Open Source Computer Vision Library https://opencv.org/
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% Matlab binding test cases
% Uses Matlab's builtin testing framework
classdef OpenCVTest < matlab.unittest.TestCase
methods(Test)
% -------------------------------------------------------------------------
% EXCEPTIONS
% Check that errors and exceptions are thrown correctly
% -------------------------------------------------------------------------
% check that std exception is thrown
function stdException(testcase)
try
std_exception();
testcase.verifyFail();
catch
% TODO: Catch more specific exception
testcase.verifyTrue(true);
end
end
% check that OpenCV exceptions are correctly caught
function cvException(testcase)
try
cv_exception();
testcase.verifyFail();
catch
% TODO: Catch more specific exception
testcase.verifyTrue(true);
end
end
% check that all exceptions are caught
function allException(testcase)
try
exception();
testcase.verifyFail();
catch
% TODO: Catch more specific exception
testcase.verifyTrue(true);
end
end
% -------------------------------------------------------------------------
% SIZES AND FILLS
% Check that matrices are correctly filled and resized
% -------------------------------------------------------------------------
% check that a matrix is correctly filled with random numbers
function randomFill(testcase)
sz = [7 11];
mat = zeros(sz);
mat = cv.randn(mat, 0, 1);
testcase.verifyEqual(size(mat), sz, 'Matrix should not change size');
testcase.verifyNotEqual(mat, zeros(sz), 'Matrix should be nonzero');
end
function transpose(testcase)
m = randn(19, 81);
mt1 = transpose(m);
mt2 = cv.transpose(m);
testcase.verifyEqual(size(mt1), size(mt2), 'Matrix transposed to incorrect dimensionality');
testcase.verifyLessThan(norm(mt1 - mt2), 1e-8, 'Too much precision lost in tranposition');
end
% multiple return
function multipleReturn(testcase)
A = randn(10);
A = A'*A;
[V1, D1] = eig(A); D1 = diag(D1);
[~, D2, V2] = cv.eigen(A);
testcase.verifyLessThan(norm(V1 - V2), 1e-6, 'Too much precision lost in eigenvectors');
testcase.verifyLessThan(norm(D1 - D2), 1e-6, 'Too much precision lost in eigenvalues');
end
% complex output from SVD
function complexOutputSVD(testcase)
A = randn(10);
[V1, D1] = eig(A);
[~, D2, V2] = cv.eigen(A);
testcase.verifyTrue(~isreal(V2) && size(V2,3) == 1, 'Output should be complex');
testcase.verifyLessThan(norm(V1 - V2), 1e-6, 'Too much precision lost in eigenvectors');
end
% complex output from Fourier Transform
function complexOutputFFT(testcase)
A = randn(10);
F1 = fft2(A);
F2 = cv.dft(A, cv.DFT_COMPLEX_OUTPUT);
testcase.verifyTrue(~isreal(F2) && size(F2,3) == 1, 'Output should be complex');
testcase.verifyLessThan(norm(F1 - F2), 1e-6, 'Too much precision lost in eigenvectors');
end
% -------------------------------------------------------------------------
% TYPE CASTS
% Check that types are correctly cast
% -------------------------------------------------------------------------
% -------------------------------------------------------------------------
% PRECISION
% Check that basic operations are performed with sufficient precision
% -------------------------------------------------------------------------
% check that summing elements is within reasonable precision
function sumElements(testcase)
a = randn(5000);
b = sum(a(:));
c = cv.sum(a);
testcase.verifyLessThan(norm(b - c), 1e-8, 'Matrix reduction with insufficient precision');
end
% check that adding two matrices is within reasonable precision
function addPrecision(testcase)
a = randn(50);
b = randn(50);
c = a+b;
d = cv.add(a, b);
testcase.verifyLessThan(norm(c - d), 1e-8, 'Matrices are added with insufficient precision');
end
% check that performing gemm is within reasonable precision
function gemmPrecision(testcase)
a = randn(10, 50);
b = randn(50, 10);
c = randn(10, 10);
alpha = 2.71828;
gamma = 1.61803;
d = alpha*a*b + gamma*c;
e = cv.gemm(a, b, alpha, c, gamma);
testcase.verifyLessThan(norm(d - e), 1e-8, 'Matrices are multiplied with insufficient precision');
end
% -------------------------------------------------------------------------
% MISCELLANEOUS
% Miscellaneous tests
% -------------------------------------------------------------------------
% check that cv::waitKey waits for at least specified time
function waitKey(testcase)
tic();
cv.waitKey(500);
elapsed = toc();
testcase.verifyGreaterThan(elapsed, 0.5, 'Elapsed time should be at least 0.5 seconds');
end
% check that highgui window can be created and destroyed
function createAndDestroyWindow(testcase)
try
cv.namedWindow('test window');
catch
testcase.verifyFail('could not create window');
end
try
cv.destroyWindow('test window');
catch
testcase.verifyFail('could not destroy window');
end
testcase.verifyTrue(true);
end
end
end