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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | mbonakda/nw-opt-master | longStepPathFollow.m | .m | nw-opt-master/longStepPathFollow.m | 3,027 | utf_8 | ffa5f2c579b898ab85d51ade04ecacef | % Author: Matt Bonakdarpour
% Description:
% - Implements the Long-Step Path-Following interior-point method for solving:
% min c'x s.t. Ax=b, x >= 0
% - See Nocedal & Wright, Algorithm 14.2
function [x_out, lambda_out, s_out] = longStepPathFollow(A, b, c)
% starting point
x1 = A'*((A*A')\b);
l... |
github | mbonakda/nw-opt-master | newton_hessMod.m | .m | nw-opt-master/newton_hessMod.m | 2,032 | utf_8 | 65c2e8c6434434e40f39c2c5701ab3e3 | % Author: Matt Bonakdarpour
% Description:
% - Line Search Newton's Method with Hessian Modificaiton. Uses Armijo backtracking.
% - Hessian modification done by modified symmetric indefinite LDL' factorization
% - See section 3.4 of Nocedal & Wright
function [ x_out, numCalls, grad_norms, numSolves ] = newton_hessMod... |
github | mbonakda/nw-opt-master | simpleLC_opt.m | .m | nw-opt-master/simpleLC_opt.m | 2,511 | utf_8 | d44ac2dd659c4cfa4a0addc9f6e68d29 | % Author: Matt Bonakdarpour
% Description:
% - Reduces linearly constrained optimization problem to unconstrainted problem.
% Original problem: min f(x) s.t. Ax = b
% - Solves unconstrained opt with modified newton line search
function [x_out, lambda] = simpleLC_opt(fncHandle, A, b)
% find a solution
... |
github | sofa-framework/sofa-master | use_cimgmatlab.m | .m | sofa-master/applications/plugins/CImgPlugin/extlibs/CImg/examples/use_cimgmatlab.m | 1,242 | utf_8 | c7cefea57d7bf6077ec6a77f3bdda6b6 | /*-----------------------------------------------------------------------
File : use_cimgmatlab.m
Description: Example of use for the CImg plugin 'plugins/cimgmatlab.h'
which allows to use CImg in order to develop matlab external
functions (mex functions).
User should be familiar with Matlab C/C++ mex functi... |
github | abhishekmeena2104/Mean-Shift-Algorithm-for-Image-Segmentation-master | colorspace.m | .m | Mean-Shift-Algorithm-for-Image-Segmentation-master/colorspace.m | 12,777 | utf_8 | ba2555a460b7f4b9f36f4885bf71e67a |
% NOTE NOTE NOTE
% NOTE: THIS CODE IS the work of 'Pascal Getreuer ' which converts all the
% possible spaces to various different spaces
%Source : Mathworks
function varargout = colorspace(Conversion,varargin)
%%% Input parsing %%%
if nargin < 2, error('Not enough input argume... |
github | abhishekmeena2104/Mean-Shift-Algorithm-for-Image-Segmentation-master | RGB2LUV.m | .m | Mean-Shift-Algorithm-for-Image-Segmentation-master/RGB2LUV.m | 1,385 | utf_8 | 0568329b695b3eba4841c0c0fb2f3602 |
% formulas for the conversions were taken from the wikipedia
function [ L,U,V ] = RGB2LUV(R,G,B)
var_R = double( R )/ 255 ;
var_G = double( G )/ 255 ;
var_B = double( B )/ 255 ;
if ( var_R >0.04045 )
var_R = ( ( var_R + 0.055 ) / 1.055 )^2.4;
else
var_R = var_R / 12.92;
end
... |
github | tokoro10g/matlab-treed-master | plottreed.m | .m | matlab-treed-master/plottreed.m | 4,043 | utf_8 | 2e49ea3d17c65940419efac2361a118f | function tdhandles = plottreed(tree, varargin)
%PLOTTREED Plot TreeD cell structure
% TDHANDLES = PLOTTREED(TREE) plots TreeD cell structure TREE on figure.
%
% TDHANDLES = PLOTTREED(TREE, 'Parent', TDHANDLE) plots TreeD cell
% structure under TDHANDLE.
%
% See also MODIFYTREED, DESTROYTREED, PRINTTREED
root =... |
github | tokoro10g/matlab-treed-master | printtreed.m | .m | matlab-treed-master/printtreed.m | 1,585 | utf_8 | 8e59e398502f87951e5520dcade4a856 | function printtreed(tree)
%PRINTTREED Gracefully print TreeD cell structure
% PRINTTREED(TREE) prints out TreeD cell structure better than DISP or
% CELLDISP function. This function is useful when examining generated
% TreeD cell structures.
%
% See also PLOTTREED
if isempty(inputname(1))
disp('tree = {')
... |
github | 6ag/V2ex-Swift-master | OnePasswordExtension.m | .m | V2ex-Swift-master/Pods/1PasswordExtension/OnePasswordExtension.m | 39,548 | utf_8 | 89c1cc65949ebd8bdbd002105254f134 | //
// 1Password Extension
//
// Lovingly handcrafted by Dave Teare, Michael Fey, Rad Azzouz, and Roustem Karimov.
// Copyright (c) 2014 AgileBits. All rights reserved.
//
#import "OnePasswordExtension.h"
// Version
#define VERSION_NUMBER @(180)
static NSString *const AppExtensionVersionNumberKey = @"version_number... |
github | shizenglin/Rank-based-Pooling-for-Deep-Convolutional-Neural-Networks-master | classification_demo.m | .m | Rank-based-Pooling-for-Deep-Convolutional-Neural-Networks-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | zclhit/HumanTimbre_recognition-master | sigma.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/sigma.m | 8,952 | utf_8 | c6d87e779f8ffe491bb3341f1a563b2b | function [gci goi] = sigma(lx,fs,fmax)
% Singularity in EGG by Multiscale Analysis (SIGMA) Algorithm
%
% [gci goi] = sigma(lx,fs,fmax)
%
% Inputs:
% lx Nx1 vector LX signal
% fs Sampling freq (Hz)
% fmax [Optional] max laryngeal freq
% Outputs:
% gci Vector of gcis as ... |
github | zclhit/HumanTimbre_recognition-master | fxpefac.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/fxpefac.m | 15,898 | utf_8 | b3207bfb140803465c8a2aed6933d115 | function [fx,tx,pv,fv]=fxpefac(s,fs,tinc,m,pp)
%FXPEFAC PEFAC pitch tracker [FX,TT,PV,FV]=(S,FS,TINC,M,PP)
%
% Input: s(ns) Speech signal
% fs Sample frequency (Hz)
% tinc Time increment between frames (s) [0.01]
% or [start increment end]
% m ... |
github | zclhit/HumanTimbre_recognition-master | psycestu.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/psycestu.m | 10,646 | utf_8 | be192cd7406b19804284cba252356c33 | function [xx,ii,m,v]=psycestu(iq,x,r,xp)
% psycestu estimate unimodal psychometric function
%
% Usage: [xx,ii,m,v]=psycestu(-n,p,q,xp) % initialize n models
% [xx,ii,m,v]=psycestu(i,x,r) % supply a trial result to psycest
% psycestu(i) % plot pdf of model i
% [p,q]=psy... |
github | zclhit/HumanTimbre_recognition-master | sphrharm.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/sphrharm.m | 15,641 | utf_8 | 583b696d66eda747778c90bcdd37a421 | function [u,v,w]=sphrharm(m,a,b,c,d)
%SPHRHARM forward and inverse spherical harmonic transform
%
% Suppose f(e,a) is a complex-valued function defined on the surface of the
% sphere (0<=e<=pi, 0<=a<2pi) where e=inclination=pi/2-elevation and
% a=azimuth. (0,*) is the North pole, (pi/2,0) is on the equator near
% Ghan... |
github | zclhit/HumanTimbre_recognition-master | fxrapt.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/fxrapt.m | 16,559 | utf_8 | 157c2b6c23b20d99c453b4ee74b9a63a | function [fx,tt]=fxrapt(s,fs,mode)
%FXRAPT RAPT pitch tracker [FX,VUV]=(S,FS)
%
% Input: s(ns) Speech signal
% fs Sample frequency (Hz)
% mode 'g' will plot a graph [default if no output arguments]
% 'u' will include unvoiced fames (with fx=NaN)
%
% Outputs: fx... |
github | zclhit/HumanTimbre_recognition-master | estnoisem.m | .m | HumanTimbre_recognition-master/MFCC算法/voicebox/estnoisem.m | 15,221 | utf_8 | 6a14074277db7e51f081932463029532 | function [x,zo,xs]=estnoisem(yf,tz,pp)
%ESTNOISEM - estimate noise spectrum using minimum statistics
% Inputs:
% yf input power spectra (one row per frame)
% tz frame increment in seconds
% Alternatively, the input state from a previous call (see below)
% pp algorithm parameters [optional... |
github | Ian-Elliott/UAV-Navigation-master | CollisionMILP5_1.m | .m | UAV-Navigation-master/CollisionMILP5_1.m | 6,986 | utf_8 | cab3d220fd81765614e8068ef24f322a | function CollisionMILP5
%%Mixed integer linear programming of trajectory in 3 dimensional space
% with obstacle avoidance. Bounded by initial and final postion and
% velocity, max thrust, and total time.
%
% Accepts values for total time (tf), time step (dt), inital and final
% states (x0,v0,xf,vf), max thrust ... |
github | Ian-Elliott/UAV-Navigation-master | CollisionMILP5.m | .m | UAV-Navigation-master/CollisionMILP5.m | 6,980 | utf_8 | 546d762112d35da43a5a97926e8cfde8 | function CollisionMILP5
%%Mixed integer linear programming of trajectory in 3 dimensional space
% with obstacle avoidance. Bounded by initial and final postion and
% velocity, max thrust, and total time.
%
% Accepts values for total time (tf), time step (dt), inital and final
% states (x0,v0,xf,vf), max thrust ... |
github | qugank/PG-framework-master | pcaApply.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/pcaApply.m | 3,483 | utf_8 | 9daebac8a3d47d48bc44b7fe6ec75d1c | 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... |
github | qugank/PG-framework-master | forestTrain.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/forestTrain.m | 5,127 | utf_8 | e3945954c49ddb41e0d9b22400d78e15 | 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 vect... |
github | qugank/PG-framework-master | fernsRegTrain.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/fernsRegTrain.m | 6,127 | utf_8 | 850cfebd063c62615a4fc3f954a7252f | 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... |
github | qugank/PG-framework-master | rbfDemo.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/rbfDemo.m | 3,092 | utf_8 | d6d2ee9e5afdcd3dc89bd5a250c45a52 | 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
% ... |
github | qugank/PG-framework-master | pdist2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/pdist2.m | 5,407 | utf_8 | 952fc9c0a6b35dcc57a027af4a7ad0cd | 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)
% i... |
github | qugank/PG-framework-master | kmeans2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/classify/kmeans2.m | 5,423 | utf_8 | 32b4eebdf4217151a308fab75827072c | 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... |
github | qugank/PG-framework-master | imwrite2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/imwrite2.m | 5,313 | utf_8 | 2195d29af1562d15e6fad4637d558547 | 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, fNa... |
github | qugank/PG-framework-master | convnFast.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/convnFast.m | 9,445 | utf_8 | e2a4b0f585468ca748dbfbab44680681 | 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
... |
github | qugank/PG-framework-master | imMlGauss.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/imMlGauss.m | 5,902 | utf_8 | 0e7d1de8c0b463e6ca5e742f5764bb64 | 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 ... |
github | qugank/PG-framework-master | montage2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/montage2.m | 7,776 | utf_8 | 3163d18441b014c930fe981b270ffec8 | 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 = montag... |
github | qugank/PG-framework-master | imagesAlign.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/imagesAlign.m | 8,409 | utf_8 | 35c2785931e620bc56566f443a5823f7 | function [H,Ip] = imagesAlign( I, Iref, varargin )
% Fast and robust estimation of homography relating two images.
%
% The algorithm for image alignment is a simple but effective variant of
% the inverse compositional algorithm. For a thorough overview, see:
% "Lucas-kanade 20 years on A unifying framework,"
% ... |
github | qugank/PG-framework-master | jitterImage.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/jitterImage.m | 5,427 | utf_8 | 5eb14e974f08496e8c644c3ef94449f7 | 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 a... |
github | qugank/PG-framework-master | opticalFlow.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/opticalFlow.m | 6,116 | utf_8 | a61c22eeebabf4b2c24c94ff589a064a | function [Vx,Vy,reliab]=opticalFlow( I1, I2, varargin )
% Coarse-to-fine optical flow using Lucas&Kanade or Horn&Schunck.
%
% Implemented 'type' of optical flow estimation:
% LK: http://en.wikipedia.org/wiki/Lucas-Kanade_method
% HS: http://en.wikipedia.org/wiki/Horn-Schunck_method
% LK is a local, fast method ... |
github | qugank/PG-framework-master | movieToImages.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/movieToImages.m | 990 | utf_8 | c6c5bfd212a560ee433db20fb9c74a4c | 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' ); [... |
github | qugank/PG-framework-master | seqWriterPlugin.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/seqWriterPlugin.m | 8,542 | utf_8 | 973c86e6f71af0d127403a07a3706136 | function varargout = seqWriterPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow writing of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (swp=seqWriterPlugin):
% h=swp('open',h,fName,info) % Open a seq file for wri... |
github | qugank/PG-framework-master | kernelTracker.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/kernelTracker.m | 9,589 | utf_8 | 2f3663da7a41eef0b35b66db7bba9727 | 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 ... |
github | qugank/PG-framework-master | seqIo.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/seqIo.m | 17,520 | utf_8 | b43efa11c0eb13a1d17901e6952c5fb6 | 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: ... |
github | qugank/PG-framework-master | seqReaderPlugin.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/seqReaderPlugin.m | 9,904 | utf_8 | 6620312efc19b3446cab300d6b0688bb | 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 rea... |
github | qugank/PG-framework-master | bbGt.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/bbGt.m | 41,333 | utf_8 | 78756337ee8c8b7d6ca82f67e0aafefb | function varargout = bbGt( action, varargin )
% Bounding box (bb) annotations struct, evaluation and sampling routines.
%
% bbGt gives acces to three types of routines:
% (1) Data structure for storing bb image annotations.
% (2) Routines for evaluating the Pascal criteria for object detection.
% (3) Routines for... |
github | qugank/PG-framework-master | bbApply.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/images/bbApply.m | 21,861 | utf_8 | a9288f020170d81ad02e005142f5178a | 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 h... |
github | qugank/PG-framework-master | toolboxUpdateHeader.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/toolboxUpdateHeader.m | 2,411 | utf_8 | 27a6650cb107fbb7f4ec43d7191aedc1 | function toolboxUpdateHeader
% Update the headers of all the files.
%
% USAGE
% toolboxUpdateHeader
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
%
% See also
%
% Piotr's Image&Video Toolbox Version 3.02
% Copyright 2012 Piotr Dollar. [pdollar-at-caltech.edu]
% Please email me if you find bugs, or have sugg... |
github | qugank/PG-framework-master | toolboxGenDoc.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/toolboxGenDoc.m | 3,392 | utf_8 | 7682c27aa763c0a79a3c6dd8dca2b8ae | function toolboxGenDoc
% Generate documentation, must run from dir toolbox.
%
% 1) Make sure to run toolboxUpdateHeader.m
% 2) Update history.txt appropriately, including w current version
% 3) Update overview.html file with the version/data/link to zip:
% edit external/m2html/templates/frame-piotr/overview.h... |
github | qugank/PG-framework-master | toolboxHeader.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/toolboxHeader.m | 2,519 | utf_8 | 7530495be10750dc20e944da853d9793 | 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.
%
% Ne... |
github | qugank/PG-framework-master | mdot.m | .m | PG-framework-master/piotr_toolbox_V3.02/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 | qugank/PG-framework-master | m2html.m | .m | PG-framework-master/piotr_toolbox_V3.02/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 | qugank/PG-framework-master | doxysearch.m | .m | PG-framework-master/piotr_toolbox_V3.02/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 | qugank/PG-framework-master | doxywrite.m | .m | PG-framework-master/piotr_toolbox_V3.02/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 | qugank/PG-framework-master | doxyread.m | .m | PG-framework-master/piotr_toolbox_V3.02/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 | qugank/PG-framework-master | imwrite2split.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/imwrite2split.m | 1,664 | utf_8 | 8fa6eef9378b3b9aa633d6c096cd78f7 | % 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 = ... |
github | qugank/PG-framework-master | playmovies.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/playmovies.m | 1,997 | utf_8 | 6d94553879ed29dca7238d26459ec685 | % [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 ... |
github | qugank/PG-framework-master | pca_apply_large.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/pca_apply_large.m | 2,132 | utf_8 | daf33ba3f73412c5d5b488d89b7cc495 | % 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... |
github | qugank/PG-framework-master | montages2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/montages2.m | 2,335 | utf_8 | 3ff14e5c538db6af4c9e1c99144d7c15 | % 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] )
%
% ... |
github | qugank/PG-framework-master | filter_gauss_1D.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/filter_gauss_1D.m | 1,178 | utf_8 | 42acb7f8ac4ce94b6dc1dabe1e51e313 | % 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 o... |
github | qugank/PG-framework-master | clfEcoc.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/clfEcoc.m | 1,539 | utf_8 | 3cb7110d53d7eefcca505365b078fe8e | 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 ... |
github | qugank/PG-framework-master | getargs.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/getargs.m | 3,550 | utf_8 | b8ee235c28195894f0743b6cd00fd609 | % 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 ... |
github | qugank/PG-framework-master | normxcorrn_fg.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/normxcorrn_fg.m | 2,771 | utf_8 | c0817b10bbc5d1793efad5fa7b4932ac | % 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 sp... |
github | qugank/PG-framework-master | makemovie.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/makemovie.m | 1,313 | utf_8 | 7cadf737855cee5cb9a336e1204773c4 | % [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' );
% ... |
github | qugank/PG-framework-master | localsum_block.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/localsum_block.m | 845 | utf_8 | d420d188aa320337183491498c7cc483 | % 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
%... |
github | qugank/PG-framework-master | imrotate2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/imrotate2.m | 1,367 | utf_8 | 21148eb1e941255d74de56b5cb8994b1 | % 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 - ['linea... |
github | qugank/PG-framework-master | imSubsResize.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/imSubsResize.m | 1,379 | utf_8 | 7bcc46113f2b8619d539a20ecb5a1835 | % 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 ... |
github | qugank/PG-framework-master | imtranslate.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/imtranslate.m | 1,221 | utf_8 | 8a46326f7c0b520a89e2c4a153118ec9 | % 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 ... |
github | qugank/PG-framework-master | randperm2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/randperm2.m | 1,444 | utf_8 | b8dc96688b2afddb3bd486803d3847b5 | % 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 ... |
github | qugank/PG-framework-master | apply_homography.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/apply_homography.m | 3,676 | utf_8 | 18c79558e14e422d02c755d8363c7460 | % 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'.... |
github | qugank/PG-framework-master | pca_apply.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/pca_apply.m | 2,506 | utf_8 | 4f38cdb1a3375943269e24dc6be6af65 | % 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
% ... |
github | qugank/PG-framework-master | mode2.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/deprecated/mode2.m | 765 | utf_8 | f6b3681635cfe16059c5483214fb9814 | % 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
% ... |
github | qugank/PG-framework-master | savefig.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/external/other/savefig.m | 13,343 | utf_8 | 5e55383fee448146f66f14d4c342b027 | 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 | qugank/PG-framework-master | dirSynch.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/dirSynch.m | 4,760 | utf_8 | 98722043acf461badcbf811797e8f35c | 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 date... |
github | qugank/PG-framework-master | plotRoc.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/plotRoc.m | 5,406 | utf_8 | 8d6c2235af0c959488807084ff4817e3 | 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 ... |
github | qugank/PG-framework-master | simpleCache.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/simpleCache.m | 4,293 | utf_8 | 22f799042e5c852998fa3462c9363fc7 | 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 sa... |
github | qugank/PG-framework-master | tpsInterpolate.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/tpsInterpolate.m | 1,760 | utf_8 | 718883df87f2cad99fe591d11b8693db | 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] ... |
github | qugank/PG-framework-master | checkNumArgs.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/checkNumArgs.m | 3,968 | utf_8 | 262a28a0ba12c107b0244a10b38606ae | 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 se... |
github | qugank/PG-framework-master | fevalDistr.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/matlab/fevalDistr.m | 12,765 | utf_8 | 3f490cb79ce1134078e2a18e6a47afba | 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 b... |
github | qugank/PG-framework-master | medfilt1m.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/filters/medfilt1m.m | 3,138 | utf_8 | 0ae9cc23ba8aec631160413b125a39a2 | 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 contai... |
github | qugank/PG-framework-master | FbMake.m | .m | PG-framework-master/piotr_toolbox_V3.02/toolbox/filters/FbMake.m | 6,962 | utf_8 | de8baf5b056d6d153f8ae0755ade2de5 | 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
% - i... |
github | qugank/PG-framework-master | boxesEval.m | .m | PG-framework-master/EdgeDetector/boxesEval.m | 5,226 | utf_8 | d74a48569e7de4191347e67e7c4ea02b | function recall = boxesEval( varargin )
% Perform object proposal bounding box evaluation and plot results.
%
% boxesEval evaluates a set bounding box object proposals on the dataset
% specified by the 'data' parameter (which is generated by boxesData.m).
% The methods are specified by the vector 'names'. For each... |
github | qugank/PG-framework-master | edgesEvalDir.m | .m | PG-framework-master/EdgeDetector/edgesEvalDir.m | 5,991 | utf_8 | bc4e65f28e28fd592f0e7886df40b820 | function varargout = edgesEvalDir( varargin )
% Calculate edge precision/recall results for directory of edge images.
%
% Enhanced replacement for boundaryBench() from BSDS500 code:
% http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/
% Uses same format for results and is fully compatible with bou... |
github | qugank/PG-framework-master | edgeBoxesSweeps.m | .m | PG-framework-master/EdgeDetector/edgeBoxesSweeps.m | 3,242 | utf_8 | 914d338eaade4ff821dfe9ef9de96a8c | function edgeBoxesSweeps()
% Parameter sweeps for Edges Boxes object proposals.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Structured Edge Detection Toolbox Version 3.01
% Code written by Piotr Dollar and Larry Zitnick, 2... |
github | qugank/PG-framework-master | edgesTrain.m | .m | PG-framework-master/EdgeDetector/edgesTrain.m | 13,669 | utf_8 | c29662f392dd5074db27a50767e39cef | function model = edgesTrain( varargin )
% Train structured edge detector.
%
% For an introductory tutorial please see edgesDemo.m.
%
% USAGE
% opts = edgesTrain()
% model = edgesTrain( opts )
%
% INPUTS
% opts - parameters (struct or name/value pairs)
% (1) model parameters:
% .imWidth - [32] width of i... |
github | qugank/PG-framework-master | spAffinities.m | .m | PG-framework-master/EdgeDetector/spAffinities.m | 4,319 | utf_8 | b2250da9ac5335d5dfcc28f819efd35e | function [A,E,U] = spAffinities( S, E, segs, nThreads )
% Compute superpixel affinities and optionally corresponding edge map.
%
% Computes an m x m affinity matrix A where A(i,j) is the affinity between
% superpixels i and j. A has values in [0,1]. Only affinities between
% spatially nearby superpixels are comput... |
github | qugank/PG-framework-master | edgesSweeps.m | .m | PG-framework-master/EdgeDetector/edgesSweeps.m | 8,831 | utf_8 | c36ed011e7daa4ea08d83453e0cf8125 | function edgesSweeps()
% Parameter sweeps for structured edge detector.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Structured Edge Detection Toolbox Version 3.01
% Code written by Piotr Dollar, 2014.
% Licensed under the ... |
github | qugank/PG-framework-master | findendsjunctions.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/findendsjunctions.m | 3,378 | utf_8 | 9de4b89d8f3794b533f458929bea85db | % FINDENDSJUNCTIONS - find junctions and endings in a line/edge image
%
% Usage: [rj, cj, re, ce] = findendsjunctions(edgeim, disp)
%
% Arguments: edgeim - A binary image marking lines/edges in an image. It is
% assumed that this is a thinned or skeleton image (or
% nearly s... |
github | qugank/PG-framework-master | maxlinedev.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/maxlinedev.m | 2,478 | utf_8 | 64cc6d88009aa2a148c843e2d4041218 | % MAXLINEDEV - Find max deviation from a line in an edge contour.
%
% Function finds the point of maximum deviation from a line joining the
% endpoints of an edge contour.
%
% Usage: [maxdev, index, D, totaldev] = maxlinedev(x,y)
%
% Arguments:
% x, y - arrays of x,y (col,row) indicies of connected pixels... |
github | qugank/PG-framework-master | drawedgelist.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/drawedgelist.m | 3,494 | utf_8 | 8378ba1176974d3b4fabb26d7e56cab8 | % DRAWEDGELIST - plots pixels in edgelists
%
% Usage: h = drawedgelist(edgelist, rowscols, lw, col, figno)
%
% Arguments:
% edgelist - Cell array of edgelists in the form
% { [r1 c1 [r1 c1 etc }
% ...
% rN cN] ....]
% rowscols - Optio... |
github | qugank/PG-framework-master | lineseg.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/lineseg.m | 3,017 | utf_8 | ff2e4a5d3f9faabdf548561ed00b22b6 | % LINESEG - Form straight line segements from an edge list.
%
% Usage: seglist = lineseg(edgelist, tol)
%
% Arguments: edgelist - Cell array of edgelists where each edgelist is an
% Nx2 array of (row col) coords.
% tol - Maximum deviation from straight line before a
% ... |
github | qugank/PG-framework-master | cleanedgelist.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/cleanedgelist.m | 13,314 | utf_8 | a79468f2b92f2ce262730a04d766d643 | % CLEANEDGELIST - remove short edges from a set of edgelists
%
% Function to clean up a set of edge lists generated by EDGELINK so that
% isolated edges and spurs that are shorter that a minimum length are removed.
% This code can also be use with a set of line segments generated by LINESEG.
%
% Usage: nedgelist = clea... |
github | qugank/PG-framework-master | edgelink.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/edgelink.m | 13,347 | utf_8 | 3e10d0cde6d34538fe0b017e715a3a79 | % EDGELINK - Link edge points in an image into lists
%
% Usage: [edgelist edgeim] = edgelink(im, minlength, location)
%
% Arguments: im - Binary edge image, it is assumed that edges
% have been thinned.
% minlength - Optional minimum edge length of interest, defaults
% ... |
github | qugank/PG-framework-master | edgelist2image.m | .m | PG-framework-master/Edge Linking and Line Segment Fitting/edgelist2image.m | 2,027 | utf_8 | 5c5436b3f23a712f883ddb43a21e1d1c | % EDGELIST2IMAGE - transfers edgelist data back into a 2D image array
%
% Usage: im = edgelist2image(edgelist, rowscols)
%
% edgelist - Cell array of edgelists in the form
% { [r1 c1 [r1 c1 etc }
% ...
% rN cN] ....]
% rowscols - Opt... |
github | qugank/PG-framework-master | RanksvmScore.m | .m | PG-framework-master/matlab/RanksvmScore.m | 2,173 | utf_8 | 7f2265b79ff6ddd3d23c8b87d72e5aed | function score = RanksvmScore( SegmentA,SegmentB,RelativeImp)
%RANKSVMSCORE Scoring by RankSVM based on two Gestalt principles (proximity and continuity)
% proximity
endpointA1 = SegmentA(1, :);
endpointA2 = SegmentA(end, :);
endpointB1 = SegmentB(1, :);
endpointB2 = SegmentB(end, :);
distance1 = ComputeDistan... |
github | qugank/PG-framework-master | GraphConstructRsvm.m | .m | PG-framework-master/matlab/GraphConstructRsvm.m | 1,459 | utf_8 | a40bbd77f7bf73aa69bd2c580d3ee016 | function graph = GraphConstructRsvm( ConSegList,seeds )
%GRAPHCONSTRUCTRSVM Edge segments construction
EdgeW = [];
EdgeIndr = [];
EdgeIndc = [];
for i = 1:size(seeds,1)
SegmentA = ConSegList{1,seeds(i)};
for j = 1:size(seeds,1)
SegmentB = ConSegList{1,seeds(j)};
... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_semisupervised_regression_variational_train.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_semisupervised_regression_variational_train.m | 6,494 | utf_8 | a36d139e7aad7eb336b0fe211808cc11 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function state = kbmf1mkl1mkl_semisupervised_regression_variational_train(Kx, Kz, Y, parameters)
rand('state', parameters.seed); %#ok<RAND>
randn('state', parameters.seed); %#ok<RAND>
Dx = size(Kx, 1);
Nx = size(Kx, 2);
Px = size(Kx, 3);
Dz = size(Kz, 1)... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_semisupervised_regression_variational_test.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_semisupervised_regression_variational_test.m | 882 | utf_8 | d0523c7484d0598c9ad2127800bf7f49 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function prediction = kbmf1mkl1mkl_semisupervised_regression_variational_test(Kx, Kz, state)
Nx = size(Kx, 2);
Px = size(Kx, 3);
Nz = size(Kz, 2);
Pz = size(Kz, 3);
R = size(state.Ax.mu, 2);
prediction.Gx.mu = zeros(R, Nx, Px);
for m = 1:Px
p... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_supervised_regression_variational_test.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_supervised_regression_variational_test.m | 878 | utf_8 | 6c1f01e845091ad10b9052159eda169a | % Mehmet Gonen (mehmet.gonen@gmail.com)
function prediction = kbmf1mkl1mkl_supervised_regression_variational_test(Kx, Kz, state)
Nx = size(Kx, 2);
Px = size(Kx, 3);
Nz = size(Kz, 2);
Pz = size(Kz, 3);
R = size(state.Ax.mu, 2);
prediction.Gx.mu = zeros(R, Nx, Px);
for m = 1:Px
predi... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_semisupervised_classification_variational_train.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_semisupervised_classification_variational_train.m | 7,163 | utf_8 | 99d584eff4fa6d8f66dd708660c62a60 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function state = kbmf1mkl1mkl_semisupervised_classification_variational_train(Kx, Kz, Y, parameters)
rand('state', parameters.seed); %#ok<RAND>
randn('state', parameters.seed); %#ok<RAND>
Dx = size(Kx, 1);
Nx = size(Kx, 2);
Px = size(Kx, 3);
Dz = size(Kz... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_supervised_classification_variational_test.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_supervised_classification_variational_test.m | 882 | utf_8 | 25267d69815b17c51c5035ec9b048449 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function prediction = kbmf1mkl1mkl_supervised_classification_variational_test(Kx, Kz, state)
Nx = size(Kx, 2);
Px = size(Kx, 3);
Nz = size(Kz, 2);
Pz = size(Kz, 3);
R = size(state.Ax.mu, 2);
prediction.Gx.mu = zeros(R, Nx, Px);
for m = 1:Px
p... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_supervised_classification_variational_train.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_supervised_classification_variational_train.m | 6,699 | utf_8 | 405d9b240d140d6e40888c10aae1f851 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function state = kbmf1mkl1mkl_supervised_classification_variational_train(Kx, Kz, Y, parameters)
rand('state', parameters.seed); %#ok<RAND>
randn('state', parameters.seed); %#ok<RAND>
Dx = size(Kx, 1);
Nx = size(Kx, 2);
Px = size(Kx, 3);
Dz = size(Kz, 1)... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_semisupervised_classification_variational_test.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_semisupervised_classification_variational_test.m | 886 | utf_8 | 93eb41d69c5e5f3fda4a90b7b111cfb4 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function prediction = kbmf1mkl1mkl_semisupervised_classification_variational_test(Kx, Kz, state)
Nx = size(Kx, 2);
Px = size(Kx, 3);
Nz = size(Kz, 2);
Pz = size(Kz, 3);
R = size(state.Ax.mu, 2);
prediction.Gx.mu = zeros(R, Nx, Px);
for m = 1:Px
... |
github | ThomasBrouwer/HMF-master | kbmf1mkl1mkl_supervised_regression_variational_train.m | .m | HMF-master/drug_sensitivity/cross_validation/kbmf/kbmf1mkl1mkl/kbmf1mkl1mkl_supervised_regression_variational_train.m | 6,040 | utf_8 | 573e4c3cce21b8441572625c37716fb1 | % Mehmet Gonen (mehmet.gonen@gmail.com)
function state = kbmf1mkl1mkl_supervised_regression_variational_train(Kx, Kz, Y, parameters)
rand('state', parameters.seed); %#ok<RAND>
randn('state', parameters.seed); %#ok<RAND>
Dx = size(Kx, 1);
Nx = size(Kx, 2);
Px = size(Kx, 3);
Dz = size(Kz, 1);
... |
github | abhishek4747/imagenet2010-devkit-master | compress_sbow.m | .m | imagenet2010-devkit-master/feature/compress_sbow.m | 256 | utf_8 | 8be502abafdb9d5d0734e83e53a7a68a | function input = compress_sbow(input)
for i=1:numel(input)
input(i).sbow = compress_v(input(i).sbow);
end
function w=compress_v(w)
w.x = single(w.x);
w.y = single(w.y);
w.scale = int8(w.scale);
w.norm = single(w.norm);
w.word = int16(w.word);
|
github | abhishek4747/imagenet2010-devkit-master | compress_vldsift.m | .m | imagenet2010-devkit-master/feature/compress_vldsift.m | 259 | utf_8 | 05cc7188848e9717f17a4925267d600c | function input = compress_vldsift(input)
for i=1:numel(input)
input(i).vldsift = compress_v(input(i).vldsift);
end
function w=compress_v(w)
w.x = single(w.x);
w.y = single(w.y);
w.scale = int8(w.scale);
w.norm = single(w.norm);
w.desc = single(w.desc);
|
github | abhishek4747/imagenet2010-devkit-master | vl_compile.m | .m | imagenet2010-devkit-master/feature/3rd-party/vlfeat/toolbox/vl_compile.m | 3,344 | utf_8 | 447fabf6af82b7a70683ce4fe66d4186 | function vl_compile(useLcc)
% VL_COMPILE Compile MEX files
% VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command
% is needed moslty under Windows to re-build problematic binares.
%
% See also:: VL_HELP().
% AUTORIGHTS
if nargin < 1
warning('Assuming the LCC compiler. Please use vl_compile(false... |
github | abhishek4747/imagenet2010-devkit-master | vl_argparse.m | .m | imagenet2010-devkit-master/feature/3rd-party/vlfeat/toolbox/misc/vl_argparse.m | 1,530 | utf_8 | 4b0ccac45af25b8dd94c9c36bff2e8a2 | function [conf, args] = vl_argparse(conf, varargin)
% VL_ARGPARSE Parse option arguments
% CONF = VL_ARGPARSE(CONF, PAR1, VAL1, ... PARN, VALN) updates the
% structure CONF based on the specified parameter-value pairs. The
% function produces an error if an uknown parameter is passed in.
%
% [CONF, ARGS] = VL_... |
github | abhishek4747/imagenet2010-devkit-master | vl_override.m | .m | imagenet2010-devkit-master/feature/3rd-party/vlfeat/toolbox/misc/vl_override.m | 4,128 | utf_8 | 2c0019960a70d69561994fb8ddea175b | function config = vl_override(config,update,varargin)
% VL_OVERRIDE Override structure subset
% CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds of
% the structure UPDATE to the corresponding fields of the struture
% CONFIG.
%
% While CONFIG and UPDATE can arbitrary structures, usually CONFIG... |
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