite an element to a matrix 9:;<=>?@ABCDEFGHI789:;<=>?@ABC9:;<=>?@ABCDEFGHI9:;<=CDEFGHIB?A@>9:;<=>?@ABCDEFGHI789:;<=>?@ABC4 Safe-InferedDEFGHIJKLMNOPQRSDEFGHIJKLMNOPQRSDEFGHIJKLMNOPQRS Safe-InferedJaFlags for the chessboard corner detector. See opencv documentation for cvFindChessboardCorners. O"Default flags for finding corners P:Find the inner corners of a chessboard in a given image. QZGiven an estimate of chessboard corners, provide a subpixel estimation of actual corners. R/Draw the found chessboard corners to an image SSee opencv function cvCalibrateCamera2. This function takes a list of world-screen coordinate pairs acquired with find-chessboard corners  and attempts to find the camera parameters for the system. It returns the fitting error, the camera matrix, list of distortion co-efficients C and rotation and translation vectors for each coordinate pair. JKLMNOPQRSTU JKLMNOPQRS JNMLKOPQRSJNMLKOPQRSTU Safe-InferedVIImageOperation is a name for unary operators that mutate images inplace. XCompose two image operations YAn unit operation for compose Z,Apply image operation to a Copy of an image _RApply list of image operations to a Copy of an image. (Makes a single copy and is  faster than folding over (<#) bIterate an operation N times TUVWXYZ[\]^_`abcdefVTUVWXYZ[\]^_`abcdefVWXYZ[TU\]^_`abcdefTUVWXYZ[\]^_`abcdefV5 Safe-InferedWCVAPI(void) cvAvgSdv(  | const CvArr* arr,  | CvScalar* mean,  | CvScalar* std_dev, ( | const CvArr* mask CV_DEFAULT(NULL)  | ); 8Calculates mean and standard deviation of pixel values. XCVAPI(void) cvMinMaxLoc(  | const CvArr* arr,  | double* min_val,  | double* max_val, ( | CvPoint* min_loc CV_DEFAULT(NULL), ( | CvPoint* max_loc CV_DEFAULT(NULL), ( | const CvArr* mask CV_DEFAULT(NULL)  | ); 2Finds global minimum, maximum and their positions YCVAPI(void) cvPolarToCart(  | const CvArr* magnitude,  | const CvArr* angle,  | CvArr* x,  | CvArr* y, ( | int angle_in_degrees CV_DEFAULT(0)  | ); .Does polar->cartesian coordinates conversion. A Either of output components (magnitude or angle) is optional. 4 If magnitude is missing it is assumed to be all 1's ZCVAPI(void) cvMerge(  | const CvArr* src0,  | const CvArr* src1,  | const CvArr* src2,  | const CvArr* src3,  | CvArr* dst  |); L |Merges a set of single-channel arrays into the single multi-channel array " |or inserts one particular [color] plane to the array <[\]^_`abcdefgWhXiYjklZmnopqrstuvwxyz{|}~<[\]^_`abcdefgWhXiYjklZmnopqrstuvwxyz{|}~<[\]^_`abcdefgWhXiYjklZmnopqrstuvwxyz{|}~ Safe-Infered,g,Calculates the per-pixel sum of two images. h3Calculates the per-pixel difference of two images. i1Calculates the natural logarithm of every pixel. j+Calculates the square root of every pixel. k5Operation to limit image with another image; same as 67. l0Calculates the per-pixel product of two images. m1Calculates the per-pixel division of two images. n0Calculates the per-pixel minimum of two images. o0Calculates the per-pixel maximum of two images. p<Calculates the per-pixel absolute difference of two images. q$Calculates the atan of every pixel. r4Calculates the atan2 of pixel values in two images. sACalculates the absolute difference of every pixel to image mean.  See also 68. t9Logical inversion of image (ie. invert, but stay on [0..1] range;  multiply by -1 and add 1). u.Calculates the absolute value of every pixel. vGCalculates the (non-absolute) difference of every pixel to image mean.  See also 69. w6Subtracts a scalar from every pixel, scalar on right. x5Subtracts a scalar from every pixel, scalar on left. y$Multiplies every pixel by a scalar. zAdds a scalar to every pixel. {@Calculates the per-pixel minimum between an image and a scalar. |@Calculates the per-pixel maximum between an image and a scalar. }GCompares each pixel to a scalar, and produces a binary image where the 5 pixel value is less than the scalar. For example, (lessThan s I) has J white pixels where value of I is less than s. Notice that the order of ; operands is opposite to the intuitive interpretation of s `}` I. ~GCompares each pixel to a scalar, and produces a binary image where the 8 pixel value is greater than the scalar. For example, (moreThan s I) has M white pixels where value of I is greater than s. Notice that the order of ; operands is opposite to the intuitive interpretation of s `~` I. ICompares two images and produces a binary image that has white pixels in > those positions where the comparison is true. For example,  (less2Than A B)9 has white pixels where value of A is less than value of J B. Notice that these functions follow the intuitive order of operands,  unlike } and ~. ICompares two images and produces a binary image that has white pixels in > those positions where the comparison is true. For example,  (less2Than A B)9 has white pixels where value of A is less than value of J B. Notice that these functions follow the intuitive order of operands,  unlike } and ~. 3Calculates the average pixel value in whole image. GCalculates the average value for pixels that have non-zero mask value. 2Calculates the sum of pixel values in whole image B (notice that OpenCV automatically casts the result to double). ICalculates the average of multiple images by adding the pixel values and 6 dividing the resulting values by number of images. BCalculates the standard deviation of pixel values in whole image. JCalculates the standard deviation of values for pixels that have non-zero  mask value. IFinds the minimum and maximum pixel value in the image and the locations " where these values were found. 8Finds the minimum and maximum pixel value in the image. KCalculates the average and standard deviation of pixel values in the image  in one operation. 8Finds the minimum and maximum pixel value in the image. IFinds the minimum and maximum value for pixels with non-zero mask value. IUtility functions for getting the maximum or minimum pixel value of the  image; equal to snd . findMinMax and fst . findMinMax. IUtility functions for getting the maximum or minimum pixel value of the  image; equal to snd . findMinMax and fst . findMinMax. ]Render image of 2D gaussian curve with standard deviation of (stdX,stdY) to image size (w,h)  The origin/+center of curve is in center of the image. Produce white image with edgeW" amount of edges fading to black. KProduce image where pixel is coloured according to distance from the edge. 0Merge two images according to a mask. Result is R = A*m + B*(m-1). NGiven a distance map and a circle, return the biggest circle with radius less F than given in the distance map that fully covers the previous one. ,ghijklmnopqrstuvwxyz{|}~,ghijklmnopqrstuvwxyz{|}~,ghplmnorvsjiuqtzxwy{|}~k,ghijklmnopqrstuvwxyz{|}~ Safe-Infered CImage addition, subtraction, and multiplication operator; same as  6:, 6;, and 6<. CImage addition, subtraction, and multiplication operator; same as  6:, 6;, and 6<. CImage addition, subtraction, and multiplication operator; same as  6:, 6;, and 6<. $Image comparison operators; same as 6= and  6> . Example: A #< B# produces a binary image that has M white pixels in those positions where value of A is less than value of B. $Image comparison operators; same as 6= and  6> . Example: A #< B# produces a binary image that has M white pixels in those positions where value of A is less than value of B. MScalar multiplication, addition, and subtraction (scalar on left) operators;  same as 6?, 6@, and 6A. MScalar multiplication, addition, and subtraction (scalar on left) operators;  same as 6?, 6@, and 6A. MScalar multiplication, addition, and subtraction (scalar on left) operators;  same as 6?, 6@, and 6A. %Scalar comparison operators; same as 6B and  6C . Example: s |> I" produces a binary image that has J white pixels in those positions where the value of I is larger than s. A Notice that this is opposite to the intuitive interpretation. %Scalar comparison operators; same as 6B and  6C . Example: s |> I" produces a binary image that has J white pixels in those positions where the value of I is larger than s. A Notice that this is opposite to the intuitive interpretation. 7Scalar subtraction operator (scalar on right); same as 6D.     Safe-InferedOAdjust the image histogram to have fixed mean and standard deviation. This can 0 be used for simple light level normalization. NPerform logarithmic compression on the image. This will enhance dark features W and suppress bright features. Use this to visualize images with high dynamic range.  (FFT results, for example) 8Histogram stretch scales the image to fit the range [0,1] >Equalize contrast of the image. This is good for visualizing N images with backgrounds and foregrounds that are both bright or both dark. E Safe-InferedFMasks a connected component by filling it with white, and filling all  other pixels with black.   K void maskConnectedComponent(const IplImage *src, IplImage *mask, int id) KFills the connected component until the color difference gets large enough    CVAPI(void) cvFloodFill(  CvArr* image,  CvPoint seed_point,  CvScalar new_val, 0 CvScalar lo_diff CV_DEFAULT(cvScalarAll(0)), 0 CvScalar up_diff CV_DEFAULT(cvScalarAll(0)), + CvConnectedComp* comp CV_DEFAULT(NULL),  int flags CV_DEFAULT(4), ! CvArr* mask CV_DEFAULT(NULL)); JLabels connected components by flood filling each with a different value.   @ void fillConnectedComponents(const IplImage* img, int *count) /Applies adaptive threshold to grayscale image. @ The two parameters for methods CV_ADAPTIVE_THRESH_MEAN_C and & CV_ADAPTIVE_THRESH_GAUSSIAN_C are: % neighborhood size (3, 5, 7 etc.), B and a constant subtracted from mean (...,-3,-2,-1,0,1,2,3,...)   $ CVAPI(void) cvAdaptiveThreshold(  const CvArr* src,  CvArr* dst,  double max_value, > int adaptive_method CV_DEFAULT(CV_ADAPTIVE_THRESH_MEAN_C), 4 int threshold_type CV_DEFAULT(CV_THRESH_BINARY), ! int block_size CV_DEFAULT(3),  double param1 CV_DEFAULT(5)); 5Threshold for each pixel is the mean calculated from  block_size  neighborhood, minus param1. 2Applies fixed-level threshold to grayscale image. A This is a basic operation applied before retrieving contours.    CVAPI(double) cvThreshold(  const CvArr* src,  CvArr* dst,  double threshold,  double max_value,  int threshold_type); Calculates 7 Hu'<s invariants from precalculated spatial and central moments    CVAPI(void) cvGetHuMoments(  CvMoments* moments,  CvHuMoments* hu_moments ); 7Retrieve particular normalized central moment (eta_xy)   / CVAPI(double) cvGetNormalizedCentralMoment(  CvMoments* moments,  int x_order,  int y_order ); +Retrieve particular central moment (mu_xy)   % CVAPI(double) cvGetCentralMoment(  CvMoments* moments,  int x_order,  int y_order ); *Retrieve particular spatial moment (m_xy)   % CVAPI(double) cvGetSpatialMoment(  CvMoments* moments,  int x_order,  int y_order ); ?Calculates all spatial and central moments up to the 3rd order    CVAPI(void) cvMoments(  const CvArr* arr,  CvMoments* moments,  int binary CV_DEFAULT(0)); +value = value > threshold ? max_value : 0 *value = value > threshold ? 0 : max_value .value = value > threshold ? threshold : value &value = value > threshold ? value : 0 &value = value > threshold ? 0 : value :Use Otsu algorithm to choose the optimal threshold value; > combine the flag with one of the above CV_THRESH_* values. : Note: when using this, the threshold value is ignored. "CV_THRESH_OTSU | CV_THRESH_BINARY !CV_THRESH_OTSU | CV_THRESH_TRUNC &CV_THRESH_OTSU | CV_THRESH_BINARY_INV "CV_THRESH_OTSU | CV_THRESH_TOZERO "CV_THRESH_OTSU | CV_THRESH_TOZERO >Threshold for each pixel is the gaussian mean calculated from  block_size  neighborhood, minus param1 BB= Safe-Infered ]A type for storing integral images. Integral image stores for every pixel the sum of pixels ` above and left of it. Such images are used for significantly accelerating the calculation of  area averages. %SUSAN adaptive smoothing filter, see  9http://users.fmrib.ox.ac.uk/~steve/susan/susan/susan.html IA selective average filter is an edge preserving noise reduction filter. ? It is a standard gaussian filter which ignores pixel values L that are more than a given threshold away from the filtered pixel value. cImage operation which applies gaussian or unifarm smoothing with a given window size to the image. cImage operation which applies gaussian or unifarm smoothing with a given window size to the image. ?Create a new image by applying gaussian, or uniform smoothing. ?Create a new image by applying gaussian, or uniform smoothing. ?Create a new image by applying gaussian, or uniform smoothing. Apply bilateral filtering 1Replace pixel values by the average of the row. 4Calculate the integral image from the given image. 1Filter the image with box shaped averaging mask. "Get an average of a given region.  Safe-InferedRGenerate a random small image, that might be constant, noisy or smoothly varying  Range of values is [0,1] Generate 10x10 constant image Generate 10x10 noisy image 'Generate 10x10 smoothly varying image *Generate a (10m x 10m) sized noisy image.  Safe-Infered FStructure that contains the opencv sequence holding the contour data. 6Count the number of connected components in the image VRemove all connected components that fall outside of given size range from the image. *Extract raw spatial moments of the image. JExtract central moments of the image. These are useful for describing the ) object shape for a classifier system. 1Extract normalized central moments of the image. HExtract Hu-moments of the image. These features are rotation invariant. :This function maps an opencv contour calculation over all  contours of the image. 7Extract contours of connected components of the image. The area of a contour.  Get the perimeter of a contour. )Get a list of the points in the contour. 4Operation for extracting Hu-moments from a contour  Safe-Infered  Safe-Infered Safe-InferedBTypeclass for images that support elementary drawing operations. PType of the pixel, i.e. Float for a grayscale image and 3-tuple for RGB image. WPut text of certain color to given coordinates. Good size seems to be around 0.5-1.5. !Draw a line between two points. Draw a Circle *Draw a Rectangle by supplying two corners Draw a filled polygon (Is the shape filled or just a boundary? !Flood fill a region of the image Apply rectOp to an image Apply fillPolyOp to an image Draw a polyline Apply drawLinesOp to an image Draw C'CvBox2D Apply circleOp to an image Apply fillOp to an image  F Safe-Infered Safe-Infered&Aperture sizes for laplacian operator "Aperture sizes for sobel operator  XPerform Sobel filtering on image. First argument gives order of horizontal and vertical Y derivative estimates and second one is the aperture. This function can also calculate 8 Scharr filter with aperture specification of sScharr  Use Scharr mask instead 7Perform laplacian filtering of given aperture to image IPerform canny thresholding using two threshold values and given aperture  Works only on 8-bit images !SUSAN edge detection filter, see  9http://users.fmrib.ox.ac.uk/~steve/susan/susan/susan.html                      Safe-Infered'Parameters for SURF feature extraction Create parameters for getMSER. SThe function encapsulates all the parameters of the MSER extraction algorithm (see   >http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions Default parameters for getSURF 2Extract Speeded Up Robust Features from an image.  Delta )prune the area which bigger than maxArea *prune the area which smaller than minArea 1prune the area have similar size to its children *trace back to cut off mser with diversity < min_diversity %for color image, the evolution steps *the area threshold to cause re-initialize ignore too small margin  the aperture size for edge blur Method parameters. See  and  Input GrayScale image Optional Binary mask image  !"#  !"#  !"# !"# Safe-Infered*3Given a (1,n) or (n,1) matrix of points, calculate : (in the least squares sense) the best ellipse around the  points +Fit a line to set of points. ,3Fit a minimum area rectangle over a set of points -HCalculate the minimum axis-aligned bounding rectangle of given points. .7Calculate the minimum enclosing circle of a point set. /4Calculcate the clockwise convex hull of a point set 0*Calculate convexity defects of a contour. $%&'()*+,-./0 $%&'()*+,-./0 $%&'()*+,-./0$%&'()*+,-./0 Safe-Infered12345123451234512345 Safe-Infered6)Mask sizes accepted by distanceTransform Q<Since DCT is valid only for even sized images, we provide a ( function to crop images to even sizes. R"Perform Discrete Cosine Transform S*Perform Inverse Discrete Cosine Transform T%Mirror an image over a cardinal axis URotate img angle radians. V+Simulate a radial distortion over an image W-Scale image by one ratio on both of the axes X.Scale an image with different ratios for axes YScale an image to a given size ZYApply a perspective transform to the image. The transformation 3x3 matrix is supplied as  a row ordered, flat, list. [aFind a homography between two sets of points in. The resulting 3x3 matrix is returned as a list. \,Return a copy of an image with an even size ]+Return a copy of an image with an odd size ^Pad images to same size `BDownsize image by 50% efficiently. Image dimensions must be even. cACalculate the laplacian pyramid of an image up to the nth level. A Notice that the image size must be divisible by 2^n or opencv  will abort (TODO!) d.Reconstruct an image from a laplacian pyramid eEnlarge image so, that it's size is divisible by 2^n 26789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdef16789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdef1QRSBDCTU=A@?>VWXYZ[\]^_`abcde9<;:687fPONMLKJIHGFE'6879<;:=A@?>BDCEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdef Safe-Infered ghijklmnop ghijklmnop ghmnoplkji ghijklmnop Safe-Infered qrstuvwxyz{|} qrstuvwxyz{|} wxyzv{|}utsrq qrstuvwxyz{|}  Safe-InferedFGiven a set of images, such as the color channels of color image, and L a histogram with corresponding number of channels, replace the pixels of 5 the image with the likelihoods from the histogram FCalculate an opencv histogram object from set of images, each with it's  own number of bins. ~~~~! Safe-Infered" Safe-InferedG Safe-Infered# Safe-Infered $ Safe-Infered   % Safe-Infered    & Safe-Infered)Perform a black tophat filtering of size )Perform a white tophat filtering of size ' Safe-Infered    ( Safe-InferedgThis function merges two images based on given mask, the first image dominates on areas where the mask k is 1 and the second where the mask is 0. The merging should be relatively seamless and is controlled by  the levels` parameter, which adjusts the accuracy. Usually, decent results can be obtained with 4 pyramid  levels. [Note that the mask should contain a tiny blurred region between images for optimal result. ) Safe-InferedAPerform subpixel template matching using intensity interpolation                     * Safe-Infered6Convert an LBP histogram into rotation invariant form !The most basic 3x3 lbp operator *The larger radius basic 5x5 lbp operator QA variant of LBP which is weighted. This can be used to select only parts of the T image by using binary masks, or to give higher weight for some areas of the image. + Safe-Infered 7Method used for selecting the adaptive threshold value AThreshold using the gaussian weighted mean of pixel neighborhood :Threshold using the arithmetic mean of pixel neighborhood CThresholding behavior for values larger and smaller than threshold FValues larger than threshold are set to zero, smaller are not touched FValues larger than threshold are not touched, smaller are set to zero QValues larger than threshold are truncated to threshold, smaller are not touched =Values larger than threshold are set to zero, smaller to max  =Values larger than threshold are set to max, smaller to zero !GThresholds a grayscale image according to the selected type, using the  given threshold value. "DThresholds a grayscale image using the otsu method according to the L selected type. Threshold value is selected automatically, and only 8-bit  images are supported. #KApplies adaptive thresholding by selecting the optimal threshold value for J each pixel. The threshold is selected by calculating the arithmetic or O gaussian-weighted mean of a pixel neighborhood, and applying a bias term to  the obtained value.  !"#$%&'() !"#$%&'() !"#$%&'()  !"#$%&'()H Safe-Infered, Safe-Infered*+*+*+*+- Safe-Infered9,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abc8,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abc8GHSREFTQDUVWXYZ.CBA@?>=<;:9876543210/[\]^_`a,-bcPONMLKJI!,-.CBA@?>=<;:9876543210/DEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                                              ! ! 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" # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m  n o p q r s t [ u v w x y z{|}~:;<798AD?@CB=>      !"#$%&'()*+,-./0123456789:;<=>?@@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~~      ~          ;     !!!!!!!!!!!!!!!!!!!!!!!!!!!!!""""""""""""""""########$$$$$$$$$$$%%%%%%%%%%%&&&&&&&&&&&&&&&&&&&&'''''''''''' ( ) ) ) ))))))))))))))))))* *!*"*#+$+%+&+'+(+)+*+++,+-+.+/+0+1+2+3+4+5,6,7-8-9-:-;-<-=->-?-@-A-B-C-D-E-F-G-H-I-J-K-L-M-N-O-P-Q-Q-R-R-S-T-U-V-W-X-Y-Z-[-\-]-^-_-`-a-b-c-d-e-f-g-h-i-j-k-l-mno.p.p.q.r.s.t.u.v.w.x.y.z.{.|.}.~.........................                    ////////////////////////////////////////////00111111111111111111111111111111112222222222                         ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; <3= > ? @ A B C D E F G H I J4K4L4M4N4O4P4Q4R4S4T4U4V4W4X4Y4Z[\]5^5_5`5a5b5c5d5e5f5g5h5i5j5k5l5m5n5o5p5q5r5s5t5u5v5w5x5y5z5{5|5}5~555555555555555555555555555EEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEFFGGGGGGGGGGGGGGGGG#&))++HHHHHHHH- CV-0.3.5.4 Utils.Stream Utils.ListUtils.Function Utils.PointerUtils.DrawingClass Utils.PointUtils.RectangleUtils.GeometryClassCV.Bindings.TypesCV.Image CV.PixelwiseCV.Conversions CV.MatrixCV.Calibration CV.ImageOp CV.ImageMathCV.ImageMathOpCV.ColourUtils CV.Filters CV.ArbitraryCV.ConnectedComponents CV.OperationsCV.DFT CV.DrawingCV.Edges CV.Features CV.FittingCV.FunnyStatistics CV.TransformsCV.Gabor CV.HighGUI CV.HistogramCV.HoughTransform CV.Sampling CV.Iterators CV.CornersCV.LightBalance CV.Morphology CV.MarkingCV.MultiresolutionSplineCV.TemplateMatching CV.TexturesCV.Thresholding CV.TrackingCV.VideoCV.Bindings.MatrixCV.Bindings.FeaturesCV.Bindings.DrawingCV.Bindings.FittingsCV.Bindings.Error CV.BinaryCV.Bindings.CalibrateCV.Bindings.Core ImageMathminsubMean subMeanAbsaddsubmul less2Than more2ThanmulSaddSsubRSmoreThanlessThansubSCV.Bindings.ImgProcCV.DrawableInstancesCV.Bindings.IteratorsCV.Bindings.TrackingLRBRBLStreamValue Terminated sideEffect listToStreamrepeatSrepeatSMiterateSfoldSfoldSMtimevaluemergeTimeStreamsmergeTimeStreamsWith mergeManyWmergeSmergeEpushzipS sequenceSmapMSdropStakeS takeWhileSconsSpairS terminateOn runStream runStream_runLastrunLast1pairs fromPairsprop_pairsFromTopairs1 fromPairs1prop_pairsFromTo1creasecreaseMranksrankBy clusterBy groupItems lookupDefpairingsforEachforPairs replicateList concatZipNub histogrambinListzeroMeantakeNAccordingToselecttakeHalf splitToNParts prop_splitEq prop_splitLencount frequenciesnormalizeFrequenciesaverage smallestBy smallestBy'mediantakeTailstdDevcumulateschwartzianTransformsortVia 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C'CvSURFPointc'CvSURFPoint'ptc'CvSURFPoint'laplacianc'CvSURFPoint'sizec'CvSURFPoint'dirc'CvSURFPoint'hessianC'CvConvexityDefectc'CvConvexityDefect'startc'CvConvexityDefect'endc'CvConvexityDefect'depth_pointc'CvConvexityDefect'depth TermCriteriaITEREPSC'CvTermCriteriac'CvTermCriteria'typec'CvTermCriteria'max_iterc'CvTermCriteria'epsilon C'CvHuMomentsc'CvHuMoments'hu1c'CvHuMoments'hu2c'CvHuMoments'hu3c'CvHuMoments'hu4c'CvHuMoments'hu5c'CvHuMoments'hu6c'CvHuMoments'hu7 C'CvMomentsc'CvMoments'm00c'CvMoments'm10c'CvMoments'm01c'CvMoments'm20c'CvMoments'm11c'CvMoments'm02c'CvMoments'm30c'CvMoments'm21c'CvMoments'm12c'CvMoments'm03c'CvMoments'mu20c'CvMoments'mu11c'CvMoments'mu02c'CvMoments'mu30c'CvMoments'mu21c'CvMoments'mu12c'CvMoments'mu03c'CvMoments'inv_sqrt_m00 C'CvBox2Dc'CvBox2D'centerc'CvBox2D'sizec'CvBox2D'angleC'CvPoint2D32fc'CvPoint2D32f'xc'CvPoint2D32f'y C'CvPoint c'CvPoint'x 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p'CvRect'yp'CvRect'widthp'CvRect'heightp'CvScalar'val_0_p'CvScalar'val_1_p'CvScalar'val_2_p'CvScalar'val_3_p'CvSize'widthp'CvSize'heightp'CvSize2D32f'widthp'CvSize2D32f'heightp'CvConnectedComp'areap'CvConnectedComp'valuep'CvConnectedComp'rectp'CvConnectedComp'contour p'CvPoint'x p'CvPoint'yp'CvPoint2D32f'xp'CvPoint2D32f'ymkCvPoint2D32Fp'CvBox2D'centerp'CvBox2D'sizep'CvBox2D'anglep'CvMoments'm00p'CvMoments'm10p'CvMoments'm01p'CvMoments'm20p'CvMoments'm11p'CvMoments'm02p'CvMoments'm30p'CvMoments'm21p'CvMoments'm12p'CvMoments'm03p'CvMoments'mu20p'CvMoments'mu11p'CvMoments'mu02p'CvMoments'mu30p'CvMoments'mu21p'CvMoments'mu12p'CvMoments'mu03p'CvMoments'inv_sqrt_m00p'CvHuMoments'hu1p'CvHuMoments'hu2p'CvHuMoments'hu3p'CvHuMoments'hu4p'CvHuMoments'hu5p'CvHuMoments'hu6p'CvHuMoments'hu7p'CvTermCriteria'typep'CvTermCriteria'max_iterp'CvTermCriteria'epsilon toCvTCritc'CV_TERMCRIT_ITERc'CV_TERMCRIT_NUMBERc'CV_TERMCRIT_EPS withNewMemory c'CV_8UC1 c'CV_8UC2 c'CV_8UC3 c'CV_8UC4 c'CV_8SC1 c'CV_8SC2 c'CV_8SC3 c'CV_8SC4 c'CV_16UC1 c'CV_16UC2 c'CV_16UC3 c'CV_16UC4 c'CV_16SC1 c'CV_16SC2 c'CV_16SC3 c'CV_16SC4 c'CV_32SC1 c'CV_32SC2 c'CV_32SC3 c'CV_32SC4 c'CV_32FC1 c'CV_32FC2 c'CV_32FC3 c'CV_32FC4 c'CV_64FC1 c'CV_64FC2 c'CV_64FC3 c'CV_64FC4c'CV_CLOCKWISEc'CV_COUNTER_CLOCKWISEp'CvConvexityDefect'startp'CvConvexityDefect'endp'CvConvexityDefect'depth_pointp'CvConvexityDefect'depthp'CvSURFPoint'ptp'CvSURFPoint'laplacianp'CvSURFPoint'sizep'CvSURFPoint'dirp'CvSURFPoint'hessian CvExceptionSetPixelSPsetPixel ImageDepth CreateImagecreateGetPixelPgetPixelSizedSizegetSizeLoadable readFromFilecomposeTag BareImageImageSD64D32D8 ChannelOf LAB_ChannelLAB_BLAB_ALAB_LRGBALAB RGB_ChannelBlueGreenRedRGBDFT GrayScale ensure32FunS imageFPTR withImage withGenImagewithGenBareImage withBareImage creatingImagecreatingBareImageunImagergbrgbalabcomposeMultichannelImage loadImageloadColorImagergbToLab rgbToGray grayToRGBbgrToRgbrgbToBgrmapImageInplaceempty emptyCopy saveImagegetArea getRegion tileImagesblitblitM subPixelBlitsafeBlit blendBlit cloneImage withClonewithCloneValueunsafeImageTo32FunsafeImageTo8Bit getImageDepthgetImageChannels getImageInfosetROIresetROIsetCOI getChannel withIOROIwithROI getAllPixelsgetAllPixelsRowMajormontagesetCatch PixelwiseMkPsizeOfeltOfremapimageToFunction fromImage toImagePartoImage remapImage mapPixelsmapImage fromFunctionimageFromFunction<$$><+>acquireImageSlow8URGB'acquireImageSlowF'acquireImageSlow'unsafe8UC_RGBFromPtrunsafe8UC_BGRFromPtrcopy8UCArrayToImagecopyCArrayToImagecopyFCArrayToImagecopyImageToFCArraycopyComplexCArrayToImagecopyImageToCArraycopyImageToExistingCArraycopyImageToComplexCArrayExistsArgsMatrix emptyMatrixidentity transpose rodrigues2mxm withMatPtrfromListtoListtoRowstoColsgetput FindFlags FastCheck FilterQuadsNormalizeImageAdaptiveThresh defaultFlagsfindChessboardCornersrefineChessboardCornersdrawChessboardCornerscalibrateCamera2IOPImageOperationImgOp#>nonOp<# fromImageOp&#& unsafeOperaterunIOP<##operate operateOntimesdirectOpoperateInPlaceunsafeOperateOnoperateWithROIlogsqrt limitToOpdivmaxabsDiffatanatan2invertabsminSmaxS averageMasksum averageImages stdDeviationstdDeviationMask findMinMaxLoc imageMinMax imageAvgSdv findMinMaxfindMinMaxMaskmaxValueminValue gaussianImagefadedEdgeImage fadeToCenter maskedMergemaximalCoveringCircle#+#-#*#<|*|+-||>|<|-balancelogarithmicCompressionstretchHistogramequalizeHistogram IntegralImageHasMedianFilteringsusan selectiveAvggetCentralMomentgetAbsCentralMoment getMomentsecondMomentBinarizeOpsecondMomentBinarizesecondMomentAdaptiveBinarizeOpsecondMomentAdaptiveBinarize gaussianOpblurOpgaussianblurblurNS bilateral convolve2D convolve2DIverticalAverage integralImagehaarhaarAt smallImage constImage noisyImage smoothImage blockNoiseContoursfillConnectedComponentsmaskConnectedComponent countBlobsselectSizedComponentsspatialMomentscentralMomentsnormalizedCentralMoments huMoments mapContours getContours contourAreacontourPerimeter contourPointscontourHuMomentsNormTypeNormDiffRelativeL2NormDiffRelativeL1NormDiffRelativeC NormDiffL2 NormDiffL1 NormDiffC NormMinMaxNormDiff NormRelativeNormMaskNormL2NormL1NormCclearset normalize unitNormalize unitStretch logNormalizeSwapDontSwapQuadrants SwapQuadrantsIpolar32Idft32I32dftdft'idftidft' swapQuadrantsdftSplitdftMerge dftToPolar dftFromPolarrgbSplitrgbMergeDrawableColor putTextOplineOpcircleOprectOp fillPolyOp ellipseBoxOp ShapeStyleStrokedFilledfillOp rectanglefillPoly drawLinesOp drawLines drawBox2Dopcircle floodfillLaplacianAperture SobelAperturesobelOpsobelsScharrs1s3s5s7l1l3l5l7 laplaceOplaplacecannyMoments SURFParams MSERParams mkMSERParamsdefaultMSERParamsgetMSERdefaultSURFParamsgetSURFmomentsgetSpatialMomentgetNormalizedCentralMomentEllipsewidthheightangle fitEllipse fitLine2D minAreaRect boundingRectboundingCircle convexHullconvexityDefects r_variancevariancer_stdDevpearsonSkewness1MaskSizeM5M3 DistanceTypeL2L1C InterpolationCubicAreaLinearNearestNeighbour MirrorAxis HorizontalVerticalcvDistTransformcvPyrUp cvPyrDownpadUp makeEvenUpfindHomographywrapPerspectivecvResize radialRemap rotateImagecvFlipcvDCT takeEvenSizeddctidctflip radialDistortscaleSingleRatio scaleToSizeperspectiveTransform getHomographyevenizeoddize sameSizePad cv_GaussianpyrDownpyrUp safePyrDownlaplacianPyramidreconstructFromLaplacianenlargedistanceTransform GaborMaskrenderRadialGaborradialGaborFilter gaborFilter renderGabor gaborImagegaborFilteringradialGaborFilteringradialGaborImage showImage'_ cvWaitKeycvCreateTrackbarcvDestroyWindowmkWin'_trackbarCallbackdisplaymkWin makeWindow destroyWindow mkTrackbarwaitKey showImage HistogramDataHGD get_histogramget_weighted_histogrambackProjectHistogramvaluescmpUnion cmpIntersect cmpEuclidiancmpAbschiSqrHGchiSqrliftBins liftValuesnoBinsgetPositivePart tcumulateweightedHistogramsimpleGetHistogramImageWithSegmentsImageWithLinesWithLinebiasθSegmentstartend HoughDescimagelinessegments lineToSegmenthoughProbabilisticToLinerho1pixrho5pix theta1deg theta2degimageHoughLinesStandardimageHoughLinesProbabilisticimageHoughLinesMultiScalehoughLinesStandardhoughLinesProbabilistichoughLinesMultiscalehoughCirclesGradient allPatches allButLastgetTiles getTilesCgetOverlappedTileCoordsgetOverlappedTilesgetOverlappedTilesCgetMarkedAndUnmarkedTiles getPatchesgetCenteredPatches randomSelectdiscardAroundEdgesgetCoordsFromMarksgetMarkedPatches ImageContextVgetPosgetValevolveF32I filterPixelsfilterPixelsSlowImageWithCornerscornersCornerposdesc HarrisDescharris harrisCornersvignettingModelPvignettingModelB3vignettingModelCos4vignettingModelCos4XCylvignettingModelX2Cylf x2cylinder cos4cylindercos4vignettingthreeBtwoParStructuringElement KernelShape EllipseShape CrossShape RectShapeopenOpopencloseOpclosegeodesic blackTopHat whiteTopHatbasicSEbigSEstructuringElementcustomSEerodeOpdilateOperodedilateMarkerboxFlawshighLightFlaws displayFlawsdisplayLargeFlaws condMarkergetCoordsForMarkedTilescuteDot cuteCircle1cuteRect cuteCircle markTilesburtAdelsonMergeShapeMatchMethodMethod3Method2Method1 MatchType CCOEFF_NORMEDCCOEFF CCORR_NORMEDCCORR SQDIFF_NORMEDSQDIFF cvMatchShapescvMatchTemplatesimpleMatchTemplate templateImagegetTemplateMapsimpleTemplateMatch matchTemplatesubPixelTemplateMatch regionToInt matchShapesrotationInvariantlbplbp5 weightedLBP AdaptiveType ByGaussianByMean ThresholdType ZeroAndValue ValueAndZeroThreshAndValue ZeroAndMax MaxAndZero threshold thresholdOtsuadaptiveThresholdbernsennibblynibblyrkittlerkittlerMeasurebetweenClassVariance meanShiftsnakeCodecMPG4CapPropCAP_PROP_MONOCROMECAP_PROP_RECTIFICATIONCAP_PROP_WHITE_BALANCE_RED_VCAP_PROP_WHITE_BALANCE_BLUE_UCAP_PROP_CONVERT_RGBCAP_PROP_EXPOSURE CAP_PROP_GAIN CAP_PROP_HUECAP_PROP_SATURATIONCAP_PROP_CONTRASTCAP_PROP_BRIGHTNESS CAP_PROP_MODECAP_PROP_FORMATCAP_PROP_FRAME_COUNTCAP_PROP_FOURCC CAP_PROP_FPSCAP_PROP_FRAME_HEIGHTCAP_PROP_FRAME_WIDTHCAP_PROP_POS_AVI_RATIOCAP_PROP_POS_FRAMESCAP_PROP_POS_MSEC VideoStream VideoWriterCapture cvWriteFramewrapCreateVideoWritercvSetCapturePropertycvGetCaptureProperty cvQueryFrame cvGrabFramecvCreateCameraCapturecvCreateFileCapturereleaseVideoWriterreleaseCapture withCapturewithVideoWriterstreamFromVideostreamFromVideo'captureFromFilecaptureFromCam dropFramegetFramefromProp getCapProp getFrameRate getFrameSize setCapPropnumberOfFrames frameNumbercreateVideoWriter writeFrame$fFunctorStream$fApplicativeStreamC'CvMat c'CvMat'type c'CvMat'stepc'CvMat'refcountc'CvMat'data'ptrc'CvMat'data'sc'CvMat'data'ic'CvMat'data'flc'CvMat'data'db c'CvMat'rows c'CvMat'colsp'cvRodrigues2c'cvRodrigues2p'cvGEMMc'cvGEMM p'cvTranspose c'cvTransposep'cvReleaseMatc'cvReleaseMat p'cvCreateMat c'cvCreateMat p'CvMat'type p'CvMat'stepp'CvMat'refcountp'CvMat'data'ptrp'CvMat'data'sp'CvMat'data'ip'CvMat'data'flp'CvMat'data'db p'CvMat'rows 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c'CV_DIST_L12c'CV_DIST_FAIRc'CV_DIST_WELSCHc'CV_DIST_HUBERtoNumC'CvErrorCallbackp'cvSetErrModec'cvSetErrModep'cvRedirectErrorc'cvRedirectErrormK'CvErrorCallbackmk'CvErrorCallbackc'CV_ErrModeLeafc'CV_ErrModeParentc'CV_ErrModeSilent$fExceptionCvIOError$fExceptionCvException$fSetPixelImage$fSetPixelImage0$fSetPixelImage1$fSetPixelImage2$fEnumImageDepth $fSaveImage $fSaveImage0 $fSaveImage1 $fSaveImage2 $fSaveImage3$fCreateImageImage$fCreateImageImage0$fCreateImageImage1$fCreateImageImage2$fCreateImageImage3$fCreateImageImage4$fCreateImageImage5$fCreateImageImage6$fCreateImageImage7$fCreateImageImage8$fCreateImageImage9$fCreateImageImage10$fCreateImageImage11$fGetPixelImage$fGetPixelImage0$fGetPixelImage1$fGetPixelImage2$fGetPixelImage3$fGetPixelImage4$fGetPixelImage5$fGetPixelImage6$fEnumCvtFlags$fEnumCvtCodes $fSizedImage$fSizedBareImage$fLoadableImage$fLoadableImage0$fLoadableImage1$fLoadableImage2$fComposesImage$fComposesImage0$fComposesImage1 $fNFDataImage$fNumPixelwise$fShowPixelwise 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c'cvSplit p'cvSetZero c'cvSetZero p'wrapSet4 c'wrapSet4 p'wrapSet3 c'wrapSet3 p'wrapSet2 c'wrapSet2 p'wrapSet1 c'wrapSet1 p'wrapSetAll c'wrapSetAll p'wrapSet c'wrapSetc'CV_Cc'CV_L1c'CV_L2c'CV_NORM_MASK c'CV_RELATIVE c'CV_DIFF c'CV_MINMAX c'CV_DIFF_C c'CV_DIFF_L1 c'CV_DIFF_L2c'CV_RELATIVE_Cc'CV_RELATIVE_L1c'CV_RELATIVE_L2c'CV_DXT_FORWARDc'CV_DXT_INVERSEc'CV_DXT_SCALEc'CV_DXT_INV_SCALE c'CV_DXT_ROWSc'CV_DXT_MUL_CONJc'CV_DXT_COMPLEX_OUTPUTc'CV_DXT_REAL_OUTPUTc'CV_DXT_INV_REALc'maskConnectedComponentc'fillConnectedComponentsc'cvAdaptiveThreshold p'cvThreshold c'cvThresholdc'cvGetHuMomentsc'CV_THRESH_BINARYc'CV_THRESH_BINARY_INVc'CV_THRESH_TRUNCc'CV_THRESH_TOZEROc'CV_THRESH_TOZERO_INVc'CV_THRESH_OTSUc'CV_THRESH_OTSU_BINARYc'CV_THRESH_OTSU_BINARY_INVc'CV_THRESH_OTSU_TRUNCc'CV_THRESH_OTSU_TOZEROc'CV_ADAPTIVE_THRESH_GAUSSIAN_C Histogram BorderType BorderWrap 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