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Merge pull request #2349 from alalek:fix_contrib_2346
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@@ -37,16 +37,24 @@
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//
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//M*/
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#include "precomp.hpp"
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#include <vector>
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#include <algorithm>
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#include <iterator>
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#include <iostream>
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#include <cmath>
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#include "precomp.hpp"
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#include "advanced_types.hpp"
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#ifdef CV_CXX11
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#define CV_USE_PARALLEL_PREDICT_EDGES_1 1
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#define CV_USE_PARALLEL_PREDICT_EDGES_2 0 //1, see https://github.com/opencv/opencv_contrib/issues/2346
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#else
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#define CV_USE_PARALLEL_PREDICT_EDGES_1 0
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#define CV_USE_PARALLEL_PREDICT_EDGES_2 0
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#endif
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/********************* Helper functions *********************/
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/*!
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@@ -730,7 +738,7 @@ protected:
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}
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// lookup tables for mapping linear index to offset pairs
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#ifdef CV_CXX11
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#if CV_USE_PARALLEL_PREDICT_EDGES_1
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parallel_for_(cv::Range(0, height), [&](const cv::Range& range)
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#else
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const cv::Range range(0, height);
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@@ -779,7 +787,7 @@ protected:
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}
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}
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}
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#ifdef CV_CXX11
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#if CV_USE_PARALLEL_PREDICT_EDGES_1
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);
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#endif
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@@ -788,8 +796,10 @@ protected:
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dstM.setTo(0);
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float step = 2.0f * CV_SQR(stride) / CV_SQR(ipSize) / nTreesEval;
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#ifdef CV_CXX11
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#if CV_USE_PARALLEL_PREDICT_EDGES_2
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parallel_for_(cv::Range(0, height), [&](const cv::Range& range)
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#elif CV_USE_PARALLEL_PREDICT_EDGES_1
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const cv::Range range(0, height);
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#endif
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{
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for(int i = range.start; i < range.end; ++i)
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@@ -814,7 +824,7 @@ protected:
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}
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}
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}
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#ifdef CV_CXX11
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#if CV_USE_PARALLEL_PREDICT_EDGES_2
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);
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#endif
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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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