Updated metrics

app.py

@@ -12,9 +12,9 @@ def allure(image, gender):
     gender = gender.lower()
     image = preprocess(image).unsqueeze(0).to(device)
     positive_terms = [f'a hot {gender}',
-                      f'a beautiful {gender}', f'an alluring {gender}', 'a photorealistic/completely-unedited image']
+                      f'a beautiful {gender}', f'an alluring {gender}', 'a photorealistic image']
     negative_terms = [f'a gross {gender}',
-                      f'an ugly {gender}', f'a hideous {gender}', 'an unrealistic/heavily-edited image']
+                      f'an ugly {gender}', f'a hideous {gender}', 'a photoshopped image']
 
     pairs = list(zip(positive_terms, negative_terms))
 
@@ -105,7 +105,7 @@ with gr.Interface(
         gr.Markdown(
             """The input image is passed to OpenAI's CLIP image captioning model and evaluated for how much it conforms to the model's idea of hotness, beauty, and attractiveness. 
 These values are then combined to produce a composite score on a scale of 0 to 100.
-# ⚠️ WARNING: This is meant solely for educational use.""")
+# ⚠️ WARNING: This is meant solely for educational use!""")
 
 iface.queue()  # Add `api_open = False` to disable direct API access.
 iface.launch()