#!/usr/bin/env python3 """ ASLLRP数据集查询工具 用于快速查询和提取特定utterance或sign的信息 """ import csv import os import argparse from collections import defaultdict # 数据路径 BASE_PATH = "/research/cbim/vast/sf895/code/Sign-X/output/huggingface_asllrp_repo" MAPPING_FILE = os.path.join(BASE_PATH, "ASLLRP_utterances_mapping.txt") CSV_FILE = os.path.join(BASE_PATH, "asllrp_sentence_signs_2025_06_28.csv") RESULTS_DIR = os.path.join(BASE_PATH, "ASLLRP_utterances_results") def load_csv_data(): """加载CSV数据""" data = defaultdict(list) with open(CSV_FILE, 'r') as f: reader = csv.DictReader(f) for row in reader: utterance_video = row['Utterance video filename'] data[utterance_video].append(row) return data def load_mapping_data(): """加载mapping数据""" mapping = {} with open(MAPPING_FILE, 'r') as f: for line in f: video_id, glosses = line.strip().split(': ', 1) mapping[video_id] = glosses.split() return mapping def query_utterance(utterance_id): """查询特定utterance的详细信息""" print("="*80) print(f"Utterance ID: {utterance_id}") print("="*80) # 从mapping获取gloss序列 mapping = load_mapping_data() if utterance_id in mapping: glosses = mapping[utterance_id] print(f"\nGloss序列 ({len(glosses)}个):") print(" " + " ".join(glosses)) else: print(f"\n警告: 在mapping.txt中找不到{utterance_id}") # 从CSV获取详细信息 csv_data = load_csv_data() utterance_key = f"{utterance_id}.mp4" if utterance_key in csv_data: signs = csv_data[utterance_key] print(f"\nCSV中的Signs ({len(signs)}个):") # 获取utterance的总帧范围 if signs: utterance_start = int(signs[0]['Start frame of the containing utterance']) utterance_end = int(signs[0]['End frame of the containing utterance']) utterance_duration = utterance_end - utterance_start print(f"\nUtterance帧范围: {utterance_start} - {utterance_end} (总共{utterance_duration}帧)") print(f"\n详细Signs列表:") print(f"{'序号':<4} {'Gloss':<30} {'原始视频帧范围':<20} {'裁剪视频帧范围':<20} {'类型':<20}") print("-"*100) for i, sign in enumerate(signs, 1): gloss = sign['Main entry gloss label'] start = int(sign['Start frame of the sign video']) end = int(sign['End frame of the sign video']) sign_type = sign['Sign type'] # 计算在裁剪视频中的帧号 cropped_start = start - utterance_start cropped_end = end - utterance_start print(f"{i:<4} {gloss:<30} {start}-{end} ({end-start}帧)".ljust(58) + f"{cropped_start}-{cropped_end}".ljust(24) + f"{sign_type}") else: print(f"\n警告: 在CSV文件中找不到{utterance_id}") # 检查results目录 results_path = os.path.join(RESULTS_DIR, utterance_id) if os.path.exists(results_path): print(f"\n处理结果目录: {results_path}") # 检查crop_frame crop_frame_dir = os.path.join(results_path, "crop_frame") if os.path.exists(crop_frame_dir): frames = [f for f in os.listdir(crop_frame_dir) if f.endswith('.jpg')] print(f" - 裁剪帧数: {len(frames)}") # 检查视频 video_path = os.path.join(results_path, "crop_original_video.mp4") if os.path.exists(video_path): size_mb = os.path.getsize(video_path) / (1024 * 1024) print(f" - 裁剪视频大小: {size_mb:.2f} MB") # 检查dwpose dwpose_dir = os.path.join(results_path, "results_dwpose/npz") if os.path.exists(dwpose_dir): npz_files = [f for f in os.listdir(dwpose_dir) if f.endswith('.npz')] print(f" - DWPose文件数: {len(npz_files)}") else: print(f"\n警告: 在results目录中找不到{utterance_id}") def search_gloss(gloss_query): """搜索包含特定gloss的utterances""" print("="*80) print(f"搜索Gloss: {gloss_query}") print("="*80) csv_data = load_csv_data() matches = [] for utterance_video, signs in csv_data.items(): for sign in signs: if gloss_query.upper() in sign['Main entry gloss label'].upper(): utterance_id = utterance_video.replace('.mp4', '') matches.append({ 'utterance_id': utterance_id, 'gloss': sign['Main entry gloss label'], 'start_frame': int(sign['Start frame of the sign video']), 'end_frame': int(sign['End frame of the sign video']), 'sign_type': sign['Sign type'] }) print(f"\n找到 {len(matches)} 个匹配的signs:") print(f"{'Utterance ID':<15} {'Gloss':<30} {'帧范围':<20} {'类型':<20}") print("-"*90) for match in matches[:20]: # 只显示前20个 print(f"{match['utterance_id']:<15} {match['gloss']:<30} " f"{match['start_frame']}-{match['end_frame']}".ljust(24) + f"{match['sign_type']}") if len(matches) > 20: print(f"\n... 还有 {len(matches) - 20} 个结果未显示") def list_all_utterances(): """列出所有utterances的统计信息""" print("="*80) print("所有Utterances统计") print("="*80) mapping = load_mapping_data() csv_data = load_csv_data() print(f"\nMapping.txt中的utterances: {len(mapping)}") print(f"CSV中的utterances: {len(csv_data)}") results_dirs = [d for d in os.listdir(RESULTS_DIR) if os.path.isdir(os.path.join(RESULTS_DIR, d))] print(f"Results目录中的文件夹: {len(results_dirs)}") # 统计gloss数量分布 gloss_counts = [len(glosses) for glosses in mapping.values()] avg_gloss = sum(gloss_counts) / len(gloss_counts) if gloss_counts else 0 min_gloss = min(gloss_counts) if gloss_counts else 0 max_gloss = max(gloss_counts) if gloss_counts else 0 print(f"\nGloss统计:") print(f" 平均每个utterance: {avg_gloss:.1f} 个glosses") print(f" 最少: {min_gloss} 个glosses") print(f" 最多: {max_gloss} 个glosses") # 统计sign类型 sign_types = defaultdict(int) for signs in csv_data.values(): for sign in signs: sign_types[sign['Sign type']] += 1 print(f"\nSign类型分布:") for sign_type, count in sorted(sign_types.items(), key=lambda x: x[1], reverse=True): print(f" {sign_type}: {count}") def extract_sign_info(utterance_id, gloss): """提取特定sign的信息，用于代码中使用""" csv_data = load_csv_data() utterance_key = f"{utterance_id}.mp4" if utterance_key not in csv_data: print(f"错误: 找不到utterance {utterance_id}") return None signs = csv_data[utterance_key] for sign in signs: if gloss.upper() == sign['Main entry gloss label'].upper(): utterance_start = int(sign['Start frame of the containing utterance']) start = int(sign['Start frame of the sign video']) end = int(sign['End frame of the sign video']) info = { 'gloss': sign['Main entry gloss label'], 'start_frame_original': start, 'end_frame_original': end, 'start_frame_cropped': start - utterance_start, 'end_frame_cropped': end - utterance_start, 'duration': end - start, 'sign_type': sign['Sign type'] } print(f"Sign信息:") print(f" Gloss: {info['gloss']}") print(f" 原始视频帧: {info['start_frame_original']} - {info['end_frame_original']}") print(f" 裁剪视频帧: {info['start_frame_cropped']} - {info['end_frame_cropped']}") print(f" 持续时间: {info['duration']} 帧") print(f" 类型: {info['sign_type']}") return info print(f"错误: 在utterance {utterance_id} 中找不到gloss '{gloss}'") return None if __name__ == "__main__": parser = argparse.ArgumentParser(description='ASLLRP数据集查询工具') parser.add_argument('--utterance', '-u', help='查询特定utterance ID') parser.add_argument('--search', '-s', help='搜索包含特定gloss的utterances') parser.add_argument('--list', '-l', action='store_true', help='列出所有utterances的统计') parser.add_argument('--extract', '-e', nargs=2, metavar=('UTTERANCE_ID', 'GLOSS'), help='提取特定sign的信息') args = parser.parse_args() if args.utterance: query_utterance(args.utterance) elif args.search: search_gloss(args.search) elif args.list: list_all_utterances() elif args.extract: extract_sign_info(args.extract[0], args.extract[1]) else: print("使用示例:") print(" 查询utterance: python query_asllrp_data.py --utterance 10006709") print(" 搜索gloss: python query_asllrp_data.py --search THAT") print(" 列出统计: python query_asllrp_data.py --list") print(" 提取sign: python query_asllrp_data.py --extract 10006709 THAT") parser.print_help()