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 | sgbasel/neuritetracker-master | vl_test_kdtree.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_kdtree.m | 2,449 | utf_8 | 9d7ad2b435a88c22084b38e5eb5f9eb9 | function results = vl_test_kdtree(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.X = single(randn(10, 1000)) ;
s.Q = single(randn(10, 10)) ;
function test_nearest(s)
for tmethod = {'median', 'mean'}
for type = {@single, @double}
conv = type{1} ;
tmethod = char(tmethod) ;... |
github | sgbasel/neuritetracker-master | vl_test_imwbackward.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_imwbackward.m | 514 | utf_8 | 33baa0784c8f6f785a2951d7f1b49199 | function results = vl_test_imwbackward(varargin)
% VL_TEST_IMWBACKWARD
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
function test_identity(s)
xr = 1:size(s.I,2) ;
yr = 1:size(s.I,1) ;
[x,y] = meshgrid(xr,yr) ;
vl_assert_almost_equal(s.I, vl_imwbackward(xr,yr,s.I,... |
github | sgbasel/neuritetracker-master | vl_test_alphanum.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_alphanum.m | 1,624 | utf_8 | 2da2b768c2d0f86d699b8f31614aa424 | function results = vl_test_alphanum(varargin)
% VL_TEST_ALPHANUM
vl_test_init ;
function s = setup()
s.strings = ...
{'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Al... |
github | sgbasel/neuritetracker-master | vl_test_printsize.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_printsize.m | 1,447 | utf_8 | 0f0b6437c648b7a2e1310900262bd765 | function results = vl_test_printsize(varargin)
% VL_TEST_PRINTSIZE
vl_test_init ;
function s = setup()
s.fig = figure(1) ;
s.usletter = [8.5, 11] ; % inches
s.a4 = [8.26772, 11.6929] ;
clf(s.fig) ; plot(1:10) ;
function teardown(s)
close(s.fig) ;
function test_basic(s)
for sigma = [1 0.5 0.2]
vl_printsize(s.fig, s... |
github | sgbasel/neuritetracker-master | vl_test_cummax.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_cummax.m | 838 | utf_8 | 5e98ee1681d4823f32ecc4feaa218611 | function results = vl_test_cummax(varargin)
% VL_TEST_CUMMAX
vl_test_init ;
function test_basic()
vl_assert_almost_equal(...
vl_cummax(1), 1) ;
vl_assert_almost_equal(...
vl_cummax([1 2 3 4], 2), [1 2 3 4]) ;
function test_multidim()
a = [1 2 3 4 3 2 1] ;
b = [1 2 3 4 4 4 4] ;
for k=1:6
dims = ones(1,6) ;
dim... |
github | sgbasel/neuritetracker-master | vl_test_imintegral.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_imintegral.m | 1,429 | utf_8 | 4750f04ab0ac9fc4f55df2c8583e5498 | function results = vl_test_imintegral(varargin)
% VL_TEST_IMINTEGRAL
vl_test_init ;
function state = setup()
state.I = ones(5,6) ;
state.correct = [ 1 2 3 4 5 6 ;
2 4 6 8 10 12 ;
3 6 9 12 15 18 ;
4 8 12 ... |
github | sgbasel/neuritetracker-master | vl_test_sift.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_sift.m | 1,318 | utf_8 | 806c61f9db9f2ebb1d649c9bfcf3dc0a | function results = vl_test_sift(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
s.I = im2single(imread(fullfile(vl_root,'data','box.pgm'))) ;
[s.ubc.f, s.ubc.d] = ...
vl_ubcread(fullfile(vl_root,'data','box.sift')) ;
function test_ubc_descriptor(s)
err = [] ;
[f, d] = vl_sift(s.I,...
... |
github | sgbasel/neuritetracker-master | vl_test_binsum.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_binsum.m | 1,377 | utf_8 | f07f0f29ba6afe0111c967ab0b353a9d | function results = vl_test_binsum(varargin)
% VL_TEST_BINSUM
vl_test_init ;
function test_three_args()
vl_assert_almost_equal(...
vl_binsum([0 0], 1, 2), [0 1]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, 1), [0 7]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, [1 2 2 2 2 2 2 2]), [0 0]) ;
function te... |
github | sgbasel/neuritetracker-master | vl_test_lbp.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_lbp.m | 892 | utf_8 | a79c0ce0c85e25c0b1657f3a0b499538 | function results = vl_test_lbp(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_unfiorm_lbps(s)
% enumerate the 56 uniform lbps
q = 0 ;
for i=0:7
for j=1:7
I = zeros(3) ;
p = mod(s.pixels - i + 8, 8) + 1 ;
I(p <= j) = 1 ;
f = vl_lbp(single(I), 3) ;
q = q + 1 ;
vl_assert_equal(find(f... |
github | sgbasel/neuritetracker-master | vl_test_colsubset.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_colsubset.m | 828 | utf_8 | be0c080007445b36333b863326fb0f15 | function results = vl_test_colsubset(varargin)
% VL_TEST_COLSUBSET
vl_test_init ;
function s = setup()
s.x = [5 2 3 6 4 7 1 9 8 0] ;
function test_beginning(s)
vl_assert_equal(1:5, vl_colsubset(1:10, 5, 'beginning')) ;
vl_assert_equal(1:5, vl_colsubset(1:10, .5, 'beginning')) ;
function test_ending(s)
vl_assert_equa... |
github | sgbasel/neuritetracker-master | vl_test_alldist.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_alldist.m | 2,373 | utf_8 | 9ea1a36c97fe715dfa2b8693876808ff | function results = vl_test_alldist(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist(zeros(15,12), zeros(15,0), 'kl2'), ...
zeros(12,0)) ;
vl_assert_equa... |
github | sgbasel/neuritetracker-master | vl_test_ihashsum.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_ihashsum.m | 581 | utf_8 | edc283062469af62056b0782b171f5fc | function results = vl_test_ihashsum(varargin)
% VL_TEST_IHASHSUM
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(round(16*rand(2,100))) ;
sel = find(all(s.data==0)) ;
s.data(1,sel)=1 ;
function test_hash(s)
D = size(s.data,1) ;
K = 5 ;
h = zeros(1,K,'uint32') ;
id = zeros(D,K,'uint8');
next = zer... |
github | sgbasel/neuritetracker-master | vl_test_grad.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_grad.m | 434 | utf_8 | 4d03eb33a6a4f68659f868da95930ffb | function results = vl_test_grad(varargin)
% VL_TEST_GRAD
vl_test_init ;
function s = setup()
s.I = rand(150,253) ;
s.I_small = rand(2,2) ;
function test_equiv(s)
vl_assert_equal(gradient(s.I), vl_grad(s.I)) ;
function test_equiv_small(s)
vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
function test_equiv... |
github | sgbasel/neuritetracker-master | vl_test_whistc.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_whistc.m | 1,384 | utf_8 | 81c446d35c82957659840ab2a579ec2c | function results = vl_test_whistc(varargin)
% VL_TEST_WHISTC
vl_test_init ;
function test_acc()
x = ones(1, 10) ;
e = 1 ;
o = 1:10 ;
vl_assert_equal(vl_whistc(x, o, e), 55) ;
function test_basic()
x = 1:10 ;
e = 1:10 ;
o = ones(1, 10) ;
vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ;
x = linspace(-1,11,100) ;
o =... |
github | sgbasel/neuritetracker-master | vl_test_roc.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_roc.m | 1,019 | utf_8 | 9b2ae71c9dc3eda0fc54c65d55054d0c | function results = vl_test_roc(varargin)
% VL_TEST_ROC
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[tpr,tnr] = vl_roc(s.labels,s.scores0) ;
vl_assert_almost_equal(tpr, [0 1 2 2 2 2] / 2) ;
vl_assert_almost_equal(tnr,... |
github | sgbasel/neuritetracker-master | vl_test_dsift.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_dsift.m | 2,048 | utf_8 | fbbfb16d5a21936c1862d9551f657ccc | function results = vl_test_dsift(varargin)
% VL_TEST_DSIFT
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = rgb2gray(single(I)) ;
function test_fast_slow(s)
binSize = 4 ; % bin size in pixels
magnif = 3 ; % bin size / keypoint scale
scale = binSize... |
github | sgbasel/neuritetracker-master | vl_test_alldist2.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_alldist2.m | 2,284 | utf_8 | 89a787e3d83516653ae8d99c808b9d67 | function results = vl_test_alldist2(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
% TODO: test integer classes
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist2(zeros(15,12), zeros(15,0), 'kl2'), ...
... |
github | sgbasel/neuritetracker-master | vl_test_fisher.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_fisher.m | 2,097 | utf_8 | c9afd9ab635bd412cbf8be3c2d235f6b | function results = vl_test_fisher(varargin)
% VL_TEST_FISHER
vl_test_init ;
function s = setup()
randn('state',0) ;
dimension = 5 ;
numData = 21 ;
numComponents = 3 ;
s.x = randn(dimension,numData) ;
s.mu = randn(dimension,numComponents) ;
s.sigma2 = ones(dimension,numComponents) ;
s.prior = ones(1,numComponents) ;
s... |
github | sgbasel/neuritetracker-master | vl_test_imsmooth.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_imsmooth.m | 1,837 | utf_8 | 718235242cad61c9804ba5e881c22f59 | function results = vl_test_imsmooth(varargin)
% VL_TEST_IMSMOOTH
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
I = max(min(vl_imdown(I),1),0) ;
s.I = single(I) ;
function test_pad_by_continuity(s)
% Convolving a constant signal padded with continuity does not change... |
github | sgbasel/neuritetracker-master | vl_test_svmtrain.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_svmtrain.m | 4,277 | utf_8 | 071b7c66191a22e8236fda16752b27aa | function results = vl_test_svmtrain(varargin)
% VL_TEST_SVMTRAIN
vl_test_init ;
end
function s = setup()
randn('state',0) ;
Np = 10 ;
Nn = 10 ;
xp = diag([1 3])*randn(2, Np) ;
xn = diag([1 3])*randn(2, Nn) ;
xp(1,:) = xp(1,:) + 2 + 1 ;
xn(1,:) = xn(1,:) - 2 + 1 ;
s.x = [xp xn] ;
s.y = [ones(1,Np) ... |
github | sgbasel/neuritetracker-master | vl_test_phow.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_phow.m | 549 | utf_8 | f761a3bb218af855986263c67b2da411 | function results = vl_test_phow(varargin)
% VL_TEST_PHOPW
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = single(s.I) ;
function test_gray(s)
[f,d] = vl_phow(s.I, 'color', 'gray') ;
assert(size(d,1) == 128) ;
function test_rgb(s)
[f,d] = vl_phow(s.I, 'color',... |
github | sgbasel/neuritetracker-master | vl_test_kmeans.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_kmeans.m | 3,632 | utf_8 | 0e1d6f4f8101c8982a0e743e0980c65a | function results = vl_test_kmeans(varargin)
% VL_TEST_KMEANS
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
function s = setup()
randn('sta... |
github | sgbasel/neuritetracker-master | vl_test_hikmeans.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_hikmeans.m | 463 | utf_8 | dc3b493646e66316184e86ff4e6138ab | function results = vl_test_hikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[tree, assign] = vl_hikmeans(s.data,3,100) ;
assign_ = vl_hikmeanspush(tree, s.data) ;
vl_assert_equal(assign,assign_) ;
function test_elka... |
github | sgbasel/neuritetracker-master | vl_test_aib.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_aib.m | 1,277 | utf_8 | 78978ae54e7ebe991d136336ba4bf9c6 | function results = vl_test_aib(varargin)
% VL_TEST_AIB
vl_test_init ;
function s = setup()
s = [] ;
function test_basic(s)
Pcx = [.3 .3 0 0
0 0 .2 .2] ;
% This results in the AIB tree
%
% 1 - \
% 5 - \
% 2 - / \
% - 7
% 3 - \ /
% 6 - /
% 4 - /
%
% coded by the map [5 ... |
github | sgbasel/neuritetracker-master | vl_test_plotbox.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_plotbox.m | 414 | utf_8 | aa06ce4932a213fb933bbede6072b029 | function results = vl_test_plotbox(varargin)
% VL_TEST_PLOTBOX
vl_test_init ;
function test_basic(s)
figure(1) ; clf ;
vl_plotbox([-1 -1 1 1]') ;
xlim([-2 2]) ;
ylim([-2 2]) ;
close(1) ;
function test_multiple(s)
figure(1) ; clf ;
randn('state', 0) ;
vl_plotbox(randn(4,10)) ;
close(1) ;
function test_style(s)
figure... |
github | sgbasel/neuritetracker-master | vl_test_imarray.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_imarray.m | 795 | utf_8 | c5e6a5aa8c2e63e248814f5bd89832a8 | function results = vl_test_imarray(varargin)
% VL_TEST_IMARRAY
vl_test_init ;
function test_movie_rgb(s)
A = rand(23,15,3,4) ;
B = vl_imarray(A,'movie',true) ;
function test_movie_indexed(s)
cmap = get(0,'DefaultFigureColormap') ;
A = uint8(size(cmap,1)*rand(23,15,4)) ;
A = min(A,size(cmap,1)-1) ;
B = vl_imarray(A,'m... |
github | sgbasel/neuritetracker-master | vl_test_homkermap.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_homkermap.m | 1,903 | utf_8 | c157052bf4213793a961bde1f73fb307 | function results = vl_test_homkermap(varargin)
% VL_TEST_HOMKERMAP
vl_test_init ;
function check_ker(ker, n, window, period)
args = {n, ker, 'window', window} ;
if nargin > 3
args = {args{:}, 'period', period} ;
end
x = [-1 -.5 0 .5 1] ;
y = linspace(0,2,100) ;
for conv = {@single, @double}
x = feval(conv{1}, x) ;... |
github | sgbasel/neuritetracker-master | vl_test_slic.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_slic.m | 200 | utf_8 | 12a6465e3ef5b4bcfd7303cd8a9229d4 | function results = vl_test_slic(varargin)
% VL_TEST_SLIC
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
function test_slic(s)
segmentation = vl_slic(s.im, 10, 0.1) ;
|
github | sgbasel/neuritetracker-master | vl_test_ikmeans.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_ikmeans.m | 466 | utf_8 | 1ee2f647ac0035ed0d704a0cd615b040 | function results = vl_test_ikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[centers, assign] = vl_ikmeans(s.data,100) ;
assign_ = vl_ikmeanspush(s.data, centers) ;
vl_assert_equal(assign,assign_) ;
function test_elk... |
github | sgbasel/neuritetracker-master | vl_test_mser.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_mser.m | 242 | utf_8 | 1ad33563b0c86542a2978ee94e0f4a39 | function results = vl_test_mser(varargin)
% VL_TEST_MSER
vl_test_init ;
function s = setup()
s.im = im2uint8(rgb2gray(vl_impattern('roofs1'))) ;
function test_mser(s)
[regions,frames] = vl_mser(s.im) ;
mask = vl_erfill(s.im, regions(1)) ;
|
github | sgbasel/neuritetracker-master | vl_test_inthist.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_inthist.m | 811 | utf_8 | 459027d0c54d8f197563a02ab66ef45d | function results = vl_test_inthist(varargin)
% VL_TEST_INTHIST
vl_test_init ;
function s = setup()
rand('state',0) ;
s.labels = uint32(8*rand(123, 76, 3)) ;
function test_basic(s)
l = 10 ;
hist = vl_inthist(s.labels, 'numlabels', l) ;
hist_ = inthist_slow(s.labels, l) ;
vl_assert_equal(double(hist),hist_) ;
function... |
github | sgbasel/neuritetracker-master | vl_test_imdisttf.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_imdisttf.m | 1,885 | utf_8 | ae921197988abeb984cbcdf9eaf80e77 | function results = vl_test_imdisttf(varargin)
% VL_TEST_DISTTF
vl_test_init ;
function test_basic()
for conv = {@single, @double}
conv = conv{1} ;
I = conv([0 0 0 ; 0 -2 0 ; 0 0 0]) ;
D = vl_imdisttf(I);
assert(isequal(D, conv(- [0 1 0 ; 1 2 1 ; 0 1 0]))) ;
I(2,2) = -3 ;
[D,map] = vl_imdisttf(I) ;
asse... |
github | sgbasel/neuritetracker-master | vl_test_vlad.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_vlad.m | 1,977 | utf_8 | d3797288d6edb1d445b890db3780c8ce | function results = vl_test_vlad(varargin)
% VL_TEST_VLAD
vl_test_init ;
function s = setup()
randn('state',0) ;
s.x = randn(128,256) ;
s.mu = randn(128,16) ;
assignments = rand(16, 256) ;
s.assignments = bsxfun(@times, assignments, 1 ./ sum(assignments,1)) ;
function test_basic (s)
x = [1, 2, 3] ;
mu = [0, 0, 0] ;
a... |
github | sgbasel/neuritetracker-master | vl_test_pr.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_pr.m | 3,763 | utf_8 | 4d1da5ccda1a7df2bec35b8f12fdd620 | function results = vl_test_pr(varargin)
% VL_TEST_PR
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[rc,pr] = vl_pr(s.labels,s.scores0) ;
vl_assert_almost_equal(pr, [1 1/1 2/2 2/3 2/4 2/5]) ;
vl_assert_almost_equal(rc, ... |
github | sgbasel/neuritetracker-master | vl_test_hog.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_hog.m | 1,555 | utf_8 | eed7b2a116d142040587dc9c4eb7cd2e | function results = vl_test_hog(varargin)
% VL_TEST_HOG
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
[x,y]= meshgrid(linspace(-1,1,128)) ;
s.round = single(x.^2+y.^2);
s.imSmall = s.im(1:128,1:128,:) ;
s.imSmall = s.im ;
s.imSmallFlipped = s.imSmall(:,end:-1:1,:) ;
function test_basic... |
github | sgbasel/neuritetracker-master | vl_test_argparse.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_argparse.m | 795 | utf_8 | e72185b27206d0ee1dfdc19fe77a5be6 | function results = vl_test_argparse(varargin)
% VL_TEST_ARGPARSE
vl_test_init ;
function test_basic()
opts.field1 = 1 ;
opts.field2 = 2 ;
opts.field3 = 3 ;
opts_ = opts ;
opts_.field1 = 3 ;
opts_.field2 = 10 ;
opts = vl_argparse(opts, {'field2', 10, 'field1', 3}) ;
assert(isequal(opts, opts_)) ;
opts_.field1 = 9 ;
... |
github | sgbasel/neuritetracker-master | vl_test_liop.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_liop.m | 1,023 | utf_8 | a162be369073bed18e61210f44088cf3 | function results = vl_test_liop(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
randn('state',0) ;
s.patch = randn(65,'single') ;
xr = -32:32 ;
[x,y] = meshgrid(xr) ;
s.blob = - single(x.^2+y.^2) ;
function test_basic(s)
d = vl_liop(s.patch) ;
function test_blob(s)
% with a blob, all local intensity ord... |
github | sgbasel/neuritetracker-master | vl_test_binsearch.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_binsearch.m | 1,339 | utf_8 | 85dc020adce3f228fe7dfb24cf3acc63 | function results = vl_test_binsearch(varargin)
% VL_TEST_BINSEARCH
vl_test_init ;
function test_inf_bins()
x = [-inf -1 0 1 +inf] ;
vl_assert_equal(vl_binsearch([], x), [0 0 0 0 0]) ;
vl_assert_equal(vl_binsearch([-inf 0], x), [1 1 2 2 2]) ;
vl_assert_equal(vl_binsearch([-inf], x), [1 1 1 1 1]) ;
vl_a... |
github | sgbasel/neuritetracker-master | vl_roc.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/plotop/vl_roc.m | 8,747 | utf_8 | 6b8b4786c9242d5112ca90a616db507a | function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
%VL_ROC ROC curve.
% [TPR,TNR] = VL_ROC(LABELS, SCORES) computes the Receiver Operating
% Characteristic (ROC) curve. LABELS are the ground truth labels,
% greather than zero for a positive sample and smaller than zero for
% a negative one. SCORES are... |
github | sgbasel/neuritetracker-master | vl_click.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/plotop/vl_click.m | 2,661 | utf_8 | 6982e869cf80da57fdf68f5ebcd05a86 | function P = vl_click(N,varargin) ;
% VL_CLICK Click a point
% P=VL_CLICK() let the user click a point in the current figure and
% returns its coordinates in P. P is a two dimensiona vectors where
% P(1) is the point X-coordinate and P(2) the point Y-coordinate. The
% user can abort the operation by pressing any k... |
github | sgbasel/neuritetracker-master | vl_pr.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/plotop/vl_pr.m | 9,135 | utf_8 | c5d1b9d67f843d10c0b2c6b48fab3c53 | function [recall, precision, info] = vl_pr(labels, scores, varargin)
%VL_PR Precision-recall curve.
% [RECALL, PRECISION] = VL_PR(LABELS, SCORES) computes the
% precision-recall (PR) curve. LABELS are the ground truth labels,
% greather than zero for a positive sample and smaller than zero for
% a negative on... |
github | sgbasel/neuritetracker-master | vl_ubcread.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/sift/vl_ubcread.m | 3,015 | utf_8 | e8ddd3ecd87e76b6c738ba153fef050f | function [f,d] = vl_ubcread(file, varargin)
% SIFTREAD Read Lowe's SIFT implementation data files
% [F,D] = VL_UBCREAD(FILE) reads the frames F and the descriptors D
% from FILE in UBC (Lowe's original implementation of SIFT) format
% and returns F and D as defined by VL_SIFT().
%
% VL_UBCREAD(FILE, 'FORMAT', '... |
github | sgbasel/neuritetracker-master | vl_frame2oell.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/sift/vl_frame2oell.m | 2,806 | utf_8 | c93792632f630743485fa4c2cf12d647 | function eframes = vl_frame2oell(frames)
% VL_FRAMES2OELL Convert a geometric frame to an oriented ellipse
% EFRAME = VL_FRAME2OELL(FRAME) converts the generic FRAME to an
% oriented ellipses EFRAME. FRAME and EFRAME can be matrices, with
% one frame per column.
%
% A frame is either a point, a disc, an orien... |
github | sgbasel/neuritetracker-master | vl_plotsiftdescriptor.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/sift/vl_plotsiftdescriptor.m | 5,114 | utf_8 | a4e125a8916653f00143b61cceda2f23 | function h=vl_plotsiftdescriptor(d,f,varargin)
% VL_PLOTSIFTDESCRIPTOR Plot SIFT descriptor
% VL_PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptor D. If D is a
% matrix, it plots one descriptor per column. D has the same format
% used by VL_SIFT().
%
% VL_PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warpe... |
github | sgbasel/neuritetracker-master | phow_caltech101.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/apps/phow_caltech101.m | 11,594 | utf_8 | 7f4890a2e6844ca56debbfe23cca64f3 | function phow_caltech101()
% PHOW_CALTECH101 Image classification in the Caltech-101 dataset
% This program demonstrates how to use VLFeat to construct an image
% classifier on the Caltech-101 data. The classifier uses PHOW
% features (dense SIFT), spatial histograms of visual words, and a
% Chi2 SVM. To speedu... |
github | sgbasel/neuritetracker-master | sift_mosaic.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/apps/sift_mosaic.m | 4,621 | utf_8 | 8fa3ad91b401b8f2400fb65944c79712 | function mosaic = sift_mosaic(im1, im2)
% SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC
%
% SIFT_MOSAIC demonstrates matching two images based on SIFT
% features and RANSAC and computing their mosaic.
%
% SIFT_MOSAIC by itself runs the algorithm on two standard test
% images. Use SIFT_MOSAI... |
github | sgbasel/neuritetracker-master | encodeImage.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/apps/recognition/encodeImage.m | 5,278 | utf_8 | 5d9dc6161995b8e10366b5649bf4fda4 | function descrs = encodeImage(encoder, im, varargin)
% ENCODEIMAGE Apply an encoder to an image
% DESCRS = ENCODEIMAGE(ENCODER, IM) applies the ENCODER
% to image IM, returning a corresponding code vector PSI.
%
% IM can be an image, the path to an image, or a cell array of
% the same, to operate on multiple ... |
github | sgbasel/neuritetracker-master | experiments.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/apps/recognition/experiments.m | 6,905 | utf_8 | 1e4a4911eed4a451b9488b9e6cc9b39c | function experiments()
% EXPERIMENTS Run image classification experiments
% The experimens download a number of benchmark datasets in the
% 'data/' subfolder. Make sure that there are several GBs of
% space available.
%
% By default, experiments run with a lite option turned on. This
% quickly runs all... |
github | sgbasel/neuritetracker-master | getDenseSIFT.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/apps/recognition/getDenseSIFT.m | 1,679 | utf_8 | 2059c0a2a4e762226d89121408c6e51c | function features = getDenseSIFT(im, varargin)
% GETDENSESIFT Extract dense SIFT features
% FEATURES = GETDENSESIFT(IM) extract dense SIFT features from
% image IM.
% Author: Andrea Vedaldi
% Copyright (C) 2013 Andrea Vedaldi
% All rights reserved.
%
% This file is part of the VLFeat library and is made availab... |
github | sgbasel/neuritetracker-master | getTrackSequences.m | .m | neuritetracker-master/trunk/GreedyTracking/getTrackSequences.m | 494 | utf_8 | 7f1e849c6a4f99dc4f1bc6d27dbb1cd1 | % extract series of track labels and time stamps for each valid track
function [trkSeq, timeSeq] = getTrackSequences(Dlist, tracks, D)
trkSeq = cell(1, max(tracks(:)));
timeSeq = cell(1, max(tracks(:)));
for i = 1:max(tracks(:))
for t = 1:length(Dlist)
detections = Dlist{t};
ids = [D(detections).ID... |
github | sgbasel/neuritetracker-master | trkGraphColoring.m | .m | neuritetracker-master/trunk/GreedyTracking/trkGraphColoring.m | 937 | utf_8 | eb6666e42de2e71b0dc99e17f83fcccd | function [T tracks] = trkGraphColoring(T,MIN_TRACK_LENGTH)
T = T | T' ;
T = double(T);
tracks = zeros(1,size(T,1));
T(T == 1) = -1;
id = 1;
first = find(T == -1, 1);
while ~isempty(first)
[r,c] = ind2sub(size(T), first);
[T, tracks] = rec_color(T,r,c,id, tracks);
id = id + 1;
first = f... |
github | sgbasel/neuritetracker-master | trkGetTrackSequences.m | .m | neuritetracker-master/trunk/GreedyTracking/trkGetTrackSequences.m | 497 | utf_8 | a3cfd59b135f9e3d936ef58d81efb741 | % extract series of track labels and time stamps for each valid track
function [trkSeq, timeSeq] = trkGetTrackSequences(Dlist, tracks, D)
trkSeq = cell(1, max(tracks(:)));
timeSeq = cell(1, max(tracks(:)));
for i = 1:max(tracks(:))
for t = 1:length(Dlist)
detections = Dlist{t};
ids = [D(detections)... |
github | sgbasel/neuritetracker-master | bipartite_matching.m | .m | neuritetracker-master/trunk/gaimc/bipartite_matching.m | 6,580 | utf_8 | bd3212ac06f51f9037ca7a7d80b45981 | function [val m1 m2 mi]=bipartite_matching(varargin)
% BIPARTITE_MATCHING Solve a maximum weight bipartite matching problem
%
% [val m1 m2]=bipartite_matching(A) for a rectangular matrix A
% [val m1 m2 mi]=bipartite_matching(x,ei,ej,n,m) for a matrix stored
% in triplet format. This call also returns a matching indic... |
github | sgbasel/neuritetracker-master | graph_draw.m | .m | neuritetracker-master/trunk/gaimc/graph_draw.m | 23,504 | utf_8 | 83adf66de4bc94aea62f934d2e1e3da0 | function h = graph_draw(adj, xy, varargin)
% GRAPH_DRAW Draw a picture of a graph when the coordinates are known
%
% graph_draw(A, xy) draws a picture of graph A where node i is placed
% at x = xy(i,1), y = xy(i,2). In the drawing, shaded nodes have
% self loops.
%
% Some of the parameters of the drawing are controll... |
github | sgbasel/neuritetracker-master | Hessian3D.m | .m | neuritetracker-master/trunk/frangi_filter_version2a/Hessian3D.m | 1,938 | utf_8 | 9204648b80240369948918e5b591d037 | function [Dxx, Dyy, Dzz, Dxy, Dxz, Dyz] = Hessian3D(Volume,Sigma)
% This function Hessian3D filters the image with an Gaussian kernel
% followed by calculation of 2nd order gradients, which aprroximates the
% 2nd order derivatives of the image.
%
% [Dxx, Dyy, Dzz, Dxy, Dxz, Dyz] = Hessian3D(I,Sigma)
%
% inp... |
github | tomasstorck/diatomas-master | CreateSave.m | .m | diatomas-master/matlab/CreateSave.m | 13,196 | utf_8 | 00ea58555d2eef247156584dfe92b499 | function CreateSave
fid=fopen('../src/cell/CModel.java','r');
fid2=fopen('../src/ser2mat/ser2mat.java','w');
c = '';
% Make header
fprintf(fid2,'package ser2mat;\n\n');
fprintf(fid2,'import java.io.IOException;\n');
fprintf(fid2,'import java.util.ArrayList;\n\n');
fprintf(fid2,'import cell.*;\n');
fprintf(fid2,'impo... |
github | tomasstorck/diatomas-master | orientation.m | .m | diatomas-master/matlab/orientation.m | 1,324 | utf_8 | 16ece313e41e0b9ced7801b29bc1d525 | % Based on Albertas Janulevicius' paper and paper cited therein
function [tt, Ct] = orientation(location)
if ~exist('location','var')
location = uigetdir;
end
pad = [location '/output/'];
Ct= [];
tt = [];
t = -1;
while true % Keep going till we run out of files
t=t+1;
files=dir([pad sprintf('g%04.0f*.mat',t(end... |
github | tomasstorck/diatomas-master | myaa.m | .m | diatomas-master/matlab/myaa.m | 11,141 | utf_8 | a66dd7fc188c3f6a1a0a0c07623cf831 | function [varargout] = myaa(varargin)
%MYAA Render figure with anti-aliasing.
% MYAA
% Anti-aliased rendering of the current figure. This makes graphics look
% a lot better than in a standard matlab figure, which is useful for
% publishing results on the web or to better see the fine details in a
% complex... |
github | tomasstorck/diatomas-master | CalculateMass.m | .m | diatomas-master/matlab/CalculateMass.m | 940 | utf_8 | 12267f1604130c68b8879318276b046b | function CalculateMass(Rinit,a,type) % Note: Mass is in Cmol
% Good value for desired radius --> initial radius is *0.9
format compact
if type==0
Minit = Msphere(Rinit)
Mdiv = 2*Minit
Rinit = Rsphere(Minit)
Rdiv = Rsphere(Mdiv)
end
if type==1
Minit = Mrodvar(Rinit,a)
Mdiv = 2*Minit
Rinit = Rrodvar(Minit,a)
... |
github | tomasstorck/diatomas-master | fitArea.m | .m | diatomas-master/matlab/fitArea.m | 1,005 | utf_8 | 80d5929f7ad06c6ee2b24f69f7dbe277 | % area = FITAREA(model)
% Determines the area covered by the cell centres (not actual positions), covered by balls in model.ballArray
function area = fitArea(model)
pos = [model.ballArray.pos];
proj = pos; proj(2,:) = []; % Project positions onto plane (we already know it's a flat biofilm)
% Fit ellipse via Nima ... |
github | HanOostdijk/matlab_mongodb-master | mm_readxls.m | .m | matlab_mongodb-master/mm_readxls.m | 5,196 | utf_8 | ce9b7cb6549da37a1968a89ab93f3700 | function mm_readxls(col, wc, xls_s, varargin)
% read the contents of an xls file into a collection
% or alternatively create test_data to insert in collection
% This software is distributed under the MIT License (MIT): see copyright.txt
%{
coll : collection to write to
wc : writecollec... |
github | BNUCNL/bat-master | prepSessid.m | .m | bat-master/prepSessid.m | 2,336 | utf_8 | 7874e055de5eaadbcede0102bf8ed7c1 | function newidlist = prepSessid(idfile,opstr,idlist)
% newidlist = prepSessid(idfile,opstr,idlist)
% prepare sessid file for the study
% idfile: text file which store the ID, every row is one ID
% opstr: operation string: 'make','add','del'
% idlist: IDs to be preprocessed(a Nx1 string cell array)
%... |
github | BNUCNL/bat-master | cohenD.m | .m | bat-master/cohenD.m | 791 | utf_8 | 2d0a3229de88c0adabef0b69fa0dff3d | % [effectsize mean1 mean2 std1 std2] = cohenD(X,Y,type)
% Effect size caculator: Cohen's d
% X, Y should be a colume of vectors;
% Type 1: indepdent sample t test; type 2: matched sample t test
% by LJG & WRS. 2010.7
% modifed by LJG @ 2011.4
function [effectsize mean1 mean2 std1 std2] = cohenD(X,Y,type)
... |
github | stoqs/stoqs-master | stoqs_loadjson.m | .m | stoqs-master/stoqs/contrib/stoqstoolbox/stoqs_loadjson.m | 16,106 | ibm852 | 3f90d22694e05a210d250845f2eedc5c | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% date: 2011/09/09
% Nedialko Krouchev: http:... |
github | stoqs/stoqs-master | stoqs_showcampaign.m | .m | stoqs-master/stoqs/contrib/stoqstoolbox/stoqs_showcampaign.m | 979 | utf_8 | ef6615afb7aa7fb4efd5c0e3d07ad075 |
function stoqs_showcampaign(u,camp)
%Show on the screen all the main information about a campaign in a STOQS
%database
%
%Usage:
%
% stoqs_showcampaign('http://odss.mbari.org/canon/','stoqs_may2012');
%Input :
%
% u = Url direction of the STOQS data server. Ex: http://odss.mbari.org/canon
% camp = name of... |
github | stoqs/stoqs-master | stoqs_qcampaigns.m | .m | stoqs-master/stoqs/contrib/stoqstoolbox/stoqs_qcampaigns.m | 1,027 | utf_8 | c8428f36c17ad610547d37b17b17b661 |
function infcs=stoqs_qcampaigns(u,show)
%Get the name of all the campaigns available in a STOQS server
%
%Usage:
%
% inf=stoqs_qcampaigns('http://odss.mbari.org/canon/',1);
%Input :
%
% u = Url direction of the STOQS data server. Ex: http://odss.mbari.org/canon/
% show = Show the info on the screen or not.... |
github | stoqs/stoqs-master | load_mb_1km.m | .m | stoqs-master/stoqs/contrib/stoqstoolbox/demo/model_vs_stoqs/load_mb_1km.m | 1,166 | utf_8 | 24f12604915ebbf3b8fb1a7b13a39780 |
function [query]=load_mb_1km(url,de)
%Get the information of the data set selected(url). Information:Date,
%depth, latitude,longitude, and parameter value
%
%Usage:
%
% [date]=load_mb_1km('http://ourocean.jpl.nasa.gov:8080/thredds/dodsC/MBNowcast/mb_das_2012052515.nc',5)
%
%
%Input :
%
% url = Url direct... |
github | lim0606/caffe-dev-master | prepare_batch.m | .m | caffe-dev-master/matlab/caffe/prepare_batch.m | 1,298 | utf_8 | 68088231982895c248aef25b4886eab0 | % ------------------------------------------------------------------------
function images = prepare_batch(image_files,IMAGE_MEAN,batch_size)
% ------------------------------------------------------------------------
if nargin < 2
d = load('ilsvrc_2012_mean');
IMAGE_MEAN = d.image_mean;
end
num_images = length... |
github | lim0606/caffe-dev-master | matcaffe_demo_vgg.m | .m | caffe-dev-master/matlab/caffe/matcaffe_demo_vgg.m | 3,036 | utf_8 | f836eefad26027ac1be6e24421b59543 | function scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file, mean_file)
%
% Demo of the matlab wrapper using the networks described in the BMVC-2014 paper "Return of the Devil in the Details: Delving Deep into Convolutional... |
github | lim0606/caffe-dev-master | matcaffe_demo.m | .m | caffe-dev-master/matlab/caffe/matcaffe_demo.m | 3,344 | utf_8 | 669622769508a684210d164ac749a614 | function [scores, maxlabel] = matcaffe_demo(im, use_gpu)
% scores = matcaffe_demo(im, use_gpu)
%
% Demo of the matlab wrapper using the ILSVRC network.
%
% input
% im color image as uint8 HxWx3
% use_gpu 1 to use the GPU, 0 to use the CPU
%
% output
% scores 1000-dimensional ILSVRC score vector
%
% You m... |
github | lim0606/caffe-dev-master | matcaffe_demo_vgg_mean_pix.m | .m | caffe-dev-master/matlab/caffe/matcaffe_demo_vgg_mean_pix.m | 3,069 | utf_8 | 04b831d0f205ef0932c4f3cfa930d6f9 | function scores = matcaffe_demo_vgg_mean_pix(im, use_gpu, model_def_file, model_file)
% scores = matcaffe_demo_vgg(im, use_gpu, model_def_file, model_file)
%
% Demo of the matlab wrapper based on the networks used for the "VGG" entry
% in the ILSVRC-2014 competition and described in the tech. report
% "Very Deep Convo... |
github | sippet/webrtc-master | apmtest.m | .m | webrtc-master/modules/audio_processing/test/apmtest.m | 9,470 | utf_8 | ad72111888b4bb4b7c4605d0bf79d572 | function apmtest(task, testname, filepath, casenumber, legacy)
%APMTEST is a tool to process APM file sets and easily display the output.
% APMTEST(TASK, TESTNAME, CASENUMBER) performs one of several TASKs:
% 'test' Processes the files to produce test output.
% 'list' Prints a list of cases in the test set,... |
github | sippet/webrtc-master | plot_neteq_delay.m | .m | webrtc-master/modules/audio_coding/neteq/test/delay_tool/plot_neteq_delay.m | 5,563 | utf_8 | 8b6a66813477863da513b1e6971dbc97 | function [delay_struct, delayvalues] = plot_neteq_delay(delayfile, varargin)
% InfoStruct = plot_neteq_delay(delayfile)
% InfoStruct = plot_neteq_delay(delayfile, 'skipdelay', skip_seconds)
%
% Henrik Lundin, 2006-11-17
% Henrik Lundin, 2011-05-17
%
try
s = parse_delay_file(delayfile);
catch
error(lasterr);
e... |
github | psuteparuk/PianoKeyDetector-master | findWhiteKeys.m | .m | PianoKeyDetector-master/findWhiteKeys.m | 3,189 | utf_8 | ae14e9a282309d195673495db1788f38 | function [ whiteKeys,numWhiteKeys ] = findWhiteKeys(blackKeys,numBlackKeys,lowerBound)
blackR = cell(1,numBlackKeys);
blackC = cell(1,numBlackKeys);
blackXPos = zeros(1,numBlackKeys);
blackYPos = zeros(1,numBlackKeys);
blackMaxR = zeros(1,numBlackKeys);
blackMinR = zeros(1,numBlackKeys);
heightBlack = zeros(1,numBlack... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_IDT_MinimumError.m | .m | HDM_OFT-master/HDM_OFT_IDT_MinimumError.m | 22,723 | utf_8 | b0ba8c7c8c8edcecb9f570a44deb0e75 | function [OFT_IDT_File, OFT_IDT_B, OFT_IDT_b]=HDM_OFT_IDT_MinimumError...
(OFT_In_PatchMeasurementFile, ...
OFT_In_CameraMeasurementFile, ...
OFT_In_PreLinearisationCurve, ...
OFT_In_NeutralsCompensation, ...
OFT_In_ErrorMinimizationDomain, ...
OFT_In_IlluminantSpectrum,...
OFT_In_Ref... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_findpeaks.m | .m | HDM_OFT-master/framework/HdM/HDM_OFT_findpeaks.m | 4,740 | utf_8 | 2c4e3a00231b0e04625e8e9034de82b0 | function [peakamps,peaklocs,peakwidths,resid] = ...
HDM_OFT_findpeaks(data,npeaks,minwidth,maxwidth,minpeak,debug);
%FINDPEAKS Find up to npeaks interpolated peaks in data.
%
% [peakamps,peaklocs,peakwidths,resid] =
% findpeaks(data,npeaks,minwidth,maxwidth,minpeak,debug);
%
% finds up to npeaks int... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_LineCalibration.m | .m | HDM_OFT-master/framework/HdM/Camera/HDM_OFT_LineCalibration.m | 12,716 | utf_8 | 5245b4afd891e3e807a514656fd015c0 | function out=HDM_OFT_LineCalibration...
(OFT_In_SpectrometerMeasurement, OFT_In_CameraMeasurement, OFT_In_PreLinearisationCurve)
OFT_Env=HDM_OFT_InitEnvironment();
HDM_OFT_Utils.OFT_DispTitle('start line calibration');
if(exist('OFT_In_SpectrometerMeasurement','var')==0)
disp('using reference patch mesuremen... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_LightCalibration.m | .m | HDM_OFT-master/framework/HdM/Camera/HDM_OFT_LightCalibration.m | 26,152 | utf_8 | e1c9d75e7bc164b8c51faf45057eef80 | function out=HDM_OFT_LightCalibration...
(OFT_In_Pixel2WavelengthLookUp, ...
OFT_In_SpectrometerMeasurement, OFT_In_CameraMeasurement,...
OFT_In_PreLinearisationCurve,...
OFT_In_Sensor, OFT_In_FocalLength)
OFT_Env=HDM_OFT_InitEnvironment();
HDM_OFT_Utils.OFT_DispTitle('start light calibration'... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_LightCalibrationPn.m | .m | HDM_OFT-master/framework/HdM/Camera/HDM_OFT_LightCalibrationPn.m | 26,689 | utf_8 | e8caa6d8588ba19b3b22cd7c57f5b04c | function out=HDM_OFT_LightCalibration...
(OFT_In_Pixel2WavelengthLookUp, ...
OFT_In_SpectrometerMeasurement, OFT_In_CameraMeasurement,...
OFT_In_PreLinearisationCurve,...
OFT_In_Sensor, OFT_In_FocalLength)
OFT_Env=HDM_OFT_InitEnvironment();
HDM_OFT_Utils.OFT_DispTitle('start light calibration'... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_LineCalibrationPn.m | .m | HDM_OFT-master/framework/HdM/Camera/HDM_OFT_LineCalibrationPn.m | 15,277 | utf_8 | 5e03635b4c80e2fe4535a1a365eff5ee | function out=HDM_OFT_LineCalibrationPn...
(i_SpectrometerMeasurement, i_CameraMeasurement, i_PreLinearisationCurve, i_maskImage)
OFT_Env=HDM_OFT_InitEnvironment();
HDM_OFT_Utils.OFT_DispTitle('start line calibration');
if(exist('i_SpectrometerMeasurement','var')==0)
disp('using reference patch mesurements');... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_IDT_PrepareClientData.m | .m | HDM_OFT-master/framework/HdM/IDT/HDM_OFT_IDT_PrepareClientData.m | 5,778 | utf_8 | 8c6a9889a78917d8cb525efe3d20c294 |
function OFT_Out_ClientData=HDM_OFT_IDT_PrepareClientData(OFT_In_ClientData)
HDM_OFT_Utils.OFT_DispTitle('prepare client data');
[OFT_ClientDataPath,OFT_ClientDataName,OFT_ClientDataExt] = fileparts(OFT_In_ClientData);
OFT_ClientDataDir=OFT_ClientDataPath;
OFT_xmlTaskFile='';
if (strfind(lower(OFT_In_Cli... |
github | janfroehlich/HDM_OFT-master | HDM_OFT_IDT_LoadFromXML.m | .m | HDM_OFT-master/framework/HdM/IDT/HDM_OFT_IDT_LoadFromXML.m | 2,102 | utf_8 | 25af0addaf79621537b364bf6ee47d6d | function theStruct = HDM_OFT_IDT_LoadFromXML(filename)
% PARSEXML Convert XML file to a MATLAB structure.
try
tree = xmlread(filename);
catch
error('Failed to read XML file %s.',filename);
end
% Recurse over child nodes. This could run into problems
% with very deeply nested trees.
try
theStruct =... |
github | janfroehlich/HDM_OFT-master | locatecc.m | .m | HDM_OFT-master/framework/COTS/CCFind/locatecc.m | 5,641 | utf_8 | 52a3000a1d728e6bba54c5ed88a8744a | function X=locatecc(Q,I)
% ColorChecker will be located on the peaks of Q.
%% find Q peaks
K = Qpeaks(Q);
[x,y]=find(K>0);
%% construct a distance matrix
% (X,Y)=difference vector in cartesian
X = x*ones(1,length(x))-ones(length(x),1)*x';
Y = y*ones(1,length(y))-ones(length(y),1)*y';
Y(X~=0) = Y(X~=0)... |
github | janfroehlich/HDM_OFT-master | pspectro.m | .m | HDM_OFT-master/framework/COTS/pspectro/pspectro.m | 15,609 | utf_8 | 88f723a201c42237f07bdbff930e54ec | %% pspectro: Process Irradiance Data
% This function processes absolute radiometric data (irradiance) with
% dimension $[\mu \mathrm{W} \cdot \mathrm{cm}^{-2}]$ and calculates:
%
% * The illuminance (lux) with dimension $[\mathrm{lm}\cdot\mathrm{m}^{-2}]$.
% * The tristimulus values X,Y, and Z (CIE 1931 standard... |
github | janfroehlich/HDM_OFT-master | Smoothspectra.m | .m | HDM_OFT-master/framework/COTS/Joensuu/Smoothspectra.m | 12,293 | utf_8 | 8ba80ed75f3f67c8f8de9f2131260fe4 | function Smoothspectra
%
% Smoothspectra for Matlab
% Version 1.0, October 15 2012
% Copyright (c) Hannu Laamanen, Mika Flinkman.
%
% This program is used for generating a set of 716784 smooth reflectance
% spectra. This data set is saved in a Matlab file "ndata.mat" in the
% current working folder. The progra... |
github | janfroehlich/HDM_OFT-master | readdpx.m | .m | HDM_OFT-master/framework/COTS/DPXReader/readdpx.m | 11,877 | utf_8 | ba34326a3655570d5b6cb204d4cc6192 | function [pixels, details] = readdpx(filename)
% DPX image file reader (SMPTE 268M-2003 Reference)
% for more info see:
% ftp://ftp.graphicsmagick.org/pub/dpx
% http://www.mathworks.com/company/newsletters/digest/2006/jan/datatypes.html
%
% Originaly from:
% (C) 2006 Jeff Mather, Mathworks
% Extended by:
... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | magnifyOnFigure.m | .m | INS-VNS-Navigation_Master-master/magnifyOnFigure.m | 97,117 | utf_8 | 602ece8d29b1a3fea8602b011364b137 | % NAME: magnifyOnFigure
%
% AUTHOR: David Fernandez Prim (david.fernandez.prim@gmail.com)
%
% PURPOSE: Shows a functional zoom tool, suitable for publishing of zoomed
% images and 2D plots
%
% INPUT ARGUMENTS:
% figureHandle [double 1x1]: graphic handle of the target figure
% axesH... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | magnifyOnFigure.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/magnifyOnFigure.m | 97,117 | utf_8 | 602ece8d29b1a3fea8602b011364b137 | % NAME: magnifyOnFigure
%
% AUTHOR: David Fernandez Prim (david.fernandez.prim@gmail.com)
%
% PURPOSE: Shows a functional zoom tool, suitable for publishing of zoomed
% images and 2D plots
%
% INPUT ARGUMENTS:
% figureHandle [double 1x1]: graphic handle of the target figure
% axesH... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | magnifyOnFigure.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/resultRelated/magnifyOnFigure.m | 97,117 | utf_8 | 602ece8d29b1a3fea8602b011364b137 | % NAME: magnifyOnFigure
%
% AUTHOR: David Fernandez Prim (david.fernandez.prim@gmail.com)
%
% PURPOSE: Shows a functional zoom tool, suitable for publishing of zoomed
% images and 2D plots
%
% INPUT ARGUMENTS:
% figureHandle [double 1x1]: graphic handle of the target figure
% axesH... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | loadCalibrationCamToCam.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/kitti/devkit/loadCalibrationCamToCam.m | 1,894 | utf_8 | 88db832a2338f205ea36b1a9f6231aed | function calib = loadCalibrationCamToCam(filename)
% open file
fid = fopen(filename,'r');
if fid<0
calib = [];
return;
end
% read corner distance
calib.cornerdist = readVariable(fid,'corner_dist',1,1);
% read all cameras (maximum: 100)
for cam=1:100
% read variables
S_ = readVariable(fid,['S_' num2s... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | loadCalibration_imuTovelo.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/kitti/devkit/loadCalibration_imuTovelo.m | 990 | utf_8 | 3eb08c27286b2d94115e366d51a25c14 | function Tr = loadCalibration_imuTovelo(filename)
% open file
if ~exist(filename,'file')
[FileName,PathName] = uigetfile('calib_imu_to_velo.txts') ;
filename = [PathName,FileName];
end
fid = fopen(filename,'r');
if fid<0
error(['ERROR: Could not load: ' filename]);
end
% read calibration
R = readVariable(f... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | loadCalibrationRigid.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/kitti/devkit/loadCalibrationRigid.m | 985 | utf_8 | 91a0599d31f33ff0d652e774150f6bbe | function Tr = loadCalibrationRigid(filename)
% open file
if ~exist(filename,'file')
[FileName,PathName] = uigetfile('calib_velo_to_cam.txts') ;
filename = [PathName,FileName];
end
fid = fopen(filename,'r');
if fid<0
error(['ERROR: Could not load: ' filename]);
end
% read calibration
R = readVariable(fid,'R... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | velocity_t_to_velocity_b.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/dataHandle/velocity_t_to_velocity_b.m | 282 | utf_8 | 91b1fb6b0b6217174cf5387c9381a826 |
function velocity_b = velocity_t_to_velocity_b(velocity_t,attitude_t)
N = length(velocity_t);
velocity_b = zeros(3,N);
for k=1:N
Cbt = FCbn(attitude_t(:,k));
Ctb = Cbt' ;
velocity_b(:,k) = Ctb* velocity_t(:,k) ;
vt=velocity_t(:,k) ;
vb = Ctb* velocity_t(:,k) ;
end
|
github | xuyongzhi/INS-VNS-Navigation_Master-master | CalWett.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/dataHandle/CalWett.m | 239 | utf_8 | debf6cd7dca833208482900931269ced | % buaa xyz 2014.1.10
% Wet_t
function Wet_t = CalWett( Vet_t,Re,e,L )
RytDs = ( 1+2*e-3*e*(sin(L))^2 )/Re; % 1/Ryt
RxtDs = ( 1-e*(sin(L))^2 )/Re ; % 1/Rxt
Wet_t = [ -Vet_t(2)*RytDs ; Vet_t(1)*RxtDs ; Vet_t(1)*RxtDs*tan(L) ]; |
github | xuyongzhi/INS-VNS-Navigation_Master-master | savepgm.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/savepgm.m | 447 | utf_8 | b8fe9ed33cbd68ea4b83271b431e3667 | %SAVEPGM Write a PGM format file
%
% SAVEPGM(filename, im)
%
% Saves the specified image array in a binary (P5) format PGM image file.
%
% SEE ALSO: loadpgm
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1994
function savepgm(fname, im)
fid = fopen(fname, 'w');
[r,c] = size(... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | ginput4.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/ginput4.m | 7,121 | utf_8 | 1d7231b0daed3533514a77f79f4e096a | function [out1,out2,out3] = ginput4(arg1)
[out1,out2,out3] = ginput(arg1);
return;
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Ar... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | loadinr.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/loadinr.m | 1,029 | utf_8 | ac39329cc5acba186f4c5ef4c62f3a33 | %LOADINR Load an INRIMAGE format file
%
% LOADINR(filename, im)
%
% Load an INRIA image format file and return it as a matrix
%
% SEE ALSO: saveinr
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1996
function im = loadinr(fname, im)
fid = fopen(fname, 'r');
s = fgets(fid);
... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | saveppm.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/saveppm.m | 722 | utf_8 | 9904ad3d075a120ca32bd9c10e019512 | %SAVEPPM Write a PPM format file
%
% SAVEPPM(filename, I)
%
% Saves the specified red, green and blue planes in a binary (P6)
% format PPM image file.
%
% SEE ALSO: loadppm
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1994
function saveppm(fname, I)
I = double(I);
if size(I,... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | ginput3.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/ginput3.m | 6,344 | utf_8 | 1cc27af57f9872f05bbf0d9b8a0fdbc9 | function [out1,out2,out3] = ginput2(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Arrow Keys on some
% systems). Data points a... |
github | xuyongzhi/INS-VNS-Navigation_Master-master | ginput2.m | .m | INS-VNS-Navigation_Master-master/code_subfunction/commonFcn/toolbox_calib/ginput2.m | 6,105 | utf_8 | 983a72db9a079ba54ab084149ced6ae9 | function [out1,out2,out3] = ginput2(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Arrow Keys on some
% systems). Data points a... |
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