Update app.py

app.py

@@ -1,4 +1,12 @@
+
+from __future__ import annotations
+from typing import Iterable
 import gradio as gr
+from gradio.themes.base import Base
+from gradio.themes.utils import colors, fonts, sizes
+
+
+
 import numpy as np
 import random
 import torch
@@ -15,6 +23,48 @@ import os
 
 from huggingface_hub import  hf_hub_download
 
+class Seafoam(Base):
+    def __init__(
+        self,
+        *,
+        primary_hue: colors.Color | str = colors.emerald,
+        secondary_hue: colors.Color | str = colors.blue,
+        neutral_hue: colors.Color | str = colors.gray,
+        spacing_size: sizes.Size | str = sizes.spacing_md,
+        radius_size: sizes.Size | str = sizes.radius_md,
+        text_size: sizes.Size | str = sizes.text_lg,
+        font: fonts.Font
+        | str
+        | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("Quicksand"),
+            "ui-sans-serif",
+            "sans-serif",
+        ),
+        font_mono: fonts.Font
+        | str
+        | Iterable[fonts.Font | str] = (
+            fonts.GoogleFont("IBM Plex Mono"),
+            "ui-monospace",
+            "monospace",
+        ),
+    ):
+        super().__init__(
+            primary_hue=primary_hue,
+            secondary_hue=secondary_hue,
+            neutral_hue=neutral_hue,
+            spacing_size=spacing_size,
+            radius_size=radius_size,
+            text_size=text_size,
+            font=font,
+            font_mono=font_mono,
+        )
+
+seafoam = Seafoam()
+CSS = """
+.fillable { max-width: 960px !important; }
+"""
+
+
 def update_textbox(selected_items):
     # Join the selected list of strings into a comma-separated string
     return ", ".join(selected_items)
@@ -315,10 +365,13 @@ _HEADER_ = '''
 </div>
 
 
-<p style="font-size: 1rem; margin-bottom: 1.5rem;">Paper: <a href='https://witcherofresearch.github.io/TeleStyleV2' target='_blank'>TeleStyle V2: Beyond Content-Preserving Style Transfer with Self-Distillation and Distribution-Matching-Distillation</a> | Codes: <a href='https://github.com/Tele-AI/TeleStyleV2' target='_blank'>GitHub</a>
+<p style="font-size: 1rem; margin-bottom: 1.5rem;">Paper: <a href='https://witcherofresearch.github.io/TeleStyleV2' target='_blank'>PromptRouter: Routing Different Image Customization Tasks via Simple Prompt</a> | Codes: <a href='https://github.com/witcherofresearch/PromptRoute' target='_blank'>GitHub</a>
 </p>
 <p style="font-size: 1rem; margin-bottom: 1.5rem;">Please light a star for the <a href='https://github.com/Tele-AI/TeleStyleV2' target='_blank'>Code</a> if you find the demo useful, thank you.</p>
-<p style="font-size: 1rem; margin-bottom: 1.5rem;">Update: prompt enhancer provided, and the model supports content ref/style ref only input, which means you could use the model as an image editing model and style transfer model at the same time. So you don't have to provide a style reference now, the model also accepts prompt for style transfer, which makes the model more flexible. If you choose infer with content/style prompt, do not forget to clean the prompt box when you run new  inference.</p>
+
+<p style="font-size: 1rem; margin-bottom: 1.5rem;">In this demo, we question whether there exists any conflicts when learning multi-ref subject-driven image generation and content-preserving style transfer given content ref and style ref with a unified model. The conclusion is no and our PromptRoute's solution is simple: we attach "Compose the pictures" for multi-ref subject generation, and "Style Transfer the style of Figure 2 to Figure 1, and keep the content and characteristics of Figure 1." for content-preserving style transfer during training and inference. Such simple prompts distinguish the tasks and eliminate the confusion. </p> 
+
+<p style="font-size: 1rem; margin-bottom: 1.5rem;">Caution: If you choose infer with content/style prompt, pls do not forget to clean the prompt box when you run a new  inference. The results of multi-ref subject generation are all 16:9 in this demo. </p>
 
 <p style="font-size: 1rem; margin-bottom: 1.5rem;">If you encounter an Error with this demo, the most possible reason is ZeroGPU out-of-memory and the solution is to decrease the Min Edge of the generated image from 1024 to a lower value.  </p>
 '''  
@@ -401,6 +454,7 @@ with gr.Blocks() as demo:
                     step=8,
                     value=1024,
                 )
+        """
         with gr.Row(), gr.Column():
             gr.Markdown("## Examples")
             gr.Markdown("changing the minedge could lead to different style similarity.")
@@ -430,13 +484,14 @@ with gr.Blocks() as demo:
                 outputs=[result, seed, content_prompt, style_prompt,prompt], 
                 fn=infer, 
                 cache_examples=False
-                )        
+                )      
                 
                 
                 
                 
 
         # gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=False)
+        """
 
     gr.on(
         triggers=[run_button.click],
@@ -460,7 +515,8 @@ with gr.Blocks() as demo:
     
 
 if __name__ == "__main__":
-    demo.launch(server_name='0.0.0.0')
+    demo.launch(server_name='0.0.0.0',theme=seafoam,
+                css=CSS,)
 '''
 ['./qwenstyleref/pulpfiction_2.jpg','./qwenstyleref/styleref=6_style_ref.png',default_prompt,123,False,1.0,4,1024,[]],
                 ['./qwenstyleref/styleref=0_content_ref.png','./qwenstyleref/110.png',default_prompt,123,False,1.0,4,1024,[]],