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https://github.com/ruby-opencv/ruby-opencv
synced 2023-03-27 23:22:12 -04:00
use CV_INTER_* constants instead of INTERPOLATION_METHOD table
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ser1zw
parent
08348ff8d3
commit
cbeeb1caee
3 changed files with 30 additions and 35 deletions
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@ -3915,14 +3915,14 @@ rb_quadrangle_sub_pix(int argc, VALUE *argv, VALUE self)
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*
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* Resize image.
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* <i>interpolation</i> is interpolation method:
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* * :nn
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* * CV_INTER_NN
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* nearest-neighbor interpolation.
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* * :linear
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* * CV_INTER_LINEAR
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* bilinear interpolation (used by default)
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* * :area
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* * CV_INTER_AREA
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* resampling using pixel area relation. It is preferred method for image decimation that give moire-free results.
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* In case of zooming it is similar to NN method.
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* * :cubic
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* * CV_INTER_CUBIC
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* bicubic interpolation.
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* Return <i>self</i> resized image that it fits exactly to <i>size</i>. If ROI is set, the method consideres the ROI as supported as usual.
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*/
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@ -3932,8 +3932,10 @@ rb_resize(int argc, VALUE *argv, VALUE self)
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VALUE size, interpolation;
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rb_scan_args(argc, argv, "11", &size, &interpolation);
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VALUE dest = new_mat_kind_object(VALUE_TO_CVSIZE(size), self);
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int method = NIL_P(interpolation) ? CV_INTER_LINEAR : NUM2INT(interpolation);
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try {
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cvResize(CVARR(self), CVARR(dest), CVMETHOD("INTERPOLATION_METHOD", interpolation, CV_INTER_LINEAR));
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cvResize(CVARR(self), CVARR(dest), method);
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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@ -3943,7 +3945,7 @@ rb_resize(int argc, VALUE *argv, VALUE self)
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/*
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* call-seq:
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* warp_affine(<i>map_matrix[,interpolation = :linear][,option = :fill_outliers][,fillval = 0]</i>) -> cvmat
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* warp_affine(<i>map_matrix[,interpolation = CV_INTER_LINEAR][,option = :fill_outliers][,fillval = 0]</i>) -> cvmat
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*
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* Applies affine transformation to the image.
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*/
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@ -3955,11 +3957,12 @@ rb_warp_affine(int argc, VALUE *argv, VALUE self)
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if (rb_scan_args(argc, argv, "13", &map_matrix, &interpolation, &option, &fill_value) < 4)
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fill_value = INT2FIX(0);
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CvArr* self_ptr = CVARR(self);
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int method = NIL_P(interpolation) ? CV_INTER_LINEAR : NUM2INT(interpolation);
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try {
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dest = new_mat_kind_object(cvGetSize(self_ptr), self);
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cvWarpAffine(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(map_matrix),
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CVMETHOD("INTERPOLATION_METHOD", interpolation, CV_INTER_LINEAR)
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| CVMETHOD("WARP_FLAG", option, CV_WARP_FILL_OUTLIERS), VALUE_TO_CVSCALAR(fill_value));
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method | CVMETHOD("WARP_FLAG", option, CV_WARP_FILL_OUTLIERS),
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VALUE_TO_CVSCALAR(fill_value));
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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@ -4047,7 +4050,7 @@ rb_rotation_matrix2D(VALUE self, VALUE center, VALUE angle, VALUE scale)
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/*
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* call-seq:
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* warp_perspective(<i>map_matrix[,interpolation=:linear][,option =:fill_outliers][,fillval=0])</i>) -> cvmat
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* warp_perspective(<i>map_matrix[,interpolation=CV_INTER_LINEAR][,option =:fill_outliers][,fillval=0])</i>) -> cvmat
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*
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* Applies perspective transformation to the image.
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*/
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@ -4059,11 +4062,11 @@ rb_warp_perspective(int argc, VALUE *argv, VALUE self)
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fillval = INT2FIX(0);
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CvArr* self_ptr = CVARR(self);
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VALUE dest = Qnil;
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int method = NIL_P(interpolation) ? CV_INTER_LINEAR : NUM2INT(interpolation);
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try {
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dest = new_mat_kind_object(cvGetSize(self_ptr), self);
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cvWarpPerspective(self_ptr, CVARR(dest), CVMAT_WITH_CHECK(map_matrix),
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CVMETHOD("INTERPOLATION_METHOD", interpolation, CV_INTER_LINEAR)
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| CVMETHOD("WARP_FLAG",option, CV_WARP_FILL_OUTLIERS),
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method | CVMETHOD("WARP_FLAG",option, CV_WARP_FILL_OUTLIERS),
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VALUE_TO_CVSCALAR(fillval));
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}
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catch (cv::Exception& e) {
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@ -4074,7 +4077,7 @@ rb_warp_perspective(int argc, VALUE *argv, VALUE self)
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/*
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* call-seq:
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* remap(<i>mapx,mapy[,interpolation=:linear][,option=:fill_outliers][,fillval=0]</i>) -> cvmat
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* remap(<i>mapx,mapy[,interpolation=CV_INTER_LINEAR][,option=:fill_outliers][,fillval=0]</i>) -> cvmat
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*
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* Applies generic geometrical transformation to the image.
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* Transforms source image using the specified map:
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@ -4090,11 +4093,11 @@ rb_remap(int argc, VALUE *argv, VALUE self)
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fillval = INT2FIX(0);
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CvArr* self_ptr = CVARR(self);
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VALUE dest = Qnil;
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int method = NIL_P(interpolation) ? CV_INTER_LINEAR : NUM2INT(interpolation);
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try {
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dest = new_mat_kind_object(cvGetSize(self_ptr), self);
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cvRemap(self_ptr, CVARR(dest), CVARR_WITH_CHECK(mapx), CVARR_WITH_CHECK(mapy),
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CVMETHOD("INTERPOLATION_METHOD", interpolation, CV_INTER_LINEAR)
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| CVMETHOD("WARP_FLAG", option, CV_WARP_FILL_OUTLIERS),
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method | CVMETHOD("WARP_FLAG", option, CV_WARP_FILL_OUTLIERS),
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VALUE_TO_CVSCALAR(fillval));
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}
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catch (cv::Exception& e) {
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@ -345,14 +345,6 @@ define_ruby_module()
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REGISTER_CVMETHOD(inversion_method, "svd_sym", CV_SVD_SYM);
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REGISTER_CVMETHOD(inversion_method, "svd_symmetric", CV_SVD_SYM);
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VALUE interpolation_method = rb_hash_new();
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/* {:nn, :linear, :area, :cubic}: Interpolation method */
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rb_define_const(rb_module, "INTERPOLATION_METHOD", interpolation_method);
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REGISTER_CVMETHOD(interpolation_method, "nn", CV_INTER_NN);
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REGISTER_CVMETHOD(interpolation_method, "linear", CV_INTER_LINEAR);
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REGISTER_CVMETHOD(interpolation_method, "area", CV_INTER_AREA);
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REGISTER_CVMETHOD(interpolation_method, "cubic", CV_INTER_CUBIC);
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VALUE warp_flag = rb_hash_new();
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/* {:fill_outliers, :inverse_map}: Warp affine optional flags */
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rb_define_const(rb_module, "WARP_FLAG", warp_flag);
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@ -388,10 +388,10 @@ class TestCvMat_imageprocessing < OpenCVTestCase
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size_512 = CvSize.new(512, 512)
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size_128 = CvSize.new(128, 128)
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mat1 = mat0.resize(size_512)
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mat2 = mat0.resize(size_512, :linear)
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mat3 = mat0.resize(size_512, :nn)
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mat4 = mat0.resize(size_128, :area)
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mat5 = mat0.resize(size_128, :cubic)
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mat2 = mat0.resize(size_512, CV_INTER_LINEAR)
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mat3 = mat0.resize(size_512, CV_INTER_NN)
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mat4 = mat0.resize(size_128, CV_INTER_AREA)
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mat5 = mat0.resize(size_128, CV_INTER_CUBIC)
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mat6 = mat0.clone
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assert_equal('b2203ccca2c17b042a90b79704c0f535', hash_img(mat1))
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@ -420,9 +420,9 @@ class TestCvMat_imageprocessing < OpenCVTestCase
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map_matrix[5] = CvScalar.new(66.08774)
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mat1 = mat0.warp_affine(map_matrix)
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mat2 = mat0.warp_affine(map_matrix, :nn)
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mat3 = mat0.warp_affine(map_matrix, :linear, :fill_outliers, CvColor::Yellow)
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mat4 = mat0.warp_affine(map_matrix, :linear, :inverse_map)
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mat2 = mat0.warp_affine(map_matrix, CV_INTER_NN)
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mat3 = mat0.warp_affine(map_matrix, CV_INTER_LINEAR, :fill_outliers, CvColor::Yellow)
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mat4 = mat0.warp_affine(map_matrix, CV_INTER_LINEAR, :inverse_map)
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assert_equal('da3d7cdefabbaf84c4080ecd40d00897', hash_img(mat1))
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assert_equal('b4abcd12c4e1103c3de87bf9ad854936', hash_img(mat2))
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@ -483,9 +483,9 @@ class TestCvMat_imageprocessing < OpenCVTestCase
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map_matrix[8] = CvScalar.new(1.00000)
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mat1 = mat0.warp_perspective(map_matrix)
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mat2 = mat0.warp_perspective(map_matrix, :nn)
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mat3 = mat0.warp_perspective(map_matrix, :linear, :inverse_map)
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mat4 = mat0.warp_perspective(map_matrix, :linear, :fill_outliers, CvColor::Yellow)
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mat2 = mat0.warp_perspective(map_matrix, CV_INTER_NN)
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mat3 = mat0.warp_perspective(map_matrix, CV_INTER_LINEAR, :inverse_map)
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mat4 = mat0.warp_perspective(map_matrix, CV_INTER_LINEAR, :fill_outliers, CvColor::Yellow)
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assert_equal('bba3a5395f9dd9a400a0083ae74d8986', hash_img(mat1))
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assert_equal('a0cc4f329f459410293b75b417fc4f25', hash_img(mat2))
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@ -522,8 +522,8 @@ class TestCvMat_imageprocessing < OpenCVTestCase
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}
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mat1 = mat0.remap(matx, maty)
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mat2 = mat0.remap(matx, maty, :nn)
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mat3 = mat0.remap(matx, maty, :linear, :fill_outliers, CvColor::Yellow)
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mat2 = mat0.remap(matx, maty, CV_INTER_NN)
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mat3 = mat0.remap(matx, maty, CV_INTER_LINEAR, :fill_outliers, CvColor::Yellow)
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assert_equal('586716c0262a3e03a54b9fc6e671e5f7', hash_img(mat1))
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assert_equal('5461ecdee23d5e8a9099500d631c9f0f', hash_img(mat2))
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