from gym_ai2thor.envs.mcs_env import McsEnv
from meta_ontroller.meta_controller import MetaController
import sys
if __name__ == "__main__":
env = McsEnv(task="interaction_scenes", scene_type="transferral", start_scene_number=2)
metaController = MetaController(env)
while env.current_scene < len(env.all_scenes) - 1:
env.reset()
result = metaController.excecute()
sys.stdout.flush()
from gym_ai2thor.envs.mcs_env import McsEnv
from int_phy.scene_state import SceneState
import matplotlib.pyplot as plt
scene_name = "object_permanence"
start_scene_number = 3
env = McsEnv(task="intphys_scenes",
scene_type=scene_name,
start_scene_number=start_scene_number)
object_states = []
for _ in range(1):
env.reset(random_init=False)
# print(env.current_scene, env.scene_config['answer'], len(env.scene_config['goal']['action_list']))
scene_state = None
for i, x in enumerate(env.scene_config['goal']['action_list']):
# print(i)
if i == 0:
scene_state = SceneState(env.step_output)
else:
scene_state.update(env.step_output)
env.step(action=x[0])
object_states.append(scene_state)
env.controller.end_scene(None, None)
for i, scene_state in enumerate(object_states):
plt.figure()
for j, (id, obj_state) in enumerate(scene_state.object_state_dict.items()):
v_xs = [v[0] for v in obj_state.velocity_history]