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import gradio as gr
import sys
from utils import load_lora_model
from bg_alpha import adjust_transparency
from lineart import get_pipe
import os
from PIL import Image
import spaces
path = os.getcwd()
output_dir = f"{path}/output"
lora_dir = f"{path}/models/lora"
load_lora_model(lora_dir)
pipe = get_pipe(lora_dir)
@spaces.GPU()
def generate(prompt, negative_prompt):
default_pos = "((white background)), lineart, <lora:sdxl_BWLine:1.0>, monochrome, "
default_neg = ""
prompt = default_pos + prompt
negative_prompt = default_neg + negative_prompt
width, height = 1024, 1024
color = (255, 255, 255)
white_bg = Image.new("RGB", (width, height), color)
image = pipe(
prompt=prompt,
negative_prompt = negative_prompt,
image=[white_bg],
num_inference_steps=50,
controlnet_conditioning_scale=[0.1]
).images[0]
return image
class webui:
def __init__(self):
self.demo = gr.Blocks()
def process(self, pos_prompt, neg_prompt):
image = generate(pos_prompt, neg_prompt)
image = adjust_transparency(image)
return [image]
def launch(self, share):
with self.demo:
with gr.Column():
pos_prompt = gr.Textbox(value="1girl, cute, kawaii, medium breasts, medium hair, smile, mini skirt, best quality, very aesthetic,", max_lines=1000, label="Positive prompt")
neg_prompt = gr.Textbox(value="bold line, multiple people,", max_lines=1000, label="Negative prompt")
submit = gr.Button(value="Start", variant="primary")
output_0 = gr.Image(label="Output", format="png")
submit.click(
self.process,
inputs=[pos_prompt, neg_prompt], #[input_image, pos_prompt, neg_prompt, alpha_th, thickness, reference_image],
outputs=[output_0]
)
self.demo.queue()
self.demo.launch(share=share)
if __name__ == "__main__":
ui = webui()
if len(sys.argv) > 1:
if sys.argv[1] == "share":
ui.launch(share=True)
else:
ui.launch(share=False)
else:
ui.launch(share=False)
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