mirror of
https://github.com/wassname/scikit-image.git
synced 2026-08-12 12:30:16 +08:00
added cvFindExtrinsicCameraParams2 and cvWatershed
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sccolbert
@@ -259,6 +259,11 @@ ctypedef void (*cvPyrUpPtr)(IplImage*, IplImage*, int)
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cdef cvPyrUpPtr c_cvPyrUp
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c_cvPyrUp = (<cvPyrUpPtr*><size_t>ctypes.addressof(cv.cvPyrUp))[0]
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# cvWatershed
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ctypedef void (*cvWatershedPtr)(IplImage*, IplImage*)
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cdef cvWatershedPtr c_cvWatershed
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c_cvWatershed = (<cvWatershedPtr*><size_t>ctypes.addressof(cv.cvWatershed))[0]
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# cvCalibrateCamera2
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ctypedef void (*cvCalibrateCamera2Ptr)(CvMat*, CvMat*, CvMat*,
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CvSize, CvMat*, CvMat*, CvMat*, CvMat*, int)
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@@ -278,6 +283,14 @@ cdef cvFindChessboardCornersPtr c_cvFindChessboardCorners
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c_cvFindChessboardCorners = (<cvFindChessboardCornersPtr*><size_t>
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ctypes.addressof(cv.cvFindChessboardCorners))[0]
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# cvFindExtrinsicCameraParams2
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ctypedef void (*cvFindExtrinsicCameraParams2Ptr)(CvMat*, CvMat*, CvMat*, CvMat*,
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CvMat*, CvMat*, int)
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cdef cvFindExtrinsicCameraParams2Ptr c_cvFindExtrinsicCameraParams2
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c_cvFindExtrinsicCameraParams2 = \
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(<cvFindExtrinsicCameraParams2Ptr*><size_t>
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ctypes.addressof(cv.cvFindExtrinsicCameraParams2))[0]
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# cvDrawChessboardCorners
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ctypedef void (*cvDrawChessboardCornersPtr)(IplImage*, CvSize, CvPoint2D32f*,
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int, int)
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@@ -2068,6 +2081,54 @@ def cvPyrUp(np.ndarray src):
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return out
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#------------
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# cvWatershed
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#------------
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@cvdoc(package='cv', group='image', doc=\
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'''cvWatershed(src, markers)
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Performs watershed segmentation.
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Parameters
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----------
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src : ndarray, 3D, dtype=uint8
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The source image.
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markers : ndarray, 2D, dtype=int32
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The markers identifying the regions of interest.
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Marker values should be non-zero.
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This array should have the same width and height as src.
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Returns
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-------
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None : None
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The markers array is modified in place. The results of which
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identify the segmented regions of the image.''')
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def cvWatershed(src, markers):
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validate_array(src)
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validate_array(markers)
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assert_ndims(src, [3])
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assert_dtype(src, [UINT8])
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assert_ndims(markers, [2])
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assert_dtype(markers, [INT32])
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#assert src.shape[:2] == markers.shape[:2], \
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# 'The src and markers array must have same width and height'
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cdef IplImage srcimg
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cdef IplImage markersimg
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populate_iplimage(src, &srcimg)
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populate_iplimage(markers, &markersimg)
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c_cvWatershed(&srcimg, &markersimg)
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return None
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#-------------------
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# cvCalibrateCamera2
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#-------------------
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@@ -2279,6 +2340,102 @@ def cvFindChessboardCorners(np.ndarray src, pattern_size,
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return out[:ncorners_found]
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#-----------------------------
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# cvFindExtrinsicCameraParams2
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#-----------------------------
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@cvdoc(package='cv', group='calibration', doc=\
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'''cvFindExtrinsicCameraParams2(object_points, image_points, intrinsic_matrix,
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distortion_coeffs)
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Calculates the extrinsic camera parameters given a set of 3D points, their
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2D locations in the image, and the camera instrinsics matrix and distortion
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coefficients.
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i.e. given this information, it calculates the offset and rotation of the
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camera from the chessboard origin.
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Parameters
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----------
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object_points: ndarray, nx3
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The 3D coordinates of the chessboard corners.
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image_points: ndarray, nx2
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The 2D image coordinates of the object_points
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intrinsic_matrix: ndarray, 3x3, dtype=float64
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The 2D camera intrinsics matrix that is the result of camera calibration
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distortion_coeffs: ndarray, 5-vector, dtype=float64
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The 5 distortion coefficients that are the result of camera calibration
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Returns
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-------
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(rvec, tvec): ndarray 3-vector dtype=float64, ndarray 3-vector dtype=float64
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rvec - the rotation vector representing the rotation of the camera
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relative to the chessboard. The direction of the vector represents the
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axis of rotation and its magnitude the amount of rotation.
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tvec - the translation vector representing the offset of the camera
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relative to the chessboard origin.''')
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def cvFindExtrinsicCameraParams2(object_points, image_points, intrinsic_matrix,
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distortion_coeffs):
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validate_array(object_points)
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validate_array(image_points)
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validate_array(intrinsic_matrix)
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assert_ndims(object_points, [2])
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assert_dtype(object_points, [FLOAT32, FLOAT64])
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assert object_points.shape[1] == 3, 'object_points should be nx3'
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assert_ndims(image_points, [2])
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assert_dtype(image_points, [FLOAT32, FLOAT64])
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assert image_points.shape[1] == 2, 'image_points should be nx2'
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assert_dtype(intrinsic_matrix, [FLOAT64])
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assert intrinsic_matrix.shape == (3, 3), 'instrinsics should be 3x3'
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assert_dtype(distortion_coeffs, [FLOAT64])
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assert distortion_coeffs.shape == (5,), 'distortions should be 5-vector'
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# allocate the numpy return arrays
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cdef np.npy_intp shape[1]
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shape[0] = 3
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cdef np.ndarray rvec = new_array(1, shape, FLOAT64)
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cdef np.ndarray tvec = new_array(1, shape, FLOAT64)
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# allocate the cv images
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cdef IplImage obj_img
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cdef IplImage img_img
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cdef IplImage intr_img
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cdef IplImage dist_img
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cdef IplImage rot_img
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cdef IplImage tran_img
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populate_iplimage(object_points, &obj_img)
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populate_iplimage(image_points, &img_img)
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populate_iplimage(intrinsic_matrix, &intr_img)
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populate_iplimage(distortion_coeffs, &dist_img)
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populate_iplimage(rvec, &rot_img)
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populate_iplimage(tvec, &tran_img)
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# allocate the cv mats
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cdef CvMat* cvobj = cvmat_ptr_from_iplimage(&obj_img)
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cdef CvMat* cvimg = cvmat_ptr_from_iplimage(&img_img)
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cdef CvMat* cvint = cvmat_ptr_from_iplimage(&intr_img)
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cdef CvMat* cvdis = cvmat_ptr_from_iplimage(&dist_img)
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cdef CvMat* cvrot = cvmat_ptr_from_iplimage(&rot_img)
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cdef CvMat* cvtrn = cvmat_ptr_from_iplimage(&tran_img)
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# the last argument is new to OpenCV 2.0 and tells it NOT to use
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# an extrinsics guess
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c_cvFindExtrinsicCameraParams2(cvobj, cvimg, cvint, cvdis, cvrot, cvtrn, 0)
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PyMem_Free(cvobj)
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PyMem_Free(cvimg)
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PyMem_Free(cvint)
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PyMem_Free(cvdis)
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PyMem_Free(cvrot)
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PyMem_Free(cvtrn)
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return (rvec, tvec)
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#------------------------
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# cvFindChessboardCorners
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#------------------------
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