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solve import conflict

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This commit is contained in:
QuanyiLi
2023-05-06 14:36:44 +01:00
parent f42487cc05
commit 792a11d513
16 changed files with 151 additions and 182 deletions
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0
scenarionet/converter/waymo/script/__init__.py → scenarionet/builder/__init__.py
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3
scenarionet/converter/waymo/script/select_demo_pickles.py → scenarionet/builder/select_demo_pickles.py
View File

@@ -1,6 +1,5 @@
import pickle
from metadrive.engine.asset_loader import AssetLoader
if __name__ == '__main__':
@@ -28,7 +27,7 @@ if __name__ == '__main__':
if len(new_summary) >= 3:
break
file_path = AssetLoader.file_path("waymo", "dataset_summary.pkl", return_raw_style=False)
file_path = AssetLoader.file_path("../converter/waymo", "dataset_summary.pkl", return_raw_style=False)
with open(file_path, "wb") as f:
pickle.dump(new_summary, f)

13
scenarionet/converter/nuplan/convert_nuplan.py
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@@ -8,14 +8,13 @@ import pickle
import shutil
import tqdm
from metadrive.engine.asset_loader import AssetLoader
from metadrive.scenario.scenario_description import ScenarioDescription
from metadrive.utils.nuplan.utils import get_nuplan_scenarios, convert_one_scenario
from metadrive.utils.utils import dict_recursive_remove_array
from scenarionet.converter.nuplan.utils import get_nuplan_scenarios, convert_one_nuplan_scenario
from scenarionet.converter.utils import dict_recursive_remove_array
def convert_scenarios(output_path, dataset_params, worker_index=None, force_overwrite=False):
def convert_nuplan(output_path, dataset_params, worker_index=None, force_overwrite=False):
save_path = copy.deepcopy(output_path)
output_path = output_path + "_tmp"
# meta recorder and data summary
@@ -42,7 +41,7 @@ def convert_scenarios(output_path, dataset_params, worker_index=None, force_over
# Init.
scenarios = get_nuplan_scenarios(dataset_params)
for scenario in tqdm.tqdm(scenarios):
sd_scenario = convert_one_scenario(scenario)
sd_scenario = convert_one_nuplan_scenario(scenario)
sd_scenario = sd_scenario.to_dict()
ScenarioDescription.sanity_check(sd_scenario, check_self_type=True)
export_file_name = "sd_{}_{}.pkl".format("nuplan", scenario.scenario_name)
@@ -102,4 +101,4 @@ if __name__ == "__main__":
output_path = AssetLoader.file_path("nuplan", return_raw_style=False)
worker_index = None
force_overwrite = True
convert_scenarios(output_path, dataset_params, worker_index=worker_index, force_overwrite=force_overwrite)
convert_nuplan(output_path, dataset_params, worker_index=worker_index, force_overwrite=force_overwrite)

42
scenarionet/converter/nuplan/type.py Normal file
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@@ -0,0 +1,42 @@
import logging
from metadrive.type import MetaDriveType
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
try:
from nuplan.common.actor_state.tracked_objects_types import TrackedObjectType
from nuplan.common.maps.maps_datatypes import TrafficLightStatusType
except ImportError:
logger.warning("Can not import nuplan-devkit")
NuPlanEgoType = TrackedObjectType.EGO
def get_traffic_obj_type(nuplan_type):
if nuplan_type == TrackedObjectType.VEHICLE:
return MetaDriveType.VEHICLE
elif nuplan_type == TrackedObjectType.TRAFFIC_CONE:
return MetaDriveType.TRAFFIC_CONE
elif nuplan_type == TrackedObjectType.PEDESTRIAN:
return MetaDriveType.PEDESTRIAN
elif nuplan_type == TrackedObjectType.BICYCLE:
return MetaDriveType.CYCLIST
elif nuplan_type == TrackedObjectType.BARRIER:
return MetaDriveType.TRAFFIC_BARRIER
elif nuplan_type == TrackedObjectType.EGO:
raise ValueError("Ego should not be in detected resukts")
else:
return None
def set_light_status(status):
if status == TrafficLightStatusType.GREEN:
return MetaDriveType.LIGHT_GREEN
elif status == TrafficLightStatusType.RED:
return MetaDriveType.LIGHT_RED
elif status == TrafficLightStatusType.YELLOW:
return MetaDriveType.LIGHT_YELLOW
elif status == TrafficLightStatusType.UNKNOWN:
return MetaDriveType.LIGHT_UNKNOWN

56
scenarionet/converter/nuplan/utils.py
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@@ -5,27 +5,25 @@ from dataclasses import dataclass
from os.path import join
import numpy as np
from nuplan.common.actor_state.agent import Agent
from nuplan.common.actor_state.static_object import StaticObject
from nuplan.common.actor_state.tracked_objects_types import TrackedObjectType
from nuplan.common.maps.maps_datatypes import TrafficLightStatusType
from metadrive.scenario import ScenarioDescription as SD
from metadrive.type import MetaDriveType
from shapely.geometry.linestring import LineString
from shapely.geometry.multilinestring import MultiLineString
from metadrive.scenario import ScenarioDescription as SD
from metadrive.type import MetaDriveType
from metadrive.utils.coordinates_shift import nuplan_to_metadrive_vector
from metadrive.utils.math import compute_angular_velocity
from scenarionet.converter.nuplan.type import get_traffic_obj_type, NuPlanEgoType, set_light_status
from scenarionet.converter.utils import nuplan_to_metadrive_vector, compute_angular_velocity
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
from metadrive.utils import is_win
import geopandas as gpd
from shapely.ops import unary_union
try:
import geopandas as gpd
from nuplan.common.actor_state.agent import Agent
from nuplan.common.actor_state.static_object import StaticObject
from nuplan.common.actor_state.state_representation import Point2D
from nuplan.common.maps.maps_datatypes import SemanticMapLayer, StopLineType
from shapely.ops import unary_union
from nuplan.planning.scenario_builder.nuplan_db.nuplan_scenario import NuPlanScenario
import hydra
from nuplan.planning.scenario_builder.nuplan_db.nuplan_scenario import NuPlanScenario
@@ -213,17 +211,6 @@ def extract_map_features(map_api, center, radius=250):
return ret
def set_light_status(status):
if status == TrafficLightStatusType.GREEN:
return MetaDriveType.LIGHT_GREEN
elif status == TrafficLightStatusType.RED:
return MetaDriveType.LIGHT_RED
elif status == TrafficLightStatusType.YELLOW:
return MetaDriveType.LIGHT_YELLOW
elif status == TrafficLightStatusType.UNKNOWN:
return MetaDriveType.LIGHT_UNKNOWN
def set_light_position(scenario, lane_id, center, target_position=8):
lane = scenario.map_api.get_map_object(str(lane_id), SemanticMapLayer.LANE_CONNECTOR)
assert lane is not None, "Can not find lane: {}".format(lane_id)
@@ -274,23 +261,6 @@ def extract_traffic_light(scenario, center):
return lights
def get_traffic_obj_type(nuplan_type):
if nuplan_type == TrackedObjectType.VEHICLE:
return MetaDriveType.VEHICLE
elif nuplan_type == TrackedObjectType.TRAFFIC_CONE:
return MetaDriveType.TRAFFIC_CONE
elif nuplan_type == TrackedObjectType.PEDESTRIAN:
return MetaDriveType.PEDESTRIAN
elif nuplan_type == TrackedObjectType.BICYCLE:
return MetaDriveType.CYCLIST
elif nuplan_type == TrackedObjectType.BARRIER:
return MetaDriveType.TRAFFIC_BARRIER
elif nuplan_type == TrackedObjectType.EGO:
raise ValueError("Ego should not be in detected resukts")
else:
return None
def parse_object_state(obj_state, nuplan_center):
ret = {}
ret["position"] = nuplan_to_metadrive_vector([obj_state.center.x, obj_state.center.y], nuplan_center)
@@ -346,9 +316,9 @@ def extract_traffic(scenario: NuPlanScenario, center):
type=MetaDriveType.UNSET,
state=dict(
position=np.zeros(shape=(episode_len, 3)),
heading=np.zeros(shape=(episode_len, )),
heading=np.zeros(shape=(episode_len,)),
velocity=np.zeros(shape=(episode_len, 2)),
valid=np.zeros(shape=(episode_len, )),
valid=np.zeros(shape=(episode_len,)),
length=np.zeros(shape=(episode_len, 1)),
width=np.zeros(shape=(episode_len, 1)),
height=np.zeros(shape=(episode_len, 1))
@@ -392,7 +362,7 @@ def extract_traffic(scenario: NuPlanScenario, center):
obj_type = MetaDriveType.VEHICLE
ego_track[SD.TYPE] = obj_type
if ego_track[SD.METADATA]["nuplan_type"] is None:
ego_track[SD.METADATA]["nuplan_type"] = int(TrackedObjectType.EGO)
ego_track[SD.METADATA]["nuplan_type"] = int(NuPlanEgoType)
ego_track[SD.METADATA]["type"] = obj_type
state = obj_state
ego_track["state"]["position"][frame_idx] = [state["position"][0], state["position"][1], 0.0]
@@ -418,7 +388,7 @@ def extract_traffic(scenario: NuPlanScenario, center):
return tracks
def convert_one_scenario(scenario: NuPlanScenario):
def convert_one_nuplan_scenario(scenario: NuPlanScenario):
"""
Data will be interpolated to 0.1s time interval, while the time interval of original key frames are 0.5s.
"""

15
scenarionet/converter/nuscenes/convert_nuscenes.py
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@@ -5,14 +5,13 @@ MetaDrive.
import copy
import os
import pickle
import shutil
import tqdm
from metadrive.engine.asset_loader import AssetLoader
from metadrive.scenario.scenario_description import ScenarioDescription
from metadrive.utils.nuscenes.utils import convert_one_scenario
from metadrive.utils.utils import dict_recursive_remove_array
import shutil
from scenarionet.converter.nuscenes.utils import convert_one_nuscenes_scenario
from scenarionet.converter.utils import dict_recursive_remove_array
try:
from nuscenes import NuScenes
@@ -20,7 +19,7 @@ except ImportError:
print("Can not find nuscenes-devkit")
def convert_scenarios(version, dataroot, output_path, worker_index=None, verbose=True, force_overwrite=False):
def convert_nuscenes(version, dataroot, output_path, worker_index=None, verbose=True, force_overwrite=False):
save_path = copy.deepcopy(output_path)
output_path = output_path + "_tmp"
# meta recorder and data summary
@@ -48,7 +47,7 @@ def convert_scenarios(version, dataroot, output_path, worker_index=None, verbose
nusc = NuScenes(version=version, verbose=verbose, dataroot=dataroot)
scenes = nusc.scene
for scene in tqdm.tqdm(scenes):
sd_scene = convert_one_scenario(scene["token"], nusc)
sd_scene = convert_one_nuscenes_scenario(scene["token"], nusc)
sd_scene = sd_scene.to_dict()
ScenarioDescription.sanity_check(sd_scene, check_self_type=True)
export_file_name = "sd_{}_{}.pkl".format("nuscenes_" + version, scene["token"])
@@ -74,4 +73,4 @@ if __name__ == "__main__":
dataroot = '/home/shady/data/nuscenes'
worker_index = None
force_overwrite = True
convert_scenarios(version, dataroot, output_path, force_overwrite=force_overwrite)
convert_nuscenes(version, dataroot, output_path, force_overwrite=force_overwrite)

0
scenarionet/converter/nuscenes/detection_type.py → scenarionet/converter/nuscenes/type.py
View File

32
scenarionet/converter/nuscenes/utils.py
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@@ -1,19 +1,25 @@
import copy
import logging
import geopandas as gpd
import numpy as np
from nuscenes import NuScenes
from nuscenes.can_bus.can_bus_api import NuScenesCanBus
from nuscenes.eval.common.utils import quaternion_yaw
from nuscenes.map_expansion.arcline_path_utils import discretize_lane
from nuscenes.map_expansion.map_api import NuScenesMap
from pyquaternion import Quaternion
from shapely.ops import unary_union, cascaded_union
import logging
from metadrive.scenario import ScenarioDescription as SD
from metadrive.type import MetaDriveType
from metadrive.utils.nuscenes.detection_type import ALL_TYPE, HUMAN_TYPE, BICYCLE_TYPE, VEHICLE_TYPE
from shapely.ops import unary_union
from scenarionet.converter.nuscenes.type import ALL_TYPE, HUMAN_TYPE, BICYCLE_TYPE, VEHICLE_TYPE
logger = logging.getLogger(__name__)
try:
from nuscenes import NuScenes
from nuscenes.can_bus.can_bus_api import NuScenesCanBus
from nuscenes.eval.common.utils import quaternion_yaw
from nuscenes.map_expansion.arcline_path_utils import discretize_lane
from nuscenes.map_expansion.map_api import NuScenesMap
from pyquaternion import Quaternion
except ImportError:
logger.warning("Can not import nuscenes-devkit")
EGO = "ego"
@@ -122,9 +128,9 @@ def get_tracks_from_frames(nuscenes: NuScenes, scene_info, frames, num_to_interp
type=MetaDriveType.UNSET,
state=dict(
position=np.zeros(shape=(episode_len, 3)),
heading=np.zeros(shape=(episode_len, )),
heading=np.zeros(shape=(episode_len,)),
velocity=np.zeros(shape=(episode_len, 2)),
valid=np.zeros(shape=(episode_len, )),
valid=np.zeros(shape=(episode_len,)),
length=np.zeros(shape=(episode_len, 1)),
width=np.zeros(shape=(episode_len, 1)),
height=np.zeros(shape=(episode_len, 1))
@@ -177,7 +183,7 @@ def get_tracks_from_frames(nuscenes: NuScenes, scene_info, frames, num_to_interp
interpolate_tracks[id]["metadata"]["track_length"] = new_episode_len
# valid first
new_valid = np.zeros(shape=(new_episode_len, ))
new_valid = np.zeros(shape=(new_episode_len,))
if track["state"]["valid"][0]:
new_valid[0] = 1
for k, valid in enumerate(track["state"]["valid"][1:], start=1):
@@ -339,7 +345,7 @@ def get_map_features(scene_info, nuscenes: NuScenes, map_center, radius=250, poi
return ret
def convert_one_scenario(scene_token: str, nuscenes: NuScenes):
def convert_one_nuscenes_scenario(scene_token: str, nuscenes: NuScenes):
"""
Data will be interpolated to 0.1s time interval, while the time interval of original key frames are 0.5s.
"""

52
scenarionet/converter/utils.py Normal file
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@@ -0,0 +1,52 @@
import math
import numpy as np
def nuplan_to_metadrive_vector(vector, nuplan_center=(0, 0)):
"All vec in nuplan should be centered in (0,0) to avoid numerical explosion"
vector = np.array(vector)
# if len(vector.shape) == 1:
# vector[1] *= -1
# else:
# vector[:, 1] *= -1
vector -= np.asarray(nuplan_center)
return vector
def compute_angular_velocity(initial_heading, final_heading, dt):
"""
Calculate the angular velocity between two headings given in radians.
Parameters:
initial_heading (float): The initial heading in radians.
final_heading (float): The final heading in radians.
dt (float): The time interval between the two headings in seconds.
Returns:
float: The angular velocity in radians per second.
"""
# Calculate the difference in headings
delta_heading = final_heading - initial_heading
# Adjust the delta_heading to be in the range (-π, π]
delta_heading = (delta_heading + math.pi) % (2 * math.pi) - math.pi
# Compute the angular velocity
angular_vel = delta_heading / dt
return angular_vel
def dict_recursive_remove_array(d):
if isinstance(d, np.ndarray):
return d.tolist()
if isinstance(d, dict):
for k in d.keys():
d[k] = dict_recursive_remove_array(d[k])
return d
def mph_to_kmh(speed_in_mph: float):
speed_in_kmh = speed_in_mph * 1.609344
return speed_in_kmh

13
scenarionet/converter/waymo/convert_waymo.py
View File

@@ -7,7 +7,6 @@ This script will create the output folder "processed_data" sharing the same leve
"""
import argparse
from metadrive.utils.utils import dict_recursive_remove_array
import copy
import os
import pickle
@@ -15,7 +14,7 @@ from collections import defaultdict
import numpy as np
from metadrive.constants import DATA_VERSION
from scenarionet.converter.utils import dict_recursive_remove_array
try:
import tensorflow as tf
@@ -35,7 +34,7 @@ except ImportError:
from metadrive.scenario import ScenarioDescription as SD
from metadrive.type import MetaDriveType
from metadrive.utils.waymo.utils import extract_tracks, extract_dynamic_map_states, extract_map_features, \
from scenarionet.converter.waymo.utils import extract_tracks, extract_dynamic_map_states, extract_map_features, \
compute_width
import sys
@@ -118,7 +117,7 @@ def _get_number_summary(scenario):
return number_summary_dict
def parse_data(file_list, input_path, output_path, worker_index=None):
def convert_waymo(file_list, input_path, output_path, worker_index=None):
scenario = scenario_pb2.Scenario()
metadata_recorder = {}
@@ -145,8 +144,8 @@ def parse_data(file_list, input_path, output_path, worker_index=None):
md_scenario = SD()
md_scenario[SD.ID] = scenario.scenario_id
md_scenario[SD.VERSION] = DATA_VERSION
# TODO LQY, get version from original files
md_scenario[SD.VERSION] = "1.2"
# Please note that SDC track index is not identical to sdc_id.
# sdc_id is a unique indicator to a track, while sdc_track_index is only the index of the sdc track
@@ -255,7 +254,7 @@ if __name__ == "__main__":
# parse raw data from input path to output path,
# there is 1000 raw data in google cloud, each of them produce about 500 pkl file
file_list = os.listdir(raw_data_path)
parse_data(file_list, raw_data_path, output_path)
convert_waymo(file_list, raw_data_path, output_path)
sys.exit()
# file_path = AssetLoader.file_path("waymo", "processed", "0.pkl", return_raw_style=False)
# data = read_waymo_data(file_path)

4
scenarionet/converter/waymo/script/batch_convert.sh
View File

@@ -1,4 +0,0 @@
#!/usr/bin/env bash
for i in 0 1 2 3 4 5 6 7 8 9; do
nohup python /home/qyli/metadrive/metadrive/utils/waymo/script/convert_waymo_to_metadrive.py ./scenario_${i} > ${i}.log 2>&1 &
done

69
scenarionet/converter/waymo/script/filter_cases.py
View File

@@ -1,69 +0,0 @@
import os
import signal
import sys
from tqdm import tqdm
from metadrive.envs.real_data_envs.waymo_env import WaymoEnv
from metadrive.policy.idm_policy import WaymoIDMPolicy
try:
from metadrive.utils.waymo.waymo_type import WaymoAgentType
from metadrive.utils.waymo.waymo_type import WaymoRoadLineType, WaymoRoadEdgeType
finally:
pass
def handler(signum, frame):
raise Exception("end of time")
if __name__ == "__main__":
scenario_data_path = sys.argv[1]
start = int(sys.argv[2])
processed_data_path = scenario_data_path + "_filtered"
if not os.path.exists(processed_data_path):
os.mkdir(processed_data_path)
if not os.path.exists(scenario_data_path) or not os.path.exists(processed_data_path):
raise ValueError("Path Not exist")
num_scenarios = len(os.listdir(scenario_data_path))
max_step = 1500
min_step = 50
env = WaymoEnv(
{
"use_render": False,
"agent_policy": WaymoIDMPolicy,
"data_directory": scenario_data_path,
"start_scenario_index": start * 1000,
"num_scenarios": num_scenarios,
"store_map": False,
# "manual_control": True,
# "debug":True,
"no_traffic": True,
"horizon": 1500,
}
)
try:
env.reset()
except:
pass
finally:
pass
for i in tqdm(range(num_scenarios)):
try:
signal.signal(signal.SIGALRM, handler)
signal.alarm(10)
env.reset(force_seed=i)
while True:
o, r, d, info = env.step([0, 0])
if d or env.episode_step > max_step:
if info["arrive_dest"] and env.episode_step > min_step:
os.rename(
os.path.join(scenario_data_path, "{}.pkl".format(i + start * 1000)),
os.path.join(processed_data_path, "{}.pkl".format(i + start * 1000))
)
break
except:
# print("\n No Route or Timeout, Fail, Seed: {}".format(i))
pass

4
scenarionet/converter/waymo/script/filter_cases.sh
View File

@@ -1,4 +0,0 @@
#!/usr/bin/env bash
for i in 0 1 2 3 4 5 6 7 8 9; do
nohup python /home/lfeng/metadrive/metadrive/utils/waymo/filter_cases.py /home/lfeng/waymo/scenarios_processed_${i} ${i} > ${i}.log 2>&1 &
done

0
scenarionet/converter/waymo/waymo_type.py → scenarionet/converter/waymo/type.py
View File

28
scenarionet/converter/waymo/utils.py
View File

@@ -1,18 +1,16 @@
import matplotlib.pyplot as plt
from metadrive.scenario.utils import read_scenario_data
from matplotlib.pyplot import figure
from metadrive.type import MetaDriveType
from metadrive.utils.math import mph_to_kmh
from metadrive.utils.waymo.waymo_type import WaymoLaneType, WaymoAgentType
from metadrive.utils.waymo.waymo_type import WaymoRoadLineType, WaymoRoadEdgeType
from scenarionet.converter.utils import mph_to_kmh
from scenarionet.converter.waymo.type import WaymoLaneType, WaymoAgentType, WaymoRoadLineType, WaymoRoadEdgeType
try:
import tensorflow as tf
except ImportError:
pass
try:
from metadrive.utils.waymo.protos import scenario_pb2
from scenarionet.converter.waymo.protos import scenario_pb2
except ImportError:
pass
import pickle
@@ -100,7 +98,6 @@ def extract_edge(f):
edge = dict()
f_ = f.road_edge
# TODO: Need to transform this to MetaDrive version
edge["type"] = WaymoRoadEdgeType.from_waymo(f_.type)
edge["polyline"] = extract_poly(f_.polyline)
@@ -302,24 +299,6 @@ class CustomUnpickler(pickle.Unpickler):
return super().find_class(module, name)
def read_waymo_data(file_path):
return read_scenario_data(file_path)
def draw_waymo_map(data):
"""
TODO: Need this function in future.
"""
figure(figsize=(8, 6), dpi=500)
for key, value in data[ScenarioDescription.MAP_FEATURES].items():
if value.get("type", None) == "center_lane":
plt.scatter([x[0] for x in value["polyline"]], [y[1] for y in value["polyline"]], s=0.5)
elif value.get("type", None) == "road_edge":
plt.scatter([x[0] for x in value["polyline"]], [y[1] for y in value["polyline"]], s=0.5, c=(0, 0, 0))
# elif value.get("type", None) == "road_line":
# plt.scatter([x[0] for x in value["polyline"]], [y[1] for y in value["polyline"]], s=0.5, c=(0.8,0.8,0.8))
plt.show()
# return the nearest point"s index of the line
def nearest_point(point, line):
@@ -369,7 +348,6 @@ def compute_width(map):
lane["width"] = width
return
# parse raw data from input path to output path
# def convert_polyline_to_metadrive(waymo_polyline, coordinate_transform=True):

2
setup.py
View File

@@ -35,6 +35,8 @@ install_requires = [
"pandas",
"tqdm",
"metadrive-simulator",
"geopandas",
"shapely"
]
setup(