#!/usr/bin/env python3 import os import glob def check_processing_progress(): """Check the progress of FT_work dataset processing""" # Paths data_path = "/apdcephfs_gy4/share_303628665/joywu/dataset/FT_work/videos/train" save_path = "/apdcephfs_gy5/share_303628665/joyewu/research/AVH-Align/ft_work_preprocessed/train" print("=== FT_Work 数据集处理进度检查 ===") print(f"数据路径: {data_path}") print(f"输出路径: {save_path}") print() # Find all MP4 files in the dataset print("扫描数据集中的MP4文件...") mp4_files = [] for mp4_path in glob.glob(os.path.join(data_path, "**", "*.mp4"), recursive=True): rel_path = os.path.relpath(mp4_path, data_path) mp4_files.append(rel_path) total_files = len(mp4_files) print(f"总MP4文件数: {total_files}") print() # Check processing status processed_files = [] unprocessed_files = [] failed_files = [] for mp4_file in mp4_files: video_dir = os.path.dirname(mp4_file) video_basename = os.path.basename(mp4_file) output_dir = os.path.join(save_path, video_dir) roi_path = os.path.join(output_dir, video_basename[:-4] + '_roi.mp4') wav_path = os.path.join(output_dir, video_basename[:-4] + '.wav') if os.path.exists(roi_path) and os.path.exists(wav_path): processed_files.append(mp4_file) else: unprocessed_files.append(mp4_file) # Check if it's a known problematic file if "Real_CelebV-HQ" in mp4_file or "Real_HDTF" in mp4_file: failed_files.append(mp4_file) # Display results processed_count = len(processed_files) unprocessed_count = len(unprocessed_files) failed_count = len(failed_files) print("=== 处理状态汇总 ===") print(f"✅ 已处理完成: {processed_count} 个文件 ({processed_count/total_files*100:.1f}%)") print(f"⏳ 待处理: {unprocessed_count} 个文件 ({unprocessed_count/total_files*100:.1f}%)") print(f"❌ 已知问题文件: {failed_count} 个文件") print() if processed_files: print("✅ 已处理的文件示例:") for i, file in enumerate(processed_files[:5]): print(f" {i+1}. {file}") if len(processed_files) > 5: print(f" ... 还有 {len(processed_files) - 5} 个文件") print() if unprocessed_files: print("⏳ 待处理的文件示例:") for i, file in enumerate(unprocessed_files[:10]): print(f" {i+1}. {file}") if len(unprocessed_files) > 10: print(f" ... 还有 {len(unprocessed_files) - 10} 个文件") print() if failed_files: print("❌ 已知问题文件 (可能需要特殊处理):") for i, file in enumerate(failed_files[:10]): print(f" {i+1}. {file}") if len(failed_files) > 10: print(f" ... 还有 {len(failed_files) - 10} 个文件") print() # Recommendations print("=== 建议 ===") if unprocessed_count > 0: print("1. 可以继续运行预处理命令,程序会自动跳过已处理的文件") print("2. 建议使用较少的worker数量进行测试:") print(" python deepfake_preprocess.py --dataset FT_work --split train --data_path /apdcephfs_gy4/share_303628665/joywu/dataset/FT_work/videos --save_path /apdcephfs_gy5/share_303628665/joyewu/research/AVH-Align/ft_work_preprocessed --max_workers 8") if failed_count > 0: print("3. 对于Real_CelebV-HQ和Real_HDTF文件,可能需要检查视频格式或质量") print() print("=== 重新运行命令 ===") print("python deepfake_preprocess.py \\") print(" --dataset FT_work \\") print(" --split train \\") print(" --data_path /apdcephfs_gy4/share_303628665/joywu/dataset/FT_work/videos \\") print(" --save_path /apdcephfs_gy5/share_303628665/joyewu/research/AVH-Align/ft_work_preprocessed") if __name__ == "__main__": check_processing_progress()