added output

optimized.py

@@ -10,6 +10,7 @@ from fastai.vision.all import load_learner
 from transformers import WhisperProcessor, WhisperForConditionalGeneration, pipeline
 
 emotion_pipeline = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-emotion")
+sentiment_pipeline = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
 
 model = load_learner("gaze-recognizer-v3.pkl")
 
@@ -17,6 +18,14 @@ def extract_audio(video_path):
     clip = mp.VideoFileClip(video_path)
     clip.audio.write_audiofile("audio.wav")
 
+def analyze_emotion(text):
+    result = emotion_pipeline(text)
+    return result
+
+def analyze_sentiment(text):
+    result = sentiment_pipeline(text)
+    return result
+
 def get_transcription(path):
     extract_audio(path)
 
@@ -34,10 +43,6 @@ def get_transcription(path):
     transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
     return transcription[0]
 
-def analyze_emotion(text):
-    result = emotion_pipeline(text)
-    return result
-
 def process_frame(frame):
     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
     face_locations = face_recognition.face_locations(gray)