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Minor updates: disable TF gpu access (#95)

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* Minor changes

* Update generate_sensor_offscreen.py
This commit is contained in:
Zhenghao Peng
2024-12-02 13:05:09 -08:00
committed by GitHub
parent c6775d7197
commit cf6b91c963
3 changed files with 21 additions and 14 deletions
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4
scenarionet/convert_pg.py
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@@ -1,18 +1,18 @@
desc = "Build database from synthetic or procedurally generated scenarios" desc = "Build database from synthetic or procedurally generated scenarios"
if __name__ == '__main__': if __name__ == '__main__':
import pkg_resources # for suppress warning
import argparse import argparse
import os.path import os.path
import os import os
import metadrive import metadrive
import tensorflow as tf
from scenarionet import SCENARIONET_DATASET_PATH from scenarionet import SCENARIONET_DATASET_PATH
from scenarionet.converter.pg.utils import get_pg_scenarios, convert_pg_scenario from scenarionet.converter.pg.utils import get_pg_scenarios, convert_pg_scenario
from scenarionet.converter.utils import write_to_directory from scenarionet.converter.utils import write_to_directory
os.environ["CUDA_VISIBLE_DEVICES"] = "" tf.config.experimental.set_visible_devices([], "GPU")
# For the PG environment config, see: scenarionet/converter/pg/utils.py:6 # For the PG environment config, see: scenarionet/converter/pg/utils.py:6
parser = argparse.ArgumentParser(description=desc) parser = argparse.ArgumentParser(description=desc)

7
scenarionet/convert_waymo.py
View File

@@ -1,17 +1,18 @@
desc = "Build database from Waymo scenarios" desc = "Build database from Waymo scenarios"
if __name__ == '__main__': if __name__ == '__main__':
import pkg_resources # for suppress warning
import shutil import shutil
import argparse import argparse
import logging import logging
import os import os
import tensorflow as tf
from scenarionet import SCENARIONET_DATASET_PATH, SCENARIONET_REPO_PATH from scenarionet import SCENARIONET_DATASET_PATH, SCENARIONET_REPO_PATH
from scenarionet.converter.utils import write_to_directory from scenarionet.converter.utils import write_to_directory
from scenarionet.converter.waymo.utils import convert_waymo_scenario, get_waymo_scenarios, preprocess_waymo_scenarios from scenarionet.converter.waymo.utils import convert_waymo_scenario, get_waymo_scenarios, \
preprocess_waymo_scenarios
os.environ["CUDA_VISIBLE_DEVICES"] = "" tf.config.experimental.set_visible_devices([], "GPU")
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)

24
scenarionet/tests/script/generate_sensor_offscreen.py
View File

@@ -29,7 +29,7 @@ if __name__ == "__main__":
"vehicle_config": dict( "vehicle_config": dict(
show_navi_mark=False, show_navi_mark=False,
use_special_color=False, use_special_color=False,
image_source="semantic_camera", # image_source="semantic_camera",
lidar=dict(num_lasers=120, distance=50), lidar=dict(num_lasers=120, distance=50),
lane_line_detector=dict(num_lasers=0, distance=50), lane_line_detector=dict(num_lasers=0, distance=50),
side_detector=dict(num_lasers=12, distance=50) side_detector=dict(num_lasers=12, distance=50)
@@ -43,11 +43,11 @@ if __name__ == "__main__":
"camera_height": 1.5, "camera_height": 1.5,
"camera_pitch": None, "camera_pitch": None,
"camera_fov": 60, "camera_fov": 60,
"interface_panel": ["semantic_camera"], # "interface_panel": ["semantic_camera"],
"sensors": dict( "sensors": dict(
semantic_camera=(SemanticCamera, 1600, 900), # semantic_camera=(SemanticCamera, 1600, 900),
depth_camera=(DepthCamera, 800, 600), # depth_camera=(DepthCamera, 800, 600),
rgb_camera=(RGBCamera, 800, 600), rgb_camera=(RGBCamera, 1600, 900),
), ),
# ===== Remove useless items in the images ===== # ===== Remove useless items in the images =====
@@ -66,8 +66,8 @@ if __name__ == "__main__":
# Run it once to initialize the TopDownRenderer # Run it once to initialize the TopDownRenderer
env.render( env.render(
mode="topdown", mode="topdown",
screen_size=(1600, 900), screen_size=(900, 900), # The output image size
film_size=(9000, 9000), film_size=(9000, 9000), # The internal canvas size. You can use this to "crop" images.
target_vehicle_heading_up=True, target_vehicle_heading_up=True,
semantic_map=True, semantic_map=True,
) )
@@ -86,10 +86,16 @@ if __name__ == "__main__":
to_image=False to_image=False
) )
pygame.image.save(ret, str(file_dir / "bev_{}.png".format(t))) pygame.image.save(ret, str(file_dir / "bev_{}.png".format(t)))
env.engine.get_sensor("depth_camera").save_image(env.agent, str(file_dir / "depth_{}.jpg".format(t))) # env.engine.get_sensor("depth_camera").save_image(env.agent, str(file_dir / "depth_{}.jpg".format(t)))
env.engine.get_sensor("rgb_camera").save_image(env.agent, str(file_dir / "rgb_{}.jpg".format(t))) env.engine.get_sensor("rgb_camera").save_image(env.agent, str(file_dir / "rgb_{}.jpg".format(t)))
env.engine.get_sensor("semantic_camera").save_image(env.agent, str(file_dir / "semantic_{}.jpg".format(t))) # env.engine.get_sensor("semantic_camera").save_image(env.agent, str(file_dir / "semantic_{}.jpg".format(t)))
print("Image at step {} is saved at: {}".format(t, file_dir)) print("Image at step {} is saved at: {}".format(t, file_dir))
scenario = env.engine.data_manager.current_scenario
print(
f"Current scenario ID {scenario['id']}, dataset version {scenario['version']}, len: {scenario['length']}"
)
if t == 30: if t == 30:
break break
env.step([1, 0.88]) env.step([1, 0.88])