change styles

app.py

@@ -17,16 +17,6 @@ scheduler = DPMSolverMultistepScheduler(
     lower_order_final=True,
 )
 
-def is_google_colab():
-    try:
-        import google.colab
-        return True
-    except:
-        return False
-
-is_colab = is_google_colab()
-
-
 class Model:
     def __init__(self, name, path, prefix):
         self.name = name
@@ -37,19 +27,9 @@ class Model:
 
 models = [
      Model("Stable-Diffusion-v1.4", "CompVis/stable-diffusion-v1-4", "The 1.4 version of official stable-diffusion"),
-    #  Model("Stable-Diffusion-v1.5", "runwayml/stable-diffusion-v1-5", "The 1.5 version of official stable-diffusion"),
-    #  Model("Arcane", "nitrosocke/Arcane-Diffusion", "arcane style "),
-    #  Model("Archer", "nitrosocke/archer-diffusion", "archer style "),
-    #  Model("Elden Ring", "nitrosocke/elden-ring-diffusion", "elden ring style "),
-    #  Model("Spider-Verse", "nitrosocke/spider-verse-diffusion", "spiderverse style "),
-    #  Model("Modern Disney", "nitrosocke/mo-di-diffusion", "modern disney style "),
-    #  Model("Classic Disney", "nitrosocke/classic-anim-diffusion", "classic disney style "),
-    #  Model("Waifu", "hakurei/waifu-diffusion", ""),
-    #  Model("Pokémon", "lambdalabs/sd-pokemon-diffusers", ""),
-    #  Model("Pony Diffusion", "AstraliteHeart/pony-diffusion", ""),
-    #  Model("Robo Diffusion", "nousr/robo-diffusion", ""),
-    #  Model("Cyberpunk Anime", "DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style "),
-    #  Model("Tron Legacy", "dallinmackay/Tron-Legacy-diffusion", "trnlgcy ")
+     Model("Waifu", "hakurei/waifu-diffusion", "anime style"),
+     Model("Pokémon", "lambdalabs/sd-pokemon-diffusers", "pokemon style"),
+     Model("Modern Disney", "nitrosocke/mo-di-diffusion", "modern disney style"),
 ]
 
 last_mode = "txt2img"
@@ -173,6 +153,7 @@ css = """
       text-align: center;
       max-width: 700px;
       margin: 0 auto;
+      font-family: 'IBM Plex Sans', sans-serif;
     }
     .finetuned-diffusion-div div {
       display: inline-flex;
@@ -182,7 +163,9 @@ css = """
     }
     .finetuned-diffusion-div div h1 {
       font-weight: 900;
-      margin-bottom: 7px;
+      margin-top: 15px;
+      margin-bottom: 15px;
+      text-align: center;
     }
     .finetuned-diffusion-div p {
       margin-bottom: 10px;
@@ -198,6 +181,11 @@ css = """
     #gallery {
       min-height: 20rem;
     }
+    .container {
+      max-width: 1000px;
+      margin: auto;
+      padding-top: 1.5rem;
+    }
   </style>
 """
 with gr.Blocks(css=css) as demo:
@@ -205,29 +193,36 @@ with gr.Blocks(css=css) as demo:
         f"""
             <div class="finetuned-diffusion-div">
               <div>
-                <h1>Finetuned Diffusion with DPM-Solver (fastest sampler for diffusion models) </h1>
+                <h1>Stable-Diffusion with DPM-Solver (fastest sampler for diffusion models) </h1>
               </div>
               <br>
+              <p>
+              Acknowledgement: Hardware resources of this demo are supported by HuggingFace 🤗 . Many thanks for the help!
+              </p>
+              <br>
+              <p>
+               This is a demo of sampling by DPM-Solver with several fine-tuned Stable Diffusion models, trained on different styles: <br>
+               <a href="https://huggingface.co/CompVis/stable-diffusion-v1-4">Stable-Diffusion-v1.4</a>, <a href="https://huggingface.co/nitrosocke/modern-disney-diffusion">Modern Disney</a>, <a href="https://huggingface.co/hakurei/waifu-diffusion">Waifu</a>, <a href="https://huggingface.co/lambdalabs/sd-pokemon-diffusers">Pokémon</a>.
+              </p>
+              <br>
               <p>
                <a href="https://github.com/LuChengTHU/dpm-solver">DPM-Solver</a> (Neurips 2022 Oral) is a fast high-order solver customized for diffusion ODEs, which can generate high-quality samples by diffusion models within only 10-25 steps. DPM-Solver has an analytical formulation and is very easy to use for all types of Gaussian diffusion models, and includes <a href="https://arxiv.org/abs/2010.02502">DDIM</a> as a first-order special case.
               </p>
               <p>
-              We use <a href="https://github.com/huggingface/diffusers">Diffusers</a> to implement this demo, which currently supports the multistep DPM-Solver scheduler. For more details of DPM-Solver with Diffusers, check <a href="https://github.com/huggingface/diffusers/pull/1132">this pull request</a>.
+              We use <a href="https://github.com/huggingface/diffusers">Diffusers</a>  🧨  to implement this demo, which currently supports the multistep DPM-Solver scheduler. For more details of DPM-Solver with Diffusers, check <a href="https://github.com/huggingface/diffusers/pull/1132">this pull request</a>.
               </p>
               <br>
               <p>
-               Demo for sampling by DPM-Solver with several fine-tuned Stable Diffusion models, trained on different styles: <br>
-               <a href="https://huggingface.co/CompVis/stable-diffusion-v1-4">Stable-Diffusion-v1.4</a>, <a href="https://huggingface.co/nitrosocke/elden-ring-diffusion">Elden Ring</a>, <a href="https://huggingface.co/hakurei/waifu-diffusion">Waifu</a>, <a href="https://huggingface.co/lambdalabs/sd-pokemon-diffusers">Pokémon</a>, <a href="https://huggingface.co/AstraliteHeart/pony-diffusion">Pony Diffusion</a>, <a href="https://huggingface.co/nousr/robo-diffusion">Robo Diffusion</a>, <a href="https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion">Cyberpunk Anime</a>, <a href="https://huggingface.co/dallinmackay/Tron-Legacy-diffusion">Tron Legacy</a> + any other custom Diffusers 🧨 SD model hosted on HuggingFace 🤗.
+              Currently, the default sampler of stable-diffusion is <a href="https://arxiv.org/abs/2202.09778">PNDM</a>, which needs 50 steps to generate high-quality samples. However, DPM-Solver can generate high-quality samples within only <span style="font-weight: bold;">20-25</span> steps, and for some samples even within <span style="font-weight: bold;">10-15</span> steps.
+              </p>
+              <br>
+              <p>
+               Running on <b>{device}</b>
               </p>
             </div>
         """
     )
-    # TODO: the colab version is wrong.
-    #     <p>Don't want to wait in queue? <a href="https://colab.research.google.com/gist/qunash/42112fb104509c24fd3aa6d1c11dd6e0/copy-of-fine-tuned-diffusion-gradio.ipynb"><img data-canonical-src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" src="https://camo.githubusercontent.com/84f0493939e0c4de4e6dbe113251b4bfb5353e57134ffd9fcab6b8714514d4d1/68747470733a2f2f636f6c61622e72657365617263682e676f6f676c652e636f6d2f6173736574732f636f6c61622d62616467652e737667"></a></p>
-    #  Running on <b>{device}</b>{(" in a <b>Google Colab</b>." if is_colab else "")}
-    # </p>
 
-    # TODO: do not support the custom model
     with gr.Row():
         
         with gr.Column(scale=55):
@@ -266,30 +261,19 @@ with gr.Blocks(css=css) as demo:
                 strength = gr.Slider(label="Transformation strength", minimum=0, maximum=1, step=0.01, value=0.5)
 
     # model_name.change(lambda x: gr.update(visible = x == models[0].name), inputs=model_name, outputs=custom_model_group)
-    # n_images.change(lambda n: gr.Gallery().style(grid=[2 if n > 1 else 1], height="auto"), inputs=n_images, outputs=gallery)
 
     inputs = [model_name, prompt, guidance, steps, width, height, seed, image, strength, neg_prompt]
     prompt.submit(inference, inputs=inputs, outputs=image_out)
-    generate.click(inference, inputs=inputs, outputs=image_out)
 
+    generate.click(inference, inputs=inputs, outputs=image_out)
 
-# TODO: the docs here are wrong.
-    # ex = gr.Examples([
-    #     [models[1].name, "jason bateman disassembling the demon core", 7.5, 50],
-    #     # [models[1+2].name, "jason bateman disassembling the demon core", 7.5, 50],
-    #     # [models[4+2].name, "portrait of dwayne johnson", 7.0, 75],
-    #     # [models[5+2].name, "portrait of a beautiful alyx vance half life", 10, 50],
-    #     # [models[6+2].name, "Aloy from Horizon: Zero Dawn, half body portrait, smooth, detailed armor, beautiful face, illustration", 7.0, 45],
-    #     # [models[5+2].name, "fantasy portrait painting, digital art", 4.0, 30],
-    # ], [model_name, prompt, guidance, steps, seed], image_out, inference, cache_examples=False)
 
     gr.Markdown('''
-      Models by [@nitrosocke](https://huggingface.co/nitrosocke), [@haruu1367](https://twitter.com/haruu1367), [@Helixngc7293](https://twitter.com/DGSpitzer) and others. Code are copied from [@anzorq's fintuned_diffusion](https://huggingface.co/spaces/anzorq/finetuned_diffusion/tree/main) ❤️<br>
-      Space by: [![Twitter Follow](https://img.shields.io/twitter/follow/ChengLu05671218?label=%40ChengLu&style=social)](https://twitter.com/ChengLu05671218)
+      Models by [@nitrosocke](https://huggingface.co/nitrosocke), [@haruu1367](https://twitter.com/haruu1367), [@Helixngc7293](https://twitter.com/DGSpitzer) and others. Most of the code of this demo are copied from [@anzorq's fintuned-diffusion](https://huggingface.co/spaces/anzorq/finetuned_diffusion/tree/main) ❤️<br>
+      Space by [Cheng Lu](https://github.com/LuChengTHU). [![Twitter Follow](https://img.shields.io/twitter/follow/ChengLu05671218?label=%40ChengLu&style=social)](https://twitter.com/ChengLu05671218)
         
       ![visitors](https://visitor-badge.glitch.me/badge?page_id=LuChengTHU.dpmsolver_sdm)
     ''')
 
-if not is_colab:
-  demo.queue(concurrency_count=1)
-demo.launch(debug=is_colab, share=is_colab)
+demo.queue(concurrency_count=1)
+demo.launch(debug=False, share=False)