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change return values of CvMat#find_chessboard_corners

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Add pattern_was_found, which indicates whether the complete board was found or not.
This value will be used as an argument for CvMat#draw_chessboard_corners (to be implemented).
This commit is contained in:
ser1zw 2012-11-16 01:52:21 +09:00
parent 4ac425411d
commit f8d9ce4a24
2 changed files with 17 additions and 10 deletions
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11
ext/opencv/cvmat.cpp
View file

@ -3701,9 +3701,10 @@ rb_corner_harris(int argc, VALUE *argv, VALUE self)
/* /*
* call-seq: * call-seq:
* find_chessboard_corners(pattern_size, flag = CV_CALIB_CB_ADAPTIVE_THRESH) -> Array<CvPoint2D32f> * find_chessboard_corners(pattern_size, flag = CV_CALIB_CB_ADAPTIVE_THRESH) -> Array<Array<CvPoint2D32f>, Boolean>
* *
* Returns the positions of internal corners of the chessboard. * Returns an array which includes the positions of internal corners of the chessboard, and
* a parameter indicating whether the complete board was found or not.
* *
* pattern_size (CvSize) - Number of inner corners per a chessboard row and column. * pattern_size (CvSize) - Number of inner corners per a chessboard row and column.
* flags (Integer) - Various operation flags that can be zero or a combination of the following values * flags (Integer) - Various operation flags that can be zero or a combination of the following values
@ -3727,8 +3728,9 @@ rb_find_chessboard_corners(int argc, VALUE *argv, VALUE self)
CvSize pattern_size = VALUE_TO_CVSIZE(pattern_size_val); CvSize pattern_size = VALUE_TO_CVSIZE(pattern_size_val);
CvPoint2D32f* corners = ALLOCA_N(CvPoint2D32f, pattern_size.width * pattern_size.height); CvPoint2D32f* corners = ALLOCA_N(CvPoint2D32f, pattern_size.width * pattern_size.height);
int num_found_corners = 0; int num_found_corners = 0;
int pattern_was_found = 0;
try { try {
cvFindChessboardCorners(CVARR(self), pattern_size, corners, &num_found_corners, flag); pattern_was_found = cvFindChessboardCorners(CVARR(self), pattern_size, corners, &num_found_corners, flag);
} }
catch (cv::Exception& e) { catch (cv::Exception& e) {
raise_cverror(e); raise_cverror(e);
@ -3739,7 +3741,8 @@ rb_find_chessboard_corners(int argc, VALUE *argv, VALUE self)
rb_ary_store(found_corners, i, cCvPoint2D32f::new_object(corners[i])); rb_ary_store(found_corners, i, cCvPoint2D32f::new_object(corners[i]));
} }
return found_corners; VALUE found = (pattern_was_found > 0) ? Qtrue : Qfalse;
return rb_assoc_new(found_corners, found);
} }
/* /*

16
test/test_cvmat_imageprocessing.rb
View file

@ -188,11 +188,11 @@ class TestCvMat_imageprocessing < OpenCVTestCase
def test_find_chessboard_corners def test_find_chessboard_corners
mat = CvMat.load(FILENAME_CHESSBOARD, CV_LOAD_IMAGE_GRAYSCALE) mat = CvMat.load(FILENAME_CHESSBOARD, CV_LOAD_IMAGE_GRAYSCALE)
pattern_size = CvSize.new(4, 4) pattern_size = CvSize.new(4, 4)
corners1 = mat.find_chessboard_corners(pattern_size) corners1, found1 = mat.find_chessboard_corners(pattern_size)
corners2 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_ADAPTIVE_THRESH) corners2, found2 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_ADAPTIVE_THRESH)
corners3 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_NORMALIZE_IMAGE) corners3, found3 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_NORMALIZE_IMAGE)
corners4 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_FILTER_QUADS) corners4, found4 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_FILTER_QUADS)
corners5 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_FAST_CHECK) corners5, found5 = mat.find_chessboard_corners(pattern_size, CV_CALIB_CB_FAST_CHECK)
expected = [[39, 39], [79, 39], [119, 39], [159, 39], [39, 79], [79, 79], expected = [[39, 39], [79, 39], [119, 39], [159, 39], [39, 79], [79, 79],
[119, 79], [159, 78], [38, 119], [79, 119], [119, 119], [158, 118], [119, 79], [159, 78], [38, 119], [79, 119], [119, 119], [158, 118],
@ -204,6 +204,9 @@ class TestCvMat_imageprocessing < OpenCVTestCase
assert_in_delta(e[1], a.y, 3.0) assert_in_delta(e[1], a.y, 3.0)
} }
} }
[found1, found2, found3, found4, found5].each { |found|
assert(found)
}
assert_raise(TypeError) { assert_raise(TypeError) {
mat.find_chessboard_corners(DUMMY_OBJ) mat.find_chessboard_corners(DUMMY_OBJ)
@ -216,7 +219,7 @@ class TestCvMat_imageprocessing < OpenCVTestCase
def test_find_corner_sub_pix def test_find_corner_sub_pix
mat = CvMat.load(FILENAME_CHESSBOARD, CV_LOAD_IMAGE_GRAYSCALE) mat = CvMat.load(FILENAME_CHESSBOARD, CV_LOAD_IMAGE_GRAYSCALE)
pattern_size = CvSize.new(4, 4) pattern_size = CvSize.new(4, 4)
corners = mat.find_chessboard_corners(pattern_size) corners, found = mat.find_chessboard_corners(pattern_size)
expected = [[39, 39], [79, 39], [119, 39], [159, 39], [39, 79], [79, 79], expected = [[39, 39], [79, 39], [119, 39], [159, 39], [39, 79], [79, 79],
[119, 79], [159, 78], [38, 119], [79, 119], [119, 119], [158, 118], [119, 79], [159, 78], [38, 119], [79, 119], [119, 119], [158, 118],
[39, 159], [79, 159], [119, 159], [159, 159]] [39, 159], [79, 159], [119, 159], [159, 159]]
@ -224,6 +227,7 @@ class TestCvMat_imageprocessing < OpenCVTestCase
refined_corners = mat.find_corner_sub_pix(corners, CvSize.new(3, 3), CvSize.new(-1, -1), refined_corners = mat.find_corner_sub_pix(corners, CvSize.new(3, 3), CvSize.new(-1, -1),
CvTermCriteria.new(20, 0.03)); CvTermCriteria.new(20, 0.03));
assert_equal(expected.size, refined_corners.size) assert_equal(expected.size, refined_corners.size)
assert(found)
expected.zip(refined_corners).each { |e, a| expected.zip(refined_corners).each { |e, a|
assert_in_delta(e[0], a.x, 3.0) assert_in_delta(e[0], a.x, 3.0)
assert_in_delta(e[1], a.y, 3.0) assert_in_delta(e[1], a.y, 3.0)