f1865048c7
* boundary to exterior * rename copy to cp, avoiding bugs * add connectivity and sidewalk/cross for nuscenes * update lane type * add semantic renderer * restore * nuplan works * format
78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
desc = "Load a database to simulator and replay scenarios"
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if __name__ == '__main__':
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import logging
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import pkg_resources # for suppress warning
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import argparse
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import os
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from metadrive.envs.scenario_env import ScenarioEnv
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from metadrive.policy.replay_policy import ReplayEgoCarPolicy
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from metadrive.scenario.utils import get_number_of_scenarios
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parser = argparse.ArgumentParser(description=desc)
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parser.add_argument("--database_path", "-d", required=True, help="The path of the database")
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parser.add_argument("--render", default="none", choices=["none", "2D", "3D", "advanced", "semantic"])
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parser.add_argument("--scenario_index", default=None, type=int, help="Specifying a scenario to run")
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args = parser.parse_args()
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database_path = os.path.abspath(args.database_path)
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num_scenario = get_number_of_scenarios(database_path)
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if args.scenario_index is not None:
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assert args.scenario_index < num_scenario, \
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"The specified scenario index exceeds the scenario range: {}!".format(num_scenario)
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env = ScenarioEnv(
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{
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"use_render": args.render == "3D" or args.render == "advanced",
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"agent_policy": ReplayEgoCarPolicy,
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"manual_control": False,
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"render_pipeline": args.render == "advanced",
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"show_interface": True,
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# "reactive_traffic": args.reactive,
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"show_logo": False,
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"show_fps": False,
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"log_level": logging.CRITICAL,
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"num_scenarios": num_scenario,
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"interface_panel": [],
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"horizon": 1000,
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"vehicle_config": dict(
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show_navi_mark=True,
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show_line_to_dest=False,
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show_dest_mark=False,
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no_wheel_friction=True,
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lidar=dict(num_lasers=120, distance=50, num_others=4),
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lane_line_detector=dict(num_lasers=12, distance=50),
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side_detector=dict(num_lasers=160, distance=50)
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),
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"data_directory": database_path,
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}
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)
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for index in range(0, num_scenario if args.scenario_index is not None else 1000000):
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env.reset(seed=index if args.scenario_index is None else args.scenario_index)
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for t in range(10000):
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env.step([0, 0])
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if env.config["use_render"]:
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env.render(
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text={
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"scenario index": env.engine.global_seed + env.config["start_scenario_index"],
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"[": "Load last scenario",
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"]": "Load next scenario",
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"r": "Reset current scenario",
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}
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)
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if args.render == "2D" or args.render == "semantic":
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env.render(
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film_size=(3000, 3000),
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semantic_map=args.render == "semantic",
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target_vehicle_heading_up=False,
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mode="top_down",
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text={
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"scenario index": env.engine.global_seed + env.config["start_scenario_index"],
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}
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)
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if env.episode_step >= env.engine.data_manager.current_scenario_length:
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print("scenario:{}, success".format(env.engine.global_random_seed))
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break
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