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app.py
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@@ -0,0 +1,225 @@
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from typing import Optional
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import gradio as gr
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import qrcode
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import torch
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from diffusers import (
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ControlNetModel,
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EulerAncestralDiscreteScheduler,
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StableDiffusionControlNetPipeline,
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)
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from gradio.components import Image, Radio, Slider, Textbox, Number
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from PIL import Image as PilImage
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from typing_extensions import Literal
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+
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def main():
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device = (
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'cuda' if torch.cuda.is_available()
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else 'mps' if torch.backends.mps.is_available()
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else 'cpu'
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)
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+
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+
controlnet_tile = ControlNetModel.from_pretrained(
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"lllyasviel/control_v11f1e_sd15_tile",
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torch_dtype=torch.float16,
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use_safetensors=False
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).to(device)
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+
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controlnet_brightness = ControlNetModel.from_pretrained(
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"ioclab/control_v1p_sd15_brightness",
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torch_dtype=torch.float16,
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use_safetensors=True
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).to(device)
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+
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def make_pipe(hf_repo: str, device: str) -> StableDiffusionControlNetPipeline:
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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hf_repo,
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controlnet=[controlnet_tile, controlnet_brightness],
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torch_dtype=torch.float16,
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)
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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# pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
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return pipe.to(device)
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+
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pipes = {
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"DreamShaper": make_pipe("Lykon/DreamShaper", "cpu"),
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# "Realistic Vision V1.4": make_pipe("SG161222/Realistic_Vision_V1.4", "cpu"),
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# "OpenJourney": make_pipe("prompthero/openjourney", "cpu"),
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# "Anything V3": make_pipe("Linaqruf/anything-v3.0", "cpu"),
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}
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+
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def move_pipe(hf_repo: str):
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for pipe_name, pipe in pipes.items():
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if pipe_name != hf_repo:
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pipe.to("cpu")
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return pipes[hf_repo].to(device)
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+
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def predict(
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model: Literal[
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"DreamShaper",
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# "Realistic Vision V1.4",
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# "OpenJourney",
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# "Anything V3"
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],
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qrcode_data: str,
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prompt: str,
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negative_prompt: Optional[str] = None,
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num_inference_steps: int = 100,
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guidance_scale: int = 9,
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controlnet_conditioning_tile: float = 0.25,
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controlnet_conditioning_brightness: float = 0.45,
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seed: int = 1331,
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) -> PilImage:
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generator = torch.Generator(device="cuda").manual_seed(seed)
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if model == "DreamShaper":
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pipe = move_pipe("DreamShaper")
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# elif model == "Realistic Vision V1.4":
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# pipe = move_pipe("Realistic Vision V1.4")
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# elif model == "OpenJourney":
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# pipe = move_pipe("OpenJourney")
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# elif model == "Anything V3":
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# pipe = move_pipe("Anything V3")
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+
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+
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qr = qrcode.QRCode(
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error_correction=qrcode.constants.ERROR_CORRECT_H,
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box_size=11,
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border=9,
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)
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qr.add_data(qrcode_data)
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qr.make(fit=True)
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qrcode_image = qr.make_image(
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fill_color="black",
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back_color="white"
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+
).convert("RGB")
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qrcode_image = qrcode_image.resize((512, 512), PilImage.LANCZOS)
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+
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image = pipe(
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prompt,
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[qrcode_image, qrcode_image],
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num_inference_steps=num_inference_steps,
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generator=generator,
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negative_prompt=negative_prompt,
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guidance_scale=guidance_scale,
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controlnet_conditioning_scale=[
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controlnet_conditioning_tile,
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controlnet_conditioning_brightness
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]
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).images[0]
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return image
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ui = gr.Interface(
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fn=predict,
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inputs=[
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Radio(
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value="DreamShaper",
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label="Model",
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choices=[
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"DreamShaper",
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# "Realistic Vision V1.4",
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# "OpenJourney",
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# "Anything V3"
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],
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),
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+
Textbox(
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value="https://twitter.com/JulienBlanchon",
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label="QR Code Data",
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),
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+
Textbox(
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value="Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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+
label="Prompt",
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),
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+
Textbox(
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value="logo, watermark, signature, text, BadDream, UnrealisticDream",
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+
label="Negative Prompt",
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optional=True
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+
),
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+
Slider(
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value=100,
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+
label="Number of Inference Steps",
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+
minimum=10,
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+
maximum=400,
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step=1,
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),
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+
Slider(
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value=9,
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+
label="Guidance Scale",
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+
minimum=1,
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+
maximum=20,
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+
step=1,
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),
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+
Slider(
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value=0.25,
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+
label="Controlnet Conditioning Tile",
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+
minimum=0.0,
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maximum=1.0,
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+
step=0.05,
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+
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),
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+
Slider(
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value=0.45,
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label="Controlnet Conditioning Brightness",
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+
minimum=0.0,
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+
maximum=1.0,
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+
step=0.05,
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+
),
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+
Number(
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value=1,
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+
label="Seed",
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+
precision=0,
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),
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+
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],
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+
outputs=Image(
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+
label="Generated Image",
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+
type="pil",
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+
),
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+
examples=[
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[
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"DreamShaper",
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+
"https://twitter.com/JulienBlanchon",
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+
"Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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+
"logo, watermark, signature, text, BadDream, UnrealisticDream",
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+
100,
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+
9,
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+
0.25,
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+
0.45,
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+
1,
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],
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# [
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# "Anything V3",
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# "https://twitter.com/JulienBlanchon",
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# "Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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+
# "logo, watermark, signature, text, BadDream, UnrealisticDream",
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+
# 100,
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+
# 9,
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+
# 0.25,
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+
# 0.60,
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+
# 1,
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# ],
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[
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+
"DreamShaper",
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+
"https://twitter.com/JulienBlanchon",
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"processor, chipset, electricity, black and white board",
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+
"logo, watermark, signature, text, BadDream, UnrealisticDream",
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+
300,
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+
9,
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+
0.50,
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+
0.30,
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1,
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],
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],
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+
cache_examples=True,
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+
title="Stable Diffusion QR Code Controlnet",
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+
description="Generate QR Code with Stable Diffusion and Controlnet",
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+
allow_flagging="never",
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+
max_batch_size=1,
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+
)
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+
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+
ui.queue(concurrency_count=10).launch()
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+
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+
if __name__ == "__main__":
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+
main()
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