Update app.py

app.py

@@ -319,13 +319,28 @@ def analyze_outfit(input_img):
         percentage_score = max(0, final_score * 100)
         percentage_score_str = f"{percentage_score:.0f}%"""
 
-        final_score = max(drip_score, mid_score, not_score)
-        percentage_score = final_score * 100
+        # Calculate average probabilities for each category
+        drip_score = np.mean(all_probs[0 : drip_len])
+        mid_score = np.mean(all_probs[drip_len : drip_len + mid_len])
+        not_score = np.mean(all_probs[drip_len + mid_len : style_prompts_end_index])
+        
+        # Use the raw probabilities to compute weighted score
+        # You can think of this like a 100-point rubric
+        # Drip contributes 100%, Mid contributes 66%, Trash contributes 33%
+        final_score = (
+            drip_score * 100 +
+            mid_score * 66 +
+            not_score * 33
+        )
         
-        if percentage_score >= 75:
+        # Clip the score between 0 and 100 for safety
+        final_score = min(max(final_score, 0), 100)
+        
+        # Assign category based on final_score ranges
+        if final_score >= 75:
             category_key = 'drippy'
             score_label = "Drip Score"
-        elif percentage_score >= 40:
+        elif final_score >= 40:
             category_key = 'mid'
             score_label = "Mid Score"
         else:
@@ -333,7 +348,8 @@ def analyze_outfit(input_img):
             score_label = "Trash Score"
         
         category_label = CATEGORY_LABEL_MAP[category_key]
-        percentage_score_str = f"{percentage_score:.0f}%"
+        percentage_score_str = f"{final_score:.0f}%"
+
 
       
         print(f"Style analysis: Category={category_label}, Score = {score_label}={percentage_score_str} (Raw Score: {final_score:.4f})")