v01

thirdparty/opengv/matlab/benchmark_relative_pose_execution_times.m

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+%% Reset everything
+
+clear all;
+clc;
+close all;
+addpath('helpers');
+
+%% Configure the benchmark
+
+% central case -> only one camera
+cam_number = 1;
+% Getting 10 points, and testing all algorithms with the respective number of points
+pt_number = 10;
+% noise test, so no outliers
+outlier_fraction = 0.0;
+% repeat 1000 iterations
+iterations = 1000;
+
+% The algorithms we want to test
+algorithms = { 'twopt';'fivept_stewenius'; 'fivept_nister'; 'fivept_kneip'; 'sevenpt'; 'eightpt'; 'eigensolver' };
+% This defines the number of points used for every algorithm
+indices = { [1,2]; [1, 2, 3, 4, 5]; [1, 2, 3, 4, 5];  [1, 2, 3, 4, 5]; [1, 2, 3, 4, 5, 6, 7]; [1, 2, 3, 4, 5, 6, 7, 8]; [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] };
+% The name of the algorithms in the final plots
+names = { '2pt';'5pt (Stewenius)'; '5pt (Nister)'; '5pt (Kneip)'; '7pt'; '8pt'; 'eigensolver' };
+
+% noise in this experiment
+noise = 1.0;
+
+%% Run the benchmark
+
+%prepare the overall result arrays
+num_algorithms = size(algorithms,1);
+execution_times = zeros(num_algorithms,iterations);
+counter = 0;
+    
+for i=1:iterations
+        
+    % generate experiment        
+    [v1,v2,t,R] = create2D2DExperiment(pt_number,cam_number,noise,outlier_fraction);
+    [t_perturbed,R_perturbed] = perturb(t,R,0.01);
+    T_perturbed = [R_perturbed,t_perturbed];
+
+    for a=1:num_algorithms
+        tic
+        Out = opengv_donotuse(algorithms{a},indices{a},v1,v2,T_perturbed);
+        execution_times(a,i) = toc/20.0;
+    end
+
+    counter = counter + 1;
+    if counter == 100
+        counter = 0;
+        display(['Iteration ' num2str(i) ' of ' num2str(iterations)]);
+    end
+end
+
+%% Plot the results
+
+hist(execution_times')
+legend(names,'Location','NorthWest')
+xlabel('execution times [s]')
+grid on
+
+mean(execution_times')