Python create_lane_highlightの例

コード例 #1

ファイル: rule.py プロジェクト: viciopoli01/duckietown-world

def evaluate_rules(poses_sequence, interval: SampledSequence[Timestamp],
                   world: PlacedObject,
                   ego_name: str) -> Dict[str, RuleEvaluationResult]:
    from duckietown_world.world_duckietown import create_lane_highlight

    lane_pose_seq = create_lane_highlight(poses_sequence, world)
    from duckietown_world.rules import DeviationFromCenterLine
    from duckietown_world.rules import InDrivableLane
    from duckietown_world.rules import DeviationHeading
    from duckietown_world.rules import DrivenLength
    from duckietown_world.rules import DrivenLengthConsecutive
    from duckietown_world.rules import SurvivalTime

    rules = {}
    rules["deviation-heading"] = DeviationHeading()
    rules["in-drivable-lane"] = InDrivableLane()
    rules["deviation-center-line"] = DeviationFromCenterLine()
    rules["driving-distance"] = DrivenLength()
    rules["driving-distance-consecutive"] = DrivenLengthConsecutive()
    rules["survival_time"] = SurvivalTime()

    context = RuleEvaluationContext(
        interval=interval,
        world=world,
        ego_name=ego_name,
        lane_pose_seq=lane_pose_seq,
        pose_seq=poses_sequence,
    )

    evaluated = {}
    for name, rule in rules.items():
        result = RuleEvaluationResult(rule)
        rule.evaluate(context, result)
        evaluated[name] = result
    return evaluated

コード例 #2

ファイル: rule.py プロジェクト: selcukercan/duckietown-world

def evaluate_rules(poses_sequence, interval, world, ego_name):
    from duckietown_world.world_duckietown import create_lane_highlight
    lane_pose_seq = create_lane_highlight(poses_sequence, world)
    from duckietown_world.rules import DeviationFromCenterLine
    from duckietown_world.rules import InDrivableLane
    from duckietown_world.rules import DeviationHeading
    from duckietown_world.rules import DrivenLength
    from duckietown_world.rules import DrivenLengthConsecutive
    rules = OrderedDict()
    rules['deviation-heading'] = DeviationHeading()
    rules['in-drivable-lane'] = InDrivableLane()
    rules['deviation-center-line'] = DeviationFromCenterLine()
    rules['driving-distance'] = DrivenLength()
    rules['driving-distance-consecutive'] = DrivenLengthConsecutive()

    context = RuleEvaluationContext(interval,
                                    world,
                                    ego_name=ego_name,
                                    lane_pose_seq=lane_pose_seq,
                                    pose_seq=poses_sequence)

    evaluated = OrderedDict()
    for name, rule in rules.items():
        result = RuleEvaluationResult(rule)
        rule.evaluate(context, result)
        evaluated[name] = result
    return evaluated