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Update Sensor API in scripts (#39)

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* add semantic cam

* update API

* format
This commit is contained in:
Quanyi Li
2023-10-24 19:20:43 +01:00
committed by GitHub
parent 63a4c38e7f
commit a88e0bd83c
1 changed files with 23 additions and 18 deletions
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41
scenarionet/tests/script/generate_sensor.py
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@@ -1,4 +1,7 @@
import pygame
from metadrive.component.sensors.semantic_camera import SemanticCamera
from metadrive.component.sensors.depth_camera import DepthCamera
from metadrive.component.sensors.rgb_camera import RGBCamera
from metadrive.engine.asset_loader import AssetLoader
from metadrive.envs.scenario_env import ScenarioEnv
from metadrive.policy.replay_policy import ReplayEgoCarPolicy
@@ -10,7 +13,8 @@ if __name__ == "__main__":
{
"use_render": True,
"agent_policy": ReplayEgoCarPolicy,
"show_interface": False,
"show_interface": True,
"interface_panel": ["semantic_camera"],
# "need_lane_localization": False,
"show_logo": False,
"no_traffic": False,
@@ -19,9 +23,9 @@ if __name__ == "__main__":
"reactive_traffic": False,
"show_fps": False,
# "debug": True,
"render_pipeline": True,
"render_pipeline": False,
"daytime": "08:10",
"window_size": (1600, 900),
"window_size": (800, 450),
"camera_dist": 0.8,
"camera_height": 1.5,
"camera_pitch": None,
@@ -36,36 +40,37 @@ if __name__ == "__main__":
# "show_coordinates": True,
# "force_destroy": True,
# "default_vehicle_in_traffic": True,
"default_vehicle_in_traffic": True,
"sensors": dict(semantic_camera=(SemanticCamera, 1600, 900)),
"vehicle_config": dict(
# light=True,
# random_color=True,
show_navi_mark=False,
use_special_color=False,
image_source="depth_camera",
rgb_camera=(1600, 900),
depth_camera=(1600, 900, True),
# no_wheel_friction=True,
image_source="semantic_camera",
lidar=dict(num_lasers=120, distance=50),
lane_line_detector=dict(num_lasers=0, distance=50),
side_detector=dict(num_lasers=12, distance=50)
),
"data_directory": AssetLoader.file_path("nuscenes", return_raw_style=False),
# "image_observation": True,
}
)
# 0,1,3,4,5,6
for seed in range(10):
env.reset(seed=seed)
# for seed in range(10):
while True:
env.reset(seed=6)
for t in range(10000):
env.capture("rgb_deluxe_{}_{}.jpg".format(env.current_seed, t))
ret = env.render(
mode="topdown", screen_size=(1600, 900), film_size=(9000, 9000), target_vehicle_heading_up=True
)
pygame.image.save(ret, "top_down_{}_{}.png".format(env.current_seed, t))
# env.capture("rgb_deluxe_{}_{}.jpg".format(env.current_seed, t))
# ret = env.render(
# mode="topdown", screen_size=(1600, 900), film_size=(9000, 9000), target_vehicle_heading_up=True
# )
# pygame.image.save(ret, "top_down_{}_{}.png".format(env.current_seed, t))
# env.vehicle.get_camera("depth_camera").save_image(env.vehicle, "depth_{}.jpg".format(t))
# env.vehicle.get_camera("rgb_camera").save_image(env.vehicle, "rgb_{}.jpg".format(t))
if t == 100:
# env.engine.get_sensor("semantic_camera").save_image(env.vehicle, "depth_{}.jpg".format(t))
env.engine.get_sensor("semantic_camera").save_image(env.vehicle, "semantic_{}.jpg".format(t))
break
env.step([1, 0.88])
# if d:
if env.episode_step >= env.engine.data_manager.current_scenario_length:
break