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LuChengTHU
commited on
Commit
β’
794bf46
1
Parent(s):
08b6795
add dpmsolver
Browse files- app.py +286 -0
- nsfw.png +0 -0
- requirements.txt +6 -0
app.py
ADDED
@@ -0,0 +1,286 @@
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1 |
+
from diffusers import AutoencoderKL, UNet2DConditionModel, StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, DPMSolverMultistepScheduler
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+
import gradio as gr
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3 |
+
import torch
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from PIL import Image
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+
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scheduler = DPMSolverMultistepScheduler(
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beta_start=0.00085,
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beta_end=0.012,
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beta_schedule="scaled_linear",
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num_train_timesteps=1000,
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+
trained_betas=None,
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predict_epsilon=True,
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thresholding=False,
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algorithm_type="dpmsolver++",
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+
solver_type="midpoint",
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lower_order_final=True,
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+
)
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+
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+
def is_google_colab():
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try:
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import google.colab
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return True
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except:
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return False
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is_colab = is_google_colab()
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+
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+
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class Model:
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def __init__(self, name, path, prefix):
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self.name = name
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self.path = path
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self.prefix = prefix
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self.pipe_t2i = None
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self.pipe_i2i = None
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+
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models = [
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+
Model("Custom model", "", ""),
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+
Model("Stable-Diffusion-v1.4", "runwayml/stable-diffusion-v1-4", "The 1.4 version of official stable-diffusion"),
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+
Model("Stable-Diffusion-v1.5", "runwayml/stable-diffusion-v1-5", "The 1.5 version of official stable-diffusion"),
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+
Model("Arcane", "nitrosocke/Arcane-Diffusion", "arcane style "),
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+
Model("Archer", "nitrosocke/archer-diffusion", "archer style "),
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+
Model("Elden Ring", "nitrosocke/elden-ring-diffusion", "elden ring style "),
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+
Model("Spider-Verse", "nitrosocke/spider-verse-diffusion", "spiderverse style "),
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Model("Modern Disney", "nitrosocke/mo-di-diffusion", "modern disney style "),
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+
Model("Classic Disney", "nitrosocke/classic-anim-diffusion", "classic disney style "),
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+
Model("Waifu", "hakurei/waifu-diffusion", ""),
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+
Model("PokΓ©mon", "lambdalabs/sd-pokemon-diffusers", ""),
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+
Model("Pony Diffusion", "AstraliteHeart/pony-diffusion", ""),
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Model("Robo Diffusion", "nousr/robo-diffusion", ""),
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+
Model("Cyberpunk Anime", "DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style "),
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Model("Tron Legacy", "dallinmackay/Tron-Legacy-diffusion", "trnlgcy ")
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]
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+
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last_mode = "txt2img"
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current_model = models[1]
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current_model_path = current_model.path
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58 |
+
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if is_colab:
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pipe = StableDiffusionPipeline.from_pretrained(current_model.path, torch_dtype=torch.float16, scheduler=scheduler)
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+
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else: # download all models
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vae = AutoencoderKL.from_pretrained(current_model.path, subfolder="vae", torch_dtype=torch.float16)
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for model in models[1:]:
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try:
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unet = UNet2DConditionModel.from_pretrained(model.path, subfolder="unet", torch_dtype=torch.float16)
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model.pipe_t2i = StableDiffusionPipeline.from_pretrained(model.path, unet=unet, vae=vae, torch_dtype=torch.float16, scheduler=scheduler)
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model.pipe_i2i = StableDiffusionImg2ImgPipeline.from_pretrained(model.path, unet=unet, vae=vae, torch_dtype=torch.float16, scheduler=scheduler)
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except:
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models.remove(model)
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pipe = models[1].pipe_t2i
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if torch.cuda.is_available():
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pipe = pipe.to("cuda")
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device = "GPU π₯" if torch.cuda.is_available() else "CPU π₯Ά"
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+
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def custom_model_changed(path):
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models[0].path = path
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global current_model
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current_model = models[0]
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def inference(model_name, prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, neg_prompt=""):
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global current_model
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for model in models:
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if model.name == model_name:
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current_model = model
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model_path = current_model.path
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generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
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if img is not None:
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return img_to_img(model_path, prompt, neg_prompt, img, strength, guidance, steps, width, height, generator)
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else:
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return txt_to_img(model_path, prompt, neg_prompt, guidance, steps, width, height, generator)
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def txt_to_img(model_path, prompt, neg_prompt, guidance, steps, width, height, generator=None):
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global last_mode
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global pipe
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global current_model_path
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if model_path != current_model_path or last_mode != "txt2img":
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current_model_path = model_path
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if is_colab or current_model == models[0]:
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pipe = StableDiffusionPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16)
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108 |
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else:
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pipe.to("cpu")
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pipe = current_model.pipe_t2i
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+
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if torch.cuda.is_available():
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pipe = pipe.to("cuda")
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last_mode = "txt2img"
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prompt = current_model.prefix + prompt
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result = pipe(
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prompt,
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negative_prompt = neg_prompt,
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# num_images_per_prompt=n_images,
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num_inference_steps = int(steps),
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guidance_scale = guidance,
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width = width,
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height = height,
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generator = generator)
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return replace_nsfw_images(result)
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def img_to_img(model_path, prompt, neg_prompt, img, strength, guidance, steps, width, height, generator=None):
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global last_mode
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global pipe
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global current_model_path
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134 |
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if model_path != current_model_path or last_mode != "img2img":
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current_model_path = model_path
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136 |
+
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137 |
+
if is_colab or current_model == models[0]:
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138 |
+
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16)
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139 |
+
else:
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pipe.to("cpu")
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pipe = current_model.pipe_i2i
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142 |
+
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143 |
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if torch.cuda.is_available():
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pipe = pipe.to("cuda")
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last_mode = "img2img"
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146 |
+
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prompt = current_model.prefix + prompt
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ratio = min(height / img.height, width / img.width)
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img = img.resize((int(img.width * ratio), int(img.height * ratio)), Image.LANCZOS)
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result = pipe(
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prompt,
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negative_prompt = neg_prompt,
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# num_images_per_prompt=n_images,
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init_image = img,
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155 |
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num_inference_steps = int(steps),
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strength = strength,
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157 |
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guidance_scale = guidance,
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width = width,
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height = height,
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generator = generator)
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return replace_nsfw_images(result)
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def replace_nsfw_images(results):
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for i in range(len(results.images)):
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+
if results.nsfw_content_detected[i]:
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results.images[i] = Image.open("nsfw.png")
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168 |
+
return results.images[0]
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169 |
+
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170 |
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css = """
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171 |
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<style>
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.finetuned-diffusion-div {
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173 |
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text-align: center;
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max-width: 700px;
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margin: 0 auto;
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+
}
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.finetuned-diffusion-div div {
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display: inline-flex;
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179 |
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align-items: center;
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180 |
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gap: 0.8rem;
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font-size: 1.75rem;
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182 |
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}
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183 |
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.finetuned-diffusion-div div h1 {
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184 |
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font-weight: 900;
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margin-bottom: 7px;
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186 |
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}
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.finetuned-diffusion-div p {
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margin-bottom: 10px;
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189 |
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font-size: 94%;
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}
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.finetuned-diffusion-div p a {
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text-decoration: underline;
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193 |
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}
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.tabs {
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margin-top: 0px;
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+
margin-bottom: 0px;
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}
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198 |
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#gallery {
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min-height: 20rem;
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}
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</style>
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"""
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203 |
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with gr.Blocks(css=css) as demo:
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gr.HTML(
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f"""
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<div class="finetuned-diffusion-div">
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<div>
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<h1>Finetuned Diffusion</h1>
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</div>
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<p>
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Demo for multiple fine-tuned Stable Diffusion models, trained on different styles: <br>
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<a href="https://huggingface.co/runwayml/stable-diffusion-v1-4">Stable-Diffusion-v1.4</a>, <a href="https://huggingface.co/runwayml/stable-diffusion-v1-5">Stable-Diffusion-v1.5</a>, <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">Spider-Verse</a>, <a href="https://huggingface.co/nitrosocke/modern-disney-diffusion">Modern Disney</a>, <a href="https://huggingface.co/nitrosocke/classic-anim-diffusion">Classic Disney</a>, <a href="https://huggingface.co/hakurei/waifu-diffusion">Waifu</a>, <a href="https://huggingface.co/lambdalabs/sd-pokemon-diffusers">PokΓ©mon</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 𧨠SD model hosted on HuggingFace π€.
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</p>
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+
<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>
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Running on <b>{device}</b>{(" in a <b>Google Colab</b>." if is_colab else "")}
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</p>
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</div>
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"""
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+
)
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with gr.Row():
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221 |
+
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222 |
+
with gr.Column(scale=55):
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223 |
+
with gr.Group():
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+
model_name = gr.Dropdown(label="Model", choices=[m.name for m in models], value=current_model.name)
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225 |
+
with gr.Box(visible=False) as custom_model_group:
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226 |
+
custom_model_path = gr.Textbox(label="Custom model path", placeholder="Path to model, e.g. nitrosocke/Arcane-Diffusion", interactive=True)
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+
gr.HTML("<div><font size='2'>Custom models have to be downloaded first, so give it some time.</font></div>")
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+
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with gr.Row():
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+
prompt = gr.Textbox(label="Prompt", show_label=False, max_lines=2,placeholder="Enter prompt. Style applied automatically").style(container=False)
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231 |
+
generate = gr.Button(value="Generate").style(rounded=(False, True, True, False))
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232 |
+
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233 |
+
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234 |
+
image_out = gr.Image(height=512)
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235 |
+
# gallery = gr.Gallery(
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236 |
+
# label="Generated images", show_label=False, elem_id="gallery"
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237 |
+
# ).style(grid=[1], height="auto")
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238 |
+
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239 |
+
with gr.Column(scale=45):
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240 |
+
with gr.Tab("Options"):
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241 |
+
with gr.Group():
|
242 |
+
neg_prompt = gr.Textbox(label="Negative prompt", placeholder="What to exclude from the image")
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243 |
+
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244 |
+
# n_images = gr.Slider(label="Images", value=1, minimum=1, maximum=4, step=1)
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245 |
+
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+
with gr.Row():
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+
guidance = gr.Slider(label="Guidance scale", value=7.5, maximum=15)
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248 |
+
steps = gr.Slider(label="Steps", value=50, minimum=2, maximum=100, step=1)
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249 |
+
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250 |
+
with gr.Row():
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251 |
+
width = gr.Slider(label="Width", value=512, minimum=64, maximum=1024, step=8)
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252 |
+
height = gr.Slider(label="Height", value=512, minimum=64, maximum=1024, step=8)
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253 |
+
|
254 |
+
seed = gr.Slider(0, 2147483647, label='Seed (0 = random)', value=0, step=1)
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255 |
+
|
256 |
+
with gr.Tab("Image to image"):
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257 |
+
with gr.Group():
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258 |
+
image = gr.Image(label="Image", height=256, tool="editor", type="pil")
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259 |
+
strength = gr.Slider(label="Transformation strength", minimum=0, maximum=1, step=0.01, value=0.5)
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260 |
+
|
261 |
+
model_name.change(lambda x: gr.update(visible = x == models[0].name), inputs=model_name, outputs=custom_model_group)
|
262 |
+
custom_model_path.change(custom_model_changed, inputs=custom_model_path, outputs=None)
|
263 |
+
# n_images.change(lambda n: gr.Gallery().style(grid=[2 if n > 1 else 1], height="auto"), inputs=n_images, outputs=gallery)
|
264 |
+
|
265 |
+
inputs = [model_name, prompt, guidance, steps, width, height, seed, image, strength, neg_prompt]
|
266 |
+
prompt.submit(inference, inputs=inputs, outputs=image_out)
|
267 |
+
generate.click(inference, inputs=inputs, outputs=image_out)
|
268 |
+
|
269 |
+
ex = gr.Examples([
|
270 |
+
[models[1].name, "jason bateman disassembling the demon core", 7.5, 50],
|
271 |
+
[models[4].name, "portrait of dwayne johnson", 7.0, 75],
|
272 |
+
[models[5].name, "portrait of a beautiful alyx vance half life", 10, 50],
|
273 |
+
[models[6].name, "Aloy from Horizon: Zero Dawn, half body portrait, smooth, detailed armor, beautiful face, illustration", 7.0, 45],
|
274 |
+
[models[5].name, "fantasy portrait painting, digital art", 4.0, 30],
|
275 |
+
], [model_name, prompt, guidance, steps, seed], image_out, inference, cache_examples=False)
|
276 |
+
|
277 |
+
gr.Markdown('''
|
278 |
+
Models by [@nitrosocke](https://huggingface.co/nitrosocke), [@haruu1367](https://twitter.com/haruu1367), [@Helixngc7293](https://twitter.com/DGSpitzer) and others. β€οΈ<br>
|
279 |
+
Space by: [![Twitter Follow](https://img.shields.io/twitter/follow/hahahahohohe?label=%40anzorq&style=social)](https://twitter.com/hahahahohohe)
|
280 |
+
|
281 |
+
![visitors](https://visitor-badge.glitch.me/badge?page_id=anzorq.finetuned_diffusion)
|
282 |
+
''')
|
283 |
+
|
284 |
+
if not is_colab:
|
285 |
+
demo.queue(concurrency_count=1)
|
286 |
+
demo.launch(debug=is_colab, share=is_colab)
|
nsfw.png
ADDED
requirements.txt
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
--extra-index-url https://download.pytorch.org/whl/cu113
|
2 |
+
torch
|
3 |
+
diffusers
|
4 |
+
transformers
|
5 |
+
scipy
|
6 |
+
ftfy
|