added separate pipe without ControlNet

app.py

@@ -25,8 +25,8 @@ vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype
 # Scheduler
 eulera_scheduler = EulerAncestralDiscreteScheduler.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", subfolder="scheduler")
 
-# Stable Diffusion Model
-pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
+# Stable Diffusion Model with ControlNet
+pipe_cn = StableDiffusionXLControlNetPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     controlnet=controlnet,
     vae=vae,
@@ -34,6 +34,14 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     scheduler=eulera_scheduler,
 )
 
+# Stable Diffusion Model without ControlNet
+pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    vae=vae,
+    torch_dtype=precision,
+    scheduler=eulera_scheduler,
+)
+
 pipe.to(device)
 
 
@@ -55,7 +63,7 @@ def generate_image(prompt, input_image, low_threshold, high_threshold, strength,
     edge_detected = apply_canny(input_image, low_threshold, high_threshold)
     
     # Generate styled image using ControlNet
-    result = pipe(
+    result = pipe_cn(
         prompt=prompt,
         image=edge_detected,
         num_inference_steps=30,