get a unified func

scenarionet/converter/__init__.py

@@ -0,0 +1,3 @@
+from scenarionet.converter.nuscenes.utils import convert_one_nuscenes_scenario
+from scenarionet.converter.nuplan.utils import convert_one_nuplan_scenario
+from scenarionet.converter.utils import write_to_directory

scenarionet/converter/nuscenes/utils.py

@@ -345,10 +345,11 @@ def get_map_features(scene_info, nuscenes: NuScenes, map_center, radius=250, poi
     return ret
 
 
-def convert_one_nuscenes_scenario(scene_token: str, nuscenes: NuScenes):
+def convert_one_nuscenes_scenario(scene, nuscenes: NuScenes):
     """
     Data will be interpolated to 0.1s time interval, while the time interval of original key frames are 0.5s.
     """
+    scene_token = scene["token"]
     scenario_log_interval = 0.1
     scene_info = nuscenes.get("scene", scene_token)
     frames = []

scenarionet/converter/scripts/convert_nuplan.py

@@ -14,7 +14,7 @@ from scenarionet.converter.nuplan.utils import get_nuplan_scenarios, convert_one
 from scenarionet.converter.utils import dict_recursive_remove_array
 
 
-def convert_nuplan(output_path, dataset_params, worker_index=None, force_overwrite=False):
+def convert_nuplan(dataset_params, output_path, worker_index=None, force_overwrite=False):
     save_path = copy.deepcopy(output_path)
     output_path = output_path + "_tmp"
     # meta recorder and data summary

scenarionet/converter/scripts/convert_nuscenes.py

@@ -2,76 +2,28 @@
 This script aims to convert nuscenes scenarios to ScenarioDescription, so that we can load any nuscenes scenarios into
 MetaDrive.
 """
-import copy
-import os
-import pickle
-import shutil
-
-import tqdm
-from metadrive.scenario.scenario_description import ScenarioDescription
 
+from scenarionet import SCENARIONET_DATASET_PATH
 from scenarionet.converter.nuscenes.utils import convert_one_nuscenes_scenario
-from scenarionet.converter.utils import dict_recursive_remove_array
+from scenarionet.converter.utils import write_to_directory
 
 try:
     from nuscenes import NuScenes
 except ImportError:
     print("Can not find nuscenes-devkit")
 
-
-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
-    if os.path.exists(output_path):
-        shutil.rmtree(output_path)
-    os.makedirs(output_path, exist_ok=False)
-
-    # make real save dir
-    delay_remove = None
-    if os.path.exists(save_path):
-        if force_overwrite:
-            delay_remove = save_path
-        else:
-            raise ValueError("Directory already exists! Abort")
-
-    metadata_recorder = {}
-    total_scenarios = 0
-    desc = ""
-    summary_file = "dataset_summary.pkl"
-    if worker_index is not None:
-        desc += "Worker {} ".format(worker_index)
-        summary_file = "dataset_summary_worker{}.pkl".format(worker_index)
-
-    # Init.
-    nusc = NuScenes(version=version, verbose=verbose, dataroot=dataroot)
-    scenes = nusc.scene
-    for scene in tqdm.tqdm(scenes):
-        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"])
-        p = os.path.join(output_path, export_file_name)
-        with open(p, "wb") as f:
-            pickle.dump(sd_scene, f)
-        metadata_recorder[export_file_name] = copy.deepcopy(sd_scene[ScenarioDescription.METADATA])
-
-    # rename and save
-    if delay_remove is not None:
-        shutil.rmtree(delay_remove)
-    os.rename(output_path, save_path)
-    summary_file = os.path.join(save_path, summary_file)
-    with open(summary_file, "wb") as file:
-        pickle.dump(dict_recursive_remove_array(metadata_recorder), file)
-    print("Summary is saved at: {}".format(summary_file))
-    assert delay_remove == save_path
-
-
+#
 if __name__ == "__main__":
-    output_path = AssetLoader.file_path("nuscenes", return_raw_style=False)
+    output_path = SCENARIONET_DATASET_PATH
     version = 'v1.0-mini'
-    verbose = True
     dataroot = '/home/shady/data/nuscenes'
-    worker_index = None
     force_overwrite = True
-    convert_nuscenes(version, dataroot, output_path, force_overwrite=force_overwrite)
+    nusc = NuScenes(version=version, dataroot=dataroot)
+    scenarios = nusc.scene
+    write_to_directory(convert_func=convert_one_nuscenes_scenario,
+                       scenarios=scenarios,
+                       output_path=output_path,
+                       version=version,
+                       dataset_name="nuscenes",
+                       force_overwrite=True,
+                       nuscenes=nusc)

scenarionet/converter/utils.py

@@ -1,8 +1,15 @@
+import copy
 import math
+import ast
+import inspect
+import os
+import pickle
+import shutil
 from collections import defaultdict
 
 import numpy as np
-from metadrive.scenario import ScenarioDescription as SD
+import tqdm
+from metadrive.scenario import ScenarioDescription as SD, ScenarioDescription
 
 
 def nuplan_to_metadrive_vector(vector, nuplan_center=(0, 0)):
@@ -99,3 +106,49 @@ def get_number_summary(scenario):
     number_summary_dict["dynamic_object_states_counter"] = dict(dynamic_object_states_counter)
 
     return number_summary_dict
+
+
+def contains_explicit_return(f):
+    return any(isinstance(node, ast.Return) for node in ast.walk(ast.parse(inspect.getsource(f))))
+
+
+def write_to_directory(convert_func, scenarios, output_path, version, dataset_name, force_overwrite=False, **kwargs):
+    if not contains_explicit_return(convert_func):
+        raise RuntimeError("The convert function should return a metadata dict")
+
+    save_path = copy.deepcopy(output_path)
+    output_path = output_path + "_tmp"
+    # meta recorder and data summary
+    if os.path.exists(output_path):
+        shutil.rmtree(output_path)
+    os.makedirs(output_path, exist_ok=False)
+
+    # make real save dir
+    delay_remove = None
+    if os.path.exists(save_path):
+        if force_overwrite:
+            delay_remove = save_path
+        else:
+            raise ValueError("Directory already exists! Abort")
+
+    summary_file = "dataset_summary.pkl"
+
+    metadata_recorder = {}
+    for scenario in tqdm.tqdm(scenarios):
+        sd_scenario = convert_func(scenario, **kwargs)
+        sd_scenario = sd_scenario.to_dict()
+        ScenarioDescription.sanity_check(sd_scenario, check_self_type=True)
+        export_file_name = "sd_{}_{}.pkl".format(dataset_name+"_" + version, scenario["token"])
+        p = os.path.join(output_path, export_file_name)
+        with open(p, "wb") as f:
+            pickle.dump(sd_scenario, f)
+
+    # rename and save
+    if delay_remove is not None:
+        shutil.rmtree(delay_remove)
+    os.rename(output_path, save_path)
+    summary_file = os.path.join(save_path, summary_file)
+    with open(summary_file, "wb") as file:
+        pickle.dump(dict_recursive_remove_array(metadata_recorder), file)
+    print("Summary is saved at: {}".format(summary_file))
+    assert delay_remove == save_path