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 | pdist2.m | .m | VideoCoSeg_MSG-master/external/pdist2.m | 4,899 | utf_8 | d80f12717795a22598f788e2d0497d37 | function D = pdist2( X, Y, metric )
% Calculates the distance between sets of vectors.
%
% Let X be an m-by-p matrix representing m points in p-dimensional space
% and Y be an n-by-p matrix representing another set of points in the same
% space. This function computes the m-by-n distance matrix D where D(i,j)
% is the ... |
github | HzFu/VideoCoSeg_MSG-master | computeColor.m | .m | VideoCoSeg_MSG-master/external/OpticalFlow_CeLiu/computeColor.m | 3,142 | utf_8 | a36a650437bc93d4d8ffe079fe712901 | function img = computeColor(u,v)
% computeColor color codes flow field U, V
% According to the c++ source code of Daniel Scharstein
% Contact: schar@middlebury.edu
% Author: Deqing Sun, Department of Computer Science, Brown University
% Contact: dqsun@cs.brown.edu
% $Date: 2007-10-31 21:20:30 (Wed, 31 O... |
github | HzFu/VideoCoSeg_MSG-master | slmetric_pw.m | .m | VideoCoSeg_MSG-master/external/proposals/external/pwmetric/slmetric_pw.m | 11,574 | utf_8 | 809160dc3e2ca2d67aa42e3961c6fad4 | function M = slmetric_pw(X1, X2, mtype, varargin)
%SLMETRIC_PW Compute the metric between column vectors pairwisely
%
% [ Syntax ]
% - M = slmetric_pw(X1, X2, mtype);
% - M = slmetric_pw(X1, X2, mtype, ...);
%
% [ Arguments ]
% - X1, X2: the sample matrices
% - mtype: the string indicating the type... |
github | HzFu/VideoCoSeg_MSG-master | glob.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/glob.m | 3,565 | utf_8 | 9a705e0eec8a8cc37c546807831c70bb | function [names,isdirs] = glob(pattern,prefix)
%GLOB Filename expansion via wildcards.
% GLOB(PATTERN) returns a cell array of file/directory names which match the
% PATTERN.
% [NAMES,ISDIRS] = GLOB(PATTERN) also returns a logical vector indicating
% which are directories.
%
% Two types of wildcards are supported... |
github | HzFu/VideoCoSeg_MSG-master | flops_pow.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/flops_pow.m | 1,369 | utf_8 | 663b15ad1cad93d89c6dd75401fb4261 | function f = flops_pow(a)
% FLOPS_POW Flops for raising to real power.
% FLOPS_POW(A) returns the number of flops for (X .^ A) where X is scalar.
% Powers like 0, 1, 2, and 1/2 are handled specially.
flops_div = 8;
flops_sqrt = 8;
if nargin < 1
a = 0.1;
end
f = 0;
if a < 0
f = f + flops_div;
a = -a;
end
if a ... |
github | HzFu/VideoCoSeg_MSG-master | duplicated.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/duplicated.m | 1,384 | utf_8 | 416fc8427b31eed738b2824c18735b59 | function d = duplicated(x)
%DUPLICATED Find duplicated rows.
% DUPLICATED(x) returns a vector d such that d(i) = 1 if x(i,:) is a
% duplicate of an earlier row.
%
% Examples:
% duplicated([2 7 8 7 1 2 8]') = [0 0 0 1 0 1 1]'
% duplicated([0 0 1 1 0; 0 1 0 1 1]') = [0 0 0 0 1]'
% duplicated(eye(100))
% duplicated(kro... |
github | HzFu/VideoCoSeg_MSG-master | subsasgn.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/@mutable/subsasgn.m | 1,433 | utf_8 | d0397a1cda0b2754fbcc752676bdca11 | function mut = subsasgn(mut,index,v)
% Written by Tom Minka
% (c) Microsoft Corporation. All rights reserved.
subsasgnJava(mut.obj,index,v,mut.cl);
function subsasgnJava(jv,index,v,cl)
if nargin < 4
% class(jv) is expensive, so we do it only once
cl = class(jv);
end
if strcmp(cl,'java.util.Hashtable')
% don't... |
github | HzFu/VideoCoSeg_MSG-master | subsref.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/@mutable/subsref.m | 1,619 | utf_8 | c3b977a439f0ed2a700529c0d55e590a | function v = subsref(mut,index)
% Written by Tom Minka
% (c) Microsoft Corporation. All rights reserved.
v = subsrefJava(mut.obj,index,mut.cl);
function v = subsrefJava(jv,index,cl)
if nargin < 3
% class(jv) is expensive, so we do it only once
cl = class(jv);
end
wantcell = 0;
if strcmp(cl,'java.util.Hashtable'... |
github | HzFu/VideoCoSeg_MSG-master | test_sameobject.m | .m | VideoCoSeg_MSG-master/external/proposals/external/lightspeed/tests/test_sameobject.m | 247 | utf_8 | 5af54d04e4fb6ce88431981f88e775f9 | function test_sameobject
% Result should be 1 in both cases below.
a = rand(4);
b = a;
if sameobject(a,b) ~= 1
error('failed');
end
if helper(a,a) ~= 1
error('failed');
end
disp('Test passed.')
function x = helper(a,b)
x = sameobject(a,b);
|
github | HzFu/VideoCoSeg_MSG-master | makeRFSfilters.m | .m | VideoCoSeg_MSG-master/external/proposals/external/textons/makeRFSfilters.m | 1,793 | utf_8 | 17ddab88b564d7bbf34c0d05fa4c2f05 | function F=makeRFSfilters
% Returns the RFS filter bank of size 49x49x38 in F. The MR8, MR4 and
% MRS4 sets are all derived from this filter bank. 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... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphs.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Benchmark/boundaryBenchGraphs.m | 2,149 | utf_8 | 5d36c953bdb6419ab347d32a33237106 | function boundaryBenchGraphs(pbDir)
% function boundaryBenchGraphs(pbDir)
%
% Create graphs, after boundaryBench(pbDir) has been run.
%
% See also boundaryBench.
%
% David Martin <dmartin@eecs.berkeley.edu>
% May 2003
fname = fullfile(pbDir,'scores.txt');
scores = dlmread(fname); % iid,thresh,r,p,f
fname = fullfile(pb... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBench.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Benchmark/boundaryBench.m | 3,527 | utf_8 | 72c57116e042a9982380b57fb6535200 | function boundaryBench(pbDir,pres,nthresh,fast)
% function boundaryBench(pbDir,pres,nthresh,fast)
%
% Run the boundary detector benchmark on the Pb files found in
% pbDir for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
if nargin<3, nthresh=30; end
if ... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphsMulti.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Benchmark/boundaryBenchGraphsMulti.m | 3,290 | utf_8 | 329d8ab5d50641ff5c45b80ea534c65b | function boundaryBenchGraphsMulti(baseDir)
% function boundaryBenchGraphsMulti(baseDir)
%
% See also boundaryBenchGraphs.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
presentations = {'gray','color'};
presNames = {'Grayscale','Color'};
iidsTest = imgList('test');
% Infer list of algorithms from directorie... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphsHuman.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Benchmark/boundaryBenchGraphsHuman.m | 2,305 | utf_8 | 22ab87b11ee29175d476f559f66be48d | function boundaryBenchGraphsHuman(pbDir)
% function boundaryBenchGraphsHuman(pbDir)
%
% Create graphs, after boundaryBenchHuman has been run.
%
% See also boundaryBenchHuman.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
iids = imgList('test');
n = numel(iids);
% read in all the data
fwrite(2,'Reading data... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchHuman.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Benchmark/boundaryBenchHuman.m | 2,560 | utf_8 | dbf3eae48252f53e5d2042206192db85 | function boundaryBenchHuman(pbRoot,pres)
% function boundaryBenchHuman(pbRoot,pres)
%
% Compute the human precision/recall data for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
iids = imgList('test');
cR_total = 0;
sR_total = 0;
cP_total = 0;
sP_total... |
github | HzFu/VideoCoSeg_MSG-master | plotem.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/plotem.m | 2,925 | utf_8 | f4a8f0ca366638ae79dde05510959f65 |
function plotem()
figure(1); clf; hold on;
pr = load('pb/bgtg_0.01_0.02_64/pr.txt');
plot(pr(:,2),pr(:,3),'co-');
pr = load('pb/bgtg/pr.txt');
plot(pr(:,2),pr(:,3),'bx-');
pr = load('pb/cgtg/pr.txt');
plot(pr(:,2),pr(:,3),'rx-');
prplot('');
legend('bgtg zone=2','bgtg zone=10','cgtg');
return
figure(1); clf; hold on... |
github | HzFu/VideoCoSeg_MSG-master | trainCG.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainCG.m | 529 | utf_8 | f26b31c142e8ebbcf87c8620eeb67dd3 | function trainCG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | HzFu/VideoCoSeg_MSG-master | trainTG.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainTG.m | 463 | utf_8 | ddb30948004726a57eecc581e6ec7d77 | function trainTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | HzFu/VideoCoSeg_MSG-master | trainCGTG.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainCGTG.m | 618 | utf_8 | 7f916f99fa0df2efaa8092302648814b | function trainCGTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('b... |
github | HzFu/VideoCoSeg_MSG-master | trainBGTG.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainBGTG.m | 504 | utf_8 | 20fd0459e57773aa11ff7eaa4e39cdcb | function trainBGTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('b... |
github | HzFu/VideoCoSeg_MSG-master | tmp.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/tmp.m | 275 | utf_8 | 3af6b6692bbaa42694b868a8cb2e8897 |
function tmp()
iids = imgList('test');
ignore = mkdir('pb');
ignore = mkdir('pb/bgtg');
for iid = iids,
im = rgb2gray(imgRead(iid));
fprintf(2,'Computing Pb for image %d using BG/TG...\n',iid);
pb = pbBGTG(im);
imwrite(pb,sprintf('pb/bgtg/%d.bmp',iid),'bmp');
end
|
github | HzFu/VideoCoSeg_MSG-master | trainGM.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainGM.m | 1,201 | utf_8 | f1233bddee2a7579e85b87462f9f38c2 | function trainGM()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_1.mat' f y;
beta = logist2(y',f');
save 'beta_gm_1.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_2.mat' f y;
beta = logist2(y',f');
sav... |
github | HzFu/VideoCoSeg_MSG-master | trainGM2.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainGM2.m | 828 | utf_8 | 75c7bd3ab84c9640886bf0613776406b | function [beta,f,y] = trainGM2()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_1_2.mat' f y;
beta = logist2(y',f');
save 'beta_gm_1_2.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_2_4.mat' f y;
beta =... |
github | HzFu/VideoCoSeg_MSG-master | train2MM.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/train2MM.m | 1,240 | utf_8 | af6b211e73cf494661ccb31e77a6d4d6 | function train2MM()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_1.mat' f y;
beta = logist2(y',f');
save 'beta_2mm_1.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_2.mat' f y;
beta = logist2(y',f');... |
github | HzFu/VideoCoSeg_MSG-master | trainBG.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/trainBG.m | 465 | utf_8 | 8a744b43d2e9e5ca3f48c186c9c413e8 | function trainBG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | HzFu/VideoCoSeg_MSG-master | train2MM2.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Detectors/train2MM2.m | 682 | utf_8 | 95dd4f445a6a665a9100a8e3669fadcd | function [beta,f,y] = train2MM2()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_1_2.mat' f y;
beta = logist2(y',f');
save 'beta_2mm_1_2.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_2_4.mat' f y;
be... |
github | HzFu/VideoCoSeg_MSG-master | kmeansML.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Util/kmeansML.m | 3,650 | utf_8 | 7a4a29d66a1f8aeb10ecf636dd483a3a | function [membership,means,rms] = kmeansML(k,data,varargin)
% [membership,means,rms] = kmeansML(k,data,...)
%
% Multi-level kmeans.
% Tries very hard to always return k clusters.
%
% INPUT
% k Number of clusters
% data dxn matrix of data points
% 'maxiter' Max number of iterations. [30]
% 'dtol' Min change in cen... |
github | HzFu/VideoCoSeg_MSG-master | cgmo.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/cgmo.m | 4,181 | utf_8 | 6c29fc1b4d710f1f7fa1e4448062c599 | function [cg,theta] = cgmo(im,radius,norient,varargin)
% function [cg] = cgmo(im,radius,norient,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% norient Number of orientations for cg.
% 'nbins'... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphs.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/boundaryBenchGraphs.m | 2,149 | utf_8 | 5d36c953bdb6419ab347d32a33237106 | function boundaryBenchGraphs(pbDir)
% function boundaryBenchGraphs(pbDir)
%
% Create graphs, after boundaryBench(pbDir) has been run.
%
% See also boundaryBench.
%
% David Martin <dmartin@eecs.berkeley.edu>
% May 2003
fname = fullfile(pbDir,'scores.txt');
scores = dlmread(fname); % iid,thresh,r,p,f
fname = fullfile(pb... |
github | HzFu/VideoCoSeg_MSG-master | cgso.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/cgso.m | 4,061 | utf_8 | b6247b3c62e7cdc72babce695b7096e3 | function [cg,theta] = cgso(im,radius,theta,varargin)
% function [cg] = cgso(im,radius,theta,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% theta Orientation orthogonal to cg.
% 'nbins' Numbe... |
github | HzFu/VideoCoSeg_MSG-master | kmeansML.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/kmeansML.m | 3,650 | utf_8 | 7a4a29d66a1f8aeb10ecf636dd483a3a | function [membership,means,rms] = kmeansML(k,data,varargin)
% [membership,means,rms] = kmeansML(k,data,...)
%
% Multi-level kmeans.
% Tries very hard to always return k clusters.
%
% INPUT
% k Number of clusters
% data dxn matrix of data points
% 'maxiter' Max number of iterations. [30]
% 'dtol' Min change in cen... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBench.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/boundaryBench.m | 3,527 | utf_8 | 72c57116e042a9982380b57fb6535200 | function boundaryBench(pbDir,pres,nthresh,fast)
% function boundaryBench(pbDir,pres,nthresh,fast)
%
% Run the boundary detector benchmark on the Pb files found in
% pbDir for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
if nargin<3, nthresh=30; end
if ... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphsMulti.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/boundaryBenchGraphsMulti.m | 3,290 | utf_8 | 329d8ab5d50641ff5c45b80ea534c65b | function boundaryBenchGraphsMulti(baseDir)
% function boundaryBenchGraphsMulti(baseDir)
%
% See also boundaryBenchGraphs.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
presentations = {'gray','color'};
presNames = {'Grayscale','Color'};
iidsTest = imgList('test');
% Infer list of algorithms from directorie... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchGraphsHuman.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/boundaryBenchGraphsHuman.m | 2,305 | utf_8 | 22ab87b11ee29175d476f559f66be48d | function boundaryBenchGraphsHuman(pbDir)
% function boundaryBenchGraphsHuman(pbDir)
%
% Create graphs, after boundaryBenchHuman has been run.
%
% See also boundaryBenchHuman.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
iids = imgList('test');
n = numel(iids);
% read in all the data
fwrite(2,'Reading data... |
github | HzFu/VideoCoSeg_MSG-master | boundaryBenchHuman.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/lib/matlab/boundaryBenchHuman.m | 2,560 | utf_8 | dbf3eae48252f53e5d2042206192db85 | function boundaryBenchHuman(pbRoot,pres)
% function boundaryBenchHuman(pbRoot,pres)
%
% Compute the human precision/recall data for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
iids = imgList('test');
cR_total = 0;
sR_total = 0;
cP_total = 0;
sP_total... |
github | HzFu/VideoCoSeg_MSG-master | cgmo.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Gradients/cgmo.m | 4,181 | utf_8 | 6c29fc1b4d710f1f7fa1e4448062c599 | function [cg,theta] = cgmo(im,radius,norient,varargin)
% function [cg] = cgmo(im,radius,norient,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% norient Number of orientations for cg.
% 'nbins'... |
github | HzFu/VideoCoSeg_MSG-master | cgso.m | .m | VideoCoSeg_MSG-master/external/proposals/external/segbench/Gradients/cgso.m | 4,061 | utf_8 | b6247b3c62e7cdc72babce695b7096e3 | function [cg,theta] = cgso(im,radius,theta,varargin)
% function [cg] = cgso(im,radius,theta,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% theta Orientation orthogonal to cg.
% 'nbins' Numbe... |
github | HzFu/VideoCoSeg_MSG-master | msTestImage2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTestImage2.m | 3,849 | utf_8 | f0a2d95d9a27727aa8bb738afbc97b10 | function [pg, data, imsegs] = msTestImage2(im, imsegs, classifiers, nsegments, normalize, ...
smaps, spdata, adjlist, edata)
% [pg, data, imsegs] = msTestImage(im, imsegs, classifiers, nsegments, smaps,
% spdata, adjlist, edata)
%
% Computes the marginals of the labels for the given input image
% spdata, adjlist,... |
github | HzFu/VideoCoSeg_MSG-master | msFormatClassifierData.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msFormatClassifierData.m | 875 | utf_8 | c97ea1a533edade8509ed8b412b8b9f7 | %% Reformat the input data to be used by classifier
function [data, lab, w] = msFormatClassifierData(features, labels, weights, maxdata)
% concatenate data
nimages = numel(features);
[tmp, nvars] = size(features{1});
% count segments
nseg = 0;
for f = 1:nimages
nseg = nseg + sum(labels{f}~=0);
end
data = zeros... |
github | HzFu/VideoCoSeg_MSG-master | msTrainLabelClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTrainLabelClassifier.m | 1,753 | utf_8 | 3e435b6d0945729104224658d82dc298 | function classifier = msTrainLabelClassifier(features, labels, weights, classnames, maxdata, classparams)
if exist('classparams', 'var') && ~isempty(classparams)
nnodes = classparams(1);
ntrees = classparams(2);
stopval = classparams(3);
else
nnodes = 8;
ntrees = 20;
stopval = 0;
end
if ~exist... |
github | HzFu/VideoCoSeg_MSG-master | msTestImage.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTestImage.m | 3,772 | utf_8 | 7bd6f224c02a731f813a6ea9e6fface1 | function [pg, data, imsegs] = msTestImage(im, imsegs, classifiers, nsegments, normalize, ...
smaps, spdata, adjlist, edata)
% [pg, data, imsegs] = msTestImage(im, imsegs, classifiers, nsegments, smaps,
% spdata, adjlist, edata)
%
% Computes the marginals of the labels for the given input image
% spdata, adjlist, ... |
github | HzFu/VideoCoSeg_MSG-master | msCreateMultipleSegmentations.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msCreateMultipleSegmentations.m | 5,003 | utf_8 | 8ee20b40091cb9bb99d8a97d3b399f56 | function smaps = msCreateMultipleSegmentations(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 | msPruneSegments.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msPruneSegments.m | 736 | utf_8 | 29d2be22e3728f7f0b913dbd79bcc85a | %% Remove duplicate segments
function smaps2 = msPruneSegments(smaps)
smaps2 = smaps;
segment_list = {};
for m = 1:size(smaps, 2)
for k = 1:max(smaps(:, m))
ind = smaps(:, m)==k;
[segment_list, isnew] = prune_add2list(segment_list, find(ind));
if ~isnew
smaps2(ind, m) = 0;
... |
github | HzFu/VideoCoSeg_MSG-master | msTestRf.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTestRf.m | 2,388 | utf_8 | d314f0933b1322ffcf039ed041954da3 | function pg = msTestRf(imsegs, data, maps, dtlab, dtseg, normalize)
% [vacc, hacc, vcm, hcm] = testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, vclassifier, hclassifier, sclassifier, ncv)
if ~exist('normalize', 'var') || isempty(normalize)
normalize = 1;
end
pg = cell(numel(imsegs), 1);
nclasses = si... |
github | HzFu/VideoCoSeg_MSG-master | msTrainEdgeClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTrainEdgeClassifier.m | 1,034 | utf_8 | 5772209099af2732242ca319ad47d097 | function eclassifier = mcmcTrainEdgeClassifier(efeatures, adjlist, imsegs, labels)
ntrees = 20;
nnodes = 8;
ndata = 50000;
% train {ground, vertical, sky} classifier
[edata, elab] = formatData(efeatures, adjlist, labels, ndata);
mean(elab==1)
eclassifier = train_boosted_dt_2c(edata, [], elab, ntrees, nnodes, 0);
... |
github | HzFu/VideoCoSeg_MSG-master | msCalibrateEdgeClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msCalibrateEdgeClassifier.m | 2,992 | utf_8 | 7c0daa45d05ba0e3a6ac89d6828fcc08 | function [eparams, errors] = msCalibrateEdgeClassifier(efeatures, adjlist, imsegs, eclassifier, labels, ncv)
% [eparams, errors] = calibrateEdgeClassifier(efeatures, adjlist, imsegs,
% eclassifier, ncv)
nimages = numel(imsegs);
for k = 1:ncv
if ncv > 1
testind = [(k-1)*nimages/ncv+1:k*nimages/ncv];
... |
github | HzFu/VideoCoSeg_MSG-master | msTest.m | .m | VideoCoSeg_MSG-master/external/proposals/src/multipleSegmentations/msTest.m | 2,592 | utf_8 | dd9814df4834324a78f9cc8c5f592661 | function pg = msTest(imsegs, data, maps, labelclassifier, segclassifier, normalize)
% pg = msTest(imsegs, data, maps, labelclassifier, segclassifier, normalize)
%
% Given features, classifies image and outputs label confidences (pg)
if ~exist('normalize', 'var') || isempty(normalize)
normalize = 1;
end
pg = cel... |
github | HzFu/VideoCoSeg_MSG-master | poly2featuresOnly.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/poly2featuresOnly.m | 832 | utf_8 | 60589c24179a37ed892cb5f1b190a665 | function feat = poly2featuresOnly(u, v, imsize, v0, yc, f)
imh = imsize(1);
imw = imsize(2);
if isempty(f)
f = 1.38; %S*max(size(im)) / imh;
end
u = u(:)';
v = v(:)';
[tmp, ind] = min(u);
u = [u(ind:end) u(1:ind-1)];
v = [v(ind:end) v(1:ind-1)];
u = (u - imw/2) ./ imh;
v = 1 - (v ./ imh);
[v1, ind1] = min(... |
github | HzFu/VideoCoSeg_MSG-master | mergeMinSafe.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/mergeMinSafe.m | 8,367 | utf_8 | 1bf3df7c485b75b07c6cf2f877f29860 | function [result, valdata, dispim] = ...
mergeMinSafe(pB, bndinfo, X, dtFast, maxProb, minRegions, DO_VAL)
% [result, valdata, dispim] = mergeMinSafe(pB, bndinfo, X, maxProb, minRegions, DO_VAL)
%
% Note that (as oppoosed to mergeMin) edges here are undirected. Also,
% when new edgelets are created, their likeliho... |
github | HzFu/VideoCoSeg_MSG-master | poly2contacts.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/poly2contacts.m | 1,672 | utf_8 | 8819c0c37ff506e1843e057d92f55c9c | function [cu, cv, cx, cz, footprint, feat] = poly2contacts(dt, u, v, imsize, v0, yc, f, minp, im)
if ~exist('minp', 'var')
minp = 0.5;
end
imh = imsize(1);
imw = imsize(2);
if isempty(f)
f = 1.38; %S*max(size(im)) / imh;
end
u = u(:)';
v = v(:)';
if exist('im', 'var')
figure(1), hold off, imshow(im), h... |
github | HzFu/VideoCoSeg_MSG-master | boundaries2hierarchy.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/occlusion/boundaries2hierarchy.m | 6,097 | utf_8 | d41dfc9404d1118172f900564f0f011a | function hier = boundaries2hierarchy(pB, spLR, cost_method, norm, wseg, cost)
% [result, valdata, dispim] = mergeMinSafe(pB, bndinfo, X, maxProb, minRegions, DO_VAL)
%
% Note that (as oppoosed to mergeMin) edges here are undirected. Also,
% when new edgelets are created, their likelihoods are re-evaluated to
% ensure... |
github | HzFu/VideoCoSeg_MSG-master | regions2hog.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/occlusion/regions2hog.m | 4,818 | utf_8 | d3c2846f4e1b29353a4a2ef89d6601c3 | function hog = regions2hog(regions, bndinfo, pb1, pb2, norient, hogSize)
%% get basic edge statistics
edges = bndinfo.edges;
theta = edges.thetaDirected; % range from 0 to pi, left side occludes
ind_c = getBoundaryCenterIndices(bndinfo);
[ey, ex] = ind2sub(bndinfo.imsize, ind_c);
ew = zeros(bndinfo.ne, 1);
for k = 1:... |
github | HzFu/VideoCoSeg_MSG-master | regions2mog.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/occlusion/regions2mog.m | 4,893 | utf_8 | 113b4fd459fb0bb112524b926a78697d | function hog = regions2mog(regions, bndinfo, pb1, pb2, norient, hogSize)
% hog = regions2mog(regions, bndinfo, pb1, pb2, norient, hogSize)
% maximum of gradient pyramid
%% get basic edge statistics
edges = bndinfo.edges;
theta = edges.thetaDirected; % range from 0 to pi, left side occludes
ind_c = getBoundaryCenterInd... |
github | HzFu/VideoCoSeg_MSG-master | fit_poly_to_fragment.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/andrew/fit_poly_to_fragment.m | 2,727 | utf_8 | d946064e20dc5f1e2b3b166709efe572 | function [curve, params, errors] = fit_poly_to_fragment(fragment, order)
%
%[curve, params, errors] = fit_poly_to_fragment(fragment, order)
%
% Fit a polynomial curve of specified order to an edge fragment. A
% fragment is simply an Nx2 vector of (x,y) coordinates.
%
% Can also return fit error and the polynomial par... |
github | HzFu/VideoCoSeg_MSG-master | fill_in_segmentation.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/andrew/fill_in_segmentation.m | 3,472 | utf_8 | 7c004304fe719a26f958ee32bac0b7a1 | function seg_new = fill_in_segmentation(img, seg, L, conn)
%
% seg_new = fill_in_segmentation(img, seg, <L>, <conn>)
%
% Fills in the unlabeled pixels of a segmentation 'seg'. Those pixels
% that are pixels with a segmentation label L do not belong to any
% valid region. Fill them in by associating them with the n... |
github | HzFu/VideoCoSeg_MSG-master | cracks2fragments.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/andrew/cracks2fragments.m | 13,810 | utf_8 | a853fa2e666b2194c298c0a6a4062e09 | function [fragments, junctions, neighbor_lookups] = cracks2fragments(crack_img, seg, isolation_check)
%
% [fragments, junctions, neighbor_lookups] = cracks2fragments(crack_img, seg, isolation_check)
%
if(nargin<3)
isolation_check = true;
end
[nrows,ncols] = size(crack_img);
JUNCTION_BIT = 5;
% Get a lookup tabl... |
github | HzFu/VideoCoSeg_MSG-master | getDepthRangeForDisplay.m | .m | VideoCoSeg_MSG-master/external/proposals/src/iccv07Final/src/display/getDepthRangeForDisplay.m | 13,334 | utf_8 | ab289cfe3fc1d046dfd1bba0536f511d | function [imdepthMin, imdepthMax, imdepthCol, contact, x, y, z] = ...
getDepthRangeForDisplay(bndinfo, glabels, elabels, dt, v0)
% getMinimumDepth(bndinfo, glabels, v0)
%
% Minimum depth is the depth of the foremost occluder. Maximum depth is
% the depth of the current region, assuming that it is touching ground a... |
github | HzFu/VideoCoSeg_MSG-master | testMultipleSegmentationsCV_tmp.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testMultipleSegmentationsCV_tmp.m | 4,174 | utf_8 | 47c6b963ec00f81a6652ac3b160d59a1 | function [vacc, hacc, vcm, hcm, pg, pg2] = ...
testMultipleSegmentationsCV_tmp(imsegs, labdata, segdata, maps, ...
vclassifier, hclassifier, sclassifier, pvSP, phSP, ncv)
% [vacc, hacc, vcm, hcm] = testMultipleSegmentationsCV_tmp(imsegs, labdata,
% segdata, maps, vclassifier, hclassifier, sclassi... |
github | HzFu/VideoCoSeg_MSG-master | testImageGraphCuts2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testImageGraphCuts2.m | 2,983 | utf_8 | 3d2bcd25a0ccab4131176a3787c6ae6e | function [labv, labh] = testImageGraphCuts2(pg, edata, adjlist, eclassifier, ecal, alpha)
[pvSP, phSP] = splitpg(pg);
% edge probability
pE = test_boosted_dt_mc(eclassifier, edata);
pE = 1 ./ (1+exp(ecal(1)*pE+ecal(2)));
labv = alphaExpansion(pvSP, pE, adjlist, alpha);
[tmp, labh] = max(phSP, [], 2);
vind = find(la... |
github | HzFu/VideoCoSeg_MSG-master | testImageGraphCuts.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testImageGraphCuts.m | 3,400 | utf_8 | e35ec5ffab3dbfdec29ae2970df9bfa9 | function [labv, labh] = testImageGraphCuts(spdata, edata, adjlist, vclassifierSP, hclassifierSP, eclassifier, ecal)
% probability of superpixel main labels
pvSP = test_boosted_dt_mc(vclassifierSP, spdata);
pvSP = 1 ./ (1+exp(-pvSP));
pvSP = pvSP ./ repmat(sum(pvSP, 2), 1, size(pvSP, 2));
[tmp, vmax] = max(pvSP, [], 2)... |
github | HzFu/VideoCoSeg_MSG-master | getTwoJunctions.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/getTwoJunctions.m | 2,062 | utf_8 | 00e5f91f58d1cb907cb5d8cd26218329 | function getTwoJunctions(imsegs, adjlist)
[boundmap, perim] = mcmcGetSuperpixelBoundaries(imsegs);
boundmap = boundmap{1};
perim = perim{1};
nsp = imsegs.nseg;
allperim = zeros(nsp, 1);
for s = 1:nsp
allperim(s) = sum(perim(s, :)) + sum(perim(:, s));
end
[ny, nx] = size(imsegs.segimage);
nadj = size(adjlist... |
github | HzFu/VideoCoSeg_MSG-master | testMultipleSegmentationsCV2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testMultipleSegmentationsCV2.m | 2,441 | utf_8 | d803a1fe089d5ab4a55483fa108490d3 | function [vacc, hacc, vcm, hcm, pg] = ...
testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, ...
vclassifier, hclassifier, sclassifier, pvSP, phSP, ncv)
% [vacc, hacc, vcm, hcm] = testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, vclassifier, hclassifier, sclassifier, ncv)
pg = cell(numel(... |
github | HzFu/VideoCoSeg_MSG-master | testMultipleSegmentationsCV2_vonly.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testMultipleSegmentationsCV2_vonly.m | 2,554 | utf_8 | 7427c03b66e934f425232e6f1039baf5 | function [vacc, vcm, pg] = ...
testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, ...
vclassifier, sclassifier, pvSP, ncv)
% [vacc, hacc, vcm, hcm] = testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, vclassifier, hclassifier, sclassifier, ncv)
pg = cell(numel(imsegs), 1);
allcount = 0;
fo... |
github | HzFu/VideoCoSeg_MSG-master | regressMajorityPercentage.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/regressMajorityPercentage.m | 3,062 | utf_8 | 97f3c8ab7bf15cb94b2d6cb4ba171740 | function [coef, bias, variance] = regressMajorityPercentage(smaps, pv, ph, imsegs)
% estimate the percentage of a region occupied by the majority label, given
% some estimate of the superpixel label likelihoods
ndata = 0;
for f = 1:numel(smaps)
for m = 1:size(smaps{f}, 2)
ndata = ndata + max(smaps{f}(:, m)... |
github | HzFu/VideoCoSeg_MSG-master | testSingleSegmentationsCV.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testSingleSegmentationsCV.m | 1,560 | utf_8 | b875797653152121fbdb349db5964cfd | function [vacc, hacc, vcm, hcm, pg] = ...
testSingleSegmentationsCV(imsegs, labdata, maps, vclassifier, hclassifier, ncv)
% [vacc, hacc, vcm, hcm, pg] = testSingleSegmentationsCV(
% imsegs, labdata, maps, vclassifier, hclassifier, ncv)
pg = cell(numel(imsegs), 1);
for f = 1:numel(imsegs)
... |
github | HzFu/VideoCoSeg_MSG-master | calibrateEdgeClassifier.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/calibrateEdgeClassifier.m | 2,865 | utf_8 | d065d08ae24c40e6abad813dbc0cd384 | function [eparams, errors] = calibrateEdgeClassifier(efeatures, adjlist, imsegs, eclassifier, ncv)
% [eparams, errors] = calibrateEdgeClassifier(efeatures, adjlist, imsegs,
% eclassifier, ncv)
nimages = numel(imsegs);
for k = 1:ncv
testind = [(k-1)*nimages/ncv+1:k*nimages/ncv];
trainind = setdiff([1:nimage... |
github | HzFu/VideoCoSeg_MSG-master | testMultipleSegmentationsCV3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testMultipleSegmentationsCV3.m | 2,422 | utf_8 | 15688fd1dd3eee30813652eb1a679a81 | function [vacc, hacc, vcm, hcm, pg] = ...
testMultipleSegmentationsCV3(imsegs, labdata, segdata, maps, ...
vclassifier, hclassifier, svclassifier, shclassifier, pvSP, phSP, ncv)
% [vacc, hacc, vcm, hcm] = testMultipleSegmentationsCV2(imsegs, labdata, segdata, maps, vclassifier, hclassifier, sclassifier, ncv)
p... |
github | HzFu/VideoCoSeg_MSG-master | testImageGraphCuts3.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/testImageGraphCuts3.m | 3,988 | utf_8 | e1bb8e00fa3ecc2317161e385d16f976 | function [labv, labh] = testImageGraphCuts3(im, imsegs, cimages, alpha)
adjmat = imsegs.adjmat;
nsp = imsegs.nseg;
spstats = regionprops(imsegs.segimage, 'PixelIdxList');
pixidx = {spstats(:).PixelIdxList};
classinds = {1, 2, 3, 4, 5, 6, 7};
pg = conf2pg(cimages, pixidx, classinds);
[pvSP, phSP] = splitpg(pg);
[s1,... |
github | HzFu/VideoCoSeg_MSG-master | pg2prcurve.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/pg2prcurve.m | 1,451 | utf_8 | 898cb28243b8b0af66d537c7f352232a | function [prv, prh] = pg2prcurve(pg, imsegs)
% For varying levels of confidence, compute roc curves (tp vs fp) for the
% vertical labels and the horizontal labels
% labels(num_im).{vert_labels(h, w), vert_conf(h, w), horz_labels(h, w),
% horz_conf(h, w)
[pv, ph] = splitpg(pg);
[y, c, w] = initData(pv, {imsegs(:).vert... |
github | HzFu/VideoCoSeg_MSG-master | train_boosted_kde_2c.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/boosting/train_boosted_kde_2c.m | 4,111 | utf_8 | c1985d62fd7ff3b62fc945d7e2c82fd4 | function density = train_boosted_kde_2c(data, labels, ranges, num_iter)
% Try to learn ln(P(x1, x2 | +)/P(x1, x2 | -), where + indicates that a pair of points,
% x, are in the same cluster and - indicates that the pair are in different
% clusters. Use boosting to estimate the parameters of the density in a
% naive str... |
github | HzFu/VideoCoSeg_MSG-master | labelImageGeometry.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/misc/labelImageGeometry.m | 3,385 | utf_8 | 695427a5efea405f52a7273067f808ff | function imsegs = labelImageGeometry(im, imsegs)
% Label the superpixels of the image
segimage = double(imsegs.segimage);
nc = 7;
if max(size(segimage)>600)
rs = 600/max(size(segimage));
segimage = imresize(segimage, rs, 'nearest');
im = imresize(im, rs, 'nearest');
end
try
labels = imsegs.labels;
ca... |
github | HzFu/VideoCoSeg_MSG-master | piecewise_linear_spline2.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/misc/piecewise_linear_spline2.m | 6,634 | utf_8 | 791866496cbe380e84a0664bfd3f4463 | function p = piecewise_linear_spline2(x, y, max_seg)
% performs piecewise linear spline for 2-d points x(1:npts) and
% y(1:ntps) when the number of segments is not known
% p - rows are parameters for each line:
% y = p(1)*x + p(2) for points with indices p(3) to p(4)
[x, ind] = sort(x);
y = y(ind);
npts = le... |
github | HzFu/VideoCoSeg_MSG-master | piecewise_linear_spline.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/misc/piecewise_linear_spline.m | 3,335 | utf_8 | 89b142a28bec7c0b4e97ee031db8caf8 | function p = piecewise_linear_spline(x, y, max_seg)
% performs piecewise linear spline for 2-d points x(1:npts) and
% y(1:ntps) when the number of segments is not known
% p - rows are parameters for each line:
% y = p(1)*x + p(2) for points with indices p(3) to p(4)
[x, ind] = sort(x);
y = y(ind);
npts = len... |
github | HzFu/VideoCoSeg_MSG-master | treetestw.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/treetestw.m | 11,926 | utf_8 | c962b14259cd0f2d21f8e3d0aa25e757 | function [cost,secost,ntnodes,bestlevel] = treetestw(Tree,TorCorR,X,Y,w,varargin)
%TREETEST Compute error rate for tree.
% COST = TREETEST(T,'resubstitution') computes the cost of the tree T
% using a resubstitution method. T is a decision tree as created by
% the TREEFIT function. The cost of the tree is the s... |
github | HzFu/VideoCoSeg_MSG-master | ksdensityw.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/ksdensityw.m | 5,397 | utf_8 | 140dd42a35ba132a8c87760ccd7fb3a1 | function [f,x,u]=ksdensityw(y,w,varargin)
%KSDENSITY Compute density estimate
% [F,XI]=KSDENSITY(X) computes a probability density estimate of the sample
% in the vector X. F is the vector of density values evaluated at the
% points in XI. The estimate is based on a normal kernel function, using a
% window pa... |
github | HzFu/VideoCoSeg_MSG-master | treefitw.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/treefitw.m | 18,534 | utf_8 | f353f7dd7444e77e7c6fb702b277a577 | function Tree=treefitw(X,y,w, equivsample, varargin)
%TREEFIT Fit a tree-based model for classification or regression.
% T = TREEFIT(X,Y) creates a decision tree T for predicting response Y
% as a function of predictors X. X is an N-by-M matrix of predictor
% values. Y is either a vector of N response values (f... |
github | HzFu/VideoCoSeg_MSG-master | statsfminbx.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/statsfminbx.m | 36,458 | utf_8 | c578fea573fd473845905084832b4e7d | function[x,FVAL,LAMBDA,EXITFLAG,OUTPUT,GRAD,HESSIAN]=statsfminbx(funfcn,x,l,u,verb,options,defaultopt,...
computeLambda,initialf,initialGRAD,initialHESS,Hstr,varargin)
%SFMINBX Nonlinear minimization with box constraints.
%
% Locate a local minimizer to
%
% min { f(x) : l <= x <= u}.
%
% where f(x) ma... |
github | HzFu/VideoCoSeg_MSG-master | addlogi.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addlogi.m | 12,286 | utf_8 | d45455f1c05b3a9d6ac3ebdeb50c53a7 | function s = addlogi(s)
%ADDLOGI Add the logistic adistributions.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.9 $ $Date: 2004/01/24 09:35:06 $
j = length(s) + 1;
s(j).name = 'Logistic';
s(j).code = 'logistic';
s(j).pnames = {'mu' 'sigma'};
s(j).pdescription = {'location' 'scale'};
s(j).prequired... |
github | HzFu/VideoCoSeg_MSG-master | addinvg.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addinvg.m | 8,904 | utf_8 | c8e9fd070db8af95f85df6b2480b8e41 | function s = addinvg(s)
%ADDINVG Add the inverse Gaussian distribution.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.10 $ $Date: 2004/04/15 01:01:53 $
j = length(s) + 1;
s(j).name = 'Inverse Gaussian';
s(j).code = 'inversegaussian';
s(j).pnames = {'mu' 'lambda'};
s(j).pdescription = {'scale' 'sha... |
github | HzFu/VideoCoSeg_MSG-master | dfgetdistributions.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfgetdistributions.m | 8,975 | utf_8 | 9f973c5bf13c0f1adf0bcae341aa566d | function [s,errid] = dfgetdistributions(distname,douser)
%DFGETDISTRIBUTIONS Get structure defining the distributions supported by dfittool
% $Revision: 1.1.6.8 $ $Date: 2004/01/24 09:35:36 $
% Copyright 2003-2004 The MathWorks, Inc.
errid = '';
% If a struct was passed in, store this for later use
if nargin>0 ... |
github | HzFu/VideoCoSeg_MSG-master | dfsetdistributions.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfsetdistributions.m | 1,527 | utf_8 | 026a62bf16dfb7ef14dddb1d4b77dfa6 | function dfsetdistributions(dft,dists)
%DFSETDISTRIBUTIONS Set distribution information into the gui
% $Revision: 1.1.6.5 $ $Date: 2004/01/24 09:35:49 $
% Copyright 2003-2004 The MathWorks, Inc.
% Store for later use in M
dfgetset('alldistributions',dists);
% Set into the gui, placing nonparametric fit into sor... |
github | HzFu/VideoCoSeg_MSG-master | dfsession.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfsession.m | 7,927 | utf_8 | 54fed362ef7733cf4ac0c3dd5777b386 | function ok=dfsession(action,fn)
%DFSESSION Clear, load, or save a Distribution Fitting session
% $Revision: 1.1.6.7 $ $Date: 2004/02/01 22:10:39 $
% Copyright 2003-2004 The MathWorks, Inc.
% Create a structure with version information
str.ftype = 'Distribution Fitting session'; % type of file
str.version = 1;... |
github | HzFu/VideoCoSeg_MSG-master | export2wsdlg.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/export2wsdlg.m | 16,896 | utf_8 | 69eb6d711e16f71042d21882e0a10159 | function hDialog=export2wsdlg(checkboxLabels, defaultVariableNames, itemsToExport, varargin)
%EXPORT2WSDLG Exports variables to the workspace.
% EXPORT2WSDLG(CHECKBOXLABELS, DEFAULTVARIABLENAMES, ITEMSTOEXPORT) creates
% a dialog with a series of checkboxes and edit fields. CHECKBOXLABELS is a
% cell array of l... |
github | HzFu/VideoCoSeg_MSG-master | statrobustfit.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/statrobustfit.m | 4,008 | utf_8 | 83f9e0c6d9b47e1a6aa48b7eeb8c4243 | function [b,stats] = statrobustfit(X,y,wfun,tune,wasnan,addconst)
%STATROBUSTFIT Calculation function for ROBUSTFIT
% Tom Lane 2-11-2000
% Copyright 1993-2002 The MathWorks, Inc.
% $Revision: 1.4 $ $Date: 2002/02/04 19:25:48 $
% Must check for valid function in this scope
c = class(wfun);
fnclass = class(@bisquare)... |
github | HzFu/VideoCoSeg_MSG-master | dfgetuserdists.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfgetuserdists.m | 9,743 | utf_8 | f3e2ede226f6c60ee9d442835e6b45f5 | function [news,errid,errmsg,newrows]=dfgetuserdists(olds,userfun)
%GETUSERDISTS Get user-defined distributions for dfittool
% [NEWS,ERRID,ERRMSG,NEWROWS]=GETUSERDISTS(OLDS) appends user-defined
% distribution information to the existing distribution information
% in the structure OLDS and returns the combined inf... |
github | HzFu/VideoCoSeg_MSG-master | dfaddparamfit.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfaddparamfit.m | 7,849 | utf_8 | 6b6e3650c370d58307f1776bed38372a | function hFit = dfaddparamfit(hFit, fitname, distname, dsname, fitframe, exclname, useestimated, fixedvals)
%DFADDPARAMFIT Add parametric fit in dfittool
% $Revision: 1.1.6.10 $ $Date: 2004/01/24 09:35:10 $
% Copyright 2003-2004 The MathWorks, Inc.
badfit = false; % badfit=true means fit failed or not attempt... |
github | HzFu/VideoCoSeg_MSG-master | dfdocontext.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfdocontext.m | 7,544 | utf_8 | a29a9a8c6c98be459fb394071737bacd | function dfdocontext(varargin)
%DFDOCONTEXT Perform context menu actions for distribution fitting tool
% Copyright 2001-2004 The MathWorks, Inc.
% $Revision: 1.1.6.7 $ $Date: 2004/03/09 16:17:04 $
import com.mathworks.toolbox.stats.*;
% Special action to create context menus
if isequal(varargin{1},'create')
make... |
github | HzFu/VideoCoSeg_MSG-master | dfupdateylim.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfupdateylim.m | 2,235 | utf_8 | f5761237221224280dc7e15ca23c0c11 | function dfupdateylim
%DFUPDATEYLIM Update the y axis min/max values
% $Revision: 1.1.6.4 $ $Date: 2004/01/24 09:36:04 $
% Copyright 2003-2004 The MathWorks, Inc.
dminmax = []; % to indicate y data limits
% Check y limits of all fits
fminmax = [];
fitdb = getfitdb;
ft = down(fitdb);
while(~is... |
github | HzFu/VideoCoSeg_MSG-master | dfupdateallplots.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfupdateallplots.m | 1,446 | utf_8 | 68ae20d6b67e69513639acd1ec70ef14 | function dfupdateallplots(dods,dofit,force)
%DFUPDATEALLPLOTS Call update methods for all data sets and fits
% $Revision: 1.1.6.5 $ $Date: 2004/01/24 09:35:59 $
% Copyright 2003-2004 The MathWorks, Inc.
le = lasterr;
msg = '';
if nargin<3
force = false;
end
% Supply defaults if missing or if called as a list... |
github | HzFu/VideoCoSeg_MSG-master | stdrinv.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/stdrinv.m | 2,425 | utf_8 | 59403e15503f9afe88589435d94f796d | function x = stdrinv(p, v, r)
%STDRINV Compute inverse c.d.f. for Studentized Range statistic
% STDRINV(P,V,R) is the inverse cumulative distribution function for
% the Studentized range statistic for R samples and V degrees of
% freedom, evaluated at P.
% Copyright 1993-2002 The MathWorks, Inc.
% $Revision... |
github | HzFu/VideoCoSeg_MSG-master | mlecustom.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/mlecustom.m | 20,093 | utf_8 | 884ff6829a9477a1b11b0c89db63a7c9 | function [phat, pci] = mlecustom(data,varargin)
%MLE Maximum likelihood estimation for custom univariate distributions.
%
% See help for MLE.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.7 $ $Date: 2004/04/04 03:42:19 $
% Process any optional input arguments.
pnames = {'pdf' 'cdf' 'logpdf' 'log... |
github | HzFu/VideoCoSeg_MSG-master | dfaxlimctrl.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfaxlimctrl.m | 11,374 | utf_8 | 0c50c1293a0421e9c3381b159a9fba2f | function dfaxlimctrl(dffig,onoff)
%DFAXLIMCTRL Turn on or off the controls for adjusting axis limits
% $Revision: 1.1.6.2 $ $Date: 2004/01/24 09:35:16 $
% Copyright 2001-2004 The MathWorks, Inc.
% Remove controls from figure if requested
if isequal(onoff,'off')
a = findall(dffig,'Tag','axlimctrl');
delete... |
github | HzFu/VideoCoSeg_MSG-master | dfevaluateplot.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfevaluateplot.m | 6,222 | utf_8 | ded62d78883b919718b6e91b3039db4d | function dfevaluateplot(plotFun,dum)
%DFEVALUATEPLOT Plot data and evaluated fits for DFITTOOL
% $Revision: 1.1.6.3 $ $Date: 2004/01/24 09:35:33 $
% Copyright 1993-2004 The MathWorks, Inc.
plotfig = dfgetset('evaluateFigure');
% If no plotting selected, delete the existing figure if there is one
if ~plotFun % &... |
github | HzFu/VideoCoSeg_MSG-master | addrice.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addrice.m | 6,577 | utf_8 | 8642ad1e0c4dbafd4f96bfa8fae5ecf2 | function s = addrice(s)
%ADDRICE Add the Rician distribution.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.10 $ $Date: 2004/02/01 22:10:34 $
j = length(s) + 1;
s(j).name = 'Rician';
s(j).code = 'rician';
s(j).pnames = {'s' 'sigma'};
s(j).pdescription = {'noncentrality' 'scale'};
s(j).prequired = ... |
github | HzFu/VideoCoSeg_MSG-master | dfupdatexlim.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfupdatexlim.m | 2,510 | utf_8 | 2896ee2fbcfd6a212e7926a8a5f7873b | function dfupdatexlim(newminmax,updateplots)
%DFUPDATEXLIM Update the stored x axis min/max values
% $Revision: 1.1.6.5 $ $Date: 2004/01/24 09:36:03 $
% Copyright 2003-2004 The MathWorks, Inc.
minmax = []; % to become new x limits
oldminmax = dfgetset('xminmax'); % previous limits
ftype = dfg... |
github | HzFu/VideoCoSeg_MSG-master | addbisa.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addbisa.m | 6,521 | utf_8 | 8abfd966c21c7a2505ca77f6a6a5b446 | function s = addbisa(s)
%ADDBISA Add the Birnbaum-Saunders distribution.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.8 $ $Date: 2004/01/24 09:35:04 $
j = length(s) + 1;
s(j).name = 'Birnbaum-Saunders';
s(j).code = 'birnbaumsaunders';
s(j).pnames = {'beta' 'gamma'};
s(j).pdescription = {'scale' '... |
github | HzFu/VideoCoSeg_MSG-master | statctexact.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/statctexact.m | 8,490 | utf_8 | b468776545db437f44c77ddec1e78a3c | function pval=statctexact(x,wts,tstar,dispopt)
%STATCTEXACT Compute exact p-value for contingency table
% P=STATCTEXACT(X,WTS,T,DISPOPT) uses a network algorithm to compute
% the exact p-value P for a 2-by-K contingency table X. The test
% statistic T is the weighted sum of the elements in the first row.
% Se... |
github | HzFu/VideoCoSeg_MSG-master | dfaddbuttons.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfaddbuttons.m | 6,442 | utf_8 | 2ff8d56af47a2c75c7e74bfcff2dc3d5 | function dfaddbuttons(dffig)
%DFADDBUTTONS Add buttons to the curve fitting plot figure window
% $Revision: 1.1.6.8 $ $Date: 2004/01/24 09:35:09 $
% Copyright 2003-2004 The MathWorks, Inc.
% Clear out any old stuff
h0 = findall(dffig,'Type','uicontrol','Style','pushbutton');
if ~isempty(h0), delete(h0); end
p0 =... |
github | HzFu/VideoCoSeg_MSG-master | dfupdateppdists.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/dfupdateppdists.m | 3,087 | utf_8 | 0cc18da7156a500080c528bc531eb10f | function dfupdateppdists(dffig)
%DFUPDATEPPDISTS Update distribution list for probability plots
% $Revision: 1.1.6.5 $ $Date: 2004/01/24 09:36:02 $
% Copyright 2003-2004 The MathWorks, Inc.
if nargin<1 || isempty(dffig)
dffig = dfgetset('dffig');
end
% Get handle to control containing the distribution list
h... |
github | HzFu/VideoCoSeg_MSG-master | addnaka.m | .m | VideoCoSeg_MSG-master/external/proposals/src/GeometricContext/tools/weightedstats/private/addnaka.m | 4,398 | utf_8 | 7e2b6a144e25ceacc9b853738b1cbac7 | function s = addnaka(s)
%ADDNAKA Add the Nakagami distribution.
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 1.1.6.7 $ $Date: 2003/12/11 03:50:49 $
j = length(s) + 1;
s(j).name = 'Nakagami';
s(j).code = 'nakagami';
s(j).pnames = {'mu' 'omega'};
s(j).pdescription = {'shape' 'scale'};
s(j).prequired = [f... |
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