Datasets:
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import click
import json
from copy import deepcopy
from pathlib import Path
@click.group(invoke_without_command=True)
@click.pass_context
def cli(ctx):
if ctx.invoked_subcommand is None:
click.echo("CLI invoked without subcommand")
else:
click.echo("Launching of command: %s" % ctx.invoked_subcommand)
@cli.command()
@click.option("--json_name", default="labels.json", help="Name of the json label file")
@click.option("--keep_col_sep", is_flag=True, help="Whether to keep column separator character")
@click.option("--rm_ool_chars", is_flag=True, help="Whether to remove out of line chars")
def formatdataset(json_name: str, keep_col_sep=True, rm_ool_chars=False):
"""
Prepare labels for training by removing column separators or out-of-line characters
"""
with open(json_name, "r") as f:
info = json.load(f)
charset = set()
new_dict = deepcopy(info)
for split_name, split_dict in info["ground_truth"].items():
for key in split_dict:
#remove annotation of out-of-line words:
if rm_ool_chars:
for char in ["!", "?"]:
if char in split_dict[key]["text"]:
cell_labels = split_dict[key]["text"].split("/")
for i, cell_label in enumerate(cell_labels):
if char in cell_label:# and cell_label != "?":
cell_labels[i] = cell_label[: cell_label.find(char)]
split_dict[key]["text"] = "/".join(cell_labels)
if not keep_col_sep:
# remove column separator characters
split_dict[key]["text"] = split_dict[key]["text"].replace("/", " ").replace("¤", "")
# update the charset:
line_charset = set([character for character in split_dict[key]["text"]])
charset = charset.union(line_charset)
new_dict['ground_truth'][split_name]=split_dict
# we replace the old charset with the new one deduced from the new labels:
new_dict["charset"] = sorted(list(charset))
output_name = Path(json_name).parent.joinpath("formatted_" + Path(json_name).name)
with open(output_name, "w") as f:
json.dump(new_dict, f)
if __name__ == "__main__":
cli() |