Merge branch 'fix/nlp_emotion_core' into 'master'

fix: nlp_emotion_core.py

See merge request !8

src/lhw_nlp/lhw_nlp/README.md

+# NLP EMOTION CORE - @nlp
+
+**TLDR**  
+Make sure to build the project.
+
+Start the following nodes:
+- text_2_emotion_1 (.py)
+- text_2_emotion_2 (.py)
+- nlp_emotion_core (.py)
+
+Listen to the topic 'nlp_emotion'
+To test the system post text responses to the topic 'dialogflow_response' as the following:
+
+ros2 topic pub /dialogflow_response lhw_interfaces/msg/Response "{recognized_text: 'I am feeling happy today!'}" -1
+
+**A bit more details**
+
+Two nodes perofm text to emotion analysis:
+- text_2_emotion_1 (.py)
+- text_2_emotion_2 (.py)
+
+Both of these nodes take input from the topic 'dialogflow_resonse' and publish to the topic 'text_emotion'.
+
+The node 'nlp_emotion_core' listens for events on the 'text_emotion' topic. It analyzes the input, weights the different emotions and publishes the best emotion(results) to the 'nlp_emotion' topic.
\ No newline at end of file

src/lhw_nlp/lhw_nlp/nlp_emotion_core.py

@@ -23,6 +23,7 @@ class NodeNlpEmotionCore(Node):
 
         # Publish data to the topic 'nlp_emotion'
         # The data type for the response is '???????'
+        self.input_dict = {}
         self.reset_data()
         self.timer = Timer(1, self.fire_emotion_event)
         self.broadcast_emotion = self.create_publisher(EventT2E, 'nlp_emotion', 10)
@@ -34,24 +35,25 @@ class NodeNlpEmotionCore(Node):
         }
 
     def event_t2e_init_zero(self, obj):
-        obj.angry = 0
-        obj.disgust = 0
-        obj.fear = 0
-        obj.happy = 0
-        obj.neutral = 0
-        obj.sad = 0
-        obj.surprised = 0
+        obj.angry = 0.0
+        obj.disgust = 0.0
+        obj.fear = 0.0
+        obj.happy = 0.0
+        obj.neutral = 0.0
+        obj.sad = 0.0
+        obj.surprised = 0.0
         return obj
 
     def event_t2e_normalize(self, obj):
         sum = 0
-        sum += obj.angry
-        sum += obj.disgust
-        sum += obj.fear
-        sum += obj.happy
-        sum += obj.neutral
-        sum += obj.sad
-        sum += obj.surprised
+        sum += obj.angry     if obj.angry > 0 else 0
+        sum += obj.disgust   if obj.disgust > 0 else 0
+        sum += obj.fear      if obj.fear > 0 else 0
+        sum += obj.happy     if obj.happy > 0 else 0
+        sum += obj.neutral   if obj.neutral > 0 else 0
+        sum += obj.sad       if obj.sad > 0 else 0
+        sum += obj.surprised if obj.surprised > 0 else 0
+
         obj.angry = obj.angry / sum
         obj.disgust = obj.disgust / sum
         obj.fear = obj.fear / sum
@@ -59,6 +61,15 @@ class NodeNlpEmotionCore(Node):
         obj.neutral = obj.neutral / sum
         obj.sad = obj.sad / sum
         obj.surprised = obj.surprised / sum
+
+        obj.angry =     obj.angry       if obj.angry > 0 else 0.0
+        obj.disgust =   obj.disgust     if obj.disgust > 0 else 0.0
+        obj.fear =      obj.fear        if obj.fear > 0 else 0.0
+        obj.happy =     obj.happy       if obj.happy > 0 else 0.0
+        obj.neutral =   obj.neutral     if obj.neutral > 0 else 0.0
+        obj.sad =       obj.sad         if obj.sad > 0 else 0.0
+        obj.surprised = obj.surprised   if obj.surprised > 0 else 0.0
+
         return obj
 
     def get_aggregated_emotion_event(self, key): 
@@ -126,7 +137,7 @@ class NodeNlpEmotionCore(Node):
 
         msg_emotion = self.event_t2e_normalize(msg_emotion)
 
-        dominant_emotion = self.CLASS_NAMES.index(max([
+        temp_lst = [
             msg_emotion.angry,
             msg_emotion.disgust,
             msg_emotion.fear,
@@ -134,9 +145,12 @@ class NodeNlpEmotionCore(Node):
             msg_emotion.neutral,
             msg_emotion.sad,
             msg_emotion.surprised
-        ]))
+        ]
+        dominant_emotion = self.CLASS_NAMES[temp_lst.index(max(temp_lst))]
         msg_emotion.dominant_emotion = dominant_emotion
-        
+
+        print('--------------------THIS IS THE FINAL EMOTION OUTPUT:\n  ', msg_emotion)
+
         self.broadcast_emotion.publish(msg_emotion)
         self.reset_data()
 
@@ -146,23 +160,17 @@ class NodeNlpEmotionCore(Node):
         print(emotion_event)
 
         if (emotion_event.source_id == Response.TEXT_2_EMOTION_1):
-            print('----- TEXT_2_EMOTION 1111111')
             self.timer.cancel()
             self.input_dict['t2e-1'].append(emotion_event)
             self.timer = Timer(timer_wait_time, self.fire_emotion_event)
             self.timer.start()
 
         elif (emotion_event.source_id == Response.TEXT_2_EMOTION_2):
-            print('----- TEXT_2_EMOTION 2222222')
             self.timer.cancel()
             self.input_dict['t2e-2'].append(emotion_event)
             self.timer = Timer(timer_wait_time, self.fire_emotion_event)
             self.timer.start()
 
-        print(self.input_dict)
-        print('')
-
-
 def main(args=None):
     rclpy.init(args=args)
     nlm_emotion_core = NodeNlpEmotionCore()