Update app.py

app.py

@@ -408,13 +408,20 @@ class IntrusionDetection:
         except Exception as e:
             raise ValueError(f"Error in detect_intrusion: {str(e)}")
 
+import torch
+import cv2
+import numpy as np
+import os
+from ultralytics import YOLO
+import gradio as gr
+
 class IntrusionDetectionEn:
     def __init__(self, model_path="yolov8n.pt", max_intrusion_time=300, iou_threshold=0.5, conf_threshold=0.7):
         self.model_path = model_path
         self.max_intrusion_time = max_intrusion_time
         self.iou_threshold = iou_threshold
         self.conf_threshold = conf_threshold
-
+        
         # Predefined staff uniform colors (RGB format)
         self.staff_colors = [
             (139, 143, 133),  # Grayish tone
@@ -423,11 +430,12 @@ class IntrusionDetectionEn:
             (143, 147, 136),  # Gray-green
             (48, 59, 71)      # Dark blue/gray
         ]
-
-        # 🔹 Load the model once
+        
+        # Initialize device and model once
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-        self.model = YOLO(self.model_path).to(self.device)
-
+        self.model = YOLO(self.model_path)
+        self.model.to(self.device)
+    
     def is_staff(self, person_crop):
         """Checks if the detected person is a staff member based on clothing color."""
         avg_color = np.mean(person_crop, axis=(0, 1))  # Compute average color (BGR)
@@ -439,7 +447,7 @@ class IntrusionDetectionEn:
             if dist < 30:  # Threshold to consider it a match
                 return True
         return False
-
+    
     @spaces.GPU
     def intrusion_detect_en(self, video_path):
         try:
@@ -466,7 +474,7 @@ class IntrusionDetectionEn:
                     break
                 frame_count += 1
 
-                results = self.model(frame)  # 🔹 Use preloaded model
+                results = self.model(frame)
                 for result in results:
                     boxes = result.boxes.xyxy.cpu().numpy()
                     classes = result.boxes.cls.cpu().numpy()
@@ -496,6 +504,7 @@ class IntrusionDetectionEn:
             raise ValueError(f"Error in detect_intrusion: {str(e)}")
 
 
+
 import cv2
 import numpy as np
 from ultralytics import YOLO