src/control_backend/agents/perception/visual_emotion_recognition_agent/visual_emotion_recognition_agent.py

@@ -6,23 +6,27 @@ import cv2
 import numpy as np
 import zmq
 import zmq.asyncio as azmq
-from control_backend.agents.perception.visual_emotion_recognition_agentvisual_emotion_recognizer import (  # noqa
-    DeepFaceEmotionRecognizer,
-)
 from pydantic_core import ValidationError
 
 from control_backend.agents import BaseAgent
+from control_backend.agents.perception.visual_emotion_recognition_agent.visual_emotion_recognizer import (  # noqa
+    DeepFaceEmotionRecognizer,
+)
 from control_backend.core.agent_system import InternalMessage
 from control_backend.core.config import settings
 from control_backend.schemas.belief_message import Belief
 
 
 class VisualEmotionRecognitionAgent(BaseAgent):
-    def __init__(self, name: str, socket_address: str, bind: bool = False, timeout_ms: int = 1000, 
+    def __init__(
-                 window_duration: 
+        self,
-                 int = settings.behaviour_settings.visual_emotion_recognition_window_duration_s
+        name: str,
-                 , min_frames_required: int = 
+        socket_address: str,
-                 settings.behaviour_settings.visual_emotion_recognition_min_frames_per_face):
+        bind: bool = False,
+        timeout_ms: int = 1000,
+        window_duration: int = settings.behaviour_settings.visual_emotion_recognition_window_duration_s,  # noqa
+        min_frames_required: int = settings.behaviour_settings.visual_emotion_recognition_min_frames_per_face,  # noqa
+    ):
         """
         Initialize the Visual Emotion Recognition Agent.
 
@@ -31,7 +35,7 @@ class VisualEmotionRecognitionAgent(BaseAgent):
         :param bind: Whether to bind to the socket address (True) or connect (False)
         :param timeout_ms: Timeout for socket receive operations in milliseconds
         :param window_duration: Duration in seconds over which to aggregate emotions
-        :param min_frames_required: Minimum number of frames per face required to consider a face 
+        :param min_frames_required: Minimum number of frames per face required to consider a face
         valid
         """
         super().__init__(name)
@@ -78,29 +82,29 @@ class VisualEmotionRecognitionAgent(BaseAgent):
 
         # Tracks counts of detected emotions per face index
         face_stats = defaultdict(Counter)
-        
+
         prev_dominant_emotions = set()
 
         while self._running:
             try:
                 frame_bytes = await self.video_in_socket.recv()
-                
+
                 # Convert bytes to a numpy buffer
                 nparr = np.frombuffer(frame_bytes, np.uint8)
-                
+
                 # Decode image into the generic Numpy Array DeepFace expects
                 frame_image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
 
                 if frame_image is None:
                     # Could not decode image, skip this frame
                     continue
-                
+
                 # Get the dominant emotion from each face
                 current_emotions = self.emotion_recognizer.sorted_dominant_emotions(frame_image)
                 # Update emotion counts for each detected face
                 for i, emotion in enumerate(current_emotions):
                     face_stats[i][emotion] += 1
-                
+
                 # If window duration has passed, process the collected stats
                 if time.time() >= next_window_time:
                     window_dominant_emotions = set()
@@ -111,35 +115,36 @@ class VisualEmotionRecognitionAgent(BaseAgent):
                         if total_detections >= self.min_frames_required:
                             dominant_emotion = counter.most_common(1)[0][0]
                             window_dominant_emotions.add(dominant_emotion)
-                    
+
                     await self.update_emotions(prev_dominant_emotions, window_dominant_emotions)
                     prev_dominant_emotions = window_dominant_emotions
                     face_stats.clear()
                     next_window_time = time.time() + self.window_duration
-                
+
             except zmq.Again:
                 self.logger.warning("No video frame received within timeout.")
 
     async def update_emotions(self, prev_emotions: set[str], emotions: set[str]):
         """
-        Compare emotions from previous window and current emotions, 
+        Compare emotions from previous window and current emotions,
         send updates to BDI Core Agent.
         """
         emotions_to_remove = prev_emotions - emotions
         emotions_to_add = emotions - prev_emotions
 
         if not emotions_to_add and not emotions_to_remove:
-            return  
+            return
-        
+
         emotion_beliefs_remove = []
         for emotion in emotions_to_remove:
             self.logger.info(f"Emotion '{emotion}' has disappeared.")
             try:
-                emotion_beliefs_remove.append(Belief(name="emotion_detected", arguments=[emotion], 
+                emotion_beliefs_remove.append(
-                                                     remove=True))
+                    Belief(name="emotion_detected", arguments=[emotion], remove=True)
+                )
             except ValidationError:
                 self.logger.warning("Invalid belief for emotion removal: %s", emotion)
-        
+
         emotion_beliefs_add = []
         for emotion in emotions_to_add:
             self.logger.info(f"New emotion detected: '{emotion}'")
@@ -147,7 +152,7 @@ class VisualEmotionRecognitionAgent(BaseAgent):
                 emotion_beliefs_add.append(Belief(name="emotion_detected", arguments=[emotion]))
             except ValidationError:
                 self.logger.warning("Invalid belief for new emotion: %s", emotion)
-        
+
         beliefs_list_add = [b.model_dump() for b in emotion_beliefs_add]
         beliefs_list_remove = [b.model_dump() for b in emotion_beliefs_remove]
         payload = {"create": beliefs_list_add, "delete": beliefs_list_remove}
@@ -158,4 +163,4 @@ class VisualEmotionRecognitionAgent(BaseAgent):
             body=json.dumps(payload),
             thread="beliefs",
         )
-        await self.send(message)
+        await self.send(message)