Update app.py

app.py

@@ -3,8 +3,8 @@ import tensorflow as tf
 from tensorflow.keras.preprocessing import image
 import numpy as np
 
-# Load your trained model (SavedModel format)
-model = tf.keras.models.load_model("waste_sort_model")  # Loading from SavedModel directory
+# Use TFSMLayer to load the SavedModel
+model = tf.keras.layers.experimental.preprocessing.TFSMLayer("waste_sort_model", call_endpoint="serving_default")
 class_names = ["Non-Recyclable", "Recyclable"]
 
 def classify_image(img):
@@ -13,7 +13,7 @@ def classify_image(img):
     img_array = np.array(img) / 255.0  # Normalize pixel values
     img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension
 
-    predictions = model.predict(img_array)
+    predictions = model(img_array)
     predicted_class = class_names[np.argmax(predictions)]
     return f"Prediction: {predicted_class}"
 
@@ -28,5 +28,4 @@ interface = gr.Interface(
 
 # Launch the Gradio app
 if __name__ == "__main__":
-    interface.launch()
-
+    interface.launch(share=True)