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")