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Merge pull request #9235 from sturkmen72:patch-3
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c95a97389d
@ -273,6 +273,9 @@ of p and len.
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*/
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CV_EXPORTS_W int borderInterpolate(int p, int len, int borderType);
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/** @example copyMakeBorder_demo.cpp
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An example using copyMakeBorder function
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*/
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/** @brief Forms a border around an image.
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The function copies the source image into the middle of the destination image. The areas to the
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@ -471,6 +474,9 @@ The function can also be emulated with a matrix expression, for example:
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*/
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CV_EXPORTS_W void scaleAdd(InputArray src1, double alpha, InputArray src2, OutputArray dst);
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/** @example AddingImagesTrackbar.cpp
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*/
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/** @brief Calculates the weighted sum of two arrays.
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The function addWeighted calculates the weighted sum of two arrays as follows:
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|
@ -2795,6 +2795,9 @@ CV_EXPORTS_W void adaptiveThreshold( InputArray src, OutputArray dst,
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//! @addtogroup imgproc_filter
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//! @{
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/** @example Pyramids.cpp
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An example using pyrDown and pyrUp functions
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*/
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/** @brief Blurs an image and downsamples it.
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By default, size of the output image is computed as `Size((src.cols+1)/2, (src.rows+1)/2)`, but in
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@ -3669,6 +3672,9 @@ enum TemplateMatchModes {
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TM_CCOEFF_NORMED = 5 //!< \f[R(x,y)= \frac{ \sum_{x',y'} (T'(x',y') \cdot I'(x+x',y+y')) }{ \sqrt{\sum_{x',y'}T'(x',y')^2 \cdot \sum_{x',y'} I'(x+x',y+y')^2} }\f]
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};
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/** @example MatchTemplate_Demo.cpp
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An example using Template Matching algorithm
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*/
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/** @brief Compares a template against overlapped image regions.
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The function slides through image , compares the overlapped patches of size \f$w \times h\f$ against
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@ -4134,6 +4140,9 @@ enum ColormapTypes
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COLORMAP_PARULA = 12 //!< 
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};
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/** @example falsecolor.cpp
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An example using applyColorMap function
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*/
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/** @brief Applies a GNU Octave/MATLAB equivalent colormap on a given image.
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@param src The source image, grayscale or colored of type CV_8UC1 or CV_8UC3.
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@ -4216,6 +4225,9 @@ CV_EXPORTS void rectangle(CV_IN_OUT Mat& img, Rect rec,
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const Scalar& color, int thickness = 1,
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int lineType = LINE_8, int shift = 0);
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/** @example Drawing_2.cpp
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An example using drawing functions
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*/
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/** @brief Draws a circle.
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The function circle draws a simple or filled circle with a given center and radius.
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@ -4339,6 +4351,9 @@ CV_EXPORTS void fillPoly(Mat& img, const Point** pts,
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const Scalar& color, int lineType = LINE_8, int shift = 0,
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Point offset = Point() );
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/** @example Drawing_1.cpp
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An example using drawing functions
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*/
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/** @brief Fills the area bounded by one or more polygons.
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The function fillPoly fills an area bounded by several polygonal contours. The function can fill
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@ -215,6 +215,8 @@ public:
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virtual Ptr<MaskGenerator> getMaskGenerator() = 0;
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};
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/** @example facedetect.cpp
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*/
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/** @brief Cascade classifier class for object detection.
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*/
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class CV_EXPORTS_W CascadeClassifier
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@ -348,6 +350,8 @@ struct DetectionROI
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std::vector<double> confidences;
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};
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/**@example peopledetect.cpp
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*/
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struct CV_EXPORTS_W HOGDescriptor
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{
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public:
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|
@ -730,6 +730,9 @@ CV_EXPORTS_W void decolor( InputArray src, OutputArray grayscale, OutputArray co
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//! @addtogroup photo_clone
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//! @{
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/** @example cloning_demo.cpp
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An example using seamlessClone function
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*/
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/** @brief Image editing tasks concern either global changes (color/intensity corrections, filters,
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deformations) or local changes concerned to a selection. Here we are interested in achieving local
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changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless
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@ -833,6 +836,9 @@ CV_EXPORTS_W void edgePreservingFilter(InputArray src, OutputArray dst, int flag
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CV_EXPORTS_W void detailEnhance(InputArray src, OutputArray dst, float sigma_s = 10,
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float sigma_r = 0.15f);
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/** @example npr_demo.cpp
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An example using non-photorealistic line drawing functions
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*/
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/** @brief Pencil-like non-photorealistic line drawing
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@param src Input 8-bit 3-channel image.
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|
@ -53,6 +53,9 @@ namespace cv
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//! @addtogroup shape
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//! @{
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/** @example shape_example.cpp
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An example using shape distance algorithm
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*/
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/** @brief Abstract base class for shape distance algorithms.
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*/
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class CV_EXPORTS_W ShapeDistanceExtractor : public Algorithm
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|
@ -78,7 +78,9 @@ See the OpenCV sample camshiftdemo.c that tracks colored objects.
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*/
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CV_EXPORTS_W RotatedRect CamShift( InputArray probImage, CV_IN_OUT Rect& window,
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TermCriteria criteria );
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/** @example camshiftdemo.cpp
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An example using the mean-shift tracking algorithm
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*/
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/** @brief Finds an object on a back projection image.
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@param probImage Back projection of the object histogram. See calcBackProject for details.
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@ -97,8 +99,6 @@ projection and remove the noise. For example, you can do this by retrieving conn
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with findContours , throwing away contours with small area ( contourArea ), and rendering the
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remaining contours with drawContours.
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@note
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- A mean-shift tracking sample can be found at opencv_source_code/samples/cpp/camshiftdemo.cpp
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*/
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CV_EXPORTS_W int meanShift( InputArray probImage, CV_IN_OUT Rect& window, TermCriteria criteria );
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@ -123,6 +123,9 @@ CV_EXPORTS_W int buildOpticalFlowPyramid( InputArray img, OutputArrayOfArrays py
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int derivBorder = BORDER_CONSTANT,
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bool tryReuseInputImage = true );
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/** @example lkdemo.cpp
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An example using the Lucas-Kanade optical flow algorithm
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*/
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/** @brief Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
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pyramids.
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@ -258,6 +261,10 @@ enum
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MOTION_HOMOGRAPHY = 3
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};
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/** @example image_alignment.cpp
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An example using the image alignment ECC algorithm
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*/
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/** @brief Finds the geometric transform (warp) between two images in terms of the ECC criterion @cite EP08 .
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@param templateImage single-channel template image; CV_8U or CV_32F array.
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@ -313,25 +320,20 @@ CV_EXPORTS_W double findTransformECC( InputArray templateImage, InputArray input
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TermCriteria criteria = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001),
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InputArray inputMask = noArray());
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/** @example kalman.cpp
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An example using the standard Kalman filter
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*/
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/** @brief Kalman filter class.
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The class implements a standard Kalman filter <http://en.wikipedia.org/wiki/Kalman_filter>,
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@cite Welch95 . However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get
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an extended Kalman filter functionality. See the OpenCV sample kalman.cpp.
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@note
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- An example using the standard Kalman filter can be found at
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opencv_source_code/samples/cpp/kalman.cpp
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an extended Kalman filter functionality.
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@note In C API when CvKalman\* kalmanFilter structure is not needed anymore, it should be released
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with cvReleaseKalman(&kalmanFilter)
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*/
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class CV_EXPORTS_W KalmanFilter
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{
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public:
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/** @brief The constructors.
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@note In C API when CvKalman\* kalmanFilter structure is not needed anymore, it should be released
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with cvReleaseKalman(&kalmanFilter)
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*/
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CV_WRAP KalmanFilter();
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/** @overload
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@param dynamParams Dimensionality of the state.
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|
@ -808,12 +808,12 @@ protected:
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class IVideoWriter;
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/** @example videowriter_basic.cpp
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An example using VideoCapture and VideoWriter class
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*/
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/** @brief Video writer class.
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The class provides C++ API for writing video files or image sequences.
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Here is how the class can be used:
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@include samples/cpp/videowriter_basic.cpp
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*/
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class CV_EXPORTS_W VideoWriter
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{
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|
@ -33,8 +33,6 @@ int flag1 = 0;
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int minx,miny,maxx,maxy,lenx,leny;
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int channel;
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void mouseHandler(int, int, int, int, void*);
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void mouseHandler(int event, int x, int y, int, void*)
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@ -121,14 +119,22 @@ void mouseHandler(int event, int x, int y, int, void*)
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}
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}
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static void help()
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{
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cout << "\nThis program demonstrates using mouse events"
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"\nCall:\n"
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"./create_mask <image_name>\n"
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"\n"
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"\tleft mouse button - set a point to create mask shape"
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"\n"
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"\tright mouse button - create mask from points\n"
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"\tmiddle mouse button - reset\n" << endl;
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}
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int main(int argc, char **argv)
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{
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cv::CommandLineParser parser(argc, argv, "{help h | | show help message}{@input | | input image}");
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if (parser.has("help"))
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{
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parser.printMessage();
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return 0;
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}
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cv::CommandLineParser parser(argc, argv, "{@input | ../data/lena.jpg | input image}");
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help();
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string input_image = parser.get<string>("@input");
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if (input_image.empty())
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{
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@ -143,8 +149,6 @@ int main(int argc, char **argv)
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img0 = src;
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channel = img0.channels();
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res1 = Mat::zeros(img0.size(),CV_8UC1);
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final = Mat::zeros(img0.size(),CV_8UC3);
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//////////// source image ///////////////////
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@ -154,6 +158,5 @@ int main(int argc, char **argv)
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imshow("Source", img0);
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waitKey(0);
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img0.release();
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img1.release();
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return 0;
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}
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|
@ -2,6 +2,7 @@
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#include "opencv2/imgproc.hpp"
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#include "opencv2/highgui.hpp"
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#include <stdio.h>
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using namespace cv;
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static void help()
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@ -16,14 +17,9 @@ static Scalar randomColor(RNG& rng)
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return Scalar(icolor&255, (icolor>>8)&255, (icolor>>16)&255);
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}
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int main(int argc, char** argv)
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{
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cv::CommandLineParser parser(argc, argv, "{help h||}");
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if (parser.has("help"))
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int main()
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{
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help();
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return 0;
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}
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char wndname[] = "Drawing Demo";
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const int NUMBER = 100;
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const int DELAY = 5;
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@ -36,7 +32,7 @@ int main(int argc, char** argv)
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imshow(wndname, image);
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waitKey(DELAY);
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for (i = 0; i < NUMBER; i++)
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for (i = 0; i < NUMBER * 2; i++)
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{
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Point pt1, pt2;
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pt1.x = rng.uniform(x1, x2);
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@ -44,14 +40,19 @@ int main(int argc, char** argv)
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pt2.x = rng.uniform(x1, x2);
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pt2.y = rng.uniform(y1, y2);
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int arrowed = rng.uniform(0, 6);
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if( arrowed < 3 )
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line( image, pt1, pt2, randomColor(rng), rng.uniform(1,10), lineType );
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else
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arrowedLine(image, pt1, pt2, randomColor(rng), rng.uniform(1, 10), lineType);
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imshow(wndname, image);
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if(waitKey(DELAY) >= 0)
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return 0;
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}
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for (i = 0; i < NUMBER; i++)
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for (i = 0; i < NUMBER * 2; i++)
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{
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Point pt1, pt2;
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pt1.x = rng.uniform(x1, x2);
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@ -59,8 +60,13 @@ int main(int argc, char** argv)
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pt2.x = rng.uniform(x1, x2);
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pt2.y = rng.uniform(y1, y2);
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int thickness = rng.uniform(-3, 10);
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int marker = rng.uniform(0, 10);
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int marker_size = rng.uniform(30, 80);
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if (marker > 5)
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rectangle(image, pt1, pt2, randomColor(rng), MAX(thickness, -1), lineType);
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else
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drawMarker(image, pt1, randomColor(rng), marker, marker_size );
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imshow(wndname, image);
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if(waitKey(DELAY) >= 0)
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@ -181,7 +187,3 @@ int main(int argc, char** argv)
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waitKey();
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return 0;
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}
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#ifdef _EiC
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main(1,"drawing.c");
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#endif
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|
@ -52,16 +52,12 @@ const char* keys =
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};
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int main( int argc, const char** argv )
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{
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CommandLineParser parser(argc, argv, keys);
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if (parser.has("help"))
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{
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help();
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return 0;
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}
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CommandLineParser parser(argc, argv, keys);
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string filename = parser.get<string>(0);
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image = imread(filename, 1);
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image = imread(filename, IMREAD_COLOR);
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if(image.empty())
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{
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printf("Cannot read image file: %s\n", filename.c_str());
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|
@ -125,11 +125,15 @@ static Mat DrawMyImage(int thickness,int nbShape)
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return img;
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}
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int main(void)
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int main(int argc, char** argv)
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{
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ParamColorMar p;
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Mat img= DrawMyImage(2,256);
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Mat img;
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if (argc > 1)
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img = imread(argv[1], 0);
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else
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img = DrawMyImage(2,256);
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p.img=img;
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p.iColormap=0;
|
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|
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|
@ -276,12 +276,9 @@ static void on_mouse( int event, int x, int y, int flags, void* param )
|
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|
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int main( int argc, char** argv )
|
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{
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cv::CommandLineParser parser(argc, argv, "{help h||}{@input||}");
|
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if (parser.has("help"))
|
||||
{
|
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cv::CommandLineParser parser(argc, argv, "{@input| ../data/messi5.jpg |}");
|
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help();
|
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return 0;
|
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}
|
||||
|
||||
string filename = parser.get<string>("@input");
|
||||
if( filename.empty() )
|
||||
{
|
||||
@ -295,8 +292,6 @@ int main( int argc, char** argv )
|
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return 1;
|
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}
|
||||
|
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help();
|
||||
|
||||
const string winName = "image";
|
||||
namedWindow( winName, WINDOW_AUTOSIZE );
|
||||
setMouseCallback( winName, on_mouse, 0 );
|
||||
|
@ -51,7 +51,7 @@ const std::string keys =
|
||||
"{e epsilon | 0.0001 | ECC's convergence epsilon }"
|
||||
"{o outputWarp | outWarp.ecc | output warp (matrix) filename }"
|
||||
"{m motionType | affine | type of motion (translation, euclidean, affine, homography) }"
|
||||
"{v verbose | 0 | display initial and final images }"
|
||||
"{v verbose | 1 | display initial and final images }"
|
||||
"{w warpedImfile | warpedECC.png | warped input image }"
|
||||
"{h help | | print help message }"
|
||||
;
|
||||
@ -165,10 +165,10 @@ static void draw_warped_roi(Mat& image, const int width, const int height, Mat&
|
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GET_HOMO_VALUES(U, bottom_right.x, bottom_right.y);
|
||||
|
||||
// draw the warped perimeter
|
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line(image, top_left, top_right, Scalar(255,0,255));
|
||||
line(image, top_right, bottom_right, Scalar(255,0,255));
|
||||
line(image, bottom_right, bottom_left, Scalar(255,0,255));
|
||||
line(image, bottom_left, top_left, Scalar(255,0,255));
|
||||
line(image, top_left, top_right, Scalar(255));
|
||||
line(image, top_right, bottom_right, Scalar(255));
|
||||
line(image, bottom_right, bottom_left, Scalar(255));
|
||||
line(image, bottom_left, top_left, Scalar(255));
|
||||
}
|
||||
|
||||
int main (const int argc, const char * argv[])
|
||||
@ -177,17 +177,9 @@ int main (const int argc, const char * argv[])
|
||||
CommandLineParser parser(argc, argv, keys);
|
||||
parser.about("ECC demo");
|
||||
|
||||
if (argc < 2) {
|
||||
parser.printMessage();
|
||||
help();
|
||||
return 1;
|
||||
}
|
||||
if (parser.has("help"))
|
||||
{
|
||||
parser.printMessage();
|
||||
help();
|
||||
return 1;
|
||||
}
|
||||
|
||||
string imgFile = parser.get<string>(0);
|
||||
string tempImgFile = parser.get<string>(1);
|
||||
string inWarpFile = parser.get<string>(2);
|
||||
@ -239,10 +231,10 @@ int main (const int argc, const char * argv[])
|
||||
}
|
||||
|
||||
}
|
||||
else{ //apply random waro to input image
|
||||
else{ //apply random warp to input image
|
||||
resize(inputImage, target_image, Size(216, 216));
|
||||
Mat warpGround;
|
||||
cv::RNG rng;
|
||||
RNG rng(getTickCount());
|
||||
double angle;
|
||||
switch (mode_temp) {
|
||||
case MOTION_TRANSLATION:
|
||||
@ -299,7 +291,7 @@ int main (const int argc, const char * argv[])
|
||||
}
|
||||
else {
|
||||
|
||||
printf("\n ->Perfomarnce Warning: Identity warp ideally assumes images of "
|
||||
printf("\n ->Performance Warning: Identity warp ideally assumes images of "
|
||||
"similar size. If the deformation is strong, the identity warp may not "
|
||||
"be a good initialization. \n");
|
||||
|
||||
@ -363,7 +355,8 @@ int main (const int argc, const char * argv[])
|
||||
namedWindow ("warped image", WINDOW_AUTOSIZE);
|
||||
namedWindow ("error (black: no error)", WINDOW_AUTOSIZE);
|
||||
|
||||
moveWindow ("template", 350, 350);
|
||||
moveWindow ("image", 20, 300);
|
||||
moveWindow ("template", 300, 300);
|
||||
moveWindow ("warped image", 600, 300);
|
||||
moveWindow ("error (black: no error)", 900, 300);
|
||||
|
||||
|
@ -17,18 +17,13 @@ static void help(char** argv)
|
||||
}
|
||||
|
||||
int main(int argc, char** argv)
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, "{help h||}{@image||}");
|
||||
if (parser.has("help"))
|
||||
{
|
||||
help(argv);
|
||||
return 0;
|
||||
}
|
||||
cv::CommandLineParser parser(argc, argv, "{@image| ../data/left%02d.jpg |}");
|
||||
string first_file = parser.get<string>("@image");
|
||||
|
||||
if(first_file.empty())
|
||||
{
|
||||
help(argv);
|
||||
return 1;
|
||||
}
|
||||
|
||||
|
@ -47,12 +47,9 @@ static void onMouse( int event, int x, int y, int flags, void* )
|
||||
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, "{help h||}{@image|../data/fruits.jpg|}");
|
||||
if (parser.has("help"))
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, "{@image|../data/fruits.jpg|}");
|
||||
help();
|
||||
return 0;
|
||||
}
|
||||
|
||||
string filename = parser.get<string>("@image");
|
||||
Mat img0 = imread(filename, -1);
|
||||
if(img0.empty())
|
||||
|
@ -26,12 +26,9 @@ int smoothType = GAUSSIAN;
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
VideoCapture cap;
|
||||
cv::CommandLineParser parser(argc, argv, "{help h | | }{ c | 0 | }{ p | | }");
|
||||
if ( parser.has("help") )
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, "{ c | 0 | }{ p | | }");
|
||||
help();
|
||||
return 0;
|
||||
}
|
||||
|
||||
if( parser.get<string>("c").size() == 1 && isdigit(parser.get<string>("c")[0]) )
|
||||
cap.open(parser.get<int>("c"));
|
||||
else
|
||||
|
@ -521,7 +521,7 @@ int main( int argc, char *argv[] )
|
||||
int method = 0;
|
||||
|
||||
cv::CommandLineParser parser(argc, argv, "{data|../data/letter-recognition.data|}{save||}{load||}{boost||}"
|
||||
"{mlp||}{knn knearest||}{nbayes||}{svm||}{help h||}");
|
||||
"{mlp||}{knn knearest||}{nbayes||}{svm||}");
|
||||
data_filename = parser.get<string>("data");
|
||||
if (parser.has("save"))
|
||||
filename_to_save = parser.get<string>("save");
|
||||
@ -537,11 +537,9 @@ int main( int argc, char *argv[] )
|
||||
method = 4;
|
||||
else if (parser.has("svm"))
|
||||
method = 5;
|
||||
if (parser.has("help"))
|
||||
{
|
||||
|
||||
help();
|
||||
return 0;
|
||||
}
|
||||
|
||||
if( (method == 0 ?
|
||||
build_rtrees_classifier( data_filename, filename_to_save, filename_to_load ) :
|
||||
method == 1 ?
|
||||
@ -555,8 +553,6 @@ int main( int argc, char *argv[] )
|
||||
method == 5 ?
|
||||
build_svm_classifier( data_filename, filename_to_save, filename_to_load ):
|
||||
-1) < 0)
|
||||
{
|
||||
help();
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
@ -45,16 +45,11 @@ int main( int argc, char** argv )
|
||||
bool needToInit = false;
|
||||
bool nightMode = false;
|
||||
|
||||
cv::CommandLineParser parser(argc, argv, "{@input||}{help h||}");
|
||||
string input = parser.get<string>("@input");
|
||||
if (parser.has("help"))
|
||||
{
|
||||
help();
|
||||
return 0;
|
||||
}
|
||||
if( input.empty() )
|
||||
cap.open(0);
|
||||
else if( input.size() == 1 && isdigit(input[0]) )
|
||||
cv::CommandLineParser parser(argc, argv, "{@input|0|}");
|
||||
string input = parser.get<string>("@input");
|
||||
|
||||
if( input.size() == 1 && isdigit(input[0]) )
|
||||
cap.open(input[0] - '0');
|
||||
else
|
||||
cap.open(input);
|
||||
|
@ -19,16 +19,12 @@ static void help()
|
||||
|
||||
int main( int argc, const char** argv )
|
||||
{
|
||||
help();
|
||||
cv::CommandLineParser parser(argc, argv,
|
||||
"{help h||}"
|
||||
"{ i | ../data/lena_tmpl.jpg | }"
|
||||
"{ t | ../data/tmpl.png | }"
|
||||
"{ m | ../data/mask.png | }");
|
||||
if (parser.has("help"))
|
||||
{
|
||||
help();
|
||||
return 0;
|
||||
}
|
||||
|
||||
string filename = parser.get<string>("i");
|
||||
string tmplname = parser.get<string>("t");
|
||||
string maskname = parser.get<string>("m");
|
||||
|
@ -28,7 +28,7 @@ using namespace cv;
|
||||
|
||||
int main(int argc, char* argv[])
|
||||
{
|
||||
cv::CommandLineParser parser(argc, argv, "{help h||show help message}{@image||input image}");
|
||||
cv::CommandLineParser parser(argc, argv, "{help h||show help message}{@image|../data/lena.jpg|input image}");
|
||||
if (parser.has("help"))
|
||||
{
|
||||
parser.printMessage();
|
||||
|
@ -53,14 +53,13 @@ int main( int argc, char** argv )
|
||||
break;
|
||||
|
||||
Point2f center( (float)frame.cols / 2, (float)frame.rows / 2 );
|
||||
double radius = (double)frame.cols / 4;
|
||||
double M = (double)frame.cols / log(radius);
|
||||
double M = 70;
|
||||
|
||||
logPolar(frame,log_polar_img, center, M, INTER_LINEAR + WARP_FILL_OUTLIERS);
|
||||
linearPolar(frame,lin_polar_img, center, radius, INTER_LINEAR + WARP_FILL_OUTLIERS);
|
||||
linearPolar(frame,lin_polar_img, center, M, INTER_LINEAR + WARP_FILL_OUTLIERS);
|
||||
|
||||
logPolar(log_polar_img, recovered_log_polar, center, M, WARP_INVERSE_MAP + INTER_LINEAR);
|
||||
linearPolar(lin_polar_img, recovered_lin_polar_img, center, radius, WARP_INVERSE_MAP + INTER_LINEAR + WARP_FILL_OUTLIERS);
|
||||
linearPolar(lin_polar_img, recovered_lin_polar_img, center, M, WARP_INVERSE_MAP + INTER_LINEAR + WARP_FILL_OUTLIERS);
|
||||
|
||||
imshow("Log-Polar", log_polar_img );
|
||||
imshow("Linear-Polar", lin_polar_img );
|
||||
|
@ -115,6 +115,7 @@ int main(int argc, char** argv)
|
||||
resize(iiIm, bestToShow, sz2Sh);
|
||||
imshow("BEST MATCH", bestToShow);
|
||||
moveWindow("BEST MATCH", sz2Sh.width+50,0);
|
||||
waitKey();
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
@ -40,10 +40,15 @@ static void on_trackbar( int, void* )
|
||||
* @function main
|
||||
* @brief Main function
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
/// Read image given by user
|
||||
image = imread( argv[1] );
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
image = imread( imageName );
|
||||
|
||||
/// Initialize values
|
||||
alpha = 1;
|
||||
@ -54,8 +59,8 @@ int main( int, char** argv )
|
||||
namedWindow("New Image", 1);
|
||||
|
||||
/// Create Trackbars
|
||||
createTrackbar( "Contrast Trackbar", "New Image", &alpha, alpha_max, on_trackbar );
|
||||
createTrackbar( "Brightness Trackbar", "New Image", &beta, beta_max, on_trackbar );
|
||||
createTrackbar( "Contrast", "New Image", &alpha, alpha_max, on_trackbar );
|
||||
createTrackbar( "Brightness", "New Image", &beta, beta_max, on_trackbar );
|
||||
|
||||
/// Show some stuff
|
||||
imshow("Original Image", image);
|
||||
|
@ -15,7 +15,7 @@ using namespace cv;
|
||||
* @function main
|
||||
* @brief Main function
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//! [basic-linear-transform-parameters]
|
||||
double alpha = 1.0; /*< Simple contrast control */
|
||||
@ -24,7 +24,12 @@ int main( int, char** argv )
|
||||
|
||||
/// Read image given by user
|
||||
//! [basic-linear-transform-load]
|
||||
Mat image = imread( argv[1] );
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
Mat image = imread( imageName );
|
||||
//! [basic-linear-transform-load]
|
||||
//! [basic-linear-transform-output]
|
||||
Mat new_image = Mat::zeros( image.size(), image.type() );
|
||||
|
@ -29,10 +29,15 @@ void Morphology_Operations( int, void* );
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//![load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/baboon.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread(imageName, IMREAD_COLOR); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{ return -1; }
|
||||
|
@ -30,10 +30,15 @@ void Threshold_Demo( int, void* );
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//! [load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/stuff.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR ); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{ return -1; }
|
||||
|
@ -58,9 +58,16 @@ void on_gamma_correction_trackbar(int, void *)
|
||||
}
|
||||
}
|
||||
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
img_original = imread( argv[1] );
|
||||
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
|
||||
img_original = imread( imageName );
|
||||
img_corrected = Mat(img_original.rows, img_original.cols*2, img_original.type());
|
||||
img_gamma_corrected = Mat(img_original.rows, img_original.cols*2, img_original.type());
|
||||
|
||||
|
@ -21,7 +21,7 @@ namespace
|
||||
const std::string usage = "Usage : tutorial_HoughCircle_Demo <path_to_input_image>\n";
|
||||
|
||||
// initial and max values of the parameters of interests.
|
||||
const int cannyThresholdInitialValue = 200;
|
||||
const int cannyThresholdInitialValue = 100;
|
||||
const int accumulatorThresholdInitialValue = 50;
|
||||
const int maxAccumulatorThreshold = 200;
|
||||
const int maxCannyThreshold = 255;
|
||||
@ -55,15 +55,13 @@ int main(int argc, char** argv)
|
||||
{
|
||||
Mat src, src_gray;
|
||||
|
||||
if (argc < 2)
|
||||
{
|
||||
std::cerr<<"No input image specified\n";
|
||||
std::cout<<usage;
|
||||
return -1;
|
||||
}
|
||||
|
||||
// Read the image
|
||||
src = imread( argv[1], IMREAD_COLOR );
|
||||
String imageName("../data/stuff.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR );
|
||||
|
||||
if( src.empty() )
|
||||
{
|
||||
|
@ -35,10 +35,15 @@ void Probabilistic_Hough( int, void* );
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
/// Read the image
|
||||
src = imread( argv[1], IMREAD_COLOR );
|
||||
// Read the image
|
||||
String imageName("../data/building.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR );
|
||||
|
||||
if( src.empty() )
|
||||
{ help();
|
||||
|
@ -13,7 +13,7 @@ using namespace cv;
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//![variables]
|
||||
Mat src, src_gray, dst;
|
||||
@ -25,7 +25,12 @@ int main( int, char** argv )
|
||||
//![variables]
|
||||
|
||||
//![load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR ); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{ return -1; }
|
||||
|
@ -23,10 +23,12 @@ void update_map( void );
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main(int argc, const char** argv)
|
||||
{
|
||||
/// Load the image
|
||||
src = imread( argv[1], IMREAD_COLOR );
|
||||
CommandLineParser parser(argc, argv, "{@image |../data/chicky_512.png|input image name}");
|
||||
std::string filename = parser.get<std::string>(0);
|
||||
src = imread( filename, IMREAD_COLOR );
|
||||
|
||||
/// Create dst, map_x and map_y with the same size as src:
|
||||
dst.create( src.size(), src.type() );
|
||||
|
@ -13,7 +13,7 @@ using namespace cv;
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//![variables]
|
||||
Mat src, src_gray;
|
||||
@ -25,7 +25,12 @@ int main( int, char** argv )
|
||||
//![variables]
|
||||
|
||||
//![load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR ); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{ return -1; }
|
||||
|
@ -21,10 +21,15 @@ RNG rng(12345);
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
//![load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR ); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{
|
||||
|
@ -13,7 +13,7 @@ using namespace cv;
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main ( int, char** argv )
|
||||
int main ( int argc, char** argv )
|
||||
{
|
||||
/// Declare variables
|
||||
Mat src, dst;
|
||||
@ -26,7 +26,12 @@ int main ( int, char** argv )
|
||||
const char* window_name = "filter2D Demo";
|
||||
|
||||
//![load]
|
||||
src = imread( argv[1], IMREAD_COLOR ); // Load an image
|
||||
String imageName("../data/lena.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread( imageName, IMREAD_COLOR ); // Load an image
|
||||
|
||||
if( src.empty() )
|
||||
{ return -1; }
|
||||
|
@ -10,11 +10,11 @@
|
||||
using namespace std;
|
||||
using namespace cv;
|
||||
|
||||
int main(int, char** argv)
|
||||
int main()
|
||||
{
|
||||
//! [load_image]
|
||||
// Load the image
|
||||
Mat src = imread(argv[1]);
|
||||
Mat src = imread("../data/cards.png");
|
||||
|
||||
// Check if everything was fine
|
||||
if (!src.data)
|
||||
|
@ -23,10 +23,16 @@ void thresh_callback(int, void* );
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main( int, char** argv )
|
||||
int main( int argc, char** argv )
|
||||
{
|
||||
/// Load source image
|
||||
src = imread(argv[1], IMREAD_COLOR);
|
||||
String imageName("../data/happyfish.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
src = imread(imageName, IMREAD_COLOR);
|
||||
|
||||
if (src.empty())
|
||||
{
|
||||
cerr << "No image supplied ..." << endl;
|
||||
|
@ -19,14 +19,13 @@ void readme();
|
||||
* @function main
|
||||
* @brief Main function
|
||||
*/
|
||||
int main( int argc, char** argv )
|
||||
int main()
|
||||
{
|
||||
if( argc != 3 )
|
||||
{ readme(); return -1; }
|
||||
readme();
|
||||
|
||||
//-- 1. Read the images
|
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Mat imgLeft = imread( argv[1], IMREAD_GRAYSCALE );
|
||||
Mat imgRight = imread( argv[2], IMREAD_GRAYSCALE );
|
||||
Mat imgLeft = imread( "../data/rubberwhale1.png", IMREAD_GRAYSCALE );
|
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Mat imgRight = imread( "../data/rubberwhale2.png", IMREAD_GRAYSCALE );
|
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//-- And create the image in which we will save our disparities
|
||||
Mat imgDisparity16S = Mat( imgLeft.rows, imgLeft.cols, CV_16S );
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Mat imgDisparity8U = Mat( imgLeft.rows, imgLeft.cols, CV_8UC1 );
|
||||
|
@ -63,7 +63,7 @@ int main(void)
|
||||
|
||||
Mat res;
|
||||
drawMatches(img1, inliers1, img2, inliers2, good_matches, res);
|
||||
imwrite("res.png", res);
|
||||
imwrite("akaze_result.png", res);
|
||||
|
||||
double inlier_ratio = inliers1.size() * 1.0 / matched1.size();
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cout << "A-KAZE Matching Results" << endl;
|
||||
@ -75,5 +75,8 @@ int main(void)
|
||||
cout << "# Inliers Ratio: \t" << inlier_ratio << endl;
|
||||
cout << endl;
|
||||
|
||||
imshow("result", res);
|
||||
waitKey();
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
@ -120,27 +120,27 @@ Mat Tracker::process(const Mat frame, Stats& stats)
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
if(argc < 2) {
|
||||
cerr << "Usage: " << endl
|
||||
<< "akaze_track input_path" << endl
|
||||
<< " (input_path can be a camera id, like 0,1,2 or a video filename)" << endl;
|
||||
return 1;
|
||||
}
|
||||
|
||||
std::string video_name = argv[1];
|
||||
std::stringstream ssFormat;
|
||||
ssFormat << atoi(argv[1]);
|
||||
CommandLineParser parser(argc, argv, "{@input_path |0|input path can be a camera id, like 0,1,2 or a video filename}");
|
||||
string input_path = parser.get<string>(0);
|
||||
string video_name = input_path;
|
||||
|
||||
VideoCapture video_in;
|
||||
if (video_name.compare(ssFormat.str())==0) { //test str==str(num)
|
||||
video_in.open(atoi(argv[1]));
|
||||
|
||||
if ( ( isdigit(input_path[0]) && input_path.size() == 1 ) )
|
||||
{
|
||||
int camera_no = input_path[0] - '0';
|
||||
video_in.open( camera_no );
|
||||
}
|
||||
else {
|
||||
video_in.open(video_name);
|
||||
}
|
||||
|
||||
if(!video_in.isOpened()) {
|
||||
cerr << "Couldn't open " << argv[1] << endl;
|
||||
cerr << "Couldn't open " << video_name << endl;
|
||||
return 1;
|
||||
}
|
||||
|
||||
|
@ -94,12 +94,16 @@ double getOrientation(const vector<Point> &pts, Mat &img)
|
||||
/**
|
||||
* @function main
|
||||
*/
|
||||
int main(int, char** argv)
|
||||
int main(int argc, char** argv)
|
||||
{
|
||||
//! [pre-process]
|
||||
// Load image
|
||||
// Mat src = imread("pca_test1.jpg");
|
||||
Mat src = imread(argv[1]);
|
||||
String imageName("../data/pca_test1.jpg"); // by default
|
||||
if (argc > 1)
|
||||
{
|
||||
imageName = argv[1];
|
||||
}
|
||||
Mat src = imread( imageName );
|
||||
|
||||
// Check if image is loaded successfully
|
||||
if(!src.data || src.empty())
|
||||
|
@ -81,7 +81,7 @@ int main(void)
|
||||
|
||||
Mat res;
|
||||
drawMatches(img1, inliers1, img2, inliers2, good_matches, res);
|
||||
imwrite("../../samples/data/latch_res.png", res);
|
||||
imwrite("latch_result.png", res);
|
||||
|
||||
|
||||
double inlier_ratio = inliers1.size() * 1.0 / matched1.size();
|
||||
@ -93,6 +93,10 @@ int main(void)
|
||||
cout << "# Inliers: \t" << inliers1.size() << endl;
|
||||
cout << "# Inliers Ratio: \t" << inlier_ratio << endl;
|
||||
cout << endl;
|
||||
|
||||
imshow("result", res);
|
||||
waitKey();
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user