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app.py

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+
+from email import generator
+from diffusers import StableDiffusionPipeline
+from diffusers import StableDiffusionImg2ImgPipeline
+import gradio as gr
+import torch
+
+models = [
+  "nitrosocke/Arcane-Diffusion",
+  "nitrosocke/archer-diffusion",
+  "nitrosocke/elden-ring-diffusion",
+  "nitrosocke/spider-verse-diffusion",
+  "nitrosocke/modern-disney-diffusion",
+  "hakurei/waifu-diffusion",
+  "lambdalabs/sd-pokemon-diffusers",
+  "yuk/fuyuko-waifu-diffusion",
+  "AstraliteHeart/pony-diffusion",
+  "IfanSnek/JohnDiffusion",
+  "nousr/robo-diffusion",
+  "DGSpitzer/Cyberpunk-Anime-Diffusion"
+]
+
+prompt_prefixes = {
+  models[0]: "arcane style ",
+  models[1]: "archer style ",
+  models[2]: "elden ring style ",
+  models[3]: "spiderverse style ",
+  models[4]: "modern disney style ",
+  models[5]: "",
+  models[6]: "",
+  models[7]: "",
+  models[8]: "",
+  models[9]: "",
+  models[10]: "",
+  models[11]: "dgs illustration style ",
+}
+
+current_model = models[0]
+pipe = StableDiffusionPipeline.from_pretrained(current_model, torch_dtype=torch.float16)
+if torch.cuda.is_available():
+  pipe = pipe.to("cuda")
+
+device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶"
+
+def inference(model, img, strength, prompt, guidance, steps, seed):
+
+  generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
+  
+  if img is not None:
+    return img_inference(model, prompt, img, strength, guidance, steps, generator)
+  else:
+    return text_inference(model, prompt, guidance, steps, generator)
+
+def text_inference(model, prompt, guidance, steps, generator=None):
+
+    global current_model
+    global pipe
+    if model != current_model:
+        current_model = model
+        pipe = StableDiffusionPipeline.from_pretrained(current_model, torch_dtype=torch.float16)
+        
+        if torch.cuda.is_available():
+            pipe = pipe.to("cuda")
+
+    prompt = prompt_prefixes[current_model] + prompt
+    image = pipe(
+      prompt,
+      num_inference_steps=int(steps),
+      guidance_scale=guidance,
+      width=512,
+      height=512,
+      generator=generator).images[0]
+    return image
+
+def img_inference(model, prompt, img, strength, guidance, steps, generator):
+
+    global current_model
+    global pipe
+    if model != current_model:
+        current_model = model
+        pipe = StableDiffusionImg2ImgPipeline.from_pretrained(current_model, torch_dtype=torch.float16)
+        
+        if torch.cuda.is_available():
+            pipe = pipe.to("cuda")
+
+    prompt = prompt_prefixes[current_model] + prompt
+    img.resize((512, 512))
+    image = pipe(
+        prompt,
+        init_image=img,
+        num_inference_steps=int(steps),
+        strength=strength,
+        guidance_scale=guidance,
+        width=512,
+        height=512,
+        generator=generator).images[0]
+    return image
+
+
+css = """
+  <style>
+  .finetuned-diffusion-div {
+      text-align: center;
+      max-width: 700px;
+      margin: 0 auto;
+    }
+    .finetuned-diffusion-div div {
+      display: inline-flex;
+      align-items: center;
+      gap: 0.8rem;
+      font-size: 1.75rem;
+    }
+    .finetuned-diffusion-div div h1 {
+      font-weight: 900;
+      margin-bottom: 7px;
+    }
+    .finetuned-diffusion-div p {
+      margin-bottom: 10px;
+      font-size: 94%;
+    }
+    .finetuned-diffusion-div p a {
+      text-decoration: underline;
+    }
+  </style>
+"""
+with gr.Blocks(css=css) as demo:
+    gr.HTML(
+        """
+            <div class="finetuned-diffusion-div">
+              <div>
+                <h1>Finetuned Diffusion</h1>
+              </div>
+              <p>
+               Demo for multiple fine-tuned Stable Diffusion models, trained on different styles: <br>
+               <a href="https://huggingface.co/nitrosocke/Arcane-Diffusion">Arcane</a>, <a href="https://huggingface.co/nitrosocke/archer-diffusion">Archer</a>, <a href="https://huggingface.co/nitrosocke/elden-ring-diffusion">Elden Ring</a>, <a href="https://huggingface.co/nitrosocke/spider-verse-diffusion">Spiderverse</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">Pokemon</a>, <a href="https://huggingface.co/yuk/fuyuko-waifu-diffusion">Fuyuko Waifu</a>, <a href="https://huggingface.co/AstraliteHeart/pony-diffusion">Pony</a>, <a href="https://huggingface.co/IfanSnek/JohnDiffusion">John</a>, <a href="https://huggingface.co/nousr/robo-diffusion">Robo</a>, <a href="https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion">Cyberpunk Anime</a>
+              </p>
+            </div>
+        """
+    )
+    with gr.Row():
+        
+        with gr.Column():
+
+            model = gr.Dropdown(label="Model", choices=models, value=models[0])
+            prompt = gr.Textbox(label="Prompt", placeholder="Style prefix is applied automatically")
+            with gr.Accordion("Image to image (optional)", open=False):
+              image = gr.Image(label="Image", height=256, tool="editor", type="pil")
+              strength = gr.Slider(label="Strength", minimum=0, maximum=1, step=0.01, value=0.75)
+            
+            with gr.Accordion("Advanced options", open=False):
+              guidance = gr.Slider(label="Guidance scale", value=7.5, maximum=15)
+              steps = gr.Slider(label="Steps", value=50, maximum=100, minimum=2)
+              seed = gr.Slider(0, 2147483647, label='Seed (0 = random)', value=0, step=1)
+
+            run = gr.Button(value="Run")
+            gr.Markdown(f"Running on: {device}")
+        with gr.Column():
+            image_out = gr.Image(height=512)
+
+    prompt.submit(inference, inputs=[model, image, strength, prompt, guidance, steps, seed], outputs=image_out)
+    run.click(inference, inputs=[model, image, strength, prompt, guidance, steps, seed], outputs=image_out)
+    gr.Examples([
+        [models[0], "jason bateman disassembling the demon core", 7.5, 50],
+        [models[3], "portrait of dwayne johnson", 7.0, 75],
+        [models[4], "portrait of a beautiful alyx vance half life", 10, 50],
+        [models[5], "Aloy from Horizon: Zero Dawn, half body portrait, smooth, detailed armor, beautiful face, illustration", 7, 45],
+        [models[4], "fantasy portrait painting, digital art", 4, 30],
+    ], [model, prompt, guidance, steps], image_out, text_inference, cache_examples=torch.cuda.is_available())
+    gr.Markdown('''
+      Models by [@nitrosocke](https://huggingface.co/nitrosocke), [@Helixngc7293](https://twitter.com/DGSpitzer) and others. ❤️<br>
+      Space by: [![Twitter Follow](https://img.shields.io/twitter/follow/hahahahohohe?label=%40anzorq&style=social)](https://twitter.com/hahahahohohe)
+  
+      ![visitors](https://visitor-badge.glitch.me/badge?page_id=anzorq.finetuned_diffusion)
+    ''')
+
+demo.queue()
+demo.launch(share = True)

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+torchvision==0.13.1+cu113
+diffusers==0.14.0
+#git+https://github.com/huggingface/diffusers.git
+transformers==4.28.1
+#git+https://github.com/huggingface/transformers
+scipy
+ftfy
+psutil
+accelerate==0.12.0
+#OmegaConf
+#pytorch_lightning
+#triton==2.0.0.dev20220701
+triton
+#https://github.com/apolinario/xformers/releases/download/0.0.3/xformers-0.0.14.dev0-cp38-cp38-linux_x86_64.whl
+https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+4c06c79.d20221205-cp38-cp38-linux_x86_64.whl