Update app.py

app.py

@@ -95,19 +95,34 @@ def load_food_data(csv_filepath='food_carb_data1 - food_carb_data1 (1) (1).csv')
 # -------------------------------------------------
 # Load Food Classification Model
 # -------------------------------------------------
-processor = AutoImageProcessor.from_pretrained("therealcyberlord/vit-indian-food")
-model = AutoModelForImageClassification.from_pretrained("therealcyberlord/vit-indian-food")
+try:
+    processor = AutoImageProcessor.from_pretrained(
+        "therealcyberlord/vit-indian-food"
+    )
+
+    model = AutoModelForImageClassification.from_pretrained(
+        "therealcyberlord/vit-indian-food",
+        torch_dtype=torch.float16,
+        device_map="auto",
+        low_cpu_mem_usage=True
+    )
+except Exception as e:
+    print("Error loading model")
 
 def classify_food(image):
     """Classify food image using the pre-trained model"""
-    if isinstance(image, np.ndarray):
-        image = Image.fromarray(image)
-    image = processor(images=image, return_tensors="pt")
-    with torch.no_grad():
-        outputs = model(**image)
-    predicted_idx = torch.argmax(outputs.logits, dim=-1).item()
-    food_name = model.config.id2label.get(predicted_idx, "Unknown Food")
-    return food_name.lower() #Convert classification to lowercase
+    try:
+        if isinstance(image, np.ndarray):
+            image = Image.fromarray(image)
+        image = processor(images=image, return_tensors="pt")
+        with torch.no_grad():
+            outputs = model(**image)
+        predicted_idx = torch.argmax(outputs.logits, dim=-1).item()
+        food_name = model.config.id2label.get(predicted_idx, "Unknown Food")
+        return food_name.lower() #Convert classification to lowercase
+    except Exception as e:
+      print("Could not classify_food", str(e))
+      return "Unknown"
 
 # -------------------------------------------------
 # USDA API Integration - REMOVED for local HF Spaces deployment