API Reference¶

class
pymvg.camera_model.
CameraModel
(name, width, height, _rquat, _camcenter, P, K, distortion, rect)[source]¶ an implementation of the Camera Model used by ROS and OpenCV
Tranformations: We can think about the overall projection to 2D in two steps. Step 1 takes 3D world coordinates and, with a simple matrix multiplication and perspective division, projects them to undistorted 2D coordinates. Step 2 takes these undistorted 2D coordinates and distorts them so they are ‘distorted’ and match up with a real camera with radial distortion, for example.
3D world –(step1)—> undistorted 2D —(step2)—> distorted 2D
Step 1 is accomplished by making the world coordinates a homogeneous vector of length 4, multiplying by a 3x4 matrix M (built from P, R and t) to get values [r,s,t] in which the undistorted 2D coordinates are [r/t, s/t]. (The implementation is vectorized so that in fact many points at once can be transformed.)
Step 2 is somewhat complicated in that it allows a separate focal length and camera center to be used for distortion. Undistorted 2D coordinates are transformed first to uncorrected normalized image coordinates using parameters from P, then corrected using a rectification matrix. These corrected normalized image coordinates are then used in conjunction with the distortion model to create distorted normalized pixels which are finally transformed to distorted image pixels by K.
Coordinate system: the camera is looking at +Z, with +X rightward and +Y down. For more information, see http://www.ros.org/wiki/image_pipeline/CameraInfo
As noted on the link above, this differs from the coordinate system of Harley and Zisserman, which has Z forward, Y up, and X to the left (looking towards +Z).’

get_aligned_camera
(scale, rotation, translation)[source]¶ return a copy of this camera with new extrinsic coordinates

get_flipped_camera
()[source]¶ return a copy of this camera looking in the opposite direction
The returned camera has the same 3D>2D projection. (The 2D>3D projection results in a vector in the opposite direction.)

get_mirror_camera
(axis='lr', hold_center=False)[source]¶ return a copy of this camera whose x coordinate is (image_widthx)
axis  string. Specifies the axis of the mirroring, either ‘lr’ or ‘ud’. hold_center  boolean. Preserve the optical center?

get_view_camera
(eye, lookat, up=None)[source]¶ return a copy of this camera with new extrinsic coordinates

is_distorted_and_skewed
(max_skew_ratio=1000000000000000.0)[source]¶ True if pixels are skewed and distorted

classmethod
load_camera_from_M
(pmat, width=None, height=None, name='cam', distortion_coefficients=None, _depth=0, eps=1e15)[source]¶ create CameraModel instance from a camera matrix M

classmethod
load_camera_from_opened_bagfile
(bag, extrinsics_required=True)[source]¶ factory function for class CameraModel
bag  an opened rosbag.Bag instance extrinsics_required  are extrinsic parameters required

project_3d_to_camera_frame
(pts3d)[source]¶ take 3D coordinates in world frame and convert to camera frame


class
pymvg.multi_camera_system.
MultiCameraSystem
(cameras)[source]¶ 
find3d
(pts, undistort=True)[source]¶ Find 3D coordinate using all data given
Implements a linear triangulation method to find a 3D point. For example, see Hartley & Zisserman section 12.2 (p.312).
By default, this function will undistort 2D points before finding a 3D point.
