#!/opt/homebrew/bin/python3.11
"""
ASR + Lip 對應分析
分析 ASR 轉錄時間段與 Lip 嘴部檢測的對應關係
"""

import json
import sys

def load_json(path):
    with open(path) as f:
        return json.load(f)

def analyze_asr_lip(asr_path, lip_path):
    """分析 ASR 與 Lip 的對應關係"""
    
    # 載入數據
    print(f"[Load] ASR: {asr_path}")
    asr_data = load_json(asr_path)
    
    print(f"[Load] Lip: {lip_path}")
    lip_data = load_json(lip_path)
    
    asr_segments = asr_data.get('segments', [])
    lip_frames = lip_data.get('frames', [])
    
    print(f"\n[Data] ASR segments: {len(asr_segments)}")
    print(f"[Data] Lip frames: {len(lip_frames)}")
    print()
    
    # 分析每個 ASR 段對應的 Lip 檢測
    print("=" * 80)
    print("ASR 與 Lip 對應分析")
    print("=" * 80)
    print()
    
    stats = {
        'total_asr_segments': len(asr_segments),
        'with_lip_detection': 0,
        'without_lip_detection': 0,
        'speaking_detected': 0,
        'not_speaking': 0,
        'avg_openness': [],
        'match_rate': 0.0
    }
    
    print(f"{'ASR 段':<6} {'時間範圍':<15} {'文字':<30} {'Lip 幀數':<10} {'說話':<10} {'平均開合度'}")
    print("-" * 100)
    
    for i, asr_seg in enumerate(asr_segments[:20]):  # 只分析前 20 段
        asr_start = asr_seg['start']
        asr_end = asr_seg['end']
        asr_text = asr_seg.get('text', '')[:28]
        
        # 找到時間範圍內的 Lip 幀
        lip_in_range = [
            f for f in lip_frames 
            if asr_start <= f['timestamp'] <= asr_end
        ]
        
        if lip_in_range:
            stats['with_lip_detection'] += 1
            
            # 統計說話狀態
            speaking_count = sum(1 for f in lip_in_range if f.get('is_speaking', False))
            openness_values = [f.get('lip_openness', 0) for f in lip_in_range if f['face_detected']]
            
            if speaking_count > 0:
                stats['speaking_detected'] += 1
                speak_status = f"✅ {speaking_count}/{len(lip_in_range)}"
            else:
                stats['not_speaking'] += 1
                speak_status = f"❌ 0/{len(lip_in_range)}"
            
            avg_openness = sum(openness_values) / len(openness_values) if openness_values else 0
            stats['avg_openness'].append(avg_openness)
            
            print(f"{i+1:<6} {asr_start:.1f}-{asr_end:.1f}s{'':<5} {asr_text:<30} {len(lip_in_range):<10} {speak_status:<10} {avg_openness:.3f}")
        else:
            stats['without_lip_detection'] += 1
            print(f"{i+1:<6} {asr_start:.1f}-{asr_end:.1f}s{'':<5} {asr_text:<30} {'0':<10} {'-':<10} {'-':<10}")
    
    # 計算匹配率
    if stats['with_lip_detection'] > 0:
        stats['match_rate'] = stats['speaking_detected'] / stats['with_lip_detection'] * 100
    
    print()
    print("=" * 80)
    print("統計摘要")
    print("=" * 80)
    print()
    
    print(f"ASR 總段數：{stats['total_asr_segments']}")
    print(f"有 Lip 檢測：{stats['with_lip_detection']} ({stats['with_lip_detection']/stats['total_asr_segments']*100:.1f}%)")
    print(f"無 Lip 檢測：{stats['without_lip_detection']} ({stats['without_lip_detection']/stats['total_asr_segments']*100:.1f}%)")
    print()
    print(f"檢測到說話：{stats['speaking_detected']} ({stats['match_rate']:.1f}%)")
    print(f"未檢測說話：{stats['not_speaking']}")
    print()
    
    if stats['avg_openness']:
        overall_avg = sum(stats['avg_openness']) / len(stats['avg_openness'])
        print(f"平均嘴部開合度：{overall_avg:.4f}")
    
    print()
    
    return stats

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: python3 analyze_asr_lip.py <asr.json> <lip.json>")
        sys.exit(1)
    
    analyze_asr_lip(sys.argv[1], sys.argv[2])