1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92
|
%% Reset everything
clear all;
clc;
close all;
addpath('helpers');
rng shuffle
%% Configure the benchmark
% noncentral case
cam_number = 4;
% Getting 10 points, and testing all algorithms with the respective number of points
pt_per_cam = 20;
% outlier test, so constant noise
noise = 0.5;
% repeat 100 tests per outlier-ratio
iterations = 50;
% The algorithms we want to test
algorithms = [ 0; 1; 2 ];
% The name of the algorithms in the final plots
names = { '6pt'; 'ge (8pt)'; '17pt'};
% The main experiment parameters
min_outlier_fraction = 0.05;
max_outlier_fraction = 0.45;
outlier_fraction_step = 0.05;
%% Run the benchmark
%prepare the overall result arrays
number_outlier_fraction_levels = round((max_outlier_fraction - min_outlier_fraction) / outlier_fraction_step + 1);
num_algorithms = size(algorithms,1);
%Run the experiment
for n=1:number_outlier_fraction_levels
outlier_fraction = (n - 1) * outlier_fraction_step + min_outlier_fraction;
display(['Analyzing outlier fraction level: ' num2str(outlier_fraction)])
clear number_iterations
clear execution_times
counter = 0;
temp_file_name1 = ['number_iterations_' num2str(outlier_fraction) '.mat'];
temp_file_name2 = ['execution_times_' num2str(outlier_fraction) '.mat'];
if exist(temp_file_name1,'file') > 0
display(['number_iterations_' num2str(outlier_fraction) '.mat exists already'])
load(temp_file_name1)
load(temp_file_name2)
startingIteration = size(number_iterations,2) + 1;
display(['starting at ' num2str(startingIteration)])
else
startingIteration = 1;
end
if startingIteration <= iterations
for i=startingIteration:iterations
% generate experiment
[v1,v2,cam_offsets,t,R] = createMulti2D2DOmniExperiment(pt_per_cam,cam_number,noise,outlier_fraction);
for a=1:num_algorithms
if strcmp(names{a,1},'6pt') && outlier_fraction > 0.25
Out = zeros(4,5);
time = 10000000.0;
else
tic
Out = opengv_experimental1( v1{1,1}, v1{2,1}, v1{3,1}, v1{4,1}, v2{1,1}, v2{2,1}, v2{3,1}, v2{4,1}, cam_offsets, algorithms(a,1) );
time = toc;
end
number_iterations(a,i) = Out(1,5);
execution_times(a,i) = time;
end
save(temp_file_name1,'number_iterations');
save(temp_file_name2,'execution_times');
counter = counter + 1;
if counter == 1
counter = 0;
display(['Iteration ' num2str(i) ' of ' num2str(iterations) '(outlier_fraction level ' num2str(outlier_fraction) ')']);
end
end
end
end
|