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import json | |
import argparse | |
def verify_layout(data): | |
scores = data["metrics"] | |
for layout_type, metrics in scores.items(): | |
if metrics["precision"] <= 0.6 or metrics["recall"] <= 0.6: | |
raise ValueError("Scores do not meet the required threshold") | |
def verify_det(data): | |
scores = data["metrics"]["surya"] | |
if scores["precision"] <= 0.9 or scores["recall"] <= 0.9: | |
raise ValueError("Scores do not meet the required threshold") | |
def verify_rec(data): | |
scores = data["surya"] | |
if scores["avg_score"] <= 0.9: | |
raise ValueError("Scores do not meet the required threshold") | |
def verify_order(data): | |
score = data["mean_accuracy"] | |
if score < 0.75: | |
raise ValueError("Scores do not meet the required threshold") | |
def verify_table_rec(data): | |
row_score = data["surya"]["mean_row_iou"] | |
col_score = data["surya"]["mean_col_iou"] | |
if row_score < 0.75 or col_score < 0.75: | |
raise ValueError("Scores do not meet the required threshold") | |
def verify_scores(file_path, bench_type): | |
with open(file_path, 'r') as file: | |
data = json.load(file) | |
if bench_type == "detection": | |
verify_det(data) | |
elif bench_type == "recognition": | |
verify_rec(data) | |
elif bench_type == "layout": | |
verify_layout(data) | |
elif bench_type == "ordering": | |
verify_order(data) | |
elif bench_type == "table_recognition": | |
verify_table_rec(data) | |
else: | |
raise ValueError("Invalid benchmark type") | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser(description="Verify benchmark scores") | |
parser.add_argument("file_path", type=str, help="Path to the json file") | |
parser.add_argument("--bench_type", type=str, help="Type of benchmark to verify", default="detection") | |
args = parser.parse_args() | |
verify_scores(args.file_path, args.bench_type) | |