(self, config, is_train)
| 24 | class PittsburghDataset(TripletDataLoader): |
| 25 | """Dataloader Wrapper for Pittsburgh Dataset""" |
| 26 | def __init__(self, config, is_train): |
| 27 | super().__init__(config, is_train) |
| 28 | self.dataset_dir = os.path.join(config.DATA.BENCHMARK_DIR, str(config.DATA.DATASET_NAME)) |
| 29 | if config.MODEL.TYPE not in ["Lidar", "LiSPH"]: |
| 30 | raise ValueError("Pittsburgh dataset only provides Lidar data!") |
| 31 | if is_train: |
| 32 | self.generate_pickles() |
| 33 | self.queries = self.get_queries_dict(os.path.join(self.dataset_dir, config.DATA.TRAIN_PICKLE)) |
| 34 | log_print("Number of training tuples: %d" % len(self.queries), "y") |
| 35 | else: |
| 36 | self.queries = self.get_queries_dict(os.path.join(self.dataset_dir, config.DATA.VAL_PICKLE)) |
| 37 | log_print("Number of val tuples: %d" % len(self.queries), "y") |
| 38 | self.file_idxs = np.arange(0, len(self.queries.keys())) |
| 39 | |
| 40 | def load_file_func(self, filename): |
| 41 | if self.config.MODEL.TYPE == "Lidar" or self.branch == "Lidar": |
nothing calls this directly
no test coverage detected