major changes

docs/source/examples/index.md

@@ -1,9 +1,9 @@
 # Examples
 Several examples are provided [here](https://github.com/inverted-ai/invertedai/tree/master/examples).
 ## Demo
-- **Goolge Colab**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/inverted-ai/invertedai-drive/blob/develop/examples/Colab-Demo.ipynb)
+- Running a demo on **Goolge Colab**: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/inverted-ai/invertedai-drive/blob/develop/examples/Colab-Demo.ipynb)
 
-- **Locally**:  Download the 
+- Running a demo **Locally**:  Download the 
 <a href="https://minhaskamal.github.io/DownGit/#/home?url=https://github.com/inverted-ai/invertedai/tree/master/examples" target="_blank">examples directory</a>, navigate to the unzipped directory in terminal and run 
 
 ```
@@ -14,5 +14,11 @@ pip install -r requirements.txt
 .venv/bin/jupyter notebook Drive-Demo.ipynb
 ```
 
+---
+```{toctree}
+:maxdepth: 2
+
+```
+
 
 

docs/source/index.md

@@ -31,7 +31,7 @@ Get Started
 
 
 ```{toctree}
-:maxdepth: 4
+:maxdepth: 2
 
 getstarted/index
 pythonapi/index
@@ -47,12 +47,12 @@ apireference
 carlasim
 ```
 
-```{toctree}
-:caption: Python SDK Library
-:maxdepth: 2
+<!-- ```{toctree} -->
+<!-- :caption: Python SDK Library -->
+<!-- :maxdepth: 2 -->
 
-modules/modules
-```
+<!-- modules/modules -->
+<!-- ``` -->
 
 
 ```{eval-rst}
@@ -62,4 +62,3 @@ REFERENCES
 * :ref:`modindex`
 * :ref:`search`
 ```
-

docs/source/pythonapi/index.md

@@ -8,6 +8,7 @@ sdk-drive
 sdk-initialize
 sdk-available-locations
 sdk-location-info
+sdk-dataclasses
 ```
 
 

docs/source/pythonapi/sdk-dataclasses.md

@@ -0,0 +1,14 @@
+# DataClasses
+
+
+```{eval-rst}
+.. automodule:: invertedai.models
+   :members:
+   :undoc-members:
+   :show-inheritance:
+```
+
+<!-- .. autoclass:: invertedai.api_resources.TestReturn -->
+
+
+

docs/source/pythonapi/sdk-drive.md

@@ -4,5 +4,3 @@
 ```{eval-rst}
 .. autofunction:: invertedai.api_resources.drive
 ```
-
-

docs/source/pythonapi/sdk-location-info.md

@@ -4,5 +4,3 @@
 ```{eval-rst}
 .. autofunction:: invertedai.api_resources.location_info
 ```
-
-

examples/Demo_Drive.py

@@ -24,43 +24,44 @@
 iai.add_apikey("")
 
 response = iai.available_locations("carla", "roundabout")
-breakpoint()
 response = iai.location_info(location=args.location)
+
 file_name = args.location.replace(":", "_")
-if response["lanelet_map_source"] is not None:
+if response.lanelet_map_source is not None:
     file_path = f"{file_name}.osm"
     with open(file_path, "w") as f:
-        f.write(response["lanelet_map_source"])
-if response["rendered_map"] is not None:
+        f.write(response.lanelet_map_source)
+if response.rendered_map is not None:
     file_path = f"{file_name}.jpg"
-    rendered_map = np.array(response["rendered_map"], dtype=np.uint8)
+    rendered_map = np.array(response.rendered_map, 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["attributes"]
+agent_sizes = response.agent_sizes
 frames = []
-for i in tqdm(range(50)):
+pbar = tqdm(range(50))
+for i in pbar:
     response = iai.drive(
-        agent_attributes=agent_attributes,
-        states=response["states"],
-        recurrent_states=response["recurrent_states"],
+        agent_sizes=agent_sizes,
+        agent_states=response.agent_states,
+        recurrent_states=response.recurrent_states,
         get_birdviews=True,
         location=args.location,
         steps=1,
-        traffic_states_id=response["traffic_states_id"],
+        traffic_states_id=response.traffic_states_id,
         get_infractions=True,
     )
-    print(
-        f"Collision rate: {100*np.array(response['collision'])[-1, :].mean():.2f}% | "
-        + f"Off-road rate: {100*np.array(response['offroad'])[-1, :].mean():.2f}% | "
-        + f"Wrong-way rate: {100*np.array(response['wrong_way'])[-1, :].mean():.2f}%"
+    pbar.set_description(
+        f"Collision rate: {100*np.array(response.collision)[-1, :].mean():.2f}% | "
+        + f"Off-road rate: {100*np.array(response.offroad)[-1, :].mean():.2f}% | "
+        + f"Wrong-way rate: {100*np.array(response.wrong_way)[-1, :].mean():.2f}%"
     )
 
-    birdview = np.array(response["bird_view"], dtype=np.uint8)
+    birdview = np.array(response.bird_view, dtype=np.uint8)
     image = cv2.imdecode(birdview, cv2.IMREAD_COLOR)
     frames.append(image)
     im = PImage.fromarray(image)

examples/Drive-Demo.ipynb

@@ -10,14 +10,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "id": "911445d4-8b61-49a1-9620-d1f3eb0c4199",
    "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib widget\n",
-    "# import sys\n",
-    "# sys.path.append('../')\n",
+    "import sys\n",
+    "sys.path.append('../')\n",
     "# !pip install invertedai==0.0.3rc0\n",
     "from IPython.display import clear_output\n",
     "from invertedai import Jupyter_Render\n",
@@ -29,7 +29,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "id": "d6b93c9a-a972-4c40-9d6d-2b21f3215b39",
    "metadata": {},
    "outputs": [
@@ -49,14 +49,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "id": "069cf9cb-30eb-4378-b4f9-9cb7d9038620",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0299dc9be2d546cfa8126756ec8722f7",
+       "model_id": "96720695a1a74d45aea3100d5df4f957",
        "version_major": 2,
        "version_minor": 0
       },
@@ -70,7 +70,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "789d889962b1437b9bd9d650f7a66a2b",
+       "model_id": "3d93a85cac944aca9b48e3ee5a784338",
        "version_major": 2,
        "version_minor": 0
       },
@@ -102,41 +102,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 5,
    "id": "94506da0-9a15-4dc0-9d57-5ac30bc36d72",
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Unable to spawn a scenario for 10 agents,  1 spawned instead.\n"
+      "Unable to spawn a scenario for 10 agents,  8 spawned instead.\n"
      ]
     }
    ],
    "source": [
-    "rendered_map = iai.location_info(location=location)['rendered_map']\n",
+    "rendered_map = iai.location_info(location=location).rendered_map\n",
     "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",
     "    location=location,\n",
     "    agent_count=10,\n",
     ")\n",
-    "agent_attributes = response[\"attributes\"]\n",
+    "agent_sizes = response.agent_sizes\n",
     "frames = []\n",
     "for t in range(simulation_length):\n",
     "    response = iai.drive(\n",
-    "        agent_attributes=agent_attributes,\n",
-    "        states=response[\"states\"],\n",
-    "        recurrent_states=response[\"recurrent_states\"],\n",
+    "        agent_sizes=agent_sizes,\n",
+    "        agent_states=response.agent_states,\n",
+    "        recurrent_states=response.recurrent_states,\n",
     "        get_birdviews=True,\n",
     "        location=location,\n",
     "        steps=1,\n",
     "        exclude_ego_agent=1,\n",
-    "        traffic_states_id=response[\"traffic_states_id\"],\n",
+    "        traffic_states_id=response.traffic_states_id,\n",
     "    )\n",
-    "    birdview = cv2.imdecode(np.array(response[\"bird_view\"], dtype=np.uint8), cv2.IMREAD_COLOR)\n",
+    "    birdview = cv2.imdecode(np.array(response.bird_view, dtype=np.uint8), cv2.IMREAD_COLOR)\n",
     "    renderer.add_frame(birdview)"
    ]
   },