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import os
import json
import datasets
_DESCRIPTION = """
TableSense Dataset - Spreadsheet Table Detection task from the VEnron2, VEUSES, and VFUSE datasets.
"""
VERSION = datasets.Version("1.0.0")
def parse_range(range_str):
start, end = range_str.split(':')
start_col = ''.join(c for c in start if c.isalpha())
start_row = int(''.join(c for c in start if c.isdigit()))
end_col = ''.join(c for c in end if c.isalpha())
end_row = int(''.join(c for c in end if c.isdigit()))
return {"start_col": start_col, "start_row": start_row, "end_col": end_col, "end_row": end_row}
class Tablesense(datasets.GeneratorBasedBuilder):
"""Dataset for loading arbitrary .xlsx files with a .jsonl metadata file."""
def _info(self):
features = {
"filepath": datasets.Value("string"),
'sheet_name': datasets.Value("string"),
'split': datasets.Value("string"),
'table_regions':[
{
"start_col": datasets.Value("string"),
"start_row": datasets.Value("int32"),
"end_col": datasets.Value("string"),
"end_row": datasets.Value("int32")
}
]
}
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(features)
)
def _split_generators(self, dl_manager):
"""Define splits."""
# Load your dataset folder
data_path = "data.tar.gz"
xlsx_dir = os.path.join(dl_manager.download_and_extract(data_path), "data")
metadata_file = "annotations.jsonl"
return [
datasets.SplitGenerator(
name="train",
gen_kwargs={
"files_dir": xlsx_dir,
"metadata_file": metadata_file,
},
)
]
def _generate_examples(self, files_dir, metadata_file):
"""Yields examples."""
# Load metadata from the .jsonl file
with open(metadata_file, "r") as f:
metadata = [json.loads(line.strip()) for line in f]
for i, meta in enumerate(metadata):
file_name = meta.get("clean_file")
# Load corresponding .xlsx file
xlsx_path = os.path.join(files_dir, file_name)
if not os.path.exists(xlsx_path):
continue
yield i, {
"filepath": xlsx_path,
"sheet_name": meta.get("sheet_name"),
"split": meta.get("split"),
"table_regions": [parse_range(rg) for rg in meta.get("table_regions")]
} |