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Webui extension #333

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Aug 25, 2023
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Webui extension #333

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4649b21
upload chinese diffusion webui extension
Bingyan-Liu Aug 25, 2023
05371fd
upload chinese diffusion webui extension
Bingyan-Liu Aug 25, 2023
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45 changes: 45 additions & 0 deletions diffusion/chinese_sd_webui/ChineseSD/README.md
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## stable-diffusion-webui-Chinese-diffusion
An extension for [webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) that lets you generate image from chinese lanuage.

## download model

Put your models into the `../stable-diffusion-webui/models/ChineseDiffusion`.
For example,
```
cd path_to_your/stable-diffusion-webui/models/ChineseDiffusion/Chinese_diffusion
git clone https://huggingface.co/alibaba-pai/pai-diffusion-artist-large-zh
cd path_to_your/stable-diffusion-webui/models/ChineseDiffusion/Chinese_Controlnet
git clone https://huggingface.co/alibaba-pai/pai-diffusion-artist-large-zh-controlnet-canny
cd path_to_your/stable-diffusion-webui/models/ChineseDiffusion/Chinese_Lora
git clone https://huggingface.co/alibaba-pai/pai-diffusion-artist-large-zh-lora-poem
```

## Directories tree
```

📁 webui root directory
┗━━ 📁 stable-diffusion-webui
┗━━ 📁 models
┗━━ 📁 ChineseDiffusion
┗━━ 📁 Chinese_diffusion
┗━━ 📁 your chinese diffusion model <----- any name can be used, such as 'pai-diffusion-artist-large-zh‘
┣━━ 📁feature_tractor
┣━━ 📁safety_checker
┣━━ 📁scheduler
┣━━ 📁text_encoder
┗━━ 📁tokenizer
┣━━ 📁unet
┗━━ 📁vae
model_index.josn
README.md
┗━━ 📁 Chinese_Lora
┗━━ 📁 your lora model <----- any name can be used, such as 'pai-diffusion-artist-large-zh-lora-poem‘
┣━━ 📁...

┗━━ 📁 Chinese_Controlnet
┗━━ 📁 your controlnet model <----- any name can be used, such as 'pai-diffusion-artist-large-zh-controlnet-canny‘
┣━━ 📁...


```

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11 changes: 11 additions & 0 deletions diffusion/chinese_sd_webui/ChineseSD/install.py
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import os
import launch

req_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "requirements_chsd.txt")

with open(req_file) as f:
for lib in f:
lib = lib.strip()
if not launch.is_installed(lib):
print("pip install {}".format(lib))
launch.run_pip(f"install {lib}", f"sd-webui requirement: {lib}")
8 changes: 8 additions & 0 deletions diffusion/chinese_sd_webui/ChineseSD/preload.py
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import os
from modules import paths

def preload(parser):
parser.add_argument("--chinese-diffusion-dir-master", type=str, help="Path to directory with all chinese diffusion models. Contains chinese base diffusion ,chinese controlnet models,chinese lora models and so on", default=None)
parser.add_argument("--chinese-diffusion-dir", type=str, help="Path to directory with chinese base diffusion models.", default=None)
parser.add_argument("--chinese-controlnet-dir", type=str, help="Path to directory with chinese controlnet models.", default=None)
parser.add_argument("--chinese-lora-dir", type=str, help="Path to directory with chinese lora models.", default=None)
1 change: 1 addition & 0 deletions diffusion/chinese_sd_webui/ChineseSD/requirements_chsd.txt
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diffusers
276 changes: 276 additions & 0 deletions diffusion/chinese_sd_webui/ChineseSD/scripts/chinese_sd_ext.py
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import gradio as gr
from modules import script_callbacks

from scripts.utils_ch.utils_ch_df import *

def get_sample_method():
return ['Euler a','Euler','Heun','DPM','DDIM','DDPM','PNDM']

def use_lora(whether_lora,model_name,tag,contorl_mode,lora_model):
if whether_lora:
warning_inf = ''
return gr.Dropdown.update(visible=True),warning_inf
else:
lora_model = 'None'
warning_inf = refresh_model(model_name,tag,contorl_mode,lora_model,whether_lora)
return gr.Dropdown.update(value='None',visible=False),warning_inf

def raise_reminder(model_name):
return 'The current selected base chinses model is '+ str(model_name)+'. Please choice the controlnet model and the control mode before using it. Please note that pai-diffusion-artist-large-zh-controlnet-canny and pai-diffusion-artist-large-zh-controlnet-depth ' \
' are based on the pai-diffusion-artist-large-zh, choose other based models may cause unexpected outputs.'
def use_download(load_model):
if load_model:
return gr.Box.update(visible=True)
else:
return gr.Box.update(visible=False)

def txt2img_ui():
list_available_models()
list_lora_models()
with gr.Row():
with gr.Column(scale=1,):
prompt = gr.Textbox(label = '提示词(prompt)')
negative_prompt = gr.Textbox(label = '负面词(negative_prompt)')
tag = gr.State('txt2img')
with gr.Column(scale=0.5 ):
scheduler = gr.Dropdown(get_sample_method(),
value='DPM',
label='scheduler')
height = gr.Slider(256,
768,
value = 512,
step = 64,
label = '高度(height)')
width = gr.Slider(256,
768,
value = 512,
step = 64,
label = '宽度(width)')
guide = gr.Slider(2,
15,
value = 5,
step = 0.1,
label = '文本引导强度(guidance scale)')
steps = gr.Slider(10,
50,
value = 20,
step = 1,
label = '迭代次数(inference steps)')
seed = gr.Slider(0,
2147483647,
default=-1,
step=1,
label='Seed')
num_images = gr.Slider(0,
8,
value =2,
step=1,
label='图像数量(images)')

with gr.Column(scale=1,):
submit_btn = gr.Button("生成图像(Generate)").style(full_width=False)
model_name = gr.Dropdown(label="模型 (Model)", elem_id="Chinese_model", choices=available_models)
whether_lora = gr.Checkbox(label='Lora, 点击选择lora模型',info="Do you want to use lora")
lora_model = gr.Dropdown(label="lora模型 (lora Model)", choices=available_lora,visible=False)
warning_box = gr.HTML("<p>&nbsp")
# select_model = gr.Button("加载模型").style(full_width=False)
image_out = gr.Gallery(label="输出(output)",
show_label=False,
elem_id="gallery").style(grid=[2], height="auto")
model_name.change(fn = refresh_model, inputs = [model_name,tag,tag,lora_model,whether_lora], outputs = [warning_box,height])
whether_lora.change(fn = use_lora, inputs= [whether_lora,model_name,tag,tag,lora_model], outputs=[lora_model,warning_box])
lora_model.change(fn = refresh_lora_model, inputs = [model_name,tag,tag,lora_model,whether_lora], outputs = warning_box)
submit_btn.click(fn = infer_text2img, inputs = [model_name, prompt, negative_prompt, height,width,guide, steps,num_images,seed,scheduler,whether_lora], outputs = image_out)

def img2img_ui():
list_available_models()
list_lora_models()

with gr.Row():
with gr.Column(scale=1, ):

prompt = gr.Textbox(label = '提示词(prompt)')
image_in = gr.Image(label = '输入图像(image)')
tag = gr.State('img2img')
with gr.Column(scale=0.5 ):
height = gr.Slider(256,
768,
value = 512,
step = 64,
label = '高度(height)')
width = gr.Slider(256,
768,
value = 512,
step = 64,
label = '宽度(width)')
num_images = gr.Slider(0,
8,
value =2,
step=1,
label='图像数量(images)')
guide = gr.Slider(2,
15,
value = 5,
step = 0.1,
label = '文本引导强度(guidance scale)')
steps = gr.Slider(10,
50,
value = 20,
step = 1,
label = '迭代次数(inference steps)')
strength = gr.Slider(0.05,
1.0,
value = 0.8,
label = '强度(strength)')
seed = gr.Slider(0,
2147483647,
default=-1,
step=1,
label='Seed')

with gr.Column(scale=1, ):
submit_btn = gr.Button("生成图像(Generate)").style(full_width=False)
model_name = gr.Dropdown(label="模型 (Model)", elem_id="Chinese_model", choices=available_models)
whether_lora = gr.Checkbox(label='使用Lora',info="Do you want to use lora")
lora_model = gr.Dropdown(label="lora模型 (lora Model)", choices=available_lora,visible=False)
warning_box = gr.HTML("<p>&nbsp")
image_out = gr.Gallery(label="输出(output)", show_label=False, elem_id="gallery").style(grid=[2], height="auto")
model_name.change(fn = refresh_model, inputs = [model_name,tag,tag,lora_model,whether_lora], outputs = [warning_box,height])
whether_lora.change(fn = use_lora, inputs= [whether_lora,model_name,tag,tag,lora_model], outputs=[lora_model,warning_box])
lora_model.change(fn = refresh_lora_model, inputs = [model_name,tag,tag,lora_model,whether_lora], outputs = warning_box)
submit_btn.click(fn = infer_img2img, inputs = [model_name, prompt, image_in, height,width,num_images,guide, steps,strength, seed,whether_lora], outputs = image_out)

def controlnet_ui():
list_available_models()
list_available_controlnet()

with gr.Row():
with gr.Column(scale=1, ):
tag = gr.State('controlnet')
prompt = gr.Textbox(label = '提示词(prompt)')
negative_prompt = gr.Textbox(label = '负面词(negative_prompt)')
image_in = gr.Image(label = '输入图像(image)')
with gr.Column(scale=0.5 ):

scheduler = gr.Dropdown(get_sample_method(),
value='Euler a',
label='scheduler')
height = gr.Slider(256,
768,
value = 512,
step = 64,
label = '高度(height)')
width = gr.Slider(256,
768,
value = 512,
step = 64,
label = '宽度(width)')
guide = gr.Slider(2,
15,
value = 5,
step = 0.1,
label = '文本引导强度(guidance scale)')
steps = gr.Slider(10,
50,
value = 20,
step = 1,
label = '迭代次数(inference steps)')
seed = gr.Slider(0,
2147483647,
default=-1,
step=1,
label='Seed')
num_images = gr.Slider(0,
8,
value =2,
step=1,
label='图像数量(images)')

with gr.Column(scale=1, ):
submit_btn = gr.Button("生成图像(Generate)").style(full_width=False)
model_name = gr.Dropdown(label="模型 (Model)", elem_id="Chinese_model", choices=available_models)
control_model = gr.Dropdown(choices=available_controlnet,label='Controlnet model',info = 'Select the control model you need.')
control_mode = gr.CheckboxGroup(value='canny',choices=['canny','depth'],label='Control mode',info = 'Select the control mode you need. Only one value to be choose.')
warning_box = gr.HTML("<p>&nbsp")
image_out = gr.Gallery(label="输出(output)", show_label=False, elem_id="gallery").style(grid=[2], height="auto")
model_name.change(fn = refresh_model, inputs = [model_name,tag,control_model,tag,tag], outputs = [warning_box,height])
control_model.change(fn= refresh_model_controlnet, inputs = [model_name,tag,control_model,tag,tag], outputs = [warning_box,height,control_mode])
# control_mode.change(fn= refresh_model, inputs = [control_model,tag,control_mode,tag,tag], outputs = warning_box)
submit_btn.click(fn = infer_controlnet, inputs = [control_mode, prompt, negative_prompt,image_in,height,width,guide, steps,num_images,seed,scheduler], outputs = image_out)

def inpainting_ui():
list_available_models()
# list_lora_models()

with gr.Row():
with gr.Column(scale=1, ):

prompt = gr.Textbox(label = '提示词(prompt)')
negative_prompt = gr.Textbox(label = '负面词(negative_prompt)')
image_in = gr.Image(label = '输入图像(image)')
mask_in = gr.Image(label = '输入掩膜(mask)')

tag = gr.State('inpainting')
with gr.Column(scale=0.5 ):

scheduler = gr.Dropdown(get_sample_method(),
value='DPM',
label='scheduler')
height = gr.Slider(256,
768,
value = 512,
step = 64,
label = '高度(height)')
width = gr.Slider(256,
768,
value = 512,
step = 64,
label = '宽度(width)')
strength = gr.Slider(0.05,
1.0,
value = 0.8,
label = '强度(strength)')
num_images = gr.Slider(0,
8,
value =2,
step=1,
label='图像数量(images)')
guide = gr.Slider(2,
15,
value = 5,
step = 0.1,
label = '文本引导强度(guidance scale)')
steps = gr.Slider(10,
50,
value = 20,
step = 1,
label = '迭代次数(inference steps)')
seed = gr.Slider(0,
2147483647,
default=-1,
step=1,
label='Seed')

with gr.Column(scale=1, ):
submit_btn = gr.Button("生成图像(Generate)").style(full_width=False)
model_name = gr.Dropdown(label="模型 (Model)", elem_id="Chinese_model", choices=available_models)
warning_box = gr.HTML("<p>&nbsp")
image_out = gr.Gallery(label="输出(output)", show_label=False, elem_id="gallery").style(grid=[2], height="auto")

model_name.change(fn= refresh_model, inputs = [model_name,tag,tag,tag,tag], outputs = [warning_box,height])
submit_btn.click(fn = infer_inpainting, inputs = [model_name, prompt,negative_prompt, image_in,mask_in, height,width,strength,num_images,guide, steps,scheduler,seed], outputs = image_out)


def add_tab():
with gr.Blocks(analytics_enabled=False) as ui:
with gr.Tab("Txt2img"):
txt2img_ui()
with gr.Tab("Img2img"):
img2img_ui()
with gr.Tab("Inpainting"):
inpainting_ui()
with gr.Tab("Controlnet"):
controlnet_ui()
return [(ui, "Chinese-Diffusion", "Chinese-Diffusion")]

script_callbacks.on_ui_tabs(add_tab)
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