feat: update Python processors and add utility scripts

- Update ASR, face, OCR, pose processors
- Add release pre-flight check script
- Add synonym generation, chunk processing scripts
- Add face recognition, stamp search utilities

scripts/analyze_asr_lip.py

@@ -0,0 +1,114 @@
+#!/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])