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github | lcnbeapp/beapp-master | MARA.m | .m | beapp-master/Packages/eeglab14_1_2b/plugins/MARA-master/MARA.m | 12,568 | utf_8 | 5127d8f931932b5c0760a9a61a0d0b6e | % MARA() - Automatic classification of multiple artifact components
% Classies artifactual ICs based on 6 features from the time domain,
% the frequency domain, and the pattern
%
% Usage:
% >> [artcomps, info] = MARA(EEG);
%
% Inputs:
% EEG - input EEG structure
%
% Outputs:
% artcom... |
github | lcnbeapp/beapp-master | pop_selectcomps_MARA.m | .m | beapp-master/Packages/eeglab14_1_2b/plugins/MARA-master/pop_selectcomps_MARA.m | 7,617 | utf_8 | 3df13de5291a735a3ae902eb9b7b4349 | % pop_selectcomps_MARA() - Display components with checkbox to label
% them for artifact rejection
%
% Usage:
% >> EEG = pop_selectcomps_MARA(EEG, gcompreject_old);
%
% Inputs:
% EEG - Input dataset with rejected components (saved in
% EEG.reject.gcompreject)
%... |
github | lcnbeapp/beapp-master | pop_processMARA.m | .m | beapp-master/Packages/eeglab14_1_2b/plugins/MARA-master/pop_processMARA.m | 5,095 | utf_8 | 7932742793cce3ca7b8caeb78ae22d82 | % pop_processMARA() - graphical interface to select MARA's actions
%
% Usage:
% >> [ALLEEG,EEG,CURRENTSET,com] = pop_processMARA(ALLEEG,EEG,CURRENTSET );
%
% Inputs and Outputs:
% ALLEEG - array of EEG dataset structures
% EEG - current dataset structure or structure array
% (EEG.re... |
github | lcnbeapp/beapp-master | fooof_group.m | .m | beapp-master/Packages/fooof-master/fooof_mat-master/matlab_wrapper/fooof_group.m | 1,475 | utf_8 | 974a8666887be9f1b2a2c5bdc3238423 | % fooof_group() run the fooof model on a group of neural power spectra
%
% Usage:
% fooof_results = fooof_group(freqs, psds, f_range, settings);
%
% Inputs:
% freqs = row vector of frequency values
% psds = matrix of power values, which each row representing a spectrum
% f_range = f... |
github | lcnbeapp/beapp-master | fooof_check_settings.m | .m | beapp-master/Packages/fooof-master/fooof_mat-master/matlab_wrapper/fooof_check_settings.m | 735 | utf_8 | 1288684349fda0893e8d12f386f68e6c | % Check fooof settings, provided as a struct
% Any settings not specified are set to default values
function settings = fooof_check_settings(settings)
if ~isfield(settings, 'peak_width_limits')
settings.peak_width_limits = [0.5, 12];
end
if ~isfield(settings, 'max_n_peaks')
setting... |
github | lcnbeapp/beapp-master | fooof_unpack_results.m | .m | beapp-master/Packages/fooof-master/fooof_mat-master/matlab_wrapper/fooof_unpack_results.m | 941 | utf_8 | 3bc34ef5c084798af19241baef790402 | % Unpack fooof_results python object into matlab struct
function results_out = fooof_unpack_results(results_in)
results_out = struct();
results_out.background_params = ...
double(py.array.array('d', results_in.background_params));
temp = double(py.array.array('d', results_in.peak_params.... |
github | lcnbeapp/beapp-master | load_fooof_results.m | .m | beapp-master/Packages/fooof-master/fooof_mat-master/mat_py_mat/utils/load_fooof_results.m | 771 | utf_8 | ae210cf78ec635a9a8eab78a8de4c6ef | % load_fooof_results () - load results from a json file (as saved out by FOOOF)
%
% Usage:
% >> fooof_results = load_fooof_results(file_name)
%
% Inputs:
% file_name = file name of the fooof-format json file to load
%
% Ouputs:
% fooof_results = fooof model ouputs, in a struct, including:
% fooof_re... |
github | lcnbeapp/beapp-master | REST.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/REST.m | 22,825 | utf_8 | 940d9f3ff2cc3e996ef7d99fee778dd5 | function varargout = REST(varargin)
% REST M-untitled_1 for REST.fig
% REST, by itself, creates a new REST or raises the existing
% singleton*.
%
% H = REST returns the handle to a new REST or the handle to
% the existing singleton*.
%
% REST('CALLBACK',hObject,eventData,handles,...) calls the ... |
github | lcnbeapp/beapp-master | iseeglabdeployed.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/iseeglabdeployed.m | 154 | utf_8 | cb8716ae372b37132bb2a58c54d09cd0 | % iseeglabdeployed - true for EEGLAB compile version and false otherwise
function val = iseeglabdeployed
try
val = isdeployed;
catch
val = 0;
end |
github | lcnbeapp/beapp-master | pop_editeventvals.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/pop_editeventvals.m | 25,793 | utf_8 | de89caf08acbbceb7572ea96a994e688 | % pop_editeventvals() - Edit events contained in an EEG dataset structure.
% If the dataset is the only input, a window pops up
% allowing the user to insert the relevant parameter values.
%
% Usage: >> EEGOUT = pop_editeventvals( EEG, 'key1', value1, ...
% ... |
github | lcnbeapp/beapp-master | readlocs.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/readlocs.m | 33,881 | utf_8 | 7e1d85669932dffeca11a8fad52e02ca | % readlocs() - read electrode location coordinates and other information from a file.
% Several standard file formats are supported. Users may also specify
% a custom column format. Defined format examples are given below
% (see File Formats).
% Usage:
% >> eloc = readlocs( ... |
github | lcnbeapp/beapp-master | pop_loadcnt.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/pop_loadcnt.m | 9,941 | utf_8 | 10cd7be4518af4743674c4648efd7912 | % pop_loadcnt() - load a neuroscan CNT file (pop out window if no arguments).
%
% Usage:
% >> EEG = pop_loadcnt; % pop-up window mode
% >> EEG = pop_loadcnt( filename, 'key', 'val', ...);
%
% Graphic interface:
% "Data fomat" - [checkbox] 16-bits or 32-bits. We couldn't find in the
% data file w... |
github | lcnbeapp/beapp-master | fastif.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/fastif.m | 1,159 | utf_8 | ac76d723f5de7649f75655cbdb653c1a | % fastif() - fast if function.
%
% Usage:
% >> res = fastif(test, s1, s2);
%
% Input:
% test - logical test with result 0 or 1
% s1 - result if 1
% s2 - result if 0
%
% Output:
% res - s1 or s2 depending on the value of the test
%
% Author: Arnaud Delorme, CNL / Salk Institute, 2001
% Copyright (... |
github | lcnbeapp/beapp-master | vararg2str.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/vararg2str.m | 6,803 | utf_8 | 547476651c6901a530169197da722d2d | % vararg2str() - transform arguments into string for evaluation
% using the eval() command
%
% Usage:
% >> strout = vararg2str( allargs );
% >> strout = vararg2str( allargs, inputnames, inputnum, nostrconv );
%
% Inputs:
% allargs - Cell array containing all arguments
% inputnames - Cell arra... |
github | lcnbeapp/beapp-master | readbvconf.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/readbvconf.m | 3,483 | utf_8 | 046693797f9f7a29e1836365b45d5273 | % readbvconf() - read Brain Vision Data Exchange format configuration
% file
%
% Usage:
% >> CONF = readbvconf(pathname, filename);
%
% Inputs:
% pathname - path to file
% filename - filename
%
% Outputs:
% CONF - structure configuration
%
% Author: Andreas Widmann, University of Leipzig,... |
github | lcnbeapp/beapp-master | eeg_eventformat.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_eventformat.m | 3,014 | utf_8 | d06b550e78556cb151a924c2b32b19f9 | % eeg_eventformat() - Convert the event information of a dataset from struct
% to array or vice versa.
%
% Usage: >> [eventout fields] = eeg_eventformat( event, 'format', fields );
%
% Inputs:
% event - event array or structure
% format - ['struct'|'array'] see below
% fields - [optional] cell ar... |
github | lcnbeapp/beapp-master | supergui.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/supergui.m | 21,015 | utf_8 | 7052cd3beac708d834c25d61e1f9a26c | % supergui() - a comprehensive gui automatic builder. This function help
% to create GUI very fast without bothering about the
% positions of the elements. After creating a geometry,
% elements just place themselves into the predefined
% locations. It is especially... |
github | lcnbeapp/beapp-master | unique_bc.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/unique_bc.m | 717 | utf_8 | 1ac4b80ca073d969c0b6d0e7a0db1f3d | % unique_bc - unique backward compatible with Matlab versions prior to 2013a
function [C,IA,IB] = unique_bc(A,varargin);
errorFlag = error_bc;
v = version;
indp = find(v == '.');
v = str2num(v(1:indp(2)-1));
if v > 7.19, v = floor(v) + rem(v,1)/10; end;
if nargin > 2
ind = strmatch('legacy', varargin);
if ~... |
github | lcnbeapp/beapp-master | pop_loadbv.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/pop_loadbv.m | 14,131 | utf_8 | fa611f0f7f28f1958c48ab15c61fbe64 | % pop_loadbv() - load Brain Vision Data Exchange format dataset and
% return EEGLAB EEG structure
%
% Usage:
% >> [EEG, com] = pop_loadbv; % pop-up window mode
% >> [EEG, com] = pop_loadbv(path, hdrfile);
% >> [EEG, com] = pop_loadbv(path, hdrfile, srange);
% >> [EEG, com] = pop_loadbv(path, hdrf... |
github | lcnbeapp/beapp-master | union_bc.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/union_bc.m | 724 | utf_8 | 958b5b56de3e20c3892b2d7809e830fd | % union_bc - union backward compatible with Matlab versions prior to 2013a
function [C,IA,IB] = union_bc(A,B,varargin);
errorFlag = error_bc;
v = version;
indp = find(v == '.');
v = str2num(v(1:indp(2)-1));
if v > 7.19, v = floor(v) + rem(v,1)/10; end;
if nargin > 2
ind = strmatch('legacy', varargin);
if ~i... |
github | lcnbeapp/beapp-master | eeg_emptyset.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_emptyset.m | 2,505 | utf_8 | a93f07a3989f904c1eade15794aab1f1 | % eeg_emptyset() - Initialize an EEG dataset structure with default values.
%
% Usage:
% >> EEG = eeg_emptyset();
%
% Outputs:
% EEG - empty dataset structure with default values.
%
% Author: Arnaud Delorme, CNL / Salk Institute, 2001
%
% See also: eeglab()
% Copyright (C) 2001 Arnaud Delorme, Salk Institute, a... |
github | lcnbeapp/beapp-master | pop_chanedit.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/pop_chanedit.m | 51,760 | utf_8 | b862a91a53ab88379de4ffc7091bf575 | % pop_chanedit() - Edit the channel locations structure of an EEGLAB dataset,
% EEG.chanlocs. For structure location and file formats,
% see >> help readlocs
%
% EEG.chanlocs. For structure location and file formats,
% see >> help readlocs
%
% Usag... |
github | lcnbeapp/beapp-master | eeg_getdatact.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_getdatact.m | 12,037 | utf_8 | bc4bb0dfeb0f9183cb320544ba36fbdd | % eeg_getdatact() - get EEG data from a specified dataset or
% component activity
%
% Usage:
% >> signal = eeg_getdatact( EEG );
% >> signal = eeg_getdatact( EEG, 'key', 'val');
%
% Inputs:
% EEG - Input dataset
%
% Optional input:
% 'channel' - [integer array] read only specifi... |
github | lcnbeapp/beapp-master | questdlg2.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/questdlg2.m | 3,133 | utf_8 | d94e219e87da50c5af28fe1007906abc | % questdlg2() - questdlg function clone with coloring and help for
% eeglab().
%
% Usage: same as questdlg()
%
% Warning:
% Case of button text and result might be changed by the function
%
% Author: Arnaud Delorme, CNL / Salk Institute, La Jolla, 11 August 2002
%
% See also: inputdlg2(), errordlg2(), s... |
github | lcnbeapp/beapp-master | eegplot_readkey.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eegplot_readkey.m | 231 | utf_8 | a65a871257ff3e64f58f29ff2c190071 | % eegplot helper function to read key strokes
function eegplot_readkey(src,evnt)
if strcmp(evnt.Key, 'rightarrow')==1
eegplot('drawp',4);
elseif strcmp(evnt.Key, 'leftarrow')==1
eegplot('drawp',1);
end
|
github | lcnbeapp/beapp-master | parsetxt.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/parsetxt.m | 1,595 | utf_8 | daf4054768bfdb3e9112cbb24966ca21 | % parsetxt() - parse text input into cell array
%
% Usage: >> cellarray = parsetxt( txt, delims );
%
% Inputs:
% txt - input text
% delims - optional char array of delimiters (default: [' ' ',' 9]);
%
% Note: commas, and simple quotes are ignored
%
% Author: Arnaud Delorme, CNL / Salk Institute, 18 April 2002... |
github | lcnbeapp/beapp-master | eeg_checkset.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_checkset.m | 66,951 | utf_8 | 3c84836557d3b6105331ba2977702cc0 | % eeg_checkset() - check the consistency of the fields of an EEG dataset
% Also: See EEG dataset structure field descriptions below.
%
% Usage: >> [EEGOUT,changes] = eeg_checkset(EEG); % perform all checks
% except 'makeur'
% >> [EEGOUT,change... |
github | lcnbeapp/beapp-master | parsebvmrk.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/parsebvmrk.m | 1,733 | utf_8 | 830dc68f40bea55d2ed6d85fccec8c51 | % parsebvmrk() - convert Brain Vision Data Exchange format marker
% configuration structure to EEGLAB event structure
%
% Usage:
% >> EVENT = parsebvmrk(MRK);
%
% Inputs:
% MRK - marker configuration structure
%
% Outputs:
% EVENT - EEGLAB event structure
%
% Author: Andreas Widmann, University o... |
github | lcnbeapp/beapp-master | eeg_checkchanlocs.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_checkchanlocs.m | 8,655 | utf_8 | 2664c683e10493731ebda7dfec52968f | % eeg_checkchanlocs() - Check the consistency of the channel locations structure
% of an EEGLAB dataset.
%
% Usage:
% >> EEG = eeg_checkchanlocs( EEG, 'key1', value1, 'key2', value2, ... );
% >> [chanlocs chaninfo] = eeg_checkchanlocs( chanlocs, chaninfo, 'key1', value1, 'key2', value2, ... );
%
%... |
github | lcnbeapp/beapp-master | eeg_epochformat.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eeg_epochformat.m | 7,674 | utf_8 | b6227100d8d67253534322618e4b81fa | % eeg_epochformat() - Convert the epoch information of a dataset from struct
% to array or vice versa.
%
% Usage: >> [epochsout fields] = eeg_epochformat( epochs, 'format', fields, events );
%
% Input:
% epochs - epoch numerical or cell array or epoch structure
% format - ['struct'|'array'] conv... |
github | lcnbeapp/beapp-master | listdlg2.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/listdlg2.m | 3,771 | utf_8 | a0820fcb823bcb9968afa377c5582498 | % listdlg2() - listdlg function clone with coloring and help for
% eeglab().
%
% Usage: same as listdlg()
%
% Author: Arnaud Delorme, CNL / Salk Institute, La Jolla, 16 August 2002
%
% See also: inputdlg2(), errordlg2(), supergui(), inputgui()
% Copyright (C) Arnaud Delorme, CNL / Salk Institute, arno@s... |
github | lcnbeapp/beapp-master | mattocell.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/mattocell.m | 1,311 | utf_8 | bb1357cab390093724fa7887f66ebef3 | % mattocell() - convert matrix to cell array
%
% Usage: >> C = mattocell( M );
%
% Author: Arnaud Delorme, CNL / Salk Institute, Jan 25 2002
%
% Note: this function overload the nnet toolbox function mattocell,
% but does not have all its capacities. You can delete the current
% function if you have the toolbox.
% ... |
github | lcnbeapp/beapp-master | pop_chansel.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/pop_chansel.m | 5,372 | utf_8 | 4773a5a96563eba18577995430d93045 | % pop_chansel() - pop up a graphic interface to select channels
%
% Usage:
% >> [chanlist] = pop_chansel(chanstruct); % a window pops up
% >> [chanlist strchannames cellchannames] = ...
% pop_chansel(chanstruct, 'key', 'val', ...);
%
% Inputs:
% chanstruct - channel structure. See readl... |
github | lcnbeapp/beapp-master | loadcnt.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/loadcnt.m | 23,166 | utf_8 | 3629cdf2a890ef76f423f15fff965b3a | % loadcnt() - Load a Neuroscan continuous signal file.
%
% Usage:
% >> cnt = loadcnt(file, varargin)
%
% Inputs:
% filename - name of the file with extension
%
% Optional inputs:
% 't1' - start at time t1, default 0. Warning, events latency
% might be innacurate (this is an open issue).
% ... |
github | lcnbeapp/beapp-master | finputcheck.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/finputcheck.m | 8,952 | utf_8 | 158851ff64b79dcefc4bead7397ee6f5 | % finputcheck() - check Matlab function {'key','value'} input argument pairs
%
% Usage: >> result = finputcheck( varargin, fieldlist );
% >> [result varargin] = finputcheck( varargin, fieldlist, ...
% callingfunc, mode, verbose );
% Input:
% varargin - Cell array ... |
github | lcnbeapp/beapp-master | eegplot.m | .m | beapp-master/Packages/REST_MATLAB_v1.1_20170828/function/Loading/eegplot.m | 87,220 | utf_8 | cff8d14db834da746efcad1710144559 | % eegplot() - Scroll (horizontally and/or vertically) through multichannel data.
% Allows vertical scrolling through channels and manual marking
% and unmarking of data stretches or epochs for rejection.
% Usage:
% >> eegplot(data, 'key1', value1 ...); % use interface buttons, etc.
%... |
github | lcnbeapp/beapp-master | eegplugin_MARA.m | .m | beapp-master/Packages/MARA-master/eegplugin_MARA.m | 2,770 | utf_8 | 7619f29fb825e45ca839265d7d4046e0 | % eegplugin_MARA() - EEGLab plugin to classify artifactual ICs based on
% 6 features from the time domain, the frequency domain,
% and the pattern
%
% Inputs:
% fig - [integer] EEGLAB figure
% try_strings - [struct] "try" strings for menu callbacks.
% catch_strin... |
github | lcnbeapp/beapp-master | pop_visualizeMARAfeatures.m | .m | beapp-master/Packages/MARA-master/pop_visualizeMARAfeatures.m | 4,558 | utf_8 | c888a9b58c7e7893d090883d152d5e09 | % pop_visualizeMARAfeatures() - Display features that MARA's decision
% for artifact rejection is based on
%
% Usage:
% >> pop_visualizeMARAfeatures(gcompreject, MARAinfo);
%
% Inputs:
% gcompreject - array <1 x nIC> containing 1 if component was rejected
% MARAin... |
github | lcnbeapp/beapp-master | processMARA.m | .m | beapp-master/Packages/MARA-master/processMARA.m | 6,510 | utf_8 | 896a41c6475ec80bf7706cc7166ce7a8 | % processMARA() - Processing for Automatic Artifact Classification with MARA.
% processMARA() calls MACA and saves the identified artifactual components
% in EEG.reject.gcompreject.
% The functions optionally filters the data, runs ICA, plots components or
% reject artifactual components immediately.
%
% U... |
github | lcnbeapp/beapp-master | MARA.m | .m | beapp-master/Packages/MARA-master/MARA.m | 12,568 | utf_8 | 5127d8f931932b5c0760a9a61a0d0b6e | % MARA() - Automatic classification of multiple artifact components
% Classies artifactual ICs based on 6 features from the time domain,
% the frequency domain, and the pattern
%
% Usage:
% >> [artcomps, info] = MARA(EEG);
%
% Inputs:
% EEG - input EEG structure
%
% Outputs:
% artcom... |
github | lcnbeapp/beapp-master | pop_selectcomps_MARA.m | .m | beapp-master/Packages/MARA-master/pop_selectcomps_MARA.m | 7,617 | utf_8 | 3df13de5291a735a3ae902eb9b7b4349 | % pop_selectcomps_MARA() - Display components with checkbox to label
% them for artifact rejection
%
% Usage:
% >> EEG = pop_selectcomps_MARA(EEG, gcompreject_old);
%
% Inputs:
% EEG - Input dataset with rejected components (saved in
% EEG.reject.gcompreject)
%... |
github | lcnbeapp/beapp-master | pop_processMARA.m | .m | beapp-master/Packages/MARA-master/pop_processMARA.m | 5,095 | utf_8 | 7932742793cce3ca7b8caeb78ae22d82 | % pop_processMARA() - graphical interface to select MARA's actions
%
% Usage:
% >> [ALLEEG,EEG,CURRENTSET,com] = pop_processMARA(ALLEEG,EEG,CURRENTSET );
%
% Inputs and Outputs:
% ALLEEG - array of EEG dataset structures
% EEG - current dataset structure or structure array
% (EEG.re... |
github | lcnbeapp/beapp-master | gen_HAPPE_output_table_after_crash.m | .m | beapp-master/reference_data/example_scripts/gen_HAPPE_output_table_after_crash.m | 3,240 | utf_8 | 2a5eb56fc5b8a26e3d27b8604f2dbe58 | % create HAPPE report table for all files in directory if there is a crash
% during the ICA module
% function takes grp_proc_info from previous run
function gen_HAPPE_output_table_after_crash(grp_proc_info_in)
cd(grp_proc_info_in.beapp_toggle_mods{'ica','Module_Dir'}{1});
ica_report_categories = {'BEAPP_Fname','Time... |
github | DSAP1718/dsap1718_group2_proj-master | export_data.m | .m | dsap1718_group2_proj-master/VBA/export_data.m | 3,451 | utf_8 | ef25565a86981986f9dddeb7f67a6a77 | % ----------------------------------------------------------------------
% Digital Signal and Audio Processing
% Final Project: Acoustic Guitar-Pitch Detection
% using Cepstral Analysis Excel-GUI Analyzer
%
% Group No. 2
% Leader: Prince Julius T. Hari
% Members: Lester Y. Besabe
% Christi... |
github | LIZHANGYAN/3D-Face-Recognition-using-Covariance-Based-Descriptors-master | read_bntfile.m | .m | 3D-Face-Recognition-using-Covariance-Based-Descriptors-master/read_bntfile.m | 1,058 | utf_8 | c560ad86fb267fbbd6f6e9e84880276e | % Author: Arman Savran (arman.savran@boun.edu.tr)
% Date: 2008
% Outputs:
% zmin : minimum depth value
% nrows : subsampled number of rows
% ncols : subsampled number of columns
% imfile : image file name
% data : Nx5 matrix where columns are 3D coordinates and 2D
% normalized... |
github | Mr-Yuppie/SPBL-master | TrainBase.m | .m | SPBL-master/TrainBase.m | 4,986 | utf_8 | 2096e6af1d0a6a57e0afae32ff7d3392 | function [new_Base,newH] = TrainBase(trainfea,traingnd,u,options)
% Function TrainBase accepts the samples' weights 'u' and their labels
% 'traingnd', and generates the current weak learner, with a type specified in
% 'options'.
% trainfea - the N x D input matrix, where each row data(i,:) corresponds to a data sample... |
github | Mr-Yuppie/SPBL-master | lbfgsb.m | .m | SPBL-master/L-BFGS-B-C-master/Matlab/lbfgsb.m | 10,268 | utf_8 | d9ca76459532b61543d9dac41d9ba87e | function [x,f,info] = lbfgsb( fcn, l, u, opts )
% x = lbfgsb( fcn, l, u )
% uses the lbfgsb v.3.0 library (fortran files must be installed;
% see compile_mex.m ) which is the L-BFGS-B algorithm.
% The algorithm is similar to the L-BFGS quasi-Newton algorithm,
% but also handles bound constraints via an acti... |
github | zucar/Driver-Assistance-System-master | sanim_XY_vehicle_viz.m | .m | Driver-Assistance-System-master/Path Planning/Resources/Matlab_simulation/sanim_XY_vehicle_viz.m | 16,640 | utf_8 | b5889ef5a1fa2d9b5713061122047130 | function [sys,x0,str,ts] = sanim_XY_vehicle_viz(t,x,u,flag,Config)
% sanim_XY_vehicle_viz() - animate a 2D vehicle using SAE coordinates.
%
% This is a modified version of the Mathwork's sanim.m for animating 3D motion.
%
% Marc Compere, comperem@gmail.com
% created : 30 July 2011
% modified: 17 Jan 2016
%
%
% Edited f... |
github | zucar/Driver-Assistance-System-master | rtwmakecfg.m | .m | Driver-Assistance-System-master/Path Planning/Resources/Matlab_simulation/rtwmakecfg.m | 2,815 | utf_8 | 16b58d91a07c158f3016ba8d1adbf057 | function makeInfo=rtwmakecfg()
%RTWMAKECFG.m adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
%... |
github | zucar/Driver-Assistance-System-master | rtwmakecfg.m | .m | Driver-Assistance-System-master/Path Planning/Resources/Matlab_simulation/BaseImpl/rtwmakecfg.m | 2,815 | utf_8 | 16b58d91a07c158f3016ba8d1adbf057 | function makeInfo=rtwmakecfg()
%RTWMAKECFG.m adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
%... |
github | zucar/Driver-Assistance-System-master | rtwmakecfg.m | .m | Driver-Assistance-System-master/Path Planning/Resources/Matlab_simulation/controller/rtwmakecfg.m | 2,815 | utf_8 | 16b58d91a07c158f3016ba8d1adbf057 | function makeInfo=rtwmakecfg()
%RTWMAKECFG.m adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
%... |
github | zucar/Driver-Assistance-System-master | rtwmakecfg.m | .m | Driver-Assistance-System-master/CarModel/Matlab-Model/BaseImpl/rtwmakecfg.m | 2,815 | utf_8 | 16b58d91a07c158f3016ba8d1adbf057 | function makeInfo=rtwmakecfg()
%RTWMAKECFG.m adds include and source directories to rtw make files.
% makeInfo=RTWMAKECFG returns a structured array containing
% following field:
% makeInfo.includePath - cell array containing additional include
% directories. Those directories will be
%... |
github | Akshitaag/Chall-Vihaan-master | MeanVariance.m | .m | Chall-Vihaan-master/routes/codes/MeanVariance.m | 1,364 | utf_8 | 8b23466de4e94d6052135ba671cde88f | ## Copyright (C) 2017 Shreya
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed in... |
github | Akshitaag/Chall-Vihaan-master | probability.m | .m | Chall-Vihaan-master/routes/codes/probability.m | 1,015 | utf_8 | a28db31f8c29e452e555c6e50edd8c41 | ## Copyright (C) 2017 Shreya
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed in... |
github | Akshitaag/Chall-Vihaan-master | main.m | .m | Chall-Vihaan-master/routes/codes/main.m | 1,710 | utf_8 | 1f7ebc3c7c60fd3954acb86f1669cac3 | ## Copyright (C) 2017 Shreya
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed ... |
github | Akshitaag/Chall-Vihaan-master | predictNature.m | .m | Chall-Vihaan-master/routes/codes/predictNature.m | 1,438 | utf_8 | 0f5d425211ad4bf375290e74adbc88bc | ## Copyright (C) 2017 Shreya
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed ... |
github | Akshitaag/Chall-Vihaan-master | exponential.m | .m | Chall-Vihaan-master/routes/codes/exponential.m | 941 | utf_8 | 5da284170d8f5071a07b143da331d909 | ## Copyright (C) 2017 Shreya
##
## This program is free software; you can redistribute it and/or modify it
## under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distributed ... |
github | CSAILVision/miniplaces-master | VOCxml2struct.m | .m | miniplaces-master/util/VOCxml2struct.m | 1,920 | utf_8 | 6a873dba4b24c57e9f86a15ee12ea366 | function res = VOCxml2struct(xml)
xml(xml==9|xml==10|xml==13)=[];
[res,xml]=parse(xml,1,[]);
function [res,ind]=parse(xml,ind,parent)
res=[];
if ~isempty(parent)&&xml(ind)~='<'
i=findchar(xml,ind,'<');
res=trim(xml(ind:i-1));
ind=i;
[tag,ind]=gettag(xml,i);
if ~strcmp(tag,['/' pare... |
github | CSAILVision/miniplaces-master | sample_refNet_initial.m | .m | miniplaces-master/model/matconvnet/sample_refNet_initial.m | 5,252 | utf_8 | 68982f59559512bce9abbee46e1a0618 | function [net] = sample_refNet_initial(varargin)
% sample code for initializing the refNet1 for mini-places challenge
% adapted from matconvnet-1.0-beta14/matconvnet-1.0-beta14/examples/cnn_imagenet_init.m
opts.scale = 1 ;
opts.initBias = 0.1 ;
opts.weightDecay = 1 ;
opts.weightInitMethod = 'gaussian' ;
opts.model = '... |
github | devaib/MXNet-SSD-master | eval_roc.m | .m | MXNet-SSD-master/matlab/kitti/eval_roc.m | 16,332 | utf_8 | 58e745530afd562972eb6733d6afb93a | function eval_roc
clear; close; clc;
val_file = '../../data/kitti/data_object_image_2/training/val.txt';
gts_file = '../../data/kitti/results/gts.txt';
dts_file = '../../data/kitti/results/dts.txt';
dts1_file = '../../data/kitti/results/dts_all_layer_customized.txt';
dts2_file = '../../data/kitti/results/dts_two_strea... |
github | devaib/MXNet-SSD-master | distribution_object_attr.m | .m | MXNet-SSD-master/matlab/kitti/distribution_object_attr.m | 607 | utf_8 | d75ba2748e2c1b866b667e6fb0c595a9 | % inputs
% attribute : which attribute of image to be explored, 'width', 'height' or 'ratio'
% nBin : number of bins in histogram
function distribution_object_attr(attribute, nBin)
imginfo_file = '../../data/kitti/results/imginfos_valset.txt';
% load file
f = fopen(imginfo_file);
imginfos = textscan(f,'%s %d %d %d %d ... |
github | devaib/MXNet-SSD-master | writeLabels.m | .m | MXNet-SSD-master/matlab/kitti/writeLabels.m | 2,759 | utf_8 | 9f25c784ee622dc760d160581deac377 | function writeLabels(objects,label_dir,img_idx)
% parse input file
fid = fopen(sprintf('%s/%06d.txt',label_dir,img_idx),'w');
% for all objects do
for o = 1:numel(objects)
% set label, truncation, occlusion
if isfield(objects(o),'type'), fprintf(fid,'%s ',objects(o).type);
else ... |
github | devaib/MXNet-SSD-master | distribution_object_attr.m | .m | MXNet-SSD-master/matlab/caltechUSA/distribution_object_attr.m | 1,618 | utf_8 | c1bb39c275cc03eecf834929335c6f14 | % inputs
% attribute : which attribute of image to be explored, 'width', 'height' or 'ratio'
% nBin : number of bins in histogram
function distribution_object_attr(attribute, nBin)
imginfo_file = '../../data/caltech-pedestrian-dataset-converter/results/imginfos.txt';
imginfo_train_file = '../../data/caltech-pedestrian-... |
github | devaib/MXNet-SSD-master | vbb.m | .m | MXNet-SSD-master/matlab/caltechUSA/vbb.m | 26,999 | utf_8 | 49eea1941e375a3293a6f9aa9ee21726 | function varargout = vbb( action, varargin )
% Data structure for video bounding box (vbb) annotations.
%
% A video bounding box (vbb) annotation stores bounding boxes (bbs) for
% objects of interest. The primary difference from a static annotation is
% that each object can exist for multiple frames, ie, a vbb annotati... |
github | devaib/MXNet-SSD-master | vbbLabeler.m | .m | MXNet-SSD-master/matlab/caltechUSA/vbbLabeler.m | 38,968 | utf_8 | 03ea75bed8df14e50d44027476666f52 | function vbbLabeler( objTypes, vidNm, annNm )
% Video bound box (vbb) Labeler.
%
% Used to annotated a video (seq file) with (tracked) bounding boxes. An
% online demo describing usage is available. The code below is fairly
% complex and poorly documented. Please do not email me with question about
% how it works (unle... |
github | devaib/MXNet-SSD-master | dbEval.m | .m | MXNet-SSD-master/matlab/caltechUSA/dbEval.m | 18,321 | utf_8 | 4051885de2cf9cce93fbb6a12d8f561a | function dbEval
% Evaluate and plot all pedestrian detection results.
%
% Set parameters by altering this function directly.
%
% USAGE
% dbEval
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
% dbEval
%
% See also bbGt, dbInfo
%
% Caltech Pedestrian Dataset Version 3.2.1
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
... |
github | devaib/MXNet-SSD-master | visualize_annotations.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/visualize_annotations.m | 5,112 | utf_8 | f6bec1dd622dcdfd3bd1e86b31b464ba | function visualize_annotations(path_to_seq_files, set_n, video_n)
% Shows standard caltech annotations and new annotations of ICCV 2015
% submission #1624.
%
% Arguments:
% path_to_seq_files path to the directory containing the set
% directories with the video frames in seq format
% ... |
github | devaib/MXNet-SSD-master | imagesAlign.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/imagesAlign.m | 8,167 | utf_8 | d125eb5beb502d940be5bd145521f34b | function [H,Ip] = imagesAlign( I, Iref, varargin )
% Fast and robust estimation of homography relating two images.
%
% The algorithm for image alignment is a simple but effective variant of
% the inverse compositional algorithm. For a thorough overview, see:
% "Lucas-kanade 20 years on A unifying framework,"
% S. B... |
github | devaib/MXNet-SSD-master | opticalFlow.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/opticalFlow.m | 7,385 | utf_8 | 0fdca13d3caa4421fc488d0031e7838c | function [Vx,Vy,reliab] = opticalFlow( I1, I2, varargin )
% Coarse-to-fine optical flow using Lucas&Kanade or Horn&Schunck.
%
% Implemented 'type' of optical flow estimation:
% LK: http://en.wikipedia.org/wiki/Lucas-Kanade_method
% HS: http://en.wikipedia.org/wiki/Horn-Schunck_method
% SD: Simple block-based sum of ... |
github | devaib/MXNet-SSD-master | seqWriterPlugin.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/seqWriterPlugin.m | 8,280 | utf_8 | 597792f79fff08b8bb709313267c3860 | function varargout = seqWriterPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow writing of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (swp=seqWriterPlugin):
% h=swp('open',h,fName,info) % Open a seq file for writing ... |
github | devaib/MXNet-SSD-master | kernelTracker.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/kernelTracker.m | 9,315 | utf_8 | 4a7d0235f1e518ab5f1c9f1b5450b3f0 | function [allRct, allSim, allIc] = kernelTracker( I, prm )
% Kernel Tracker from Comaniciu, Ramesh and Meer PAMI 2003.
%
% Implements the algorithm described in "Kernel-Based Object Tracking" by
% Dorin Comaniciu, Visvanathan Ramesh and Peter Meer, PAMI 25, 564-577,
% 2003. This is a fast tracking algorithm that utili... |
github | devaib/MXNet-SSD-master | seqIo.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/seqIo.m | 17,019 | utf_8 | 9c631b324bb527372ec3eed3416c5dcc | function out = seqIo( fName, action, varargin )
% Utilities for reading and writing seq files.
%
% A seq file is a series of concatentated image frames with a fixed size
% header. It is essentially the same as merging a directory of images into
% a single file. seq files are convenient for storing videos because: (1)
%... |
github | devaib/MXNet-SSD-master | seqReaderPlugin.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/videos/seqReaderPlugin.m | 9,617 | utf_8 | ad8f912634cafe13df6fc7d67aeff05a | function varargout = seqReaderPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow reading of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (srp=seqReaderPlugin):
% h = srp('open',h,fName) % Open a seq file for reading ... |
github | devaib/MXNet-SSD-master | dirSynch.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/dirSynch.m | 4,570 | utf_8 | d288299d31d15f1804183206d0aa0227 | function dirSynch( root1, root2, showOnly, flag, ignDate )
% Synchronize two directory trees (or show differences between them).
%
% If a file or directory 'name' is found in both tree1 and tree2:
% 1) if 'name' is a file in both the pair is considered the same if they
% have identical size and identical datestamp... |
github | devaib/MXNet-SSD-master | plotRoc.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/plotRoc.m | 5,212 | utf_8 | 008f9c63073c6400c4960e9e213c47e5 | function [h,miss,stds] = plotRoc( D, varargin )
% Function for display of rocs (receiver operator characteristic curves).
%
% Display roc curves. Consistent usage ensures uniform look for rocs. The
% input D should have n rows, each of which is of the form:
% D = [falsePosRate truePosRate]
% D is generated, for exampl... |
github | devaib/MXNet-SSD-master | simpleCache.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/simpleCache.m | 4,098 | utf_8 | 92df86b0b7e919c9a26388e598e4d370 | function varargout = simpleCache( op, cache, varargin )
% A simple cache that can be used to store results of computations.
%
% Can save and retrieve arbitrary values using a vector (includnig char
% vectors) as a key. Especially useful if a function must perform heavy
% computation but is often called with the same in... |
github | devaib/MXNet-SSD-master | tpsInterpolate.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/tpsInterpolate.m | 1,646 | utf_8 | d3bd3a26d048f32cfdc17884ccae6d8c | function [xsR,ysR] = tpsInterpolate( warp, xs, ys, show )
% Apply warp (obtained by tpsGetWarp) to a set of new points.
%
% USAGE
% [xsR,ysR] = tpsInterpolate( warp, xs, ys, [show] )
%
% INPUTS
% warp - [see tpsGetWarp] bookstein warping parameters
% xs, ys - points to apply warp to
% show - [1] will disp... |
github | devaib/MXNet-SSD-master | checkNumArgs.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/checkNumArgs.m | 3,796 | utf_8 | 726c125c7dc994c4989c0e53ad4be747 | function [ x, er ] = checkNumArgs( x, siz, intFlag, signFlag )
% Helper utility for checking numeric vector arguments.
%
% Runs a number of tests on the numeric array x. Tests to see if x has all
% integer values, all positive values, and so on, depending on the values
% for intFlag and signFlag. Also tests to see if ... |
github | devaib/MXNet-SSD-master | fevalDistr.m | .m | MXNet-SSD-master/matlab/caltechUSA/GT-visualization/toolbox/matlab/fevalDistr.m | 11,227 | utf_8 | 7e4d5077ef3d7a891b2847cb858a2c6c | function [out,res] = fevalDistr( funNm, jobs, varargin )
% Wrapper for embarrassingly parallel function evaluation.
%
% Runs "r=feval(funNm,jobs{i}{:})" for each job in a parallel manner. jobs
% should be a cell array of length nJob and each job should be a cell array
% of parameters to pass to funNm. funNm must be a f... |
github | haoranleo/Super-Resolution-Image-Reconstruction-master | generation.m | .m | Super-Resolution-Image-Reconstruction-master/generation.m | 19,112 | utf_8 | 9384a8218695302ca4b4883159523357 | function varargout = generation(varargin)
% GENERATION - GUI for creating low resolution images from an input image
% varargout = generation(varargin)
% graphical user interface used to create a number of shifted and
% rotated low resolution images from a single high resolution input
% image
%% ----... |
github | xuewenfei/EducationAlgorithms-master | ex02_java.m | .m | EducationAlgorithms-master/THEALGORITHMS/IRT_Resources/oscats-0.6 2/examples/ex02_java.m | 6,274 | utf_8 | 87438e3f75b8e3c0a32b96e231be8b6f | % OSCATS: Open-Source Computerized Adaptive Testing System
% Copyright 2011 Michael Culbertson <culbert1@illinois.edu>
%
% Example 2
%
% Example 2
%
% 500 Items: 2D 2PL with covariate
% a1 ~ U(0, 1), a2 ~ U(0, 2), b ~ N(0,3), covariate coef ~ U(0.5, 1.5)
% 500 Examinees on each point of the grid {-1, 0, 1} ... |
github | xuewenfei/EducationAlgorithms-master | ex01_java.m | .m | EducationAlgorithms-master/THEALGORITHMS/IRT_Resources/oscats-0.6 2/examples/ex01_java.m | 5,859 | utf_8 | 0f8a8a8738518e1dde827c23b300aae4 | % OSCATS: Open-Source Computerized Adaptive Testing System
% Copyright 2010, 2011 Michael Culbertson <culbert1@illinois.edu>
%
% Example 1
%
% 400 Items: 1PL, b ~ N(0,1)
% 1000 Examinees: theta ~ N(0,1)
% Item selection:
% - pick randomly
% - match theta with b, exactly
% - match theta with b, randomize 5... |
github | safecrypto/libsafecrypto-master | huffman.m | .m | libsafecrypto-master/huffman.m | 1,976 | utf_8 | 45149521f88dd8ef4d638b578731fa60 | function [huffman, tree] = huffman(bits, sig)
depth = 2^bits;
d = 1 / (sqrt(2 * pi) * sig);
e = -0.5 / (sig * sig);
p(1:depth) = d * exp(e * [0:depth-1].^2);
nodes = num2cell(1:depth);
probs = p;
while length(nodes) > 1
[mn, idx] = min(probs);
probs(idx) = Inf;
[mn2, idx2] = min(probs);
probs(idx) = mn + mn2;... |
github | BestSonny/SSTD-master | classification_demo.m | .m | SSTD-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | ATajadod94/Functional-Connectivity-Analysis-master | myCheckRegistraAndNormalization.m | .m | Functional-Connectivity-Analysis-master/Code/myCheckRegistraAndNormalization.m | 1,601 | utf_8 | 2835a47014775ebc26bb74e1c8b6024b | function myCheckRegistraAndNormalization(isubj,checkFlag)
%i subject id
%checkFlag ===1: check coregistration ==2 check nomormalization
spm('defaults', 'FMRI');
spm_jobman('initcfg');
facefMRIDCMDirectories = importDicomDirectoryExcel;
dataDir = 'C:\Users\zliu\Documents\myStudies\fixMTL\Faces_Repetiion_fMRI\';
[a ia i... |
github | ATajadod94/Functional-Connectivity-Analysis-master | Getting_labels.m | .m | Functional-Connectivity-Analysis-master/Code/4. Label_Code/4.3 Mapping/Getting_labels.m | 8,315 | utf_8 | f9cb09ad034981690b8c486134e142ff | function files = Getting_labels(type,subject,label)
switch type
case 'label'
files = get_labels(subject,label);
case 'structure'
files = get_structure(subject,label);
case 'function'
files = get_functional(subject,label);
case 'motion'
... |
github | ATajadod94/Functional-Connectivity-Analysis-master | resize_img.m | .m | Functional-Connectivity-Analysis-master/Code/4. Label_Code/4.2 Segmenting/resize_img.m | 4,516 | utf_8 | b1e768cfb8086d7aa410954b6b0bf07f | function resize_img(imnames, Voxdim, BB, ismask)
% resize_img -- resample images to have specified voxel dims and BBox
% resize_img(imnames, voxdim, bb, ismask)
%
% Output images will be prefixed with 'r', and will have voxel dimensions
% equal to voxdim. Use NaNs to determine voxdims from transformation matrix
% of i... |
github | hihixuyang/formation_control-master | graph_create.m | .m | formation_control-master/graph_create.m | 3,946 | utf_8 | 8624b473d2653e9c9ff836062facdc37 | function [A_c, A_c_2, A, A_2] = graph_create(connections, connections2, N)
%creates two random graphs using Erdos-Renyi-Algorithm of n-vehicles and
%finds minimum directed spanning tree of these two graphs
%
% Inputs:
% N - number of vehicles
% connections - to leader connected vehicles in graph 1
%... |
github | MINED-MATKIT/SpatStat-Tools-master | LightningCLD2.m | .m | SpatStat-Tools-master/Functions/LightningCLD2.m | 1,625 | utf_8 | f502c2a2b73ba2933d89590845b3c90a | function [chords, ids] = LightningCLD2(A,direction,varargin)
% Calculates the chord length frequency or distribution from 2D or 3D
% binary image.
if direction == 'x'
elseif direction == 'y'
A = permute(A,[2 1 3]);
elseif direction == 'z'
A = permute(A,[1 3 2]);
else
error('Direction must either be ''x'',... |
github | jpeyre/unrel-master | extract_spatialconfig.m | .m | unrel-master/preprocessing/extract_spatialconfig.m | 1,366 | utf_8 | 4b1d3a6dfcd5fb871bc0d2a4eb80da8b | function [features] = extract_spatialconfig(pairs)
[x1,y1,w1,h1,x2,y2,w2,h2] = get_boxes_xywh(pairs);
% Scale
scale1 = w1.*h1;
scale2 = w2.*h2;
% Offset
x1_c = x1+w1/2;
y1_c = y1+h1/2;
x2_c = x2+w2/2;
y2_c = y2+h2/2;
offsetx = x2_c-x1_c;
offsety = -(y2_c-y1_c);
% Aspect ratio
aspectx = w1... |
github | jpeyre/unrel-master | VOCap.m | .m | unrel-master/eval/Lu-eval/VOCap.m | 313 | utf_8 | 3f7eece0efb56f494c27047656d2c31d | % This code was originally written and distributed as part of the
% PASCAL VOC challenge
function ap = VOCap(rec,prec)
mrec=[0 ; rec ; 1];
mpre=[0 ; prec ; 0];
for i=numel(mpre)-1:-1:1
mpre(i)=max(mpre(i),mpre(i+1));
end
i=find(mrec(2:end)~=mrec(1:end-1))+1;
ap=sum((mrec(i)-mrec(i-1)).*mpre(i));
|
github | jpeyre/unrel-master | vis_retrieval.m | .m | unrel-master/vis/vis_retrieval.m | 4,037 | utf_8 | 96b9fb6d0303de57dd6d173bc7eec458 | function vis_retrieval()
% Visualize the top retrieved candidate pairs given a triplet query
% For this, put the images of each dataset in subfloder : ./data/datasetname/images
opts = config();
opts.split = 'test';
opts.use_languagescores = 0;
opts.use_objectscores = 0;
opts.IoUmode = 'subject-object'; % choose... |
github | jpeyre/unrel-master | test_retrieval_Densecap_baseline.m | .m | unrel-master/experiments/test_retrieval_Densecap_baseline.m | 4,043 | utf_8 | 6a9dcceacab24afba4f580f688380bab | function [ap] = test_retrieval_Densecap_baseline()
% DenseCap [1] provides only a region proposal (contrary to our method which provide a pair of boxes).
% Once can interpret this region proposal either as a subject box or union box.
% We obtained these candidate regions and scores by forwarding VRD and
... |
github | auroua/tf_rfcn-master | voc_eval.m | .m | tf_rfcn-master/lib/datasets/VOCdevkit-matlab-wrapper/voc_eval.m | 1,332 | utf_8 | 3ee1d5373b091ae4ab79d26ab657c962 | function res = voc_eval(path, comp_id, test_set, output_dir)
VOCopts = get_voc_opts(path);
VOCopts.testset = test_set;
for i = 1:length(VOCopts.classes)
cls = VOCopts.classes{i};
res(i) = voc_eval_cls(cls, VOCopts, comp_id, output_dir);
end
fprintf('\n~~~~~~~~~~~~~~~~~~~~\n');
fprintf('Results:\n');
aps = [res(:... |
github | jbhuang0604/LapSRN-master | vllab_cnn_train_dag.m | .m | LapSRN-master/vllab_cnn_train_dag.m | 16,946 | utf_8 | 31a94eb8574989c25368eff1ca37acbd | function [net,stats] = vllab_cnn_train_dag(net, imdb, getBatch, varargin)
%CNN_TRAIN_DAG Demonstrates training a CNN using the DagNN wrapper
% CNN_TRAIN_DAG() is similar to CNN_TRAIN(), but works with
% the DagNN wrapper instead of the SimpleNN wrapper.
% Copyright (C) 2014-16 Andrea Vedaldi.
% All rights reserv... |
github | jbhuang0604/LapSRN-master | sp3Filters.m | .m | LapSRN-master/utils/matlabPyrTools/sp3Filters.m | 17,188 | utf_8 | a3514d77e5a92b96d96197ebad343395 | % Steerable pyramid filters. Transform described in:
%
% @INPROCEEDINGS{Simoncelli95b,
% TITLE = "The Steerable Pyramid: A Flexible Architecture for
% Multi-Scale Derivative Computation",
% AUTHOR = "E P Simoncelli and W T Freeman",
% BOOKTITLE = "Second Int'l Conf on Image Processing",
% ADDRESS = "Washington, DC"... |
github | jbhuang0604/LapSRN-master | buildWpyr.m | .m | LapSRN-master/utils/matlabPyrTools/buildWpyr.m | 2,644 | utf_8 | e741b2037d9a1358d4de94580ebcc4bf | % [PYR, INDICES] = buildWpyr(IM, HEIGHT, FILT, EDGES)
%
% Construct a separable orthonormal QMF/wavelet pyramid on matrix (or vector) IM.
%
% HEIGHT (optional) specifies the number of pyramid levels to build. Default
% is maxPyrHt(IM,FILT). You can also specify 'auto' to use this value.
%
% FILT (optional) can be a st... |
github | jbhuang0604/LapSRN-master | reconLpyr.m | .m | LapSRN-master/utils/matlabPyrTools/reconLpyr.m | 2,049 | utf_8 | 657b8012a1ed06b6573496855309b2ae | % RES = reconLpyr(PYR, INDICES, LEVS, FILT2, EDGES)
%
% Reconstruct image from Laplacian pyramid, as created by buildLpyr.
%
% PYR is a vector containing the N pyramid subbands, ordered from fine
% to coarse. INDICES is an Nx2 matrix containing the sizes of
% each subband. This is compatible with the MatLab Wavelet t... |
github | jbhuang0604/LapSRN-master | mkDisc.m | .m | LapSRN-master/utils/matlabPyrTools/mkDisc.m | 1,428 | utf_8 | c6acae0ac1aa738b7ef094eb2ac60f52 | % IM = mkDisc(SIZE, RADIUS, ORIGIN, TWIDTH, VALS)
%
% Make a "disk" image. SIZE specifies the matrix size, as for
% zeros(). RADIUS (default = min(size)/4) specifies the radius of
% the disk. ORIGIN (default = (size+1)/2) specifies the
% location of the disk center. TWIDTH (in pixels, default = 2)
% specifies th... |
github | jbhuang0604/LapSRN-master | spyrHigh.m | .m | LapSRN-master/utils/matlabPyrTools/spyrHigh.m | 189 | utf_8 | 3132a747e0c7bf1879bb32e4d5fda257 | % RES = spyrHigh(PYR, INDICES)
%
% Access the highpass residual band from a steerable pyramid.
% Eero Simoncelli, 6/96.
function res = spyrHigh(pyr,pind)
res = pyrBand(pyr, pind, 1);
|
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