95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
import urllib.request
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import shutil
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import argparse
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import logging
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import os
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from scenarionet import SCENARIONET_DATASET_PATH, SCENARIONET_REPO_PATH
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from scenarionet.converter.utils import write_to_directory
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from scenarionet.converter.waymo.utils import convert_waymo_scenario, get_waymo_scenarios, preprocess_waymo_scenarios
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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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def test_waymo_and_sim():
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url = "https://github.com/metadriverse/scenarionet/releases/download/releases%2F0.01/waymo_test_data"
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waymo_data_directory = os.path.join(SCENARIONET_DATASET_PATH, "waymo_raw")
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if os.path.exists(waymo_data_directory):
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shutil.rmtree(waymo_data_directory)
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os.makedirs(waymo_data_directory)
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urllib.request.urlretrieve(url, os.path.join(waymo_data_directory, "training_20s.tfrecord-00000-of-01000"))
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#
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dataset_name = "waymo"
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output_path = "waymo_test_data"
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version = "v1.2"
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#
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files = get_waymo_scenarios(waymo_data_directory, 0, 1)
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write_to_directory(
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convert_func=convert_waymo_scenario,
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scenarios=files,
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output_path=output_path,
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dataset_version=version,
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dataset_name=dataset_name,
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overwrite=True,
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num_workers=4,
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preprocess=preprocess_waymo_scenarios,
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)
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database_path = os.path.abspath(output_path)
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num_scenario = get_number_of_scenarios(database_path)
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env = ScenarioEnv(
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{
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"use_render": False,
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"agent_policy": ReplayEgoCarPolicy,
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"manual_control": False,
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"render_pipeline": False,
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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, 20):
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print(index)
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env.reset(seed=index)
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for t in range(10000):
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env.step([0, 0])
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env.render(
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film_size=(3000, 3000),
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semantic_map=True,
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target_vehicle_heading_up=False,
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window=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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if __name__ == '__main__':
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test_waymo_and_sim()
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