""" 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()