Namespaces |
| 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))) |
