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import pandas as pd
import jsonlines
import re
import random
def convert_excel_to_json(excel_file, json_file):
df = pd.read_excel(excel_file)
df = df.where(pd.notnull(df), None)
df.to_json(json_file, orient='records', lines=True, default_handler=str)
def count_bbox(answer: str):
PATTERN = re.compile(r'\((.*?)\),\((.*?)\)')
bbox_num = len(re.findall(PATTERN, answer))
return bbox_num
xlsx_input = 'public_eval/bbox_step_300/MathVerse_MINI/20250418/bbox_step_300/bbox_step_300_MathVerse_MINI.xlsx'
json_output = xlsx_input.replace('.xlsx', '.jsonl')
convert_excel_to_json(xlsx_input, json_output)
box_output = []
with jsonlines.open(json_output, 'r') as reader:
for obj in reader:
total_num = 0
total_bbox_num = 0
bbox_sample_num = 0
for obj in reader:
total_num += 1
answer = obj["full_prediction"]
bbox_num = count_bbox(answer)
total_bbox_num += bbox_num
if bbox_num > 0:
bbox_sample_num += 1
box_output.append(obj)
random.shuffle(box_output)
with jsonlines.open(json_output.replace('.jsonl', '_bbox.jsonl'), 'w') as writer:
for obj in box_output:
writer.write(obj)
print(f"total_num: {total_num}, total_bbox_num: {total_bbox_num}, bbox_sample_num: {bbox_sample_num}")
print(f"average box num: {total_bbox_num / bbox_sample_num}, bbox num ratio: {bbox_sample_num / total_num}")
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