scripts/filter.py

import json
import os
from pathlib import Path
from tqdm import tqdm

def check_json_data(json_file_path, images_root_dir):
    """检查JSON数据的完整性 - 只过滤有image字段但图像不存在的数据"""
    
    # 加载JSON文件
    try:
        with open(json_file_path, 'r', encoding='utf-8') as f:
            data = json.load(f)
    except Exception as e:
        print(f"加载JSON文件失败: {e}")
        return []
    
    anomalous_data = []
    total_entries = len(data)
    
    print(f"开始检查 {total_entries} 条数据...")
    
    for i, entry in enumerate(tqdm(data, desc="检查图像文件", unit="条")):
        issues = []
        
        # 只检查image字段相关的问题
        if 'image' in entry:
            image_path = entry['image']
            # if not image_path or image_path.strip() == '':
            #     issues.append("图像路径为空")
            # else:
            #     # 检查图像文件是否存在
            #     if images_root_dir:
            #        # 构建完整的图像文件路径
            #        full_image_path = Path(images_root_dir) / image_path
            #     else:
            #         full_image_path = Path(json_file_path).parent / image_path
            #     if not full_image_path.exists():
            #         issues.append(f"图像文件不存在: {image_path}")

            if len(image_path) == 0:
                issues.append("图像路径为空")
            else:
                for img in image_path:
                   if not Path(img).exists():
                       issues.append(f"图像文件不存在: {img}")
        
        # 如果有问题，记录异常数据
        if issues:
            anomalous_entry = {
                'index': i,
                'id': entry.get('id', 'Unknown'),
                'image': entry.get('image', 'N/A'),
                'entry': entry,
                'issues': issues
            }
            anomalous_data.append(anomalous_entry)
    
    return anomalous_data

def save_valid_data(json_file_path, anomalous_data, output_file='filtered_data.json'):
    """保存过滤后的有效数据"""
    # 加载原始数据
    with open(json_file_path, 'r', encoding='utf-8') as f:
        original_data = json.load(f)
    
    # 获取异常数据的索引
    anomalous_indices = {anomaly['index'] for anomaly in anomalous_data}
    
    # 过滤出有效数据
    valid_data = [entry for i, entry in enumerate(original_data) if i not in anomalous_indices]
    
    # 保存有效数据
    with open(output_file, 'w', encoding='utf-8') as f:
        json.dump(valid_data, f, indent=2, ensure_ascii=False)
    
    print(f"过滤后的有效数据已保存到: {output_file}")
    print(f"原始数据: {len(original_data)} 条")
    print(f"有效数据: {len(valid_data)} 条")
    print(f"过滤掉: {len(anomalous_data)} 条")

def save_anomalous_data(anomalous_data, output_file='anomalous_data.json'):
    """保存异常数据到文件"""
    if anomalous_data:
        with open(output_file, 'w', encoding='utf-8') as f:
            json.dump(anomalous_data, f, indent=2, ensure_ascii=False)
        print(f"异常数据已保存到: {output_file}")
    else:
        print("没有异常数据需要保存")

def print_statistics(json_file_path, anomalous_data):
    """打印统计信息"""
    with open(json_file_path, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    total_entries = len(data)
    anomalous_count = len(anomalous_data)
    
    print(f"\n=== 数据统计 ===")
    print(f"总条目数: {total_entries}")
    print(f"图像异常条目数: {anomalous_count}")
    print(f"有效条目数: {total_entries - anomalous_count}")
    print(f"数据有效率: {((total_entries - anomalous_count) / total_entries * 100):.2f}%")
    
    # 字段存在统计
    fields_stats = {
        'id': sum(1 for entry in data if 'id' in entry),
        'image': sum(1 for entry in data if 'image' in entry),
        'conversations': sum(1 for entry in data if 'conversations' in entry)
    }
    
    print(f"\n=== 字段存在统计 ===")
    for field, count in fields_stats.items():
        print(f"包含'{field}'字段的条目: {count}/{total_entries} ({count/total_entries*100:.1f}%)")

# 主执行函数
def main():
    json_file = 'train_data_processed.json'
    images_root_dir = 'images'
    
    # 检查文件是否存在
    if not os.path.exists(json_file):
        print(f"文件不存在: {json_file}")
        return
    
    # 检查数据
    anomalous_data = check_json_data(json_file, images_root_dir)
    
    # 输出结果
    if anomalous_data:
        print(f"\n发现 {len(anomalous_data)} 条图像异常数据:")
        print("=" * 50)
        
        # 只显示前10条异常数据，避免输出过多
        for anomaly in anomalous_data[:10]:
            print(f"索引: {anomaly['index']}")
            print(f"ID: {anomaly['id']}")
            print(f"图像: {anomaly['image']}")
            print(f"问题: {', '.join(anomaly['issues'])}")
            print("-" * 30)
        
        if len(anomalous_data) > 10:
            print(f"... 还有 {len(anomalous_data) - 10} 条异常数据")
        
        # 保存异常数据
        # save_anomalous_data(anomalous_data)
        
        # 保存过滤后的有效数据
        # save_valid_data(json_file, anomalous_data)
        
        # 按问题类型统计
        issue_counts = {}
        for anomaly in anomalous_data:
            for issue in anomaly['issues']:
                issue_type = issue.split(':')[0] if ':' in issue else issue
                issue_counts[issue_type] = issue_counts.get(issue_type, 0) + 1
        
        print(f"\n=== 问题类型统计 ===")
        for issue_type, count in sorted(issue_counts.items()):
            print(f"{issue_type}: {count}次")
    
    else:
        print("✅ 所有数据的图像文件都正常！")
        # 即使没有异常数据，也保存一份完整的数据
        # save_valid_data(json_file, anomalous_data, 'filtered_filtered_data.json')
    
    # 打印统计信息
    print_statistics(json_file, anomalous_data)

if __name__ == "__main__":
    main()