Merge branch 'master' into patch-6
This commit is contained in:
AUTOMATIC1111
GitHub
commit
013e9a4bda
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@ -20,6 +20,8 @@ A browser interface based on Gradio library for Stable Diffusion.
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- CodeFormer, face restoration tool as an alternative to GFPGAN
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network with a lot of third party models
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- SwinIR, neural network upscaler
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Interrupt processing at any time
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@ -41,6 +43,10 @@ A browser interface based on Gradio library for Stable Diffusion.
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- Seed resizing
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- CLIP interrogator
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- Prompt Editing
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- Batch Processing
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- Img2img Alternative
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- Highres Fix
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- LDSR Upscaling
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## Installation and Running
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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.
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@ -79,6 +85,8 @@ The documentation was moved from this README over to the project's [wiki](https:
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- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- CodeFormer - https://github.com/sczhou/CodeFormer
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- SwinIR - https://github.com/JingyunLiang/SwinIR
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- LDSR - https://github.com/Hafiidz/latent-diffusion
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- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
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- Doggettx - Cross Attention layer optimization - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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@ -1,27 +1,33 @@
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// code related to showing and updating progressbar shown as the image is being made
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global_progressbar = null
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onUiUpdate(function(){
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progressbar = gradioApp().getElementById('progressbar')
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progressbar = gradioApp().getElementById('progressbar')
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progressDiv = gradioApp().querySelectorAll('.progressDiv').length > 0;
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interrupt = gradioApp().getElementById('interrupt')
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if(progressbar!= null && progressbar != global_progressbar){
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global_progressbar = progressbar
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var mutationObserver = new MutationObserver(function(m){
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txt2img_preview = gradioApp().getElementById('txt2img_preview')
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txt2img_gallery = gradioApp().getElementById('txt2img_gallery')
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img2img_preview = gradioApp().getElementById('img2img_preview')
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img2img_gallery = gradioApp().getElementById('img2img_gallery')
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if(txt2img_preview != null && txt2img_gallery != null){
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txt2img_preview.style.width = txt2img_gallery.clientWidth + "px"
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txt2img_preview.style.height = txt2img_gallery.clientHeight + "px"
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txt2img_preview.style.height = txt2img_gallery.clientHeight + "px"
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if(!progressDiv){
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interrupt.style.display = "none"
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}
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}
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if(img2img_preview != null && img2img_gallery != null){
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img2img_preview.style.width = img2img_gallery.clientWidth + "px"
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img2img_preview.style.height = img2img_gallery.clientHeight + "px"
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img2img_preview.style.height = img2img_gallery.clientHeight + "px"
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if(!progressDiv){
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interrupt.style.display = "none"
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}
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}
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window.setTimeout(requestMoreProgress, 500)
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@ -29,12 +35,15 @@ onUiUpdate(function(){
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mutationObserver.observe( progressbar, { childList:true, subtree:true })
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}
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})
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function requestMoreProgress(){
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btn = gradioApp().getElementById("check_progress");
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if(btn==null) return;
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btn.click();
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progressDiv = gradioApp().querySelectorAll('.progressDiv').length > 0;
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if(progressDiv){
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interrupt.style.display = "block"
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}
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}
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function requestProgress(){
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@ -43,4 +52,3 @@ function requestProgress(){
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btn.click();
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}
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@ -1,17 +1,66 @@
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import sys
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import traceback
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from collections import namedtuple
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import numpy as np
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from PIL import Image
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from realesrgan import RealESRGANer
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import modules.images
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from modules.shared import cmd_opts, opts
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RealesrganModelInfo = namedtuple("RealesrganModelInfo", ["name", "location", "model", "netscale"])
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realesrgan_models = []
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have_realesrgan = False
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RealESRGANer_constructor = None
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def get_realesrgan_models():
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try:
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from basicsr.archs.rrdbnet_arch import RRDBNet
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from realesrgan import RealESRGANer
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from realesrgan.archs.srvgg_arch import SRVGGNetCompact
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models = [
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RealesrganModelInfo(
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name="Real-ESRGAN General x4x3",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
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netscale=4,
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model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
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),
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RealesrganModelInfo(
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name="Real-ESRGAN General WDN x4x3",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
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netscale=4,
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model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
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),
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RealesrganModelInfo(
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name="Real-ESRGAN AnimeVideo",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth",
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netscale=4,
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model=lambda: SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16, upscale=4, act_type='prelu')
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),
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RealesrganModelInfo(
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name="Real-ESRGAN 4x plus",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
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netscale=4,
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model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
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),
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RealesrganModelInfo(
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name="Real-ESRGAN 4x plus anime 6B",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
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netscale=4,
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model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
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),
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RealesrganModelInfo(
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name="Real-ESRGAN 2x plus",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
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netscale=2,
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model=lambda: RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=2)
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),
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]
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return models
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except Exception as e:
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print("Error makeing Real-ESRGAN midels list:", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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class UpscalerRealESRGAN(modules.images.Upscaler):
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@ -27,35 +76,18 @@ class UpscalerRealESRGAN(modules.images.Upscaler):
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def setup_realesrgan():
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global realesrgan_models
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global have_realesrgan
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global RealESRGANer_constructor
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try:
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from basicsr.archs.rrdbnet_arch import RRDBNet
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from realesrgan import RealESRGANer
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from realesrgan.archs.srvgg_arch import SRVGGNetCompact
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realesrgan_models = [
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RealesrganModelInfo(
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name="Real-ESRGAN 4x plus",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth",
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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)
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),
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RealesrganModelInfo(
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name="Real-ESRGAN 4x plus anime 6B",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth",
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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)
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),
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RealesrganModelInfo(
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name="Real-ESRGAN 2x plus",
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location="https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth",
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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)
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),
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]
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realesrgan_models = get_realesrgan_models()
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have_realesrgan = True
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RealESRGANer_constructor = RealESRGANer
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for i, model in enumerate(realesrgan_models):
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modules.shared.sd_upscalers.append(UpscalerRealESRGAN(model.netscale, i))
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if model.name in opts.realesrgan_enabled_models:
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modules.shared.sd_upscalers.append(UpscalerRealESRGAN(model.netscale, i))
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except Exception:
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print("Error importing Real-ESRGAN:", file=sys.stderr)
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@ -66,13 +98,13 @@ def setup_realesrgan():
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def upscale_with_realesrgan(image, RealESRGAN_upscaling, RealESRGAN_model_index):
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if not have_realesrgan or RealESRGANer_constructor is None:
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if not have_realesrgan:
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return image
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info = realesrgan_models[RealESRGAN_model_index]
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model = info.model()
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upsampler = RealESRGANer_constructor(
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upsampler = RealESRGANer(
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scale=info.netscale,
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model_path=info.location,
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model=model,
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@ -95,6 +95,11 @@ face_restorers = []
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modules.sd_models.list_models()
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def realesrgan_models_names():
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import modules.realesrgan_model
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return [x.name for x in modules.realesrgan_model.get_realesrgan_models()]
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class Options:
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class OptionInfo:
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def __init__(self, default=None, label="", component=None, component_args=None, onchange=None):
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@ -142,14 +147,12 @@ class Options:
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"save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
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"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
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"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
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"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()}),
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"SWIN_tile": OptionInfo(192, "Tile size for all SwinIR.", gr.Slider, {"minimum": 16, "maximum": 512, "step": 16}),
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"SWIN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SwinIR. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
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"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster",
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gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
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"ldsr_pre_down":OptionInfo(1, "LDSR Pre-process downssample scale. 1 = no down-sampling, 4 = 1/4 scale.",
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gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
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"ldsr_post_down":OptionInfo(1, "LDSR Post-process down-sample scale. 1 = no down-sampling, 4 = 1/4 scale.",
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gr.Slider, {"minimum": 1, "maximum": 4, "step": 1}),
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"ldsr_steps": OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}),
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"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}),
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"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}),
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"random_artist_categories": OptionInfo([], "Allowed categories for random artists selection when using the Roll button", gr.CheckboxGroup, {"choices": artist_db.categories()}),
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"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}),
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"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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|
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@ -350,8 +350,15 @@ def create_toprow(is_img2img):
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with gr.Column(scale=1):
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with gr.Row():
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interrupt = gr.Button('Interrupt', elem_id="interrupt")
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submit = gr.Button('Generate', elem_id="generate", variant='primary')
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interrupt.click(
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fn=lambda: shared.state.interrupt(),
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inputs=[],
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outputs=[],
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)
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with gr.Row():
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if is_img2img:
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interrogate = gr.Button('Interrogate', elem_id="interrogate")
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@ -386,6 +393,15 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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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)
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dummy_component = gr.Label(visible=False)
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with gr.Row(elem_id='progressRow'):
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with gr.Column(scale=1):
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columnEmpty = "Empty"
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with gr.Column(scale=1):
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progressbar = gr.HTML(elem_id="progressbar")
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txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
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setup_progressbar(progressbar, txt2img_preview)
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with gr.Row().style(equal_height=False):
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with gr.Column(variant='panel'):
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steps = gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=20)
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|
|
@ -416,21 +432,17 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
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custom_inputs = modules.scripts.scripts_txt2img.setup_ui(is_img2img=False)
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with gr.Column(variant='panel'):
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progressbar = gr.HTML(elem_id="progressbar")
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with gr.Group():
|
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txt2img_preview = gr.Image(elem_id='txt2img_preview', visible=False)
|
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txt2img_gallery = gr.Gallery(label='Output', elem_id='txt2img_gallery').style(grid=4)
|
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setup_progressbar(progressbar, txt2img_preview)
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|
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with gr.Group():
|
||||
with gr.Row():
|
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save = gr.Button('Save')
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send_to_img2img = gr.Button('Send to img2img')
|
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send_to_inpaint = gr.Button('Send to inpaint')
|
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send_to_extras = gr.Button('Send to extras')
|
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interrupt = gr.Button('Interrupt')
|
||||
|
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with gr.Group():
|
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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()]",
|
||||
|
|
|
|||
|
|
@ -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
|
||||
27
style.css
27
style.css
|
|
@ -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;
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue