Skip to content
This repository has been archived by the owner on Dec 3, 2021. It is now read-only.

Commit

Permalink
tested CvMat.compute_correspond_epilines
Browse files Browse the repository at this point in the history
  • Loading branch information
@ser1zw
ser1zw committed Apr 19, 2011
1 parent a3e1078 commit fc5a680
Show file tree
Hide file tree
Showing 2 changed files with 105 additions and 11 deletions.
18 changes: 10 additions & 8 deletions ext/opencv/cvmat.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -5185,16 +5185,18 @@ VALUE
rb_compute_correspond_epilines(VALUE klass, VALUE points, VALUE which_image, VALUE fundamental_matrix)
{
VALUE correspondent_lines;
CvSize size = cvGetSize(CVARR(points));
CvMat* points_ptr = CVMAT(points);
int n;
if(size.width <= 3 && size.height >= 7)
n = size.height;
else if(size.height <= 3 && size.width >= 7)
n = size.width;
if(points_ptr->cols <= 3 && points_ptr->rows >= 7)
n = points_ptr->rows;
else if(points_ptr->rows <= 3 && points_ptr->cols >= 7)
n = points_ptr->cols;
else
rb_raise(rb_eTypeError, "input points should 2xN, Nx2 or 3xN, Nx3 matrix(N >= 7).");
correspondent_lines = cCvMat::new_object(n, 3, CV_32F);
cvComputeCorrespondEpilines(CVMAT(points), FIX2INT(which_image), CVMAT(fundamental_matrix), CVMAT(correspondent_lines));
rb_raise(rb_eArgError, "input points should 2xN, Nx2 or 3xN, Nx3 matrix(N >= 7).");

correspondent_lines = cCvMat::new_object(n, 3, CV_MAT_DEPTH(points_ptr->type));
cvComputeCorrespondEpilines(points_ptr, FIX2INT(which_image), CVMAT(fundamental_matrix),
CVMAT(correspondent_lines));
return correspondent_lines;
}

Expand Down
98 changes: 95 additions & 3 deletions test/test_cvmat.rb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2121,7 +2121,7 @@ def test_find_fundamental_mat_lmeds

# default
[CvMat.find_fundamental_mat_lmeds(mat1, mat2, :with_status => false,
:maximum_distance => 1.0, :desirable_level => 0.99),
:maximum_distance => 1.0, :desirable_level => 0.99),
CvMat.find_fundamental_mat_lmeds(mat1, mat2)].each { |f_mat|
assert_equal(3, f_mat.rows)
assert_equal(3, f_mat.cols)
Expand Down Expand Up @@ -2271,7 +2271,7 @@ def test_find_fundamental_mat
}

[CvMat.find_fundamental_mat(mat1, mat2, CV_FM_RANSAC, :with_status => false,
:maximum_distance => 1.0, :desirable_level => 0.99),
:maximum_distance => 1.0, :desirable_level => 0.99),
CvMat.find_fundamental_mat(mat1, mat2, CV_FM_RANSAC)].each { |f_mat|
assert_equal(3, f_mat.rows)
assert_equal(3, f_mat.cols)
Expand Down Expand Up @@ -2317,7 +2317,7 @@ def test_find_fundamental_mat
}

[CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS, :with_status => false,
:maximum_distance => 1.0, :desirable_level => 0.99),
:maximum_distance => 1.0, :desirable_level => 0.99),
CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS)].each { |f_mat|
assert_equal(3, f_mat.rows)
assert_equal(3, f_mat.cols)
Expand Down Expand Up @@ -2348,5 +2348,97 @@ def test_find_fundamental_mat
assert_in_delta(val, status[i][0], 1.0e-5)
}
end

def test_compute_correspond_epilines
test_func = lambda { |mat1, mat2, f_mat_arr, num_points|
f_mat = CvMat.new(3, 3, CV_64F, 1)
f_mat_arr.each_with_index { |a, i|
f_mat[i] = CvScalar.new(a)
}

line = CvMat.compute_correspond_epilines(mat1, 1, f_mat)
assert_equal(num_points, line.rows)
assert_equal(3, line.cols)

expected = [[-0.221257, -0.975215, 6.03758],
[0.359337, -0.933208, -3.61419],
[0.958304, -0.28575, -15.0573],
[0.73415, -0.678987, -10.4037],
[0.0208539, -0.999783, 2.11625],
[0.284451, -0.958691, -2.31993],
[0.624647, -0.780907, -8.35208],
[0.618494, -0.785789, -8.23888],
[0.766694, -0.642012, -11.0298],
[0.700293, -0.713855, -9.76109]]

expected.size.times { |i|
assert_in_delta(expected[i][0], line[i, 0][0], 1.0e-3)
assert_in_delta(expected[i][1], line[i, 1][0], 1.0e-3)
assert_in_delta(expected[i][2], line[i, 2][0], 1.0e-3)
}

assert_raise(ArgumentError) {
m = CvMat.new(10, 10, CV_32F, 1)
CvMat.compute_correspond_epilines(m, 1, f_mat)
}
}

num_points = 10
# input points are Nx2 matrix
points1 =[[17, 175],
[370, 24],
[192, 456],
[614, 202],
[116, 111],
[305, 32],
[249, 268],
[464, 157],
[259, 333],
[460, 224]]

points2 = [[295, 28],
[584, 221],
[67, 172],
[400, 443],
[330, 9],
[480, 140],
[181, 140],
[350, 265],
[176, 193],
[333, 313]]

mat1 = CvMat.new(num_points, 2, CV_64F, 1)
mat2 = CvMat.new(num_points, 2, CV_64F, 1)
points1.flatten.each_with_index { |pt, i|
mat1[i] = CvScalar.new(pt)
}
points2.flatten.each_with_index { |pt, i|
mat2[i] = CvScalar.new(pt)
}

# pre computed f matrix from points1, points2
# f_mat = CvMat.find_fundamental_mat(mat1, mat2, CV_FM_LMEDS)
f_mat_arr = [0.000266883, 0.000140277, -0.0445223,
-0.00012592, 0.000245543, -0.108868,
-0.00407942, -0.00291097, 1]
test_func.call(mat1, mat2, f_mat_arr, num_points)

# input points are 2xN matrix
points1 = [[17, 370, 192, 614, 116, 305, 249, 464, 259, 460],
[175, 24, 456, 202, 111, 32, 268, 157, 333, 224]]

points2 = [[295, 584, 67, 400, 330, 480, 181, 350, 176, 333],
[28, 221, 172, 443, 9, 140, 140, 265, 193, 313]]

mat1 = CvMat.new(2, num_points, CV_64F, 1)
mat2 = CvMat.new(2, num_points, CV_64F, 1)
points1.flatten.each_with_index { |pt, i|
mat1[i] = CvScalar.new(pt)
}
points2.flatten.each_with_index { |pt, i|
mat2[i] = CvScalar.new(pt)
}
test_func.call(mat1, mat2, f_mat_arr, num_points)
end
end

0 comments on commit fc5a680

Please sign in to comment.