try again

app.py

@@ -31,9 +31,6 @@ generator = torch.manual_seed(0)
 # inference function takes prompt, negative prompt and image
 def infer(prompt, negative_prompt, image):
     # implement your inference function here
-    
-    inp = np.copy(image)
-    inp.setflags(write=False)
 
     cond_input = conditioning_image_transforms(image)
     
@@ -45,7 +42,7 @@ def infer(prompt, negative_prompt, image):
         num_inference_steps=20
             )
 
-    return output[0]
+    return output
 
     # you need to pass inputs and outputs according to inference function
 title = "Categorical Conditioning Controlnet for One-Shot Image Stylization."