Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL
+from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler
 import torch
 import numpy as np
 import cv2
@@ -20,11 +20,15 @@ controlnet = ControlNetModel.from_pretrained(
 # when test with other base model, you need to change the vae also.
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=precision)
 
+# Scheduler
+eulera_scheduler = EulerAncestralDiscreteScheduler.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", subfolder="scheduler")
+
 pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
     controlnet=controlnet,
     vae=vae,
     torch_dtype=precision,
+    scheduler=eulera_scheduler,
 ).to(device)
 
 # 📸 Edge detection function using OpenCV (Canny)
@@ -68,7 +72,7 @@ with gr.Blocks() as demo:
             
             strength = gr.Slider(0.1, 1.0, value=0.8, label="Denoising Strength")
             guidance = gr.Slider(1, 20, value=7.5, label="Guidance Scale (Creativity)")
-            controlnet_conditioning_scale = gr.Slider(0, 1, value=0.5, label="ControlNet Conditioning Scale")
+            controlnet_conditioning_scale = gr.Slider(0, 1, value=0.5, step=0.01, label="ControlNet Conditioning Scale")
             
             generate_button = gr.Button("Generate Styled Image")