def getState(self, observation, env_id=0):
if getNChannels() > 3:
observation = np.dstack((preprocessImage(observation[:, :, :3],
convert_to_rgb=False),
preprocessImage(observation[:, :, 3:],
convert_to_rgb=False)))
else:
observation = preprocessImage(observation, convert_to_rgb=False)
# Create 4D Tensor
observation = observation.reshape(1, *observation.shape)
# Channel first
observation = np.transpose(observation, (0, 3, 2, 1))
observation = th.from_numpy(observation).float().to(self.device)
with th.no_grad():
state = self.model.getStates(observation)[0]
return state.to(th.device("cpu")).detach().numpy()
def getExtendedObservation(self):
if getNChannels() > 3:
self.multi_view = True
self._observation = self.render("rgb_array")
return self._observation