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typo
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@@ -5,7 +5,7 @@
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namespace opencv_test { namespace {
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TEST(ximpgroc_Edgeboxes, regression)
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TEST(ximgproc_Edgeboxes, regression)
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{
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//Testing Edgeboxes implementation by asking for one proposal
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//on a simple test image from the PASCAL VOC 2012 dataset.
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@@ -5,7 +5,7 @@
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namespace opencv_test { namespace {
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TEST(ximpgroc_StructuredEdgeDetection, regression)
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TEST(ximgproc_StructuredEdgeDetection, regression)
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{
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cv::String subfolder = "cv/ximgproc/";
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cv::String dir = cvtest::TS::ptr()->get_data_path() + subfolder;
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@@ -18,7 +18,7 @@ static int createTestImage(Mat& src)
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return src_pixels;
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}
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TEST(ximpgroc_Thinning, simple_ZHANGSUEN)
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TEST(ximgproc_Thinning, simple_ZHANGSUEN)
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{
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Mat src;
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int src_pixels = createTestImage(src);
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@@ -33,7 +33,7 @@ TEST(ximpgroc_Thinning, simple_ZHANGSUEN)
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#endif
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}
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TEST(ximpgroc_Thinning, simple_GUOHALL)
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TEST(ximgproc_Thinning, simple_GUOHALL)
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{
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Mat src;
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int src_pixels = createTestImage(src);
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@@ -103,7 +103,7 @@ Training pipeline
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-# The final step is converting trained model from Matlab binary format to YAML which you can use
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with our ocv::StructuredEdgeDetection. For this purpose run
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opencv_contrib/ximpgroc/tutorials/scripts/modelConvert(model, "model.yml")
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opencv_contrib/ximgproc/tutorials/scripts/modelConvert(model, "model.yml")
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How to use your model
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---------------------
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