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run_optimization_fake.py File Reference

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namespace  camera_pose_calibration::run_optimization_fake

Variables

tuple camera_pose_calibration::run_optimization_fake.cal_estimate = CalibrationEstimate()
tuple camera_pose_calibration::run_optimization_fake.cal_pattern = CalibrationPattern()
tuple camera_pose_calibration::run_optimization_fake.cal_sample = RobotMeasurement()
list camera_pose_calibration::run_optimization_fake.cal_samples = []
tuple camera_pose_calibration::run_optimization_fake.camera_a = CameraPose()
tuple camera_pose_calibration::run_optimization_fake.camera_b = CameraPose()
list camera_pose_calibration::run_optimization_fake.check_points = []
tuple camera_pose_calibration::run_optimization_fake.meas = CameraMeasurement()
float camera_pose_calibration::run_optimization_fake.noise = 5.0
tuple camera_pose_calibration::run_optimization_fake.offset = PyKDL.Frame(PyKDL.Rotation.RPY(0.1, 0.1, 0), PyKDL.Vector(0, 0.1, 0))
list camera_pose_calibration::run_optimization_fake.P = [525, 0, 319.5, 0, 0, 525, 239.5, 0, 0, 0, 1, 0]
tuple camera_pose_calibration::run_optimization_fake.P_mat = reshape( matrix(P, float), (3,4) )
tuple camera_pose_calibration::run_optimization_fake.pnt = Point32()
tuple camera_pose_calibration::run_optimization_fake.pnt_mat = P_mat*matrix([pnt_msg[0], pnt_msg[1], pnt_msg[2], 1])
tuple camera_pose_calibration::run_optimization_fake.pnt_msg = posemath.fromMsg(camera.pose)
tuple camera_pose_calibration::run_optimization_fake.target_1 = posemath.toMsg(PyKDL.Frame(PyKDL.Vector(0, -2, 1)))
tuple camera_pose_calibration::run_optimization_fake.target_2 = posemath.toMsg(PyKDL.Frame(PyKDL.Vector(0, 2, 1)))
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camera_pose_calibration
Author(s): Vijay Pradeep, Wim Meeussen
autogenerated on Thu Aug 15 2013 10:18:08