Merge pull request #333 from alibaba/webui_extension

Webui extension

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‘
+                        ┣━━ 📁...   
+
+
+```
+

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}")

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)

diffusion/chinese_sd_webui/ChineseSD/requirements_chsd.txt

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+diffusers

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)