| """Hugging Face `datasets` loading script for the local ModelNet10 layout (CSV + ModelNet10/*.off).""" |
|
|
| import csv |
| import os |
|
|
| from datasets import ( |
| BuilderConfig, |
| DatasetInfo, |
| Features, |
| GeneratorBasedBuilder, |
| Split, |
| SplitGenerator, |
| Value, |
| Version, |
| ) |
|
|
|
|
| class ModelNet10(GeneratorBasedBuilder): |
| """Build train/test splits from metadata_modelnet10.csv next to the ModelNet10 mesh folder.""" |
|
|
| VERSION = Version("1.0.0") |
| BUILDER_CONFIGS = [BuilderConfig(name="default", version=VERSION)] |
| DEFAULT_CONFIG_NAME = "default" |
|
|
| def _info(self): |
| return DatasetInfo( |
| description=( |
| "ModelNet10: 3D mesh classification subset (10 categories). " |
| "Each row references an OFF file under ModelNet10/ and metadata_modelnet10.csv at the dataset root." |
| ), |
| features=Features( |
| { |
| "object_id": Value("string"), |
| "class": Value("string"), |
| "split": Value("string"), |
| "file_path": Value("string"), |
| } |
| ), |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| if self.config.data_dir is not None: |
| data_dir = os.path.abspath(os.path.expanduser(self.config.data_dir)) |
| if not os.path.isdir(data_dir): |
| raise FileNotFoundError(f"data_dir is not a directory: {data_dir}") |
| elif self.config.data_files is not None: |
| data_dir = dl_manager.download_and_extract(self.config.data_files) |
| else: |
| raise ValueError( |
| "Pass data_dir=... (folder containing metadata_modelnet10.csv and ModelNet10/) " |
| "or data_files=... when calling load_dataset." |
| ) |
|
|
| return [ |
| SplitGenerator( |
| name=Split.TRAIN, |
| gen_kwargs={"split": "train", "data_dir": data_dir}, |
| ), |
| SplitGenerator( |
| name=Split.TEST, |
| gen_kwargs={"split": "test", "data_dir": data_dir}, |
| ), |
| ] |
|
|
| def _generate_examples(self, split, data_dir): |
| csv_path = os.path.join(data_dir, "metadata_modelnet10.csv") |
| if not os.path.isfile(csv_path): |
| raise FileNotFoundError(f"Missing metadata CSV: {csv_path}") |
|
|
| with open(csv_path, newline="", encoding="utf-8") as f: |
| reader = csv.DictReader(f) |
| for row in reader: |
| if row["split"] != split: |
| continue |
| object_id = row["object_id"] |
| yield object_id, { |
| "object_id": object_id, |
| "class": row["class"], |
| "split": row["split"], |
| "file_path": os.path.join(data_dir, "ModelNet10", row["object_path"]), |
| } |
|
|
