plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | davisvideochallenge/davis-matlab-master | db_set_properties.m | .m | davis-matlab-master/db_util/db_set_properties.m | 3,741 | utf_8 | e477dd0f492925d28eef6be5c5b9ca6e | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.cat/
% March 2017
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWilliams,
... |
github | davisvideochallenge/davis-matlab-master | db_write_result.m | .m | davis-matlab-master/db_util/db_write_result.m | 1,009 | utf_8 | 1c08ba9c0d3b350ccf618e61e5dc0b98 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_results_dir.m | .m | davis-matlab-master/db_util/db_results_dir.m | 727 | utf_8 | 8441a08ebf386973e892a3a9af88c36b | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_seqs.m | .m | davis-matlab-master/db_util/db_seqs.m | 6,282 | utf_8 | bd9f05dd1650590a5709c11d62bbe43e | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWill... |
github | davisvideochallenge/davis-matlab-master | db_read_image.m | .m | davis-matlab-master/db_util/db_read_image.m | 952 | utf_8 | b3bca05dfde5652d98ddca8f5cc66c87 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_attributes.m | .m | davis-matlab-master/db_util/db_attributes.m | 1,807 | utf_8 | 609221acaef7f40b52ffdf5e4795928b | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_read_result.m | .m | davis-matlab-master/db_util/db_read_result.m | 2,026 | utf_8 | 3487aa536aac0c048329eef41ae5d5b0 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_read_annot.m | .m | davis-matlab-master/db_util/db_read_annot.m | 1,549 | utf_8 | 9c05987df004e3cfe93a86951756d05a | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_get_properties.m | .m | davis-matlab-master/db_util/db_get_properties.m | 207 | utf_8 | 41c20f3f54d0bd39dc09c8d18dd2437c |
function str_props = db_get_properties()
if db_sing_mult_obj==0
str1 = 'single';
else
str1 = 'multiple';
end
str_props = [num2str(db_year) '-' str1 '-' db_im_size];
end
|
github | davisvideochallenge/davis-matlab-master | db_sing_mult_obj.m | .m | davis-matlab-master/db_util/private/db_sing_mult_obj.m | 117 | utf_8 | d4f23bc38c4529b391de55e5f516b516 | % Automatically-generated function, do not edit manually
function sing_mult = db_sing_mult_obj()
sing_mult = 1;
end
|
github | davisvideochallenge/davis-matlab-master | read_list_from_file.m | .m | davis-matlab-master/db_util/private/read_list_from_file.m | 1,026 | utf_8 | 14f7af5372fa6b43701dd70539537fa2 | % ------------------------------------------------------------------------
% Copyright (C)
% ETHZ - Computer Vision Lab
%
% Jordi Pont-Tuset <jponttuset@vision.ee.ethz.ch>
% September 2015
% ------------------------------------------------------------------------
% This file is part of the BOP package presented ... |
github | davisvideochallenge/davis-matlab-master | db_im_dir.m | .m | davis-matlab-master/db_util/private/db_im_dir.m | 707 | utf_8 | a9bf8724082a09dbd4cab4a21c581400 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_im_size.m | .m | davis-matlab-master/db_util/private/db_im_size.m | 112 | utf_8 | bc599ae1ec07de3bd1b3bce5d54df35d | % Automatically-generated function, do not edit manually
function im_size = db_im_size()
im_size = '480p';
end
|
github | davisvideochallenge/davis-matlab-master | db_annot_dir.m | .m | davis-matlab-master/db_util/private/db_annot_dir.m | 713 | utf_8 | 96353a5b7cf129c9d10b5574dcd27a80 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | db_year.m | .m | davis-matlab-master/db_util/private/db_year.m | 101 | utf_8 | 946da9181495151cc04321a2dd1f6713 | % Automatically-generated function, do not edit manually
function year = db_year()
year = 2017;
end
|
github | davisvideochallenge/davis-matlab-master | t_stability.m | .m | davis-matlab-master/measures/t_stability.m | 5,377 | utf_8 | 3179a74a7768213bd6102732aa9bf002 | % [T, raw_results] = t_stability( object, ground_truth )
% ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presen... |
github | davisvideochallenge/davis-matlab-master | eval_result.m | .m | davis-matlab-master/measures/eval_result.m | 3,682 | utf_8 | 64d67fb0ee3b1f6f854cb5d34577fc8b | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | jaccard_region.m | .m | davis-matlab-master/measures/jaccard_region.m | 2,638 | utf_8 | a5d8490633600b6d924c8f1bd753d59c | %[J, inters, fp, fn] = jaccard( object, ground_truth )
% ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented... |
github | davisvideochallenge/davis-matlab-master | eval_sequence.m | .m | davis-matlab-master/measures/eval_sequence.m | 4,950 | utf_8 | 57d1ea4535fdc8e696f33a744f233fa8 | % ------------------------------------------------------------------------
% Sergi Caelles, October 2016
% Jordi Pont-Tuset, March 2017
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWill... |
github | davisvideochallenge/davis-matlab-master | eval_frame.m | .m | davis-matlab-master/measures/eval_frame.m | 476 | utf_8 | 4da76d541262d8d18d074fdee5e53b10 |
function eval = eval_frame(mask, measures, mask_gt, num_objects, mask_prev)
if ~exist('num_objects','var')
num_objects = max(length(mask), length(mask_gt));
end
% Compute measures
if ismember('J',measures), eval.J = jaccard_region(mask, mask_gt, num_objects); end
if ismember('F',meas... |
github | davisvideochallenge/davis-matlab-master | f_boundary.m | .m | davis-matlab-master/measures/f_boundary.m | 3,690 | utf_8 | 169ced1cf502ce81ef6291c183796762 | % [precision, recall] = f_boundary(foreground_mask,gt_mask,bound_th)
% ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS pac... |
github | davisvideochallenge/davis-matlab-master | get_bijective_matching.m | .m | davis-matlab-master/measures/private/get_bijective_matching.m | 1,256 | utf_8 | 1a8694fc1d658a1b6828f0583631dd8b | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | points_dist.m | .m | davis-matlab-master/measures/private/points_dist.m | 914 | utf_8 | 4a6cacc648f5069b89e430d52d1ae95c | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | p_poly_dist.m | .m | davis-matlab-master/measures/private/p_poly_dist.m | 2,060 | utf_8 | c1ee7cd783f66765abb8b3d61b96753b | %*******************************************************************************
% function: p_poly_dist
% Description: distance from pont to polygon whose vertices are specified by the
% vectors xv and yv
% Input:
% x - point's x coordinate
% y - point's y coordinate
% xv - vector of pol... |
github | davisvideochallenge/davis-matlab-master | segment_dist.m | .m | davis-matlab-master/measures/private/segment_dist.m | 1,513 | utf_8 | f6ab6aec288e0e6901a8ac57e6f69d5a | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | get_longest_cont.m | .m | davis-matlab-master/measures/auxiliar/get_longest_cont.m | 915 | utf_8 | 00563398f1bc088b5ea262e53f53e38d | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | contour_upsample.m | .m | davis-matlab-master/measures/auxiliar/contour_upsample.m | 1,480 | utf_8 | f89904b17ba315be13df5d9c3cad8b65 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | eval_all.m | .m | davis-matlab-master/experiments/eval_all.m | 1,053 | utf_8 | 94ad5bb5c101b93d6fbf6a639177886a | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | write_to_file.m | .m | davis-matlab-master/experiments/auxiliar/write_to_file.m | 1,114 | utf_8 | ddb66f3fd099d306ebc9152e7f26f282 | % ------------------------------------------------------------------------
% Jordi Pont-Tuset - http://jponttuset.github.io/
% April 2016
% ------------------------------------------------------------------------
% This file is part of the DAVIS package presented in:
% Federico Perazzi, Jordi Pont-Tuset, Brian McWi... |
github | davisvideochallenge/davis-matlab-master | strpad.m | .m | davis-matlab-master/experiments/auxiliar/strpad.m | 2,145 | utf_8 | f0dfdcdc60d9bda251c4967a128e7d84 | %STRPAD pads a string with any number of char either at the start or the
%end
%
% % To pad the string ABC with zeros ('0') at the front to make it 8
% % characters long ('i.e. 00000ABC')
% strpad('ABC',8,'pre','0')
%
% % To pad the string Hello with zeros ('Q') at the end to make it 14
... |
github | CityU-HAN/Dictionary-learning-master | zero_mean_y.m | .m | Dictionary-learning-master/zero_mean_y.m | 90 | utf_8 | 43022e58c6558af8f3bcdca783fcc1d1 | % response to have 0 mean
function z_m_y = zero_mean_y(y),
z_m_y = y - mean(y);
end |
github | CityU-HAN/Dictionary-learning-master | lars.m | .m | Dictionary-learning-master/lars.m | 5,113 | utf_8 | 2ed39c85e3abf7b1172ab70c0ae25597 | % Least Angle Regression
% Inputs:
% X: design matrix
% Y: response
% t: regularization term
%
% Note: We assume the X has been normalized and Y has zero mean
% Returns:
%
% beta:
% Row 1 is the beginning, therefore has no beta being updated
% Row 2 gives the beta being updated after the first step
% R... |
github | CityU-HAN/Dictionary-learning-master | Normalize.m | .m | Dictionary-learning-master/Normalize.m | 582 | utf_8 | 18be1b164d65f5cbe9ed799b7f28a64b | %feature normalization
function nx = Normalize(X)
% nx is the normalized X (the design matrix)
% first, set nx as the original design matrix
nx = X;
% mu is the mean of each feature of the design matrix
% use a zero matrix
mu = zeros(1, size(X,2));
mu = mean(X);
% sig is the standard deviation of each featur... |
github | apast1/cpp_project_group_G-master | trans4_16.m | .m | cpp_project_group_G-master/matlab code v2/trans4_16.m | 366 | utf_8 | cf28676be63108cedcae0c859ee44723 |
% data = rand(2,4);
% data= [95,0.2,0.06,0.5;105,0.4,0.1,1];
function test_matrix = trans4_16(data)
i=1;
for a=1:2
for b=1:2
for c=1:2
for d=1:2
temp = [data(a,1),data(b,2),data(c,3),data(d,4)];
mat(i,:)=temp;
i=i+1;
end... |
github | apast1/cpp_project_group_G-master | trans4_16.m | .m | cpp_project_group_G-master/matlab code/trans4_16.m | 366 | utf_8 | cf28676be63108cedcae0c859ee44723 |
% data = rand(2,4);
% data= [95,0.2,0.06,0.5;105,0.4,0.1,1];
function test_matrix = trans4_16(data)
i=1;
for a=1:2
for b=1:2
for c=1:2
for d=1:2
temp = [data(a,1),data(b,2),data(c,3),data(d,4)];
mat(i,:)=temp;
i=i+1;
end... |
github | ZipCPU/wbpwmaudio-master | showspectrogram.m | .m | wbpwmaudio-master/demo-rtl/showspectrogram.m | 3,451 | utf_8 | dc4c635a669b9a217f323596b36ed2d8 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%% Filename: showspectrogram.m
%%
%% Project: A Wishbone Controlled PWM (audio) controller
%%
%% Purpose: To generate a spectrogram image which can then be used to
%% evaluate the wavfp.dbl file produced by the pdmdemo executable
%% i... |
github | ZipCPU/wbpwmaudio-master | mymap.m | .m | wbpwmaudio-master/demo-rtl/mymap.m | 2,136 | utf_8 | 4e32d6fb2f841c016ab68b3002bdc0c4 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%
%% Filename: mymap.m
%%
%% Project: A Wishbone Controlled PWM (audio) controller
%%
%% Purpose: This file generates my favorite spectrogram color map. The map
%% is designed so that zero maps to black, and one maps to white.
%% In be... |
github | dafrick/codegen-master | example.m | .m | codegen-master/example.m | 10,990 | utf_8 | 62b4a213b0cbdb53ebfc9617bdd49761 | %% Example 1, automatic code generation for hybrid model predictive control with piecewise affine (PWA) dynamics
%
% [x, u, consensus, t, nIt] = EXAMPLE(options)
%
% Generates code for and runs a closed-loop simulation of a hybrid MPC problem
% OUTPUT:
% x - Closed-loop state trajectory [x0 ... xN]
% u ... |
github | dafrick/codegen-master | generateProxCode.m | .m | codegen-master/+pcg/generateProxCode.m | 10,857 | utf_8 | de3fa94aba4b3ca9f13e5359d7ab1cc8 | % GENERATEPROXCODE Generate a fixed-point iteration .mex file
%
% generateProxCode(model, 'par1', val1, 'par2', val2, ...)
%
function generateProxCode(varargin)
p = inputParser;
p.addRequired('M', @isnumeric);
p.addRequired('W', @isnumeric);
p.addRequired('nr', @isnumeric);
p.addParameter('stepSi... |
github | dafrick/codegen-master | generateMVMult.m | .m | codegen-master/+pcg/generateMVMult.m | 2,240 | utf_8 | ff78912f1360b5e2436afc5fea4a19f3 | % GENERATEMVMULT Generate a fixed-point iteration .mex file
%
% generateProxCode(model, 'par1', val1, 'par2', val2, ...)
%
function [data, code] = generateMVMult(varargin)
p = inputParser;
p.addRequired('M', @isnumeric);
p.addRequired('Mname', @ischar)
p.addRequired('vname', @ischar);
p.addRequir... |
github | dafrick/codegen-master | generateSolver.m | .m | codegen-master/+pcg/generateSolver.m | 8,065 | utf_8 | 8bca31ad900f726b09554e744d3afd40 | %% Automatic code generation for hybrid model predictive control with piecewise affine (PWA) dynamics
%
% [update, xi] = GENERATESOLVER(model, N, Hx, hx, Hu, hu, options)
%
% min sum_{k=0}^N 0.5*-x_{k+1}'*Hx*x_{k+1} + hx'*x_{k+1} + 0.5*u_{k}'*Hu*u_{k} + hu'*u_{k}
% s.t. x_{k+1} = dyn.A{i}*x_{k} + dyn.B{i}*u{k} + dyn.c... |
github | dafrick/codegen-master | generateProjections.m | .m | codegen-master/+pcg/generateProjections.m | 14,599 | utf_8 | 3755e811bc23600a4d4d3e276361fd5e | % GENERATEPROJECTIONS Generate a projection .mex file using MPT3
%
% generateProjections(model, 'par1', val1, 'par2', val2, ...)
%
% - model needs to contain structs
% - dims, with the problem dimensions
% - nx, number of states
% - nu, number of inputs
% - nw, number of auxiliaries - needs to be equal ... |
github | dafrick/codegen-master | generateProjection.m | .m | codegen-master/+pcg/generateProjection.m | 3,682 | utf_8 | bcfa2683fa3081b01eb83ec8c0c4c679 | %%
%
% Aeq*x + Ceq*w == beq
% Aineq*x + Cineq*w <= bineq
%
function info = generateProjection(varargin)
p = inputParser;
p.addRequired('name', @ischar);
p.addRequired('n', @(x) (isnumeric(x) && x>0));
p.addParameter('Aeq', [], @isnumeric);
p.addParameter('beq', [], @isnumeric);
p.addParameter(... |
github | at15/mk-fld-master | sample.m | .m | mk-fld-master/sample/gui/sample.m | 3,461 | utf_8 | 429e41e37dba75a8a9bf64eb6383bbbf | function varargout = sample(varargin)
% SAMPLE MATLAB code for sample.fig
% SAMPLE, by itself, creates a new SAMPLE or raises the existing
% singleton*.
%
% H = SAMPLE returns the handle to a new SAMPLE or the handle to
% the existing singleton*.
%
% SAMPLE('CALLBACK',hObject,eventData,handles,... |
github | at15/mk-fld-master | list_log.m | .m | mk-fld-master/sample/gui/list_log.m | 4,247 | utf_8 | b7c10fbfef360558be085a63e1af7575 | function varargout = list_log(varargin)
% LIST_LOG MATLAB code for list_log.fig
% LIST_LOG, by itself, creates a new LIST_LOG or raises the existing
% singleton*.
%
% H = LIST_LOG returns the handle to a new LIST_LOG or the handle to
% the existing singleton*.
%
% LIST_LOG('CALLBACK',hObject,ev... |
github | at15/mk-fld-master | animation.m | .m | mk-fld-master/sample/gui/animation.m | 4,694 | utf_8 | 4ae233aa9c2713ff7bcfac55ebbcdd42 | function varargout = animation(varargin)
% ANIMATION MATLAB code for animation.fig
% ANIMATION, by itself, creates a new ANIMATION or raises the existing
% singleton*.
%
% H = ANIMATION returns the handle to a new ANIMATION or the handle to
% the existing singleton*.
%
% ANIMATION('CALLBACK',hO... |
github | at15/mk-fld-master | changeme_dialog.m | .m | mk-fld-master/sample/gui_advanced/changeme_dialog.m | 6,235 | utf_8 | cff6d5ebe8cca3d0b6b8b0bfbdeefad0 | function varargout = changeme_dialog(varargin)
%CHANGEME_DIALOG M-file for changeme_dialog.fig
% CHANGEME_DIALOG, by itself, creates a new CHANGEME_DIALOG or raises the existing
% singleton*.
%
% H = CHANGEME_DIALOG returns the handle to a new CHANGEME_DIALOG or the handle to
% the existing singleto... |
github | at15/mk-fld-master | changeme_main.m | .m | mk-fld-master/sample/gui_advanced/changeme_main.m | 4,024 | utf_8 | 6cf64ff88cdefce775bae44a5cfdbf61 | function varargout = changeme_main(varargin)
%CHANGEME_MAIN M-file for changeme_main.fig
% CHANGEME_MAIN, by itself, creates a new CHANGEME_MAIN or raises the existing
% singleton*.
%
% H = CHANGEME_MAIN returns the handle to a new CHANGEME_MAIN or the handle to
% the existing singleton*.
%
% C... |
github | at15/mk-fld-master | savejson.m | .m | mk-fld-master/third_party/jsonlab/savejson.m | 19,032 | utf_8 | fcdcba8e45230c57a5d825c60a071e81 | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | at15/mk-fld-master | loadjson.m | .m | mk-fld-master/third_party/jsonlab/loadjson.m | 16,162 | ibm852 | 2bc1da81d0f677f843944b84f0181d58 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | at15/mk-fld-master | loadubjson.m | .m | mk-fld-master/third_party/jsonlab/loadubjson.m | 13,317 | utf_8 | e090cd22109f32b58c8d63b948cfbfcd | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id$
%
% input:
% fname: ... |
github | at15/mk-fld-master | saveubjson.m | .m | mk-fld-master/third_party/jsonlab/saveubjson.m | 17,740 | utf_8 | e8182109b9c4bc0cca50de08f1254247 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | at15/mk-fld-master | fld_solver.m | .m | mk-fld-master/src/ui_solver/fld_solver.m | 7,518 | utf_8 | 2af206a2be1755ef3d8de84dca22293e | function varargout = fld_solver(varargin)
% FLD_SOLVER MATLAB code for fld_solver.fig
% FLD_SOLVER, by itself, creates a new FLD_SOLVER or raises the existing
% singleton*.
%
% H = FLD_SOLVER returns the handle to a new FLD_SOLVER or the handle to
% the existing singleton*.
%
% FLD_SOLVER('CALL... |
github | at15/mk-fld-master | fld.m | .m | mk-fld-master/src/ui_config/fld.m | 18,200 | utf_8 | 3faa18f999c4369d5f45c55d0583ea99 | function varargout = fld(varargin)
% FLD MATLAB code for fld.fig
% FLD, by itself, creates a new FLD or raises the existing
% singleton*.
%
% H = FLD returns the handle to a new FLD or the handle to
% the existing singleton*.
%
% FLD('CALLBACK',hObject,eventData,handles,...) calls the local
% ... |
github | Huangying-Zhan/py-faster-rcnn-master | voc_eval.m | .m | py-faster-rcnn-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 | chaoyan1037/PnP_Solvers-master | p3p.m | .m | PnP_Solvers-master/p3pf/ext/p3p_code_kneip/p3p.m | 6,878 | utf_8 | d624eafb3c1568d6d9f7f7751a6cab47 | % Copyright (c) 2011, Laurent Kneip, ETH Zurich
% 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 | chaoyan1037/PnP_Solvers-master | solveQuartic.m | .m | PnP_Solvers-master/p3pf/ext/p3p_code_kneip/solveQuartic.m | 2,592 | utf_8 | 74f88b5276461cd93fe0d00b39cd0b76 | % Copyright (c) 2011, Laurent Kneip, ETH Zurich
% 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 | rehmanali1994/Plane_Wave_Ultrasound_Stolt_F-K_Migration.github.io-master | fkmig.m | .m | Plane_Wave_Ultrasound_Stolt_F-K_Migration.github.io-master/MATLAB/fkmig.m | 13,780 | utf_8 | 73c9800fae9bd09b66ccc0db6a4b1d8f | function [migSIG,param] = fkmig(SIG,param)
%FKMIG f-k migration for plane wave imaging
% MIGSIG = FKMIG(SIG,PARAM) performs a f-k migration of the signals
% stored in the array SIG. MIGSIG contains the migrated signals. PARAM is
% a structure that contains all the parameter values required for the
% mi... |
github | hotnAny/forte-master | top88_o.m | .m | forte-master/matlab/top88_o.m | 4,980 | utf_8 | 525e79306f1dcd948b1e19dd6e3b221c | %%%% AN 88 LINE TOPOLOGY OPTIMIZATION CODE Nov, 2010 %%%%
function top88_o(nelx,nely,volfrac,penal,rmin,ft)
%% MATERIAL PROPERTIES
E0 = 1;
Emin = 1e-9;
nu = 0.3;
%% PREPARE FINITE ELEMENT ANALYSIS
A11 = [12 3 -6 -3; 3 12 3 0; -6 3 12 -3; -3 0 -3 12];
A12 = [-6 -3 0 3; -3 -6 -3 -6; 0 -3 -6 3; 3 -6 3 -6];
B11... |
github | hotnAny/forte-master | masstransport.m | .m | forte-master/matlab/masstransport.m | 1,197 | utf_8 | 75ee8f7c8b7dac0cd31c9674f7ebf2d9 | function geommean = masstransport(pdf1, pdf2, lambda, niters, kernelsize)
b1 = ones(size(pdf1));
b2 = ones(size(pdf1));
gaussian = fspecial('gaussian', [kernelsize, kernelsize]);
% gaussian = fspecial('gaussian', size(pdf1));
eps = 1e-12;
for iter = 1:niters
c1 = conv2(b1, gauss... |
github | OpenDGPS/Zynq-optimized-RTKLIB-master | plotlexion.m | .m | Zynq-optimized-RTKLIB-master/util/testlex/plotlexion.m | 1,593 | utf_8 | 1333e9ae36ebce0dfcb9da8ab7972734 | function plotlexion(file,index)
%
% plot lex ionosphere correction error
%
% 2010/12/09 0.1 new
%
if nargin<1, file='LEXION_20101204'; end
if nargin<2, index=2; end
eval(file);
td=caltomjd(epoch);
time=time(index);
ep=mjdtocal(td+(time+0.5)/86400);
ts=sprintf('%04.0f/%02.0f/%02.0f %02.0f:%02.0f',ep(1:5));
% plot le... |
github | OpenDGPS/Zynq-optimized-RTKLIB-master | testionex.m | .m | Zynq-optimized-RTKLIB-master/test/utest/testionex.m | 326,974 | utf_8 | e8fe871f5e28acb961451acf230d028f | function testionex
[tec,rms]=testdata1;
range=0:0.01:10;
figure
[c,h]=contourf(0:2:360,90:-2:-90,tec,range);
set(h,'edgecolor','none');
caxis(range([1,end]));
title('vertical iono delay');
figure
[c,h]=contourf(0:2:360,90:-2:-90,sqrt(rms),range);
set(h,'edgecolor','none');
caxis(range([1,end]));
title('vertical ion... |
github | OpenDGPS/Zynq-optimized-RTKLIB-master | testionppp.m | .m | Zynq-optimized-RTKLIB-master/test/utest/testionppp.m | 1,136 | utf_8 | 7023ec339e81fd7fa267d573c3d2d588 | function testionppp
%
% test RTCA/DO229C bug (A.4.4.10.1 A-22,23)
%
az=0:0.1:360;
figure, axes, hold on, box on, grid on;
pos=[80,0];
for i=1:length(az), posp(i,:)=ionppp(pos,[az(i),0]); end
plot(posp(:,2),posp(:,1),'.');
pos=[-75,170];
for i=1:length(az), posp(i,:)=ionppp(pos,[az(i),0]); end
plot(posp(:,2),posp(:,... |
github | OpenDGPS/Zynq-optimized-RTKLIB-master | plotigp.m | .m | Zynq-optimized-RTKLIB-master/test/utest/plotigp.m | 1,278 | utf_8 | bf7bb7d90d3221bbc76f008e0c03363f | function plotigp
figure
mesh=readmesh;
gmt('mmap','proj','eq','cent',[135,35],'scale',10,'pos',[0,0,1,1]);
gmt('mcoast');
gmt('mgrid','gint',2,'lint',10,'color',[.5 .5 .5]);
for i=1:size(mesh,1)
gmt('mplot',mesh(i,1),mesh(i,2),'r','marker','.','markersize',10);
end
plotarea([36,138],15);
% plot ipp area ------... |
github | thunlp/TADW-master | evaluate.m | .m | TADW-master/evaluate.m | 2,358 | utf_8 | 88ce32f587577de4b98c7896dadead0f | function [perf, pred] = evaluate(pred, Y, flag_label)
% perf = evaluate(pred, Y)
% suppose we know the number of labels for ground truth
% calculate the precision, recall and F1 for each label
% as well as micro-F1
% pred: the prediction scores
% Y: a SPARSE matrix of 0 or 1 (size: n X k)
% remove those inst... |
github | austynguo/thesis-ca-master | recursegap.m | .m | thesis-ca-master/recursegap.m | 949 | utf_8 | 8b3365c1ba848c6915f83c31ef78d4f8 | %% Calculate vehicle gap recursively
% pseudocode:
% if next cell is a ' ' (space)
% gap = recursegap()
% then increment gap variable by 1
% else return 1
function gap = recursegap(cellgrid, row, position, arraylength)
% Grid is a toroid (essentially a loop connected from finish to start)
% Take m... |
github | austynguo/thesis-ca-master | cell2csv.m | .m | thesis-ca-master/cell2csv.m | 2,830 | utf_8 | 69d845851d9c9930b9f2d94e219bf8a0 | function cell2csv(fileName, cellArray, separator, excelYear, decimal)
% % Writes cell array content into a *.csv file.
% %
% % CELL2CSV(fileName, cellArray[, separator, excelYear, decimal])
% %
% % fileName = Name of the file to save. [ e.g. 'text.csv' ]
% % cellArray = Name of the Cell Array where the data is ... |
github | austynguo/thesis-ca-master | NStoTEMatrix.m | .m | thesis-ca-master/NStoTEMatrix.m | 1,543 | utf_8 | a332b82f278a8d9baebfabd9f61de056 | %% Convert Nagel-Schreckenberg formatted data to TE-friendly format
% This function converts data given by ns_model.m which is in 'cell' format
% to a matrix (array) format that is required by the JIDT Toolkit for the
% calculation of Transfer Entropy and related meaures
function data = NStoTEMatrix(cellgrid, timestep... |
github | CSAILVision/ihog-master | showHOG.m | .m | ihog-master/showHOG.m | 1,374 | utf_8 | b004848cdd6833041bde8ba7f946cc71 | % showHOG(w)
%
% Legacy HOG visualization
function out = showHOG(w)
w = w(:, :, 1:9) + w(:, :, 10:18) + w(:, :, 19:27);
w = w / 3;
w = repmat(w, [1 1 3]);
w = padarray(w, [0 0 5], 'post');
% Make pictures of positive and negative weights
bs = 20;
pos = HOGpicture(w, bs);
neg = HOGpicture(-w, bs);
% Put pictures toge... |
github | CSAILVision/ihog-master | invertHOG.m | .m | ihog-master/invertHOG.m | 3,290 | utf_8 | 1b902c34830aedfce5c0d5faf808db87 | % invertHOG(feat)
%
% This function recovers the natural image that may have generated the HOG
% feature 'feat'. Usage is simple:
%
% >> feat = features(im, 8);
% >> ihog = invertHOG(feat);
% >> imagesc(ihog); axis image;
%
% By default, invertHOG() will load a prelearned paired dictionary to perform
% the invers... |
github | CSAILVision/ihog-master | nmf.m | .m | ihog-master/spams/src_release/nmf.m | 3,099 | utf_8 | 04975453432077d74521a3a5fe37cf74 | %
% Usage: [U [,V]]=nmf(X,param);
%
% Name: nmf
%
% Description: mexTrainDL is an efficient implementation of the
% non-negative matrix factorization technique presented in
%
% "Online Learning for Matrix Factorization and Sparse Coding"
% by Julien Mairal, Francis Bach, Jean Ponce and Guillermo Sapiro
... |
github | CSAILVision/ihog-master | learnpairdict.m | .m | ihog-master/internal/learnpairdict.m | 4,304 | utf_8 | f7617c6ef5edbe1f7e363e439ec8a117 | % learnpairdict(stream, n, k, size)
%
% This function learns a pair of dictionaries 'dgray' and 'dhog' to allow for
% regression between HOG and grayscale images.
%
% Arguments:
% stream List of filepaths where images are located
% n Number of window patches to extract in total
% k The size of ... |
github | CSAILVision/ihog-master | showpairdict.m | .m | ihog-master/internal/showpairdict.m | 1,192 | utf_8 | 168004a98643d7d486b634e23a8a5a7f | % showpairdict(pd, sy, sx)
%
% Visualizes a few random elements from the paired dictionaries 'pd'. The
% parameters sy and sx are optional and specify the number of elements to show.
function im = showpairdict(pd, sy, sx),
if ~exist('sy', 'var'),
sy = 10;
end
if ~exist('sx', 'var'),
sx = 10;
end
hny = pd.ny;
hnx ... |
github | CSAILVision/ihog-master | resolvestream.m | .m | ihog-master/internal/resolvestream.m | 542 | utf_8 | 6e69bf6b31f6dcca7ae24f402da61e61 | % resolvestream(stream)
%
% If stream is a directory, convert to list of paths. Otherwise,
% do nothing.
function stream = resolvestream(stream),
if isstr(stream),
fprintf('ihog: reading images from directory: %s\n', stream);
directory = stream;
files = dir(stream);
clear stream;
c = 1;
iii = randperm(leng... |
github | CSAILVision/ihog-master | reportcard.m | .m | ihog-master/internal/reportcard.m | 750 | utf_8 | eeab549f9371d13c8d95f144e700bb86 | % reportcard(in, out, pd)
%
% Processes every image in input directory 'in' and outputs
% the inversion to 'out' using the paired dictionary 'pd'. This
% is useful for diagnosis purposes.
function reportcard(in, out, pd),
images = dir(in);
for i=1:length(images);
if ~images(i).isdir,
filepath = [in '/' images(i)... |
github | CSAILVision/ihog-master | invertHOGtriangle.m | .m | ihog-master/internal/invertHOGtriangle.m | 3,426 | utf_8 | 959ac14f4d20035788e30471c0fb8632 | % invertHOGtriangle(feat)
%
% Attempts to reconstruct the image for the HOG features 'feat' using a brute
% force algorithm that repeatedly adds triangles to an image only if doing
% so improves the reconstruction.
%
% Optionally, you can specify an initialization image 'init' to use as
% the starting point. Otherwise,... |
github | ilcb-crex/CREx_fMRI-master | CREx_fMRI_First_Level.m | .m | CREx_fMRI-master/CREx_fMRI_First_Level.m | 12,025 | windows_1250 | 0c7059235b7dfe427e0ae6e5fff062db | function CREx_fMRI_First_Level
% Example of First-Level implementation for SPM12
% Author: Valérie Chanoine, Research Engineer at Brain and Language
% Institute (http://www.blri.fr/)
% Co-authors from BLRI: Samuel Planton and Chotiga Pattadimalok
% Co-authors from fMRI platform: Julien Sein, ... |
github | ilcb-crex/CREx_fMRI-master | CREx_fMRI_QA_tsdiffana.m | .m | CREx_fMRI-master/CREx_fMRI_QA_tsdiffana.m | 10,386 | windows_1250 | 15517b59225d2d03aefcc8cc0cb1dc54 | function CREx_fMRI_QA_tsdiffana
% Author: Valérie Chanoine, Research Engineer at Brain and Language
% Institute (http://www.blri.fr/)
% From Matthew Brett website - 'Time series diagnostics' script (see
% http://imaging.mrc-cbu.cam.ac.uk/imaging/DataDiagnostics)
%
% w.dataDir ... |
github | ilcb-crex/CREx_fMRI-master | CREx_fMRI_Preprocessing_Prisma.m | .m | CREx_fMRI-master/CREx_fMRI_Preprocessing_Prisma.m | 20,991 | windows_1250 | 3bcc421fbc4cd681eb10e97d4ed2e3c5 | function CREx_fMRI_Preprocessing_Prisma
% Example of Preprocessing implementation for SPM12
% Author: Valérie Chanoine, Research Engineer at Brain and Language
% Institute (http://www.blri.fr/)
% Co-authors from BLRI: Samuel Planton and Chotiga Pattadimalok
% Co-authors from fMRI platform: Ju... |
github | ilcb-crex/CREx_fMRI-master | CREx_fMRI_classical_PPI.m | .m | CREx_fMRI-master/gPPI/CREx_fMRI_classical_PPI.m | 24,191 | windows_1250 | 806cb3a7955d98ac518afc78ca4e4005 | function CREx_fMRI_classical_PPI
%==========================================================================
% CLASSICAL PSYCHO-PHYSIOLOGICAL INTERACTION (PPI)
%
% Script for Classical implementation of PPI using SPM12
% Author: Valérie Chanoine, Research Engineer at Brain and Language
% Co-authors from BLRI: Sa... |
github | ilcb-crex/CREx_fMRI-master | CREx_fMRI_classical_PPI_withOneVOI.m | .m | CREx_fMRI-master/gPPI/CREx_fMRI_classical_PPI_withOneVOI.m | 22,644 | windows_1250 | 7afb9a9f2a148a0d59ef7926b75521b1 | function CREx_fMRI_classical_PPI_withOneVOI
%==========================================================================
% CLASSICAL PSYCHO-PHYSIOLOGICAL INTERACTION (PPI)
%
% Script for Classical implementation of PPI using SPM12
% Author: Valérie Chanoine, Research Engineer at Brain and Language
% Co-authors fr... |
github | zhenglab/IQA-master | logGabors.m | .m | IQA-master/Codes/OriginalVersion/ILNIQE/logGabors.m | 4,151 | utf_8 | c97d34ea05e1a74d9d2b7c72a3fc2e67 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function filter = logGabors(rows, cols,minWaveLength, sigmaOnf,mult,dThetaOnSigma)
nscale = 3; % Number of wavelet scales.
norient = 4; % Number of filter orientations.
thetaSigma = pi/norient/dThetaOnSig... |
github | zhenglab/IQA-master | MyPCA.m | .m | IQA-master/Codes/OriginalVersion/ILNIQE/MyPCA.m | 1,306 | utf_8 | 2667d26079cb21ea4400da22529d6637 | %this is my implementation of principle component analysis
%sampleData contains the sample data in each column
function [principleVectors, meanOfSampleData,projectionOfTrainingData] = MyPCA(sampleData, reservedRatio)
principleVectors = [];
meanOfSampleData = mean(sampleData,2);
meanMatrix = repmat(meanOfS... |
github | zhenglab/IQA-master | CPBD_compute.m | .m | IQA-master/Codes/OriginalVersion/CPBDM/CPBD_compute.m | 11,407 | utf_8 | 570cfd3b687fddc29567d396a45e1742 | %=====================================================================
% File: CPBD_compute.m
% Original code written by Niranjan D. Narvekar
% IVU Lab (http://ivulab.asu.edu)
% Last Revised: October 2009 by Niranjan D. Narvekar
%=====================================================================
% Copyright Notice... |
github | zhenglab/IQA-master | evaluate_metric_performance.m | .m | IQA-master/Codes/OriginalVersion/CPBDM/evaluate_metric_performance.m | 4,236 | utf_8 | 5ad9315dfedb1d1f7410e8060563d0d6 | %=====================================================================
% File: evaluate_metric_performance.m
% Original code written by Rony Ferzli, IVU Lab (http://ivulab.asu.edu)
% Last Revised: October 2009 by Niranjan D. Narvekar
%=====================================================================
% Copyright No... |
github | zhenglab/IQA-master | spear.m | .m | IQA-master/Codes/OriginalVersion/CPBDM/spear.m | 2,407 | utf_8 | bac11bf4ca0fb2f488353ded24a04655 | %======================================================================
% File: spear.m
%
%======================================================================
function [r,t,p]=spear(x,y)
%Syntax: [r,t,p]=spear(x,y)
%__________________________
%
% Spearman's rank correlation coefficient.
%
% r is the Spearman's r... |
github | zhenglab/IQA-master | evaluate_metric_performance.m | .m | IQA-master/Codes/OriginalVersion/JNBM/JNBM_Release_v1.0/evaluate_metric_performance.m | 3,902 | utf_8 | a106c754a0ee3d49756875ca9afdd3be | %=====================================================================
% File: evaluate_metric_performance.m
% Original code written by Rony Ferzli, IVU Lab (http://ivulab.asu.edu)
% Last Revised: September 2009 by Lina Karam
%=====================================================================
% Copyright Notice:
% ... |
github | zhenglab/IQA-master | spear.m | .m | IQA-master/Codes/OriginalVersion/JNBM/JNBM_Release_v1.0/spear.m | 2,407 | utf_8 | bac11bf4ca0fb2f488353ded24a04655 | %======================================================================
% File: spear.m
%
%======================================================================
function [r,t,p]=spear(x,y)
%Syntax: [r,t,p]=spear(x,y)
%__________________________
%
% Spearman's rank correlation coefficient.
%
% r is the Spearman's r... |
github | MikeyGBG/BETR--master | initializeTracks.m | .m | BETR--master/tracking/initializeTracks.m | 353 | utf_8 | 374029563e7207622225ce318402bd69 | %% Tracking the image
function tracks = initializeTracks()
% create an empty array of tracks
tracks = struct(...
'id', {}, ...
'bbox', {}, ...
'kalmanFilter', {}, ...
'age', {}, ...
'totalVisibleCount', {}, ...
'consecutiv... |
github | litoeknee/mxnet-master | parse_json.m | .m | mxnet-master/matlab/+mxnet/private/parse_json.m | 19,095 | utf_8 | 2d934e0eae2779e69f5c3883b8f89963 | function data = parse_json(fname,varargin)
%PARSE_JSON parse a JSON (JavaScript Object Notation) file or string
%
% Based on jsonlab (https://github.com/fangq/jsonlab) created by Qianqian Fang. Jsonlab is lisonced under BSD or GPL v3.
global pos inStr len esc index_esc len_esc isoct arraytoken
if(regexp(fname,'^\s*(... |
github | sinbag/EmpiricalErrorAnalysis-master | CollectConvData.m | .m | EmpiricalErrorAnalysis-master/matlab/CollectConvData.m | 1,648 | utf_8 | 74b44378586c2322c01bec038eb3b0f9 | function out = ColectConvData (ns, nr, ofile, binfile, sstructs, istructs, atype)
nsamps = num2str(ns) ;
nreps = num2str(nr) ;
delete(ofile);
nstypes = length(sstructs) ;
nitypes = length(istructs) ;
for i=1:nstypes
stype = sstructs(i).stype ;
sarg = sstructs(i).sarg ;
dispstr = ['Collecting data using ... |
github | Prof-Lu-Cewu/Visual-Relationship-Detection-master | top_recall_Relationship.m | .m | Visual-Relationship-Detection-master/evaluation/top_recall_Relationship.m | 3,923 | utf_8 | d7f4f28fe2b662a09488f28405075eb9 | % this code is revised based on ILSVRC 2013 (http://www.image-net.org/challenges/LSVRC/2013/)
function top_recall = top_recall_Relationship(Nre, tuple_confs_cell, tuple_labels_cell, sub_bboxes_cell, obj_bboxes_cell)
load('gt.mat','gt_tuple_label','gt_obj_bboxes','gt_sub_bboxes');
%num_imgs = length(gt_tuple... |
github | Prof-Lu-Cewu/Visual-Relationship-Detection-master | zeroShot_top_recall_Relationship.m | .m | Visual-Relationship-Detection-master/evaluation/zeroShot_top_recall_Relationship.m | 4,107 | utf_8 | def66041071ab92e3e32956e78c31fae | % this code is revised based on ILSVRC 2013 (http://www.image-net.org/challenges/LSVRC/2013/)
function zeroShot = zeroShot_top_recall_Relationship(Nre, tuple_confs_cell, tuple_labels_cell, sub_bboxes_cell, obj_bboxes_cell)
load('gt.mat','gt_tuple_label','gt_obj_bboxes','gt_sub_bboxes');
load('zeroShot.mat','zer... |
github | Prof-Lu-Cewu/Visual-Relationship-Detection-master | top_recall_Phrase.m | .m | Visual-Relationship-Detection-master/evaluation/top_recall_Phrase.m | 3,750 | utf_8 | 5bc5b50f95f90a8b72f34a73469e5819 | % this code is revised based on ILSVRC 2013 (http://www.image-net.org/challenges/LSVRC/2013/)
function top_recall = top_recall_Phrase(Nre, tuple_confs_cell, tuple_labels_cell, sub_bboxes_cell, obj_bboxes_cell)
load('gt.mat','gt_tuple_label','gt_obj_bboxes','gt_sub_bboxes');
%num_imgs = length(gt_tuple_label);... |
github | Prof-Lu-Cewu/Visual-Relationship-Detection-master | zeroShot_top_recall_Phrase.m | .m | Visual-Relationship-Detection-master/evaluation/zeroShot_top_recall_Phrase.m | 3,928 | utf_8 | 68a4eb5ac5e72043b92e95847cfbfaab | % this code is revised based on ILSVRC 2013 (http://www.image-net.org/challenges/LSVRC/2013/)
function zeroShot = zeroShot_top_recall_Phrase(Nre, tuple_confs_cell, tuple_labels_cell, sub_bboxes_cell, obj_bboxes_cell)
load('gt.mat','gt_tuple_label','gt_obj_bboxes','gt_sub_bboxes');
load('zeroShot.mat','zeroShot'... |
github | lucasplus/MABDIwriting-master | f_Plane.m | .m | MABDIwriting-master/proposal/Figures/Adaptive Mesh Figure/f_Plane.m | 713 | utf_8 | 0c8b587c4585c4e4c1a091faade562e2 | % function to find coefficients of a plane from a set of points
% z = XCoeff * x + YCoeff * y + CCoeff
%
% N - normal of plane
% C - coefficents of plane
%
function [N C] = f_Plane(Pts)
Xcolv = Pts(:,1); % Make X a column vector
Ycolv = Pts(:,2); % Make Y a column vector
Zcolv = Pts(:,3); % Make Z a column vector
Cons... |
github | lucasplus/MABDIwriting-master | f_MSplane.m | .m | MABDIwriting-master/proposal/Figures/Adaptive Mesh Figure/f_MSplane.m | 524 | utf_8 | fcae763a950704bf60b680495b2decc0 | % function to make tikz string to draw plane
%
% inputs:
% x,y,z - columns of x,y,z points
% color - string specifying color
% ouput:
% S - string of tikz instructions
%
function S = f_MSplane(x,y,z,color)
pts = [x y z];
S = sprintf('\\\\filldraw[fill opacity = .1,fill=%s] ',color);
for i = 1:length(x);
if i==1... |
github | lucasplus/MABDIwriting-master | f_FindN.m | .m | MABDIwriting-master/proposal/Figures/Adaptive Mesh Figure/f_FindN.m | 489 | utf_8 | 8930e4aa49f06447139593c22f519bd6 | % function to find the neighbors of a given vertice
%
% input:
% index - index in rp of central point
% t - 3xN connectivity of triangles
% rp - 3xN list of vertices
%
% output:
% conN - 3xM list of neighbors
%
function conN = f_FindN(index,t,rp)
% find the edges connected to the choosen node
[nI,nJ] = find(t==ind... |
github | lucasplus/MABDIwriting-master | f_Q.m | .m | MABDIwriting-master/proposal/Figures/Adaptive Mesh Figure/f_Q.m | 134 | utf_8 | 5fad57f2300aa5d5809b02392ef4e85d | % function to create quadric from the normal
%
function Q = f_Q(n,w)
n = n / norm(n);
d = n(:)'*w(:);
nt = [n(:); -d];
Q = nt*nt'; |
github | fdsa1860/GramRiemannian-master | drawskt.m | .m | GramRiemannian-master/skeleton_data/MSRAction3D/real_world_coordinates/drawskt.m | 1,142 | utf_8 | 39ba4c3f206fe79351b2d3ba8f183a80 | %USAGE: drawskt(1,3,1,4,1,2) --- show actions 1,2,3 performed by subjects 1,2,3,4 with instances 1 and 2.
function drawskt(a1,a2,s1,s2,e1,e2)
J=[20 1 2 1 8 10 2 9 11 3 4 7 7 5 6 14 15 16 17;
3 3 3 8 10 12 9 11 13 4 ... |
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