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github | ZhangYong19800721/ImageTool-master | fchcode.m | .m | ImageTool-master/+dipum/fchcode.m | 8,636 | utf_8 | eb259f55a40a91882b462eb4b06eb36a | function c = fchcode(b, conn, dir)
%FCHCODE Computes the Freeman chain code of a boundary.
% C = FCHCODE(B) computes the 8-connected Freeman chain code of a
% set of 2-D coordinate pairs contained in B, an np-by-2 array. C
% is a structure with the following fields:
%
% c.fcc = Freeman chain code (1-by-n... |
github | ZhangYong19800721/ImageTool-master | wavefast.m | .m | ImageTool-master/+dipum/wavefast.m | 5,382 | utf_8 | e45d76e82d64ea03a31f3eabf01916d1 | function [c, s] = wavefast(x, n, varargin)
%WAVEFAST Computes the FWT of a '3-D extended' 2-D array.
% [C, L] = WAVEFAST(X, N, LP, HP) computes 'PAGES' 2D N-level
% FWTs of a 'ROWS x COLUMNS x PAGES' matrix X with respect to
% decomposition filters LP and HP.
%
% [C, L] = WAVEFAST(X, N, WNAME) performs the ... |
github | ZhangYong19800721/ImageTool-master | cnotch.m | .m | ImageTool-master/+dipum/cnotch.m | 5,984 | utf_8 | 4ea34c3843ab27ca5624c1540a5a29bf | function H = cnotch(type, notch, M, N, C, D0, n)
%CNOTCH Generates circularly symmetric notch filters.
% H = CNOTCH(TYPE, NOTCH, M, N, C, D0, n) generates a notch filter
% of size M-by-N. C is a K-by-2 matrix with K pairs of frequency
% domain coordinates (u, v) that define the centers of the filter
% notches (when spe... |
github | ZhangYong19800721/ImageTool-master | bound2eight.m | .m | ImageTool-master/+dipum/bound2eight.m | 3,000 | utf_8 | 9585c986f3b9de477d7578349bd6012d | function rc_new = bound2eight(rc)
%BOUND2EIGHT Convert 4-connected boundary to 8-connected boundary.
% RC_NEW = BOUND2EIGHT(RC) converts a four-connected boundary to an
% eight-connected boundary. RC is a P-by-2 matrix, each row of
% which contains the row and column coordinates of a boundary
% pixel. RC must... |
github | ZhangYong19800721/ImageTool-master | waveback.m | .m | ImageTool-master/+dipum/waveback.m | 4,916 | utf_8 | 24f8298844d06233ebde3a1e38e6aa2a | function [varargout] = waveback(c, s, varargin)
%WAVEBACK Computes inverse FWTs for multi-level decomposition [C, S].
% [VARARGOUT] = WAVEBACK(C, S, VARARGIN) performs a 2D N-level
% partial or complete wavelet reconstruction of decomposition
% structure [C, S].
%
% SYNTAX:
% Y = WAVEBACK(C, S, 'WNAME'); Ou... |
github | ZhangYong19800721/ImageTool-master | endpoints.m | .m | ImageTool-master/+dipum/endpoints.m | 1,580 | utf_8 | 782024a0b9ef2ea3d1c2c52ec1f95464 | function g = endpoints(f)
%ENDPOINTS Computes end points of a binary image.
% G = ENDPOINTS(F) computes the end points of the binary image F
% and returns them in the binary image G.
% Copyright 2002-2009 R. C. Gonzalez, R. E. Woods, and S. L. Eddins
% From the book Digital Image Processing Using MATLAB, 2nd ... |
github | ZhangYong19800721/ImageTool-master | specxture.m | .m | ImageTool-master/+dipum/specxture.m | 2,659 | utf_8 | ffd71e3cf93a9647dab82447ddb94f4b | function [srad, sang, S] = specxture(f)
%SPECXTURE Computes spectral texture of an image.
% [SRAD, SANG, S] = SPECXTURE(F) computes SRAD, the spectral energy
% distribution as a function of radius from the center of the
% spectrum, SANG, the spectral energy distribution as a function of
% angle for 0 to 180 deg... |
github | ZhangYong19800721/ImageTool-master | im2jpeg2k.m | .m | ImageTool-master/+dipum/im2jpeg2k.m | 4,039 | utf_8 | b5b25aebf9eb3657b13306dbc5da97ec | function y = im2jpeg2k(x, n, q)
%IM2JPEG2K Compresses an image using a JPEG 2000 approximation.
% Y = IM2JPEG2K(X, N, Q) compresses image X using an N-scale JPEG
% 2K wavelet transform, implicit or explicit coefficient
% quantization, and Huffman symbol coding augmented by zero
% run-length coding. If quantiza... |
github | ZhangYong19800721/ImageTool-master | polyangles.m | .m | ImageTool-master/+dipum/polyangles.m | 6,244 | utf_8 | 5ccde6e5ce22041c171a415493ae86a4 | function angles = polyangles(x, y)
%POLYANGLES Computes internal polygon angles.
% ANGLES = POLYANGLES(X, Y) computes the interior angles (in
% degrees) of an arbitrary polygon whose vertices are given in
% [X, Y], ordered in a clockwise manner. The program eliminates
% duplicate adjacent rows in [X Y], excep... |
github | ZhangYong19800721/ImageTool-master | intrans.m | .m | ImageTool-master/+dipum/intrans.m | 4,489 | utf_8 | 0a06df74a441a64de8b2c92125fb713d | function g = intrans(f, method, varargin)
%INTRANS Performs intensity (gray-level) transformations.
% G = INTRANS(F, 'neg') computes the negative of input image F.
%
% G = INTRANS(F, 'log', C, CLASS) computes C*log(1 + F) and
% multiplies the result by (positive) constant C. If the last two
% parameters are om... |
github | ZhangYong19800721/ImageTool-master | diameter.m | .m | ImageTool-master/+dipum/diameter.m | 6,534 | utf_8 | 96b38c5d2e9fe984bd5b5dd5f7eb8458 | function s = diameter(L)
%DIAMETER Measure diameter and related properties of image regions.
% S = DIAMETER(L) computes the diameter, the major axis endpoints,
% the minor axis endpoints, and the basic rectangle of each labeled
% region in the label matrix L. Positive integer elements of L
% correspond to diffe... |
github | ZhangYong19800721/ImageTool-master | huffman.m | .m | ImageTool-master/+dipum/huffman.m | 2,936 | utf_8 | aae08280f88b39cc63c93374916c29f0 | function CODE = huffman(p)
%HUFFMAN Builds a variable-length Huffman code for a symbol source.
% CODE = HUFFMAN(P) returns a Huffman code as binary strings in
% cell array CODE for input symbol probability vector P. Each word
% in CODE corresponds to a symbol whose probability is at the
% corresponding index of... |
github | ZhangYong19800721/ImageTool-master | recnotch.m | .m | ImageTool-master/+dipum/recnotch.m | 3,819 | utf_8 | 5bdbf7c51721f193cd8ef35d8b5f6306 | function H = recnotch(notch, mode, M, N, W, SV, SH)
%RECNOTCH Generates rectangular notch (axes) filters.
% H = RECNOTCH(NOTCH, MODE, M, N, W, SV, SH) generates an M-by-N
% notch filter consisting of symmetric pairs of rectangles of
% width W placed on the vertical and horizontal axes of the
% (centered) frequency rect... |
github | ZhangYong19800721/ImageTool-master | imnoise2.m | .m | ImageTool-master/+dipum/imnoise2.m | 5,201 | utf_8 | 38b1a3cf8f04b304542eefc2024bd9fb | function R = imnoise2(type, varargin)
%IMNOISE2 Generates an array of random numbers with specified PDF.
% R = IMNOISE2(TYPE, M, N, A, B) generates an array, R, of size
% M-by-N, whose elements are random numbers of the specified TYPE
% with parameters A and B. If only TYPE is included in the
% input argument l... |
github | ZhangYong19800721/ImageTool-master | spfilt.m | .m | ImageTool-master/+dipum/spfilt.m | 3,837 | utf_8 | 1acd4a9307f27ad351b31576789cfe19 | function f = spfilt(g, type, varargin)
%SPFILT Performs linear and nonlinear spatial filtering.
% F = SPFILT(G, TYPE, M, N, PARAMETER) performs spatial filtering
% of image G using a TYPE filter of size M-by-N. Valid calls to
% SPFILT are as follows:
%
% F = SPFILT(G, 'amean', M, N) Arithmetic mean fil... |
github | ZhangYong19800721/ImageTool-master | imratio.m | .m | ImageTool-master/+dipum/imratio.m | 1,480 | utf_8 | 47ae639a61975658e6fdfc4897fcb5d0 | function cr = imratio(f1, f2)
%IMRATIO Computes the ratio of the bytes in two images/variables.
% CR = IMRATIO(F1, F2) returns the ratio of the number of bytes in
% variables/files F1 and F2. If F1 and F2 are an original and
% compressed image, respectively, CR is the compression ratio.
% Copyright 2002-2009 ... |
github | jlr581/correlation-master | joint_sort.m | .m | correlation-master/MATLAB/joint_sort.m | 347 | utf_8 | c07d271a623eb0ca5299aec381fe9c23 | % JOINT_SORT
%
% Sorts variable a, a union of two vectors.
%
% Parameters:
% a union of two vectors
% ia union of indices of two vectors
%
% Returns:
% asort sorted values from a
% iasort sorted indices from ia
function [asort,iasort] = joint_sort(a,ia)
[asort,inds] = sort(a)... |
github | jlr581/correlation-master | icpdf.m | .m | correlation-master/MATLAB/icpdf.m | 900 | utf_8 | 842e77af6a4bc5bd156afdd54108c5df | % ICPDF
%
% Parameters:
% x vector (N x 1)
%
% Returns:
% zp ICPDF vector (N x 1) of x
function zp = icpdf(x)
a0=3.3871327179; a1=50.434271938; a2=159.29113202;
a3=59.109374720; b1=17.895169469; b2=78.757757664;
b3=67.187563600; c0=1.4234372777; c1=2.7568153900;
c2=1.3067284816; c3=0.1702... |
github | jlr581/correlation-master | bootstrap_ci.m | .m | correlation-master/MATLAB/bootstrap_ci.m | 5,613 | utf_8 | 674da1adeeccdd3186c4343b1dd9eb6b | % BOOSTRAP_CI
%
% Parameters:
% x timeseries (N x 1)
% y timeseries (M x 1)
% tx time intervals associated with x
% ty time intervals associated with y
%
% Returns:
% bci1, bci2 upper and lower confidence intervals
function [bci1, bci2] = bootstrap_ci(x, y, tx, ty)
max_it... |
github | jlr581/correlation-master | correlate_gaussian.m | .m | correlation-master/MATLAB/correlate_gaussian.m | 928 | utf_8 | 89bedb41f2813bc20dbf8de697484f50 | % CORRELATE_GAUSSIAN
%
% Following method by Rehfeld et al. (Nonlin. Processes Geophys. 2011)
%
% Parameters:
% x timeseries (N x 1)
% y timeseries (M x 1)
% tx time intervals associated with x
% ty time intervals associated with y
%
% Returns:
% corrgauss
function corrgaus... |
github | jlr581/correlation-master | cpdf.m | .m | correlation-master/MATLAB/cpdf.m | 389 | utf_8 | 3b3297ed9b6f944e622841ef4e9d791d | % CPDF
%
% Cumulative probability density function of variable x
%
% Parameters:
% x vector (N x 1)
%
% Returns:
% cx CPDF vector (N x 1) of x
function cx = cpdf(x)
if x>=0
cx=1-0.5/((1+0.196854*x+0.115194*x.^2+0.000344*x.^3+0.019527*x.^4).^4);
return
else
cx=0.5/((1-0.196854*x+... |
github | JamesMegariotis/SLAM_Mapping-master | rotx.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/rotx.m | 306 | utf_8 | e3472a26436b5f238dac19d5fd0b871c | %ROTX Rotation about X axis
%
% ROTX(theta) returns a homogeneous transformation representing a
% rotation of theta about the X axis.
%
% See also ROTY, ROTZ, ROTVEC.
% Copyright (C) Peter Corke 1990
function r = rotx(t)
ct = cos(t);
st = sin(t);
r = [1 0 0 0
0 ct -st 0
0 st ct 0
0 0 0 1];
|
github | JamesMegariotis/SLAM_Mapping-master | rotz.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/rotz.m | 306 | utf_8 | 46e0bf3113efb75d4014488b019f3576 | %ROTZ Rotation about Z axis
%
% ROTZ(theta) returns a homogeneous transformation representing a
% rotation of theta about the X axis.
%
% See also ROTX, ROTY, ROTVEC.
% Copyright (C) Peter Corke 1990
function r = rotz(t)
ct = cos(t);
st = sin(t);
r = [ct -st 0 0
st ct 0 0
0 0 1 0
0 0 0 1];
|
github | JamesMegariotis/SLAM_Mapping-master | rpy2tr.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/rpy2tr.m | 511 | utf_8 | a94f613d4341e10ddaf4c0551555471f | %RPY2TR Roll/pitch/yaw to homogenous transform
%
% RPY2TR([R P Y])
% RPY2TR(R,P,Y) returns a homogeneous tranformation for the specified
% roll/pitch/yaw angles. These correspond to rotations about the
% Z, X, Y axes respectively.
%
% See also TR2RPY, EUL2TR
% Copright (C) Peter Corke 1993
function r = rpy2tr(roll, p... |
github | JamesMegariotis/SLAM_Mapping-master | roty.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/roty.m | 306 | utf_8 | d1d8eb762d99bd1091278e9fc3c26dc2 | %ROTY Rotation about Y axis
%
% ROTY(theta) returns a homogeneous transformation representing a
% rotation of theta about the Y axis.
%
% See also ROTX, ROTZ, ROTVEC.
% Copyright (C) Peter Corke 1990
function r = roty(t)
ct = cos(t);
st = sin(t);
r = [ct 0 st 0
0 1 0 0
-st 0 ct 0
0 0 0 1];
|
github | JamesMegariotis/SLAM_Mapping-master | q2tr.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/q2tr.m | 452 | utf_8 | a142148cdf478b8beae43593bc74cb66 | %Q2TR Convert unit-quaternion to homogeneous transform
%
% T = q2tr(Q)
%
% Return the rotational homogeneous transform corresponding to the unit
% quaternion Q.
%
% See also TR2Q
% Copyright (C) 1993 Peter Corke
function t = q2tr(q)
s = q(1);
x = q(2);
y = q(3);
z = q(4);
r = [ 1-2*(y^2+z^2) 2*(x*y-s*z) 2*(x*z+s... |
github | JamesMegariotis/SLAM_Mapping-master | tr2rpy.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/tr2rpy.m | 647 | utf_8 | bfaa28ddb877e05439892857e8cdc115 | %TR2RPY Convert a homogeneous transform matrix to roll/pitch/yaw angles
%
% [A B C] = TR2RPY(TR) returns a vector of Euler angles
% corresponding to the rotational part of the homogeneous transform TR.
%
% See also RPY2TR, TR2EUL
% Copright (C) Peter Corke 1993
function rpy = tr2rpy(m)
rpy = zeros(1,3);
if abs(... |
github | JamesMegariotis/SLAM_Mapping-master | tr2q.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/tr2q.m | 1,163 | utf_8 | b848d8e8dd98bb791156d6b2e1684d69 | %TR2Q Convert homogeneous transform to a unit-quaternion
%
% Q = tr2q(T)
%
% Return a unit quaternion corresponding to the rotational part of the
% homogeneous transform T.
%
% See also Q2TR
% Copyright (C) 1993 Peter Corke
function q = tr2q(t)
q = zeros(1,4);
q(1) = sqrt(trace(t))/2;
kx = t(3,2) - t(2,3); % Oz - A... |
github | JamesMegariotis/SLAM_Mapping-master | fast_corner_detect_12.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/fast-matlab-src/fast_corner_detect_12.m | 126,136 | utf_8 | a893a7b42ef9722d64ec819cfb934614 | %FAST_CORNER_DETECT_12 perform an 12 point FAST corner detection.
% corners = FAST_CORNER_DETECT_12(image, threshold) performs the detection on the image
% and returns the X coordinates in corners(:,1) and the Y coordinares in corners(:,2).
%
% If you use this in published work, please cite:
% Fusing Po... |
github | JamesMegariotis/SLAM_Mapping-master | fast_corner_detect_9.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/fast-matlab-src/fast_corner_detect_9.m | 177,871 | utf_8 | 23105cc2b05a91688c4a17e952fcd7e3 | %FAST_CORNER_DETECT_9 perform an 9 point FAST corner detection.
% corners = FAST_CORNER_DETECT_9(image, threshold) performs the detection on the image
% and returns the X coordinates in corners(:,1) and the Y coordinares in corners(:,2).
%
% If you use this in published work, please cite:
% Fusing Point... |
github | JamesMegariotis/SLAM_Mapping-master | fast_corner_detect_10.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/fast-matlab-src/fast_corner_detect_10.m | 164,469 | utf_8 | 219987a5a165436df9ac811d9ec40fdb | %FAST_CORNER_DETECT_10 perform an 10 point FAST corner detection.
% corners = FAST_CORNER_DETECT_10(image, threshold) performs the detection on the image
% and returns the X coordinates in corners(:,1) and the Y coordinares in corners(:,2).
%
% If you use this in published work, please cite:
% Fusing Po... |
github | JamesMegariotis/SLAM_Mapping-master | fast_nonmax.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/fast-matlab-src/fast_nonmax.m | 2,828 | utf_8 | d1862ded31ac358dc7d19418039cb6ea | % FAST_NONMAX perform non-maximal suppression on FAST features.
%
% nonmax = FAST_NONMAX(image, threshold, FAST_CORNER_DETECT_9(image, threshold));
% returns a list of nonmaximally suppressed corners with the X coordinate
% in nonmax(:,1) and Y in nonmax(:,2).
%
% If you use this in published work, plea... |
github | JamesMegariotis/SLAM_Mapping-master | fast_corner_detect_11.m | .m | SLAM_Mapping-master/SLAM/Matlab/ekf_monocular_SLAM/matlab_code/fast-matlab-src/fast_corner_detect_11.m | 132,321 | utf_8 | ae44e523c1f863bcd9e42e13bb4612d2 | %FAST_CORNER_DETECT_11 perform an 11 point FAST corner detection.
% corners = FAST_CORNER_DETECT_11(image, threshold) performs the detection on the image
% and returns the X coordinates in corners(:,1) and the Y coordinares in corners(:,2).
%
% If you use this in published work, please cite:
% Fusing Po... |
github | marcsous/gpuSparse-master | mex_all.m | .m | gpuSparse-master/private/mex_all.m | 2,663 | utf_8 | 98830d0b239c69a9f73d660565a7a78e | function mex_all()
% checks
if ~exist('/usr/local/cuda','dir')
warning('/usr/local/cuda directory not found. Try:\n%s','"sudo ln -s /usr/local/cuda-11 /usr/local/cuda"')
end
% override MATLAB's supplied version of nvcc - not sure what difference this makes
setenv('MW_ALLOW_ANY_CUDA','1')
setenv('MW_NVCC_PATH', '/... |
github | neurofractal/MEG_preprocessing-master | maxfilter_all.m | .m | MEG_preprocessing-master/maxfilter/maxfilter_all.m | 2,475 | utf_8 | 2a3276600d9b847d653e311dac2be772 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Function to Maxfilter all .fif files in a directory
% Use as maxfilter_all('path_to_directory')
% Make sure there are no Maxfiltered datasets in your directory.
% This script will estimate head position and apply tSSS with a .9
% correlation... |
github | psturmfels/online_COS-master | offline_dp.m | .m | online_COS-master/offline_dp.m | 2,103 | utf_8 | 25105f07b391be19f35e41f0e3bc6f94 | function [perm, wcs] = offline_dp(weights, p_times)
% A function that optimally solves an instance of concurrent open shop
% (with objective function as sum of weighted completion times)
% using an exponential dynamic programming algorithm.
% Inputs:
% p_times = an M x N matrix; ijth entry = processing time of
% ... |
github | psturmfels/online_COS-master | offline_bf.m | .m | online_COS-master/offline_bf.m | 1,193 | utf_8 | 9183428fba96320a685d57209cccdaec | function [perm, wcs] = offline_bf(weights, p_times)
% A function that optimally solves an instance of concurrent open shop
% (with objective function as sum of weighted completion times)
% by trying all permuations of jobs.
% Inputs:
% p_times = an M x N matrix; ijth entry = processing time of
% job j on ... |
github | psturmfels/online_COS-master | MUWP_find_best_alpha.m | .m | online_COS-master/archived/MUWP_find_best_alpha.m | 1,092 | utf_8 | b43bed414ba4017bd9c78f55456604a1 | function [subset] = MUWP_find_best_alpha(RA_weights, RA_tk, interval_size)
[x_bar] = MUWP_LP(RA_weights, RA_tk, interval_size);
[~, ind] = sort(-x_bar);
[~, ~, subset, ~, ~, ~] = find_best_step(x_bar, RA_weights, RA_tk, ind, interval_size);
end
function [obj_val_round, mp_time_round, new_x_vals, temp_p_ratios, temp_w_... |
github | psturmfels/online_COS-master | MUWP_relaxtime.m | .m | online_COS-master/archived/MUWP_relaxtime.m | 1,035 | utf_8 | c9751c426bd7ea8c8e0251c3e6de1f60 | function [subset] = MUWP_relaxtime(RA_weights, RA_tk, interval_size)
% Solves the Minimum Unscheduled Weight Problem for
% concurrent open shop by using a linear program, and then rounding
% fractional values upwards until the objective value is achieved.
x_bar = MUWP_LP(RA_weights, RA_tk, interval_size);
x_bar_round ... |
github | rasake/MPCAS-master | DivideGraph.m | .m | MPCAS-master/FFR120 Simulation of Complex Systems/Homework 5/DivideGraph.m | 776 | utf_8 | 1cf3411b8882ace56b522786662e94fa | function [ Q, communities ] = DivideGraph( A )
%DIVIDEGRAPH Summary of this function goes here
% Detailed explanation goes here
m = sum(sum(A))/2;
nodes = 1:length(A);
B = ModularityMatrix(A,m);
communities = cell(0);
[Q, communities] = modularityRec(B,0,m,nodes,communities);
function [Q, communities] = modularityR... |
github | rasake/MPCAS-master | TournamentSelect.m | .m | MPCAS-master/FFR105 Stochastic Optimization/Home Problem 2/2.1/2.1d/TournamentSelect.m | 1,785 | utf_8 | d44b17594d34db11f108618a92d2c7c1 | function [ iSelected ] = TournamentSelect( fitness, tournamentSelectionParameter, tournamentSize )
populationSize = size(fitness,1);
indicesContestants = zeros(1,tournamentSize);
fitnessContestants = zeros(1,tournamentSize);
% Randomly Select individuals to enter the tournament
for k = 1:tournamentSize
kIndex = 1 ... |
github | rasake/MPCAS-master | TournamentSelect.m | .m | MPCAS-master/FFR105 Stochastic Optimization/Home Problem 2/2.1/2.1b/TournamentSelect.m | 1,785 | utf_8 | d44b17594d34db11f108618a92d2c7c1 | function [ iSelected ] = TournamentSelect( fitness, tournamentSelectionParameter, tournamentSize )
populationSize = size(fitness,1);
indicesContestants = zeros(1,tournamentSize);
fitnessContestants = zeros(1,tournamentSize);
% Randomly Select individuals to enter the tournament
for k = 1:tournamentSize
kIndex = 1 ... |
github | rasake/MPCAS-master | TournamentSelect.m | .m | MPCAS-master/FFR105 Stochastic Optimization/Home Problem 2/2.3/TournamentSelect.m | 1,785 | utf_8 | d44b17594d34db11f108618a92d2c7c1 | function [ iSelected ] = TournamentSelect( fitness, tournamentSelectionParameter, tournamentSize )
populationSize = size(fitness,1);
indicesContestants = zeros(1,tournamentSize);
fitnessContestants = zeros(1,tournamentSize);
% Randomly Select individuals to enter the tournament
for k = 1:tournamentSize
kIndex = 1 ... |
github | rasake/MPCAS-master | TournamentSelect.m | .m | MPCAS-master/FFR105 Stochastic Optimization/Home Problem 2/2.4/TournamentSelect.m | 1,785 | utf_8 | 17132c9d040e6c58daf06401e78b8306 | function [ iSelected ] = TournamentSelect( fitness, tournamentSelectionParameter, tournamentSize )
populationSize = length(fitness);
indicesContestants = zeros(1,tournamentSize);
fitnessContestants = zeros(1,tournamentSize);
% Randomly Select individuals to enter the tournament
for k = 1:tournamentSize
kIndex = 1 ... |
github | rasake/MPCAS-master | TournamentSelect.m | .m | MPCAS-master/FFR105 Stochastic Optimization/Home Problem 1/Problem 1.3/TournamentSelect.m | 1,785 | utf_8 | 9fef91f91f7108e8069f419ae925375c | function [ iSelected ] = TournamentSelect( fitness, tournamentSelectionParameter, tournamentSize )
populationSize = size(fitness,2);
indicesContestants = zeros(1,tournamentSize);
fitnessContestants = zeros(1,tournamentSize);
% Randomly Select individuals to enter the tournament
for k = 1:tournamentSize
kIndex = 1 ... |
github | imatge-upc/pcl-master | plot_camera_poses.m | .m | pcl-master/gpu/kinfu/tools/plot_camera_poses.m | 3,407 | utf_8 | d210c150da98c3f4667f2c1e8d4eb6d2 | % Copyright (c) 2014-, Open Perception, Inc.
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions
% are met:
%
% * Redistributions of source code must retain the above copyright
% notice, this list of ... |
github | mcv-m1-project/Team5-master | rgb2yuv.m | .m | Team5-master/week1/rgb2yuv.m | 643 | utf_8 | a08cf3a0f2c43a09cc25d8c521506f7e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%This function rgb2yuv converts the RB matrix of an image to an YUV format%
%matrix for the image. It plots the images, if Plot Flag is eqaul to 1. %
% Code from: Mathworks
%%%%%%%%%%... |
github | mcv-m1-project/Team5-master | mystrel.m | .m | Team5-master/week5/Morphologic_operators/Our operators/mystrel.m | 1,337 | utf_8 | a8cc8a5733e4559fc8ea3365a9f20396 | % Task 1. mystrel is a function that creates the morphological structuring
% element that will be used by the morphological operators. The function
% has the next three input parameters (IP) and one output parameter (OP).
%
% size1: (IP) parameter used to create the circle and square structuring element
% size2: (IP) p... |
github | mcv-m1-project/Team5-master | TrafficSignDetection.m | .m | Team5-master/week5/TrafficSignDetection/TrafficSignDetection.m | 6,423 | utf_8 | fb3ab5108eed95507bf253c519d06025 | %
% Template example for using on the validation set.
%
function TrafficSignDetection(directory, pixel_method, window_method, decision_method)
% TrafficSignDetection
% Perform detection of Traffic signs on images. Detection is performed first at the pixel level
% using a color segmentation. Then, using t... |
github | mcv-m1-project/Team5-master | TrafficSignDetection_test.m | .m | Team5-master/week5/TrafficSignDetection/TrafficSignDetection_test.m | 3,876 | utf_8 | 4a32b363bcfd524bfc179d2b7873fa7a | %
% Template example for using on the test set (no annotations).
%
function TrafficSignDetection_validation(input_dir, output_dir, pixel_method, window_method, decision_method)
% TrafficSignDetection
% Perform detection of Traffic signs on images. Detection is performed first at the pixel level
% using a... |
github | mcv-m1-project/Team5-master | colorspace_demo.m | .m | Team5-master/week5/colorspace/colorspace_demo.m | 6,856 | utf_8 | f7d66bc3e0e1bf1611fbd525c617323c | function colorspace_demo(Cmd)
% Demo for colorspace.m - 3D visualizations of various color spaces
% Pascal Getreuer 2006
if nargin == 0
% Create a figure with a drop-down menu
figure('Color',[1,1,1]);
h = uicontrol('Style','popup','Position',[15,10,90,21],...
'BackgroundColor',[1,1,1],'Value',2,...
... |
github | mcv-m1-project/Team5-master | colorspace.m | .m | Team5-master/week5/colorspace/colorspace.m | 16,178 | utf_8 | 2ca0aee9ae4d0f5c12a7028c45ef2b8d | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Transform a color image between color representations.
% B = COLORSPACE(S,A) transforms the color representation of image A
% where S is a string specifying the conversion. The input array A
% should be a real full double array of size Mx3 or MxN... |
github | mcv-m1-project/Team5-master | rgb2yuv.m | .m | Team5-master/week5/color_segmentation/Other color spaces/rgb2yuv.m | 643 | utf_8 | a08cf3a0f2c43a09cc25d8c521506f7e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%This function rgb2yuv converts the RB matrix of an image to an YUV format%
%matrix for the image. It plots the images, if Plot Flag is eqaul to 1. %
% Code from: Mathworks
%%%%%%%%%%... |
github | mcv-m1-project/Team5-master | Template.m | .m | Team5-master/week5/Template_Matching/Manual_Templates/Template.m | 754 | utf_8 | e5aafc846e7fcad7a03e50c638865598 | %Task 1 w4
function template = Template(signType,siz)
switch signType
case 1
template = template_model1(siz);
template = edge(template,'canny');
% figure();
% imshow(template);
case 2
template = template_model2(siz);
... |
github | mcv-m1-project/Team5-master | segment_ucm.m | .m | Team5-master/week5/UCM/segment-ucm/segment_ucm.m | 536 | utf_8 | 01d9c9826818aed0c9a3cf01e588bf78 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% Ramon Morros
%
function seg = segment_ucm(ima, tresh)
% Segment an image by thresholding an UCM
% Usage: seg = segment_ucm(ima, thresh)
%
% INPUT:
% ima ... |
github | mcv-m1-project/Team5-master | label2color.m | .m | Team5-master/week5/UCM/segment-ucm/label2color.m | 293 | utf_8 | 69e8578eba6978322e9597e5b56b9dca |
function out = label2color(P1,lut)
if nargin == 1
lut=round(rand (256,3)*255);
end;
out = zeros([size(P1) 3]);
num_labels=max(max(P1));
for i=0:num_labels
[x y] = find(P1 == i);
for j=1:length(x)
out(x(j),y(j),:)=lut(P1(x(j),y(j)),:);
end
end
out = uint8(out); |
github | mcv-m1-project/Team5-master | im2ucm.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/im2ucm.m | 2,047 | utf_8 | 4421cb356d72c12a78ccfbedc8dc797b | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | build.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/build.m | 9,922 | utf_8 | 62c5480408ada1b97c6405a20bc425ce | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | im2mcg.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/im2mcg.m | 5,919 | utf_8 | 3687839f11d2bb6a167890706d9ce6ae | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | root_dir.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/root_dir.m | 894 | utf_8 | c282f71bb5106221992ac98b0168249e | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | im2mcg_all.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/scripts/im2mcg_all.m | 2,313 | utf_8 | bef0c1d062820723d2607d13d02a3ad7 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | im2ucm_all.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/scripts/im2ucm_all.m | 2,003 | utf_8 | ebb5a39595e92fb3e4465d500d0e50c6 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | get_image.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/datasets/get_image.m | 1,113 | utf_8 | f58ee1137ccc5bb555ffbb54b4ec2da0 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | database_ids.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/datasets/database_ids.m | 972 | utf_8 | e0364e977e88995d1760a588f94e3bb9 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | database_root_dir.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/datasets/database_root_dir.m | 1,429 | utf_8 | bf9aaf2194f65c3ae68986064b437601 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | get_ground_truth.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/datasets/get_ground_truth.m | 1,468 | utf_8 | d35bcfec9349d8701ca750a506bdbf00 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | eval_and_save_labels.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/benchmark/eval_and_save_labels.m | 4,637 | utf_8 | 8a71c66631ff70cbb33adf72c5cd9891 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | eval_masks.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/benchmark/eval_masks.m | 5,449 | utf_8 | f6be8bb04472131e2da891a8d22fdac1 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | eval_labels.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/benchmark/eval_labels.m | 5,458 | utf_8 | fd9330183b2081c2e18ca34c9fe1d507 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | eval_and_save_masks.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/benchmark/eval_and_save_masks.m | 3,373 | utf_8 | b4a83624eb4a8b05c3b7eceafd4cf2b6 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | img2ucms.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/img2ucms.m | 3,815 | utf_8 | b52be0caec199a96f1d096f49ffb9927 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | seg2bdry.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/seg2bdry.m | 1,654 | utf_8 | 74e74810d5300e25537eb3602e4cbfea | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | contours2OWT.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/contours2OWT.m | 7,309 | utf_8 | 383d9b5b61eedca5cadcfff386c38da5 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | resample_ucm2_sp.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/resample_ucm2_sp.m | 1,724 | utf_8 | cfb56e99ed1056e42db1619078f4fe87 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | apply_sigmoid.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/apply_sigmoid.m | 921 | utf_8 | 0267ef5c72aa92e1314635b39bb6c497 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | project_ucms_wrap.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/project_ucms_wrap.m | 1,129 | utf_8 | e50cc3218fd49fec37b63a08e61b7dcb | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | spectralPb_fast.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/spectralPb_fast.m | 3,834 | utf_8 | 750e5564b38f1990675b71f360d80e59 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | whiten.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/whiten.m | 2,973 | utf_8 | ffcacd11d6b9741ad39cbdff39fa9cf5 | % Copyright (c) 2012, Jonathan Barron and Jitendra Malik (UC Berkeley)
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
% * Redistributions of source code must retain the above copyright
% ... |
github | mcv-m1-project/Team5-master | resample_ucm2.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/resample_ucm2.m | 1,307 | utf_8 | 611cc2357048d34b1a132ea258b17ed3 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | seg2bdry_wt.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/ucms/seg2bdry_wt.m | 1,661 | utf_8 | fa44358ded48a7a64e1b7469b69a9632 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% -... |
github | mcv-m1-project/Team5-master | mask2box.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/bboxes/mask2box.m | 1,042 | utf_8 | a7aa0f22e975b029a3665e5630f2dcc0 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | boxes_iou.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/bboxes/boxes_iou.m | 530 | utf_8 | 3191fe8b4059676fe014f652c833df41 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% June 2013
% ------------------------------------------------------------------------
function iou = boxes_iou(... |
github | mcv-m1-project/Team5-master | box2mask.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/bboxes/box2mask.m | 1,011 | utf_8 | 23da7e097efeec41a1c7538bd4f57022 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | box_area.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/bboxes/box_area.m | 892 | utf_8 | 2ec6564f43c0f7d955e5ca78fd14e4a6 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | boxes_intersection.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/bboxes/boxes_intersection.m | 1,344 | utf_8 | 82e36aab8034ef6ceb8bdb2804177478 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | compute_full_features.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/cands/compute_full_features.m | 2,072 | utf_8 | ab0b550c895af707a646b8a7b7532983 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | compute_base_features.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/cands/compute_base_features.m | 6,341 | utf_8 | bb7a4fbec9641c701300dde338798853 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | fuse_bpts.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/cands/fuse_bpts.m | 2,389 | utf_8 | a9733ab50f5b48eb58b183f668d66ed9 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | full_cands_from_hiers.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/cands/full_cands_from_hiers.m | 4,717 | utf_8 | 5099dda0e9ecf536de996322da531813 | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | hole_filling.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/cands/hole_filling.m | 1,384 | utf_8 | aa2df0c9f6303c43ce4002638476deeb | % ------------------------------------------------------------------------
% Copyright (C)
% Universitat Politecnica de Catalunya BarcelonaTech (UPC) - Spain
% University of California Berkeley (UCB) - USA
%
% Jordi Pont-Tuset <jordi.pont@upc.edu>
% Pablo Arbelaez <arbelaez@berkeley.edu>
% June 2014
% ---------... |
github | mcv-m1-project/Team5-master | regRF_predict.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/RF_Reg_C/regRF_predict.m | 2,355 | utf_8 | 902ec69826d5e1a1934282844538ffd4 | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls the... |
github | mcv-m1-project/Team5-master | regRF_train.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/RF_Reg_C/regRF_train.m | 14,672 | utf_8 | 8e71e57007779bbc8411a1dbd4e845ab | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Regression Random Forest
% A wrapper matlab file that calls th... |
github | mcv-m1-project/Team5-master | rfImpute.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/RF_Reg_C/rfImpute.m | 2,694 | utf_8 | 2a8efadbda8fb3a7c7f24e56b6ec44d2 | function rfImpute_test
%Testing code, which uses the rfImpute_reg function below it
%load the diabetes dataset
load data/diabetes
%modify so that training data is NxD and labels are Nx1, where N=#of
%examples, D=# of features
X = diabetes.x;
Y = diabetes.y;
[N D] =size(X);
%rando... |
github | mcv-m1-project/Team5-master | compile_windows.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/RF_Reg_C/compile_windows.m | 906 | utf_8 | 3a72c18ccf410164c64be827cf6f8846 | % ********************************************************************
% * mex File compiling code for Random Forest (for windows)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% ... |
github | mcv-m1-project/Team5-master | compile_linux.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/RF_Reg_C/compile_linux.m | 976 | utf_8 | 47918ffe762bb7fb86758848f78ff5f7 | % ********************************************************************
% * mex File compiling code for Random Forest (for linux)
% * mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
% * Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
% * License: GPLv2
% * Version: 0.02
% *... |
github | mcv-m1-project/Team5-master | edgesDetect.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/structured_forest/edgesDetect.m | 3,386 | utf_8 | f2ca2b9f519d7215249b84e2e76a4fbe | function [E,Es,O] = edgesDetect( I, model )
% Detect edges in image.
%
% For an introductory tutorial please see edgesDemo.m.
%
% The following model params may be altered prior to detecting edges:
% prm = stride, multiscale, nTreesEval, nThreads, nms
% Simply alter model.opts.prm. For example, set model.opts.n... |
github | mcv-m1-project/Team5-master | edgesTrain.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/structured_forest/edgesTrain.m | 13,326 | utf_8 | a33a2dfef0576f48f5c642f27c34bad7 | function model = edgesTrain( varargin )
% Train structured edge detector.
%
% For an introductory tutorial please see edgesDemo.m.
%
% USAGE
% opts = edgesTrain()
% model = edgesTrain( opts )
%
% INPUTS
% opts - parameters (struct or name/value pairs)
% (1) model parameters:
% .imWidth - [32] width of i... |
github | mcv-m1-project/Team5-master | edgesSweeps.m | .m | Team5-master/week5/UCM/segment-ucm/MCG-PreTrained/src/external/structured_forest/edgesSweeps.m | 8,283 | utf_8 | 7172de7672356db5f5362f115cf199da | function edgesSweeps()
% Parameter sweeps for structured edge detector.
%
% Running the parameter sweeps requires altering internal flags.
% The sweeps are not well documented, use at your own discretion.
%
% Structured Edge Detection Toolbox Version 1.0
% Copyright 2013 Piotr Dollar. [pdollar-at-microsoft.com... |
github | mcv-m1-project/Team5-master | mystrel.m | .m | Team5-master/week4/Morphologic_operators/Our operators/mystrel.m | 1,337 | utf_8 | a8cc8a5733e4559fc8ea3365a9f20396 | % Task 1. mystrel is a function that creates the morphological structuring
% element that will be used by the morphological operators. The function
% has the next three input parameters (IP) and one output parameter (OP).
%
% size1: (IP) parameter used to create the circle and square structuring element
% size2: (IP) p... |
github | mcv-m1-project/Team5-master | TrafficSignDetection.m | .m | Team5-master/week4/TrafficSignDetection/TrafficSignDetection.m | 6,423 | utf_8 | fb3ab5108eed95507bf253c519d06025 | %
% Template example for using on the validation set.
%
function TrafficSignDetection(directory, pixel_method, window_method, decision_method)
% TrafficSignDetection
% Perform detection of Traffic signs on images. Detection is performed first at the pixel level
% using a color segmentation. Then, using t... |
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