Update app.py

app.py

@@ -5,15 +5,12 @@ compostable = ["vegetable", "fruit", "food", "leaves"]
 recyclable = ["plastic", "paper", "glass", "metal", "bottle", "can"]
 harmful = ["syringe", "battery", "medical", "chemical"]
 
-def classify_waste(image):
+def classify_waste(image_path):
     """
     Demo classifier based on the uploaded image filename.
-    In a real app, you would use an ML model to classify the image.
+    In a real app, you would use an ML model to classify the image content.
     """
-    # Get filename in lowercase
-    filename = image.name.lower()
-    
-    # Simple filename-based rules for demo
+    filename = image_path.lower()
     if any(word in filename for word in compostable):
         return "✅ Compostable Waste (Green Bin)"
     elif any(word in filename for word in recyclable):
@@ -21,12 +18,12 @@ def classify_waste(image):
     elif any(word in filename for word in harmful):
         return "⚠️ Harmful/Non-Decomposable Waste (Red Bin)"
     else:
-        return "🚮 common Waste (Grey Bin)"
+        return "🚮 General Waste (Grey Bin)"
 
 # Gradio UI
 iface = gr.Interface(
     fn=classify_waste,
-    inputs=gr.Image(type="file", label="Upload a photo of your waste item"),
+    inputs=gr.Image(type="filepath", label="Upload a photo of your waste item"),  # FIXED here
     outputs="text",
     title="♻️ Eco-Friendly Waste Classifier (Image Upload)",
     description="Upload a photo of a waste item and see which bin it belongs to!"
@@ -41,3 +38,5 @@ if __name__ == "__main__":
 
 
 
+
+