fixesss

app.py

@@ -809,7 +809,7 @@ with gr.Blocks(fill_height=True, title="Dressify - Advanced Outfit Recommendatio
         with gr.Row():
             occasion = gr.Dropdown(choices=["casual", "business", "formal", "sport"], value="casual", label="Occasion")
             weather = gr.Dropdown(choices=["any", "hot", "mild", "cold", "rain"], value="any", label="Weather")
-            outfit_style = gr.Dropdown(choices=["casual", "smart_casual", "formal", "sporty"], value="casual", label="Outfit Style")
+            outfit_style = gr.Dropdown(choices=["casual", "smart_casual", "formal", "sporty", "traditional"], value="casual", label="Outfit Style")
         with gr.Row():
             num_outfits = gr.Slider(minimum=1, maximum=8, step=1, value=3, label="Number of outfits")
         out_gallery = gr.Gallery(label="Recommended Outfits", columns=1, height=320)

inference.py

@@ -89,7 +89,7 @@ class InferenceService:
             return "other"
         
         try:
-            # Define clothing categories with descriptions
+            # Define clothing categories with descriptions (including Pakistani traditional wear)
             categories = [
                 "a shirt, t-shirt, blouse, or top",
                 "pants, jeans, trousers, or bottoms", 
@@ -101,7 +101,10 @@ class InferenceService:
                 "a watch, ring, necklace, or jewelry",
                 "a bag, purse, or handbag",
                 "a hat, cap, or headwear",
-                "a belt or accessory"
+                "a belt or accessory",
+                "a kameez, kurta, or traditional Pakistani shirt",
+                "shalwar, traditional Pakistani pants, or loose trousers",
+                "Peshawari chappal, traditional Pakistani sandals, or ethnic footwear"
             ]
             
             # Prepare image and text
@@ -117,7 +120,7 @@ class InferenceService:
                 similarity = (100.0 * image_features @ text_features.T).softmax(dim=-1)
                 values, indices = similarity[0].topk(1)
                 
-                # Map to outfit categories
+                # Map to outfit categories (including Pakistani traditional wear)
                 category_map = {
                     0: "shirt",      # shirt, t-shirt, blouse, top
                     1: "pants",      # pants, jeans, trousers, bottoms
@@ -129,7 +132,10 @@ class InferenceService:
                     7: "accessory",  # watch, ring, necklace, jewelry
                     8: "accessory",  # bag, purse, handbag
                     9: "accessory",  # hat, cap, headwear
-                    10: "accessory"  # belt, accessory
+                    10: "accessory", # belt, accessory
+                    11: "kameez",    # kameez, kurta, traditional Pakistani shirt
+                    12: "shalwar",   # shalwar, traditional Pakistani pants
+                    13: "peshawari"  # Peshawari chappal, traditional Pakistani sandals
                 }
                 
                 predicted_category = category_map.get(indices[0].item(), "other")
@@ -429,17 +435,18 @@ class InferenceService:
             },
             "formal": {
                 "style": "professional, elegant, sophisticated",
-                "preferred_categories": ["blazer", "dress shirt", "dress pant", "oxford", "suit", "shirt", "pants", "shoes"],
+                "preferred_categories": ["blazer", "jacket", "suit jacket", "dress shirt", "dress pant", "oxford", "suit", "shirt", "pants", "shoes"],
                 "color_palette": ["navy", "black", "white", "gray", "charcoal"],
                 "accessory_limit": 4,
+                "requires_outerwear": True,  # Flag to indicate formal outfits should include jackets
                 "weather_modifiers": {
-                    "hot": {"preferred_categories": ["light shirt", "light pant", "oxford"]},
-                    "cold": {"preferred_categories": ["blazer", "suit", "boot"]},
-                    "rain": {"preferred_categories": ["blazer", "boot", "umbrella"]}
+                    "hot": {"preferred_categories": ["light shirt", "light pant", "oxford"], "requires_outerwear": False},
+                    "cold": {"preferred_categories": ["blazer", "suit", "boot"], "requires_outerwear": True},
+                    "rain": {"preferred_categories": ["blazer", "boot", "umbrella"], "requires_outerwear": True}
                 },
                 "occasion_modifiers": {
-                    "business": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 4},
-                    "casual": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 3}
+                    "business": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 4, "requires_outerwear": True},
+                    "casual": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 3, "requires_outerwear": False}
                 }
             },
             "sporty": {
@@ -456,6 +463,23 @@ class InferenceService:
                     "business": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 2},
                     "formal": {"preferred_categories": ["shirt", "pants", "shoes"], "accessory_limit": 3}
                 }
+            },
+            "traditional": {
+                "style": "Pakistani traditional, cultural, ethnic",
+                "preferred_categories": ["kameez", "kurta", "shalwar", "peshawari", "chappal", "traditional", "ethnic"],
+                "color_palette": ["white", "black", "navy", "maroon", "gold", "green", "traditional colors"],
+                "accessory_limit": 3,
+                "requires_traditional": True,  # Flag for traditional outfit combinations
+                "weather_modifiers": {
+                    "hot": {"preferred_categories": ["light kameez", "cotton shalwar", "peshawari chappal"]},
+                    "cold": {"preferred_categories": ["warm kameez", "thick shalwar", "traditional boots"]},
+                    "rain": {"preferred_categories": ["waterproof kameez", "shalwar", "traditional boots"]}
+                },
+                "occasion_modifiers": {
+                    "business": {"preferred_categories": ["formal kameez", "shalwar", "peshawari"], "accessory_limit": 2},
+                    "formal": {"preferred_categories": ["elegant kameez", "shalwar", "peshawari"], "accessory_limit": 3},
+                    "casual": {"preferred_categories": ["casual kameez", "shalwar", "chappal"], "accessory_limit": 2}
+                }
             }
         }
         
@@ -591,15 +615,29 @@ class InferenceService:
                 return "bottom"
             elif cat_lower == "shoes":
                 return "shoe"
+            elif cat_lower == "jacket":
+                return "outerwear"  # Separate category for jackets/blazers
             elif cat_lower == "accessory":
                 return "accessory"
+            elif cat_lower == "kameez":
+                return "upper"  # Kameez is upper body wear
+            elif cat_lower == "shalwar":
+                return "bottom"  # Shalwar is bottom wear
+            elif cat_lower == "peshawari":
+                return "shoe"  # Peshawari chappal is footwear
             
-            # Upper body items (tops, outerwear)
+            # Upper body items (tops, innerwear)
             upper_keywords = [
                 "top", "shirt", "tshirt", "t-shirt", "blouse", "tank", "camisole", "cami",
-                "jacket", "blazer", "coat", "hoodie", "sweater", "pullover", "cardigan",
-                "vest", "waistcoat", "windbreaker", "bomber", "denim jacket", "leather jacket",
-                "polo", "henley", "tunic", "crop top", "bodysuit", "romper", "jumpsuit"
+                "hoodie", "sweater", "pullover", "cardigan", "polo", "henley", "tunic", 
+                "crop top", "bodysuit", "romper", "jumpsuit", "kameez", "kurta", "shalwar kameez"
+            ]
+            
+            # Outerwear items (jackets, coats, blazers)
+            outerwear_keywords = [
+                "jacket", "blazer", "coat", "vest", "waistcoat", "windbreaker", "bomber", 
+                "denim jacket", "leather jacket", "suit jacket", "sport coat", "trench coat",
+                "pea coat", "overcoat", "cardigan", "sweater jacket"
             ]
             
             # Bottom items
@@ -608,7 +646,7 @@ class InferenceService:
                 "skirt", "short", "shorts", "legging", "leggings", "tights",
                 "chino", "khaki", "cargo", "jogger", "sweatpant", "sweatpants",
                 "culotte", "palazzo", "mini skirt", "midi skirt", "maxi skirt",
-                "bermuda", "capri", "bike short", "bike shorts"
+                "bermuda", "capri", "bike short", "bike shorts", "shalwar", "shalwar kameez"
             ]
             
             # Footwear
@@ -617,7 +655,8 @@ class InferenceService:
                 "sandal", "sandals", "flat", "flats", "loafer", "loafers", "oxford",
                 "pump", "pumps", "stiletto", "wedge", "ankle boot", "knee high boot",
                 "combat boot", "hiking boot", "running shoe", "athletic shoe",
-                "mule", "mules", "clog", "clogs", "espadrille", "espadrilles"
+                "mule", "mules", "clog", "clogs", "espadrille", "espadrilles",
+                "peshawari", "chappal", "peshawari chappal", "traditional sandal"
             ]
             
             # Accessories (can have multiple)
@@ -630,7 +669,9 @@ class InferenceService:
             ]
             
             # Check each category
-            if any(k in cat_lower for k in upper_keywords):
+            if any(k in cat_lower for k in outerwear_keywords):
+                return "outerwear"
+            elif any(k in cat_lower for k in upper_keywords):
                 return "upper"
             elif any(k in cat_lower for k in bottom_keywords):
                 return "bottom"
@@ -646,13 +687,14 @@ class InferenceService:
         uppers = [i for i in ids if get_category_type(cat_str(i)) == "upper"]
         bottoms = [i for i in ids if get_category_type(cat_str(i)) == "bottom"]
         shoes = [i for i in ids if get_category_type(cat_str(i)) == "shoe"]
+        outerwear = [i for i in ids if get_category_type(cat_str(i)) == "outerwear"]
         accs = [i for i in ids if get_category_type(cat_str(i)) == "accessory"]
         others = [i for i in ids if get_category_type(cat_str(i)) == "other"]
         
-        print(f"🔍 DEBUG: Category pools - uppers: {len(uppers)}, bottoms: {len(bottoms)}, shoes: {len(shoes)}, accessories: {len(accs)}, others: {len(others)}")
+        print(f"🔍 DEBUG: Category pools - uppers: {len(uppers)}, bottoms: {len(bottoms)}, shoes: {len(shoes)}, outerwear: {len(outerwear)}, accessories: {len(accs)}, others: {len(others)}")
         
         # Check if we have enough items to create outfits
-        total_items = len(uppers) + len(bottoms) + len(shoes) + len(accs) + len(others)
+        total_items = len(uppers) + len(bottoms) + len(shoes) + len(outerwear) + len(accs) + len(others)
         if total_items < 2:
             print(f"🔍 DEBUG: Not enough items to create outfits - total: {total_items}")
             return []
@@ -719,10 +761,39 @@ class InferenceService:
             
             # Strategy 1: Core outfit (shirt + pants + shoes) + accessories
             if strategy == 0 and uppers and bottoms and shoes:
-                # Core outfit: exactly 1 of each required slot
-                subset.append(int(rng.choice(uppers)))
-                subset.append(int(rng.choice(bottoms)))
-                subset.append(int(rng.choice(shoes)))
+                # Special handling for traditional Pakistani outfits: kameez + shalwar + peshawari
+                if outfit_style == "traditional":
+                    # Check for traditional items
+                    traditional_uppers = [i for i in uppers if "kameez" in cat_str(i) or "kurta" in cat_str(i)]
+                    traditional_bottoms = [i for i in bottoms if "shalwar" in cat_str(i)]
+                    traditional_shoes = [i for i in shoes if "peshawari" in cat_str(i) or "chappal" in cat_str(i)]
+                    
+                    if traditional_uppers and traditional_bottoms and traditional_shoes:
+                        # Traditional Pakistani outfit: kameez + shalwar + peshawari
+                        subset.append(int(rng.choice(traditional_uppers)))    # Kameez/Kurta
+                        subset.append(int(rng.choice(traditional_bottoms)))   # Shalwar
+                        subset.append(int(rng.choice(traditional_shoes)))     # Peshawari chappal
+                        print(f"🔍 DEBUG: Generated traditional Pakistani outfit: kameez + shalwar + peshawari")
+                    else:
+                        # Fallback to regular outfit if traditional items not available
+                        subset.append(int(rng.choice(uppers)))
+                        subset.append(int(rng.choice(bottoms)))
+                        subset.append(int(rng.choice(shoes)))
+                        print(f"🔍 DEBUG: Generated regular outfit (traditional items not available)")
+                
+                # Special handling for formal outfits: require jacket + shirt + pants + shoes
+                elif occasion == "formal" and outerwear and len(outerwear) > 0:
+                    # Formal 3-piece suit: jacket + shirt + pants + shoes
+                    subset.append(int(rng.choice(outerwear)))  # Jacket/blazer
+                    subset.append(int(rng.choice(uppers)))     # Shirt
+                    subset.append(int(rng.choice(bottoms)))    # Pants
+                    subset.append(int(rng.choice(shoes)))      # Shoes
+                    print(f"🔍 DEBUG: Generated formal 3-piece suit with jacket")
+                else:
+                    # Regular core outfit: shirt + pants + shoes
+                    subset.append(int(rng.choice(uppers)))
+                    subset.append(int(rng.choice(bottoms)))
+                    subset.append(int(rng.choice(shoes)))
                 
                 # Prioritize accessories - higher chance of including them
                 remaining_slots = outfit_length - len(subset)
@@ -851,6 +922,10 @@ class InferenceService:
             if category_counts.get("shoe", 0) == 0:
                 penalty += -1000.0
             
+            # Special penalty for formal outfits missing outerwear
+            if occasion == "formal" and category_counts.get("outerwear", 0) == 0:
+                penalty += -500.0  # Strong penalty but not -∞ for formal without jacket
+            
             # Duplicate non-accessory categories: -∞ penalty
             for cat, count in category_counts.items():
                 if cat != "accessory" and count > 1:
@@ -884,6 +959,18 @@ class InferenceService:
             if "accessory" in categories:
                 bonus += 0.3  # Bonus for including accessories
             
+            # Formal outfit bonus for including outerwear
+            if occasion == "formal" and "outerwear" in categories:
+                bonus += 0.5  # Strong bonus for formal outfits with jackets
+            
+            # Traditional Pakistani outfit bonus
+            if outfit_style == "traditional":
+                traditional_items = [cat for cat in categories if any(traditional in cat.lower() for traditional in ["kameez", "kurta", "shalwar", "peshawari", "chappal"])]
+                if len(traditional_items) >= 2:  # At least 2 traditional items
+                    bonus += 0.6  # Strong bonus for traditional outfit combinations
+                if len(traditional_items) == 3:  # Complete traditional set
+                    bonus += 0.3  # Additional bonus for complete traditional outfit
+            
             return base_score + penalty + bonus
         
         # Score and filter valid outfits with penalty adjustment