The data is generated with ```leaderboard/team_code/auto_pilot.py``` in 8 CARLA towns using the routes and scenarios files provided at ```leaderboard/data``` on CARLA 0.9.10.1
```Shell
chmod +x download_carla.sh
./download_data.sh
```
We have provided two datasets:
- clear_weather_data: contains only `ClearNoon` weather. This dataset is used for the experiments described in the paper and generalization to new town results shown in the [video](https://youtu.be/WxadQyQ2gMs).
- 14_weathers_data: contains 14 preset weather conditions mentioned in ```leaderboard/team_code/auto_pilot.py```. This dataset is used for training models for the [leaderboard](https://leaderboard.carla.org/leaderboard) and the generalization to new weather results shown in the [video](https://youtu.be/WxadQyQ2gMs).
The dataset is structured as follows:
```
- TownX_{tiny,small,long}: corresponding to different towns and routes files
- routes_X: contains data for an individual route
- rgb_{front, left, right, rear}: multi-view camera images at 400x300 resolution
- topdown: topdown segmentation images required for training LBC
- 2d_bbs_{front, left, right, rear}: 2d bounding boxes for different agents in the corresponding camera view
- 3d_bbs: 3d bounding boxes for different agents
- affordances: different types of affordances
- measurements: contains ego-agent's position, velocity and other metadata
```
While our work uses only `rgb_front`, `lidar` and `measurements` data, we have provided multi-view camera data with different perception labels and affordances to facilitate development of imitation learning agents.
## Data Generation
The training data is generated using ```leaderboard/team_code/auto_pilot.py``` in 8 CARLA towns and 14 weather conditions. The routes and scenarios files to be used for data generation are provided at ```leaderboard/data```.
In addition to the dataset, we have also provided all the scripts used for generating data and these can be modified as required for different CARLA versions.
