Update app.py

app.py

@@ -11,6 +11,7 @@ controlnet = ControlNetModel.from_pretrained(
     "briaai/ControlNet-Canny",
     torch_dtype=torch.float16
 )
+# force_zeros_for_empty_prompt=False
 
 pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     "briaai/BRIA-2.0",
@@ -52,17 +53,11 @@ def process(input_image, prompt, negative_prompt, num_steps, controlnet_conditio
     canny_image = get_canny_filter(input_image)
 
     pipe.enable_freeu(b1=1.1, b2=1.1, s1=0.5, s2=0.7)
-
-    if negative_prompt != '':    
-        images = pipe(
-            prompt, negative_prompt=negative_prompt, image=canny_image, num_inference_steps=num_steps, controlnet_conditioning_scale=float(controlnet_conditioning_scale),
-            generator=generator,
-            ).images
-    else:
-        images = pipe(
-            prompt, force_zeros_for_empty_prompt=False, image=canny_image, num_inference_steps=num_steps, controlnet_conditioning_scale=float(controlnet_conditioning_scale),
-            generator=generator,
-            ).images
+  
+    images = pipe(
+        prompt, negative_prompt=negative_prompt, image=canny_image, num_inference_steps=num_steps, controlnet_conditioning_scale=float(controlnet_conditioning_scale),
+        generator=generator,
+        ).images
 
     return [canny_image,images[0]]