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"""
Custom HuggingFace dataset loading script for GeoParquet files.
References:
- https://huggingface.co/docs/datasets/v2.15.0/en/dataset_script
- https://github.com/huggingface/datasets/blob/2.15.0/templates/new_dataset_script.py
- https://huggingface.co/docs/datasets/v2.15.0/en/package_reference/builder_classes
- https://huggingface.co/docs/datasets/v2.15.0/en/about_dataset_load
- https://discuss.huggingface.co/t/how-to-tweak-a-dataset-without-a-loading-script/43533/5
"""
import datasets
import pyarrow as pa
import pyarrow.parquet as pq
_URLS = {"32VLM": " 32VLM_v01.gpq"}
_MGRS_TILES = ["32VLM"]
class ClayVectorEmbeddings(datasets.ArrowBasedBuilder):
"""Clay Vector Embeddings in GeoParquet format."""
# You will be able to load one or the other configurations in the following list with
# data = datasets.load_dataset('my_dataset', 'MGRS_TILE')
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name=name,
version=datasets.Version(version="0.0.1"),
description=f"Clay vector embeddings for MGRS tile {name}",
)
for name in _MGRS_TILES
]
# DEFAULT_CONFIG_NAME = "32VLM"
def _info(self):
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description="Clay Vector Embeddings in GeoParquet format.",
# This defines the different columns of the dataset and their types
features=datasets.Features(
{
"source_url": datasets.Value(dtype="string"),
"date": datasets.Value(dtype="date32"),
"embeddings": datasets.Value("string"),
"geometry": datasets.Value("binary"),
# These are the features of your dataset like images, labels ...
}
),
)
def _split_generators(self, dl_manager: datasets.download.DownloadManager):
files = _URLS[self.config.name]
downloaded_files = dl_manager.download(files)
return [
datasets.SplitGenerator(
name=datasets.Split.ALL,
# These kwargs will be passed to _generate_tables
gen_kwargs={"filepaths": downloaded_files},
)
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_tables(self, filepaths: list[str] = ["32VLM_v01.gpq"]):
for file_idx, filepath in enumerate(filepaths):
with open(filepath, mode="rb") as f:
parquet_file = pq.ParquetFile(source=filepath)
for batch_idx, record_batch in enumerate(parquet_file.iter_batches()):
pa_table = pa.Table.from_batches([record_batch])
yield f"{file_idx_batch_idx}", pa_table
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