Update app.py

app.py

@@ -27,27 +27,28 @@ def predict(img):
 title = "Facial Emotion Detector"
 
 description = gr.Markdown(
-                """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. You can now see what they might have felt when the picture
-                 was taken.
+    """Ever wondered what a person might be feeling just by looking at their picture? 
+    Well, get ready to unleash your inner psychic with this hilarious app! 
+    Simply upload a close-up facial image in JPG or PNG format, and brace yourself for the laugh riot. 
+    Our emotion detector will take one look at their face and reveal what they might have felt 
+    when the picture was taken. 
 
-                 **Tip**: Be sure to only include face to get best results. Check some sample images
-                 below for inspiration!""").value
+    **Pro Tip**: For best results, make sure only their face is in the picture. 
+    It's like reading their mind, but with pixels! 😄
 
-article = gr.Markdown(
-             """**DISCLAIMER:** This model does not reveal the actual emotional state of a person. Use and
-             interpret results at your own risk!. 
+    And hey, if you're feeling a bit down, this app is sure to turn that frown upside down!""").value
 
-             **PREMISE:** The idea is to determine an overall emotion of a person
-             based on the pictures. We are restricting pictures to only include close-up facial
-             images.
+article = gr.Markdown(
+    """**DISCLAIMER:** This app isn't powered by actual mind-reading technology! 
+    So, take the results with a grain of salt, or better yet, a pinch of laughter! 
 
-             **DATA:** FER2013 dataset consists of 48x48 pixel grayscale images of faces.Images
-             are assigned one of the 7 emotions: Angry, Disgust, Fear, Happy, Sad, Surprise, and Neutral.
-             
-              """).value
+    **FUN FACT:** Our facial emotion detector was trained on a bunch of wacky pictures 
+    from the FER2013 dataset. It's not perfect, but it'll give you a good chuckle! 
 
+    **DATA JOKES:** Did you know the FER2013 dataset consists of 48x48 pixel grayscale images of faces? 
+    We're talking emotions captured in a tiny pixel universe! 
+    It's like trying to decipher emotions from a microcosm of hilarity! 🧐
+    """).value
 enable_queue=True
 
 examples = ["happy1.jpg","happy2.jpeg","netural.jpg","sad.jpeg","surprise.jpeg"]