Merge pull request #116 from inverted-ai/develop

Develop

.gitignore

@@ -1,7 +1,8 @@
 # Dev Stuff
 dev/
 dev.py
-
+img/
+gifs/
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

examples/carla/carla_demo.py

@@ -12,25 +12,24 @@
 the supported area, so that's where the NPCs need to be maximally realistic.
 """
 import invertedai as iai
-from carla_simulator import CarlaEnv, CarlaSimulationConfig
+from carla_simulator import CarlaEnv, CarlaSimulationConfig, PreSets
 import argparse
 import pygame
 from tqdm import tqdm
 
-
 # Configuration options to set from command line.
 parser = argparse.ArgumentParser(description="Simulation Parameters.")
-parser.add_argument("-n", "--location", type=str, default="carla:Town03:Roundabout",
+parser.add_argument("-n", "--location", type=str, default="carla:Town03",
                     help='See data/static_carla.py for a list of available locations.')
 parser.add_argument("-c", "--agent_count", type=int, default=8)
 parser.add_argument("-l", "--episode_length", type=int, default=30)
 parser.add_argument("-e", "--ego_spawn_point", default="demo")
 parser.add_argument("-s", "--spectator_transform", default=None)
 parser.add_argument("-i", "--initial_states", default=None)
-parser.add_argument("-m", "--non_roi_npc_mode", type=int, default=1)
+parser.add_argument("-m", "--non_roi_npc_mode", type=int, default=2)
 parser.add_argument("-pi", "--npc_population_interval", type=int, default=6)
 parser.add_argument("-ca", "--max_cars_in_map", type=int, default=100)
-parser.add_argument("-ep", "--episodes", type=int, default=5)
+parser.add_argument("-ep", "--episodes", type=int, default=1)
 parser.add_argument("--api_key", type=str, default=None)
 parser.add_argument("-mc", "--manual_control_ego", action="store_true")
 
@@ -54,16 +53,25 @@
     npc_population_interval=args.npc_population_interval,
     max_cars_in_map=args.max_cars_in_map,
     manual_control_ego=args.manual_control_ego,
+    map_center=PreSets.map_centers["carla:Town03:Roundabout"]
 )
 sim = CarlaEnv(
     cfg=carla_cfg,
 )
 
-# Initialize simulation with an API call
-response = iai.initialize(
-    location=args.location,
-    agent_count=args.agent_count,
-)
+for _ in range(10):
+    try:
+        # Initialize simulation with an API call
+        response = iai.initialize(
+            location=args.location,
+            agent_count=args.agent_count,
+            location_of_interest=carla_cfg.map_center,
+        )
+        break
+    except:
+        print("Re-initializing")
+else:
+    raise Exception("Unable to initialize")
 
 pygame.init()
 

examples/carla/carla_demo_traffic_light.py

@@ -22,7 +22,7 @@
 
 # Configuration options to set from command line.
 parser = argparse.ArgumentParser(description="Simulation Parameters.")
-parser.add_argument("-n", "--location", type=str, default="carla:Town03:Roundabout",
+parser.add_argument("-n", "--location", type=str, default="carla:Town03",
                     help='See data/static_carla.py for a list of available locations.')
 parser.add_argument("-c", "--agent_count", type=int, default=8)
 parser.add_argument("-l", "--episode_length", type=int, default=30)
@@ -32,7 +32,7 @@
 parser.add_argument("-m", "--non_roi_npc_mode", type=int, default=1)
 parser.add_argument("-pi", "--npc_population_interval", type=int, default=6)
 parser.add_argument("-ca", "--max_cars_in_map", type=int, default=100)
-parser.add_argument("-ep", "--episodes", type=int, default=5)
+parser.add_argument("-ep", "--episodes", type=int, default=1)
 parser.add_argument("--api_key", type=str, default=None)
 parser.add_argument("-mc", "--manual_control_ego", action="store_true")
 
@@ -60,7 +60,6 @@
     npc_population_interval=args.npc_population_interval,
     max_cars_in_map=args.max_cars_in_map,
     manual_control_ego=args.manual_control_ego,
-    pygame_window=False,
     spectator_fov=150
 )
 sim = CarlaEnv(

examples/carla/carla_simulator.py

@@ -25,6 +25,13 @@
 import pygame
 
 
+@dataclass
+class PreSets:
+    map_centers = MAP_CENTERS
+    demo_locations = DEMO_LOCATIONS
+    npc_bps = NPC_BPS
+
+
 @dataclass
 class CarlaSimulationConfig:
     """
@@ -36,7 +43,8 @@ class CarlaSimulationConfig:
     """
     ego_bp: str = "vehicle.tesla.model3"  #: blueprint name for the ego vehicle
     npc_bps: Tuple[str] = NPC_BPS  #: blueprint names for NPC vehicles
-    location: str = "CARLA:Town03:Roundabout"  #: in format recognized by Inverted AI API
+    location: str = "carla:Town03"  #: in format recognized by Inverted AI API center map coordinate of the selected carla town
+    map_center: Tuple[float] = (0.0, 0.0)
     fps: int = 10  #: 10 is the only value currently compatible with Inverted AI API
     traffic_count: int = 20  #: total number of vehicles to place in simulation
     episode_length: int = 20  #: in seconds
@@ -162,7 +170,7 @@ def __init__(
         self.rng = random.Random(cfg.seed)
 
         # assemble information about area where Inverted AI NPCs will be deployed
-        centers = MAP_CENTERS[cfg.location]
+        centers = cfg.map_center
         self.roi_center = cord(x=centers[0], y=centers[1])
         self.proximity_threshold = (
             50
@@ -195,7 +203,7 @@ def __init__(
                 if tl.agent_type == "traffic-light-actor":
                     for tlo in traffic_lights_obj:
                         x, y = tlo.get_transform().location.x, tlo.get_transform().location.y
-                        if (abs(x + tl.center.x) + abs(y - tl.center.y)) < 1:
+                        if (abs(x - tl.center.x) + abs(y - tl.center.y)) < 1:
                             for traffic_line in tl.dependant:
                                 self.traffic_lights[traffic_line] = tlo