Update app.py

app.py

@@ -10,19 +10,17 @@ pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=torc
 
 # Define the inference function
 def ghibli_transform(input_image, prompt="ghibli style", strength=0.75, guidance_scale=7.5):
-    # Debug: Check input type and value
+    print(f"Input received: {input_image is not None}")
     print(f"Input type: {type(input_image)}")
     if input_image is None:
         raise gr.Error("Please upload an image before clicking Transform!")
     
-    # Since input is now PIL, just resize and ensure RGB
     try:
         init_image = input_image.resize((768, 768)).convert("RGB")
         print(f"Converted to PIL Image: {type(init_image)}")
     except Exception as e:
         raise gr.Error(f"Failed to process image: {str(e)}")
     
-    # Generate the Ghibli-style image
     try:
         output = pipe(
             prompt=prompt,