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https://huggingface.co/datasets/farmaieu/plantorgans/resolve/main/utils/csv_constructor.py
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1.35 kB
| #!/bin/env python3 | |
| import json | |
| import glob | |
| import os | |
| import pandas as pd | |
| import argparse | |
| def main(label_path): | |
| unwanted = [ | |
| 'parent_prediction', 'parent_annotation', | |
| 'last_created_by', 'completed_by', | |
| 'created_username', 'created_ago', | |
| 'project', 'updated_by', | |
| 'file_upload', 'comment_authors', 'meta', | |
| 'unresolved_comment_count', 'last_comment_updated_at', | |
| 'project', 'updated_by', | |
| 'file_upload', 'comment_authors', 'created_at', 'updated_at', 'is_labeled', | |
| 'inner_id', 'total_annotations', 'cancelled_annotations', 'total_predictions', 'comment_count'] | |
| label_files = [p for p in glob.glob(os.path.join(label_path, "*"))] | |
| label_csv = [] | |
| for l in label_files: | |
| with open(l) as label: | |
| label = json.load(label) | |
| for k in unwanted: | |
| label.pop(k, None) | |
| label['task'].pop(k, None) | |
| label_csv.append(label) | |
| label_csv = pd.DataFrame(label_csv) | |
| label_csv = label_csv.drop(columns=['draft_created_at', 'lead_time', 'last_action'], errors='ignore') | |
| label_csv.to_csv('labels.csv') | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser("labelconvertor") | |
| parser.add_argument("label_path", type=str) | |
| arguments = parser.parse_args() | |
| main(arguments.label_path) | |