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import os
import argparse
import pandas as pd
from tqdm import tqdm
from concurrent.futures import ThreadPoolExecutor, as_completed
import threading
# 添加线程锁保护共享资源
video_data_lock = threading.Lock()
matched_count_lock = threading.Lock()
def process_video_file(video_file, args, csv_video_mapping):
"""处理单个视频文件的函数"""
video_path = os.path.join(args.input_video_root, video_file)
video_filename = os.path.splitext(video_file)[0]
matched_row = None
for csv_prefix, row in csv_video_mapping.items():
if video_filename.startswith(csv_prefix):
matched_row = row
break
result = None
if matched_row is not None:
final_csv_path = os.path.join(args.output_csv_path, (video_filename + ".csv"))
if os.path.exists(final_csv_path):
# 检查CSV文件是否损坏
try:
import pandas as pd
# 尝试读取CSV文件来验证其完整性
pd.read_csv(final_csv_path)
return None # 文件存在且有效，不需要重新处理
except (pd.errors.EmptyDataError, pd.errors.ParserError, UnicodeDecodeError, FileNotFoundError) as e:
# CSV文件损坏，删除它
print(f"Warning: CSV file {final_csv_path} is corrupted ({e}). Deleting and will recreate.")
os.remove(final_csv_path)
result = {
'videoFile': video_filename + ".mp4",
'cameraFile': matched_row['cameraFile'],
'location': matched_row['location'],
'scene': matched_row['scene'],
'crowdDensity': matched_row['crowdDensity'],
'weather': matched_row['weather'],
'timeOfDay': matched_row['timeOfDay'],
}
else:
print(f"Warning: No CSV record found for video file: {video_file}")
return result
# 多线程处理主代码
def process_videos_multithreaded(video_files, args, csv_video_mapping, max_workers=4):
video_data = []
matched_count = 0
with ThreadPoolExecutor(max_workers=max_workers) as executor:
# 提交所有任务
future_to_video = {
executor.submit(process_video_file, video_file, args, csv_video_mapping): video_file
for video_file in video_files
}
# 处理完成的任务
for future in tqdm(as_completed(future_to_video), total=len(video_files), desc="Processing videos"):
video_file = future_to_video[future]
try:
result = future.result()
if result is not None:
with video_data_lock:
video_data.append(result)
with matched_count_lock:
matched_count += 1
except Exception as exc:
print(f'Video {video_file} generated an exception: {exc}')
return video_data, matched_count
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--input_csv",
type=str,
default="/mnt/bn/yufan-dev-my/ysh/Ckpts/Lixsp11/0_final_sekai_dataset/yamls/sekai-game-walking_updated.csv",
)
parser.add_argument(
"--input_video_root", type=str, default="/mnt/bn/yufan-dev-my/ysh/Ckpts/Lixsp11/0_final_sekai_dataset/sekai-game-walking-386"
)
parser.add_argument(
"--output_csv_path",
type=str,
default="/mnt/bn/yufan-dev-my/ysh/Ckpts/Lixsp11/0_final_sekai_dataset/yamls/sekai-game-walking-386",
)
parser.add_argument(
"--output_csv_file",
type=str,
default="/mnt/bn/yufan-dev-my/ysh/Ckpts/Lixsp11/0_final_sekai_dataset/yamls/temp_input_csv/sekai-game-walking-386.csv",
)
parser.add_argument("--num_workers", type=int, default=16)
args = parser.parse_args()
return args
if __name__ == "__main__":
args = parse_args()
# 读取CSV文件
df = pd.read_csv(args.input_csv)
# 保留需要的字段，过滤掉不需要的字段
keep_columns = ['videoFile', 'cameraFile', 'caption', 'location', 'scene', 'crowdDensity', 'weather', 'timeOfDay']
df = df[keep_columns].copy()
# 创建CSV中视频文件名前缀到记录的映射
csv_video_mapping = {}
for idx, row in df.iterrows():
video_prefix = os.path.splitext(os.path.basename(row['videoFile']))[0]
csv_video_mapping[video_prefix] = row
# 获取视频文件夹中的所有视频文件
video_files = []
for file in os.listdir(args.input_video_root):
if file.lower().endswith(('.mp4', '.avi', '.mov', '.mkv', '.wmv', '.flv')): # 添加更多视频格式
video_files.append(file)
# # 准备视频数据
# video_data = []
# matched_count = 0
# for video_file in tqdm(video_files):
# video_path = os.path.join(args.input_video_root, video_file)
# video_filename = os.path.splitext(video_file)[0]
# matched_row = None
# for csv_prefix, row in csv_video_mapping.items():
# if video_filename.startswith(csv_prefix):
# matched_row = row
# break
# if matched_row is not None:
# final_csv_path = os.path.join(args.output_csv_path, (video_filename + ".csv"))
# if not os.path.exists(final_csv_path):
# video_data.append({
# "video_key": video_filename,
# 'videoFile': video_filename + ".mp4",
# 'cameraFile': matched_row['cameraFile'],
# 'location': matched_row['location'],
# 'scene': matched_row['scene'],
# 'crowdDensity': matched_row['crowdDensity'],
# 'weather': matched_row['weather'],
# 'timeOfDay': matched_row['timeOfDay'],
# })
# matched_count += 1
# else:
# print(f"Warning: No CSV record found for video file: {video_file}")
video_data, matched_count = process_videos_multithreaded(video_files, args, csv_video_mapping, max_workers=args.num_workers)
print(f"Successfully matched {matched_count} videos with CSV records")
print(f"Total video data to process: {len(video_data)}")
if video_data:
output_df = pd.DataFrame(video_data)
output_csv_file = args.output_csv_file
output_df.to_csv(output_csv_file, index=False)
print(f"Video data saved to: {output_csv_file}")
print(f"Saved {len(video_data)} video records")
else:
output_df = pd.DataFrame()
output_csv_file = args.output_csv_file
output_df.to_csv(output_csv_file, index=False)
print(f"Empty video data saved to: {output_csv_file}")
print("No video data to save - created empty CSV file") |