update: new output and text

app.py

@@ -19,15 +19,23 @@ def predict(img):
     
     pred_sentiment, pred_sentiment_idx, probs_sentiment = learn_sentiment.predict(img)
     
-    emotions = {f'emotion_{learn_emotion_labels[i]}': float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
-    sentiments = {f'sentiment_{learn_sentiment_labels[i]}': float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
+    #emotions = {f'emotion_{learn_emotion_labels[i]}': float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
+    #sentiments = {f'sentiment_{learn_sentiment_labels[i]}': float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
+    
+    emotions = {learn_emotion_labels[i]: float(probs_emotion[i]) for i in range(len(learn_emotion_labels))}
+    sentiments = {learn_sentiment_labels[i]: float(probs_sentiment[i]) for i in range(len(learn_sentiment_labels))}
         
-    return {**emotions, **sentiments}
+    return [emotions, sentiments] #{**emotions, **sentiments}
 
 # Gradio
 title = "Facial Expression Sentiment Classifier"
-description = "A model to detect emotion and sentiment from facial expressions trained on FER2013 dataset using FastAi. Created as a demo for AI Course."
-article = 'Sample images are taken from VG & AftenPoften webpages. Copyrights belong to respective brands. All rights reserved.'
+description = "Ever wondered what a person might be feeling looking at their picture? Well, now you can! Try this fun " + \
+              "app - just upload a facial image in jpg or png format. Voila! you can now see what they might have felt when the " + \
+              "picture was taken. Be sure to only include face to get best results. Check some sample images at the bottom for " + \
+              "inspiration!"
+article = "DISCLAIMER: This model does not reveal the actual emotional state of a person. Use and interpret results at your own risk! " + \
+          "It was built as a demo for AI course. The model is trained on FER2013 dataset using FastAI. Sample images are taken " + \
+          "from VG & AftenPoften webpages. Copyrights belong to respective brands. All rights reserved."
 interpretation='default'
 enable_queue=True
 
@@ -35,7 +43,7 @@ examples = ['happy1.jpg', 'happy2.jpg', 'angry1.png', 'angry2.jpg', 'neutral1.jp
 
 gr.Interface(fn = predict, 
              inputs = gr.Image(shape=(48, 48), image_mode='L'), 
-             outputs = gr.Label(),
+             outputs = [gr.Label(label='Emotion'), gr.Label(label='Sentiment')], #gr.Label(),
              title = title,
              examples = examples,
              description = description,