Update app.py

app.py

@@ -9,10 +9,10 @@ import os
 
 class CrowdDetection:
     def __init__(self, model_path="yolov8n.pt"):
-        self.model_path = model_path  # Store path, load model later
+        self.model_path = model_path
 
     @spaces.GPU
-    def detect_crowd(self, video_path):
+    def crowd_detection(self, video_path):
         try:
             device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
             if not os.path.exists(self.model_path):
@@ -69,14 +69,14 @@ class CrowdDetection:
                 raise ValueError("❌ Processing failed: No frames processed or output not created")
             return output_path
         except Exception as e:
-            raise ValueError(f"Error in detect_crowd: {str(e)}")
+            raise ValueError(f"Error in crowd_detection: {str(e)}")
 
 class PeopleTracking:
     def __init__(self, yolo_model_path="yolov8n.pt"):
         self.model_path = yolo_model_path
 
     @spaces.GPU
-    def track_people(self, video_path):
+    def people_tracking(self, video_path):
         try:
             device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
             if not os.path.exists(self.model_path):
@@ -124,14 +124,14 @@ class PeopleTracking:
                 raise ValueError("❌ Processing failed")
             return output_path
         except Exception as e:
-            raise ValueError(f"Error in track_people: {str(e)}")
+            raise ValueError(f"Error in people_tracking: {str(e)}")
 
 class FallDetection:
     def __init__(self, yolo_model_path="yolov8l.pt"):
         self.model_path = yolo_model_path
 
     @spaces.GPU
-    def detect_fall(self, video_path):
+    def fall_detection(self, video_path):
         try:
             device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
             if not os.path.exists(self.model_path):
@@ -189,14 +189,14 @@ class FallDetection:
                 raise ValueError("❌ Processing failed")
             return output_path
         except Exception as e:
-            raise ValueError(f"Error in detect_fall: {str(e)}")
+            raise ValueError(f"Error in fall_detection: {str(e)}")
 
 class FightDetection:
     def __init__(self, yolo_model_path="yolov8n-pose.pt"):
         self.model_path = yolo_model_path
 
     @spaces.GPU
-    def detect_fight(self, video_path):
+    def fight_detection(self, video_path):
         try:
             device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
             if not os.path.exists(self.model_path):
@@ -254,7 +254,7 @@ class FightDetection:
                 raise ValueError("❌ Processing failed")
             return output_path
         except Exception as e:
-            raise ValueError(f"Error in detect_fight: {str(e)}")
+            raise ValueError(f"Error in fight_detection: {str(e)}")
 
 # Unified processing function with status output
 def process_video(feature, video):