#!/usr/bin/env python3
"""
人臉統計報告生成
"""

import psycopg2
from datetime import datetime
import sys


def get_face_statistics():
    """獲取人臉統計數據"""
    conn = psycopg2.connect(
        host="localhost",
        port=5432,
        database="momentry",
        user="accusys",
        password="accusys",
    )

    cursor = conn.cursor()

    # 1. 總體統計
    cursor.execute("""
        SELECT 
          COUNT(*) as total_faces,
          SUM(CASE WHEN attributes->>'gender' = 'male' THEN 1 ELSE 0 END) as male_count,
          SUM(CASE WHEN attributes->>'gender' = 'female' THEN 1 ELSE 0 END) as female_count,
          ROUND(AVG(CASE WHEN attributes->>'age' ~ '^[0-9]+$' THEN (attributes->>'age')::numeric ELSE NULL END)::numeric, 1) as avg_age,
          MIN(CASE WHEN attributes->>'age' ~ '^[0-9]+$' THEN (attributes->>'age')::numeric ELSE NULL END) as min_age,
          MAX(CASE WHEN attributes->>'age' ~ '^[0-9]+$' THEN (attributes->>'age')::numeric ELSE NULL END) as max_age
        FROM face_detections
    """)

    total_stats = cursor.fetchone()

    # 2. 按視頻統計
    cursor.execute("""
        SELECT 
          video_uuid,
          COUNT(*) as total_faces,
          SUM(CASE WHEN attributes->>'gender' = 'male' THEN 1 ELSE 0 END) as male_count,
          SUM(CASE WHEN attributes->>'gender' = 'female' THEN 1 ELSE 0 END) as female_count,
          ROUND(AVG(CASE WHEN attributes->>'age' ~ '^[0-9]+$' THEN (attributes->>'age')::numeric ELSE NULL END)::numeric, 1) as avg_age
        FROM face_detections 
        GROUP BY video_uuid 
        ORDER BY total_faces DESC
    """)

    video_stats = cursor.fetchall()

    # 3. 年齡性別分布
    cursor.execute("""
        WITH age_groups AS (
          SELECT 
            CASE 
              WHEN (attributes->>'age')::numeric < 20 THEN '10-19'
              WHEN (attributes->>'age')::numeric < 30 THEN '20-29'
              WHEN (attributes->>'age')::numeric < 40 THEN '30-39'
              WHEN (attributes->>'age')::numeric < 50 THEN '40-49'
              WHEN (attributes->>'age')::numeric < 60 THEN '50-59'
              ELSE '60+'
            END as age_group,
            attributes->>'gender' as gender
          FROM face_detections 
          WHERE attributes->>'gender' IN ('male', 'female')
            AND attributes->>'age' ~ '^[0-9]+$'
        )
        SELECT 
          age_group,
          gender,
          COUNT(*) as count
        FROM age_groups
        GROUP BY age_group, gender
        ORDER BY 
          CASE age_group
            WHEN '10-19' THEN 1
            WHEN '20-29' THEN 2
            WHEN '30-39' THEN 3
            WHEN '40-49' THEN 4
            WHEN '50-59' THEN 5
            ELSE 6
          END,
          gender DESC
    """)

    age_gender_dist = cursor.fetchall()

    # 4. 置信度統計
    cursor.execute("""
        SELECT 
          ROUND(AVG(confidence)::numeric, 3) as avg_confidence,
          MIN(confidence) as min_confidence,
          MAX(confidence) as max_confidence,
          COUNT(CASE WHEN confidence >= 0.8 THEN 1 END) as high_confidence,
          COUNT(CASE WHEN confidence >= 0.6 AND confidence < 0.8 THEN 1 END) as medium_confidence,
          COUNT(CASE WHEN confidence < 0.6 THEN 1 END) as low_confidence
        FROM face_detections
    """)

    confidence_stats = cursor.fetchone()

    # 5. 時間分布
    cursor.execute("""
        SELECT 
          FLOOR(timestamp_secs / 60) * 60 as minute_mark,
          COUNT(*) as faces_in_minute,
          SUM(CASE WHEN attributes->>'gender' = 'male' THEN 1 ELSE 0 END) as males_in_minute,
          SUM(CASE WHEN attributes->>'gender' = 'female' THEN 1 ELSE 0 END) as females_in_minute
        FROM face_detections 
        GROUP BY FLOOR(timestamp_secs / 60) * 60
        ORDER BY minute_mark
    """)

    time_dist = cursor.fetchall()

    cursor.close()
    conn.close()

    return {
        "total_stats": total_stats,
        "video_stats": video_stats,
        "age_gender_dist": age_gender_dist,
        "confidence_stats": confidence_stats,
        "time_dist": time_dist,
    }


def generate_report(stats):
    """生成統計報告"""
    report = []

    report.append("=" * 70)
    report.append("人臉識別統計報告")
    report.append("=" * 70)
    report.append(f"生成時間: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
    report.append("")

    # 總體統計
    total_stats = stats["total_stats"]
    report.append("📊 總體統計")
    report.append("-" * 40)
    report.append(f"總人臉數: {total_stats[0]}")
    report.append(
        f"男性: {total_stats[1]} ({total_stats[1] / total_stats[0] * 100:.1f}%)"
    )
    report.append(
        f"女性: {total_stats[2]} ({total_stats[2] / total_stats[0] * 100:.1f}%)"
    )
    report.append(f"平均年齡: {total_stats[3]} 歲")
    report.append(f"年齡範圍: {total_stats[4]} - {total_stats[5]} 歲")
    report.append("")

    # 視頻統計
    report.append("🎬 視頻統計")
    report.append("-" * 40)
    for video in stats["video_stats"]:
        video_uuid, total, male, female, avg_age = video
        video_name = (
            "Old_Time_Movie_Show_-_Charade_1963.HD.mov"
            if video_uuid == "384b0ff44aaaa1f1"
            else "ExaSAN PCIe series"
        )
        report.append(f"視頻: {video_name}")
        report.append(f"  UUID: {video_uuid}")
        report.append(f"  總人臉: {total}")
        report.append(f"  男性: {male} ({male / total * 100:.1f}%)")
        report.append(f"  女性: {female} ({female / total * 100:.1f}%)")
        report.append(f"  平均年齡: {avg_age} 歲")
        report.append("")

    # 年齡性別分布
    report.append("👥 年齡性別分布")
    report.append("-" * 40)

    # 創建分布表
    age_groups = {}
    for age_group, gender, count in stats["age_gender_dist"]:
        if age_group not in age_groups:
            age_groups[age_group] = {"male": 0, "female": 0}
        age_groups[age_group][gender] = count

    for age_group in sorted(age_groups.keys(), key=lambda x: int(x.split("-")[0])):
        male = age_groups[age_group]["male"]
        female = age_groups[age_group]["female"]
        total = male + female
        if total > 0:
            report.append(f"{age_group}歲: {total}人 (男{male}/女{female})")

    report.append("")

    # 置信度統計
    conf_stats = stats["confidence_stats"]
    report.append("🎯 檢測置信度")
    report.append("-" * 40)
    report.append(f"平均置信度: {conf_stats[0]:.3f}")
    report.append(f"範圍: {conf_stats[1]:.3f} - {conf_stats[2]:.3f}")
    report.append(
        f"高置信度(≥0.8): {conf_stats[3]} ({conf_stats[3] / total_stats[0] * 100:.1f}%)"
    )
    report.append(
        f"中置信度(0.6-0.8): {conf_stats[4]} ({conf_stats[4] / total_stats[0] * 100:.1f}%)"
    )
    report.append(
        f"低置信度(<0.6): {conf_stats[5]} ({conf_stats[5] / total_stats[0] * 100:.1f}%)"
    )
    report.append("")

    # 時間分布
    report.append("⏰ 時間分布 (每分鐘)")
    report.append("-" * 40)
    for minute_mark, total, male, female in stats["time_dist"]:
        minutes = int(minute_mark // 60)
        seconds = int(minute_mark % 60)
        report.append(f"{minutes:02d}:{seconds:02d} - {total}人 (男{male}/女{female})")

    report.append("")
    report.append("=" * 70)

    return "\n".join(report)


def main():
    print("正在生成人臉統計報告...")

    try:
        stats = get_face_statistics()
        report = generate_report(stats)

        # 輸出到控制台
        print(report)

        # 保存到文件
        with open("/tmp/face_statistics_report.txt", "w") as f:
            f.write(report)

        print("\n報告已保存到: /tmp/face_statistics_report.txt")

    except Exception as e:
        print(f"❌ 生成報告時出錯: {e}")
        sys.exit(1)


if __name__ == "__main__":
    main()