| |
|
|
| 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) |
|
|