AV-Dense-60k / metadata /align_csv.py
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import pandas as pd
import os
import sys
def align_csv_structure(csv1_path, csv2_path):
"""
Reads csv1 and csv2, reformats csv1 to match csv2's columns,
and overwrites csv1.
"""
# 1. 读取 CSV 文件
try:
df1 = pd.read_csv(csv1_path)
df2 = pd.read_csv(csv2_path)
except FileNotFoundError as e:
print(f"Error: {e}")
return
# 获取目标列结构 (来自 csv2)
target_columns = df2.columns.tolist()
# 2. 遍历目标列,处理 csv1 中缺失的列
for col in target_columns:
if col in df1.columns:
# 如果 csv1 已经有这个列,跳过(保留原数据)
continue
# 如果 csv1 缺少这个列,根据 pattern 进行生成或填充默认值
if col == 'id':
# Pattern: 从 path 中提取文件名(不带扩展名)
df1['id'] = df1['path'].apply(lambda x: os.path.splitext(os.path.basename(x))[0] if pd.notnull(x) else '')
elif col == 'relpath':
# Pattern: 从 path 中提取完整文件名
df1['relpath'] = df1['path'].apply(lambda x: os.path.basename(x) if pd.notnull(x) else '')
elif col == 'audio_id':
# Pattern: 从 audio_path 中提取文件名(不带扩展名)
if 'audio_path' in df1.columns:
df1['audio_id'] = df1['audio_path'].apply(lambda x: os.path.splitext(os.path.basename(x))[0] if pd.notnull(x) else '')
else:
df1['audio_id'] = ''
elif col == 'audio_fps':
# 默认填充 16000 (参考 csv2 的常见值,或者是 NaN)
df1['audio_fps'] = 16000
# 处理 Category Title 列 (例如 cat0_title)
elif 'title' in col and col.startswith('cat'):
# 由于没有 ID 到 Title 的映射表,这里留空
df1[col] = ''
# 其他技术参数 (num_frames, height, width, fps, aes, flow, ocr 等)
else:
# 填充为空值 (NaN),表示数据缺失
df1[col] = pd.NA
# 3. 重新排序并筛选列,确保与 csv2 完全一致
# reindex 会自动丢弃 csv1 中多余的列(如果 csv2 没有的话),并对齐顺序
df1_final = df1.reindex(columns=target_columns)
# 4. 覆盖保存 csv1
df1_final.to_csv(csv1_path, index=False)
print(f"Successfully processed and overwritten: {csv1_path}")
print(f"Columns aligned: {len(target_columns)}")
if __name__ == "__main__":
if len(sys.argv) != 3:
print("Usage: python align_csv.py <csv-to-align> <reference-schema-csv>", file=sys.stderr)
raise SystemExit(2)
align_csv_structure(sys.argv[1], sys.argv[2])