new

app.py

@@ -9,6 +9,10 @@ model = load_model('cats_and_dogs_classifier.h5')
 
 # Define prediction function
 def predict(image):
+    # Ensure the image is a PIL Image object
+    if isinstance(image, np.ndarray):
+        image = Image.fromarray(image)
+    
     # Resize image to match model's expected sizing (150x150 pixels)
     img = image.resize((150, 150))
     # Convert image to array and expand dimensions to fit model input requirements
@@ -23,3 +27,4 @@ def predict(image):
 # Create a Gradio interface
 interface = gr.Interface(fn=predict, inputs="image", outputs="text")
 interface.launch()
+