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import os |
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import pyarrow.parquet as pq |
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import datasets |
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_CITATION = "" |
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_DESCRIPTION = "Wyvern dataset with encoded image arrays and masks per 2400m tile." |
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_HOMEPAGE = "" |
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_LICENSE = "cc-by-4.0" |
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class NestEOPrototype(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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citation=_CITATION, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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features=datasets.Features({ |
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"tile_id": datasets.Value("string"), |
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"scene_id": datasets.Value("string"), |
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"start_datetime": datasets.Value("timestamp[us]"), |
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"end_datetime": datasets.Value("timestamp[us]"), |
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"image": datasets.Value("binary"), |
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"data_mask": datasets.Value("binary"), |
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"pixel_quality_mask": datasets.Value("binary"), |
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"shape": [datasets.Value("int32")], |
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}), |
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) |
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def _split_generators(self, dl_manager): |
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wyvern_path = os.path.join(dl_manager.manual_dir, "datasets_EO/Wyvern/grid_2400m") |
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return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"folder_path": wyvern_path})] |
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def _generate_examples(self, folder_path): |
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idx = 0 |
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for fname in sorted(os.listdir(folder_path)): |
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if fname.endswith(".parquet"): |
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table = pq.read_table(os.path.join(folder_path, fname)) |
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df = table.to_pandas() |
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for _, row in df.iterrows(): |
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yield idx, { |
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"tile_id": row["tile_id"], |
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"scene_id": row["scene_id"], |
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"start_datetime": row["start_datetime"], |
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"end_datetime": row["end_datetime"], |
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"image": row["image"], |
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"data_mask": row["data_mask"], |
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"pixel_quality_mask": row["pixel_quality_mask"], |
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"shape": row["shape"], |
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} |
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idx += 1 |
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