generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Unified handling of InputOutputArrays in Python wrapper generator

Browse Source 
This makes arguments of type InputOutputArray required in python unless they
have a default value in C++.

As result following python functions changes signatures in non-trivial way:

* calcOpticalFlowFarneback
* calcOpticalFlowPyrLK
* calibrateCamera
* findContours
* findTransformECC
* floodFill
* kmeans
* PCACompute
* stereoCalibrate

And the following functions become return their modified inputs as a return
value:

* accumulate
* accumulateProduct
* accumulateSquare
* accumulateWeighted
* circle
* completeSymm
* cornerSubPix
* drawChessboardCorners
* drawContours
* drawDataMatrixCodes
* ellipse
* fillConvexPoly
* fillPoly
* filterSpeckles
* grabCut
* insertChannel
* line
* patchNaNs
* polylines
* randn
* randShuffle
* randu
* rectangle
* setIdentity
* updateMotionHistory
* validateDisparity
* watershed
This commit is contained in:
Andrey Kamaev
2013-03-15 16:55:58 +04:00
parent a1c456b7c3
commit e75df56317
18 changed files with 51 additions and 47 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
View File

@@ -117,7 +117,7 @@ Finds the camera intrinsic and extrinsic parameters from several views of a cali
.. 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
.. ocv:pyfunction:: cv2.calibrateCamera(objectPoints, imagePoints, imageSize, cameraMatrix, distCoeffs[, rvecs[, tvecs[, flags[, criteria]]]]) -> retval, cameraMatrix, distCoeffs, rvecs, tvecs
.. ocv:cfunction:: double cvCalibrateCamera2( const CvMat* object_points, const CvMat* image_points, const CvMat* point_counts, CvSize image_size, CvMat* camera_matrix, CvMat* distortion_coeffs, CvMat* rotation_vectors=NULL, CvMat* translation_vectors=NULL, int flags=0, CvTermCriteria term_crit=cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,DBL_EPSILON) )
@@ -433,7 +433,7 @@ Renders the detected chessboard corners.
.. ocv:function:: void drawChessboardCorners( InputOutputArray image, Size patternSize, InputArray corners, bool patternWasFound )
.. ocv:pyfunction:: cv2.drawChessboardCorners(image, patternSize, corners, patternWasFound) -> None
.. ocv:pyfunction:: cv2.drawChessboardCorners(image, patternSize, corners, patternWasFound) -> image
.. ocv:cfunction:: void cvDrawChessboardCorners( CvArr* image, CvSize pattern_size, CvPoint2D32f* corners, int count, int pattern_was_found )
.. ocv:pyoldfunction:: cv.DrawChessboardCorners(image, patternSize, corners, patternWasFound)-> None
@@ -923,7 +923,7 @@ Filters off small noise blobs (speckles) in the disparity map
.. ocv:function:: void filterSpeckles( InputOutputArray img, double newVal, int maxSpeckleSize, double maxDiff, InputOutputArray buf=noArray() )
.. ocv:pyfunction:: cv2.filterSpeckles(img, newVal, maxSpeckleSize, maxDiff[, buf]) -> None
.. ocv:pyfunction:: cv2.filterSpeckles(img, newVal, maxSpeckleSize, maxDiff[, buf]) -> img, buf
:param img: The input 16-bit signed disparity image
@@ -1362,7 +1362,7 @@ Calibrates the stereo camera.
.. ocv:function:: double stereoCalibrate( InputArrayOfArrays objectPoints, InputArrayOfArrays imagePoints1, InputArrayOfArrays imagePoints2, InputOutputArray cameraMatrix1, InputOutputArray distCoeffs1, InputOutputArray cameraMatrix2, InputOutputArray distCoeffs2, Size imageSize, OutputArray R, OutputArray T, OutputArray E, OutputArray F, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 1e-6), int flags=CALIB_FIX_INTRINSIC )
.. ocv:pyfunction:: cv2.stereoCalibrate(objectPoints, imagePoints1, imagePoints2, imageSize[, cameraMatrix1[, distCoeffs1[, cameraMatrix2[, distCoeffs2[, R[, T[, E[, F[, criteria[, flags]]]]]]]]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F
.. ocv:pyfunction:: cv2.stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize[, R[, T[, E[, F[, criteria[, flags]]]]]]) -> retval, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, R, T, E, F
.. ocv:cfunction:: double cvStereoCalibrate( const CvMat* object_points, const CvMat* image_points1, const CvMat* image_points2, const CvMat* npoints, CvMat* camera_matrix1, CvMat* dist_coeffs1, CvMat* camera_matrix2, CvMat* dist_coeffs2, CvSize image_size, CvMat* R, CvMat* T, CvMat* E=0, CvMat* F=0, CvTermCriteria term_crit=cvTermCriteria( CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,30,1e-6), int flags=CV_CALIB_FIX_INTRINSIC )