impart-client / app.py
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import os
import datetime
import gradio as gr
from pnginfo import read_info_from_image, send_paras
from utils import set_token, generate_novelai_image, image_from_bytes
today_count = 0
today = datetime.date.today().strftime('%Y-%m-%d')
def get_count():
global today_count, today
now = datetime.date.today().strftime('%Y-%m-%d')
if now != today:
today = now
today_count = 0
return "Total number of today's image generation: " + str(today_count)
def control_ui():
prompt = gr.TextArea(label="Prompt", lines=3, value="{breast expansion},{gigantic breasts},[artist:ningen_mame],artist:ciloranko,[artist:sho_(sho_lwlw)],[artist:foifoi (marfoyfoyfoy)],1girl,skinny,narrow waist,")
quality_tags = gr.TextArea(
label="Quality Tags", lines=1,
value="best quality, amazing quality, very aesthetic, absurdres",
)
neg_prompt = gr.TextArea(
label="Negative Prompt", lines=1,
value="wide hips,thick thighs,plump,lowres, {bad}, error, fewer, extra, missing, worst quality, jpeg artifacts, bad quality, watermark, unfinished, displeasing, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract],pubic hair",
)
with gr.Row():
sampler = gr.Dropdown(
choices=[
"k_euler", "k_euler_ancestral", "k_dpmpp_2s_ancestral",
"k_dpmpp_2m", "k_dpmpp_sde", "ddim_v3"
],
value="k_euler",
label="Sampler",
interactive=True
)
scale = gr.Slider(label="Scale", value=5.0, minimum=1, maximum=10, step=0.1)
steps = gr.Slider(label="Steps", value=28, minimum=1, maximum=28, step=1)
with gr.Row():
seed = gr.Number(label="Seed", value=-1, step=1, maximum=2**32-1, minimum=-1, scale=3)
rand_seed = gr.Button('🎲️', scale=1)
reuse_seed = gr.Button('♻️', scale=1)
with gr.Row():
width = gr.Slider(label="Width", value=1024, minimum=64, maximum=2048, step=64)
height = gr.Slider(label="Height", value=1024, minimum=64, maximum=2048, step=64)
with gr.Column():
with gr.Accordion('风格迁移', open=False):
ref_image = gr.Image(label="上传图片", value=None, interactive=True, type="pil")
info_extract = gr.Slider(label='参考信息提取', value=1, minimum=0, maximum=1, step=0.1)
ref_str = gr.Slider(label='参考强度', value=0.6, minimum=0, maximum=1, step=0.1)
reuse_img_vibe = gr.Button(value='使用上一次生成的图片')
with gr.Accordion('蒙版重绘', open=False):
with gr.Row():
use_inp = gr.Checkbox(label='启用', value=False)
overlay = gr.Checkbox(label='覆盖原图', value=True)
inp_img = gr.Image(label="上传图片", value=None, interactive=True, type="pil", tool="sketch")
inp_str = gr.Slider(label='重绘强度', value=0.7, minimum=0, maximum=0.99, step=0.01)
reuse_img_inp = gr.Button(value='使用上一次生成的图片')
with gr.Row():
with gr.Column():
with gr.Accordion('Advanced Gen Setting', open=False):
scheduler = gr.Dropdown(
choices=[
"native", "karras", "exponential", "polyexponential"
],
value="native",
label="Scheduler",
interactive=True
)
with gr.Row():
smea = gr.Checkbox(False, label="SMEA")
dyn = gr.Checkbox(False, label="SMEA DYN")
with gr.Row():
dyn_threshold = gr.Checkbox(False, label="Dynamic Thresholding")
cfg_rescale = gr.Slider(0, 1, 0, step=0.01, label="CFG rescale")
with gr.Column():
gr.Textbox(value=get_count, label='Usage count', every=10)
save = gr.Checkbox(value=False, label='Always save all generated images', visible=False)
gen_btn = gr.Button(value="Generate", variant="primary")
rand_seed.click(fn=lambda: -1, inputs=None, outputs=seed)
width.change(lambda w, h: h if w*h<=1024*1024 else (1024*1024//w//64)*64, [width, height], height)
height.change(lambda w, h: w if w*h<=1024*1024 else (1024*1024//h//64)*64, [width, height], width)
return gen_btn,[prompt, quality_tags, neg_prompt, seed, scale, width, height, steps, sampler, scheduler, smea, dyn, dyn_threshold, cfg_rescale, ref_image, info_extract, ref_str, inp_img, overlay, inp_str], [save, rand_seed, reuse_seed, reuse_img_vibe, use_inp, reuse_img_inp]
def generate(prompt, quality_tags, neg_prompt, seed, scale, width, height, steps, sampler, scheduler, smea, dyn, dyn_threshold, cfg_rescale, ref_image, info_extract, ref_str, inp_img, overlay, inp_str, save, use_inp):
global today_count
set_token(os.environ.get('token'))
img_data, payload = generate_novelai_image(
f"{prompt}, {quality_tags}", neg_prompt, seed, scale,
width, height, steps, sampler, scheduler,
smea, dyn, dyn_threshold, cfg_rescale, ref_image, info_extract, ref_str,
inp_img, overlay, use_inp, inp_str
)
if not isinstance(img_data, bytes):
return None, payload
today_count += 1
img = image_from_bytes(img_data)
return img, payload
def preview_ui():
with gr.Blocks(css='#preview_image { height: 100%;}') as page:
image = gr.Image(elem_id='preview_image', interactive=False, type='pil')
info = gr.JSON(value={}, label="Submitted Payload")
return image, info
def main_ui():
with gr.Blocks() as page:
with gr.Row(variant="panel"):
with gr.Column():
gen_btn, paras, others = control_ui()
with gr.Column():
image, info = preview_ui()
gen_btn.click(generate, paras + [others[0], others[4]], [image, info])
others[2].click(lambda o, s: o if len(s) == 0 else s['parameters']['seed'], inputs=[paras[3], info], outputs=paras[3])
others[3].click(lambda i: i, inputs=image, outputs=paras[14])
others[5].click(lambda i: i, inputs=image, outputs=paras[17])
return page, paras[:14]
def util_ui():
with gr.Blocks(analytics_enabled=False) as page:
with gr.Row(equal_height=False):
with gr.Column(variant='panel'):
image = gr.Image(label="Source", interactive=True, type="pil")
with gr.Column(variant='panel'):
info = gr.HTML()
items = gr.JSON(value=None, visible=False)
png2main = gr.Button('Send to txt2img')
return page, png2main, items, info, image
def ui():
with gr.Blocks(title="NAI Client") as website:
with gr.Tabs():
with gr.TabItem("Main", elem_id="client_ui_main"):
_, paras = main_ui()
with gr.TabItem("PNG Info"):
_, png2main, png_items, info, image = util_ui()
png2main.click(fn=send_paras,
inputs=[png_items] + paras,
outputs=paras)
png2main.click(fn=None,
_js="(x) => { if (x !== null) document.getElementById('client_ui_main-button').click(); "
"return null; }",
inputs=image)
image.change(read_info_from_image, inputs=image, outputs=[info, png_items])
return website
if __name__ == '__main__':
website = ui()
website.queue()
website.launch(auth=(os.environ.get('account'), os.environ.get('password')))