(file_name, voxel_size=0.05, batch_size=1)
| 72 | |
| 73 | |
| 74 | def generate_input_sparse_tensor(file_name, voxel_size=0.05, batch_size=1): |
| 75 | # Create a batch, this process is done in a data loader during training in parallel. |
| 76 | batch = [load_file(file_name, voxel_size),] * batch_size |
| 77 | coordinates_, featrues_, pcds = list(zip(*batch)) |
| 78 | coordinates, features = ME.utils.sparse_collate(coordinates_, featrues_) |
| 79 | |
| 80 | # Normalize features and create a sparse tensor |
| 81 | return features, coordinates |
| 82 | |
| 83 | |
| 84 | if __name__ == "__main__": |
no test coverage detected