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move pyr_segmentation to IplImage

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This commit is contained in:
ser1zw 2013-01-20 02:53:24 +09:00
parent 6331e8dc53
commit 55aab3538a
6 changed files with 72 additions and 77 deletions
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37
ext/opencv/cvmat.cpp
View file

@ -381,7 +381,6 @@ void define_ruby_class()
rb_define_method(rb_klass, "draw_contours!", RUBY_METHOD_FUNC(rb_draw_contours_bang), -1);
rb_define_method(rb_klass, "draw_chessboard_corners", RUBY_METHOD_FUNC(rb_draw_chessboard_corners), 3);
rb_define_method(rb_klass, "draw_chessboard_corners!", RUBY_METHOD_FUNC(rb_draw_chessboard_corners_bang), 3);
rb_define_method(rb_klass, "pyr_segmentation", RUBY_METHOD_FUNC(rb_pyr_segmentation), 3);
rb_define_method(rb_klass, "pyr_mean_shift_filtering", RUBY_METHOD_FUNC(rb_pyr_mean_shift_filtering), -1);
rb_define_method(rb_klass, "watershed", RUBY_METHOD_FUNC(rb_watershed), 1);
@ -4959,42 +4958,6 @@ rb_draw_chessboard_corners_bang(VALUE self, VALUE pattern_size, VALUE corners, V
return self;
}
/*
* call-seq:
* pyr_segmentation(<i>level, threshold1, threshold2</i>) -> [cvmat, cvseq(include cvconnectedcomp)]
*
* Does image segmentation by pyramids.
* The pyramid builds up to the level <i>level<i>.
* The links between any pixel a on <i>level<i>i and
* its candidate father pixel b on the adjacent level are established if
* p(c(a),c(b)) < threshold1. After the connected components are defined, they are joined into several clusters. Any two segments A and B belong to the same cluster, if
* p(c(A),c(B)) < threshold2. The input image has only one channel, then
* p(c^2,c^2)=|c^2-c^2|. If the input image has three channels (red, green and blue), then
* p(c^2,c^2)=0,3*(c^2 r-c^2 r)+0.59*(c^2 g-c^2 g)+0,11*(c^2 b-c^2 b) . There may be more than one connected component per a cluster.
*
* Return segmented image and sequence of connected components.
* <b>support single-channel or 3-channel 8bit unsigned image only</b>
*/
VALUE
rb_pyr_segmentation(VALUE self, VALUE level, VALUE threshold1, VALUE threshold2)
{
IplImage* self_ptr = IPLIMAGE(self);
CvSeq *comp = NULL;
VALUE storage = cCvMemStorage::new_object();
VALUE dest = Qnil;
try {
dest = cIplImage::new_object(cvGetSize(self_ptr), cvGetElemType(self_ptr));
cvPyrSegmentation(self_ptr, IPLIMAGE(dest), CVMEMSTORAGE(storage), &comp,
NUM2INT(level), NUM2DBL(threshold1), NUM2DBL(threshold2));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
if (!comp)
comp = cvCreateSeq(CV_SEQ_CONNECTED_COMP, sizeof(CvSeq), sizeof(CvConnectedComp), CVMEMSTORAGE(storage));
return rb_ary_new3(2, dest, cCvSeq::new_sequence(cCvSeq::rb_class(), comp, cCvConnectedComp::rb_class(), storage));
}
/*
* call-seq:
* pyr_mean_shift_filtering(<i>sp, sr[,max_level = 1][termcrit = CvTermCriteria.new(5,1)]</i>) -> cvmat

1
ext/opencv/cvmat.h
View file

@ -204,7 +204,6 @@ VALUE rb_draw_contours(int argc, VALUE *argv, VALUE self);
VALUE rb_draw_contours_bang(int argc, VALUE *argv, VALUE self);
VALUE rb_draw_chessboard_corners(VALUE self, VALUE pattern_size, VALUE corners, VALUE pattern_was_found);
VALUE rb_draw_chessboard_corners_bang(VALUE self, VALUE pattern_size, VALUE corners, VALUE pattern_was_found);
VALUE rb_pyr_segmentation(VALUE self, VALUE level, VALUE threshold1, VALUE threshold2);
VALUE rb_pyr_mean_shift_filtering(int argc, VALUE *argv, VALUE self);
VALUE rb_watershed(VALUE self, VALUE markers);
VALUE rb_moments(int argc, VALUE *argv, VALUE self);

38
ext/opencv/iplimage.cpp
View file

@ -60,7 +60,7 @@ define_ruby_class()
rb_define_method(rb_klass, "set_coi", RUBY_METHOD_FUNC(rb_set_coi), 1);
rb_define_alias(rb_klass, "coi=", "set_coi");
rb_define_method(rb_klass, "reset_coi", RUBY_METHOD_FUNC(rb_reset_coi), 0);
rb_define_method(rb_klass, "pyr_segmentation", RUBY_METHOD_FUNC(rb_pyr_segmentation), 3);
rb_define_method(rb_klass, "smoothness", RUBY_METHOD_FUNC(rb_smoothness), -1);
rb_define_singleton_method(rb_klass, "decode_image", RUBY_METHOD_FUNC(rb_decode_image), -1);
@ -591,6 +591,42 @@ high_pass_range(const IplImage *pImage, float lostPercentage, int &outLow, int &
outLow = (int)(lostPercentage * outHigh);
}
/*
* call-seq:
* pyr_segmentation(<i>level, threshold1, threshold2</i>) -> [iplimage, cvseq(include cvconnectedcomp)]
*
* Does image segmentation by pyramids.
* The pyramid builds up to the level <i>level<i>.
* The links between any pixel a on <i>level<i>i and
* its candidate father pixel b on the adjacent level are established if
* p(c(a),c(b)) < threshold1. After the connected components are defined, they are joined into several clusters. Any two segments A and B belong to the same cluster, if
* p(c(A),c(B)) < threshold2. The input image has only one channel, then
* p(c^2,c^2)=|c^2-c^2|. If the input image has three channels (red, green and blue), then
* p(c^2,c^2)=0,3*(c^2 r-c^2 r)+0.59*(c^2 g-c^2 g)+0,11*(c^2 b-c^2 b) . There may be more than one connected component per a cluster.
*
* Return segmented image and sequence of connected components.
* <b>support single-channel or 3-channel 8bit unsigned image only</b>
*/
VALUE
rb_pyr_segmentation(VALUE self, VALUE level, VALUE threshold1, VALUE threshold2)
{
IplImage* self_ptr = IPLIMAGE(self);
CvSeq *comp = NULL;
VALUE storage = cCvMemStorage::new_object();
VALUE dest = Qnil;
try {
dest = cIplImage::new_object(cvGetSize(self_ptr), cvGetElemType(self_ptr));
cvPyrSegmentation(self_ptr, IPLIMAGE(dest), CVMEMSTORAGE(storage), &comp,
NUM2INT(level), NUM2DBL(threshold1), NUM2DBL(threshold2));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
if (!comp) {
comp = cvCreateSeq(CV_SEQ_CONNECTED_COMP, sizeof(CvSeq), sizeof(CvConnectedComp), CVMEMSTORAGE(storage));
}
return rb_ary_new3(2, dest, cCvSeq::new_sequence(cCvSeq::rb_class(), comp, cCvConnectedComp::rb_class(), storage));
}
VALUE
new_object(int width, int height, int type)

2
ext/opencv/iplimage.h
View file

@ -38,6 +38,8 @@ VALUE rb_get_coi(VALUE self);
VALUE rb_set_coi(VALUE self, VALUE coi);
VALUE rb_reset_coi(VALUE self);
VALUE rb_pyr_segmentation(VALUE self, VALUE level, VALUE threshold1, VALUE threshold2);
VALUE rb_smoothness(int argc, VALUE *argv, VALUE self);
typedef enum { SMOOTH = 1, BLANK = 2, MESSY = 3 } Smoothness;
Smoothness compute_smoothness(const IplImage *pFourierImage, const double lowFreqRatio, const double blankDensity, const double messyDensity, const double highFreqRatio, double &outLowDensity, double &outHighDensity);

38
test/test_cvmat_imageprocessing.rb
View file

@ -1316,44 +1316,6 @@ class TestCvMat_imageprocessing < OpenCVTestCase
}
end
def test_pyr_segmentation
mat0 = CvMat.load(FILENAME_LENA256x256, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH)
mat1, seq1 = mat0.pyr_segmentation(4, 255, 50)
assert_equal('ebd9bad0bbc90b1d4a25289b7d59c958', hash_img(mat1))
assert_equal(5, seq1.total)
img0 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH)
img0.set_roi(CvRect.new(0, 0, 256, 512))
img2, seq2 = img0.pyr_segmentation(2, 255, 50)
assert_equal('963b26f51b14f175fbbf128e9b9e979f', hash_img(img2))
assert_equal(11, seq2.total)
assert_raise(CvStsAssert) {
img0.pyr_segmentation(-1, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(1000, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, -1, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, 255, -1)
}
assert_raise(TypeError) {
img0.pyr_segmentation(DUMMY_OBJ, 255, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, DUMMY_OBJ, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, 255, DUMMY_OBJ)
}
assert_raise(CvBadDepth) {
IplImage.new(10, 10, :cv32f, 2).pyr_segmentation(4, 255, 50)
}
end
def test_pyr_mean_shift_filtering
mat0 = CvMat.load(FILENAME_LENA256x256, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH)
mat1 = mat0.pyr_mean_shift_filtering(30, 30)

33
test/test_iplimage.rb
View file

@ -198,6 +198,39 @@ class TestIplImage < OpenCVTestCase
should_classify_images_as image, :blank
end
end
def test_pyr_segmentation
img0 = IplImage.load(FILENAME_CAT, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH)
img0.set_roi(CvRect.new(0, 0, 256, 512))
img1, seq1 = img0.pyr_segmentation(2, 255, 50)
assert_equal('963b26f51b14f175fbbf128e9b9e979f', hash_img(img1))
assert_equal(11, seq1.total)
assert_raise(CvStsAssert) {
img0.pyr_segmentation(-1, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(1000, 255, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, -1, 50)
}
assert_raise(CvStsAssert) {
img0.pyr_segmentation(4, 255, -1)
}
assert_raise(TypeError) {
img0.pyr_segmentation(DUMMY_OBJ, 255, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, DUMMY_OBJ, 50)
}
assert_raise(TypeError) {
img0.pyr_segmentation(4, 255, DUMMY_OBJ)
}
assert_raise(CvBadDepth) {
IplImage.new(10, 10, :cv32f, 2).pyr_segmentation(4, 255, 50)
}
end
end