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