nightmare-nectarine/segmentation-based-imitation-learning-in-CARLA
Updated
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This dataset consists of 80 episodes of driving data collected using an autopilot agent in CARLA simulator for training imitation learning models for autonomous driving tasks. Each frame is structured as follows:
frame_data = {
'frame': the frame index,
'hlc': an integer representing the high-level command,
'light': an integer representing current traffic light status,
'controls': an array of [throttle, steer, brake],
'measurements': current speed in km/h,
'rgb': rgb camera image,
'segmentation': ground truth segmentation image,
}
This dataset is used in this project and the trained models are available here. Check out the example code for loading the dataset.