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This repository only contains our model architecture in PyTorch. We don't provide any code for the dataset, training, or evaluation, but you should be able to use this model architecture with your own data and training code for solving multi-modal object-detection tasks as the model is derived from Faster R-CNN.
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We used the radiate sdk function get_from_timestamp to get the sensor data for each input modality and corresponding annotations.
https://github.com/marcelsheeny/radiate_sdk/blob/master/radiate.py#L187
We used annotations['radar_cartesian'] as the radar_y and annotations['camera_right_rect'] as cam_y. However, since Faster R-CNN is a 2D bounding box predictor, we flatten the pseudo-3D camera annotations for cam_y into 2D boxes.
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