Update app.py

app.py

@@ -90,34 +90,26 @@ def transform_my_model(content_image, style_image):
         logger.error(f"Error in transform_my_model: {str(e)}")
         raise
 
-# Verify example images exist
-example_images = [
-    ["Content_Images/contnt12.jpg", "VG516.jpg"],
-    ["Content_Images/contnt2.jpg", "Content_Images/styl9.jpg"],
-    ["Content_Images/contnt.jpg", "Content_Images/styl22.jpg"]
-]
-
-valid_examples = []
-for content_path, style_path in example_images:
-    if os.path.exists(content_path) and os.path.exists(style_path):
-        valid_examples.append([content_path, style_path])
-    else:
-        logger.warning(f"Example image not found: {content_path} or {style_path}")
+# Create examples directory if it doesn't exist
+os.makedirs("examples", exist_ok=True)
 
+# Create the Gradio interface with minimal configuration
 demo = gr.Interface(
     fn=transform_my_model,
-    inputs=[gr.Image(label="Content Image"), gr.Image(label="Style Image")],
-    outputs=gr.Image(label="Result"),
+    inputs=[
+        gr.Image(type="numpy", label="Content Image"),
+        gr.Image(type="numpy", label="Style Image")
+    ],
+    outputs=gr.Image(type="pil", label="Result"),
     title="Neural Style Transfer",
     description="Upload a content image and a style image to create a stylized version of your content image.",
-    examples=valid_examples if valid_examples else None,
-    article="References-\n\nExploring the structure of a real-time, arbitrary neural artistic stylization network. Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin."
+    examples=None,  # Disable examples to avoid API issues
+    allow_flagging="never"  # Disable flagging to avoid API issues
 )
 
 if __name__ == "__main__":
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=True,
-        show_error=True
+        share=True
     )