Merge branch 'master' into patch-6

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AUTOMATIC1111 2022-09-22 08:15:22 +03:00 committed by GitHub
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7 changed files with 143 additions and 71 deletions

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@ -20,6 +20,8 @@ A browser interface based on Gradio library for Stable Diffusion.
- CodeFormer, face restoration tool as an alternative to GFPGAN
- RealESRGAN, neural network upscaler
- ESRGAN, neural network with a lot of third party models
- SwinIR, neural network upscaler
- LDSR, Latent diffusion super resolution upscaling
- Resizing aspect ratio options
- Sampling method selection
- Interrupt processing at any time
@ -41,6 +43,10 @@ A browser interface based on Gradio library for Stable Diffusion.
- Seed resizing
- CLIP interrogator
- Prompt Editing
- Batch Processing
- Img2img Alternative
- Highres Fix
- LDSR Upscaling
## Installation and Running
Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
@ -79,6 +85,8 @@ The documentation was moved from this README over to the project's [wiki](https:
- GFPGAN - https://github.com/TencentARC/GFPGAN.git
- CodeFormer - https://github.com/sczhou/CodeFormer
- ESRGAN - https://github.com/xinntao/ESRGAN
- SwinIR - https://github.com/JingyunLiang/SwinIR
- LDSR - https://github.com/Hafiidz/latent-diffusion
- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
- Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd

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@ -1,27 +1,33 @@
// code related to showing and updating progressbar shown as the image is being made
global_progressbar = null
onUiUpdate(function(){
progressbar = gradioApp().getElementById('progressbar')
progressbar = gradioApp().getElementById('progressbar')
progressDiv = gradioApp().querySelectorAll('.progressDiv').length > 0;
interrupt = gradioApp().getElementById('interrupt')
if(progressbar!= null && progressbar != global_progressbar){
global_progressbar = progressbar
var mutationObserver = new MutationObserver(function(m){
txt2img_preview = gradioApp().getElementById('txt2img_preview')
txt2img_gallery = gradioApp().getElementById('txt2img_gallery')
img2img_preview = gradioApp().getElementById('img2img_preview')
img2img_gallery = gradioApp().getElementById('img2img_gallery')
if(txt2img_preview != null && txt2img_gallery != null){
txt2img_preview.style.width = txt2img_gallery.clientWidth + "px"
txt2img_preview.style.height = txt2img_gallery.clientHeight + "px"
txt2img_preview.style.height = txt2img_gallery.clientHeight + "px"
if(!progressDiv){
interrupt.style.display = "none"
}
}
if(img2img_preview != null && img2img_gallery != null){
img2img_preview.style.width = img2img_gallery.clientWidth + "px"
img2img_preview.style.height = img2img_gallery.clientHeight + "px"
img2img_preview.style.height = img2img_gallery.clientHeight + "px"
if(!progressDiv){
interrupt.style.display = "none"
}
}
window.setTimeout(requestMoreProgress, 500)
@ -29,12 +35,15 @@ onUiUpdate(function(){
mutationObserver.observe( progressbar, { childList:true, subtree:true })
}
})
function requestMoreProgress(){
btn = gradioApp().getElementById("check_progress");
if(btn==null) return;
btn.click();
progressDiv = gradioApp().querySelectorAll('.progressDiv').length > 0;
if(progressDiv){
interrupt.style.display = "block"
}
}
function requestProgress(){
@ -43,4 +52,3 @@ function requestProgress(){
btn.click();
}

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@ -1,17 +1,66 @@
import sys
import traceback
from collections import namedtuple
import numpy as np
from PIL import Image
from realesrgan import RealESRGANer
import modules.images
from modules.shared import cmd_opts, opts
RealesrganModelInfo = namedtuple("RealesrganModelInfo", ["name", "location", "model", "netscale"])
realesrgan_models = []
have_realesrgan = False
RealESRGANer_constructor = None
def get_realesrgan_models():
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
models = [
RealesrganModelInfo(
name="Real-ESRGAN General x4x3",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN General WDN x4x3",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN AnimeVideo",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth",
netscale=4,
model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
netscale=4,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus anime 6B",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
netscale=4,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 2x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
netscale=2,
model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
),
]
return models
except Exception as e:
print("Error makeing Real-ESRGAN midels list:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
class UpscalerRealESRGAN(modules.images.Upscaler):
@ -27,35 +76,18 @@ class UpscalerRealESRGAN(modules.images.Upscaler):
def setup_realesrgan():
global realesrgan_models
global have_realesrgan
global RealESRGANer_constructor
try:
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
from realesrgan.archs.srvgg_arch import SRVGGNetCompact
realesrgan_models = [
RealesrganModelInfo(
name="Real-ESRGAN 4x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
netscale=4, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 4x plus anime 6B",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
netscale=4, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
),
RealesrganModelInfo(
name="Real-ESRGAN 2x plus",
location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
netscale=2, model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
),
]
realesrgan_models = get_realesrgan_models()
have_realesrgan = True
RealESRGANer_constructor = RealESRGANer
for i, model in enumerate(realesrgan_models):
modules.shared.sd_upscalers.append(UpscalerRealESRGAN(model.netscale, i))
if model.name in opts.realesrgan_enabled_models:
modules.shared.sd_upscalers.append(UpscalerRealESRGAN(model.netscale, i))
except Exception:
print("Error importing Real-ESRGAN:", file=sys.stderr)
@ -66,13 +98,13 @@ def setup_realesrgan():
def upscale_with_realesrgan(image, RealESRGAN_upscaling, RealESRGAN_model_index):
if not have_realesrgan or RealESRGANer_constructor is None:
if not have_realesrgan:
return image
info = realesrgan_models[RealESRGAN_model_index]
model = info.model()
upsampler = RealESRGANer_constructor(
upsampler = RealESRGANer(
scale=info.netscale,
model_path=info.location,
model=model,

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@ -95,6 +95,11 @@ face_restorers = []
modules.sd_models.list_models()
def realesrgan_models_names():
import modules.realesrgan_model
return [x.name for x in modules.realesrgan_model.get_realesrgan_models()]
class Options:
class OptionInfo:
def __init__(self, default=None, label="", component=None, component_args=None, onchange=None):
@ -142,14 +147,12 @@ class Options:
"save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
"realesrgan_enabled_models": OptionInfo(["Real-ESRGAN 4x plus", "Real-ESRGAN 4x plus anime 6B"],"Select which RealESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": realesrgan_models_names()}),
"SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),
"SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster",
gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
"ldsr_pre_down":OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.",
gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_post_down":OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.",
gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
"ldsr_pre_down":OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"ldsr_post_down":OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.", gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
"upscale_at_full_resolution_padding": OptionInfo(16, "Inpainting at full resolution: padding, in pixels, for the masked region.", gr.Slider, {"minimum": 0, "maximum": 128, "step": 4}),
"upscaler_for_hires_fix": OptionInfo(None, "Upscaler for highres. fix", gr.Radio, lambda: {"choices": [x.name for x in sd_upscalers]}),

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@ -350,8 +350,15 @@ def create_toprow(is_img2img):
with gr.Column(scale=1):
with gr.Row():
interrupt = gr.Button('Interrupt', elem_id="interrupt")
submit = gr.Button('Generate', elem_id="generate", variant='primary')
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
with gr.Row():
if is_img2img:
interrogate = gr.Button('Interrogate', elem_id="interrogate")
@ -386,6 +393,15 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
txt2img_prompt, roll, txt2img_prompt_style, txt2img_negative_prompt, txt2img_prompt_style2, submit, _, txt2img_prompt_style_apply, txt2img_save_style = create_toprow(is_img2img=False)
dummy_component = gr.Label(visible=False)
with gr.Row(elem_id='progressRow'):
with gr.Column(scale=1):
columnEmpty = "Empty"
with gr.Column(scale=1):
progressbar = gr.HTML(elem_id="progressbar")
txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
setup_progressbar(progressbar, txt2img_preview)
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
@ -416,21 +432,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
with gr.Column(variant='panel'):
progressbar = gr.HTML(elem_id="progressbar")
with gr.Group():
txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery').style(grid=4)
setup_progressbar(progressbar, txt2img_preview)
with gr.Group():
with gr.Row():
save = gr.Button('Save')
send_to_img2img = gr.Button('Send to img2img')
send_to_inpaint = gr.Button('Send to inpaint')
send_to_extras = gr.Button('Send to extras')
interrupt = gr.Button('Interrupt')
with gr.Group():
html_info = gr.HTML()
@ -479,12 +491,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
outputs=[hr_options],
)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
_js="(x, y, z) => [x, y, selected_gallery_index()]",
@ -513,6 +519,15 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Blocks(analytics_enabled=False) as img2img_interface:
img2img_prompt, roll, img2img_prompt_style, img2img_negative_prompt, img2img_prompt_style2, submit, img2img_interrogate, img2img_prompt_style_apply, img2img_save_style = create_toprow(is_img2img=True)
with gr.Row(elem_id='progressRow'):
with gr.Column(scale=1):
columnEmpty = "Empty"
with gr.Column(scale=1):
progressbar = gr.HTML(elem_id="progressbar")
img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
setup_progressbar(progressbar, img2img_preview)
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Group():
@ -561,21 +576,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
custom_inputs = modules.scripts.scripts_img2img.setup_ui(is_img2img=True)
with gr.Column(variant='panel'):
progressbar = gr.HTML(elem_id="progressbar")
with gr.Group():
img2img_preview = gr.Image(elem_id='img2img_preview', visible=False)
img2img_gallery = gr.Gallery(label='Output', elem_id='img2img_gallery').style(grid=4)
setup_progressbar(progressbar, img2img_preview)
with gr.Group():
with gr.Row():
save = gr.Button('Save')
img2img_send_to_img2img = gr.Button('Send to img2img')
img2img_send_to_inpaint = gr.Button('Send to inpaint')
img2img_send_to_extras = gr.Button('Send to extras')
interrupt = gr.Button('Interrupt')
img2img_save_style = gr.Button('Save prompt as style')
@ -689,12 +700,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
outputs=[img2img_prompt],
)
interrupt.click(
fn=lambda: shared.state.interrupt(),
inputs=[],
outputs=[],
)
save.click(
fn=wrap_gradio_call(save_files),
_js="(x, y, z) => [x, y, selected_gallery_index()]",

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@ -1,18 +1,17 @@
transformers==4.19.2
diffusers==0.2.4
basicsr==1.3.5
gfpgan
diffusers==0.3.0
basicsr==1.4.2
gfpgan==1.3.8
gradio==3.3.1
numpy==1.23.3
Pillow==9.2.0
realesrgan==0.2.5.0
realesrgan==0.3.0
torch
transformers==4.19.2
omegaconf==2.1.1
pytorch_lightning==1.7.2
omegaconf==2.2.3
pytorch_lightning==1.7.6
scikit-image==0.19.2
fonts
font-roboto
timm==0.4.12
fairscale==0.4.4
timm==0.6.7
fairscale==0.4.9
piexif==1.1.3

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@ -86,7 +86,7 @@
}
#style_pos_col, #style_neg_col{
min-width: 4em !important;
min-width: 8em !important;
}
#style_index, #style2_index{
@ -208,11 +208,19 @@ input[type="range"]{
position: absolute;
z-index: 1000;
right: 0;
padding-left: 5px;
padding-right: 5px;
display: block;
}
#progressRow{
margin-bottom: 10px;
margin-top: -18px;
}
.progressDiv{
width: 100%;
height: 30px;
height: 20px;
background: #b4c0cc;
border-radius: 8px;
}
@ -223,11 +231,11 @@ input[type="range"]{
.progressDiv .progress{
width: 0%;
height: 30px;
height: 20px;
background: #0060df;
color: white;
font-weight: bold;
line-height: 30px;
line-height: 20px;
padding: 0 8px 0 0;
text-align: right;
border-radius: 8px;
@ -337,5 +345,14 @@ input[type="range"]{
background:rgba(255, 0, 0, 0.3);
z-index: 900;
pointer-events:none;
display:none;
display:none
}
#interrupt{
position: absolute;
width: 100%;
height: 72px;
background: #b4c0cc;
border-radius: 8px;
display: none;
}