Update app.py

app.py

@@ -177,8 +177,11 @@ def run_temporal_analysis(stream_id, frames_3d_copy, prob_max, prob_mean, prob_m
         state["cnn"] = round(yolo_max_conf, 1)
         state["rcnn"] = round(float(np.max(prob_3d)) * 100, 1)
 
-        # FIX: Restored threshold back to 85 from 75 to completely eliminate false positives on noisy live feeds
-        if confidence > 85:
+        # FIX: Dynamic Threshold - 85% for strict Live IP noise filtering, 75% for fast Uploads detection
+        is_live_stream = state.get("is_live", False)
+        threshold = 85 if is_live_stream else 75
+
+        if confidence > threshold:
             state["final_decision"] = True
             state["label"] = f"Incident Logged: {severity.capitalize()}"
             threading.Thread(target=process_accident_async, args=(stream_id, raw_frame, location, confidence, severity)).start()
@@ -337,7 +340,7 @@ def video_stream_gen(stream_id, source, location):
         if w > 1280: frame = cv2.resize(frame, (1280, int(h * 1280 / w)))
 
         if is_live:
-            state['progress'] = 100 # Hide for live
+            state['progress'] = 100 
         elif total_frames > 0:
             state['progress'] = (current_frame_idx / total_frames) * 100
 
@@ -365,7 +368,6 @@ def video_stream_gen(stream_id, source, location):
                 yolo_probs.append(probs)
                 if len(yolo_probs) > 10: yolo_probs.pop(0)
 
-                # LIVE update of Spatial UI data
                 if len(yolo_probs) > 0:
                     curr_max = np.max(yolo_probs, axis=0)
                     acc_conf = float(np.max(curr_max[:3])) * 100 if len(curr_max) >= 3 else float(np.max(curr_max)) * 100
@@ -376,12 +378,13 @@ def video_stream_gen(stream_id, source, location):
                 f_3d = cv2.resize(frame, (112, 112))
                 frames_3d.append(cv2.cvtColor(f_3d, cv2.COLOR_BGR2RGB))
                 
-                # FIX: Removed artificial frame padding. It now strictly waits for 16 genuine frames.
-                # This prevents network stutters from being interpreted as "crashes" by the 3D-CNN.
                 if len(frames_3d) > 16: 
                     frames_3d.pop(0)
 
-                if len(frames_3d) == 16 and frame_count % 10 == 0 and not state.get("is_analyzing"):
+                # FIX: Adaptive Polling Rate - Analyzes 2x faster (every 5 frames instead of 10) for uploads
+                analyze_interval = 10 if is_live else 5
+                
+                if len(frames_3d) == 16 and frame_count % analyze_interval == 0 and not state.get("is_analyzing"):
                     state["is_analyzing"] = True
                     
                     analysis_frames = list(frames_3d)