Found solution at https://github.com/opencv/opencv/issues/4943
OpenCV Error:
Assertion failed (CV_IS_MAT(_src) && CV_IS_MAT(_dst) && (_src->rows == 1 || _src->cols == 1) && (_dst->rows == 1 || _dst->cols == 1) && _src->cols + _src->rows - 1 == _dst->rows + _dst->cols - 1 && (CV_MAT_TYPE(_src->type) == CV_32FC2 || CV_MAT_TYPE(_src->type) == CV_64FC2) && (CV_MAT_TYPE(_dst->type) == CV_32FC2 || CV_MAT_TYPE(_dst->type) == CV_64FC2)) in cvUndistortPoints, file /home/javvaji/opencv-3.2.0/modules/imgproc/src/undistort.cpp, line 293
retval, rvec, tvec = cv2.solvePnP(cam.object_points, cam.image_points, cam.camera_matrix, cam.dist_coefficients, None, None, False, cv2.SOLVEPNP_P3P)
I am using solvePnP function with flag SOLVEPNP_P3P. It is giving assertion error. The same solvePnP code works fine with SOLVEPNP_ITERATIVE flag. With P3P flag it internally calls undistortPoints function which is giving error.
How to resolve this?
Incomplete docs -- solvePnP in python (Problem is known, an issue is open in the opencv github repository)
Numpy array slices won't work as input because solvePnP requires contiguous arrays (enforced by the assertion using cv::Mat::checkVector() around line 55 of modules/calib3d/src/solvepnp.cpp version 2.4.9)
The P3P algorithm requires image points to be in an array of shape (N,1,2) since it's calling cv::undistortPoints (around line 75 of modules/calib3d/src/solvepnp.cpp version 2.4.9) which requires 2-channel information.
Thus, given some data D = np.array(...) where D.shape = (N,M), in order to use a subset of it as, e.g., imagePoints, one must effectively copy it into a new array: imagePoints = np.ascontiguousarray(D[:,:2]).reshape((N,1,2))