(file_name, voxel_size=0.05, batch_size=1)
| 57 | |
| 58 | |
| 59 | def generate_input_sparse_tensor(file_name, voxel_size=0.05, batch_size=1): |
| 60 | # Create a batch, this process is done in a data loader during training in parallel. |
| 61 | batch = [ |
| 62 | load_file(file_name, voxel_size), |
| 63 | ] * batch_size |
| 64 | coordinates_, featrues_, pcds = list(zip(*batch)) |
| 65 | coordinates, features = ME.utils.sparse_collate(coordinates_, featrues_) |
| 66 | |
| 67 | # Normalize features and create a sparse tensor |
| 68 | return features, coordinates |
| 69 | |
| 70 | |
| 71 | if __name__ == '__main__': |