mirror of
https://github.com/Sygil-Dev/sygil-webui.git
synced 2024-12-15 06:21:34 +03:00
Merge remote-tracking branch 'origin/dev' into dev
This commit is contained in:
ZeroCool940711
commit
afaff01253
14
.env_docker.example
Normal file
14
.env_docker.example
Normal file
@ -0,0 +1,14 @@
|
||||
# Force miniconda to attempt to update on every container restart
|
||||
# instead only when changes are detected
|
||||
CONDA_FORCE_UPDATE=false
|
||||
|
||||
# Validate the model files on every container restart
|
||||
# (useful to set to false after you're sure the model files are already in place)
|
||||
VALIDATE_MODELS=true
|
||||
|
||||
#Automatically relaunch the webui on crashes
|
||||
WEBUI_RELAUNCH=true
|
||||
|
||||
#Pass cli arguments to webui.py e.g:
|
||||
#WEBUI_ARGS=--gpu=1 --esrgan-gpu=1 --gfpgan-gpu=1
|
||||
WEBUI_ARGS=
|
||||
0
entrypoint.sh
Normal file → Executable file
0
entrypoint.sh
Normal file → Executable file
@ -4,12 +4,14 @@ from frontend.job_manager import JobManager
|
||||
import frontend.ui_functions as uifn
|
||||
import uuid
|
||||
|
||||
def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda x: x, txt2img_defaults={}, RealESRGAN=True, GFPGAN=True,LDSR=True,
|
||||
|
||||
def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x, imgproc=lambda x: x, txt2img_defaults={},
|
||||
RealESRGAN=True, GFPGAN=True, LDSR=True,
|
||||
txt2img_toggles={}, txt2img_toggle_defaults='k_euler', show_embeddings=False, img2img_defaults={},
|
||||
img2img_toggles={}, img2img_toggle_defaults={}, sample_img2img=None, img2img_mask_modes=None,
|
||||
img2img_resize_modes=None, imgproc_defaults={},imgproc_mode_toggles={},user_defaults={}, run_GFPGAN=lambda x: x, run_RealESRGAN=lambda x: x,
|
||||
img2img_resize_modes=None, imgproc_defaults={}, imgproc_mode_toggles={}, user_defaults={},
|
||||
run_GFPGAN=lambda x: x, run_RealESRGAN=lambda x: x,
|
||||
job_manager: JobManager = None) -> gr.Blocks:
|
||||
|
||||
with gr.Blocks(css=css(opt), analytics_enabled=False, title="Stable Diffusion WebUI") as demo:
|
||||
with gr.Tabs(elem_id='tabss') as tabs:
|
||||
with gr.TabItem("Text-to-Image", id='txt2img_tab'):
|
||||
@ -40,34 +42,37 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
|
||||
txt2img_job_ui = job_manager.draw_gradio_ui() if job_manager else None
|
||||
|
||||
txt2img_dimensions_info_text_box = gr.Textbox(label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
|
||||
txt2img_dimensions_info_text_box = gr.Textbox(
|
||||
label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
|
||||
with gr.Column():
|
||||
with gr.Box():
|
||||
output_txt2img_gallery = gr.Gallery(label="Images", elem_id="txt2img_gallery_output").style(grid=[4, 4])
|
||||
gr.Markdown("Select an image from the gallery, then click one of the buttons below to perform an action.")
|
||||
output_txt2img_gallery = gr.Gallery(label="Images", elem_id="txt2img_gallery_output").style(
|
||||
grid=[4, 4])
|
||||
gr.Markdown(
|
||||
"Select an image from the gallery, then click one of the buttons below to perform an action.")
|
||||
with gr.Row(elem_id='txt2img_actions_row'):
|
||||
gr.Button("Copy to clipboard").click(fn=None,
|
||||
inputs=output_txt2img_gallery,
|
||||
outputs=[],
|
||||
#_js=js_copy_to_clipboard( 'txt2img_gallery_output')
|
||||
)
|
||||
inputs=output_txt2img_gallery,
|
||||
outputs=[],
|
||||
# _js=js_copy_to_clipboard( 'txt2img_gallery_output')
|
||||
)
|
||||
output_txt2img_copy_to_input_btn = gr.Button("Push to img2img")
|
||||
output_txt2img_to_imglab = gr.Button("Send to Lab",visible=True)
|
||||
output_txt2img_to_imglab = gr.Button("Send to Lab", visible=True)
|
||||
|
||||
output_txt2img_params = gr.Highlightedtext(label="Generation parameters", interactive=False, elem_id='highlight')
|
||||
output_txt2img_params = gr.Highlightedtext(label="Generation parameters", interactive=False,
|
||||
elem_id='highlight')
|
||||
with gr.Group():
|
||||
with gr.Row(elem_id='txt2img_output_row'):
|
||||
output_txt2img_copy_params = gr.Button("Copy full parameters").click(
|
||||
inputs=[output_txt2img_params], outputs=[],
|
||||
_js=js_copy_txt2img_output,
|
||||
fn=None, show_progress=False)
|
||||
fn=None, show_progress=False)
|
||||
output_txt2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
|
||||
output_txt2img_copy_seed = gr.Button("Copy only seed").click(
|
||||
inputs=[output_txt2img_seed], outputs=[],
|
||||
_js='(x) => navigator.clipboard.writeText(x)', fn=None, show_progress=False)
|
||||
output_txt2img_stats = gr.HTML(label='Stats')
|
||||
with gr.Column():
|
||||
|
||||
txt2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
|
||||
value=txt2img_defaults['ddim_steps'])
|
||||
txt2img_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
|
||||
@ -93,7 +98,8 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
choices=['RealESRGAN_x4plus',
|
||||
'RealESRGAN_x4plus_anime_6B'],
|
||||
value='RealESRGAN_x4plus',
|
||||
visible=False)#RealESRGAN is not None # invisible until removed) # TODO: Feels like I shouldnt slot it in here.
|
||||
visible=False) # RealESRGAN is not None # invisible until removed) # TODO: Feels like I shouldnt slot it in here.
|
||||
|
||||
txt2img_ddim_eta = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="DDIM ETA",
|
||||
value=txt2img_defaults['ddim_eta'], visible=False)
|
||||
txt2img_variant_amount = gr.Slider(minimum=0.0, maximum=1.0, label='Variation Amount',
|
||||
@ -133,7 +139,8 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
# txt2img_width.change(fn=uifn.update_dimensions_info, inputs=[txt2img_width, txt2img_height], outputs=txt2img_dimensions_info_text_box)
|
||||
# txt2img_height.change(fn=uifn.update_dimensions_info, inputs=[txt2img_width, txt2img_height], outputs=txt2img_dimensions_info_text_box)
|
||||
|
||||
live_prompt_params = [txt2img_prompt, txt2img_width, txt2img_height, txt2img_steps, txt2img_seed, txt2img_batch_count, txt2img_cfg]
|
||||
live_prompt_params = [txt2img_prompt, txt2img_width, txt2img_height, txt2img_steps, txt2img_seed,
|
||||
txt2img_batch_count, txt2img_cfg]
|
||||
txt2img_prompt.change(
|
||||
fn=None,
|
||||
inputs=live_prompt_params,
|
||||
@ -141,7 +148,6 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
_js=js_parse_prompt
|
||||
)
|
||||
|
||||
|
||||
with gr.TabItem("Image-to-Image Unified", id="img2img_tab"):
|
||||
with gr.Row(elem_id="prompt_row"):
|
||||
img2img_prompt = gr.Textbox(label="Prompt",
|
||||
@ -158,39 +164,58 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
with gr.Row().style(equal_height=False):
|
||||
with gr.Column():
|
||||
gr.Markdown('#### Img2Img Input')
|
||||
img2img_image_mask = gr.Image(value=sample_img2img, source="upload", interactive=True,
|
||||
type="pil", tool="sketch", elem_id="img2img_editor", image_mode="RGBA"
|
||||
)
|
||||
img2img_image_editor = gr.Image(value=sample_img2img, source="upload", interactive=False,
|
||||
type="pil", tool="sketch", visible=False, image_mode="RGBA",
|
||||
elem_id="img2img_mask")
|
||||
img2img_image_mask = gr.Image(
|
||||
value=sample_img2img,
|
||||
source="upload",
|
||||
interactive=True,
|
||||
type="pil", tool="sketch",
|
||||
elem_id="img2img_mask",
|
||||
image_mode="RGBA"
|
||||
)
|
||||
img2img_image_editor = gr.Image(
|
||||
value=sample_img2img,
|
||||
source="upload",
|
||||
interactive=True,
|
||||
type="pil",
|
||||
tool="select",
|
||||
visible=False,
|
||||
image_mode="RGBA",
|
||||
elem_id="img2img_editor"
|
||||
)
|
||||
|
||||
with gr.Tabs():
|
||||
with gr.TabItem("Editor Options"):
|
||||
with gr.Row():
|
||||
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop", "Uncrop"], label="Image Editor Mode",
|
||||
value="Mask", elem_id='edit_mode_select', visible=False)
|
||||
# disable Uncrop for now
|
||||
# choices=["Mask", "Crop", "Uncrop"]
|
||||
img2img_image_editor_mode = gr.Radio(choices=["Mask", "Crop"],
|
||||
label="Image Editor Mode",
|
||||
value="Mask", elem_id='edit_mode_select',
|
||||
visible=True)
|
||||
img2img_mask = gr.Radio(choices=["Keep masked area", "Regenerate only masked area"],
|
||||
label="Mask Mode", type="index",
|
||||
value=img2img_mask_modes[img2img_defaults['mask_mode']], visible=True)
|
||||
label="Mask Mode", type="index",
|
||||
value=img2img_mask_modes[img2img_defaults['mask_mode']],
|
||||
visible=True)
|
||||
|
||||
img2img_mask_blur_strength = gr.Slider(minimum=1, maximum=10, step=1,
|
||||
label="How much blurry should the mask be? (to avoid hard edges)",
|
||||
value=3, visible=False)
|
||||
label="How much blurry should the mask be? (to avoid hard edges)",
|
||||
value=3, visible=False)
|
||||
|
||||
img2img_resize = gr.Radio(label="Resize mode",
|
||||
choices=["Just resize", "Crop and resize", "Resize and fill"],
|
||||
type="index",
|
||||
value=img2img_resize_modes[img2img_defaults['resize_mode']], visible=False)
|
||||
choices=["Just resize", "Crop and resize",
|
||||
"Resize and fill"],
|
||||
type="index",
|
||||
value=img2img_resize_modes[
|
||||
img2img_defaults['resize_mode']], visible=False)
|
||||
|
||||
img2img_painterro_btn = gr.Button("Advanced Editor")
|
||||
with gr.TabItem("Hints"):
|
||||
img2img_help = gr.Markdown(visible=False, value=uifn.help_text)
|
||||
|
||||
|
||||
with gr.Column():
|
||||
gr.Markdown('#### Img2Img Results')
|
||||
output_img2img_gallery = gr.Gallery(label="Images", elem_id="img2img_gallery_output").style(grid=[4,4,4])
|
||||
output_img2img_gallery = gr.Gallery(label="Images", elem_id="img2img_gallery_output").style(
|
||||
grid=[4, 4, 4])
|
||||
img2img_job_ui = job_manager.draw_gradio_ui() if job_manager else None
|
||||
with gr.Tabs():
|
||||
with gr.TabItem("Generated image actions", id="img2img_actions_tab"):
|
||||
@ -206,7 +231,8 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
with gr.Row():
|
||||
output_img2img_copy_params = gr.Button("Copy full parameters").click(
|
||||
inputs=output_img2img_params, outputs=[],
|
||||
_js='(x) => {navigator.clipboard.writeText(x.replace(": ",":"))}', fn=None, show_progress=False)
|
||||
_js='(x) => {navigator.clipboard.writeText(x.replace(": ",":"))}', fn=None,
|
||||
show_progress=False)
|
||||
output_img2img_seed = gr.Number(label='Seed', interactive=False, visible=False)
|
||||
output_img2img_copy_seed = gr.Button("Copy only seed").click(
|
||||
inputs=output_img2img_seed, outputs=[],
|
||||
@ -229,7 +255,8 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
img2img_batch_count = gr.Slider(minimum=1, maximum=50, step=1,
|
||||
label='Batch count (how many batches of images to generate)',
|
||||
value=img2img_defaults['n_iter'])
|
||||
img2img_dimensions_info_text_box = gr.Textbox(label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
|
||||
img2img_dimensions_info_text_box = gr.Textbox(
|
||||
label="Aspect ratio (4:3 = 1.333 | 16:9 = 1.777 | 21:9 = 2.333)")
|
||||
with gr.Column():
|
||||
img2img_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
|
||||
value=img2img_defaults['ddim_steps'])
|
||||
@ -310,7 +337,8 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
img2img_realesrgan_model_name, img2img_batch_count, img2img_cfg,
|
||||
img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
|
||||
img2img_image_editor, img2img_image_mask, img2img_embeddings]
|
||||
img2img_outputs = [output_img2img_gallery, output_img2img_seed, output_img2img_params, output_img2img_stats]
|
||||
img2img_outputs = [output_img2img_gallery, output_img2img_seed, output_img2img_params,
|
||||
output_img2img_stats]
|
||||
|
||||
# If a JobManager was passed in then wrap the Generate functions
|
||||
if img2img_job_ui:
|
||||
@ -325,15 +353,16 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
img2img_inputs,
|
||||
img2img_outputs
|
||||
)
|
||||
|
||||
def img2img_submit_params():
|
||||
#print([img2img_prompt, img2img_image_editor_mode, img2img_mask,
|
||||
# print([img2img_prompt, img2img_image_editor_mode, img2img_mask,
|
||||
# img2img_mask_blur_strength, img2img_steps, img2img_sampling, img2img_toggles,
|
||||
# img2img_realesrgan_model_name, img2img_batch_count, img2img_cfg,
|
||||
# img2img_denoising, img2img_seed, img2img_height, img2img_width, img2img_resize,
|
||||
# img2img_image_editor, img2img_image_mask, img2img_embeddings])
|
||||
return (img2img_func,
|
||||
img2img_inputs,
|
||||
img2img_outputs)
|
||||
img2img_inputs,
|
||||
img2img_outputs)
|
||||
|
||||
img2img_btn_editor.click(*img2img_submit_params())
|
||||
|
||||
@ -348,26 +377,31 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
_js=call_JS("Painterro.init", toId="img2img_editor")
|
||||
)
|
||||
|
||||
img2img_width.change(fn=uifn.update_dimensions_info, inputs=[img2img_width, img2img_height], outputs=img2img_dimensions_info_text_box)
|
||||
img2img_height.change(fn=uifn.update_dimensions_info, inputs=[img2img_width, img2img_height], outputs=img2img_dimensions_info_text_box)
|
||||
|
||||
with gr.TabItem("Image Lab", id='imgproc_tab'):
|
||||
gr.Markdown("Post-process results")
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
with gr.Tabs():
|
||||
with gr.TabItem('Single Image'):
|
||||
imgproc_source = gr.Image(label="Source", source="upload", interactive=True, type="pil",elem_id="imglab_input")
|
||||
img2img_width.change(fn=uifn.update_dimensions_info, inputs=[img2img_width, img2img_height],
|
||||
outputs=img2img_dimensions_info_text_box)
|
||||
img2img_height.change(fn=uifn.update_dimensions_info, inputs=[img2img_width, img2img_height],
|
||||
outputs=img2img_dimensions_info_text_box)
|
||||
|
||||
#gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength",
|
||||
with gr.TabItem("Image Lab", id='imgproc_tab'):
|
||||
gr.Markdown("Post-process results")
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
with gr.Tabs():
|
||||
with gr.TabItem('Single Image'):
|
||||
imgproc_source = gr.Image(label="Source", source="upload", interactive=True, type="pil",
|
||||
elem_id="imglab_input")
|
||||
|
||||
# gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength",
|
||||
# value=gfpgan_defaults['strength'])
|
||||
#select folder with images to process
|
||||
with gr.TabItem('Batch Process'):
|
||||
imgproc_folder = gr.File(label="Batch Process", file_count="multiple",source="upload", interactive=True, type="file")
|
||||
imgproc_pngnfo = gr.Textbox(label="PNG Metadata", placeholder="PngNfo", visible=False, max_lines=5)
|
||||
with gr.Row():
|
||||
imgproc_btn = gr.Button("Process", variant="primary")
|
||||
gr.HTML("""
|
||||
# select folder with images to process
|
||||
with gr.TabItem('Batch Process'):
|
||||
imgproc_folder = gr.File(label="Batch Process", file_count="multiple", source="upload",
|
||||
interactive=True, type="file")
|
||||
imgproc_pngnfo = gr.Textbox(label="PNG Metadata", placeholder="PngNfo", visible=False,
|
||||
max_lines=5)
|
||||
with gr.Row():
|
||||
imgproc_btn = gr.Button("Process", variant="primary")
|
||||
gr.HTML("""
|
||||
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
|
||||
<p><b>Upscale Modes Guide</b></p>
|
||||
<p></p>
|
||||
@ -381,142 +415,170 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x,imgproc=lambda
|
||||
<p>A 8X upscaler with high VRAM usage, uses GoBig to add details and then uses a Latent Diffusion model to upscale the image, this will result in less artifacting/sharpeninng, use the settings to feed GoBig settings that will contribute to the result, this mode is considerbly slower</p>
|
||||
</div>
|
||||
""")
|
||||
with gr.Column():
|
||||
with gr.Tabs():
|
||||
with gr.TabItem('Output'):
|
||||
imgproc_output = gr.Gallery(label="Output", elem_id="imgproc_gallery_output")
|
||||
with gr.Row(elem_id="proc_options_row"):
|
||||
with gr.Box():
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>Processor Selection</b>")
|
||||
imgproc_toggles = gr.CheckboxGroup(label = '',choices=imgproc_mode_toggles, type="index")
|
||||
#.change toggles to show options
|
||||
#imgproc_toggles.change()
|
||||
with gr.Box(visible=False) as gfpgan_group:
|
||||
with gr.Column():
|
||||
with gr.Tabs():
|
||||
with gr.TabItem('Output'):
|
||||
imgproc_output = gr.Gallery(label="Output", elem_id="imgproc_gallery_output")
|
||||
with gr.Row(elem_id="proc_options_row"):
|
||||
with gr.Box():
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>Processor Selection</b>")
|
||||
imgproc_toggles = gr.CheckboxGroup(label='', choices=imgproc_mode_toggles,
|
||||
type="index")
|
||||
# .change toggles to show options
|
||||
# imgproc_toggles.change()
|
||||
with gr.Box(visible=False) as gfpgan_group:
|
||||
|
||||
gfpgan_defaults = {
|
||||
'strength': 100,
|
||||
}
|
||||
gfpgan_defaults = {
|
||||
'strength': 100,
|
||||
}
|
||||
|
||||
if 'gfpgan' in user_defaults:
|
||||
gfpgan_defaults.update(user_defaults['gfpgan'])
|
||||
if GFPGAN is None:
|
||||
gr.HTML("""
|
||||
if 'gfpgan' in user_defaults:
|
||||
gfpgan_defaults.update(user_defaults['gfpgan'])
|
||||
if GFPGAN is None:
|
||||
gr.HTML("""
|
||||
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
|
||||
<p><b> Please download GFPGAN to activate face fixing features</b>, instructions are available at the <a href='https://github.com/hlky/stable-diffusion-webui'>Github</a></p>
|
||||
</div>
|
||||
""")
|
||||
#gr.Markdown("")
|
||||
#gr.Markdown("<b> Please download GFPGAN to activate face fixing features</b>, instructions are available at the <a href='https://github.com/hlky/stable-diffusion-webui'>Github</a>")
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>GFPGAN Settings</b>")
|
||||
imgproc_gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Effect strength",
|
||||
value=gfpgan_defaults['strength'],visible=GFPGAN is not None)
|
||||
with gr.Box(visible=False) as upscale_group:
|
||||
# gr.Markdown("")
|
||||
# gr.Markdown("<b> Please download GFPGAN to activate face fixing features</b>, instructions are available at the <a href='https://github.com/hlky/stable-diffusion-webui'>Github</a>")
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>GFPGAN Settings</b>")
|
||||
imgproc_gfpgan_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.001,
|
||||
label="Effect strength",
|
||||
value=gfpgan_defaults['strength'],
|
||||
visible=GFPGAN is not None)
|
||||
with gr.Box(visible=False) as upscale_group:
|
||||
|
||||
if LDSR:
|
||||
upscaleModes = ['RealESRGAN','GoBig','Latent Diffusion SR','GoLatent ']
|
||||
else:
|
||||
gr.HTML("""
|
||||
if LDSR:
|
||||
upscaleModes = ['RealESRGAN', 'GoBig', 'Latent Diffusion SR', 'GoLatent ']
|
||||
else:
|
||||
gr.HTML("""
|
||||
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
|
||||
<p><b> Please download LDSR to activate more upscale features</b>, instructions are available at the <a href='https://github.com/hlky/stable-diffusion-webui'>Github</a></p>
|
||||
</div>
|
||||
""")
|
||||
upscaleModes = ['RealESRGAN','GoBig']
|
||||
upscaleModes = ['RealESRGAN', 'GoBig']
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>Upscaler Selection</b>")
|
||||
imgproc_upscale_toggles = gr.Radio(label='', choices=upscaleModes, type="index",
|
||||
visible=RealESRGAN is not None, value='RealESRGAN')
|
||||
with gr.Box(visible=False) as upscalerSettings_group:
|
||||
|
||||
with gr.Box(visible=True) as realesrgan_group:
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>Upscaler Selection</b>")
|
||||
imgproc_upscale_toggles = gr.Radio(label = '',choices=upscaleModes, type="index",visible=RealESRGAN is not None,value='RealESRGAN')
|
||||
with gr.Box(visible=False) as upscalerSettings_group:
|
||||
|
||||
with gr.Box(visible=True) as realesrgan_group:
|
||||
gr.Markdown("<b>RealESRGAN Settings</b>")
|
||||
imgproc_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model',
|
||||
interactive=RealESRGAN is not None,
|
||||
choices=['RealESRGAN_x4plus',
|
||||
'RealESRGAN_x4plus_anime_6B',
|
||||
'RealESRGAN_x2plus',
|
||||
'RealESRGAN_x2plus_anime_6B'],
|
||||
value='RealESRGAN_x4plus',
|
||||
visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
|
||||
with gr.Box(visible=False) as ldsr_group:
|
||||
with gr.Row(elem_id="ldsr_settings_row"):
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>RealESRGAN Settings</b>")
|
||||
imgproc_realesrgan_model_name = gr.Dropdown(label='RealESRGAN model', interactive=RealESRGAN is not None,
|
||||
choices= ['RealESRGAN_x4plus',
|
||||
'RealESRGAN_x4plus_anime_6B','RealESRGAN_x2plus',
|
||||
'RealESRGAN_x2plus_anime_6B'],
|
||||
value='RealESRGAN_x4plus',
|
||||
visible=RealESRGAN is not None) # TODO: Feels like I shouldnt slot it in here.
|
||||
with gr.Box(visible=False) as ldsr_group:
|
||||
with gr.Row(elem_id="ldsr_settings_row"):
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>Latent Diffusion Super Sampling Settings</b>")
|
||||
imgproc_ldsr_steps = gr.Slider(minimum=0, maximum=500, step=10, label="LDSR Sampling Steps",
|
||||
value=100,visible=LDSR is not None)
|
||||
imgproc_ldsr_pre_downSample = gr.Dropdown(label='LDSR Pre Downsample mode (Lower resolution before processing for speed)',
|
||||
choices=["None", '1/2', '1/4'],value="None",visible=LDSR is not None)
|
||||
imgproc_ldsr_post_downSample = gr.Dropdown(label='LDSR Post Downsample mode (aka SuperSampling)',
|
||||
choices=["None", "Original Size", '1/2', '1/4'],value="None",visible=LDSR is not None)
|
||||
with gr.Box(visible=False) as gobig_group:
|
||||
with gr.Row(elem_id="proc_prompt_row"):
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>GoBig Settings</b>")
|
||||
imgproc_prompt = gr.Textbox(label="",
|
||||
elem_id='prompt_input',
|
||||
placeholder="A corgi wearing a top hat as an oil painting.",
|
||||
lines=1,
|
||||
max_lines=1,
|
||||
value=imgproc_defaults['prompt'],
|
||||
show_label=True,
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_sampling = gr.Dropdown(label='Sampling method (k_lms is default k-diffusion sampler)',
|
||||
choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler',
|
||||
'k_heun', 'k_lms'],
|
||||
value=imgproc_defaults['sampler_name'],visible=RealESRGAN is not None)
|
||||
imgproc_steps = gr.Slider(minimum=1, maximum=250, step=1, label="Sampling Steps",
|
||||
value=imgproc_defaults['ddim_steps'],visible=RealESRGAN is not None)
|
||||
imgproc_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
|
||||
label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
|
||||
value=imgproc_defaults['cfg_scale'],visible=RealESRGAN is not None)
|
||||
imgproc_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising Strength',
|
||||
value=imgproc_defaults['denoising_strength'],visible=RealESRGAN is not None)
|
||||
imgproc_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
|
||||
value=imgproc_defaults["height"],visible=False) # not currently implemented
|
||||
imgproc_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
|
||||
value=imgproc_defaults["width"],visible=False) # not currently implemented
|
||||
imgproc_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1, max_lines=1,
|
||||
value=imgproc_defaults["seed"],visible=RealESRGAN is not None)
|
||||
imgproc_btn.click(
|
||||
imgproc,
|
||||
[imgproc_source, imgproc_folder,imgproc_prompt,imgproc_toggles,
|
||||
imgproc_upscale_toggles,imgproc_realesrgan_model_name,imgproc_sampling, imgproc_steps, imgproc_height,
|
||||
imgproc_width, imgproc_cfg, imgproc_denoising, imgproc_seed,imgproc_gfpgan_strength,imgproc_ldsr_steps,imgproc_ldsr_pre_downSample,imgproc_ldsr_post_downSample],
|
||||
[imgproc_output])
|
||||
gr.Markdown("<b>Latent Diffusion Super Sampling Settings</b>")
|
||||
imgproc_ldsr_steps = gr.Slider(minimum=0, maximum=500, step=10,
|
||||
label="LDSR Sampling Steps",
|
||||
value=100, visible=LDSR is not None)
|
||||
imgproc_ldsr_pre_downSample = gr.Dropdown(
|
||||
label='LDSR Pre Downsample mode (Lower resolution before processing for speed)',
|
||||
choices=["None", '1/2', '1/4'], value="None", visible=LDSR is not None)
|
||||
imgproc_ldsr_post_downSample = gr.Dropdown(
|
||||
label='LDSR Post Downsample mode (aka SuperSampling)',
|
||||
choices=["None", "Original Size", '1/2', '1/4'], value="None",
|
||||
visible=LDSR is not None)
|
||||
with gr.Box(visible=False) as gobig_group:
|
||||
with gr.Row(elem_id="proc_prompt_row"):
|
||||
with gr.Column():
|
||||
gr.Markdown("<b>GoBig Settings</b>")
|
||||
imgproc_prompt = gr.Textbox(label="",
|
||||
elem_id='prompt_input',
|
||||
placeholder="A corgi wearing a top hat as an oil painting.",
|
||||
lines=1,
|
||||
max_lines=1,
|
||||
value=imgproc_defaults['prompt'],
|
||||
show_label=True,
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_sampling = gr.Dropdown(
|
||||
label='Sampling method (k_lms is default k-diffusion sampler)',
|
||||
choices=["DDIM", 'k_dpm_2_a', 'k_dpm_2', 'k_euler_a', 'k_euler',
|
||||
'k_heun', 'k_lms'],
|
||||
value=imgproc_defaults['sampler_name'], visible=RealESRGAN is not None)
|
||||
imgproc_steps = gr.Slider(minimum=1, maximum=250, step=1,
|
||||
label="Sampling Steps",
|
||||
value=imgproc_defaults['ddim_steps'],
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_cfg = gr.Slider(minimum=1.0, maximum=30.0, step=0.5,
|
||||
label='Classifier Free Guidance Scale (how strongly the image should follow the prompt)',
|
||||
value=imgproc_defaults['cfg_scale'],
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_denoising = gr.Slider(minimum=0.0, maximum=1.0, step=0.01,
|
||||
label='Denoising Strength',
|
||||
value=imgproc_defaults['denoising_strength'],
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_height = gr.Slider(minimum=64, maximum=2048, step=64, label="Height",
|
||||
value=imgproc_defaults["height"],
|
||||
visible=False) # not currently implemented
|
||||
imgproc_width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width",
|
||||
value=imgproc_defaults["width"],
|
||||
visible=False) # not currently implemented
|
||||
imgproc_seed = gr.Textbox(label="Seed (blank to randomize)", lines=1,
|
||||
max_lines=1,
|
||||
value=imgproc_defaults["seed"],
|
||||
visible=RealESRGAN is not None)
|
||||
imgproc_btn.click(
|
||||
imgproc,
|
||||
[imgproc_source, imgproc_folder, imgproc_prompt, imgproc_toggles,
|
||||
imgproc_upscale_toggles, imgproc_realesrgan_model_name, imgproc_sampling,
|
||||
imgproc_steps, imgproc_height,
|
||||
imgproc_width, imgproc_cfg, imgproc_denoising, imgproc_seed,
|
||||
imgproc_gfpgan_strength, imgproc_ldsr_steps, imgproc_ldsr_pre_downSample,
|
||||
imgproc_ldsr_post_downSample],
|
||||
[imgproc_output])
|
||||
|
||||
imgproc_source.change(
|
||||
uifn.get_png_nfo,
|
||||
[imgproc_source],
|
||||
[imgproc_pngnfo] )
|
||||
imgproc_source.change(
|
||||
uifn.get_png_nfo,
|
||||
[imgproc_source],
|
||||
[imgproc_pngnfo])
|
||||
|
||||
output_txt2img_to_imglab.click(
|
||||
fn=uifn.copy_img_params_to_lab,
|
||||
inputs = [output_txt2img_params],
|
||||
outputs = [imgproc_prompt,imgproc_seed,imgproc_steps,imgproc_cfg,imgproc_sampling],
|
||||
)
|
||||
|
||||
output_txt2img_to_imglab.click(
|
||||
fn=uifn.copy_img_to_lab,
|
||||
inputs = [output_txt2img_gallery],
|
||||
outputs = [imgproc_source, tabs],
|
||||
_js=call_JS("moveImageFromGallery",
|
||||
fromId="txt2img_gallery_output",
|
||||
toId="imglab_input")
|
||||
)
|
||||
if RealESRGAN is None:
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
#seperator
|
||||
gr.HTML("""
|
||||
output_txt2img_to_imglab.click(
|
||||
fn=uifn.copy_img_params_to_lab,
|
||||
inputs=[output_txt2img_params],
|
||||
outputs=[imgproc_prompt, imgproc_seed, imgproc_steps, imgproc_cfg,
|
||||
imgproc_sampling],
|
||||
)
|
||||
|
||||
output_txt2img_to_imglab.click(
|
||||
fn=uifn.copy_img_to_lab,
|
||||
inputs=[output_txt2img_gallery],
|
||||
outputs=[imgproc_source, tabs],
|
||||
_js=call_JS("moveImageFromGallery",
|
||||
fromId="txt2img_gallery_output",
|
||||
toId="imglab_input")
|
||||
)
|
||||
if RealESRGAN is None:
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
# seperator
|
||||
gr.HTML("""
|
||||
<div id="90" style="max-width: 100%; font-size: 14px; text-align: center;" class="output-markdown gr-prose border-solid border border-gray-200 rounded gr-panel">
|
||||
<p><b> Please download RealESRGAN to activate upscale features</b>, instructions are available at the <a href='https://github.com/hlky/stable-diffusion-webui'>Github</a></p>
|
||||
</div>
|
||||
""")
|
||||
imgproc_toggles.change(fn=uifn.toggle_options_gfpgan, inputs=[imgproc_toggles], outputs=[gfpgan_group])
|
||||
imgproc_toggles.change(fn=uifn.toggle_options_upscalers, inputs=[imgproc_toggles], outputs=[upscale_group])
|
||||
imgproc_toggles.change(fn=uifn.toggle_options_upscalers, inputs=[imgproc_toggles], outputs=[upscalerSettings_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_realesrgan, inputs=[imgproc_upscale_toggles], outputs=[realesrgan_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_ldsr, inputs=[imgproc_upscale_toggles], outputs=[ldsr_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_gobig, inputs=[imgproc_upscale_toggles], outputs=[gobig_group])
|
||||
imgproc_toggles.change(fn=uifn.toggle_options_upscalers, inputs=[imgproc_toggles],
|
||||
outputs=[upscalerSettings_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_realesrgan, inputs=[imgproc_upscale_toggles],
|
||||
outputs=[realesrgan_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_ldsr, inputs=[imgproc_upscale_toggles],
|
||||
outputs=[ldsr_group])
|
||||
imgproc_upscale_toggles.change(fn=uifn.toggle_options_gobig, inputs=[imgproc_upscale_toggles],
|
||||
outputs=[gobig_group])
|
||||
|
||||
"""
|
||||
if GFPGAN is not None:
|
||||
|
||||
@ -11,7 +11,7 @@ def change_image_editor_mode(choice, cropped_image, masked_image, resize_mode, w
|
||||
update_image_result = update_image_mask(cropped_image, resize_mode, width, height)
|
||||
return [gr.update(visible=False), update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)]
|
||||
|
||||
update_image_result = update_image_mask(masked_image["image"], resize_mode, width, height)
|
||||
update_image_result = update_image_mask(masked_image["image"] if masked_image is not None else None, resize_mode, width, height)
|
||||
return [update_image_result, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)]
|
||||
|
||||
def update_image_mask(cropped_image, resize_mode, width, height):
|
||||
|
||||
59
webui.sh
Executable file
59
webui.sh
Executable file
@ -0,0 +1,59 @@
|
||||
#!/bin/bash
|
||||
#
|
||||
# Starts the gui using the conda env
|
||||
#
|
||||
|
||||
ENV_NAME="ldm"
|
||||
ENV_FILE="environment.yaml"
|
||||
ENV_UPDATED=0
|
||||
ENV_MODIFIED=$(date -r $ENV_FILE "+%s")
|
||||
ENV_MODIFED_FILE=".env_updated"
|
||||
if [[ -f $ENV_MODIFED_FILE ]]; then ENV_MODIFIED_CACHED=$(<${ENV_MODIFED_FILE}); else ENV_MODIFIED_CACHED=0; fi
|
||||
|
||||
# Set conda path if it is not already in default environment
|
||||
custom_conda_path=
|
||||
|
||||
# Allow setting custom path via file to allow updates of this script without undoing custom path
|
||||
if [ -f custom-conda-path.txt ]; then
|
||||
custom_conda_path=$(cat custom-conda-path.txt)
|
||||
fi
|
||||
|
||||
# If custom path is set above, try to setup conda environment
|
||||
if [ -f "${custom_conda_path}/etc/profile.d/conda.sh" ]; then
|
||||
. "${custom_conda_path}/etc/profile.d/conda.sh"
|
||||
elif [ -n "${custom_conda_path}" ] && [ -f "${custom_conda_path}/bin" ]; then
|
||||
export PATH="${custom_conda_path}/bin:$PATH"
|
||||
fi
|
||||
|
||||
if ! command -v conda >/dev/null; then
|
||||
echo "anaconda3/miniconda3 not found. Install from here https://docs.conda.io/en/latest/miniconda.html"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Create/update conda env if needed
|
||||
if ! conda env list | grep ".*${ENV_NAME}.*" >/dev/null 2>&1; then
|
||||
echo "Could not find conda env: ${ENV_NAME} ... creating ..."
|
||||
conda env create -f $ENV_FILE
|
||||
ENV_UPDATED=1
|
||||
elif [[ ! -z $CONDA_FORCE_UPDATE && $CONDA_FORCE_UPDATE == "true" ]] || (( $ENV_MODIFIED > $ENV_MODIFIED_CACHED )); then
|
||||
echo "Updating conda env: ${ENV_NAME} ..."
|
||||
conda env update --file $ENV_FILE --prune
|
||||
ENV_UPDATED=1
|
||||
fi
|
||||
|
||||
# Clear artifacts from conda after create/update
|
||||
if (( $ENV_UPDATED > 0 )); then
|
||||
conda clean --all
|
||||
echo -n $ENV_MODIFIED > $ENV_MODIFED_FILE
|
||||
fi
|
||||
|
||||
# Activate conda environment
|
||||
conda activate $ENV_NAME
|
||||
conda info | grep active
|
||||
|
||||
if [ ! -e "models/ldm/stable-diffusion-v1/model.ckpt" ]; then
|
||||
echo "Your model file does not exist! Place it in 'models/ldm/stable-diffusion-v1' with the name 'model.ckpt'."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
python scripts/relauncher.py
|
||||
Loading…
Reference in New Issue
Block a user