feat(motion_app): implement asynchronous similarity calculation

pose_analyzer.py

@@ -1,6 +1,7 @@
 import numpy as np
 import math
 import time
+import threading
 from collections import deque
 import plotly.graph_objects as go
 
@@ -11,6 +12,7 @@ class PoseSimilarityAnalyzer:
         self.similarity_history = deque(maxlen=500)
         self.frame_timestamps = deque(maxlen=500)
         self.start_time = None
+        self._lock = threading.Lock()  # Thread safety for shared data
 
         self.keypoint_map = {
             'nose': 0, 'neck': 1, 'left_shoulder': 2, 'left_elbow': 3, 'left_wrist': 4,
@@ -94,21 +96,27 @@ class PoseSimilarityAnalyzer:
 
     def add_similarity_score(self, score, timestamp=None):
         """Adds a similarity score to the history."""
-        if self.start_time is None: self.start_time = time.time()
-        timestamp = timestamp if timestamp is not None else time.time() - self.start_time
-        self.similarity_history.append(float(score))
-        self.frame_timestamps.append(float(timestamp))
+        with self._lock:
+            if self.start_time is None: self.start_time = time.time()
+            timestamp = timestamp if timestamp is not None else time.time() - self.start_time
+            self.similarity_history.append(float(score))
+            self.frame_timestamps.append(float(timestamp))
         
     def get_similarity_plot(self):
         """Generates a Plotly figure for the similarity history."""
-        if len(self.similarity_history) < 2: return None
+        with self._lock:
+            if len(self.similarity_history) < 2: return None
+            
+            # Create copies to avoid data changes during plotting
+            timestamps_copy = list(self.frame_timestamps)
+            history_copy = list(self.similarity_history)
         
         fig = go.Figure()
-        fig.add_trace(go.Scatter(x=list(self.frame_timestamps), y=list(self.similarity_history),
+        fig.add_trace(go.Scatter(x=timestamps_copy, y=history_copy,
                                  mode='lines+markers', name='Similarity',
                                  line=dict(color='#2E86AB', width=2), marker=dict(size=4)))
         
-        avg_score = sum(self.similarity_history) / len(self.similarity_history)
+        avg_score = sum(history_copy) / len(history_copy)
         fig.add_hline(y=avg_score, line_dash="dash", line_color="red",
                       annotation_text=f"Avg: {avg_score:.1f}%")
 
@@ -119,6 +127,7 @@ class PoseSimilarityAnalyzer:
 
     def reset(self):
         """Resets the analyzer's history."""
-        self.similarity_history.clear()
-        self.frame_timestamps.clear()
-        self.start_time = None
+        with self._lock:
+            self.similarity_history.clear()
+            self.frame_timestamps.clear()
+            self.start_time = None