142 lines
5.2 KiB
Python
142 lines
5.2 KiB
Python
# -*- coding: utf-8 -*-
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"""
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图片相似度统计脚本
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统计各状态的图片数量和重复率
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"""
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import configparser
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import pymysql
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from datetime import datetime
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def main():
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# 读取配置
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config = configparser.ConfigParser()
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config.read('config.ini', encoding='utf-8')
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# 连接数据库
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db_conn = pymysql.connect(
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host=config.get('database', 'host'),
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port=config.getint('database', 'port'),
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user=config.get('database', 'user'),
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password=config.get('database', 'password'),
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database=config.get('database', 'database'),
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charset=config.get('database', 'charset'),
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cursorclass=pymysql.cursors.DictCursor
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)
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print("=" * 70)
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print(f"图片相似度统计报告 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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print("=" * 70)
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with db_conn.cursor() as cursor:
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# 1. 总体统计
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print("\n【一、总体统计】\n")
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stats = [
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("待处理 (draft/draft)", "status = 'draft' AND similarity = 'draft'"),
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("重复图片 (similarity/yes)", "status = 'similarity' AND similarity = 'yes'"),
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("不重复图片 (tag_extension/calc)", "status = 'tag_extension' AND similarity = 'calc'"),
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("待重算 (draft/recalc)", "status = 'draft' AND similarity = 'recalc'"),
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]
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results = {}
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for name, condition in stats:
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cursor.execute(f"SELECT COUNT(*) as cnt FROM ai_image_tags WHERE {condition}")
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count = cursor.fetchone()['cnt']
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results[name] = count
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print(f" {name:<35} : {count:>10,} 张")
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# 总计
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cursor.execute("SELECT COUNT(*) as cnt FROM ai_image_tags")
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total = cursor.fetchone()['cnt']
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print(f" {'─' * 50}")
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print(f" {'总计':<35} : {total:>10,} 张")
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# 2. 重复率计算
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print("\n【二、重复率分析】\n")
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duplicate_count = results["重复图片 (similarity/yes)"]
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unique_count = results["不重复图片 (tag_extension/calc)"]
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processed = duplicate_count + unique_count
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if processed > 0:
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duplicate_rate = (duplicate_count / processed) * 100
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print(f" 已处理图片数 : {processed:>10,} 张")
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print(f" 重复图片数 : {duplicate_count:>10,} 张")
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print(f" 不重复图片数 : {unique_count:>10,} 张")
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print(f" 重复率 : {duplicate_rate:>10.2f} %")
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else:
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print(" 暂无已处理的图片数据")
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# 3. 处理进度
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print("\n【三、处理进度】\n")
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pending = results["待处理 (draft/draft)"]
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recalc = results["待重算 (draft/recalc)"]
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if total > 0:
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progress = (processed / total) * 100
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print(f" 总进度 : {progress:>10.2f} %")
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print(f" 待处理 : {pending:>10,} 张")
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print(f" 待重算 : {recalc:>10,} 张")
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print(f" 已完成 : {processed:>10,} 张")
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# 4. 相似度分数分布（仅重复图片）
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print("\n【四、相似度分数分布】\n")
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cursor.execute("""
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SELECT
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CASE
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WHEN similarity_score >= 0.99 THEN '0.99-1.00 (几乎相同)'
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WHEN similarity_score >= 0.97 THEN '0.97-0.99 (非常相似)'
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WHEN similarity_score >= 0.95 THEN '0.95-0.97 (高度相似)'
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WHEN similarity_score >= 0.94 THEN '0.94-0.95 (相似)'
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ELSE '< 0.94 (其他)'
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END as score_range,
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COUNT(*) as cnt
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FROM ai_image_tags
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WHERE status = 'similarity' AND similarity = 'yes'
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GROUP BY score_range
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ORDER BY score_range DESC
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""")
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score_stats = cursor.fetchall()
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if score_stats:
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for row in score_stats:
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print(f" {row['score_range']:<25} : {row['cnt']:>10,} 张")
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else:
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print(" 暂无重复图片数据")
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# 5. 最近处理记录
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print("\n【五、最近 10 条重复记录】\n")
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cursor.execute("""
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SELECT id, image_name, similarity_image_tags_id, similarity_score, updated_at
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FROM ai_image_tags
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WHERE status = 'similarity' AND similarity = 'yes'
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ORDER BY updated_at DESC
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LIMIT 10
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""")
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recent = cursor.fetchall()
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if recent:
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print(f" {'ID':<10} {'相似ID':<10} {'分数':<10} {'更新时间':<20}")
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print(f" {'-' * 55}")
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for row in recent:
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score = f"{row['similarity_score']:.4f}" if row['similarity_score'] else "-"
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updated = row['updated_at'].strftime('%Y-%m-%d %H:%M') if row['updated_at'] else "-"
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print(f" {row['id']:<10} {row['similarity_image_tags_id']:<10} {score:<10} {updated:<20}")
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else:
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print(" 暂无重复记录")
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db_conn.close()
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print("\n" + "=" * 70)
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print("统计完成")
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print("=" * 70)
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if __name__ == '__main__':
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main()
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