Add test for waymo example (#58)

* add test script

* test first 10 scenarios

* add dependency

* add dependency

.github/workflows/main.yml

@@ -35,6 +35,8 @@ jobs:
           python-version: 3.9
       - name: Blackbox tests
         run: |
+          pip install tensorflow==2.11.0
+          pip install protobuf==3.20
           pip install cython
           pip install numpy
           pip install -e .

.gitignore

@@ -25,3 +25,5 @@ dataset/*
 **/wandb/
 /tutorial/*.gif
 /tutorial/.ipynb_checkpoints/
+/scenarionet/tests/waymo_raw
+/scenarionet/tests/waymo_test_data/

scenarionet/tests/test_waymo.py

@@ -0,0 +1,94 @@
+import urllib.request
+import shutil
+import argparse
+import logging
+import os
+
+from scenarionet import SCENARIONET_DATASET_PATH, SCENARIONET_REPO_PATH
+from scenarionet.converter.utils import write_to_directory
+from scenarionet.converter.waymo.utils import convert_waymo_scenario, get_waymo_scenarios, preprocess_waymo_scenarios
+import logging
+
+import pkg_resources  # for suppress warning
+import argparse
+import os
+from metadrive.envs.scenario_env import ScenarioEnv
+from metadrive.policy.replay_policy import ReplayEgoCarPolicy
+from metadrive.scenario.utils import get_number_of_scenarios
+
+
+def test_waymo_and_sim():
+    url = "https://github.com/metadriverse/scenarionet/releases/download/releases%2F0.01/waymo_test_data"
+    waymo_data_directory = os.path.join(SCENARIONET_DATASET_PATH, "waymo_raw")
+    if os.path.exists(waymo_data_directory):
+        shutil.rmtree(waymo_data_directory)
+    os.makedirs(waymo_data_directory)
+    urllib.request.urlretrieve(url, os.path.join(waymo_data_directory, "training_20s.tfrecord-00000-of-01000"))
+    #
+    dataset_name = "waymo"
+    output_path = "waymo_test_data"
+    version = "v1.2"
+    #
+    files = get_waymo_scenarios(waymo_data_directory, 0, 1)
+
+    write_to_directory(
+        convert_func=convert_waymo_scenario,
+        scenarios=files,
+        output_path=output_path,
+        dataset_version=version,
+        dataset_name=dataset_name,
+        overwrite=True,
+        num_workers=4,
+        preprocess=preprocess_waymo_scenarios,
+    )
+    database_path = os.path.abspath(output_path)
+    num_scenario = get_number_of_scenarios(database_path)
+
+    env = ScenarioEnv(
+        {
+            "use_render": False,
+            "agent_policy": ReplayEgoCarPolicy,
+            "manual_control": False,
+            "render_pipeline": False,
+            "show_interface": True,
+            # "reactive_traffic": args.reactive,
+            "show_logo": False,
+            "show_fps": False,
+            "log_level": logging.CRITICAL,
+            "num_scenarios": num_scenario,
+            "interface_panel": [],
+            "horizon": 1000,
+            "vehicle_config": dict(
+                show_navi_mark=True,
+                show_line_to_dest=False,
+                show_dest_mark=False,
+                no_wheel_friction=True,
+                lidar=dict(num_lasers=120, distance=50, num_others=4),
+                lane_line_detector=dict(num_lasers=12, distance=50),
+                side_detector=dict(num_lasers=160, distance=50)
+            ),
+            "data_directory": database_path,
+        }
+    )
+    for index in range(0, 20):
+        print(index)
+        env.reset(seed=index)
+        for t in range(10000):
+            env.step([0, 0])
+            env.render(
+                film_size=(3000, 3000),
+                semantic_map=True,
+                target_vehicle_heading_up=False,
+                window=False,
+                mode="top_down",
+                text={
+                    "scenario index": env.engine.global_seed + env.config["start_scenario_index"],
+                }
+            )
+            if env.episode_step >= env.engine.data_manager.current_scenario_length:
+                print("scenario:{}, success".format(env.engine.global_random_seed))
+                break
+
+
+if __name__ == '__main__':
+    test_waymo_and_sim()