Update app.py

app.py

@@ -34,7 +34,7 @@ vae = AutoencoderKL.from_pretrained(
 ).to("cuda")
 
 pipe = StableDiffusionXLFillPipeline.from_pretrained(
-    "SG161222/RealVisXL_V5.0_Lightning",
+    "RunDiffusion/Juggernaut-XI-Lightning",
     torch_dtype=torch.float16,
     vae=vae,
     controlnet=model,
@@ -179,14 +179,18 @@ def infer(image, width, height, overlap_percentage, num_inference_steps, resize_
     cnet_image.paste(0, (0, 0), mask)
 
     final_prompt = f"{prompt_input} , high quality, 4k"
+    negative_final_prompt = f"{negative_prompt_input}"
 
     (
         prompt_embeds,
-        negative_prompt_embeds,
         pooled_prompt_embeds,
-        negative_pooled_prompt_embeds,
     ) = pipe.encode_prompt(final_prompt, "cuda", True)
 
+    (
+        negative_prompt_embeds,
+        negative_pooled_prompt_embeds,
+    ) = pipe.encode_prompt(negative_final_prompt, "cuda", True)
+    
     for image in pipe(
         prompt_embeds=prompt_embeds,
         negative_prompt_embeds=negative_prompt_embeds,
@@ -251,13 +255,6 @@ css = """
 
 title = """<h1 align="center">Diffusers Image Outpaint</h1>
 <div align="center">Drop an image you would like to extend, pick your expected ratio and hit Generate.</div>
-<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
-    <p style="display: flex;gap: 6px;">
-         <a href="https://huggingface.co/spaces/fffiloni/diffusers-image-outpout?duplicate=true">
-            <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-md.svg" alt="Duplicate this Space">
-        </a> to skip the queue and enjoy faster inference on the GPU of your choice 
-    </p>
-</div>
 """
 
 with gr.Blocks(css=css) as demo:
@@ -274,6 +271,8 @@ with gr.Blocks(css=css) as demo:
                 with gr.Row():
                     with gr.Column(scale=2):
                         prompt_input = gr.Textbox(label="Prompt (Optional)")
+                    with gr.Column(scale=2):
+                        negative_prompt_input = gr.Textbox(label="Negative Prompt (Optional)")
                     with gr.Column(scale=1):
                         run_button = gr.Button("Generate")
 
@@ -298,23 +297,23 @@ with gr.Blocks(css=css) as demo:
                                 label="Target Width",
                                 minimum=720,
                                 maximum=1536,
-                                step=8,
-                                value=720,  # Set a default value
+                                step=32,
+                                value=1280,  # Set a default value
                             )
                             height_slider = gr.Slider(
                                 label="Target Height",
                                 minimum=720,
                                 maximum=1536,
-                                step=8,
-                                value=1280,  # Set a default value
+                                step=32,
+                                value=720,  # Set a default value
                             )
                         
-                        num_inference_steps = gr.Slider(label="Steps", minimum=4, maximum=12, step=1, value=8)
+                        num_inference_steps = gr.Slider(label="Steps", minimum=4, maximum=20, step=1, value=8)
                         with gr.Group():
                             overlap_percentage = gr.Slider(
                                 label="Mask overlap (%)",
                                 minimum=1,
-                                maximum=50,
+                                maximum=75,
                                 value=10,
                                 step=1
                             )