Comments (2)
Hello @RnRi, I think the key to support other datasets is to write a dataset class to return the necessary information (point cloud, bboxes, classes, etc.), such as the following dictionary in kitti.py
.
data_dict = {
'pts': pts,
'gt_bboxes_3d': gt_bboxes_3d,
'gt_labels': np.array(gt_labels),
'gt_names': annos_name,
'difficulty': annos_info['difficulty'],
'image_info': image_info,
'calib_info': calib_info
}
Best.
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@RnRi Did you end up using NuScenes and did you train successfully? I have the data loading part working (and have verified it by visualising loaded frames), but I seem to not be able to overfit on a single training example, which must be due to ill define parameters.
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Related Issues (20)
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