pull/2349/head
Alexander Alekhin 6 years ago
parent 22f0ea0cb3
commit ad8f00017a
  1. 2
      modules/ximgproc/test/test_edgeboxes.cpp
  2. 2
      modules/ximgproc/test/test_structured_edge_detection.cpp
  3. 4
      modules/ximgproc/test/test_thinning.cpp
  4. 2
      modules/ximgproc/tutorials/training.markdown

@ -5,7 +5,7 @@
namespace opencv_test { namespace {
TEST(ximpgroc_Edgeboxes, regression)
TEST(ximgproc_Edgeboxes, regression)
{
//Testing Edgeboxes implementation by asking for one proposal
//on a simple test image from the PASCAL VOC 2012 dataset.

@ -5,7 +5,7 @@
namespace opencv_test { namespace {
TEST(ximpgroc_StructuredEdgeDetection, regression)
TEST(ximgproc_StructuredEdgeDetection, regression)
{
cv::String subfolder = "cv/ximgproc/";
cv::String dir = cvtest::TS::ptr()->get_data_path() + subfolder;

@ -18,7 +18,7 @@ static int createTestImage(Mat& src)
return src_pixels;
}
TEST(ximpgroc_Thinning, simple_ZHANGSUEN)
TEST(ximgproc_Thinning, simple_ZHANGSUEN)
{
Mat src;
int src_pixels = createTestImage(src);
@ -33,7 +33,7 @@ TEST(ximpgroc_Thinning, simple_ZHANGSUEN)
#endif
}
TEST(ximpgroc_Thinning, simple_GUOHALL)
TEST(ximgproc_Thinning, simple_GUOHALL)
{
Mat src;
int src_pixels = createTestImage(src);

@ -103,7 +103,7 @@ Training pipeline
-# The final step is converting trained model from Matlab binary format to YAML which you can use
with our ocv::StructuredEdgeDetection. For this purpose run
opencv_contrib/ximpgroc/tutorials/scripts/modelConvert(model, "model.yml")
opencv_contrib/ximgproc/tutorials/scripts/modelConvert(model, "model.yml")
How to use your model
---------------------

Loading…
Cancel
Save