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🔥 Add app.py
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app.py
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| 1 |
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from typing import Optional
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| 2 |
+
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| 3 |
+
import gradio as gr
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| 4 |
+
import qrcode
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| 5 |
+
import torch
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| 6 |
+
from diffusers import (
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| 7 |
+
ControlNetModel,
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| 8 |
+
EulerAncestralDiscreteScheduler,
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| 9 |
+
StableDiffusionControlNetPipeline,
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| 10 |
+
)
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| 11 |
+
from gradio.components import Image, Radio, Slider, Textbox, Number
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| 12 |
+
from PIL import Image as PilImage
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| 13 |
+
from typing_extensions import Literal
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| 14 |
+
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| 15 |
+
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| 16 |
+
def main():
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| 17 |
+
device = (
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| 18 |
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'cuda' if torch.cuda.is_available()
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| 19 |
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else 'mps' if torch.backends.mps.is_available()
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| 20 |
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else 'cpu'
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| 21 |
+
)
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| 22 |
+
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| 23 |
+
controlnet_tile = ControlNetModel.from_pretrained(
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| 24 |
+
"lllyasviel/control_v11f1e_sd15_tile",
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| 25 |
+
torch_dtype=torch.float16,
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| 26 |
+
use_safetensors=False
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| 27 |
+
).to(device)
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| 28 |
+
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| 29 |
+
controlnet_brightness = ControlNetModel.from_pretrained(
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| 30 |
+
"ioclab/control_v1p_sd15_brightness",
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| 31 |
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torch_dtype=torch.float16,
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| 32 |
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use_safetensors=True
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| 33 |
+
).to(device)
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| 34 |
+
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| 35 |
+
def make_pipe(hf_repo: str, device: str) -> StableDiffusionControlNetPipeline:
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| 36 |
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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| 37 |
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hf_repo,
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| 38 |
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controlnet=[controlnet_tile, controlnet_brightness],
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| 39 |
+
torch_dtype=torch.float16,
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| 40 |
+
)
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| 41 |
+
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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| 42 |
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# pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
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| 43 |
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return pipe.to(device)
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| 44 |
+
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| 45 |
+
pipes = {
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| 46 |
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"DreamShaper": make_pipe("Lykon/DreamShaper", "cpu"),
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| 47 |
+
# "Realistic Vision V1.4": make_pipe("SG161222/Realistic_Vision_V1.4", "cpu"),
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| 48 |
+
# "OpenJourney": make_pipe("prompthero/openjourney", "cpu"),
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| 49 |
+
# "Anything V3": make_pipe("Linaqruf/anything-v3.0", "cpu"),
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| 50 |
+
}
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| 51 |
+
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| 52 |
+
def move_pipe(hf_repo: str):
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| 53 |
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for pipe_name, pipe in pipes.items():
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| 54 |
+
if pipe_name != hf_repo:
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| 55 |
+
pipe.to("cpu")
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| 56 |
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return pipes[hf_repo].to(device)
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| 57 |
+
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| 58 |
+
def predict(
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| 59 |
+
model: Literal[
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| 60 |
+
"DreamShaper",
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| 61 |
+
# "Realistic Vision V1.4",
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| 62 |
+
# "OpenJourney",
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| 63 |
+
# "Anything V3"
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| 64 |
+
],
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| 65 |
+
qrcode_data: str,
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| 66 |
+
prompt: str,
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| 67 |
+
negative_prompt: Optional[str] = None,
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| 68 |
+
num_inference_steps: int = 100,
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| 69 |
+
guidance_scale: int = 9,
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| 70 |
+
controlnet_conditioning_tile: float = 0.25,
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| 71 |
+
controlnet_conditioning_brightness: float = 0.45,
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| 72 |
+
seed: int = 1331,
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| 73 |
+
) -> PilImage:
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| 74 |
+
generator = torch.Generator(device="cuda").manual_seed(seed)
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| 75 |
+
if model == "DreamShaper":
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| 76 |
+
pipe = move_pipe("DreamShaper")
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| 77 |
+
# elif model == "Realistic Vision V1.4":
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| 78 |
+
# pipe = move_pipe("Realistic Vision V1.4")
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| 79 |
+
# elif model == "OpenJourney":
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| 80 |
+
# pipe = move_pipe("OpenJourney")
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| 81 |
+
# elif model == "Anything V3":
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| 82 |
+
# pipe = move_pipe("Anything V3")
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| 83 |
+
|
| 84 |
+
|
| 85 |
+
qr = qrcode.QRCode(
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| 86 |
+
error_correction=qrcode.constants.ERROR_CORRECT_H,
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| 87 |
+
box_size=11,
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| 88 |
+
border=9,
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| 89 |
+
)
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| 90 |
+
qr.add_data(qrcode_data)
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| 91 |
+
qr.make(fit=True)
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| 92 |
+
qrcode_image = qr.make_image(
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| 93 |
+
fill_color="black",
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| 94 |
+
back_color="white"
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| 95 |
+
).convert("RGB")
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| 96 |
+
qrcode_image = qrcode_image.resize((512, 512), PilImage.LANCZOS)
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| 97 |
+
|
| 98 |
+
image = pipe(
|
| 99 |
+
prompt,
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| 100 |
+
[qrcode_image, qrcode_image],
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| 101 |
+
num_inference_steps=num_inference_steps,
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| 102 |
+
generator=generator,
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| 103 |
+
negative_prompt=negative_prompt,
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| 104 |
+
guidance_scale=guidance_scale,
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| 105 |
+
controlnet_conditioning_scale=[
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| 106 |
+
controlnet_conditioning_tile,
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| 107 |
+
controlnet_conditioning_brightness
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| 108 |
+
]
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| 109 |
+
).images[0]
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| 110 |
+
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| 111 |
+
return image
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| 112 |
+
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| 113 |
+
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| 114 |
+
ui = gr.Interface(
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| 115 |
+
fn=predict,
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| 116 |
+
inputs=[
|
| 117 |
+
Radio(
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| 118 |
+
value="DreamShaper",
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| 119 |
+
label="Model",
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| 120 |
+
choices=[
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| 121 |
+
"DreamShaper",
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| 122 |
+
# "Realistic Vision V1.4",
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| 123 |
+
# "OpenJourney",
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| 124 |
+
# "Anything V3"
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| 125 |
+
],
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| 126 |
+
),
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| 127 |
+
Textbox(
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| 128 |
+
value="https://twitter.com/JulienBlanchon",
|
| 129 |
+
label="QR Code Data",
|
| 130 |
+
),
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| 131 |
+
Textbox(
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| 132 |
+
value="Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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| 133 |
+
label="Prompt",
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| 134 |
+
),
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| 135 |
+
Textbox(
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| 136 |
+
value="logo, watermark, signature, text, BadDream, UnrealisticDream",
|
| 137 |
+
label="Negative Prompt",
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| 138 |
+
optional=True
|
| 139 |
+
),
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| 140 |
+
Slider(
|
| 141 |
+
value=100,
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| 142 |
+
label="Number of Inference Steps",
|
| 143 |
+
minimum=10,
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| 144 |
+
maximum=400,
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| 145 |
+
step=1,
|
| 146 |
+
),
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| 147 |
+
Slider(
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| 148 |
+
value=9,
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| 149 |
+
label="Guidance Scale",
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| 150 |
+
minimum=1,
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| 151 |
+
maximum=20,
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| 152 |
+
step=1,
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| 153 |
+
),
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| 154 |
+
Slider(
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| 155 |
+
value=0.25,
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| 156 |
+
label="Controlnet Conditioning Tile",
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| 157 |
+
minimum=0.0,
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| 158 |
+
maximum=1.0,
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| 159 |
+
step=0.05,
|
| 160 |
+
|
| 161 |
+
),
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| 162 |
+
Slider(
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| 163 |
+
value=0.45,
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| 164 |
+
label="Controlnet Conditioning Brightness",
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| 165 |
+
minimum=0.0,
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| 166 |
+
maximum=1.0,
|
| 167 |
+
step=0.05,
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| 168 |
+
),
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| 169 |
+
Number(
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| 170 |
+
value=1,
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| 171 |
+
label="Seed",
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| 172 |
+
precision=0,
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| 173 |
+
),
|
| 174 |
+
|
| 175 |
+
],
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| 176 |
+
outputs=Image(
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| 177 |
+
label="Generated Image",
|
| 178 |
+
type="pil",
|
| 179 |
+
),
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| 180 |
+
examples=[
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| 181 |
+
[
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| 182 |
+
"DreamShaper",
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| 183 |
+
"https://twitter.com/JulienBlanchon",
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| 184 |
+
"Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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| 185 |
+
"logo, watermark, signature, text, BadDream, UnrealisticDream",
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| 186 |
+
100,
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| 187 |
+
9,
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| 188 |
+
0.25,
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| 189 |
+
0.45,
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| 190 |
+
1,
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| 191 |
+
],
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| 192 |
+
# [
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| 193 |
+
# "Anything V3",
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| 194 |
+
# "https://twitter.com/JulienBlanchon",
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| 195 |
+
# "Japanese ramen with chopsticks, egg and steam, ultra detailed 8k",
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| 196 |
+
# "logo, watermark, signature, text, BadDream, UnrealisticDream",
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| 197 |
+
# 100,
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| 198 |
+
# 9,
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| 199 |
+
# 0.25,
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| 200 |
+
# 0.60,
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| 201 |
+
# 1,
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| 202 |
+
# ],
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| 203 |
+
[
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| 204 |
+
"DreamShaper",
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| 205 |
+
"https://twitter.com/JulienBlanchon",
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| 206 |
+
"processor, chipset, electricity, black and white board",
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| 207 |
+
"logo, watermark, signature, text, BadDream, UnrealisticDream",
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| 208 |
+
300,
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| 209 |
+
9,
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| 210 |
+
0.50,
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| 211 |
+
0.30,
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| 212 |
+
1,
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| 213 |
+
],
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| 214 |
+
],
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| 215 |
+
cache_examples=True,
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| 216 |
+
title="Stable Diffusion QR Code Controlnet",
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| 217 |
+
description="Generate QR Code with Stable Diffusion and Controlnet",
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| 218 |
+
allow_flagging="never",
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| 219 |
+
max_batch_size=1,
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| 220 |
+
)
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| 221 |
+
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| 222 |
+
ui.queue(concurrency_count=10).launch()
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| 223 |
+
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| 224 |
+
if __name__ == "__main__":
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| 225 |
+
main()
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