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Move C API of opencv_calib3d to separate file

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This commit is contained in:
Andrey Kamaev
2013-04-11 19:27:54 +04:00
parent 199a35a105
commit e5a33723fc
70 changed files with 836 additions and 792 deletions
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10
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
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@@ -115,7 +115,7 @@ calibrateCamera
---------------
Finds the camera intrinsic and extrinsic parameters from several views of a calibration pattern.
.. ocv:function:: double calibrateCamera( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria( TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON) )
.. ocv:function:: double calibrateCamera( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs, OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs, int flags=0, TermCriteria criteria=TermCriteria( TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON) )
.. ocv:pyfunction:: cv2.calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix, distCoeffs[, rvecs[, tvecs[, flags[, criteria]]]]) -> retval, cameraMatrix, distCoeffs, rvecs, tvecs
@@ -454,7 +454,7 @@ findChessboardCorners
-------------------------
Finds the positions of internal corners of the chessboard.
.. ocv:function:: bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners, int flags=CALIB_CB_ADAPTIVE_THRESH+CALIB_CB_NORMALIZE_IMAGE )
.. ocv:function:: bool findChessboardCorners( InputArray image, Size patternSize, OutputArray corners, int flags=CALIB_CB_ADAPTIVE_THRESH + CALIB_CB_NORMALIZE_IMAGE )
.. ocv:pyfunction:: cv2.findChessboardCorners(image, patternSize[, corners[, flags]]) -> retval, corners
@@ -515,7 +515,7 @@ Finds centers in the grid of circles.
.. ocv:function:: bool findCirclesGrid( InputArray image, Size patternSize, OutputArray centers, int flags=CALIB_CB_SYMMETRIC_GRID, const Ptr<FeatureDetector> &blobDetector = new SimpleBlobDetector() )
.. ocv:pyfunction:: cv2.findCirclesGridDefault(image, patternSize[, centers[, flags]]) -> retval, centers
.. ocv:pyfunction:: cv2.findCirclesGrid(image, patternSize[, centers[, flags[, blobDetector]]]) -> retval, centers
:param image: grid view of input circles; it must be an 8-bit grayscale or color image.
@@ -694,7 +694,7 @@ findEssentialMat
------------------
Calculates an essential matrix from the corresponding points in two images.
.. ocv:function:: Mat findEssentialMat( InputArray points1, InputArray points2, double focal=1.0, Point2d pp=Point2d(0, 0), int method=CV_RANSAC, double prob=0.999, double threshold=1.0, OutputArray mask=noArray() )
.. ocv:function:: Mat findEssentialMat( InputArray points1, InputArray points2, double focal=1.0, Point2d pp=Point2d(0, 0), int method=RANSAC, double prob=0.999, double threshold=1.0, OutputArray mask=noArray() )
:param points1: Array of ``N`` ``(N >= 5)`` 2D points from the first image. The point coordinates should be floating-point (single or double precision).
@@ -975,7 +975,7 @@ initCameraMatrix2D
----------------------
Finds an initial camera matrix from 3D-2D point correspondences.
.. ocv:function:: Mat initCameraMatrix2D( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, double aspectRatio=1.)
.. ocv:function:: Mat initCameraMatrix2D( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints, Size imageSize, double aspectRatio=1.0 )
.. ocv:pyfunction:: cv2.initCameraMatrix2D(objectPoints, imagePoints, imageSize[, aspectRatio]) -> retval