Update app.py

app.py

@@ -4,8 +4,8 @@ from tensorflow.keras.preprocessing.image import img_to_array
 import numpy as np
 from PIL import Image
 
-# Load the trained model
-model = load_model("waste_classification(Mobilenetv2).h5")
+# Load model
+model = load_model("waste_classifier_model.h5")
 class_names = ['cardboard', 'glass', 'metal', 'paper', 'plastic', 'trash']
 
 # Prediction function
@@ -20,12 +20,11 @@ def predict_from_webcam(image):
 
     return f"{predicted_class} ({confidence*100:.1f}%)"
 
-# Gradio interface with webcam input
+# Use gr.Camera() for webcam input (Gradio 4.x)
 gr.Interface(
     fn=predict_from_webcam,
-    inputs=gr.Image(source="webcam", tool=None, type="pil"),
+    inputs=gr.Camera(type="pil"),  # webcam input as PIL image
     outputs="text",
-    live=True,
     title="Live Waste Classifier",
-    description="Show waste to your webcam. This app predicts if it's paper, glass, plastic, etc."
+    description="Point your webcam at waste material. The model will classify it live."
 ).launch()