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Convenience script to make a video out of initial environment
configurations. This can be a useful debugging tool to understand
what different sampled environment configurations look like.
"""
import argparse
import imageio
import numpy as np
import robosuite as suite
from robosuite.utils.input_utils import *
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# camera to use for generating frames
parser.add_argument(
"--camera",
type=str,
default="agentview",
)
# number of frames in output video
parser.add_argument(
"--frames",
type=int,
default=10,
)
# path to output video
parser.add_argument(
"--output",
type=str,
default="reset.mp4",
)
args = parser.parse_args()
camera_name = args.camera
num_frames = args.frames
output_path = args.output
# Create dict to hold options that will be passed to env creation call
options = {}
# print welcome info
print("Welcome to robosuite v{}!".format(suite.__version__))
print(suite.__logo__)
# Choose environment and add it to options
options["env_name"] = choose_environment()
# If a multi-arm environment has been chosen, choose configuration and appropriate robot(s)
if "TwoArm" in options["env_name"]:
# Choose env config and add it to options
options["env_configuration"] = choose_multi_arm_config()
# If chosen configuration was bimanual, the corresponding robot must be Baxter. Else, have user choose robots
if options["env_configuration"] == "bimanual":
options["robots"] = "Baxter"
else:
options["robots"] = []
# Have user choose two robots
print("A multiple single-arm configuration was chosen.\n")
for i in range(2):
print("Please choose Robot {}...\n".format(i))
options["robots"].append(choose_robots(exclude_bimanual=True))
# Else, we simply choose a single (single-armed) robot to instantiate in the environment
else:
options["robots"] = choose_robots(exclude_bimanual=True)
# initialize the task
env = suite.make(
**options,
has_renderer=False,
has_offscreen_renderer=True,
ignore_done=True,
use_camera_obs=False,
control_freq=20,
)
# write a video
video_writer = imageio.get_writer(output_path, fps=5)
for i in range(num_frames):
env.reset()
video_img = env.sim.render(height=512, width=512, camera_name=camera_name)[::-1]
env.step(np.zeros_like(env.action_spec[0]))
video_writer.append_data(video_img)
video_writer.close()
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