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github | garrickbrazil/SDS-RCNN-master | kernelTracker.m | .m | SDS-RCNN-master/external/pdollar_toolbox/videos/kernelTracker.m | 9,315 | utf_8 | 4a7d0235f1e518ab5f1c9f1b5450b3f0 | function [allRct, allSim, allIc] = kernelTracker( I, prm )
% Kernel Tracker from Comaniciu, Ramesh and Meer PAMI 2003.
%
% Implements the algorithm described in "Kernel-Based Object Tracking" by
% Dorin Comaniciu, Visvanathan Ramesh and Peter Meer, PAMI 25, 564-577,
% 2003. This is a fast tracking algorithm that utili... |
github | garrickbrazil/SDS-RCNN-master | seqIo.m | .m | SDS-RCNN-master/external/pdollar_toolbox/videos/seqIo.m | 17,019 | utf_8 | 9c631b324bb527372ec3eed3416c5dcc | function out = seqIo( fName, action, varargin )
% Utilities for reading and writing seq files.
%
% A seq file is a series of concatentated image frames with a fixed size
% header. It is essentially the same as merging a directory of images into
% a single file. seq files are convenient for storing videos because: (1)
%... |
github | garrickbrazil/SDS-RCNN-master | seqReaderPlugin.m | .m | SDS-RCNN-master/external/pdollar_toolbox/videos/seqReaderPlugin.m | 9,617 | utf_8 | ad8f912634cafe13df6fc7d67aeff05a | function varargout = seqReaderPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow reading of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (srp=seqReaderPlugin):
% h = srp('open',h,fName) % Open a seq file for reading ... |
github | garrickbrazil/SDS-RCNN-master | pcaApply.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/pcaApply.m | 3,320 | utf_8 | a06fc0e54d85930cbc0536c874ac63b7 | function varargout = pcaApply( X, U, mu, k )
% Companion function to pca.
%
% Use pca.m to retrieve the principal components U and the mean mu from a
% set of vectors x, then use pcaApply to get the first k coefficients of
% x in the space spanned by the columns of U. See pca for general usage.
%
% If x is large, pcaAp... |
github | garrickbrazil/SDS-RCNN-master | forestTrain.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/forestTrain.m | 6,138 | utf_8 | de534e2a010f452a7b13167dbf9df239 | function forest = forestTrain( data, hs, varargin )
% Train random forest classifier.
%
% Dimensions:
% M - number trees
% F - number features
% N - number input vectors
% H - number classes
%
% USAGE
% forest = forestTrain( data, hs, [varargin] )
%
% INPUTS
% data - [NxF] N length F feature vectors
% hs ... |
github | garrickbrazil/SDS-RCNN-master | fernsRegTrain.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/fernsRegTrain.m | 5,914 | utf_8 | b9ed2d87a22cb9cbb1e2632495ddaf1d | function [ferns,ysPr] = fernsRegTrain( data, ys, varargin )
% Train boosted fern regressor.
%
% Boosted regression using random ferns as the weak regressor. See "Greedy
% function approximation: A gradient boosting machine", Friedman, Annals of
% Statistics 2001, for more details on boosted regression.
%
% A few notes ... |
github | garrickbrazil/SDS-RCNN-master | rbfDemo.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/rbfDemo.m | 2,929 | utf_8 | 14cc64fb77bcac3edec51cf6b84ab681 | function rbfDemo( dataType, noiseSig, scale, k, cluster, show )
% Demonstration of rbf networks for regression.
%
% See rbfComputeBasis for discussion of rbfs.
%
% USAGE
% rbfDemo( dataType, noiseSig, scale, k, cluster, show )
%
% INPUTS
% dataType - 0: 1D sinusoid
% 1: 2D sinusoid
% 2: ... |
github | garrickbrazil/SDS-RCNN-master | pdist2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/pdist2.m | 5,162 | utf_8 | 768ff9e8818251f756c8325368ee7d90 | function D = pdist2( X, Y, metric )
% Calculates the distance between sets of vectors.
%
% Let X be an m-by-p matrix representing m points in p-dimensional space
% and Y be an n-by-p matrix representing another set of points in the same
% space. This function computes the m-by-n distance matrix D where D(i,j)
% is the ... |
github | garrickbrazil/SDS-RCNN-master | pca.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/pca.m | 3,244 | utf_8 | 848f2eb05c18a6e448e9d22af27b9422 | function [U,mu,vars] = pca( X )
% Principal components analysis (alternative to princomp).
%
% A simple linear dimensionality reduction technique. Use to create an
% orthonormal basis for the points in R^d such that the coordinates of a
% vector x in this basis are of decreasing importance. Instead of using all
% d bas... |
github | garrickbrazil/SDS-RCNN-master | kmeans2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/classify/kmeans2.m | 5,251 | utf_8 | f941053f03c3e9eda40389a4cc64ee00 | function [ IDX, C, d ] = kmeans2( X, k, varargin )
% Fast version of kmeans clustering.
%
% Cluster the N x p matrix X into k clusters using the kmeans algorithm. It
% returns the cluster memberships for each data point in the N x 1 vector
% IDX and the K x p matrix of cluster means in C.
%
% This function is in some w... |
github | garrickbrazil/SDS-RCNN-master | acfModify.m | .m | SDS-RCNN-master/external/pdollar_toolbox/detector/acfModify.m | 4,202 | utf_8 | 7a49406d51e7a9431b8fd472be0476e8 | function detector = acfModify( detector, varargin )
% Modify aggregate channel features object detector.
%
% Takes an object detector trained by acfTrain() and modifies it. Only
% certain modifications are allowed to the detector and the detector should
% never be modified directly (this may cause the detector to be in... |
github | garrickbrazil/SDS-RCNN-master | acfDetect.m | .m | SDS-RCNN-master/external/pdollar_toolbox/detector/acfDetect.m | 3,659 | utf_8 | cf1384311b16371be6fa4715140e5c81 | function bbs = acfDetect( I, detector, fileName )
% Run aggregate channel features object detector on given image(s).
%
% The input 'I' can either be a single image (or filename) or a cell array
% of images (or filenames). In the first case, the return is a set of bbs
% where each row has the format [x y w h score] and... |
github | garrickbrazil/SDS-RCNN-master | acfSweeps.m | .m | SDS-RCNN-master/external/pdollar_toolbox/detector/acfSweeps.m | 10,731 | utf_8 | db60505e8ee70092d7967ff95c483db8 | function acfSweeps
% Parameter sweeps for ACF pedestrian detector.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Piotr's Computer Vision Matlab Toolbox Version 3.50
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Li... |
github | garrickbrazil/SDS-RCNN-master | bbGt.m | .m | SDS-RCNN-master/external/pdollar_toolbox/detector/bbGt.m | 34,046 | utf_8 | 69e66c9a0cc143fb9a794fbc9233246e | function varargout = bbGt( action, varargin )
% Bounding box (bb) annotations struct, evaluation and sampling routines.
%
% bbGt gives access to two types of routines:
% (1) Data structure for storing bb image annotations.
% (2) Routines for evaluating the Pascal criteria for object detection.
%
% The bb annotation sto... |
github | garrickbrazil/SDS-RCNN-master | bbApply.m | .m | SDS-RCNN-master/external/pdollar_toolbox/detector/bbApply.m | 21,195 | utf_8 | 8c02a6999a84bfb5fcbf2274b8b91a97 | function varargout = bbApply( action, varargin )
% Functions for manipulating bounding boxes (bb).
%
% A bounding box (bb) is also known as a position vector or a rectangle
% object. It is a four element vector with the fields: [x y w h]. A set of
% n bbs can be stores as an [nx4] array, most funcitons below can handle... |
github | garrickbrazil/SDS-RCNN-master | imwrite2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/imwrite2.m | 5,086 | utf_8 | c98d66c2cddd9ec90beb9b1bbde31fe0 | function I = imwrite2( I, mulFlag, imagei, path, ...
name, ext, nDigits, nSplits, spliti, varargin )
% Similar to imwrite, except follows a strict naming convention.
%
% Wrapper for imwrite that writes file to the filename:
% fName = [path name int2str2(i,nDigits) '.' ext];
% Using imwrite:
% imwrite( I, fName, wri... |
github | garrickbrazil/SDS-RCNN-master | convnFast.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/convnFast.m | 9,102 | utf_8 | 03d05e74bb7ae2ecb0afd0ac115fda39 | function C = convnFast( A, B, shape )
% Fast convolution, replacement for both conv2 and convn.
%
% See conv2 or convn for more information on convolution in general.
%
% This works as a replacement for both conv2 and convn. Basically,
% performs convolution in either the frequency or spatial domain, depending
% on wh... |
github | garrickbrazil/SDS-RCNN-master | imMlGauss.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/imMlGauss.m | 5,674 | utf_8 | 56ead1b25fbe356f7912993d46468d02 | function varargout = imMlGauss( G, symmFlag, show )
% Calculates max likelihood params of Gaussian that gave rise to image G.
%
% Suppose G contains an image of a gaussian distribution. One way to
% recover the parameters of the gaussian is to threshold the image, and
% then estimate the mean/covariance based on the c... |
github | garrickbrazil/SDS-RCNN-master | montage2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/montage2.m | 7,484 | utf_8 | 828f57d7b1f67d36eeb6056f06568ebf | function varargout = montage2( IS, prm )
% Used to display collections of images and videos.
%
% Improved version of montage, with more control over display.
% NOTE: Can convert between MxNxT and MxNx3xT image stack via:
% I = repmat( I, [1,1,1,3] ); I = permute(I, [1,2,4,3] );
%
% USAGE
% varargout = montage2( IS, ... |
github | garrickbrazil/SDS-RCNN-master | jitterImage.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/jitterImage.m | 5,252 | utf_8 | 3310f8412af00fd504c6f94b8c48992c | function IJ = jitterImage( I, varargin )
% Creates multiple, slightly jittered versions of an image.
%
% Takes an image I, and generates a number of images that are copies of the
% original image with slight translation, rotation and scaling applied. If
% the input image is actually an MxNxK stack of images then applie... |
github | garrickbrazil/SDS-RCNN-master | movieToImages.m | .m | SDS-RCNN-master/external/pdollar_toolbox/images/movieToImages.m | 889 | utf_8 | 28c71798642af276951ee27e2d332540 | function I = movieToImages( M )
% Creates a stack of images from a matlab movie M.
%
% Repeatedly calls frame2im. Useful for playback with playMovie.
%
% USAGE
% I = movieToImages( M )
%
% INPUTS
% M - a matlab movie
%
% OUTPUTS
% I - MxNxT array (of images)
%
% EXAMPLE
% load( 'images.mat' ); [X,map]=gray2ind... |
github | garrickbrazil/SDS-RCNN-master | toolboxUpdateHeader.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/toolboxUpdateHeader.m | 2,255 | utf_8 | ade06ae438e20ad8faa66e41267915f3 | function toolboxUpdateHeader
% Update the headers of all the files.
%
% USAGE
% toolboxUpdateHeader
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
%
% See also
%
% Piotr's Computer Vision Matlab Toolbox Version 3.50
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Licensed under the Simplified BSD License [see extern... |
github | garrickbrazil/SDS-RCNN-master | toolboxGenDoc.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/toolboxGenDoc.m | 3,639 | utf_8 | 4c21fb34fa9b6002a1a98a28ab40c270 | function toolboxGenDoc
% Generate documentation, must run from dir toolbox.
%
% 1) Make sure to update and run toolboxUpdateHeader.m
% 2) Update history.txt appropriately, including w current version
% 3) Update overview.html file with the version/date/link to zip:
% edit external/m2html/templates/frame-piotr/overv... |
github | garrickbrazil/SDS-RCNN-master | toolboxHeader.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/toolboxHeader.m | 2,391 | utf_8 | 30c24a94fb54ca82622719adcab17903 | function [y1,y2] = toolboxHeader( x1, x2, x3, prm )
% One line description of function (will appear in file summary).
%
% General commments explaining purpose of function [width is 75
% characters]. There may be multiple paragraphs. In special cases some or
% all of these guidelines may need to be broken.
%
% Next come... |
github | garrickbrazil/SDS-RCNN-master | mdot.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/m2html/mdot.m | 2,516 | utf_8 | 34a14428c433e118d1810e23f5a6caf5 | function mdot(mmat, dotfile,f)
%MDOT - Export a dependency graph into DOT language
% MDOT(MMAT, DOTFILE) loads a .mat file generated by M2HTML using option
% ('save','on') and writes an ascii file using the DOT language that can
% be drawn using <dot> or <neato> .
% MDOT(MMAT, DOTFILE,F) builds the graph containing... |
github | garrickbrazil/SDS-RCNN-master | m2html.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/m2html/m2html.m | 49,063 | utf_8 | 472047b4c36a4f8b162012840e31b59b | function m2html(varargin)
%M2HTML - Documentation Generator for Matlab M-files and Toolboxes in HTML
% M2HTML by itself generates an HTML documentation of the Matlab M-files found
% in the direct subdirectories of the current directory. HTML files are
% written in a 'doc' directory (created if necessary). All the o... |
github | garrickbrazil/SDS-RCNN-master | doxysearch.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/m2html/private/doxysearch.m | 7,724 | utf_8 | 8331cde8495f34b86aef8c18656b37f2 | function result = doxysearch(query,filename)
%DOXYSEARCH Search a query in a 'search.idx' file
% RESULT = DOXYSEARCH(QUERY,FILENAME) looks for request QUERY
% in FILENAME (Doxygen search.idx format) and returns a list of
% files responding to the request in RESULT.
%
% See also DOXYREAD, DOXYWRITE
% Copyright (C)... |
github | garrickbrazil/SDS-RCNN-master | doxywrite.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/m2html/private/doxywrite.m | 3,584 | utf_8 | 3255d8f824957ebc173dde374d0f78af | function doxywrite(filename, kw, statinfo, docinfo)
%DOXYWRITE Write a 'search.idx' file compatible with DOXYGEN
% DOXYWRITE(FILENAME, KW, STATINFO, DOCINFO) writes file FILENAME
% (Doxygen search.idx. format) using the cell array KW containing the
% word list, the sparse matrix (nbword x nbfile) with non-null value... |
github | garrickbrazil/SDS-RCNN-master | doxyread.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/m2html/private/doxyread.m | 3,093 | utf_8 | 3152e7d26bf7ac64118be56f72832a20 | function [statlist, docinfo] = doxyread(filename)
%DOXYREAD Read a 'search.idx' file generated by DOXYGEN
% STATLIST = DOXYREAD(FILENAME) reads FILENAME (Doxygen search.idx
% format) and returns the list of keywords STATLIST as a cell array.
% [STATLIST, DOCINFO] = DOXYREAD(FILENAME) also returns a cell array
% con... |
github | garrickbrazil/SDS-RCNN-master | imwrite2split.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/imwrite2split.m | 1,617 | utf_8 | 4222fd45df123e6dec9ef40ae793004f | % Writes/reads a large set of images into/from multiple directories.
%
% This is useful since certain OS handle very large directories (of say
% >20K images) rather poorly (I'm talking to you Bill). Thus, can take
% 100K images, and write into 5 separate directories, then read them back
% in.
%
% USAGE
% I = imwrite2... |
github | garrickbrazil/SDS-RCNN-master | playmovies.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/playmovies.m | 1,935 | utf_8 | ef2eaad8a130936a1a281f1277ca0ea1 | % [4D] shows R videos simultaneously as a movie.
%
% Plays a movie.
%
% USAGE
% playmovies( I, [fps], [loop] )
%
% INPUTS
% I - MxNxTxR or MxNx1xTxR or MxNx3xTxR array (if MxNxT calls
% playmovie)
% fps - [100] maximum number of frames to display per second use
% fps==0 to introduce n... |
github | garrickbrazil/SDS-RCNN-master | pca_apply_large.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/pca_apply_large.m | 2,062 | utf_8 | af84a2179b9d8042519bc6b378736a88 | % Wrapper for pca_apply that allows for application to large X.
%
% Wrapper for pca_apply that splits and processes X in parts, this may be
% useful if processing cannot be done fully in parallel because of memory
% constraints. See pca_apply for usage.
%
% USAGE
% same as pca_apply
%
% INPUTS
% same as pca_apply
%
%... |
github | garrickbrazil/SDS-RCNN-master | montages2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/montages2.m | 2,269 | utf_8 | 505e2be915d65fff8bfef8473875cc98 | % MONTAGES2 [4D] Used to display R sets of T images each.
%
% Displays one montage (see montage2) per row. Each of the R image sets is
% flattened to a single long image by concatenating the T images in the
% set. Alternative to montages.
%
% USAGE
% varargout = montages2( IS, [montage2prms], [padSiz] )
%
% INPUTS
% ... |
github | garrickbrazil/SDS-RCNN-master | filter_gauss_1D.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/filter_gauss_1D.m | 1,137 | utf_8 | 94a453b82dcdeba67bd886e042d552d9 | % 1D Gaussian filter.
%
% Equivalent to (but faster then):
% f = fspecial('Gaussian',[2*r+1,1],sigma);
% f = filter_gauss_nD( 2*r+1, r+1, sigma^2 );
%
% USAGE
% f = filter_gauss_1D( r, sigma, [show] )
%
% INPUTS
% r - filter size=2r+1, if r=[] -> r=ceil(2.25*sigma)
% sigma - standard deviation of filter
% ... |
github | garrickbrazil/SDS-RCNN-master | clfEcoc.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/clfEcoc.m | 1,493 | utf_8 | e77e1b4fd5469ed39f47dd6ed15f130f | function clf = clfEcoc(p,clfInit,clfparams,nclasses,use01targets)
% Wrapper for ecoc that makes ecoc compatible with nfoldxval.
%
% Requires the SVM toolbox by Anton Schwaighofer.
%
% USAGE
% clf = clfEcoc(p,clfInit,clfparams,nclasses,use01targets)
%
% INPUTS
% p - data dimension
% clfInit - bi... |
github | garrickbrazil/SDS-RCNN-master | getargs.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/getargs.m | 3,455 | utf_8 | de2bab917fa6b9ba3099f1c6b6d68cf0 | % Utility to process parameter name/value pairs.
%
% DEPRECATED -- ONLY USED BY KMEANS2? SHOULD BE REMOVED.
% USE GETPARAMDEFAULTS INSTEAD.
%
% Based on code fromt Matlab Statistics Toolobox's "private/statgetargs.m"
%
% [EMSG,A,B,...]=GETARGS(PNAMES,DFLTS,'NAME1',VAL1,'NAME2',VAL2,...)
% accepts a cell array PNAMES o... |
github | garrickbrazil/SDS-RCNN-master | normxcorrn_fg.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/normxcorrn_fg.m | 2,699 | utf_8 | e65c38d97efb3a624e0fa94a97f75eb6 | % Normalized n-dimensional cross-correlation with a mask.
%
% Similar to normxcorrn, except takes an additional argument that specifies
% a figure ground mask for the T. That is T_fg must be of the same
% dimensions as T, with each entry being 0 or 1, where zero specifies
% regions to ignore (the ground) and 1 specifi... |
github | garrickbrazil/SDS-RCNN-master | makemovie.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/makemovie.m | 1,266 | utf_8 | 9a03d9a5227c4eaa86520f206ce283e7 | % [3D] Used to convert a stack of T images into a movie.
%
% To display same data statically use montage.
%
% USAGE
% M = makemovies( IS )
%
% INPUTS
% IS - MxNxT or MxNx1xT or MxNx3xT array of movies.
%
% OUTPUTS
% M - resulting movie
%
% EXAMPLE
% load( 'images.mat' );
% M = makemovie(... |
github | garrickbrazil/SDS-RCNN-master | localsum_block.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/localsum_block.m | 815 | utf_8 | 1216b03a3bd44ff1fc3256de16a2f1c6 | % Calculates the sum in non-overlapping blocks of I of size dims.
%
% Similar to localsum except gets sum in non-overlapping windows.
% Equivalent to doing localsum, and then subsampling (except more
% efficient).
%
% USAGE
% I = localsum_block( I, dims )
%
% INPUTS
% I - matrix to compute sum over
% dims -... |
github | garrickbrazil/SDS-RCNN-master | imrotate2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/imrotate2.m | 1,326 | utf_8 | bb2ff6c3138ce5f53154d58d7ebc4f31 | % Custom version of imrotate that demonstrates use of apply_homography.
%
% Works exactly the same as imrotate. For usage see imrotate.
%
% USAGE
% IR = imrotate2( I, angle, [method], [bbox] )
%
% INPUTS
% I - 2D image [converted to double]
% angle - angle to rotate in degrees
% method - ['linear'] 'neare... |
github | garrickbrazil/SDS-RCNN-master | imSubsResize.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/imSubsResize.m | 1,338 | utf_8 | cd7dedf790c015adfb1f2d620e9ed82f | % Resizes subs by resizVals.
%
% Resizes subs in subs/vals image representation by resizVals.
%
% This essentially replaces each sub by sub.*resizVals. The only subtlety
% is that in images the leftmost sub value is .5, so for example when
% resizing by a factor of 2, the first pixel is replaced by 2 pixels and so
% l... |
github | garrickbrazil/SDS-RCNN-master | imtranslate.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/imtranslate.m | 1,183 | utf_8 | 054727fb31c105414b655c0f938b6ced | % Translate an image to subpixel accuracy.
%
% Note that for subplixel accuracy cannot use nearest neighbor interp.
%
% USAGE
% IR = imtranslate( I, dx, dy, [method], [bbox] )
%
% INPUTS
% I - 2D image [converted to double]
% dx - x translation (right)
% dy - y translation (up)
% method - ['linear... |
github | garrickbrazil/SDS-RCNN-master | randperm2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/randperm2.m | 1,398 | utf_8 | 5007722f3d5f5ba7c0f83f32ef8a3a2c | % Returns a random permutation of integers.
%
% randperm2(n) is a random permutation of the integers from 1 to n. For
% example, randperm2(6) might be [2 4 5 6 1 3]. randperm2(n,k) is only
% returns the first k elements of the permuation, so for example
% randperm2(6) might be [2 4]. This is a faster version of randp... |
github | garrickbrazil/SDS-RCNN-master | apply_homography.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/apply_homography.m | 3,582 | utf_8 | 9c3ed72d35b1145f41114e6e6135b44f | % Applies the homography defined by H on the image I.
%
% Takes the center of the image as the origin, not the top left corner.
% Also, the coordinate system is row/ column format, so H must be also.
%
% The bounding box of the image is set by the BBOX argument, a string that
% can be 'loose' (default) or 'crop'. When ... |
github | garrickbrazil/SDS-RCNN-master | pca_apply.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/pca_apply.m | 2,427 | utf_8 | 0831befb6057f8502bc492227455019a | % Companion function to pca.
%
% Use pca to retrieve the principal components U and the mean mu from a
% set fo vectors X1 via [U,mu,vars] = pca(X1). Then given a new
% vector x, use y = pca_apply( x, U, mu, vars, k ) to get the first k
% coefficients of x in the space spanned by the columns of U. See pca for
% genera... |
github | garrickbrazil/SDS-RCNN-master | mode2.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/deprecated/mode2.m | 731 | utf_8 | 5c9321ef4b610b4f4a2d43902a68838e | % Returns the mode of a vector.
%
% Was mode not part of Matlab before?
%
% USAGE
% y = mode2( x )
%
% INPUTS
% x - vector of integers
%
% OUTPUTS
% y - mode
%
% EXAMPLE
% x = randint2( 1, 10, [1 3] )
% mode(x), mode2( x )
%
% See also MODE
% Piotr's Image&Video Toolbox Version 1.5
% Written and maintain... |
github | garrickbrazil/SDS-RCNN-master | savefig.m | .m | SDS-RCNN-master/external/pdollar_toolbox/external/other/savefig.m | 13,459 | utf_8 | 2b8463f9b01ceb743e440d8fb5755829 | function savefig(fname, varargin)
% Usage: savefig(filename, fighdl, options)
%
% Saves a pdf, eps, png, jpeg, and/or tiff of the contents of the fighandle's (or current) figure.
% It saves an eps of the figure and the uses Ghostscript to convert to the other formats.
% The result is a cropped, clean picture. There a... |
github | garrickbrazil/SDS-RCNN-master | dirSynch.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/dirSynch.m | 4,570 | utf_8 | d288299d31d15f1804183206d0aa0227 | function dirSynch( root1, root2, showOnly, flag, ignDate )
% Synchronize two directory trees (or show differences between them).
%
% If a file or directory 'name' is found in both tree1 and tree2:
% 1) if 'name' is a file in both the pair is considered the same if they
% have identical size and identical datestamp... |
github | garrickbrazil/SDS-RCNN-master | plotRoc.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/plotRoc.m | 5,212 | utf_8 | 008f9c63073c6400c4960e9e213c47e5 | function [h,miss,stds] = plotRoc( D, varargin )
% Function for display of rocs (receiver operator characteristic curves).
%
% Display roc curves. Consistent usage ensures uniform look for rocs. The
% input D should have n rows, each of which is of the form:
% D = [falsePosRate truePosRate]
% D is generated, for exampl... |
github | garrickbrazil/SDS-RCNN-master | simpleCache.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/simpleCache.m | 4,098 | utf_8 | 92df86b0b7e919c9a26388e598e4d370 | function varargout = simpleCache( op, cache, varargin )
% A simple cache that can be used to store results of computations.
%
% Can save and retrieve arbitrary values using a vector (includnig char
% vectors) as a key. Especially useful if a function must perform heavy
% computation but is often called with the same in... |
github | garrickbrazil/SDS-RCNN-master | tpsInterpolate.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/tpsInterpolate.m | 1,646 | utf_8 | d3bd3a26d048f32cfdc17884ccae6d8c | function [xsR,ysR] = tpsInterpolate( warp, xs, ys, show )
% Apply warp (obtained by tpsGetWarp) to a set of new points.
%
% USAGE
% [xsR,ysR] = tpsInterpolate( warp, xs, ys, [show] )
%
% INPUTS
% warp - [see tpsGetWarp] bookstein warping parameters
% xs, ys - points to apply warp to
% show - [1] will disp... |
github | garrickbrazil/SDS-RCNN-master | checkNumArgs.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/checkNumArgs.m | 3,796 | utf_8 | 726c125c7dc994c4989c0e53ad4be747 | function [ x, er ] = checkNumArgs( x, siz, intFlag, signFlag )
% Helper utility for checking numeric vector arguments.
%
% Runs a number of tests on the numeric array x. Tests to see if x has all
% integer values, all positive values, and so on, depending on the values
% for intFlag and signFlag. Also tests to see if ... |
github | garrickbrazil/SDS-RCNN-master | fevalDistr.m | .m | SDS-RCNN-master/external/pdollar_toolbox/matlab/fevalDistr.m | 11,227 | utf_8 | 7e4d5077ef3d7a891b2847cb858a2c6c | function [out,res] = fevalDistr( funNm, jobs, varargin )
% Wrapper for embarrassingly parallel function evaluation.
%
% Runs "r=feval(funNm,jobs{i}{:})" for each job in a parallel manner. jobs
% should be a cell array of length nJob and each job should be a cell array
% of parameters to pass to funNm. funNm must be a f... |
github | garrickbrazil/SDS-RCNN-master | medfilt1m.m | .m | SDS-RCNN-master/external/pdollar_toolbox/filters/medfilt1m.m | 2,998 | utf_8 | a3733d27c60efefd57ada9d83ccbaa3d | function y = medfilt1m( x, r, z )
% One-dimensional adaptive median filtering with missing values.
%
% Applies a width s=2*r+1 one-dimensional median filter to vector x, which
% may contain missing values (elements equal to z). If x contains no
% missing values, y(j) is set to the median of x(j-r:j+r). If x contains
% ... |
github | garrickbrazil/SDS-RCNN-master | FbMake.m | .m | SDS-RCNN-master/external/pdollar_toolbox/filters/FbMake.m | 6,692 | utf_8 | b625c1461a61485af27e490333350b4b | function FB = FbMake( dim, flag, show )
% Various 1D/2D/3D filterbanks (hardcoded).
%
% USAGE
% FB = FbMake( dim, flag, [show] )
%
% INPUTS
% dim - dimension
% flag - controls type of filterbank to create
% - if d==1
% 1: gabor filter bank for spatiotemporal stuff
% - if d==2
% ... |
github | nscholtes/Default-Cascades-master | lnbin.m | .m | Default-Cascades-master/lnbin.m | 1,412 | utf_8 | b27c6f1c9406b20ad7536b447c724a16 | % This function take the input of a data vector x, which is to be binned;
% it also takes in the amount bins one would like the data binned into. The
% output is two vectors, one containing the normalised frequency of each bin
% (Freq), the other, the midpoint of each bin (midpts).
% Added and error to the binned ... |
github | egg5562/Electronic-Nose-master | normalize_data.m | .m | Electronic-Nose-master/source_code/normalize_data.m | 470 | utf_8 | 5649f07241d28cea2852755d76f6e1ea |
function normalized_data = normalize_data(set,m,s)
si= size(set);
ForRepmat = si(1);
new_mean = repmat(m,ForRepmat,1);
new_std = repmat(s,ForRepmat,1);
normalized_data = (set- new_mean)./new_std;
end
% si= size(tr_set(:,1:end-1));
% ForRepmat = si(2);
% new_mean... |
github | egg5562/Electronic-Nose-master | cal_std.m | .m | Electronic-Nose-master/source_code/cal_std.m | 547 | utf_8 | 34787ea76a9210756ea14220a6d7de6f | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Mean and Std calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [mean_vec, std_vec] = cal_std(data);
[N_P, N_F] = size(data);
for j=1:N_F,
sum(j) = 0;
for i=1:N_P,
s... |
github | egg5562/Electronic-Nose-master | L1PCA.m | .m | Electronic-Nose-master/source_code/L1PCA.m | 2,724 | utf_8 | ec8b30e80cd9ad3aac81864b7e7f4382 | % 1DPCA
% by Spinoz Kim (spinoz@csl.snu.ac.kr)
% Dec. 8 2004
% n_it = iteration number
function [w, n_it, elap_time, tr_prj] = L1PCA(tr_data, Ns);
%Read input file
% [N, temp] = size(tr_data);
[N, N_f] = size(tr_data);
% N_f = temp-1; %N_Tr = 100*2, %N_F = 100*120
data_tr = tr_data(:,1:N_f);
%cl... |
github | haitaozhao/Dynamic-Graph-Embedding-for-Fault-Detection-master | kde.m | .m | Dynamic-Graph-Embedding-for-Fault-Detection-master/Matlab_code/kde.m | 5,361 | utf_8 | 984530c222928bc6fba29542faa4d5cd | function [bandwidth,density,xmesh,cdf]=kde(data,n,MIN,MAX)
% Reliable and extremely fast kernel density estimator for one-dimensional data;
% Gaussian kernel is assumed and the bandwidth is chosen automatically;
% Unlike many other implementations, this one is immune to problems
% caused by mul... |
github | ROCmSoftwarePlatform/CNTK-1-master | ComputeConfusion.m | .m | CNTK-1-master/Examples/Speech/Miscellaneous/TIMIT/AdditionalFiles/ComputeConfusion.m | 6,047 | utf_8 | 9c31b020d02c3e11bbdb1db0a04bcc32 | function confusionData = ComputeConfusion(mlfFile)
% function confusionData = ComputeConfusion(mlfFile)
% Compute all the confusions for one experiment. Read in the TIMIT MLF file
% so we know which utterances we have. For each utterance, read in the
% CNTK output and compute the confusion matrix. Sum them all togeth... |
github | ROCmSoftwarePlatform/CNTK-1-master | ShowConfusions.m | .m | CNTK-1-master/Examples/Speech/Miscellaneous/TIMIT/AdditionalFiles/ShowConfusions.m | 2,174 | utf_8 | 0e7784a2f2e8b497f6ad9e7cd07e9377 | function ShowConfusions(confusionData, squeeze)
% function ShowConfusions(confusionData)
% Average the three-state confusion data into monophone confusions. Then
% display the data. A graphical interface lets you interrogate the data,
% by moving the mouse, and clicking at various points. The phonetic labels
% are s... |
github | SNURobotics/AdaptiveControl_-master | skew.m | .m | AdaptiveControl_-master/IROS2018/adaptive control/matlab_code_MTtest/skew.m | 436 | utf_8 | d16b20d6af4d5e9151fb41c84b47f8fd | %% return skew-symmetric matrix : r -> [r] or [r] - > r
function mat=skew(r)
% mat=[0 -r(3) r(2);
% r(3) 0 -r(1);
% -r(2) r(1) 0];
if (size(r) == [3,1])
mat=zeros(3);
mat(1,2)=-r(3);
mat(1,3)=r(2);
mat(2,1)=r(3);
mat(2,3)=-r(1);
mat(3,1)=-r(2);
mat(3,2)=r(1);
elseif... |
github | SNURobotics/AdaptiveControl_-master | robot_dyn_eq.m | .m | AdaptiveControl_-master/IROS2018/adaptive control/matlab_code_MTtest/robot_dyn_eq.m | 1,057 | utf_8 | 573fd2eca9a67040a6e9a0615df6ec80 | % function [MM,CC,gg, Jt] = robot_dyn_eq(S, M, J,f_iti, q,q_dot)
function [MM,CC,gg] = robot_dyn_eq(robot,q,q_dot)
n_joints=robot.nDOF;
SS=zeros(n_joints*6,n_joints);
GG=eye(6*n_joints, 6*n_joints);
JJ=zeros(6*n_joints, 6*n_joints);
adV=zeros(6*n_joints, 6*n_joints);
f_=cell(n_joints,1);
% Ad_ft=zeros(6*n_joint... |
github | SukritGupta17/Chess-Board-Recognition-master | DeepLearningImageClassificationExample.m | .m | Chess-Board-Recognition-master/Code/DeepLearningImageClassificationExample.m | 15,434 | utf_8 | 07974ce7f3f0aa58be243f2f530bd2d5 | %% Image Category Classification Using Deep Learning
% This example shows how to use a pre-trained Convolutional Neural Network
% (CNN) as a feature extractor for training an image category classifier.
%
% Copyright 2016 The MathWorks, Inc.
%% Overview
% A Convolutional Neural Network (CNN) is a powerful machine lea... |
github | zhoujinglin/matlab-master | mkR.m | .m | matlab-master/video_fusion/mkR.m | 807 | utf_8 | 1d284110ac41a7451780fa347b65ff9f | % IM = mkR(SIZE, EXPT, ORIGIN)
%
% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
% containing samples of a radial ramp function, raised to power EXPT
% (default = 1), with given ORIGIN (default = (size+1)/2, [1 1] =
% upper left). All but the first argument are optional.
% Eero Simoncelli... |
github | zhoujinglin/matlab-master | mkZonePlate.m | .m | matlab-master/video_fusion/mkZonePlate.m | 666 | utf_8 | c8865ffd7d38f1f3cb5c4593ee1f7ff9 | % IM = mkZonePlate(SIZE, AMPL, PHASE)
%
% Make a "zone plate" image:
% AMPL * cos( r^2 + PHASE)
% SIZE specifies the matrix size, as for zeros().
% AMPL (default = 1) and PHASE (default = 0) are optional.
% Eero Simoncelli, 6/96.
function [res] = mkZonePlate(sz, ampl, ph)
sz = sz(:);
if (size(sz,1)... |
github | zhoujinglin/matlab-master | ucurvrec3d.m | .m | matlab-master/video_fusion/ucurvrec3d.m | 3,171 | utf_8 | 0f315695d3e044d0a538bef4d38e96db | function im = ucurvrec3d(ydec, Cf, F)
% UCURVREC3D 3-d ucurvelet reconstruction using normal 3-D window
%
% im = ucurvrec3d_s(ydec, Cf, F)
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In uniform curvelet, n is 3*2^n
% r : parameter of the meyer window used in diameter dir... |
github | zhoujinglin/matlab-master | ucurvdec3d_s.m | .m | matlab-master/video_fusion/ucurvdec3d_s.m | 4,297 | utf_8 | 8bac35e6f8a639b0f5f585c2b8feb2bc | function [ydec, cf_ydec] = ucurvdec3d_s(im, Cf, F2, ind2, cfind )
% UCURVDEC3D_S 3-d ucurvelet decomposition using sparse 3-D window
%
% ydec = ucurvdec3d_s(im, Cf, F2, ind2, cfind )
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In uniform curvelet, n is 3*2^n
% r : para... |
github | zhoujinglin/matlab-master | ucurvrec3d_s.m | .m | matlab-master/video_fusion/ucurvrec3d_s.m | 3,421 | utf_8 | 6ef728e9d4077d1fe26222dd8d6bb03a | function im = ucurvrec3d_s(ydec, Cf, F2, ind2, cfind )
% UCURVREC3D_S 3-d ucurvelet reconstruction using sparse 3-D window
%
% im = ucurvrec3d_s(ydec, Cf, F2, ind2, cfind )
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In uniform curvelet, n is 3*2^n
% r : parameter of the... |
github | zhoujinglin/matlab-master | ucurvdec3d.m | .m | matlab-master/video_fusion/ucurvdec3d.m | 3,537 | utf_8 | 3c1056a7c969012669fc15cdb74d7a32 | function ydec = ucurvdec3d(im, Cf, F)
% UCURVDEC3D 3-d ucurvelet decomposition using normal 3-D window
%
% ydec = ucurvdec3d_s(im, Cf, F)
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In uniform curvelet, n is 3*2^n
% r : parameter of the meyer window used in diameter di... |
github | zhoujinglin/matlab-master | ucurvwin3d_s.m | .m | matlab-master/video_fusion/ucurvwin3d_s.m | 13,516 | utf_8 | a62c1b03857e727311b10e423f6b00f4 | function [F2, ind2, cf] = ucurvwin3d_s(Sz, Cf, r, alpha)
% UCURVWIN3D_S Generate the sparse curvelet windows that used in 3-D
% uniform curvelet inverse and foward transform
%
% [F2, ind2, cf] = ucurvwin3d_s(Sz, Cf, r, alpha)
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In... |
github | zhoujinglin/matlab-master | ucurvwin3d.m | .m | matlab-master/video_fusion/ucurvwin3d.m | 9,774 | utf_8 | b2d4a9150b181494e86ae0331f19eb0d | function F2 = ucurvwin3d(Sz, Cf, r, alpha)
% UCURV_WIN3D Generate the curvelet windows that used in 3-D uniform curvelet
% inverse and foward transform
%
% F = ucurv_win(Sz, Cf, r, alpha)
%
% Input:
% Sz : size of the generated window
% Cf : number of directional curvelet. In uniform curvelet, n is 3*2^n
% r : ... |
github | zhoujinglin/matlab-master | iisum.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/iisum.m | 390 | utf_8 | 065f814dffc187bce6e3caf48b6b642a | %---------------------------------------------------------
%---------------------------------------------------------
function sum = iisum(iimg,x1,y1,x2,y2)
if(x1>1 && y1>1)
sum = iimg(y2,x2)+iimg(y1-1,x1-1)-iimg(y1-1,x2)-iimg(y2,x1-1);
elseif(x1<=1 && y1>1)
sum = iimg(y2,x2)-iimg(y1-1,x2);
elseif(y1<=1 && x1>1... |
github | zhoujinglin/matlab-master | fdct_wrapping_dispcoef.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/fdct_wrapping_matlab/fdct_wrapping_dispcoef.m | 1,919 | utf_8 | 2af5a55f76ce583e6879244514db1b37 | function img = fdct_wrapping_dispcoef(C)
% fdct_wrapping_dispcoef - returns an image containing all the curvelet coefficients
%
% Inputs
% C Curvelet coefficients
%
% Outputs
% img Image containing all the curvelet coefficients. The coefficents are rescaled so that
% the largest coefficent... |
github | zhoujinglin/matlab-master | extend2.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/nsct_toolbox/extend2.m | 1,792 | utf_8 | 607c7de17e89483c3983b26b6987cb80 | function y = extend2(x, ru, rd, cl, cr, extmod)
% EXTEND2 2D extension
%
% y = extend2(x, ru, rd, cl, cr, extmod)
%
% Input:
% x: input image
% ru, rd: amount of extension, up and down, for rows
% cl, cr: amount of extension, left and rigth, for column
% extmod: extension mode. The valid modes are:
% 'per': period... |
github | zhoujinglin/matlab-master | gen_x_y_cordinates.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/shearlet_toolbox/gen_x_y_cordinates.m | 2,307 | utf_8 | 48e8b6cf36ec28307441e81a22da1b11 | function [x1n,y1n,x2n,y2n,D]=gen_x_y_cordinates(n)
%
% This function generates the x and y vectors that contain
% the i,j coordinates to extract radial slices
%
% Input: n is the order of the block to be used
%
% Outputs: x1,y1 are the i,j values that correspond to
% the radial slices from the endpoints 1,... |
github | zhoujinglin/matlab-master | colorspace.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/dtcwt_toolbox/colorspace.m | 13,590 | utf_8 | b1a9eb973fa39950345a1df707b5d2c8 | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Convert a color image between color representations.
% B = COLORSPACE(S,A) converts the color representation of image A
% where S is a string specifying the conversion. S tells the
% source and destination color spaces, S = 'dest<-src', or
% alt... |
github | zhoujinglin/matlab-master | dtwaveifm.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/dtcwt_toolbox/dtwaveifm.m | 3,486 | utf_8 | 07a0631bc29c7e92d8255a7f52ecec0b | function Z = dtwaveifm(Yl,Yh,biort,qshift,gain_mask);
% Function to perform an n-level dual-tree complex wavelet (DTCWT)
% 1-D reconstruction.
%
% Z = dtwaveifm(Yl,Yh,biort,qshift,gain_mask);
%
% Yl -> The real lowpass subband from the final level
% Yh -> A cell array containing the complex highpass subban... |
github | zhoujinglin/matlab-master | dDTCWT.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/dtcwt_toolbox/dDTCWT.m | 1,565 | utf_8 | 8c9992a796e21805fbcd88f6acc567bd |
function [Y1 h11]=derotated_dtcwt(I1,n,biot,Qshift)
% X -> 2D real matrix/Image
%
% nlevels -> No. of levels of wavelet decomposition
%
% biort -> 'antonini' => Antonini 9,7 tap filters.
% 'legall' => LeGall 5,3 tap filters.
% 'near_sym_a' => Near-Symmetric 5,7 tap filter... |
github | zhoujinglin/matlab-master | dtwavexfm2.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/dtcwt_toolbox/dtwavexfm2.m | 6,425 | utf_8 | dc2ac3ba8198284e20b2982574de6174 | function [Yl,Yh,Yscale] = dtwavexfm2(X,nlevels,biort,qshift);
% Function to perform a n-level DTCWT-2D decompostion on a 2D matrix X
%
% [Yl,Yh,Yscale] = dtwavexfm2(X,nlevels,biort,qshift);
%
% X -> 2D real matrix/Image
%
% nlevels -> No. of levels of wavelet decomposition
%
% biort -> 'antonini' => Ant... |
github | zhoujinglin/matlab-master | dtwaveifm2.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/dtcwt_toolbox/dtwaveifm2.m | 4,884 | utf_8 | b7b8d7bbbe5209e8550b34297949f93c | function Z = dtwaveifm2(Yl,Yh,biort,qshift,gain_mask);
% Function to perform an n-level dual-tree complex wavelet (DTCWT)
% 2-D reconstruction.
%
% Z = dtwaveifm2(Yl,Yh,biort,qshift,gain_mask);
%
% Yl -> The real lowpass image from the final level
% Yh -> A cell array containing the 6 complex highpass subi... |
github | zhoujinglin/matlab-master | ompdemo.m | .m | matlab-master/video_fusion/MST_SR_fusion_toolbox/sparsefusion/ksvdbox/ompbox/ompdemo.m | 2,294 | utf_8 | 330e3e897edffa6b88c516d30fc4e96b | function ompdemo
%OMPDEMO Demonstration of the OMP toolbox.
% OMPDEMO generates a random sparse mixture of cosines and spikes, adds
% noise, and applies OMP to recover the original signal.
%
% To run the demo, type OMPDEMO from the Matlab prompt.
%
% See also OMPSPEEDTEST.
% Ron Rubinstein
% Computer Science De... |
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