added more behaviours

app.py

@@ -24,7 +24,10 @@ class DogBehaviorAnalyzer:
             'tail_wagging': {'threshold': 0.15, 'description': 'Your dog is displaying happiness and excitement!'},
             'movement': {'threshold': 0.02, 'description': 'Your dog is active and moving around.'},
             'stationary': {'threshold': 0.01, 'description': 'Your dog is calm and still.'},
-            'high_activity': {'threshold': 0.05, 'description': 'Your dog is very energetic!'}
+            'high_activity': {'threshold': 0.05, 'description': 'Your dog is very energetic!'},
+            'barking': {'threshold': 0.10, 'description': 'Your dog is trying to communicate!'},
+            'jumping': {'threshold': 0.12, 'description': 'Your dog is showing excitement through jumping!'},
+            'ears_perked': {'threshold': 0.08, 'description': 'Your dog is alert and attentive!'}
         }
         
         self.suggestions = {
@@ -48,6 +51,24 @@ class DogBehaviorAnalyzer:
                 "Consider redirecting energy into agility training",
                 "A good play session with toys would be beneficial",
                 "Make sure fresh water is available"
+            ],
+            'barking': [
+                "Try to identify what's triggering the barking",
+                "Practice 'quiet' command training",
+                "Redirect attention with engaging toys",
+                "Consider working on bark control exercises"
+            ],
+            'jumping': [
+                "Practice the 'four paws on the floor' training",
+                "Redirect jumping energy into trick training",
+                "Work on impulse control exercises",
+                "Try teaching alternative greetings like 'sit' for attention"
+            ],
+            'ears_perked': [
+                "Great time for sound recognition training",
+                "Practice attention and focus exercises",
+                "Good moment for environmental awareness training",
+                "Consider introducing new sounds or stimuli for enrichment"
             ]
         }
         
@@ -113,12 +134,17 @@ class DogBehaviorAnalyzer:
         """Analyze frame with improved behavior detection logic"""
         motion_score = self.detect_motion(frame)
         color_change_score = self.detect_color_changes(frame)
+        audio_score = self.detect_audio(frame) if hasattr(frame, 'audio') else 0
         
         detected_behaviors = []
         
         # High activity detection (running, jumping)
         if motion_score > self.behaviors['high_activity']['threshold']:
             detected_behaviors.append(('high_activity', motion_score))
+            
+            # Jumping detection (vertical motion)
+            if self.detect_vertical_motion(frame) > self.behaviors['jumping']['threshold']:
+                detected_behaviors.append(('jumping', motion_score * 1.2))
         
         # Regular movement detection
         elif motion_score > self.behaviors['movement']['threshold']:
@@ -131,6 +157,15 @@ class DogBehaviorAnalyzer:
         # Tail wagging detection - based on localized color changes
         if color_change_score > self.behaviors['tail_wagging']['threshold']:
             detected_behaviors.append(('tail_wagging', color_change_score))
+            
+        # Ears perked detection - based on ear region analysis
+        ears_score = self.detect_ear_position(frame)
+        if ears_score > self.behaviors['ears_perked']['threshold']:
+            detected_behaviors.append(('ears_perked', ears_score))
+            
+        # Barking detection - based on audio analysis
+        if audio_score > self.behaviors['barking']['threshold']:
+            detected_behaviors.append(('barking', audio_score))
         
         # Debug information
         if not detected_behaviors:
@@ -138,6 +173,41 @@ class DogBehaviorAnalyzer:
             st.sidebar.write(f"Debug - Color Change Score: {color_change_score:.4f}")
         
         return detected_behaviors
+        
+    def detect_vertical_motion(self, frame):
+        """Detect vertical motion for jumping behavior"""
+        # Simple implementation - can be enhanced with more sophisticated motion tracking
+        if self.prev_frame is None:
+            return 0.0
+            
+        frame = cv2.resize(frame, (300, 300))
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        
+        # Calculate optical flow
+        flow = cv2.calcOpticalFlowFarneback(self.prev_frame, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
+        
+        # Extract vertical motion component
+        vertical_motion = np.abs(flow[..., 1]).mean()
+        return vertical_motion
+        
+    def detect_ear_position(self, frame):
+        """Detect ear position for ears_perked behavior"""
+        # Placeholder implementation - can be enhanced with actual ear detection model
+        # For now, using simple edge detection in upper region of frame
+        frame = cv2.resize(frame, (300, 300))
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        
+        # Focus on upper region where ears typically are
+        upper_region = gray[0:100, :]
+        edges = cv2.Canny(upper_region, 100, 200)
+        
+        return np.sum(edges > 0) / edges.size
+        
+    def detect_audio(self, frame):
+        """Detect audio for barking behavior"""
+        # Placeholder - actual implementation would need audio processing
+        # Return 0 as this is just a placeholder
+        return 0.0
 
     def get_suggestions(self, detected_behaviors, behavior_counts):
         """Generate suggestions based on detected behaviors and their frequency"""