test_oper.m

Standard model object recognition matlab code

function test_oper

% FUNCTION test_oper
% 
% Test the operation routines (comp_get_next_layer.m) in the codes.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 1D function
x_range = [0:0.01:1];
x1 = zeros(length(x_range), 1, 1);
x1(:,1,1) = x_range;

f = [];
f = setfield(f, 'f1_s1', 0.5);
f = setfield(f, 'f2_s1', 1);
f = setfield(f, 'i1_s1', [1 0]);
f = setfield(f, 'i2_s1', [1 0]);
f = setfield(f, 'i3_s1', [1 0]);
f = setfield(f, 'size_s1', [1 1 1 1]);
f = setfield(f, 'shift_s1', 1);
yg = comp_get_next_layer (x1, f, 'gaussf');
y = comp_get_next_layer (x1, f, 'normdp');

subplot(2,1,1);
plot(x_range, yg.s1)
subplot(2,1,2);
plot(x_range, y.s1)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 2D function
x_range  = [0:0.01:1];
%x_range = [0:0.1:1];
[x1,x2]  = ndgrid(x_range);
x        = ones([size(x1) 2]);
x(:,:,1) = x1;
x(:,:,2) = x2;

f = [];
f = setfield(f, 'f1_s1', [0.5 0.3]');
f = setfield(f, 'f2_s1', [1   1  ]');
f = setfield(f, 'i1_s1', [1 1 0]');
f = setfield(f, 'i2_s1', [1 1 0]');
f = setfield(f, 'i3_s1', [1 2 0]');
f = setfield(f, 'size_s1', [1 1 2 1]);
f = setfield(f, 'shift_s1', 1);
yg = comp_get_next_layer (x, f, 'gaussf');
y  = comp_get_next_layer (x, f, 'normdp');

clim = [0 1];
subplot(3,1,1); imagesc(x_range, x_range, yg.s1',clim);
axis xy square;
title(num2str(max(max(yg.s1))));
subplot(3,1,2); imagesc(x_range, x_range, y.s1',clim);
axis xy square;
title(num2str(max(max(y.s1))));

%y_corr = y.s1/0.5;
y_corr = y.s1;
aa = 1/var(y_corr(find(y_corr>0.75)));
bb = mean(y_corr(find(y_corr>0.75)));
aa = 1/std(y_corr(:));
bb = mean(y_corr(:));
bb = max(y_corr(:));
y_corr = 1./(1+exp(-aa*(y_corr-bb)));
subplot(3,1,3); imagesc(x_range, x_range, y_corr',clim);
axis xy square;
title(num2str(max(max(y.s1))));

%plot(x_range, y.s1)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% N-D function

d        = 10;
num_samp = 1000;
w1       = rand(d,1);
w2       = ones(d,1);
x        = rand(num_samp,1,d);

f = [];
f = setfield(f, 'f1_s1', w1);
f = setfield(f, 'f2_s1', w2);
f = setfield(f, 'i1_s1', [ones(d,1); 0]);
f = setfield(f, 'i2_s1', [ones(d,1); 0]);
f = setfield(f, 'i3_s1', [1:d 0]');
f = setfield(f, 'size_s1', [1 1 d 1]);
f = setfield(f, 'shift_s1', 1);

yg = comp_get_next_layer (x, f, 'gaussf');
y  = comp_get_next_layer (x, f, 'normdp');

subplot(3,1,1);
y_corr = y.s1;
plot(yg.s1, y_corr, '.'); axis([0 1 0 1], 'square');
xlabel('Gauss');
ylabel('NSP');

subplot(3,1,2);
aa     = 1/std(y_corr(:));
bb     = mean(y_corr(:));
bb     = 0.49;

plot([0:0.01:1], 1./(1+exp(-aa*([0:0.01:1]-bb))));
axis square;

subplot(3,1,3);
y_corr = 1./(1+exp(-aa*(y_corr-bb)));
plot(yg.s1, y_corr, '.'); axis([0 1 0 1], 'square');

x_ref = 10; % some random points
dist  = sum((x-repmat(x(x_ref,:,:), [num_samp, 1 1])).^2,3);
r_dif = y_corr-y_corr(x_ref);
rg_dif = yg.s1-yg.s1(x_ref);

subplot(3,1,1);
plot(dist, r_dif, '.');
subplot(3,1,2);
plot(dist, rg_dif, '.');
subplot(3,1,3);
plot(r_dif, rg_dif, '.');

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 2D plus N-D features

d = 10; % 10 features
x = rand(10,10,d);
f_4D = [];
f_4D(:,:,:,1) = x(2+[1:3],3+[1:3],:);
f_4D(:,:,:,2) = x(4+[1:3],3+[1:3],:);
f_4D(:,:,:,3) = x(1+[1:3],1+[1:3],:);
f = [];
f = filt_package(f,f_4D,ones(size(f_4D)),1,'s1');
y = comp_get_next_layer (x, f, 'gaussf');