| OpenCV 3.4.7 Open Source Computer Vision

Structured forests for fast edge detection

## Introduction

In this tutorial you will learn how to use structured forests for the purpose of edge detection in an image.

## Examples

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Note
  binarization techniques like Canny edge detector are applicable to edges produced by both algorithms (Sobel and StructuredEdgeDetection::detectEdges).

## Source Code

1 /**************************************************************************************
2 The structered edge demo requires you to provide a model.
3 This model can be found at the opencv_extra repository on Github on the following link:
4 https://github.com/opencv/opencv_extra/blob/master/testdata/cv/ximgproc/model.yml.gz
5 ***************************************************************************************/
6
7 #include <opencv2/ximgproc.hpp>
8 #include "opencv2/highgui.hpp"
9 #include "opencv2/core/utility.hpp"
10 #include <iostream>
11
12 using namespace cv;
13 using namespace cv::ximgproc;
14
15 const char* keys =
16 {
17 "{i || input image name}"
18 "{m || model name}"
19 "{o || output image name}"
20 };
21
22 int main( int argc, const char** argv )
23 {
24 bool printHelp = ( argc == 1 );
25 printHelp = printHelp || ( argc == 2 && String(argv[1]) == "--help" );
26 printHelp = printHelp || ( argc == 2 && String(argv[1]) == "-h" );
27
28 if ( printHelp )
29 {
30 std::cout << "\nThis sample demonstrates structured forests for fast edge detection\n"
31 "Call:\n"
32 " structured_edge_detection -i=in_image_name -m=model_name [-o=out_image_name]\n\n";
33 return 0;
34 }
35
36 CommandLineParser parser(argc, argv, keys);
37 if ( !parser.check() )
38 {
39 parser.printErrors();
40 return -1;
41 }
42
43 String modelFilename = parser.get<String>("m");
44 String inFilename = parser.get<String>("i");
45 String outFilename = parser.get<String>("o");
46
47 Mat image = imread(inFilename, 1);
48 if ( image.empty() )
49 CV_Error(Error::StsError, String("Cannot read image file: ") + inFilename);
50
51 if ( modelFilename.size() == 0)
52 CV_Error(Error::StsError, String("Empty model name"));
53
54 image.convertTo(image, DataType<float>::type, 1/255.0);
55
56 Mat edges(image.size(), image.type());
57
58 Ptr<StructuredEdgeDetection> pDollar =
59 createStructuredEdgeDetection(modelFilename);
60 pDollar->detectEdges(image, edges);
61
62 // computes orientation from edge map
63 Mat orientation_map;
64 pDollar->computeOrientation(edges, orientation_map);
65
66 // suppress edges
67 Mat edge_nms;
68 pDollar->edgesNms(edges, orientation_map, edge_nms, 2, 0, 1, true);
69
70 if ( outFilename.size() == 0 )
71 {
72 namedWindow("edges", 1);
73 imshow("edges", edges);
74 namedWindow("edges nms", 1);
75 imshow("edges nms", edge_nms);
76 waitKey(0);
77 }
78 else
79 imwrite(outFilename, 255*edges);
80
81 return 0;
82 }
cv::imwrite
bool imwrite(const String &filename, InputArray img, const std::vector< int > &params=std::vector< int >())
Saves an image to a specified file.
cv::Error::StsError
unknown /unspecified error
Definition: base.hpp:71
cv::imread
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
CV_Error
#define CV_Error(code, msg)
Call the error handler.
Definition: base.hpp:347
highgui.hpp
cv::imshow
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
cv
Definition: affine.hpp:51
cv::CommandLineParser
Designed for command line parsing.
Definition: utility.hpp:862
cv::ximgproc::createStructuredEdgeDetection
Ptr< StructuredEdgeDetection > createStructuredEdgeDetection(const String &model, Ptr< const RFFeatureGetter > howToGetFeatures=Ptr< RFFeatureGetter >())
utility.hpp
cv::namedWindow
void namedWindow(const String &winname, int flags=WINDOW_AUTOSIZE)
Creates a window.
cv::ximgproc
Definition: brightedges.hpp:47
cv::Ptr
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:261
cv::DataType
Template "trait" class for OpenCV primitive data types.
Definition: traits.hpp:112
cv::String
Definition: cvstd.hpp:458
cv::String::size
size_t size() const
cv::Mat
n-dimensional dense array class
Definition: mat.hpp:804
cv::waitKey
int waitKey(int delay=0)
Waits for a pressed key.
ximgproc.hpp

## Explanation

1. Load source color image
   cv::Mat image = cv::imread(inFilename, 1);
   if ( image.empty() )
   {
   printf("Cannot read image file: %s\n", inFilename.c_str());
   return -1;
   }
2. Convert source image to [0;1] range
   image.convertTo(image, cv::DataType<float>::type, 1/255.0);
3. Run main algorithm
   cv::Mat edges(image.size(), image.type());
   cv::Ptr<StructuredEdgeDetection> pDollar =
   cv::createStructuredEdgeDetection(modelFilename);
   pDollar->detectEdges(image, edges);
4. Show results
   if ( outFilename == "" )
   {
   cv::namedWindow("edges", 1);
   cv::imshow("edges", edges);
   cv::waitKey(0);
   }
   else
   cv::imwrite(outFilename, 255*edges);

## Literature

For more information, refer to the following papers : [49] [124]