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 image']
+                      f'a beautiful {gender}', f'an alluring {gender}', 'a photorealistic/completely-unedited image']
     negative_terms = [f'a gross {gender}',
-                      f'an ugly {gender}', f'a hideous {gender}', 'an unrealistic image']
+                      f'an ugly {gender}', f'a hideous {gender}', 'an unrealistic/heavily-edited image']
 
     pairs = list(zip(positive_terms, negative_terms))
 
@@ -41,7 +41,16 @@ def allure(image, gender):
     ugly_score = sum(negative_probs[:-1])/len(negative_probs[:-1])
     composite = ((hot_score - ugly_score)+1) * 50
     composite = round(composite, 2)
-    return composite, hotness_score, beauty_score, attractiveness_score, authenticity_score
+
+    judgement = "extremely toonish or altered"
+    if authenticity_score > 80:
+        judgement = "likely real"
+    elif authenticity_score > 70:
+        judgement = "moderately altered"
+    elif authenticity_score > 50:
+        judgement = "toonish or very altered"
+    
+    return composite, hotness_score, beauty_score, attractiveness_score, f"{authenticity_score} ({judgement})"
 
 
 theme = gr.themes.Soft(
@@ -83,7 +92,7 @@ with gr.Interface(
         gr.Textbox(label="Hotness (%)"),
         gr.Textbox(label="Beauty (%)"),
         gr.Textbox(label="Allure (%)"),
-        gr.Textbox(label="Authenticity (> 80% → likely real)"),
+        gr.Textbox(label="Authenticity (≥ 80% → likely real)"),
     ],
     examples=[
         ['Mansib_01_x2048.png', 'Man'],