Update app.py

app.py

@@ -13,18 +13,27 @@ def ghibli_transform(input_image, prompt="ghibli style", strength=0.75, guidance
     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!")
+        raise gr.Error("No image uploaded! Please upload an image before clicking Transform.")
     
+    # Process the input image
     try:
+        print(f"Input size: {input_image.size}, mode: {input_image.mode}")
         init_image = input_image.resize((768, 768)).convert("RGB")
-        print(f"Converted to PIL Image: {type(init_image)}")
+        print(f"Converted init_image size: {init_image.size}, mode: {init_image.mode}")
+    except AttributeError as e:
+        raise gr.Error(f"Input is not a valid image: {str(e)}")
     except Exception as e:
         raise gr.Error(f"Failed to process image: {str(e)}")
     
+    # Convert to NumPy array as a workaround
+    init_image_np = np.array(init_image)
+    print(f"Converted to NumPy: {type(init_image_np)}, shape: {init_image_np.shape}")
+    
+    # Generate the Ghibli-style image
     try:
         output = pipe(
             prompt=prompt,
-            init_image=init_image,
+            init_image=init_image_np,  # Pass NumPy array instead
             strength=strength,
             guidance_scale=guidance_scale,
             num_inference_steps=50
@@ -42,7 +51,7 @@ with gr.Blocks(title="Ghibli Diffusion Image Transformer") as demo:
     
     with gr.Row():
         with gr.Column():
-            input_img = gr.Image(label="Upload Image", type="pil")  # Changed to "pil"
+            input_img = gr.Image(label="Upload Image", type="pil")
             prompt = gr.Textbox(label="Prompt", value="ghibli style")
             strength = gr.Slider(0, 1, value=0.75, step=0.05, label="Strength (How much to transform)")
             guidance = gr.Slider(1, 20, value=7.5, step=0.5, label="Guidance Scale")