Update app.py

app.py

@@ -177,8 +177,8 @@ def run_temporal_analysis(stream_id, frames_3d_copy, prob_max, prob_mean, prob_m
         state["rcnn"] = round(float(np.max(prob_3d)) * 100, 1)
 
         # 🚨 FIX: Strict Dual-Consensus checks to prevent IP camera frame-drop false positives!
-        # Requires 85% overall confidence AND at least 45% spatial confirmation of an actual object collision.
-        if confidence > 85 and yolo_max_conf > 45.0:
+        # Requires 75% overall confidence AND at least 50% spatial confirmation from YOLO of an actual object collision.
+        if confidence > 75 and yolo_max_conf > 50.0:
             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()
@@ -186,7 +186,7 @@ def run_temporal_analysis(stream_id, frames_3d_copy, prob_max, prob_mean, prob_m
             state["label"] = f"Analyzing... ({severity.capitalize()})"
 
     except Exception as e:
-        print(f"AI Error: {e}", flush=True)
+        print(f"AI Error in Temporal Engine: {e}", flush=True)
     finally:
         if state: state["is_analyzing"] = False
 
@@ -204,9 +204,9 @@ def init_upload():
     active_streams[stream_id] = {
         "label": "Initializing...", "final_decision": False, "confidence": 0, "severity": "--", 
         "plates": [], "show_tracking": True, "paused": False, "seek_to": None, "skip_val": 0, "progress": 0,
-        "cnn": 0, "rcnn": 0, "force_update": False
+        "cnn": 0, "rcnn": 0, "force_update": False, "is_live": False
     }
-    return jsonify({"stream_id": stream_id, "location": loc, "weather": wx, "time": file_time})
+    return jsonify({"stream_id": stream_id, "location": loc, "weather": wx, "time": file_time, "is_live": False})
 
 @app.route('/init_stream', methods=['POST'])
 def init_stream():
@@ -234,9 +234,9 @@ def init_stream():
     active_streams[stream_id] = {
         "label": "Connecting...", "final_decision": False, "confidence": 0, "severity": "--", 
         "plates": [], "show_tracking": True, "paused": False, "seek_to": None, "skip_val": 0, "progress": 0,
-        "cnn": 0, "rcnn": 0, "force_update": False
+        "cnn": 0, "rcnn": 0, "force_update": False, "is_live": True
     }
-    return jsonify({"stream_id": stream_id, "location": loc, "weather": wx, "time": v_time})
+    return jsonify({"stream_id": stream_id, "location": loc, "weather": wx, "time": v_time, "is_live": True})
 
 @app.route('/video_control/<stream_id>', methods=['POST'])
 def video_control(stream_id):
@@ -279,7 +279,7 @@ def video_stream_gen(stream_id, source, location):
 
         force_read = False
 
-        if state.get('skip_val', 0) != 0:
+        if state.get('skip_val', 0) != 0 and not is_live:
             target = max(0, min(current_frame_idx + (state['skip_val'] * fps), total_frames - 1))
             cap.set(cv2.CAP_PROP_POS_FRAMES, target)
             current_frame_idx = int(target)
@@ -288,7 +288,7 @@ def video_stream_gen(stream_id, source, location):
             frames_3d.clear(); yolo_probs.clear()
             force_read = True
 
-        if state.get('seek_to') is not None:
+        if state.get('seek_to') is not None and not is_live:
             target = int(state['seek_to'] * total_frames)
             cap.set(cv2.CAP_PROP_POS_FRAMES, target)
             current_frame_idx = target
@@ -336,7 +336,9 @@ def video_stream_gen(stream_id, source, location):
         h, w = frame.shape[:2]
         if w > 1280: frame = cv2.resize(frame, (1280, int(h * 1280 / w)))
 
-        if total_frames > 0:
+        if is_live:
+            state['progress'] = 100 # Hide for live
+        elif total_frames > 0:
             state['progress'] = (current_frame_idx / total_frames) * 100
 
         try:
@@ -363,7 +365,7 @@ def video_stream_gen(stream_id, source, location):
                 yolo_probs.append(probs)
                 if len(yolo_probs) > 10: yolo_probs.pop(0)
 
-                # 🚨 FIX: LIVE update of Spatial UI data so the screen doesn't feel stuck
+                # 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
@@ -373,15 +375,16 @@ 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))
-                if len(frames_3d) > 16: frames_3d.pop(0)
+                
+                # 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) >= 8 and frame_count % 10 == 0 and not state.get("is_analyzing"):
+                if len(frames_3d) == 16 and frame_count % 10 == 0 and not state.get("is_analyzing"):
                     state["is_analyzing"] = True
                     
                     analysis_frames = list(frames_3d)
-                    while len(analysis_frames) < 16:
-                        analysis_frames.append(analysis_frames[-1])
-                        
                     p_max = np.max(yolo_probs, axis=0) if len(yolo_probs) > 0 else np.zeros(4)
                     p_mean = np.mean(yolo_probs, axis=0) if len(yolo_probs) > 0 else np.zeros(4)
                     p_min = np.min(yolo_probs, axis=0) if len(yolo_probs) > 0 else np.zeros(4)
@@ -427,8 +430,7 @@ def predict_traffic_risk():
     except Exception as e: return jsonify({"error": str(e)}), 500
 
 @app.route('/favicon.ico')
-@app.route('/logo.png')
-@app.route('/logo.PNG')
+@app.route('/app_logo')
 def serve_logo():
     static_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'static')
     if os.path.exists(os.path.join(static_dir, 'logo.png')):