Merge branch 'documentation' into mock-api

examples/Demo_Drive.py

@@ -21,13 +21,9 @@
 parser.add_argument("--location", type=str, default="iai:ubc_roundabout")
 args = parser.parse_args()
 
-api_key = args.api_key or os.environ.get('IAI_API_KEY', None)
-if api_key:
-    iai.add_apikey(api_key)
-else:
-    print("Running mock API - specify IAI_API_KEY to obtain real results")
-    iai.use_mock_api()
+iai.add_apikey(args.api_key)
 
+# response = iai.available_locations("carla", "roundabout")
 response = iai.location_info(location=args.location)
 
 file_name = args.location.replace(":", "_")
@@ -40,30 +36,24 @@
     rendered_map = np.array(response.birdview_image, dtype=np.uint8)
     image = cv2.imdecode(rendered_map, cv2.IMREAD_COLOR)
     cv2.imwrite(file_path, image)
-response = iai.initialize(
+simulation = iai.Simulation(
     location=args.location,
     agent_count=10,
-    agent_attributes=None,
+    monitor_infractions=True,
+    render_birdview=True,
 )
-agent_attributes = response.agent_attributes
 frames = []
 pbar = tqdm(range(50))
 for i in pbar:
-    response = iai.drive(
-        agent_attributes=agent_attributes,
-        agent_states=response.agent_states,
-        recurrent_states=response.recurrent_states,
-        get_birdviews=True,
-        location=args.location,
-        get_infractions=True,
-    )
+    simulation.step(current_ego_agent_states=[])
+    collision, offroad, wrong_way = simulation.infractions
     pbar.set_description(
-        f"Collision rate: {100*np.array([inf.collisions for inf in response.infractions]).mean():.2f}% | "
-        + f"Off-road rate: {100*np.array([inf.offroad for inf in response.infractions]).mean():.2f}% | "
-        + f"Wrong-way rate: {100*np.array([inf.wrong_way for inf in response.infractions]).mean():.2f}%"
+        f"Collision rate: {100*np.array(collision).mean():.2f}% | "
+        + f"Off-road rate: {100*np.array(offroad).mean():.2f}% | "
+        + f"Wrong-way rate: {100*np.array(wrong_way).mean():.2f}%"
     )
 
-    birdview = np.array(response.bird_view, dtype=np.uint8)
+    birdview = np.array(simulation.birdview, dtype=np.uint8)
     image = cv2.imdecode(birdview, cv2.IMREAD_COLOR)
     frames.append(image)
     im = PImage.fromarray(image)

examples/Demo_Drive_REST.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env ipython
+import os
+import sys
+from PIL import Image as PImage
+import imageio
+import numpy as np
+import cv2
+from tqdm import tqdm
+import argparse
+from dotenv import load_dotenv
+
+load_dotenv()
+if os.environ.get("DEV", False):
+    sys.path.append("../")
+import invertedai as iai
+
+# logger.setLevel(10)
+
+parser = argparse.ArgumentParser(description="Simulation Parameters.")
+parser.add_argument("--api_key", type=str, default="")
+parser.add_argument("--location", type=str, default="iai:ubc_roundabout")
+args = parser.parse_args()
+
+iai.add_apikey("")
+
+response = iai.location_info(location=args.location)
+
+file_name = args.location.replace(":", "_")
+if response.osm_map is not None:
+    file_path = f"{file_name}.osm"
+    with open(file_path, "w") as f:
+        f.write(response.osm_map[0])
+if response.birdview_image is not None:
+    file_path = f"{file_name}.jpg"
+    rendered_map = np.array(response.birdview_image, dtype=np.uint8)
+    image = cv2.imdecode(rendered_map, cv2.IMREAD_COLOR)
+    cv2.imwrite(file_path, image)
+response = iai.initialize(
+    location=args.location,
+    agent_count=10,
+)
+agent_attributes = response.agent_attributes
+frames = []
+pbar = tqdm(range(50))
+for i in pbar:
+    response = iai.drive(
+        agent_attributes=agent_attributes,
+        agent_states=response.agent_states,
+        recurrent_states=response.recurrent_states,
+        get_birdviews=True,
+        location=args.location,
+        get_infractions=True,
+    )
+    pbar.set_description(
+        f"Collision rate: {100*np.array([inf.collisions for inf in response.infractions]).mean():.2f}% | "
+        + f"Off-road rate: {100*np.array([inf.offroad for inf in response.infractions]).mean():.2f}% | "
+        + f"Wrong-way rate: {100*np.array([inf.wrong_way for inf in response.infractions]).mean():.2f}%"
+    )
+
+    birdview = np.array(response.bird_view, dtype=np.uint8)
+    image = cv2.imdecode(birdview, cv2.IMREAD_COLOR)
+    frames.append(image)
+    im = PImage.fromarray(image)
+imageio.mimsave("iai-drive.gif", np.array(frames), format="GIF-PIL")

examples/Drive-Demo.ipynb

@@ -126,22 +126,15 @@
     "rendered_map = cv2.imdecode(np.array(rendered_map, dtype=np.uint8), cv2.IMREAD_COLOR)\n",
     "renderer.add_frame(rendered_map)\n",
     "\n",
-    "response = iai.initialize(\n",
+    "simulation = iai.Simulation(\n",
     "    location=location,\n",
     "    agent_count=10,\n",
-    "    agent_attributes=None,\n",
+    "    render_birdview=True,\n",
     ")\n",
-    "agent_attributes = response.agent_attributes\n",
     "frames = []\n",
     "for t in range(simulation_length):\n",
-    "    response = iai.drive(\n",
-    "        agent_attributes=agent_attributes,\n",
-    "        agent_states=response.agent_states,\n",
-    "        recurrent_states=response.recurrent_states,\n",
-    "        get_birdviews=True,\n",
-    "        location=location,\n",
-    "    )\n",
-    "    birdview = cv2.imdecode(np.array(response.bird_view, dtype=np.uint8), cv2.IMREAD_COLOR)\n",
+    "    simulation.step(current_ego_agent_states=[])\n",
+    "    birdview = cv2.imdecode(np.array(simulation.birdview, dtype=np.uint8), cv2.IMREAD_COLOR)\n",
     "    renderer.add_frame(birdview)"
    ]
   },

invertedai/__init__.py

@@ -7,6 +7,7 @@
     initialize,
     location_info,
 )
+from invertedai.simulation import Simulation
 from invertedai.utils import Jupyter_Render, IAILogger, Session
 
 load_dotenv()
@@ -28,12 +29,12 @@
     use_mock_api()
 
 model_resources = {
-    "initialize": ("get", "/initialize"),
+    "initialize": ("post", "/initialize"),
     "drive": ("post", "/drive"),
     "location_info": ("get", "/location_info"),
-    "available_locations": ("get", "/available_locations"),
 }
 __all__ = [
+    "Simulation",
     "drive",
     "initialize",
     "location_info",

invertedai/api_resources.py

@@ -17,8 +17,14 @@
 from typing import List, Optional, Dict
 import time
 import invertedai as iai
-from invertedai.mock import get_mock_birdview, get_mock_agent_attributes, get_mock_agent_state, \
-    get_mock_recurrent_state, mock_update_agent_state, get_mock_infractions
+from invertedai.mock import (
+    get_mock_birdview,
+    get_mock_agent_attributes,
+    get_mock_agent_state,
+    get_mock_recurrent_state,
+    mock_update_agent_state,
+    get_mock_infractions,
+)
 from invertedai.models import (
     LocationResponse,
     InitializeResponse,
@@ -80,7 +86,14 @@ def location_info(
     """
 
     if mock_api:
-        response = LocationResponse(rendered_map=get_mock_birdview(), lanelet_map_source=None, static_actors=None)
+        response = LocationResponse(
+            version="v0.0.0",
+            birdview_image=get_mock_birdview(),
+            osm_map=None,
+            static_actors=[],
+            bounding_polygon=[],
+            max_agent_number=10,
+        )
         return response
 
     start = time.time()
@@ -94,6 +107,9 @@ def location_info(
                 response["static_actors"] = [
                     StaticMapActor(**actor) for actor in response["static_actors"]
                 ]
+            if response["osm_map"] is not None:
+                response["osm_map"] = (response["osm_map"], response["map_origin"])
+            del response["map_origin"]
             return LocationResponse(**response)
         except TryAgain as e:
             if timeout is not None and time.time() > start + timeout:
@@ -164,36 +180,29 @@ def initialize(
             agent_states = states_history[-1]
         recurrent_states = [get_mock_recurrent_state() for _ in range(agent_count)]
         response = InitializeResponse(
-            agent_states=agent_states, agent_attributes=agent_attributes, recurrent_states=recurrent_states
+            agent_states=agent_states,
+            agent_attributes=agent_attributes,
+            recurrent_states=recurrent_states,
         )
         return response
 
+    model_inputs = dict(
+        location=location,
+        num_agents_to_spawn=agent_count,
+        states_history=states_history
+        if states_history is None
+        else [state.tolist() for state in states_history],
+        agent_attributes=agent_attributes
+        if agent_attributes is None
+        else [state.tolist() for state in agent_attributes],
+        traffic_light_state_history=traffic_light_state_history,
+        random_seed=random_seed,
+    )
     start = time.time()
     timeout = TIMEOUT
-
     while True:
         try:
-            include_recurrent_states = (
-                False if location.split(":")[0] == "huawei" else True
-            )
-            params = {
-                "location": location,
-                "num_agents_to_spawn": agent_count,
-                "include_recurrent_states": include_recurrent_states,
-            }
-            model_inputs = dict(
-                states_history=states_history
-                if states_history is None
-                else [state.tolist() for state in states_history],
-                agent_attributes=agent_attributes
-                if agent_attributes is None
-                else [state.tolist() for state in agent_attributes],
-                traffic_light_state_history=traffic_light_state_history,
-                random_seed=random_seed,
-            )
-            initial_states = iai.session.request(
-                model="initialize", params=params, data=model_inputs
-            )
+            initial_states = iai.session.request(model="initialize", data=model_inputs)
             agents_spawned = len(initial_states["agent_states"])
             if agents_spawned != agent_count:
                 iai.logger.warning(
@@ -221,9 +230,7 @@ def drive(
     agent_states: List[AgentState] = [],
     agent_attributes: List[AgentAttributes] = [],
     recurrent_states: List[RecurrentState] = [],
-    traffic_lights_states: Optional[
-        Dict[TrafficLightId, TrafficLightState]
-    ] = None,
+    traffic_lights_states: Optional[Dict[TrafficLightId, TrafficLightState]] = None,
     get_birdviews: bool = False,
     get_infractions: bool = False,
     random_seed: Optional[int] = None,
@@ -294,8 +301,11 @@ def drive(
         bird_view = get_mock_birdview()
         infractions = get_mock_infractions(len(agent_states))
         response = DriveResponse(
-            agent_states=agent_states, present_mask=present_mask, recurrent_states=recurrent_states,
-            bird_view=bird_view, infractions=infractions
+            agent_states=agent_states,
+            is_inside_supported_area=present_mask,
+            recurrent_states=recurrent_states,
+            bird_view=bird_view,
+            infractions=infractions,
         )
         return response
 
@@ -318,7 +328,6 @@ def _tolist(input_data: List):
         get_infractions=get_infractions,
         random_seed=random_seed,
     )
-
     start = time.time()
     timeout = TIMEOUT