plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | HzFu/VideoCoSeg_MSG-master | dfgraphexclude.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfgraphexclude.m | 11,965 | utf_8 | ff8e69b2697cd9fd7e593aa8f323e7ab | function dfgraphexclude(dsname,xlo,xhi)
%DFGRAPHEXCLUDE Create graph for selecting (x,y) pairs to exclude
% DFGRAPHEXCLUDE(EXCLUDEPANEL,DSNAME,LOBND,UPBND) creates a graph
% tied to the Java exclusion panel EXCLUDEPANEL, for dataset DSNAME, with
% current lower and upper bounds LOBND and UPBND. It provides a gr... |
github | HzFu/VideoCoSeg_MSG-master | statglmeval.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/statglmeval.m | 3,168 | utf_8 | 98ac5b2371c64f178386fc4edc80d77b | function retval=statglmeval(action,fn,varargin)
%STATGLMEVAL Evaluate or test link function in proper environment
% STATGLMEVAL('eval',FN,ARGS,...) evaluates the function FN in an
% environment in which certain functions such as LOGIT and
% D_LOGIT are defined. This allows the function FN to be either
% a use... |
github | HzFu/VideoCoSeg_MSG-master | im2mis.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/im2mis.m | 5,031 | utf_8 | ed612a7fa662f25817b2742f636c83e8 | function mis = im2mis(varargin)
%IM2MIS Convert image to Java MemoryImageSource.
%
% MIS = IM2MIS(I) converts the intensity image I to a Java
% MemoryImageSource.
%
% MIS = IM2MIS(X,MAP) converts the indexed image X with colormap MAP to a
% Java MemoryImageSource.
%
% MIS = IM2MIS(RGB) converts the RGB image ... |
github | HzFu/VideoCoSeg_MSG-master | dfcustomdist.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfcustomdist.m | 6,194 | utf_8 | 75dd6db6d545865f7218add1c516a353 | function dfcustomdist(ignore1,ignore2,action)
%DFCUSTOM Callbacks for menu items related to custom distributions
% $Revision: 1.1.6.3 $ $Date: 2004/02/01 22:10:36 $
% Copyright 2003-2004 The MathWorks, Inc.
fnpath = which('dfittooldists.m');
dft = com.mathworks.toolbox.stats.DistributionFitting.getDistributionFi... |
github | HzFu/VideoCoSeg_MSG-master | addtls.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addtls.m | 6,220 | utf_8 | a3e59b1843fd4a619b0af6ccf0515470 | function s = addtls(s)
%ADDTLS Add the t location-scale distribution.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.7 $ $Date: 2004/01/24 09:35:08 $
j = length(s) + 1;
s(j).name = 't location-scale';
s(j).code = 'tlocationscale';
s(j).pnames = {'mu' 'sigma' 'nu'};
s(j).pdescription = {'location' '... |
github | HzFu/VideoCoSeg_MSG-master | dffig2m.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dffig2m.m | 27,041 | utf_8 | 6271ee715d3cc8f2d3beb6502425fa8d | function dffig2m(dffig,outfilename)
%DFFIG2M Turn figure into an M file that can produce the figure
% $Revision: 1.1.6.12 $ $Date: 2004/03/22 23:55:33 $
% Copyright 2003-2004 The MathWorks, Inc.
dsdb = getdsdb;
fitdb = getfitdb;
if isempty(down(dsdb)) && isempty(down(fitdb))
emsg = 'Cannot save M file when no... |
github | HzFu/VideoCoSeg_MSG-master | dfcreateplot.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfcreateplot.m | 4,044 | utf_8 | 5f3f14c9c9e3b02534f6c47f82f9d901 | function dffig = dfcreateplot
%DFCREATEPLOT Create plot window for DFITTOOL
% $Revision: 1.1.6.8 $ $Date: 2004/03/09 16:17:03 $
% Copyright 2003-2004 The MathWorks, Inc.
% Get some screen and figure position measurements
tempFigure=figure('visible','off','units','pixels',...
'Tag','Distribution... |
github | HzFu/VideoCoSeg_MSG-master | dftoolinittemplate.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dftoolinittemplate.m | 6,341 | utf_8 | 75c97e650face984cbf4f1aea9014bf4 | function s = dfittooldists
%DFITTOOLDISTS Initialize dfittool with custom distributions.
%
% S=DFITTOOLDISTS is called during the initialization of DFITTOOL to get
% any custom distributions you may want to define. This function should
% appear somewhere on your MATLAB path. You can edit it to define
% di... |
github | HzFu/VideoCoSeg_MSG-master | dftips.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dftips.m | 6,165 | utf_8 | 317736e5c3583d9f8170cb10bc0aafa4 | function dftips(varargin)
%DFTIPS Display data and fit tips for Distribution Fitting figure
%No input arguments are used here.
% $Revision: 1.1.6.4 $ $Date: 2004/01/24 09:35:52 $
% Copyright 2001-2004 The MathWorks, Inc.
dffig = gcbf;
if ~isequal(get(dffig,'SelectionType'),'normal')
return;
end
h = hittest... |
github | HzFu/VideoCoSeg_MSG-master | APPfitGroundHough.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/vrml/APPfitGroundHough.m | 14,089 | utf_8 | e081b75b7ee4d4be889652280d3db8ac | function pobjs = APPfitGroundHough(x,y, imsize)
% pobjs = APPfitGroundHough(x,y, imsize)
% Fits the ground-vertical boundary with a set of polylines
%
% Input:
% x, y: the x and y positions of ground-vertical boundaries
% imsize: the image size
% Output:
% pobjs(nplanes, [m b x1 x2 maxy disconnect])
%
% Copyright... |
github | HzFu/VideoCoSeg_MSG-master | APPlabels2planes.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/vrml/APPlabels2planes.m | 12,555 | utf_8 | a9a5cf80efa6e6b355afb919494fb8cf | function [gplanes, vplanes, gim, vim] = ...
APPlabels2planes(vlabels, hlabels, hy, segimage, image)
% [gplanes, vplanes, gim, vim] = ...
% APPlabels2planes(vlabels, hlabels, hy, segimage, image)
% Converts a label map into a set of planes
%
% planes(nplanes).{inds(npoints), vertices(1:2, npoints), label}
% gim a... |
github | HzFu/VideoCoSeg_MSG-master | APPestimateHorizon.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/geom/APPestimateHorizon.m | 2,200 | utf_8 | bb9037f8116f5d9cf91897fa49454f12 | function y_h = APPestimateHorizon(lines)
% Estimates horizon position of image
% lines should be normalized according to size of image
% need to multiply output by mean(imsize(1:2)) to get pixel value
%
% Copyright(C) Derek Hoiem, Carnegie Mellon University, 2005
% Permission granted to non-commercial enterprises for
%... |
github | HzFu/VideoCoSeg_MSG-master | iccvTrainUnary.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/iccv07/iccvTrainUnary.m | 5,589 | utf_8 | 63170791ca1e5d231ab640a09b535f7a | function w = iccvTrainUnary
% iccvTrainUnary
outdir = '/usr1/projects/GeometricContext/data/iccv07/train/unary/';
classifiers = load('/usr1/projects/GeometricContext/data/ijcv06/ijcvClassifier.mat');
load('/usr1/projects/GeometricContext/data/allimsegs2.mat');
load('/usr1/projects/GeometricContext/data/rand_indices.m... |
github | HzFu/VideoCoSeg_MSG-master | iccvTestUnary.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/iccv07/iccvTestUnary.m | 5,995 | utf_8 | 09c5049e6545568a0f8a75befad076cf | function [vacc2, hacc2, vcm2, hcm2, cimages2] = iccvTestUnary(w)
% iccvTrainUnary
outdir = '/usr1/projects/GeometricContext/data/iccv07/test/unary/';
%classifiers = load('/usr1/projects/GeometricContext/data/ijcv06/ijcvClassifier.mat');
tmp = load('/usr1/projects/GeometricContext/data/ijcv06/multisegResults2.mat');
p... |
github | HzFu/VideoCoSeg_MSG-master | ijcvTestImage2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/ijcv06/ijcvTestImage2.m | 3,536 | utf_8 | 7a019410d73b9bfe216933bba300a8d4 | function [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps, spdata, adjlist, edata)
% [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps,
% spdata, adjlist, edata)
%
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edata are optional inputs
% Note: o... |
github | HzFu/VideoCoSeg_MSG-master | ijcvTestImage_noNormalization.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/ijcv06/ijcvTestImage_noNormalization.m | 3,718 | utf_8 | e9b7bc65895e04cb966bb5db3f8335a8 | function [pg, data, imsegs, smaps] = ijcvTestImage_noNormalization(im, imsegs, ...
classifiers, smaps, spdata, adjlist, edata)
% [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps,
% spdata, adjlist, edata)
%
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edat... |
github | HzFu/VideoCoSeg_MSG-master | ijcvTestImage.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/ijcv06/ijcvTestImage.m | 3,474 | utf_8 | cc380144b862ef95e8f769b546ed717f | function [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps, spdata, adjlist, edata)
% [pg, data, imsegs] = ijcvTestImage(im, imsegs, classifiers, smaps,
% spdata, adjlist, edata)
%
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edata are optional inputs
% Note: o... |
github | HzFu/VideoCoSeg_MSG-master | makeLMfilters.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/textons/makeLMfilters.m | 1,924 | utf_8 | 3b72a66373a5ffc869a4e755de3d6b3d | function F=makeLMfilters
% Returns the LML filter bank of size 49x49x48 in F. To convolve an
% image I with the filter bank you can either use the matlab function
% conv2, i.e. responses(:,:,i)=conv2(I,F(:,:,i),'valid'), or use the
% Fourier transform.
SUP=19;%49; % Support of the largest filter (mus... |
github | HzFu/VideoCoSeg_MSG-master | crfTrainInteractionPotential.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfTrainInteractionPotential.m | 2,062 | utf_8 | bfb115e80e881bbdd2974d7bc8b71cb9 | function params = crfTrainInteractionPotential(imsegs, adjlist, pE)
nlab = numel(imsegs(1).label_names);
% get label priors
pLab = zeros(1, nlab);
for f = 1:numel(imsegs)
npix = imsegs(f).npixels / sum(imsegs(f).npixels);
for k = 1:imsegs(f).nseg
if imsegs(f).labels(k)~=0
pLab(imsegs(f).la... |
github | HzFu/VideoCoSeg_MSG-master | crfTestCV.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfTestCV.m | 2,774 | utf_8 | f31f6bed4059e0508a062379332600e2 | function [vacc, hacc, vcm, hcm, pg] = crfTestCV(imsegs, pvSP, phSP, adjlist, pE, crfw)
ncv = numel(crfw);
nimages = numel(imsegs);
for f = 1:nimages
disp(num2str(f))
c = ceil(f/nimages*ncv);
pg{f} = crfTestImage(pvSP{f}, phSP{f}, adjlist{f}, pE{f}, crfw{c});
[tmpvacc2, tmphacc2] = mcmcProcessResul... |
github | HzFu/VideoCoSeg_MSG-master | crfPairwiseTrain3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfPairwiseTrain3.m | 4,520 | utf_8 | afe0332fcaa9f0fb0e810e93b83654dd | function [crfw, priors] = crfPairwiseTrain(imsegs, pvSP, phSP, adjlist, pE, params, edgelen)
global itercount;
itercount = 0;
vlab = {imsegs(:).vert_labels};
hlab = {imsegs(:).horz_labels};
spweight = {imsegs(:).npixels};
for f = 1:numel(imsegs)
spweight{f} = spweight{f} / sum(spweight{f});
end
% get f1(y1, y2) ... |
github | HzFu/VideoCoSeg_MSG-master | crfPLTrain.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfPLTrain.m | 4,552 | utf_8 | ad5b0b6bdc435da18cd01c2971cf7d19 | function crfw = crfPLTrain(vlab, hlab, pvSP, phSP, adjlist, pE)
% get f1(y1, y2) = log(P(y1|x)) + log(P(y2|x))
% and f2(y1, y2) = I(y1=y2)*log(P(y1=y2|x)) + I(y1~=y2)*log(P(y1~=y2|x))
npair = 0;
for f = 1:numel(adjlist)
npair = npair + size(adjlist{f}, 1);
end
f1 = zeros(npair, 49);
f2 = zeros(npair, 49);
lab = ... |
github | HzFu/VideoCoSeg_MSG-master | crfTestCV2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfTestCV2.m | 3,613 | utf_8 | 355ee76e4358af788f42a9099d18e2c1 | function [vacc, hacc, vcm, hcm, pg] = crfTestCV2(imsegs, pvSP, phSP, adjlist, pE, crfw, param, edgelen)
ncv = numel(crfw);
nimages = numel(imsegs);
for f = 1:nimages
disp(num2str(f))
c = ceil(f/nimages*ncv);
pg{f} = crfTestImage(pvSP{f}, phSP{f}, adjlist{f}, pE{f}, crfw{c}, param{c}, edgelen{f});
... |
github | HzFu/VideoCoSeg_MSG-master | crfPairwiseTrain.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfPairwiseTrain.m | 2,581 | utf_8 | b0ccc5b1f0ea237dc47adf580852c1cb | function crfw = crfPairwiseTrain(vlab, hlab, pvSP, phSP, adjlist, pE)
% get f1(y1, y2) = log(P(y1|x)) + log(P(y2|x))
% and f2(y1, y2) = I(y1=y2)*log(P(y1=y2|x)) + I(y1~=y2)*log(P(y1~=y2|x))
npair = 0;
for f = 1:numel(adjlist)
npair = npair + size(adjlist{f}, 1);
end
f1 = zeros(npair, 49);
f2 = zeros(npair, 49);... |
github | HzFu/VideoCoSeg_MSG-master | crfPLTrain2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfPLTrain2.m | 5,780 | utf_8 | 16d20ede39a8f4028a6ab8cb1237a308 | function crfw = crfPLTrain2(vlab, hlab, pvSP, phSP, adjlist, pE, params)
% get f1(y1, y2) = log(P(y1|x)) + log(P(y2|x))
% and f2(y1, y2) = I(y1=y2)*log(P(y1=y2|x)) + I(y1~=y2)*log(P(y1~=y2|x))
npair = 0;
for f = 1:numel(adjlist)
npair = npair + size(adjlist{f}, 1);
end
f1 = zeros(npair, 49);
f2 = zeros(npair, 49... |
github | HzFu/VideoCoSeg_MSG-master | crfTestCV3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfTestCV3.m | 3,673 | utf_8 | ee2c503d70d580dfe1e1a7f70e317d2d | function [vacc, hacc, vcm, hcm, pg] = crfTestCV3(imsegs, pvSP, phSP, adjlist, pE, crfw, param, edgelen, priors)
ncv = numel(crfw);
nimages = numel(imsegs);
for f = 1:nimages
disp(num2str(f))
c = ceil(f/nimages*ncv);
pg{f} = crfTestImage(pvSP{f}, phSP{f}, adjlist{f}, pE{f}, crfw{c}, param{c}, edgelen{f... |
github | HzFu/VideoCoSeg_MSG-master | crfPairwiseTrain2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/crf/crfPairwiseTrain2.m | 3,818 | utf_8 | 7c998f6d7df8d7292d2de912d7ad8fe3 | function crfw = crfPairwiseTrain(vlab, hlab, pvSP, phSP, adjlist, pE, params, edgelen)
% get f1(y1, y2) = log(P(y1|x)) + log(P(y2|x))
% and f2(y1, y2) = I(y1=y2)*log(P(y1=y2|x)) + I(y1~=y2)*log(P(y1~=y2|x))
npair = 0;
for f = 1:numel(adjlist)
npair = npair + size(adjlist{f}, 1);
end
f1 = zeros(npair, 49);
f2 = ... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGenerateGoodSegments.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGenerateGoodSegments.m | 5,455 | utf_8 | 8b20cbdf50a4fe3b6e62c8d0f030b6bf | function [features, labels, labelprobs, weights] = ...
mcmcGenerateGoodSegments(im, imsegs, vclassifierSP, hclassifierSP,eclassifier, ...
segclassifier, spdata, adjlist, edata)
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edata are optional inputs
niter = 2500;
feature... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentClassifier3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentClassifier3.m | 1,379 | utf_8 | e8273f424f264edbe15f18f2206e0a94 | function [vclassifier, hclassifier] = mcmcTrainSegmentClassifier3(features, vlabels, hlabels, vw, hw)
ntrees = 20;
nnodes = 16;
maxdata = 30000;
[vdata, vlab, vw] = formatData(features, vlabels, vw, maxdata);
[hdata, hlab, hw] = formatData(features, hlabels, hw, maxdata);
vnames = {'000', '090', 'sky'};
hnames = {... |
github | HzFu/VideoCoSeg_MSG-master | testImagesSuperpixels.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/testImagesSuperpixels.m | 1,498 | utf_8 | ce7c0a569a25cdea608ea50117645bde | function [vacc, hacc, vcm, hcm] = testImagesSuperpixels(imsegs, vclassifierSP, hclassifierSP, spdata)
vacc = 0;
hacc = 0;
vtotal = 0;
htotal = 0;
vcm = zeros(3);
hcm = zeros(5);
for f = 1:numel(imsegs)
[pv, ph] = spClassify(spdata{f}, vclassifierSP, hclassifierSP);
[vmaxval, vmax] = max(pv, [], 2);
[h... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentRegressor.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentRegressor.m | 2,342 | utf_8 | 6d360cd100adb7909b630835d58284e6 | function [vclassifier, hclassifier] = mcmcTrainSegmentRegressor(features, labelprobs, weights)
ntrees = 20;
nnodes = 8;
maxdata = 30000;
for f = 1:numel(labelprobs)
vprobs{f} = [labelprobs{f}(:, 1) sum(labelprobs{f}(:, 2:6), 2) labelprobs{f}(:, 7)];
ind = find(vprobs{f}(:, 2)~=0);
hprobs{f} = zeros(size(... |
github | HzFu/VideoCoSeg_MSG-master | testSuperpixelCCImagesCV.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/testSuperpixelCCImagesCV.m | 1,939 | utf_8 | e6e9529a19aa033061a4632ff0c27f8e | function [vacc, hacc, vcm, hcm] = testSuperpixelCCImagesCV(imsegs, vclassifier, hclassifier, segdata, smap, ncv)
vacc = 0;
hacc = 0;
vtotal = 0;
htotal = 0;
vcm = zeros(3);
hcm = zeros(5);
nimages = numel(imsegs);
for f = 1:nimages
k = ceil(f / (nimages/ncv));
[pv, ph] = segClassify(segdata{f}, ... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestImage.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestImage.m | 6,819 | utf_8 | 9e186e2858a7a38055e5e6ab3fd836a9 | function [pg, pgIter] = mcmcTestImage(im, imsegs, vclassifierSP, hclassifierSP, ...
eclassifier, vclassifier, hclassifier, segclassifier, niter, spdata, adjlist, edata)
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edata are optional inputs
DO_LABEL = 1;
grayim = rgb2gray(i... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestImageSA.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestImageSA.m | 13,398 | utf_8 | 43ea6284c27104866d08d0580c9936fa | function [bestpg, bestmap, energyIter, bestsp] = mcmcTestImageSA(im, imsegs, vclassifierSP, hclassifierSP, ...
eclassifier, ecal, vclassifier, hclassifier, segclassifier, maxiter, spdata, adjlist, edata)
% Computes the marginals of the geometry for the given input image
% spdata, adjlist, edata are optional inputs
... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGetAllSegmentFeatures.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGetAllSegmentFeatures.m | 965 | utf_8 | 73140ce0d6cd822fc60996d2b7e65f0d | function features = mcmcGetAllSegmentFeatures(imsegs, imdir, gtmaps, spfeatures, vclassifierSP, hclassifierSP)
for f = 1:numel(imsegs)
disp([num2str(f) ': ' imsegs(f).imname])
im = im2double(imread([imdir '/' imsegs(f).imname]));
%[pvSP, phSP] = spClassify(spfeatures{f}, vclassifierSP, hclassifierSP... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentationClassifier2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentationClassifier2.m | 1,503 | utf_8 | 7e0fabdd4d7236a9f2cb584fdcc2da04 | function [segclassifier] = mcmcTrainSegmentationClassifier2(features, labels, weights, maxdata, classparams)
if exist('classparams') && ~isempty(classparams)
nnodes = classparams(1);
ntrees = classparams(2);
stopval = classparams(3);
else
ntrees = 20;
nnodes = 8;
stopval = 0;
end
if ~exist('ma... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGetDisjointEdgeData.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGetDisjointEdgeData.m | 3,554 | utf_8 | 2d4b72e0eb1307de4fa21040a2eb4912 | function [edata, adjlist, boundmap, perim] = mcmcGetDisjointEdgeData(imsegs, spdata, npertype, ignorelist)
% edata(nadj, nfeatures)
% edata feature descriptions:
% 01 - 03: abs diff mean rgb
% 04 - 06: abs diff hsv conversion
% 07 - 07: chi-squared hue histogram
% 08 - 08: chi-squared sat histogra... |
github | HzFu/VideoCoSeg_MSG-master | generateMultipleSegmentations2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/generateMultipleSegmentations2.m | 4,821 | utf_8 | 6ed9f13e1afd90641099cf529457b2db | function smaps = generateMultipleSegmentations2(pE, adjlist, nsp, nsegall)
% 1) Randomly select superpixel s1, then randomly selects different superpixel
% s2 within same segment (if one exists); remove s1,s2 from s
% 2) Then, for randomly ordered i:
% if si is adjacent to s1, assign si to s1 with probability pE(s... |
github | HzFu/VideoCoSeg_MSG-master | generateMultipleSegmentations.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/generateMultipleSegmentations.m | 3,622 | utf_8 | e49148b9d94a1a120203483083e939c0 | function smaps = generateMultipleSegmentations(pE, adjlist, nsp, nsegall)
% 1) Randomly select superpixel s1, then randomly selects different superpixel
% s2 within same segment (if one exists); remove s1,s2 from s
% 2) Then, for randomly ordered i:
% if si is adjacent to s1, assign si to s1 with probability pE(si... |
github | HzFu/VideoCoSeg_MSG-master | generateInitialSegments.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/generateInitialSegments.m | 3,423 | utf_8 | 443df99f371accc845896e51675b6dce | function [labdata, segdata, labels, weights, smap] = generateInitialSegments(imsegs, imdir, ...
adjlist, spdata, vclassifierSP, hclassifierSP, edata, eclassifier)
ngoodv = 0;
ngoodh = 0;
ntotalv = 0;
ntotalh = 0;
for f = 1:numel(imsegs)
disp([num2str(f) ': ' imsegs(f).imname])
im = im2dou... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentClassifier2_vonly.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentClassifier2_vonly.m | 2,131 | utf_8 | 03438f3f343eea4b0b1f2bf10f2ef89a | function [vclassifier] = mcmcTrainSegmentClassifier2(features, labels, weights, maxdata, classparams)
if exist('classparams') && ~isempty(classparams)
nnodes = classparams(1);
ntrees = classparams(2);
stopval = classparams(3);
else
nnodes = 8;
ntrees = 20;
stopval = 0;
end
if ~exist('maxdata')... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGetSegmentFeatures.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGetSegmentFeatures.m | 5,259 | utf_8 | c024c78af3ef2a50098eeadefbb9cd06 | function features = mcmcGetSegmentFeatures(imsegs, spdata, imdata, smap, sinds, usedFeatures)
% features = mcmcGetSegmentFeatures(imsegs, spdata, imdata, smap, sinds)
%
% Input:
% im - the rgb image
% imsegs - superpixel structure
% spdata - superpixel features
% imdata - data computed once for each image
% s... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGetEdgeData.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGetEdgeData.m | 2,631 | utf_8 | fcc4b77a151cf4b963d570498dd11ba7 | function [edata, adjlist, perim, boundmap] = mcmcGetEdgeData(imsegs, spdata)
% edata(nadj, nfeatures)
% edata feature descriptions:
% 01 - 03: abs diff mean rgb
% 04 - 06: abs diff hsv conversion
% 07 - 07: chi-squared hue histogram
% 08 - 08: chi-squared sat histogram
% 09 - 23: abs diff mea... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainEdgeClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainEdgeClassifier.m | 1,055 | utf_8 | 877ab4a3c6843bf47331493b332d7127 | function eclassifier = mcmcTrainEdgeClassifier(efeatures, adjlist, imsegs)
ntrees = 20;
nnodes = 8;
ndata = 50000;
labels = {imsegs(:).labels};
% train {ground, vertical, sky} classifier
[edata, elab] = formatData(efeatures, adjlist, labels, ndata);
mean(elab==1)
eclassifier = train_boosted_dt_2c(edata, [], elab, nt... |
github | HzFu/VideoCoSeg_MSG-master | mcmcGenerateRandomSegments3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcGenerateRandomSegments3.m | 4,473 | utf_8 | ba052cbf21c720b17c3f6f57d7e3c923 | function [data, labels, imind] = mcmcGenerateRandomSegments3(imsegs, imdir, ...
adjlist, spdata, edata, vclassifierSP, hclassifierSP, eclassifier)
% Generate random segments for training good (1) vs. bad (-1) segments
% segment, where good segments consist entirely of one label
nimages = numel(im... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestImageSA3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestImageSA3.m | 11,834 | utf_8 | e7732a65afd62fca663335729b2bc17d | function [bestpg, bestmap, segs, segpg, pg2, firsten, bestenergy] = ...
mcmcTestImageSA3(im, imsegs, vclassifierSP, hclassifierSP, ...
eclassifier, ecal, vclassifier, hclassifier, segrt, ...
priors, maxiter, spdata, adjlist, edata)
% Computes the marginals of the geometry for the given input image
% spdata,... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestImageSA2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestImageSA2.m | 12,135 | utf_8 | 3bfbd8aeaa128bfa5f62316f09d8c06c | function [bestpg, bestmap, segs, segpg, pg2, energyIter, bestsp] = ...
mcmcTestImageSA2(im, imsegs, vclassifierSP, hclassifierSP, ...
eclassifier, ecal, vclassifier, hclassifier, segclassifier, ...
priors, maxiter, spdata, adjlist, edata)
% Computes the marginals of the geometry for the given input image
% ... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestEdgeClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestEdgeClassifier.m | 1,770 | utf_8 | 6381c5797d83259d8dbeabc7ffa25bfb | function errors = mcmcTestEdgeClassifier(efeatures, adjlist, imsegs, eclassifier)
labels = {imsegs(:).labels};
[edata, elab] = formatData(efeatures, adjlist, labels);
econf = test_boosted_dt_mc(eclassifier, edata);
econf = 1 ./ (1+exp(-econf));
mean(elab)
eerror = mean((econf>0.5)~=elab);
econf2 = 1-abs(elab-econf)... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTestSuperpixelClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTestSuperpixelClassifier.m | 5,126 | utf_8 | 0d00504cf7ddd5b0e4b6fb53c1ac7fca | function [errors, perrors] = ...
mcmcTestSuperpixelClassifier(spfeatures, imsegs, vclassifier, hclassifier)
spvlabels = {imsegs(:).vert_labels};
sphlabels = {imsegs(:).horz_labels};
% test vertical
[vdata, vlab, imind] = formatData(spfeatures, spvlabels);
vconf = test_boosted_dt_mc(vclassifier, vdata);
vconf = 1 ... |
github | HzFu/VideoCoSeg_MSG-master | testImageBottomUp.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/testImageBottomUp.m | 4,294 | utf_8 | f48e8c221da67eda5127e9c89462f600 | function [pv, ph, smap, vacc, hacc] = testImageBottomUp(im, imsegs, vclassifierSP, hclassifierSP, ...
eclassifier, vclassifier, hclassifier, segclassifier, spdata, adjlist, edata)
% Initialize
nsp = imsegs.nseg;
grayim = rgb2gray(im);
if ~exist('spdata') || isempty(spdata)
spdata = mcmcGetSuperpixelData(im, ... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSuperpixelClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSuperpixelClassifier.m | 1,345 | utf_8 | 16a34ce0da3868c28b1694ffa1fc87dc | function [vclassifier, hclassifier] = ...
mcmcTrainSuperpixelClassifier(spfeatures, imsegs)
ntrees = 25;
nnodes = 8;
ndata = 10000;
vnames = imsegs(1).vert_names;
hnames = imsegs(1).horz_names;
spvlabels = {imsegs(:).vert_labels};
sphlabels = {imsegs(:).horz_labels};
% train {ground, vertical, sky} classifier
[vd... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentClassifier2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentClassifier2.m | 2,193 | utf_8 | 8b6680b7722b2d0404a43b9332b38425 | function [vclassifier, hclassifier] = mcmcTrainSegmentClassifier2(features, labels, weights, maxdata, classparams)
if exist('classparams') && ~isempty(classparams)
nnodes = classparams(1);
ntrees = classparams(2);
stopval = classparams(3);
else
nnodes = 8;
ntrees = 20;
stopval = 0;
end
if ~exi... |
github | HzFu/VideoCoSeg_MSG-master | mcmcTrainSegmentClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/mcmcTrainSegmentClassifier.m | 1,771 | utf_8 | 9956192beb947c8ae3296ff31884cd37 | function [vclassifier, hclassifier] = ...
mcmcTrainSegmentClassifier(imsegs, features, labels)
ntrees = 15;
nnodes = 8;
maxdata = 25000;
vlabels = labels;
hlabels = labels;
for f = 1:numel(labels)
vlabels{f} = 1*(labels{f}==1) + 2*((labels{f}>1) & (labels{f}<7)) + ...
3*(labels{f}==7);
hlabels{f}... |
github | HzFu/VideoCoSeg_MSG-master | generateMultipleSegmentationsGC.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/mcmc/generateMultipleSegmentationsGC.m | 4,352 | utf_8 | 24798315c652c021ce26f9bd25c85dcb | function smaps = generateMultipleSegmentationsGC(pE, adjlist, nsp, nsegall)
% smaps = generateMultipleSegmentationsGC(pE, adjlist, nsp, nsegall)
%
% Uses graph cuts to segment image, maximizing an approximation of log(pE)
% Different segments result from random superpixels initially being set to
% segments.
nmap... |
github | HzFu/VideoCoSeg_MSG-master | colorspace.m | .m | VideoCoSeg_MSG-master/external/Co_saliency_code/colorspace.m | 16,178 | utf_8 | 2ca0aee9ae4d0f5c12a7028c45ef2b8d | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Transform a color image between color representations.
% B = COLORSPACE(S,A) transforms the color representation of image A
% where S is a string specifying the conversion. The input array A
% should be a real full double array of size Mx3 or MxN... |
github | KeremKaratas/RSSLocalizationSimulations-master | GoldoniTestbed.m | .m | RSSLocalizationSimulations-master/GoldoniTestbed.m | 5,412 | utf_8 | 66f924a93dd294484fd2973a0000a767 | function [] = GoldoniTestbed()
%% Goldoni Testbed
% Initialize parameters for the simulation and run localization algorithms
% with the placements done in Goldoni's article. Plot a scatterplot with 25
% estimations and actual placements
clear variables;
clc;
close all;
%% Main simulation parameters
% Area of Interest... |
github | KeremKaratas/RSSLocalizationSimulations-master | FGS_SE.m | .m | RSSLocalizationSimulations-master/FGS_SE.m | 19,361 | utf_8 | ea64ae5fb9e367084e5ff847e3f0e790 | %% Iterative Grid Search for RSS-Based Emitter Localization
% Main function implements the Full Grid search method provided in the
% article given in the title. The variables required as input to the
% function is described below. Detailed descriptions of these variables are
% given in under the "Main Function" sectio... |
github | KeremKaratas/RSSLocalizationSimulations-master | Trilateration.m | .m | RSSLocalizationSimulations-master/Trilateration.m | 10,169 | utf_8 | 53eef166b4513c99ca7c05db954378c0 | function [estErr, sPos, ePos, estELoc] = ...
Trilateration( ROI, gridSize, N_s, P_T, P_E, sigma, alpha_actual ...
, alpha_assumed, recSens ...
, dispON ...
, useTime, assignS, assignE)
%% TRILATERATION
% This function implements Trilateration method to localize the emitter. If
% sensor and emitter locations... |
github | KeremKaratas/RSSLocalizationSimulations-master | MinMax.m | .m | RSSLocalizationSimulations-master/MinMax.m | 8,467 | utf_8 | f9d0dc933522fdb6db8cfae503c3a613 | function [estErr, sPos, ePos, estELoc] = ...
MinMax( ROI, gridSize, N_s, P_T, P_E, sigma, alpha_actual ...
, alpha_assumed, recSens ...
, dispON ...
, useTime, assignS, assignE)
%% MINMAX
% This function implements Minmax method to localize the emitter. If
% sensor and emitter locations are not provided in ... |
github | KeremKaratas/RSSLocalizationSimulations-master | MaximumLikelihood.m | .m | RSSLocalizationSimulations-master/MaximumLikelihood.m | 10,749 | utf_8 | c9d5437fc6ea0ce0e1bfee27e6051af8 | function [estErr, sPos, ePos, estELoc] = ...
MaximumLikelihood( ROI, gridSize, N_s, P_T, P_E, sigma, alpha_actual ...
, alpha_assumed, recSens ...
, dispON ...
, useTime, assignS, assignE)
%% MAXIMUMLIKELIHOOD
% This function implements Maximum Likelihood method to localize the
% emitter. If sensor and emi... |
github | ingle/ultrasound-simulation-master | binary2matrix.m | .m | ultrasound-simulation-master/matlab_scripts/binary2matrix.m | 1,753 | utf_8 | 20be1df9c3246625fce5c7eef2f25464 | function A0 = binary2matrix(rf_file)
%%%%%the RF data is read from file and converted to B-mode values
%%Adjust the center frequency and bandwidth%%%
bandwidth=.5;
centerFreq=5e6; %in Hz
[A0, fs]=generate_rf( rf_file, centerFreq, bandwidth);
%info for plotting
BeamSpace=0.2; %again in mm, equal to element spacing?
... |
github | ingle/ultrasound-simulation-master | writeBscFile.m | .m | ultrasound-simulation-master/matlab_scripts/writeBscFile.m | 5,798 | utf_8 | e233a4bfc3d4ab90a9e27507eb971446 | function BSCCurve = writeBscFile(fname, maxFreq, diam,sosm,soss,sosshear,rhom,rhos,maxang,maxn)
%a function which calculates scattering cross sections for spheres
%according to Faran's theory; the output is a (1+maxang) by (size of x3) matrix
%where rows correspond to angles (0 to maxang) and columns correspond to dif... |
github | Magnus1990P/biqa-master | jp2knr_quality.m | .m | biqa-master/jp2knr_quality.m | 5,136 | utf_8 | 625cb5f9169dd01a4d2eca38927cdb81 | function q=jp2knr_quality(img)
% img is grayscale image compressed by jpeg2000 (or uncompressed)
% -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------
% Copyright (c) 2003 The University of Texas at Austin
% All rights reserved.
%
% Permission is hereby granted, without written agreement and withou... |
github | Magnus1990P/biqa-master | iso_isc.m | .m | biqa-master/iso_isc.m | 2,692 | utf_8 | 158a3277d6e229a0cecce031f278d8b7 | % IRIS SCLERA CONTRAST
%outbound -> radius from center to bound between iris and sclera
%inbound -> radius from center to bound between iris and pupil
%IRIS_SCLERA_CONTRAST -> The proportion of the irisa that is visible (in %)
function IRIS_SCLERA_CONTRAST = iso_isc( IMG, PUPIL, IRIS )
delRad = floor(IRIS(1,3) - PU... |
github | Magnus1990P/biqa-master | iso_uia.m | .m | biqa-master/iso_uia.m | 382 | utf_8 | c6595e5b8e1a1428779819ad51a55f5a | % USABLE IRIS AREA
%occluded -> Radius of pupil, px
%iris -> Radius of iris, px
%USABLE_IRIS_AREA -> The proportion of the irisa that is viewable (in %)
function USABLE_IRIS_AREA = iso_uia( iris, pupil)
irisArea = 3.14 * ( double(iris) ^ 2);
pupilArea = 3.14 * ( double(pupil) ^ 2);
... |
github | Magnus1990P/biqa-master | mainBIQA.m | .m | biqa-master/mainBIQA.m | 6,044 | utf_8 | c3d291163415954128725f78b9cda722 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Testing file for testing correct iteration of databases
%% Takse the parameter of number of databses to be run
%%
%% Author: Magnus Øverbø
%% Copyright: Magnus Øverbø
%% Supervisor: Kiran Bylappa Raja NISlab
%% Last rev:
%% Com... |
github | Magnus1990P/biqa-master | iso_ipc.m | .m | biqa-master/iso_ipc.m | 1,799 | utf_8 | 0da7017a5fe31effd9b14c97468ac7a7 | % IRIS PUPIL CONTRAST - Above 30
%IMG -> RGB image
%PUPIL -> Center and radius of pupil
%IRIS -> Center and radius of iris
%IRIS_PUPIL_CONTRAST -> The proportion of the irisa that is viewable (in %)
function [IRIS_PUPIL_CONTRAST, CONTRAST] = iso_ipc( IMG, PUPIL, IRIS )
delRad = floor(double(IRIS(1,3)) - double(P... |
github | Magnus1990P/biqa-master | iso_gsu.m | .m | biqa-master/iso_gsu.m | 2,118 | utf_8 | 0ede8ee446c71f4f0bd4f72d126db929 | % GREY SCALE UTILISATION - Above 30
%IMG0 -> image in RGB format
%IRIS -> Iris information, center and radius
%PUPIL -> Pupil information, center and radius
%GREY_SCALE_UTILISATION -> The proportion of the iris that is viewable (in %)
function GREY_SCALE_UTILISATION = iso_gsu( IMG, PUPIL, IRIS )
IMG1 = ... |
github | Magnus1990P/biqa-master | dataTesting.m | .m | biqa-master/dataTesting.m | 7,564 | utf_8 | 1bde5d47fbfd435ce4f4a06ba1cc0027 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function dat = dataTesting( )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Variables
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | baowenbo/SelfExSR-master | compute_difference.m | .m | SelfExSR-master/quant_eval/compute_difference.m | 2,013 | utf_8 | 206fd3db5a2b6622f6940f5d688f8641 | function [psnr, ssim, ifc] = compute_difference(im, imgt, SRF)
% COMPUTE_DIFFERENCE: compute image quality
%
% Input:
% - im: super-resolved image
% - imgt: groundtruth high-resolution image
% - SRF: super-resolution factor
% Output:
% - psnr: Peak signal-to-noise ratio
% - ssim: Structural simi... |
github | baowenbo/SelfExSR-master | sp3Filters.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/sp3Filters.m | 17,188 | utf_8 | a3514d77e5a92b96d96197ebad343395 | % Steerable pyramid filters. Transform described in:
%
% @INPROCEEDINGS{Simoncelli95b,
% TITLE = "The Steerable Pyramid: A Flexible Architecture for
% Multi-Scale Derivative Computation",
% AUTHOR = "E P Simoncelli and W T Freeman",
% BOOKTITLE = "Second Int'l Conf on Image Processing",
% ADDRESS = "Washington, DC"... |
github | baowenbo/SelfExSR-master | buildWpyr.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/buildWpyr.m | 2,644 | utf_8 | e741b2037d9a1358d4de94580ebcc4bf | % [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES)
%
% Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM.
%
% HEIGHT (optional) specifies the number of pyramid levels to build. Default
% is maxPyrHt(IM,FILT). You can also specify 'auto' to use this value.
%
% FILT (optional) can be a st... |
github | baowenbo/SelfExSR-master | reconLpyr.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/reconLpyr.m | 2,049 | utf_8 | 657b8012a1ed06b6573496855309b2ae | % RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES)
%
% Reconstruct image from Laplacian pyramid, as created by buildLpyr.
%
% PYR is a vector containing the N pyramid subbands, ordered from fine
% to coarse. INDICES is an Nx2 matrix containing the sizes of
% each subband. This is compatible with the MatLab Wavelet t... |
github | baowenbo/SelfExSR-master | mkDisc.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/mkDisc.m | 1,428 | utf_8 | c6acae0ac1aa738b7ef094eb2ac60f52 | % IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS)
%
% Make a "disk" image. SIZE specifies the matrix size, as for
% zeros(). RADIUS (default = min(size)/4) specifies the radius of
% the disk. ORIGIN (default = (size+1)/2) specifies the
% location of the disk center. TWIDTH (in pixels, default = 2)
% specifies th... |
github | baowenbo/SelfExSR-master | spyrHigh.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/spyrHigh.m | 189 | utf_8 | 3132a747e0c7bf1879bb32e4d5fda257 | % RES = spyrHigh(PYR, INDICES)
%
% Access the highpass residual band from a steerable pyramid.
% Eero Simoncelli, 6/96.
function res = spyrHigh(pyr,pind)
res = pyrBand(pyr, pind, 1);
|
github | baowenbo/SelfExSR-master | mkImpulse.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/mkImpulse.m | 529 | utf_8 | cf6f3809cb123791501bb0e92845a0c6 | % IM = mkImpulse(SIZE, ORIGIN, AMPLITUDE)
%
% Compute a matrix of dimension SIZE (a [Y X] 2-vector, or a scalar)
% containing a single non-zero entry, at position ORIGIN (defaults to
% ceil(size/2)), of value AMPLITUDE (defaults to 1).
% Eero Simoncelli, 6/96.
function [res] = mkImpulse(sz, origin, amplitude)
sz = s... |
github | baowenbo/SelfExSR-master | rconv2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/rconv2.m | 1,435 | utf_8 | da3a54d6c7b1ac17c78eab0a4a7648d9 | % RES = RCONV2(MTX1, MTX2, CTR)
%
% Convolution of two matrices, with boundaries handled via reflection
% about the edge pixels. Result will be of size of LARGER matrix.
%
% The origin of the smaller matrix is assumed to be its center.
% For even dimensions, the origin is determined by the CTR (optional)
% argument:... |
github | baowenbo/SelfExSR-master | mkR.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/mkR.m | 775 | utf_8 | 504bc90f67c72730edc4a9d86630bdf2 | % 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, 6/96.... |
github | baowenbo/SelfExSR-master | blur.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/blur.m | 1,731 | utf_8 | a2dc57fdfe85f98549b2f7ddf721c298 | % RES = blur(IM, LEVELS, FILT)
%
% Blur an image, by filtering and downsampling LEVELS times
% (default=1), followed by upsampling and filtering LEVELS times. The
% blurring is done with filter kernel specified by FILT (default =
% 'binom5'), which can be a string (to be passed to namedFilter), a
% vector (applied sep... |
github | baowenbo/SelfExSR-master | pyrBand.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/pyrBand.m | 395 | utf_8 | 39c1e3772426a1362119d302d9767a24 | % RES = pyrBand(PYR, INDICES, BAND_NUM)
%
% Access a subband from a pyramid (gaussian, laplacian, QMF/wavelet,
% or steerable). Subbands are numbered consecutively, from finest
% (highest spatial frequency) to coarsest (lowest spatial frequency).
% Eero Simoncelli, 6/96.
function res = pyrBand(pyr, pind, band)
re... |
github | baowenbo/SelfExSR-master | kurt2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/kurt2.m | 551 | utf_8 | cd20c1a5155cba8de454011552ec4f2a | % K = KURT2(MTX,MEAN,VAR)
%
% Sample kurtosis (fourth moment divided by squared variance)
% of a matrix. Kurtosis of a Gaussian distribution is 3.
% MEAN (optional) and VAR (optional) make the computation faster.
% Eero Simoncelli, 6/96.
function res = kurt2(mtx, mn, v)
if (exist('mn') ~= 1)
mn = mean(mean(mtx)... |
github | baowenbo/SelfExSR-master | buildSpyr.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/buildSpyr.m | 2,064 | utf_8 | b0caf60e63a52aa734956dd74ea39f95 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSpyr(IM, HEIGHT, FILTFILE, EDGES)
%
% Construct a steerable pyramid on matrix IM. Convolutions are
% done with spatial filters.
%
% HEIGHT (optional) specifies the number of pyramid levels to build. Default
% is maxPyrHt(size(IM),size(FILT)).
% You can also specify 'auto' ... |
github | baowenbo/SelfExSR-master | setPyrBand.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/setPyrBand.m | 1,049 | utf_8 | 76554eb735e969097a4723a508facd37 | % NEWPYR = setPyrBand(PYR, INDICES, NEWBAND, BAND_NUM)
%
% Insert an image (BAND) into a pyramid (gaussian, laplacian, QMF/wavelet,
% or steerable). Subbands are numbered consecutively, from finest
% (highest spatial frequency) to coarsest (lowest spatial frequency).
% Eero Simoncelli, 1/03.
function pyr = setPyrB... |
github | baowenbo/SelfExSR-master | var2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/var2.m | 390 | utf_8 | de26727e055081aa670024c273f0e885 | % V = VAR2(MTX,MEAN)
%
% Sample variance of a matrix.
% Passing MEAN (optional) makes the calculation faster.
function res = var2(mtx, mn)
if (exist('mn') ~= 1)
mn = mean2(mtx);
end
if (isreal(mtx))
res = sum(sum(abs(mtx-mn).^2)) / max((prod(size(mtx)) - 1),1);
else
res = sum(sum(real(mtx-mn).^2)) + i*sum(su... |
github | baowenbo/SelfExSR-master | reconSFpyrLevs.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/reconSFpyrLevs.m | 2,016 | utf_8 | ff83a4f3d2f0927dcaa8851535e6b20a | % RESDFT = reconSFpyrLevs(PYR,INDICES,LOGRAD,XRCOS,YRCOS,ANGLE,NBANDS,LEVS,BANDS)
%
% Recursive function for reconstructing levels of a steerable pyramid
% representation. This is called by reconSFpyr, and is not usually
% called directly.
% Eero Simoncelli, 5/97.
function resdft = reconSFpyrLevs(pyr,pind,log_rad,Xr... |
github | baowenbo/SelfExSR-master | rcosFn.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/rcosFn.m | 1,122 | utf_8 | 36283e0a34f1baf7ea2c5e6cb23aab89 | % [X, Y] = rcosFn(WIDTH, POSITION, VALUES)
%
% Return a lookup table (suitable for use by INTERP1)
% containing a "raised cosine" soft threshold function:
%
% Y = VALUES(1) + (VALUES(2)-VALUES(1)) *
% cos^2( PI/2 * (X - POSITION + WIDTH)/WIDTH )
%
% WIDTH is the width of the region over which the tra... |
github | baowenbo/SelfExSR-master | wpyrLev.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/wpyrLev.m | 729 | utf_8 | 77f309b76f98f3421e786fde4fe2d429 | % [LEV,IND] = wpyrLev(PYR,INDICES,LEVEL)
%
% Access a level from a separable QMF/wavelet pyramid.
% Return as an SxB matrix, B = number of bands, S = total size of a band.
% Also returns an Bx2 matrix containing dimensions of the subbands.
% Eero Simoncelli, 6/96.
function [lev,ind] = wpyrLev(pyr,pind,level)
if ((p... |
github | baowenbo/SelfExSR-master | binomialFilter.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/binomialFilter.m | 309 | utf_8 | 47b67219b2519bd65a435f3df318d41a | % KERNEL = binomialFilter(size)
%
% Returns a vector of binomial coefficients of order (size-1) .
% Eero Simoncelli, 2/97.
function [kernel] = binomialFilter(sz)
if (sz < 2)
error('size argument must be larger than 1');
end
kernel = [0.5 0.5]';
for n=1:sz-2
kernel = conv([0.5 0.5]', kernel);
end
|
github | baowenbo/SelfExSR-master | cconv2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/cconv2.m | 1,325 | utf_8 | 8e564b623ba5cebd51e585eac6c66ba8 | % RES = CCONV2(MTX1, MTX2, CTR)
%
% Circular convolution of two matrices. Result will be of size of
% LARGER vector.
%
% The origin of the smaller matrix is assumed to be its center.
% For even dimensions, the origin is determined by the CTR (optional)
% argument:
% CTR origin
% 0 DIM/2 (defaul... |
github | baowenbo/SelfExSR-master | reconSCFpyr.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/reconSCFpyr.m | 4,475 | utf_8 | a0a6a06af4b5c9f7aa195bb8188fc754 | % RES = reconSCFpyr(PYR, INDICES, LEVS, BANDS, TWIDTH)
%
% The inverse of buildSCFpyr: Reconstruct image from its complex steerable pyramid representation,
% in the Fourier domain.
%
% The image is reconstructed by forcing the complex subbands to be analytic
% (zero on half of the 2D Fourier plane, as they are supossed... |
github | baowenbo/SelfExSR-master | buildSCFpyr.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/buildSCFpyr.m | 2,713 | utf_8 | d94b4004138b50b6651511e8ba6ccb93 | % [PYR, INDICES, STEERMTX, HARMONICS] = buildSCFpyr(IM, HEIGHT, ORDER, TWIDTH)
%
% This is a modified version of buildSFpyr, that constructs a
% complex-valued steerable pyramid using Hilbert-transform pairs
% of filters. Note that the imaginary parts will *not* be steerable.
%
% To reconstruct from this representati... |
github | baowenbo/SelfExSR-master | showIm.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/showIm.m | 6,111 | utf_8 | 15fbbf55e2fd54e3f48ca936e23c3f32 | % RANGE = showIm (MATRIX, RANGE, ZOOM, LABEL, NSHADES )
%
% Display a MatLab MATRIX as a grayscale image in the current figure,
% inside the current axes. If MATRIX is complex, the real and imaginary
% parts are shown side-by-side, with the same grayscale mapping.
%
% If MATRIX is a string, it should be the name of... |
github | baowenbo/SelfExSR-master | pyrLow.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/pyrLow.m | 287 | utf_8 | b3514ec06e2e106d7b61e534cac20a8e | % RES = pyrLow(PYR, INDICES)
%
% Access the lowpass subband from a pyramid
% (gaussian, laplacian, QMF/wavelet, steerable).
% Eero Simoncelli, 6/96.
function res = pyrLow(pyr,pind)
band = size(pind,1);
res = reshape( pyr(pyrBandIndices(pind,band)), pind(band,1), pind(band,2) );
|
github | baowenbo/SelfExSR-master | pgmRead.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/pgmRead.m | 1,259 | utf_8 | 6f07c13cf0f5d8930a46ac0d778bf86f | % IM = pgmRead( FILENAME )
%
% Load a pgm image into a MatLab matrix.
% This format is accessible from the XV image browsing utility.
% Only works for 8bit gray images (raw or ascii)
% Hany Farid, Spring '96. Modified by Eero Simoncelli, 6/96.
function im = pgmRead( fname );
[fid,msg] = fopen( fname, 'r' );
... |
github | baowenbo/SelfExSR-master | upConv.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/upConv.m | 2,779 | utf_8 | 34137e966f38700416bfb0ebb72663ee | % RES = upConv(IM, FILT, EDGES, STEP, START, STOP, RES)
%
% Upsample matrix IM, followed by convolution with matrix FILT. These
% arguments should be 1D or 2D matrices, and IM must be larger (in
% both dimensions) than FILT. The origin of filt
% is assumed to be floor(size(filt)/2)+1.
%
% EDGES is a string determinin... |
github | baowenbo/SelfExSR-master | mean2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/mean2.m | 97 | utf_8 | cacc007ef6e32ba40a1e0da3b3d80a0e | % M = MEAN2(MTX)
%
% Sample mean of a matrix.
function res = mean2(mtx)
res = mean(mean(mtx));
|
github | baowenbo/SelfExSR-master | range2.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/range2.m | 523 | utf_8 | b9f23c3a4f73bf568a1b5793f516aa80 | % [MIN, MAX] = range2(MTX)
%
% Compute minimum and maximum values of MTX, returning them as a 2-vector.
% Eero Simoncelli, 3/97.
function [mn, mx] = range2(mtx)
%% NOTE: THIS CODE IS NOT ACTUALLY USED! (MEX FILE IS CALLED INSTEAD)
fprintf(1,'WARNING: You should compile the MEX version of "range2.c",\n found... |
github | baowenbo/SelfExSR-master | buildSCFpyrLevs.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/buildSCFpyrLevs.m | 2,187 | utf_8 | 26747285064a0eaa2f3db75013e80849 | % [PYR, INDICES] = buildSCFpyrLevs(LODFT, LOGRAD, XRCOS, YRCOS, ANGLE, HEIGHT, NBANDS)
%
% Recursive function for constructing levels of a steerable pyramid. This
% is called by buildSCFpyr, and is not usually called directly.
% Original code: Eero Simoncelli, 5/97.
% Modified by Javier Portilla to generate complex b... |
github | baowenbo/SelfExSR-master | clip.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/clip.m | 814 | utf_8 | 13c82937ba69d5bc8c94b2ccca783e1b | % [RES] = clip(IM, MINVALorRANGE, MAXVAL)
%
% Clip values of matrix IM to lie between minVal and maxVal:
% RES = max(min(IM,MAXVAL),MINVAL)
% The first argument can also specify both min and max, as a 2-vector.
% If only one argument is passed, the range defaults to [0,1].
function res = clip(im, minValOrRange, m... |
github | baowenbo/SelfExSR-master | upBlur.m | .m | SelfExSR-master/quant_eval/ifcvec_release/matlabPyrTools/upBlur.m | 1,213 | utf_8 | 7b07d26940520537edb6e8dc25b72242 | % RES = upBlur(IM, LEVELS, FILT)
%
% Upsample and blur an image. The blurring is done with filter
% kernel specified by FILT (default = 'binom5'), which can be a string
% (to be passed to namedFilter), a vector (applied separably as a 1D
% convolution kernel in X and Y), or a matrix (applied as a 2D
% convolution kern... |
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