Merge branch 'develop' of github.com:inverted-ai/invertedai into docu…

…mentation

examples/Demo_Drive_REST.py

@@ -47,7 +47,7 @@
         + f"Wrong-way rate: {100*np.array([inf.wrong_way for inf in response.infractions]).mean():.2f}%"
     )
 
-    image = response.bird_view.decode()
+    image = response.birdview.decode()
     frames.append(image)
     im = PImage.fromarray(image)
 imageio.mimsave("iai-drive.gif", np.array(frames), format="GIF-PIL")

invertedai/api/drive.py

@@ -18,7 +18,7 @@ class DriveResponse:
     """
     agent_states: List[AgentState]  #: Predicted states for all agents at the next time step.
     recurrent_states: List[RecurrentState]  #: To pass to :func:`iai.drive` at the subsequent time step.
-    bird_view: Optional[Image]  #: If `get_birdview` was set, this contains the resulting image.
+    birdview: Optional[Image]  #: If `get_birdview` was set, this contains the resulting image.
     infractions: Optional[List[InfractionIndicators]]  #: If `get_infractions` was set, they are returned here.
     is_inside_supported_area: List[bool]  #: For each agent, indicates whether the predicted state is inside supported area.
 
@@ -74,13 +74,13 @@ def drive(
     if should_use_mock_api():
         agent_states = [mock_update_agent_state(s) for s in agent_states]
         present_mask = [True for _ in agent_states]
-        bird_view = get_mock_birdview()
+        birdview = get_mock_birdview()
         infractions = get_mock_infractions(len(agent_states))
         response = DriveResponse(
             agent_states=agent_states,
             is_inside_supported_area=present_mask,
             recurrent_states=recurrent_states,
-            bird_view=bird_view,
+            birdview=birdview,
             infractions=infractions,
         )
         return response
@@ -100,7 +100,7 @@ def _tolist(input_data: List):
         agent_attributes=[state.tolist() for state in agent_attributes],
         recurrent_states=[r.packed for r in recurrent_states],
         traffic_lights_states=traffic_lights_states,
-        get_birdviews=get_birdview,
+        get_birdview=get_birdview,
         get_infractions=get_infractions,
         random_seed=random_seed,
     )
@@ -114,7 +114,7 @@ def _tolist(input_data: List):
             response = DriveResponse(
                 agent_states=[AgentState.fromlist(state) for state in response["agent_states"]],
                 recurrent_states=[RecurrentState(r) for r in response["recurrent_states"]],
-                bird_view=Image(response["bird_view"]) if response['bird_view'] is not None else None,
+                birdview=Image(response["birdview"]) if response['birdview'] is not None else None,
                 infractions=[
                     InfractionIndicators(*infractions)
                     for infractions in response["infraction_indicators"]

invertedai/cosimulation.py

@@ -115,7 +115,7 @@ def npc_states(self) -> List[AgentState]:
         The predictions for ego agents are excluded.
         """
         npc_states = []
-        for (i, s) in self._agent_states:
+        for (i, s) in enumerate(self._agent_states):
             if not self._ego_agent_mask[i]:
                 npc_states.append(s)
         return npc_states
@@ -148,7 +148,7 @@ def step(self, current_ego_agent_states: List[AgentState]) -> None:
                 [inf.wrong_way for inf in response.infractions],
             )
         if self._render_birdview:
-            self._birdview = response.bird_view
+            self._birdview = response.birdview
         self._time_step += 1
 
     def _update_ego_states(self, ego_agent_states):