cleanup: remove dead code and duplicate docs

- Remove session-ses_2f27.md (161KB raw session log)
- Remove 49 ROOT_* duplicate files across REFERENCE/
- Remove 14 duplicate files between REFERENCE/ root and history/
- Remove asr_legacy.rs (dead code, replaced by asr.rs)
- Remove src/core/worker/ (duplicate JobWorker)
- Remove src/core/layers/ (empty directory)
- Remove 4 .bak files in src/
- Remove 7 dead private methods in worker/processor.rs
- Remove backup directory from git tracking

scripts/utils/body_action_decoder.py

@@ -44,12 +44,10 @@ Architecture:
 └─────────────────────────────────────────────────────────────────┘
 """
 
-import sys
 import json
 import argparse
 import numpy as np
-from typing import Dict, List, Optional
-from collections import defaultdict
+from typing import Dict, List
 
 
 # =============================================================================

scripts/utils/face_trace_visualizer.py

@@ -7,12 +7,10 @@ Output:
 2. Trace statistics CSV
 """
 
-import sys
 import json
 import argparse
 import numpy as np
 import matplotlib.pyplot as plt
-from matplotlib.patches import Rectangle
 from collections import defaultdict
 from typing import Dict
 

scripts/utils/face_tracker.py

@@ -25,11 +25,10 @@ Output:
 - trace statistics report
 """
 
-import sys
 import json
 import argparse
 import numpy as np
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List
 from collections import defaultdict
 
 

scripts/utils/pose_action_decoder.py

@@ -18,12 +18,10 @@ Output:
 3. Action visualization (timeline plot)
 """
 
-import sys
 import json
 import argparse
-import numpy as np
 import matplotlib.pyplot as plt
-from typing import Dict, List, Optional
+from typing import Dict, List
 from collections import defaultdict
 
 
@@ -445,29 +443,29 @@ def print_action_report(action_data: Dict) -> None:
         print(f"{'='*70}")
         
         summary = data["action_summary"]
-        print(f"\nSummary:")
+        print("\nSummary:")
         print(f"  Total Actions: {summary['total_actions']}")
         print(f"  Unique Actions: {summary['unique_actions']}")
         print(f"  Complex Actions: {summary['complex_action_count']}")
         print(f"  Stable Percentage: {summary['stable_percentage']}%")
         
-        print(f"\nAction Counts:")
+        print("\nAction Counts:")
         for action, count in sorted(summary["action_counts"].items(), key=lambda x: x[1], reverse=True):
             print(f"  {action}: {count}")
         
-        print(f"\nAction Timeline (前 10 个):")
+        print("\nAction Timeline (前 10 个):")
         timeline = data["action_timeline"]
         for act in timeline[:10]:
             print(f"  Frame {act['frame']}: {act['action']} ({act['type']}, {act['duration_frames']} frames)")
         
         if data["complex_actions"]:
-            print(f"\nComplex Actions:")
+            print("\nComplex Actions:")
             for act in data["complex_actions"]:
                 print(f"  {act['action']}: frames {act['start_frame']}-{act['end_frame']} ({act['duration_frames']} frames)")
         
         # Generate description
         desc = generate_action_description(data["action_timeline"])
-        print(f"\nHuman-readable Description:")
+        print("\nHuman-readable Description:")
         print(f"  {desc}")
 
 

scripts/utils/pose_analyzer.py

@@ -32,7 +32,7 @@ Usage:
 """
 
 import numpy as np
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Tuple
 
 
 def calculate_nose_to_eye_ratio(landmarks: List) -> Tuple[float, float, float]:

scripts/utils/pose_transition_analyzer.py

@@ -13,13 +13,11 @@ Output:
 3. Stability score per trace
 """
 
-import sys
 import json
 import argparse
 import numpy as np
 import matplotlib.pyplot as plt
-from typing import Dict, List
-from collections import defaultdict
+from typing import Dict
 
 
 def analyze_pose_transitions(face_data: Dict) -> Dict:
@@ -199,7 +197,7 @@ def print_transition_analysis(analysis: Dict) -> None:
         print(f"Stability Score: {data['stability_score']} (0-1, higher = more stable)")
         print(f"Longest Stable Pose: {data['longest_stable_pose']['angle']} ({data['longest_stable_pose']['duration_frames']} frames)")
         
-        print(f"\nPose Average Duration:")
+        print("\nPose Average Duration:")
         for angle, avg_dur in data['pose_avg_duration'].items():
             print(f"  {angle}: {avg_dur} frames")
         

scripts/utils/test_mediapipe.py

@@ -9,7 +9,6 @@ Test modules:
 4. Holistic (Face + Pose + Hands)
 """
 
-import sys
 import cv2
 import numpy as np
 import mediapipe as mp
@@ -81,7 +80,7 @@ def test_face_mesh():
             horizontal_dist = abs(p4.x - p3.x)
             ear_left = vertical_dist / horizontal_dist if horizontal_dist > 0 else 0
             
-            print(f"\nEye Aspect Ratio (EAR):")
+            print("\nEye Aspect Ratio (EAR):")
             print(f"  Left eye EAR: {ear_left:.3f}")
             print(f"  Interpretation: {'wide_open' if ear_left > 0.35 else 'normal' if ear_left > 0.2 else 'closed'}")
             
@@ -95,7 +94,7 @@ def test_face_mesh():
             mouth_width = abs(mouth_right.x - mouth_left.x)
             mar = mouth_height / mouth_width if mouth_width > 0 else 0
             
-            print(f"\nMouth Aspect Ratio (MAR):")
+            print("\nMouth Aspect Ratio (MAR):")
             print(f"  MAR: {mar:.3f}")
             print(f"  Interpretation: {'open' if mar > 0.5 else 'closed' if mar < 0.2 else 'slightly_open'}")
         else:
@@ -179,7 +178,7 @@ def test_pose():
             
             # Check if arm is raised
             if right_wrist.y < right_elbow.y < right_shoulder.y:
-                print(f"  Action: raise_right (arm raised)")
+                print("  Action: raise_right (arm raised)")
             
             # Knee angles
             left_hip = landmarks[23]
@@ -241,7 +240,7 @@ def test_hands():
                     "pinky_tip": 20,
                 }
                 
-                print(f"  Key landmarks:")
+                print("  Key landmarks:")
                 for name, i in key_indices.items():
                     lm = landmarks[i]
                     print(f"    {name} ({i}): x={lm.x:.3f}, y={lm.y:.3f}")