OpenCV 4.5.3(日本語機械翻訳)
erfilter.hpp
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43
44 #ifndef __OPENCV_TEXT_ERFILTER_HPP__
45 #define __OPENCV_TEXT_ERFILTER_HPP__
46
47 #include "opencv2/core.hpp"
48 #include <vector>
49 #include <deque>
50 #include <string>
51
52 namespace cv
53{
54 namespace text
55{
56
59
66 struct CV_EXPORTS ERStat
67{
68 public:
70 explicit ERStat(int level = 256, int pixel = 0, int x = 0, int y = 0);
72 ~ERStat() { }
73
75 int pixel;
76 int level;
77
79 int area;
80 int perimeter;
81 int euler;
82 Rect rect;
83 double raw_moments[2];
84 double central_moments[3];
85 Ptr<std::deque<int> > crossings;
86 float med_crossings;
87
89 float hole_area_ratio;
90 float convex_hull_ratio;
91 float num_inflexion_points;
92
93 // TODO Other features can be added (average color, standard deviation, and such)
94
95
96 // TODO shall we include the pixel list whenever available (i.e. after 2nd stage) ?
97 std::vector<int> *pixels;
98
100 double probability;
101
103 ERStat* parent;
104 ERStat* child;
105 ERStat* next;
106 ERStat* prev;
107
109 bool local_maxima;
110 ERStat* max_probability_ancestor;
111 ERStat* min_probability_ancestor;
112};
113
118 class CV_EXPORTS_W ERFilter : public Algorithm
119{
120 public:
121
127 class CV_EXPORTS_W Callback
128 {
129 public:
130 virtual ~Callback() { }
135 virtual double eval(const ERStat& stat) = 0; //const = 0; //TODO why cannot use const = 0 here?
136 };
137
151 virtual void run( InputArray image, std::vector<ERStat>& regions ) = 0;
152
153
155 virtual void setCallback(const Ptr<ERFilter::Callback>& cb) = 0;
156 virtual void setThresholdDelta(int thresholdDelta) = 0;
157 virtual void setMinArea(float minArea) = 0;
158 virtual void setMaxArea(float maxArea) = 0;
159 virtual void setMinProbability(float minProbability) = 0;
160 virtual void setMinProbabilityDiff(float minProbabilityDiff) = 0;
161 virtual void setNonMaxSuppression(bool nonMaxSuppression) = 0;
162 virtual int getNumRejected() const = 0;
163};
164
165
166
187 CV_EXPORTS_W Ptr<ERFilter> createERFilterNM1(const Ptr<ERFilter::Callback>& cb,
188 int thresholdDelta = 1, float minArea = (float)0.00025,
189 float maxArea = (float)0.13, float minProbability = (float)0.4,
190 bool nonMaxSuppression = true,
191 float minProbabilityDiff = (float)0.1);
192
204 CV_EXPORTS_W Ptr<ERFilter> createERFilterNM2(const Ptr<ERFilter::Callback>& cb,
205 float minProbability = (float)0.3);
206
212 CV_EXPORTS_W Ptr<ERFilter> createERFilterNM1(const String& filename,
213 int thresholdDelta = 1, float minArea = (float)0.00025,
214 float maxArea = (float)0.13, float minProbability = (float)0.4,
215 bool nonMaxSuppression = true,
216 float minProbabilityDiff = (float)0.1);
217
223 CV_EXPORTS_W Ptr<ERFilter> createERFilterNM2(const String& filename,
224 float minProbability = (float)0.3);
225
232 CV_EXPORTS_W Ptr<ERFilter::Callback> loadClassifierNM1(const String& filename);
233
240 CV_EXPORTS_W Ptr<ERFilter::Callback> loadClassifierNM2(const String& filename);
241
242
244 enum { ERFILTER_NM_RGBLGrad,
245 ERFILTER_NM_IHSGrad
246 };
247
262 CV_EXPORTS_W void computeNMChannels(InputArray _src, CV_OUT OutputArrayOfArrays _channels, int _mode = ERFILTER_NM_RGBLGrad);
263
264
265
267 enum erGrouping_Modes {
268
279 ERGROUPING_ORIENTATION_HORIZ,
290 ERGROUPING_ORIENTATION_ANY
291 };
292
316 CV_EXPORTS void erGrouping(InputArray img, InputArrayOfArrays channels,
317 std::vector<std::vector<ERStat> > &regions,
318 std::vector<std::vector<Vec2i> > &groups,
319 std::vector<Rect> &groups_rects,
320 int method = ERGROUPING_ORIENTATION_HORIZ,
321 const std::string& filename = std::string(),
322 float minProbablity = 0.5);
323
324CV_EXPORTS_W void erGrouping(InputArray image, InputArray channel,
325 std::vector<std::vector<Point> > regions,
326 CV_OUT std::vector<Rect> &groups_rects,
327 int method = ERGROUPING_ORIENTATION_HORIZ,
328 const String& filename = String(),
329 float minProbablity = (float)0.5);
330
347 CV_EXPORTS void MSERsToERStats(InputArray image, std::vector<std::vector<Point> > &contours,
348 std::vector<std::vector<ERStat> > &regions);
349
350 // Utility funtion for scripting
351CV_EXPORTS_W void detectRegions(InputArray image, const Ptr<ERFilter>& er_filter1, const Ptr<ERFilter>& er_filter2, CV_OUT std::vector< std::vector<Point> >& regions);
352
353
366 CV_EXPORTS_W void detectRegions(InputArray image, const Ptr<ERFilter>& er_filter1, const Ptr<ERFilter>& er_filter2, CV_OUT std::vector<Rect> &groups_rects,
367 int method = ERGROUPING_ORIENTATION_HORIZ,
368 const String& filename = String(),
369 float minProbability = (float)0.5);
370
372
373}
374}
375 #endif // _OPENCV_TEXT_ERFILTER_HPP_
cv::_OutputArray
This type is very similar to InputArray except that it is used for input/output and output function p...
Definition: mat.hpp:295
cv::Algorithm
This is a base class for all more or less complex algorithms in OpenCV
Definition: core.hpp:3091
cv::Rect_
Template class for 2D rectangles
Definition: core/types.hpp:421
cv::text::ERFilter::Callback
Callback with the classifier is made a class.
Definition: erfilter.hpp:128
cv::text::ERFilter::Callback::eval
virtual double eval(const ERStat &stat)=0
The classifier must return probability measure for the region.
cv::text::ERFilter
Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm ....
Definition: erfilter.hpp:119
cv::text::ERFilter::run
virtual void run(InputArray image, std::vector< ERStat > &regions)=0
The key method of ERFilter algorithm.
cv::text::ERFilter::setCallback
virtual void setCallback(const Ptr< ERFilter::Callback > &cb)=0
set/get methods to set the algorithm properties,
cv::text::loadClassifierNM2
CV_EXPORTS_W Ptr< ERFilter::Callback > loadClassifierNM2(const String &filename)
Allow to implicitly load the default classifier when creating an ERFilter object.
cv::text::MSERsToERStats
CV_EXPORTS void MSERsToERStats(InputArray image, std::vector< std::vector< Point > > &contours, std::vector< std::vector< ERStat > > &regions)
Converts MSER contours (vector<Point>) to ERStat regions.
cv::text::computeNMChannels
CV_EXPORTS_W void computeNMChannels(InputArray _src, CV_OUT OutputArrayOfArrays _channels, int _mode=ERFILTER_NM_RGBLGrad)
Compute the different channels to be processed independently in the N&M algorithm .
cv::text::detectRegions
CV_EXPORTS_W void detectRegions(InputArray image, const Ptr< ERFilter > &er_filter1, const Ptr< ERFilter > &er_filter2, CV_OUT std::vector< Rect > &groups_rects, int method=ERGROUPING_ORIENTATION_HORIZ, const String &filename=String(), float minProbability=(float) 0.5)
Extracts text regions from image.
cv::text::createERFilterNM1
CV_EXPORTS_W Ptr< ERFilter > createERFilterNM1(const String &filename, int thresholdDelta=1, float minArea=(float) 0.00025, float maxArea=(float) 0.13, float minProbability=(float) 0.4, bool nonMaxSuppression=true, float minProbabilityDiff=(float) 0.1)
Reads an Extremal Region Filter for the 1st stage classifier of N&M algorithm from the provided path ...
cv::text::erGrouping
CV_EXPORTS void erGrouping(InputArray img, InputArrayOfArrays channels, std::vector< std::vector< ERStat > > &regions, std::vector< std::vector< Vec2i > > &groups, std::vector< Rect > &groups_rects, int method=ERGROUPING_ORIENTATION_HORIZ, const std::string &filename=std::string(), float minProbablity=0.5)
Find groups of Extremal Regions that are organized as text blocks.
cv::text::createERFilterNM2
CV_EXPORTS_W Ptr< ERFilter > createERFilterNM2(const String &filename, float minProbability=(float) 0.3)
Reads an Extremal Region Filter for the 2nd stage classifier of N&M algorithm from the provided path ...
cv::text::erGrouping_Modes
erGrouping_Modes
text::erGrouping operation modes
Definition: erfilter.hpp:267
cv::text::loadClassifierNM1
CV_EXPORTS_W Ptr< ERFilter::Callback > loadClassifierNM1(const String &filename)
Allow to implicitly load the default classifier when creating an ERFilter object.
cv::text::ERGROUPING_ORIENTATION_HORIZ
@ ERGROUPING_ORIENTATION_HORIZ
Definition: erfilter.hpp:279
cv::text::ERGROUPING_ORIENTATION_ANY
@ ERGROUPING_ORIENTATION_ANY
Definition: erfilter.hpp:290
cv
"black box" representation of the file storage associated with a file on disk.
Definition: aruco.hpp:75
cv::Ptr
Definition: cvstd_wrapper.hpp:74
cv::text::ERStat
The ERStat structure represents a class-specific Extremal Region (ER).
Definition: erfilter.hpp:67
cv::text::ERStat::hole_area_ratio
float hole_area_ratio
2nd stage features
Definition: erfilter.hpp:89
cv::text::ERStat::local_maxima
bool local_maxima
whenever the regions is a local maxima of the probability
Definition: erfilter.hpp:109
cv::text::ERStat::area
int area
incrementally computable features
Definition: erfilter.hpp:79
cv::text::ERStat::ERStat
ERStat(int level=256, int pixel=0, int x=0, int y=0)
Constructor
cv::text::ERStat::crossings
Ptr< std::deque< int > > crossings
horizontal crossings
Definition: erfilter.hpp:85
cv::text::ERStat::med_crossings
float med_crossings
median of the crossings at three different height levels
Definition: erfilter.hpp:86
cv::text::ERStat::probability
double probability
probability that the ER belongs to the class we are looking for
Definition: erfilter.hpp:100
cv::text::ERStat::parent
ERStat * parent
pointers preserving the tree structure of the component tree
Definition: erfilter.hpp:103
cv::text::ERStat::euler
int euler
Euler's number
Definition: erfilter.hpp:81
cv::text::ERStat::pixel
int pixel
seed point and the threshold (max grey-level value)
Definition: erfilter.hpp:75
cv::text::ERStat::~ERStat
~ERStat()
Destructor
Definition: erfilter.hpp:72
構築: doxygen 1.9.2