基于C++的OpenCV常⽤函数
C++版本的好处：
1、在于可以尽量避免使⽤指针这种危险的东西；
2、不⽤费⼼去release资源了，因为在其destructor⾥⾯，系统会⾃动帮你搞定。
3、在某些情况下会⽐C版本运⾏速度快。
在⽂件中包含 using namespace cv;
rectangle函数opencv1. Imread(CvLoadImage)：loads an image from a file；
2. imshow(cvShowImage)：displays an image in the specifiedwidow；
3. waitKey(cvWaitKey)：waits for a pressed key；
4. cvtColor(cvCvtColor)：converts an image from one colorspace to another；
5. reduce(cvReduce)：reduces a matrix to a vector；
6. minMaxLoc(cvMinMaxLoc)：finds the global minimum andmaximum in a whole array or sub-array；
7. namedWindow(cvNamedWindow)：creates a window；
8. destroyWindow(cvDestroyWindow)：destroys a window；
9. destroyAllWindows(cvDestroyAllWindows)：destroys all of the HighGUIwindows；
10. imwrite(cvSaveImage)：saves an image to a specified file；
11. resize(cvResize)：resizes an image；
12. pyrDown(cvPyrDown)：blurs an image and downsamples it；
13. pyrUp(cvPyrUp)：upsamples an image and then blursit；
14. threshold(cvThreshold)：applies a fixed-level threshold toeach array element；
15. adaptiveThreshold(cvAdaptiveThreshold)：applies an adaptive threshold toan array；
16. VideoCapthure::open(cvCaptureFromFile)：open video file or a capturingdevice for video capturing；
17. VideoCapture::isOpened：returns true if video capturinghas been initialized already；
18. VideoCapture::release(cvReleaseCapture)：closes video file or capturingdevice；
19. VideoCapture::grab(cvGrabFrame)：grabs the next frame from videofile or capturing device；
20. VideoCaputre::retrieve(cvRetrieveFrame)：decodes and returns the grabbedvideo frame；
21. VideoCapture::read(cvQueryFrame)：grabs,decodes and returns the nextvideo frame；
22. VideoCapture::get(cvGetCaptureProperty)：returns the specified VideoCaptureproperty；
23. VideoCapture::set(cvSetCaptureProperty)：sets a property in theVideoCapture；
24. VideoWriter::open：initializes or reinitializes videowriter；
25. VideoWriter::isOpened：returns true if video writer hasbeen successfully initialized；
26. VideoWriter::write：writes the next video frame；
27. Mat::row：creates a matrix header for thespecified matrix row；
28. Mat::col：creates a matrix header for thespecified matrix column；
28. Mat::col：creates a matrix header for thespecified matrix column；
29. Mat::rowRange：creates a matrix header for thespecified row span；
30. Mat::colRange：creates a matrix header for thespecified col span；
31. Mat::diag：extracts a diagonal from a matrix,or creates a diagonal matrix；
32. Mat::clone：creates a full copy of the arrayand the underlying data；
33. Mat::copyTo(cvCopy)：copies the matrix to another one；
34. Mat::convertTo(cvConvertScale)：converts an array to anotherdatatype with optional scaling；
35. Mat::assignTo：provides a functional form ofconvertTo；
36. Mat::setTo：sets all or some of the arrayelements to the specified value；
37. Mat::reshape：changes the shape and/or thenumber of channels of a 2D matrix without copying the data；
38. Mat::t：transposes a matrix；
39. Mat::inv：inverses a matrix；
40. Mat::mul：performs an element-wisemultiplication or division of the two matrices；
41. Mat::cross：computes a cross-product of two3-element vectors；
42. Mat::dot：computes a dot-product of twovectors；
43. Mat::zeros：returns a zero array of thespecified size and type；
44. Mat::ones：returns an array of all 1’s of thespecified size and type；
45. Mat::eye：returns an identity matrix of thespecified size and type；
46. Mat::create：allocates new array data if needed；
47. Mat::addref：increments the reference counter；
48. Mat::release：decrements the reference counterand deallocates the matrix if needed；
49. Mat::resize：changes the number of matrix rows；
50. Mat::reserve：reserves space for the certainnumber of rows；
51. Mat::push_back：adds elements to the bottom of thematrix；
52. Mat::pop_back：removes elements from the bottomof the matrix；
53. Mat::locateROI：locates the matrix header within aparent matrix；
54. Mat::adjustROI：adjusts a submatrix size andposition within the parent matrix；
55. Mat::operator：extracts a rectangular submatrix；
56. Mat::operatorCvMat：creates the CvMat header for thematrix；
57. Mat::operatorIplImage：creates the IplImage header forthe matrix；
58. Mat::total：returns the total number fo arrayelements；
59. Mat::isContinuous：reports whether the matrix iscontinuous or not；
60. Mat::elemSize：returns the matrix element size inbytes；
61. Mat::elemSize1：returns the size of each matrixelement channel in bytes；
62. Mat::type：returns the type of a matrixelement；
62. Mat::type：returns the type of a matrixelement；
63. Mat::depth：returns the depth of a matrixelement；
64. Mat::channels：returns the number of matrix channels；
65. Mat::step1：returns a normalized step；
66. Mat::size：returns a matrix size；
67. Mat::empty：returns true if the array has noelemens；
68. Mat::ptr：returns a pointer to the specifiedmatrix row；
69. Mat::at：returns a reference to thespecified array element；
70. Mat::begin：returns the matrix iterator andsets it to the first matrix element；
71. Mat::end：returns the matrix iterator andsets it to the after-last matrix element；
72. calcHist(cvCalcHist)：calculates a histogram of a set ofarrays；
73. compareHist(cvCompareHist)：compares two histograms；
74. equalizeHist(cvEqualizeHist)：equalizes the histogram of agrayscale image(直⽅图均衡化);
75. normalize：normalizes the norm or value rangeof an array；
76. CascadeClassifier::CascadeClassifier：loads a classifier from a file；
77. CascadeClassifier::empth：checks whether the classifier hasbeen loaded；
78. CascadeClassifier::load(cvLoadHaarClassifierCascade)：loads a classifier from a file；
79. CascadeClassifier::read：reads a classifier from aFileStorage node；
80. CascadeClassifier::delectMultiScale(cvHaarDetectObjects)：detects objects of different sizesin the input image(检测图
像中的⽬标)；
81. CascadeClassifier::setImage(cvSetImagesForHaarClassifierCascade)：sets an image for detection(隐藏的
cascade(hidden cascade)指定图像)；
82. CascadeClassifier::runAt(cvRunHaarClassifierCascade)：runs the detector at the specifiedpoint(在给定位置的图像中运⾏
cascade of boosted classifier)；
83. groupRectangles：groups the object candidaterectangles；
84. split(cvSplit)：divides a multi-channel array intoseveral single-channel arrays；
85. merge(cvMerge)：creates one multichannel array outof several single-channel ones；
86. mixChannels(cvMixChannels)：copies specified channels frominput arrays to the specified channels of output
arrays；
87. setMouseCallback(cvSetMouseCallback)：sets mouse handler for thespecified window；
88. bilateralFilter：applies the bilateral filter to animage(双边滤波)；
89. blur(cvSmooth)：blurs an image using thenormalized box filter(均值模糊)；
90. medianBlur：blurs an image using the medianfilter(中值模糊)；
91. boxFilter：blurs an image using the boxfilter；
92. GaussianBlur：blurs an image using a Gaussianfilter(⾼斯模糊)；
93. getGaussianKernel：returns Gaussian filtercoefficients；
94. sepFilter2D：applies a separable linear filterto an image；
95. filter2D(cvFilter2D)：convolves an image with the kernel；
96. norm(cvNorm)：calculates an absolute array norm,an absolute difference norm, or a relative defference norm；
97. flip(cvFlip)：filps a 2D array around vertical,horizontal, or both axes；
98. Algorithm::get：returns the algorithm parameter；
99. Algorithm::set：set the algorithm parameter；
100. Algorithm::write：stores algorithm parameters in afile storage；
101. Algorithm::read：reads algorithm parameters from afile storage；
102. Algorithm::getList：returns the list of registeredalgorithms；
103. Algorithm::create：creates algorithm instance by name；
104. FaceRecognizer::train：trains a FaceRecognizer with givendata and associated labels；
105. FaceRecognizer::update：updates a FaceRecognizer withgiven data and associated labels；
106. FaceRecognizer::predict：predicts a label and distance) for a given input image；
107. FaceRecognizer::save：saves a FaceRecognizer and itsmodel state；
108. FaceRecognizer::load：loads a FaceRecognizer and itsmodel state；
109. createEigenFaceRecognizer：；
110. createFisherFaceRecognizer：；
111. createBPHFaceRecognizer：；
112. getTextSize(cvGetTextSize)：calculates the width and height ofa textstring；
113. putText(cvPutText)：draws a text string；
114. getStructuringElement(cvCreateStructingElementEx)：returns a structuring element ofthe specified size and shape for morphological operations；
115. morphologyEx(cvMorphologyEx)：performs advanced morphologicaltransformations；
116. findContours(cvFindContours)：finds contours in a binary image；
117. drawContours(cvDrawContours)：draw contours outlines or filledcontours；
118. minAreaRect(cvMinAreaRect2)：finds a rotated rectangle of theminimum area enclosing the input 2D point set；
119. floodFill(cvFloodFill)：fills a connected component withthe given color；
120. getRectSubPix(cvGetRectSubPix)：retrieves a pixel rectangle froman image with sub-pixel accuracy；
121. CvSVM::CvSVM：default and training constructors；
122. CvSVM::train：trains an SVM；
123. CvSVM::train_auto：trains an SVM with optimalparameters；
124. CvSVM::predict：predicts the response for inputsample(s)；
125. CvSVM::get_default_grid：generates a grid for SVMparameters；
126. CvSVM::get_params：returns the current SVM parameters；
127. CvSVM::get_support_vector：retrieves a number of supportvectors and the particular vector；
128. CvSVM::get_var_count：returns thenumber of used features(variables count)；
129. CvANN_MLP(multi-layerperceptrons)::CvANN_MLP：the constructors；
130. CvANN_MLP::create：constructs MLP with the specifiedtopology；
131. CvANN_MLP::train：trains/updates MLP；
132. CvANN_MLP::predict：predicts responses for inputsamples；
133. CvANN_MLP::get_layer_count：returns the number fo layers inthe MLP；
134. CvANN_MLP::get_layer_size：returns numbers of neurons in eachlayer of the MLP；
135. CvANN_MLP::get_weights：returns neurons weights of theparticular layer；
136. CvKNearest::CvKNearest：default and training constructors；
137. CvKNearest::train：trains the model；
138. CvKNearest::find_nearest：finds the neighbors and predictsresponses for input vectors；
139. CvKNearest::get_max_k：returns the number of maximumneighbors that may be passed to the method CvKNearest::find_nearest()；
140. CvKNearest::get_var_count：returns the number of usedfeatures(variables count)；
141. CvKNearest::get_sample_count：returns the total number of trainsamples；
142. CvKNearest::is_regression：returns type of the problem(truefor regression and false for classification)；
143. HoughLines(cvHoughLines)：finds lines in a binary imageusing the standard Hough transform；
144. HoughLinesP：finds line segments in a binaryimage using the probabilistic Hough transform；
145. HoughCircles(cvHoughCircles)：finds circles in a grayscale imageusing the Hough transform；
146. line(cvLine)：draws a line segment connectingtwo points；
147. fitLine(cvFitLine)：fits a line to a 2D or 3D pointset；
148. fitEllipse(cvFitEllipse2)：fits an ellipse around a set of 2Dpoints；
149. ellipse(cvEllipse、cvEllipseBox)：draws a simple or thick ellipticarc or fills an ellipse sector；
150. boundingRect(cvBoundingRect)：calculatesthe up-right bounding rectangle of a point set；
151. rectangle(cvRectangle)：draws a simple, thick, or filledup-right rectangle；
152. minEnclosingCircle(cvMinEnclosingCircle)：finds acircle of the minimum area enclosing a 2D point set；
153. circle(cvCircle)：draw a circle；
154. fillPoly：fills the area bounded by one ormore polygons；
155. approxPolyDP(cvApproxPoly)：approximates a polygonal curve(s)with the specified precision；
156. pointPolygonTest(cvPointPolygonTest)：performs a point-in-contour test(判断点在多边形中的位置)；
157. convexHull(cvConvexHull2)：finds the convex hull of a pointset；
158. transpose(cvTranspose)：transposes a matrix；
159. invert(cvInvert)：finds the inverse orpseudo-inverse of a matrix；
160. getStructuringElement(cvCreateStructuringElementEx)：returns a structuring element ofthe specified size and shape for morphological operations；

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