Merged develop into branch

.github/workflows/CI.yml

@@ -0,0 +1,44 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - master
+      - develop
+  pull_request:
+    branches:
+      - "*"
+    types:
+      - opened
+      - reopened
+      - synchronize
+      - ready_for_review
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install Poetry
+      run: |
+        curl -sSL https://install.python-poetry.org | python3 -
+
+    - name: Install dependencies
+      run: |
+        $HOME/.local/bin/poetry install --without dev
+
+    - name: Run tests
+      env:
+        IAI_API_KEY: ${{ secrets.IAI_API_KEY }}
+      run: |
+        $HOME/.local/bin/poetry run pytest tests/

.github/workflows/publish-to-pypi.yml

@@ -34,4 +34,4 @@ jobs:
       if: startsWith(github.ref, 'refs/tags')
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        password: ${{ secrets.PYPI_API_TOKEN }}
+        password: ${{ secrets.PYPI_API_TOKEN }}

README.md

@@ -1,7 +1,7 @@
 [pypi-badge]: https://badge.fury.io/py/invertedai.svg
 [pypi-link]: https://pypi.org/project/invertedai/
 [colab-badge]: https://colab.research.google.com/assets/colab-badge.svg
-[colab-link]: https://colab.research.google.com/github/inverted-ai/invertedai/blob/develop/examples/IAI_demo.ipynb
+[colab-link]: https://colab.research.google.com/github/inverted-ai/invertedai/blob/develop/examples/IAI_full_demo.ipynb
 [rest-link]: https://app.swaggerhub.com/apis-docs/InvertedAI/InvertedAI
 [examples-link]: https://github.com/inverted-ai/invertedai/tree/master/examples
 
@@ -15,7 +15,7 @@
 <!-- start elevator-pitch -->
 Inverted AI provides an API for controlling non-playable characters (NPCs) in autonomous driving simulations,
 available as either a [REST API][rest-link] or a [Python SDK](https://docs.inverted.ai/en/latest/pythonapi/index.html), (and [C++ SDK](https://docs.inverted.ai/en/latest/cppapi/index.html)) built on top of it. Using the API requires an access key -
-[contact us](mailto:sales@inverted.ai) to get yours. This page describes how to get started quickly. For more in-depth understanding,
+create an account on our [user portal](https://www.inverted.ai/portal/login) to get one.  New users are given keys preloaded with an API access budget; researcher users affiliated to academic institutions generally receive a sufficient amount of credits to conduct their research for free.  This page describes how to get started quickly. For more in-depth understanding,
 see the [API usage guide](https://docs.inverted.ai/en/latest/userguide.html), and detailed documentation for the [REST API][rest-link],
 the [Python SDK](https://docs.inverted.ai/en/latest/pythonapi/index.html), and the [C++ SDK](https://docs.inverted.ai/en/latest/cppapi/index.html).
 To understand the underlying technology and why it's necessary for autonomous driving simulations, visit the

examples/carla/region_drive.py

@@ -1,6 +1,9 @@
+import sys
+sys.path.append('../')
+
 import argparse
 import invertedai as iai
-from invertedai.simulation.simulator import Simulation, SimulationConfig
+from simulation.simulator import Simulation, SimulationConfig
 import pathlib
 import pygame
 from tqdm import tqdm
@@ -17,7 +20,7 @@
 parser.add_argument("-cap", "--quadtree_capacity", type=int, default=15)
 parser.add_argument("-ad", "--agent_density", type=int, default=10)
 parser.add_argument("-ri", "--re_initialization", type=int, default=30)
-parser.add_argument("-len", "--simulation_length", type=int, default=10000)
+parser.add_argument("-len", "--simulation_length", type=int, default=600)
 args = parser.parse_args()
 
 
@@ -29,12 +32,12 @@
 
 cfg = SimulationConfig(location=args.location, map_center=(response.map_center.x, response.map_center.y),
                        map_fov=response.map_fov, rendered_static_map=rendered_static_map,
-                       map_width=response.map_fov+200, map_height=response.map_fov+200, agent_density=args.agent_density,
+                       map_width=response.map_fov, map_height=response.map_fov, agent_density=args.agent_density,
                        initialize_stride=50, quadtree_capacity=args.quadtree_capacity,
                        re_initialization_period=args.re_initialization)
 simulation = Simulation(cfg=cfg)
 
-fps = 100
+fps = 60
 clock = pygame.time.Clock()
 run = True
 start = perf_counter()

examples/simulation/regions.py

@@ -2,7 +2,7 @@
 from simulation.utils import Rectangle, RE_INITIALIZATION_PERIOD, DEBUG
 from typing import List, Optional, Callable
 from random import randint
-from invertedai import drive, async_drive
+from invertedai.api.drive import drive, async_drive
 from simulation.car import Car
 
 

invertedai/__init__.py

@@ -13,15 +13,20 @@
 dev = strtobool(os.environ.get("IAI_DEV", "false"))
 if dev:
     dev_url = os.environ.get("IAI_DEV_URL", "http://localhost:8000")
+commercial_url = "https://api.inverted.ai/v0/aws/m1"
+academic_url = "https://api.inverted.ai/v0/academic/m1"
 
 log_level = os.environ.get("IAI_LOG_LEVEL", "WARNING")
 log_console = strtobool(os.environ.get("IAI_LOG_CONSOLE", "true"))
 log_file = strtobool(os.environ.get("IAI_LOG_FILE", "false"))
 api_key = os.environ.get("IAI_API_KEY", "")
 
+
 logger = IAILogger(level=log_level, consoel=bool(log_console), log_file=bool(log_file))
 
-session = Session(api_key)
+session = Session()
+if api_key:
+    session.add_apikey(api_key)
 add_apikey = session.add_apikey
 use_mock_api = session.use_mock_api
 

invertedai/api/drive.py

@@ -41,20 +41,22 @@ class DriveResponse(BaseModel):
     is_inside_supported_area: List[
         bool
     ]  #: For each agent, indicates whether the predicted state is inside supported area.
+    model_version: str  # Model version used for this API call
 
 
 @validate_arguments
 def drive(
-    location: str,
-    agent_states: List[AgentState],
-    agent_attributes: List[AgentAttributes],
-    recurrent_states: List[RecurrentState],
-    traffic_lights_states: Optional[TrafficLightStatesDict] = None,
-    get_birdview: bool = False,
-    rendering_center: Optional[Tuple[float, float]] = None,
-    rendering_fov: Optional[float] = None,
-    get_infractions: bool = False,
-    random_seed: Optional[int] = None,
+        location: str,
+        agent_states: List[AgentState],
+        agent_attributes: List[AgentAttributes],
+        recurrent_states: List[RecurrentState],
+        traffic_lights_states: Optional[TrafficLightStatesDict] = None,
+        get_birdview: bool = False,
+        rendering_center: Optional[Tuple[float, float]] = None,
+        rendering_fov: Optional[float] = None,
+        get_infractions: bool = False,
+        random_seed: Optional[int] = None,
+        model_version: Optional[str] = None
 ) -> DriveResponse:
     """
     Parameters
@@ -71,7 +73,8 @@ def drive(
     agent_attributes:
         Static attributes of all agents.
         List of agent attributes. Each agent requires, length: [float]
-        width: [float] and rear_axis_offset: [float] all in meters.
+        width: [float] and rear_axis_offset: [float] all in meters. agent_type: [str],
+        currently supports 'car' and 'pedestrian'.
 
     recurrent_states:
         Recurrent states for all agents, obtained from the previous call to
@@ -99,17 +102,15 @@ def drive(
     random_seed:
         Controls the stochastic aspects of agent behavior for reproducibility.
 
+    model_version:
+        Optionally specify the version of the model. If None is passed which is by default, the best model will be used.
     See Also
     --------
     :func:`initialize`
     :func:`location_info`
     :func:`light`
     :func:`blame`
     """
-    if len(agent_states) != len(agent_attributes):
-        raise InvalidInput("Incompatible Number of Agents in either 'agent_states' or 'agent_attributes'.")
-    if len(agent_states) != len(recurrent_states):
-        raise InvalidInput("Incompatible Number of Agents in either 'agent_states' or 'recurrent_states'.")
 
     if should_use_mock_api():
         agent_states = [mock_update_agent_state(s) for s in agent_states]
@@ -144,7 +145,8 @@ def _tolist(input_data: List):
         get_infractions=get_infractions,
         random_seed=random_seed,
         rendering_center=rendering_center,
-        rendering_fov=rendering_fov
+        rendering_fov=rendering_fov,
+        model_version=model_version
     )
     start = time.time()
     timeout = TIMEOUT
@@ -170,33 +172,36 @@ def _tolist(input_data: List):
                 if response["infraction_indicators"]
                 else [],
                 is_inside_supported_area=response["is_inside_supported_area"],
+                model_version=response["model_version"]
             )
 
             return response
         except APIConnectionError as e:
             iai.logger.warning("Retrying")
             if (
-                timeout is not None and time.time() > start + timeout
+                    timeout is not None and time.time() > start + timeout
             ) or not e.should_retry:
                 raise e
 
 
 @validate_arguments
 async def async_drive(
-    location: str,
-    agent_states: List[AgentState],
-    agent_attributes: List[AgentAttributes],
-    recurrent_states: List[RecurrentState],
-    traffic_lights_states: Optional[TrafficLightStatesDict] = None,
-    get_birdview: bool = False,
-    rendering_center: Optional[Tuple[float, float]] = None,
-    rendering_fov: Optional[float] = None,
-    get_infractions: bool = False,
-    random_seed: Optional[int] = None,
+        location: str,
+        agent_states: List[AgentState],
+        agent_attributes: List[AgentAttributes],
+        recurrent_states: List[RecurrentState],
+        traffic_lights_states: Optional[TrafficLightStatesDict] = None,
+        get_birdview: bool = False,
+        rendering_center: Optional[Tuple[float, float]] = None,
+        rendering_fov: Optional[float] = None,
+        get_infractions: bool = False,
+        random_seed: Optional[int] = None,
+        model_version: Optional[str] = None
 ) -> DriveResponse:
     """
     A light async version of :func:`drive`
     """
+
     def _tolist(input_data: List):
         if not isinstance(input_data, list):
             return input_data.tolist()
@@ -216,7 +221,8 @@ def _tolist(input_data: List):
         get_infractions=get_infractions,
         random_seed=random_seed,
         rendering_center=rendering_center,
-        rendering_fov=rendering_fov
+        rendering_fov=rendering_fov,
+        model_version=model_version,
     )
     response = await iai.session.async_request(model="drive", data=model_inputs)
 
@@ -237,6 +243,7 @@ def _tolist(input_data: List):
         if response["infraction_indicators"]
         else [],
         is_inside_supported_area=response["is_inside_supported_area"],
+        model_version=response["model_version"]
     )
 
     return response