mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
change onboarding and remove download default model
This commit is contained in:
Vladimir Mandic
+5
-1
@@ -1,6 +1,6 @@
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# Change Log for SD.Next
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## Update for 2023-12-25
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## Update for 2023-12-26
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*Note*: based on `diffusers==0.25.0.dev0`
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@@ -52,6 +52,9 @@
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- allow setting of resize method directly in image tab
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(previously via settings -> upscaler_for_img2img)
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- **General**
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- new **onboarding**
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if no models are found during startup, app will no longer ask to download default checkpoint
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instead, it will show message in UI with options to change model path or download any of the reference checkpoints
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- support for **Torch 2.1.2**
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- **Process** create videos from batch or folder processing
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supports *GIF*, *PNG* and *MP4* with full interpolation, scene change detection, etc.
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@@ -98,6 +101,7 @@
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- **chaiNNer** fix `NaN` issues due to autocast
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- **Upscale** increase limit from 4x to 8x given the quality of some upscalers
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- **Extra Networks** fix sort
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- reduced default **CFG scale** from 6 to 4 to be more out-of-the-box compatibile with LCM/Turbo models
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- disable google fonts check on server startup
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- fix torchvision/basicsr compatibility
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- fix styles quick save
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+1
-1
@@ -32,5 +32,5 @@ Any code commit is validated before merge
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- Download extensions and themes indexes from automatically updated indexes
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- Download required packages and repositories from GitHub during installation/upgrade
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- Download installed/enabled extensions
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- Download default model from official repository
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- Download models from CivitAI and/or Huggingface when instructed by user
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- Submit benchmark info upon user interaction
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+6
-5
@@ -43,17 +43,18 @@
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"tabs": [
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{"id":"","label":"Text","localized":"","hint":"Create image from text"},
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{"id":"","label":"Image","localized":"","hint":"Create image from image"},
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{"id":"","label":"Control","localized":"","hint":"Create image with additional control"},
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{"id":"","label":"Process","localized":"","hint":"Process existing image"},
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{"id":"","label":"Train","localized":"","hint":"Run training or model merging"},
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{"id":"","label":"Interrogate","localized":"","hint":"Run interrogate to get description of your image"},
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{"id":"","label":"Train","localized":"","hint":"Run training"},
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{"id":"","label":"Models","localized":"","hint":"Convert or merge your models"},
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{"id":"","label":"Interrogator","localized":"","hint":"Run interrogate to get description of your image"},
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{"id":"","label":"System Info","localized":"","hint":"System information"},
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{"id":"","label":"Agent Scheduler","localized":"","hint":"Enqueue your generate requests and run them in the background"},
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{"id":"","label":"Image Browser","localized":"","hint":"Browse through your generated image database"},
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{"id":"","label":"System","localized":"","hint":"System settings and information"},
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{"id":"","label":"System Info","localized":"","hint":"System information"},
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{"id":"","label":"Settings","localized":"","hint":"Application settings"},
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{"id":"","label":"Extensions","localized":"","hint":"Application extensions"},
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{"id":"","label":"Script","localized":"","hint":"Addtional scripts to be used"}
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{"id":"","label":"Script","localized":"","hint":"Addtional scripts to be used"},
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{"id":"","label":"Extensions","localized":"","hint":"Application extensions"}
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],
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"action panel": [
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{"id":"","label":"Generate","localized":"","hint":"Start processing"},
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@@ -1,4 +1,24 @@
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{
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"DreamShaper SD 1.5 v8": {
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"path": "dreamshaper_8.safetensors@https://civitai.com/api/download/models/128713",
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"desc": "Showcase finetuned model based on Stable diffusion 1.5",
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"preview": "dreamshaper_8.jpg"
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},
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"DreamShaper SD XL Turbo": {
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"path": "dreamshaperXL_turboDpmppSDE.safetensors@https://civitai.com/api/download/models/251662",
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"desc": "Showcase finetuned model based on Stable diffusion XL",
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"preview": "dreamshaperXL_turboDpmppSDE.jpg"
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},
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"Juggernaut Reborn": {
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"path": "juggernaut_reborn.safetensors@https://civitai.com/api/download/models/274039",
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"desc": "Showcase finetuned model based on Stable diffusion 1.5",
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"preview": "juggernaut_reborn.jpg"
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},
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"Juggernaut XL v7 RunDiffusion": {
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"path": "juggernautXL_v7Rundiffusion.safetensors@https://civitai.com/api/download/models/240840",
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"desc": "Showcase finetuned model based on Stable diffusion XL",
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"preview": "juggernautXL_v7Rundiffusion.jpg"
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},
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"RunwayML SD 1.5": {
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"path": "runwayml/stable-diffusion-v1-5",
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"desc": "Stable Diffusion 1.5 is the base model all other 1.5 checkpoint were trained from. It's a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. The Stable-Diffusion-v1-5 checkpoint was initialized with the weights of the Stable-Diffusion-v1-2 checkpoint and subsequently fine-tuned on 595k steps at resolution 512x512.",
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+1
-1
@@ -363,7 +363,7 @@ def check_torch():
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log.debug(f'Torch allowed: cuda={allow_cuda} rocm={allow_rocm} ipex={allow_ipex} diml={allow_directml} openvino={allow_openvino}')
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torch_command = os.environ.get('TORCH_COMMAND', '')
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xformers_package = os.environ.get('XFORMERS_PACKAGE', 'none')
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install('onnxruntime', 'onnxruntime', ignore=True)
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install('onnxruntime onnxruntimegpu', 'onnxruntime', ignore=True)
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if torch_command != '':
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pass
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elif allow_cuda and (shutil.which('nvidia-smi') is not None or args.use_xformers or os.path.exists(os.path.join(os.environ.get('SystemRoot') or r'C:\Windows', 'System32', 'nvidia-smi.exe'))):
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@@ -263,6 +263,9 @@ table.settings-value-table td { padding: 0.4em; border: 1px solid #ccc; max-widt
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.processor-settings { padding: 0 !important; max-width: 300px; }
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.processor-group>div { flex-flow: wrap;gap: 1em; }
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/* main info */
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.main-info { font-weight: var(--section-header-text-weight); color: var(--body-text-color-subdued); padding: 1em !important; margin-top: 2em !important; line-height: var(--line-lg) !important; }
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/* loader */
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.splash { position: fixed; top: 0; left: 0; width: 100vw; height: 100vh; z-index: 1000; display: block; text-align: center; }
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.motd { margin-top: 2em; color: var(--body-text-color-subdued); font-family: monospace; font-variant: all-petite-caps; }
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+37
-2
@@ -108,7 +108,7 @@ onAfterUiUpdate(async () => {
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const settingsSearch = gradioApp().querySelectorAll('#settings_search > label > textarea')[0];
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settingsSearch.oninput = (e) => {
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setTimeout(() => {
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log('settingsSearch', e.target.value)
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log('settingsSearch', e.target.value);
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showAllSettings();
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gradioApp().querySelectorAll('#tab_settings .tabitem').forEach((section) => {
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section.querySelectorAll('.dirtyable').forEach((setting) => {
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@@ -129,6 +129,40 @@ onOptionsChanged(() => {
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});
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});
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async function initModels() {
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const warn = () => `
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<p style='color: white'>No models available</p>
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- Select a model from reference list to download or<br>
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- Set model path to a folder containing your models<br>
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Current model path: ${opts.ckpt_dir}<br>
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`;
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const el = gradioApp().getElementById('main_info');
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const en = gradioApp().getElementById('txt2img_extra_networks');
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if (!el || !en) return;
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const req = await fetch('/sdapi/v1/sd-models');
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const res = req.ok ? await req.json() : [];
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log('initModels', res.length);
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const ready = () => `
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<p style='color: white'>Ready</p>
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${res.length} models available<br>
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`;
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el.innerHTML = res.length > 0 ? ready() : warn();
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el.style.display = 'block';
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setTimeout(() => el.style.display = 'none', res.length === 0 ? 30000 : 1500);
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if (res.length === 0) {
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if (en.classList.contains('hide')) gradioApp().getElementById('txt2img_extra_networks_btn').click();
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const repeat = setInterval(() => {
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const buttons = Array.from(gradioApp().querySelectorAll('#txt2img_model_subdirs > button')) || [];
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const reference = buttons.find((b) => b.innerText === 'Reference');
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if (reference) {
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clearInterval(repeat);
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reference.click();
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log('enReferenceSelect');
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}
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}, 100);
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}
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}
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function initSettings() {
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if (settingsInitialized) return;
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settingsInitialized = true;
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@@ -138,7 +172,7 @@ function initSettings() {
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const observer = new MutationObserver((mutations) => {
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const showAllPages = gradioApp().getElementById('settings_show_all_pages');
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if (showAllPages.style.display === 'none') return;
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const mutation = (mut) => mut.type === 'attributes' && mut.attributeName === 'style'
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const mutation = (mut) => mut.type === 'attributes' && mut.attributeName === 'style';
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if (mutations.some(mutation)) showAllSettings();
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});
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const tabContentWrapper = document.createElement('div');
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@@ -155,3 +189,4 @@ function initSettings() {
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}
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onUiLoaded(initSettings);
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onUiLoaded(initModels);
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+12
-12
@@ -9,12 +9,12 @@ from PIL import Image
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from modules.control import util
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from modules.control import unit
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from modules.control import processors
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from modules.control import controlnets # lllyasviel ControlNet
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from modules.control import controlnetsxs # VisLearn ControlNet-XS
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from modules.control import controlnetslite # Kohya ControlLLLite
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from modules.control import adapters # TencentARC T2I-Adapter
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from modules.control import reference # ControlNet-Reference
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from modules.control import ipadapter # IP-Adapter
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from modules.control.units import controlnet # lllyasviel ControlNet
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from modules.control.units import xs # VisLearn ControlNet-XS
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from modules.control.units import lite # Kohya ControlLLLite
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from modules.control.units import t2iadapter # TencentARC T2I-Adapter
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from modules.control.units import reference # ControlNet-Reference
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from modules.control.units import ipadapter # IP-Adapter
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from modules import devices, shared, errors, processing, images, sd_models, sd_samplers
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@@ -77,7 +77,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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inputs = [None]
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output_images: List[Image.Image] = [] # output images
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active_process: List[processors.Processor] = [] # all active preprocessors
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active_model: List[Union[controlnets.ControlNet, controlnetsxs.ControlNetXS, adapters.Adapter]] = [] # all active models
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active_model: List[Union[controlnet.ControlNet, xs.ControlNetXS, t2iadapter.Adapter]] = [] # all active models
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active_strength: List[float] = [] # strength factors for all active models
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active_start: List[float] = [] # start step for all active models
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active_end: List[float] = [] # end step for all active models
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@@ -177,7 +177,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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p.ops.append('control')
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has_models = False
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selected_models: List[Union[controlnets.ControlNetModel, controlnetsxs.ControlNetXSModel, adapters.AdapterModel]] = None
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selected_models: List[Union[controlnet.ControlNetModel, xs.ControlNetXSModel, t2iadapter.AdapterModel]] = None
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if unit_type == 'adapter' or unit_type == 'controlnet' or unit_type == 'xs' or unit_type == 'lite':
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if len(active_model) == 0:
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selected_models = None
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@@ -198,7 +198,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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p.extra_generation_params["Control mode"] = 'Adapter'
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p.extra_generation_params["Control conditioning"] = use_conditioning
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p.task_args['adapter_conditioning_scale'] = use_conditioning
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instance = adapters.AdapterPipeline(selected_models, shared.sd_model)
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instance = t2iadapter.AdapterPipeline(selected_models, shared.sd_model)
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pipe = instance.pipeline
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if inits is not None:
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shared.log.warning('Control: T2I-Adapter does not support separate init image')
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@@ -209,7 +209,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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p.task_args['control_guidance_start'] = active_start[0] if len(active_start) == 1 else list(active_start)
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p.task_args['control_guidance_end'] = active_end[0] if len(active_end) == 1 else list(active_end)
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p.task_args['guess_mode'] = p.guess_mode
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instance = controlnets.ControlNetPipeline(selected_models, shared.sd_model)
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instance = controlnet.ControlNetPipeline(selected_models, shared.sd_model)
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pipe = instance.pipeline
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elif unit_type == 'xs' and has_models:
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p.extra_generation_params["Control mode"] = 'ControlNet-XS'
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@@ -217,7 +217,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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p.controlnet_conditioning_scale = use_conditioning
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p.control_guidance_start = active_start[0] if len(active_start) == 1 else list(active_start)
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p.control_guidance_end = active_end[0] if len(active_end) == 1 else list(active_end)
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instance = controlnetsxs.ControlNetXSPipeline(selected_models, shared.sd_model)
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instance = xs.ControlNetXSPipeline(selected_models, shared.sd_model)
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pipe = instance.pipeline
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if inits is not None:
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shared.log.warning('Control: ControlNet-XS does not support separate init image')
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@@ -225,7 +225,7 @@ def control_run(units: List[unit.Unit], inputs, inits, unit_type: str, is_genera
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p.extra_generation_params["Control mode"] = 'ControlLLLite'
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p.extra_generation_params["Control conditioning"] = use_conditioning
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p.controlnet_conditioning_scale = use_conditioning
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instance = controlnetslite.ControlLLitePipeline(shared.sd_model)
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instance = lite.ControlLLitePipeline(shared.sd_model)
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pipe = instance.pipeline
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if inits is not None:
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shared.log.warning('Control: ControlLLLite does not support separate init image')
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+16
-16
@@ -49,25 +49,25 @@ def test_processors(image):
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def test_controlnets(prompt, negative, image):
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from modules import devices, sd_models
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from modules.control import controlnets
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from modules.control.units import controlnet
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if image is None:
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shared.log.error('Image not loaded')
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return None, None, None
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from PIL import ImageDraw, ImageFont
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images = []
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for model_id in controlnets.list_models():
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for model_id in controlnet.list_models():
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if model_id is None:
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model_id = 'None'
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if shared.state.interrupted:
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continue
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output = image
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if model_id != 'None':
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controlnet = controlnets.ControlNet(model_id=model_id, device=devices.device, dtype=devices.dtype)
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controlnet = controlnet.ControlNet(model_id=model_id, device=devices.device, dtype=devices.dtype)
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if controlnet is None:
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shared.log.error(f'ControlNet load failed: id="{model_id}"')
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continue
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shared.log.info(f'Testing ControlNet: {model_id}')
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pipe = controlnets.ControlNetPipeline(controlnet=controlnet.model, pipeline=shared.sd_model)
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pipe = controlnet.ControlNetPipeline(controlnet=controlnet.model, pipeline=shared.sd_model)
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pipe.pipeline.to(device=devices.device, dtype=devices.dtype)
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sd_models.set_diffuser_options(pipe)
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try:
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@@ -101,25 +101,25 @@ def test_controlnets(prompt, negative, image):
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def test_adapters(prompt, negative, image):
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from modules import devices, sd_models
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from modules.control import adapters
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from modules.control.units import t2iadapter
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if image is None:
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shared.log.error('Image not loaded')
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return None, None, None
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from PIL import ImageDraw, ImageFont
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images = []
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for model_id in adapters.list_models():
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for model_id in t2iadapter.list_models():
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if model_id is None:
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model_id = 'None'
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if shared.state.interrupted:
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continue
|
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output = image.copy()
|
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if model_id != 'None':
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adapter = adapters.Adapter(model_id=model_id, device=devices.device, dtype=devices.dtype)
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adapter = t2iadapter.Adapter(model_id=model_id, device=devices.device, dtype=devices.dtype)
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if adapter is None:
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shared.log.error(f'Adapter load failed: id="{model_id}"')
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||||
continue
|
||||
shared.log.info(f'Testing Adapter: {model_id}')
|
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pipe = adapters.AdapterPipeline(adapter=adapter.model, pipeline=shared.sd_model)
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pipe = t2iadapter.AdapterPipeline(adapter=adapter.model, pipeline=shared.sd_model)
|
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pipe.pipeline.to(device=devices.device, dtype=devices.dtype)
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sd_models.set_diffuser_options(pipe)
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image = image.convert('L') if 'Canny' in model_id or 'Sketch' in model_id else image.convert('RGB')
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@@ -154,25 +154,25 @@ def test_adapters(prompt, negative, image):
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def test_xs(prompt, negative, image):
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from modules import devices, sd_models
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from modules.control import controlnetsxs
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from modules.control.units import xs
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if image is None:
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shared.log.error('Image not loaded')
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return None, None, None
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from PIL import ImageDraw, ImageFont
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images = []
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for model_id in controlnetsxs.list_models():
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for model_id in xs.list_models():
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if model_id is None:
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model_id = 'None'
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if shared.state.interrupted:
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continue
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output = image
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if model_id != 'None':
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xs = controlnetsxs.ControlNetXS(model_id=model_id, device=devices.device, dtype=devices.dtype)
|
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xs = xs.ControlNetXS(model_id=model_id, device=devices.device, dtype=devices.dtype)
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if xs is None:
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shared.log.error(f'ControlNet-XS load failed: id="{model_id}"')
|
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continue
|
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shared.log.info(f'Testing ControlNet-XS: {model_id}')
|
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pipe = controlnetsxs.ControlNetXSPipeline(controlnet=xs.model, pipeline=shared.sd_model)
|
||||
pipe = xs.ControlNetXSPipeline(controlnet=xs.model, pipeline=shared.sd_model)
|
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pipe.pipeline.to(device=devices.device, dtype=devices.dtype)
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||||
sd_models.set_diffuser_options(pipe)
|
||||
try:
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||||
@@ -206,25 +206,25 @@ def test_xs(prompt, negative, image):
|
||||
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||||
def test_lite(prompt, negative, image):
|
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from modules import devices, sd_models
|
||||
from modules.control import controlnetslite
|
||||
from modules.control.units import lite
|
||||
if image is None:
|
||||
shared.log.error('Image not loaded')
|
||||
return None, None, None
|
||||
from PIL import ImageDraw, ImageFont
|
||||
images = []
|
||||
for model_id in controlnetslite.list_models():
|
||||
for model_id in lite.list_models():
|
||||
if model_id is None:
|
||||
model_id = 'None'
|
||||
if shared.state.interrupted:
|
||||
continue
|
||||
output = image
|
||||
if model_id != 'None':
|
||||
lite = controlnetslite.ControlLLLite(model_id=model_id, device=devices.device, dtype=devices.dtype)
|
||||
lite = lite.ControlLLLite(model_id=model_id, device=devices.device, dtype=devices.dtype)
|
||||
if lite is None:
|
||||
shared.log.error(f'Control-LLite load failed: id="{model_id}"')
|
||||
continue
|
||||
shared.log.info(f'Testing ControlNet-XS: {model_id}')
|
||||
pipe = controlnetslite.ControlLLitePipeline(pipeline=shared.sd_model)
|
||||
pipe = lite.ControlLLitePipeline(pipeline=shared.sd_model)
|
||||
pipe.apply(controlnet=lite.model, image=image, conditioning=1.0)
|
||||
pipe.pipeline.to(device=devices.device, dtype=devices.dtype)
|
||||
sd_models.set_diffuser_options(pipe)
|
||||
|
||||
+11
-11
@@ -2,11 +2,11 @@ from typing import Union
|
||||
from PIL import Image
|
||||
from modules.shared import log
|
||||
from modules.control import processors
|
||||
from modules.control import controlnets
|
||||
from modules.control import controlnetsxs
|
||||
from modules.control import controlnetslite
|
||||
from modules.control import adapters
|
||||
from modules.control import reference # pylint: disable=unused-import
|
||||
from modules.control.units import controlnet
|
||||
from modules.control.units import xs
|
||||
from modules.control.units import lite
|
||||
from modules.control.units import t2iadapter
|
||||
from modules.control.units import reference # pylint: disable=unused-import
|
||||
|
||||
|
||||
default_device = None
|
||||
@@ -45,8 +45,8 @@ class Unit(): # mashup of gradio controls and mapping to actual implementation c
|
||||
self.end = max(self.start, self.end)
|
||||
# processor always exists, adapter and controlnet are optional
|
||||
self.process: processors.Processor = processors.Processor()
|
||||
self.adapter: adapters.Adapter = None
|
||||
self.controlnet: Union[controlnets.ControlNet, controlnetsxs.ControlNetXS] = None
|
||||
self.adapter: t2iadapter.Adapter = None
|
||||
self.controlnet: Union[controlnet.ControlNet, xs.ControlNetXS] = None
|
||||
# map to input image
|
||||
self.input: Image = image_input
|
||||
self.override: Image = None
|
||||
@@ -106,13 +106,13 @@ class Unit(): # mashup of gradio controls and mapping to actual implementation c
|
||||
|
||||
# actual init
|
||||
if self.type == 'adapter':
|
||||
self.adapter = adapters.Adapter(device=default_device, dtype=default_dtype)
|
||||
self.adapter = t2iadapter.Adapter(device=default_device, dtype=default_dtype)
|
||||
elif self.type == 'controlnet':
|
||||
self.controlnet = controlnets.ControlNet(device=default_device, dtype=default_dtype)
|
||||
self.controlnet = controlnet.ControlNet(device=default_device, dtype=default_dtype)
|
||||
elif self.type == 'xs':
|
||||
self.controlnet = controlnetsxs.ControlNetXS(device=default_device, dtype=default_dtype)
|
||||
self.controlnet = xs.ControlNetXS(device=default_device, dtype=default_dtype)
|
||||
elif self.type == 'lite':
|
||||
self.controlnet = controlnetslite.ControlLLLite(device=default_device, dtype=default_dtype)
|
||||
self.controlnet = lite.ControlLLLite(device=default_device, dtype=default_dtype)
|
||||
elif self.type == 'reference':
|
||||
pass
|
||||
else:
|
||||
|
||||
@@ -6,7 +6,7 @@ from PIL import Image
|
||||
from diffusers import StableDiffusionPipeline, StableDiffusionXLPipeline
|
||||
from modules.shared import log, opts
|
||||
from modules import errors
|
||||
from modules.control.controlnetslite_model import ControlNetLLLite
|
||||
from modules.control.units.lite_model import ControlNetLLLite
|
||||
|
||||
|
||||
what = 'ControlLLLite'
|
||||
@@ -130,6 +130,6 @@ class ControlLLitePipeline():
|
||||
cn.apply(pipe=self.pipeline, cond=np.asarray(images[i % len(images)]), weight=weight[i % len(weight)])
|
||||
|
||||
def restore(self):
|
||||
from modules.control.controlnetslite_model import clear_all_lllite
|
||||
from modules.control.units.lite_model import clear_all_lllite
|
||||
clear_all_lllite()
|
||||
self.nets = []
|
||||
+26
-2
@@ -294,8 +294,9 @@ def load_diffusers_models(model_path: str, command_path: str = None, clear=True)
|
||||
if os.path.exists(os.path.join(folder, 'hidden')):
|
||||
continue
|
||||
output.append(name)
|
||||
except Exception as e:
|
||||
shared.log.error(f"Error analyzing diffusers model: {folder} {e}")
|
||||
except Exception:
|
||||
# shared.log.error(f"Error analyzing diffusers model: {folder} {e}")
|
||||
pass
|
||||
except Exception as e:
|
||||
shared.log.error(f"Error listing diffusers: {place} {e}")
|
||||
shared.log.debug(f'Scanning diffusers cache: {model_path} {command_path} items={len(output)} time={time.time()-t0:.2f}')
|
||||
@@ -339,6 +340,29 @@ def load_reference(name: str):
|
||||
return True
|
||||
|
||||
|
||||
def load_civitai(model: str, url: str):
|
||||
from modules import sd_models
|
||||
name, _ext = os.path.splitext(model)
|
||||
info = sd_models.get_closet_checkpoint_match(name)
|
||||
if info is not None:
|
||||
shared.log.debug(f'Reference model: {name}')
|
||||
return name # already downloaded
|
||||
else:
|
||||
shared.log.debug(f'Reference model: {name} download start')
|
||||
download_civit_model_thread(model_name=model, model_url=url, model_path='', model_type='safetensors', preview=None, token=None)
|
||||
shared.log.debug(f'Reference model: {name} download complete')
|
||||
sd_models.list_models()
|
||||
info = sd_models.get_closet_checkpoint_match(name)
|
||||
print('HERE1', info)
|
||||
print('HERE2', name)
|
||||
if info is not None:
|
||||
shared.log.debug(f'Reference model: {name}')
|
||||
return name # already downloaded
|
||||
else:
|
||||
shared.log.debug(f'Reference model: {name} not found')
|
||||
return None
|
||||
|
||||
|
||||
cache_folders = {}
|
||||
cache_last = 0
|
||||
cache_time = 1
|
||||
|
||||
@@ -565,13 +565,13 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
|
||||
if index is None:
|
||||
index = position_in_batch + iteration * p.batch_size
|
||||
if all_prompts is None:
|
||||
all_prompts = p.all_prompts
|
||||
all_prompts = p.all_prompts or [p.prompt]
|
||||
if all_negative_prompts is None:
|
||||
all_negative_prompts = p.all_negative_prompts
|
||||
all_negative_prompts = p.all_negative_prompts or [p.negative_prompt]
|
||||
if all_seeds is None:
|
||||
all_seeds = p.all_seeds
|
||||
all_seeds = p.all_seeds or [p.seed]
|
||||
if all_subseeds is None:
|
||||
all_subseeds = p.all_subseeds
|
||||
all_subseeds = p.all_subseeds or [p.subseed]
|
||||
while len(all_prompts) <= index:
|
||||
all_prompts.append(all_prompts[-1])
|
||||
while len(all_seeds) <= index:
|
||||
|
||||
@@ -168,6 +168,7 @@ def list_models():
|
||||
shared.log.info(f'Available models: path="{shared.opts.ckpt_dir}" items={len(checkpoints_list)} time={time.time()-t0:.2f}')
|
||||
|
||||
checkpoints_list = dict(sorted(checkpoints_list.items(), key=lambda cp: cp[1].filename))
|
||||
"""
|
||||
if len(checkpoints_list) == 0:
|
||||
if not shared.cmd_opts.no_download:
|
||||
key = input('Download the default model? (y/N) ')
|
||||
@@ -185,7 +186,7 @@ def list_models():
|
||||
checkpoint_info = CheckpointInfo(filename)
|
||||
if checkpoint_info.name is not None:
|
||||
checkpoint_info.register()
|
||||
|
||||
"""
|
||||
|
||||
def update_model_hashes():
|
||||
txt = []
|
||||
|
||||
@@ -38,6 +38,8 @@ def single_sample_to_image(sample, approximation=None):
|
||||
warn_once('Unknown decode type, please reset preview method')
|
||||
approximation = 0
|
||||
|
||||
if len(sample.shape) > 4: # likely unknown video latent (e.g. svd)
|
||||
return Image.new(mode="RGB", size=(512, 512))
|
||||
if len(sample.shape) == 4 and sample.shape[0]: # likely animatediff latent
|
||||
sample = sample.permute(1, 0, 2, 3)[0]
|
||||
if approximation == 0: # Simple
|
||||
|
||||
+12
-6
@@ -182,10 +182,10 @@ def create_advanced_inputs(tab):
|
||||
with gr.Accordion(open=False, label="Advanced", elem_id=f"{tab}_advanced", elem_classes=["small-accordion"]):
|
||||
with gr.Group():
|
||||
with FormRow():
|
||||
cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='CFG scale', value=6.0, elem_id=f"{tab}_cfg_scale")
|
||||
cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='CFG scale', value=4.0, elem_id=f"{tab}_cfg_scale")
|
||||
clip_skip = gr.Slider(label='CLIP skip', value=1, minimum=1, maximum=14, step=1, elem_id=f"{tab}_clip_skip", interactive=True)
|
||||
with FormRow():
|
||||
image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Secondary CFG scale', value=6.0, elem_id=f"{tab}_image_cfg_scale")
|
||||
image_cfg_scale = gr.Slider(minimum=0.0, maximum=30.0, step=0.1, label='Secondary CFG scale', value=4.0, elem_id=f"{tab}_image_cfg_scale")
|
||||
diffusers_guidance_rescale = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Guidance rescale', value=0.7, elem_id=f"{tab}_image_cfg_rescale", visible=shared.backend == shared.Backend.DIFFUSERS)
|
||||
with gr.Group():
|
||||
with FormRow():
|
||||
@@ -648,6 +648,9 @@ def create_ui(startup_timer = None):
|
||||
|
||||
ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
|
||||
|
||||
with FormRow():
|
||||
gr.HTML(value="", elem_id="main_info", visible=False, elem_classes=["main-info"])
|
||||
|
||||
timer.startup.record("ui-txt2img")
|
||||
|
||||
import modules.img2img # pylint: disable=redefined-outer-name
|
||||
@@ -1136,9 +1139,9 @@ def create_ui(startup_timer = None):
|
||||
interfaces += [(img2img_interface, "Image", "img2img")]
|
||||
interfaces += [(control_interface, "Control", "control")] if control_interface is not None else []
|
||||
interfaces += [(extras_interface, "Process", "process")]
|
||||
interfaces += [(interrogate_interface, "Interrogate", "interrogate")]
|
||||
interfaces += [(train_interface, "Train", "train")]
|
||||
interfaces += [(models_interface, "Models", "models")]
|
||||
interfaces += [(interrogate_interface, "Interrogate", "interrogate")]
|
||||
interfaces += script_callbacks.ui_tabs_callback()
|
||||
interfaces += [(settings_interface, "System", "system")]
|
||||
|
||||
@@ -1224,10 +1227,13 @@ def create_ui(startup_timer = None):
|
||||
)
|
||||
|
||||
def reference_submit(model):
|
||||
loaded = modelloader.load_reference(model)
|
||||
if loaded:
|
||||
if '@' not in model: # diffusers
|
||||
loaded = modelloader.load_reference(model)
|
||||
return model if loaded else opts.sd_model_checkpoint
|
||||
return loaded
|
||||
else: # civitai
|
||||
model, url = model.split('@')
|
||||
loaded = modelloader.load_civitai(model, url)
|
||||
return loaded if loaded is not None else opts.sd_model_checkpoint
|
||||
|
||||
button_set_reference = gr.Button('Change reference', elem_id='change_reference', visible=False)
|
||||
button_set_reference.click(
|
||||
|
||||
+22
-22
@@ -1,13 +1,13 @@
|
||||
import os
|
||||
import gradio as gr
|
||||
from modules.control import unit
|
||||
from modules.control import controlnets # lllyasviel ControlNet
|
||||
from modules.control import controlnetsxs # vislearn ControlNet-XS
|
||||
from modules.control import controlnetslite # vislearn ControlNet-XS
|
||||
from modules.control import adapters # TencentARC T2I-Adapter
|
||||
from modules.control import processors # patrickvonplaten controlnet_aux
|
||||
from modules.control import reference # reference pipeline
|
||||
from modules.control import ipadapter # reference pipeline
|
||||
from modules.control.units import controlnet # lllyasviel ControlNet
|
||||
from modules.control.units import xs # vislearn ControlNet-XS
|
||||
from modules.control.units import lite # vislearn ControlNet-XS
|
||||
from modules.control.units import t2iadapter # TencentARC T2I-Adapter
|
||||
from modules.control.units import reference # reference pipeline
|
||||
from modules.control.units import ipadapter # reference pipeline
|
||||
from modules import errors, shared, progress, sd_samplers, ui, ui_components, ui_symbols, ui_common, generation_parameters_copypaste, call_queue
|
||||
from modules.ui_components import FormRow, FormGroup
|
||||
|
||||
@@ -24,18 +24,18 @@ debug('Trace: CONTROL')
|
||||
def initialize():
|
||||
from modules import devices
|
||||
shared.log.debug(f'Control initialize: models={shared.opts.control_dir}')
|
||||
controlnets.cache_dir = os.path.join(shared.opts.control_dir, 'controlnet')
|
||||
controlnetsxs.cache_dir = os.path.join(shared.opts.control_dir, 'xs')
|
||||
controlnetslite.cache_dir = os.path.join(shared.opts.control_dir, 'lite')
|
||||
adapters.cache_dir = os.path.join(shared.opts.control_dir, 'adapter')
|
||||
controlnet.cache_dir = os.path.join(shared.opts.control_dir, 'controlnet')
|
||||
xs.cache_dir = os.path.join(shared.opts.control_dir, 'xs')
|
||||
lite.cache_dir = os.path.join(shared.opts.control_dir, 'lite')
|
||||
t2iadapter.cache_dir = os.path.join(shared.opts.control_dir, 'adapter')
|
||||
processors.cache_dir = os.path.join(shared.opts.control_dir, 'processor')
|
||||
unit.default_device = devices.device
|
||||
unit.default_dtype = devices.dtype
|
||||
os.makedirs(shared.opts.control_dir, exist_ok=True)
|
||||
os.makedirs(controlnets.cache_dir, exist_ok=True)
|
||||
os.makedirs(controlnetsxs.cache_dir, exist_ok=True)
|
||||
os.makedirs(controlnetslite.cache_dir, exist_ok=True)
|
||||
os.makedirs(adapters.cache_dir, exist_ok=True)
|
||||
os.makedirs(controlnet.cache_dir, exist_ok=True)
|
||||
os.makedirs(xs.cache_dir, exist_ok=True)
|
||||
os.makedirs(lite.cache_dir, exist_ok=True)
|
||||
os.makedirs(t2iadapter.cache_dir, exist_ok=True)
|
||||
os.makedirs(processors.cache_dir, exist_ok=True)
|
||||
|
||||
|
||||
@@ -324,8 +324,8 @@ def create_ui(_blocks: gr.Blocks=None):
|
||||
with gr.Row():
|
||||
enabled_cb = gr.Checkbox(value= i==0, label="")
|
||||
process_id = gr.Dropdown(label="Processor", choices=processors.list_models(), value='None')
|
||||
model_id = gr.Dropdown(label="ControlNet", choices=controlnets.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, controlnets.list_models, lambda: {"choices": controlnets.list_models(refresh=True)}, 'refresh_control_models')
|
||||
model_id = gr.Dropdown(label="ControlNet", choices=controlnet.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, controlnet.list_models, lambda: {"choices": controlnet.list_models(refresh=True)}, 'refresh_control_models')
|
||||
model_strength = gr.Slider(label="Strength", minimum=0.01, maximum=1.0, step=0.01, value=1.0-i/10)
|
||||
control_start = gr.Slider(label="Start", minimum=0.0, maximum=1.0, step=0.05, value=0)
|
||||
control_end = gr.Slider(label="End", minimum=0.0, maximum=1.0, step=0.05, value=1.0)
|
||||
@@ -369,8 +369,8 @@ def create_ui(_blocks: gr.Blocks=None):
|
||||
with gr.Row():
|
||||
enabled_cb = gr.Checkbox(value= i==0, label="")
|
||||
process_id = gr.Dropdown(label="Processor", choices=processors.list_models(), value='None')
|
||||
model_id = gr.Dropdown(label="ControlNet-XS", choices=controlnetsxs.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, controlnetsxs.list_models, lambda: {"choices": controlnetsxs.list_models(refresh=True)}, 'refresh_control_models')
|
||||
model_id = gr.Dropdown(label="ControlNet-XS", choices=xs.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, xs.list_models, lambda: {"choices": xs.list_models(refresh=True)}, 'refresh_control_models')
|
||||
model_strength = gr.Slider(label="Strength", minimum=0.01, maximum=1.0, step=0.01, value=1.0-i/10)
|
||||
control_start = gr.Slider(label="Start", minimum=0.0, maximum=1.0, step=0.05, value=0)
|
||||
control_end = gr.Slider(label="End", minimum=0.0, maximum=1.0, step=0.05, value=1.0)
|
||||
@@ -414,8 +414,8 @@ def create_ui(_blocks: gr.Blocks=None):
|
||||
with gr.Row():
|
||||
enabled_cb = gr.Checkbox(value= i == 0, label="Enabled")
|
||||
process_id = gr.Dropdown(label="Processor", choices=processors.list_models(), value='None')
|
||||
model_id = gr.Dropdown(label="Adapter", choices=adapters.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, adapters.list_models, lambda: {"choices": adapters.list_models(refresh=True)}, 'refresh_adapter_models')
|
||||
model_id = gr.Dropdown(label="Adapter", choices=t2iadapter.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, t2iadapter.list_models, lambda: {"choices": t2iadapter.list_models(refresh=True)}, 'refresh_adapter_models')
|
||||
model_strength = gr.Slider(label="Strength", minimum=0.01, maximum=1.0, step=0.01, value=1.0-i/10)
|
||||
reset_btn = ui_components.ToolButton(value=ui_symbols.reset)
|
||||
image_upload = gr.UploadButton(label=ui_symbols.upload, file_types=['image'], elem_classes=['form', 'gradio-button', 'tool'])
|
||||
@@ -454,8 +454,8 @@ def create_ui(_blocks: gr.Blocks=None):
|
||||
with gr.Row():
|
||||
enabled_cb = gr.Checkbox(value= i == 0, label="Enabled")
|
||||
process_id = gr.Dropdown(label="Processor", choices=processors.list_models(), value='None')
|
||||
model_id = gr.Dropdown(label="Model", choices=controlnetslite.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, controlnetslite.list_models, lambda: {"choices": controlnetslite.list_models(refresh=True)}, 'refresh_lite_models')
|
||||
model_id = gr.Dropdown(label="Model", choices=lite.list_models(), value='None')
|
||||
ui_common.create_refresh_button(model_id, lite.list_models, lambda: {"choices": lite.list_models(refresh=True)}, 'refresh_lite_models')
|
||||
model_strength = gr.Slider(label="Strength", minimum=0.01, maximum=1.0, step=0.01, value=1.0-i/10)
|
||||
reset_btn = ui_components.ToolButton(value=ui_symbols.reset)
|
||||
image_upload = gr.UploadButton(label=ui_symbols.upload, file_types=['image'], elem_classes=['form', 'gradio-button', 'tool'])
|
||||
|
||||
+13
-10
@@ -16,19 +16,19 @@ from modules import scripts, processing, shared, devices
|
||||
image_encoder = None
|
||||
image_encoder_type = None
|
||||
loaded = None
|
||||
ADAPTERS = [
|
||||
'none',
|
||||
'ip-adapter_sd15',
|
||||
'ip-adapter_sd15_light',
|
||||
'ip-adapter-plus_sd15',
|
||||
'ip-adapter-plus-face_sd15',
|
||||
'ip-adapter-full-face_sd15',
|
||||
ADAPTERS = {
|
||||
'None': 'none',
|
||||
'Base': 'ip-adapter_sd15',
|
||||
'Light': 'ip-adapter_sd15_light',
|
||||
'Plus': 'ip-adapter-plus_sd15',
|
||||
'Plus Face': 'ip-adapter-plus-face_sd15',
|
||||
'Full face': 'ip-adapter-full-face_sd15',
|
||||
'Base SXDL': 'ip-adapter_sdxl',
|
||||
# 'models/ip-adapter_sd15_vit-G', # RuntimeError: mat1 and mat2 shapes cannot be multiplied (2x1024 and 1280x3072)
|
||||
'ip-adapter_sdxl',
|
||||
# 'sdxl_models/ip-adapter_sdxl_vit-h',
|
||||
# 'sdxl_models/ip-adapter-plus_sdxl_vit-h',
|
||||
# 'sdxl_models/ip-adapter-plus-face_sdxl_vit-h',
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
class Script(scripts.Script):
|
||||
@@ -41,7 +41,7 @@ class Script(scripts.Script):
|
||||
def ui(self, _is_img2img):
|
||||
with gr.Accordion('IP Adapter', open=False, elem_id='ipadapter'):
|
||||
with gr.Row():
|
||||
adapter = gr.Dropdown(label='Adapter', choices=ADAPTERS, value='none')
|
||||
adapter = gr.Dropdown(label='Adapter', choices=list(ADAPTERS), value='none')
|
||||
scale = gr.Slider(label='Scale', minimum=0.0, maximum=1.0, step=0.01, value=0.5)
|
||||
with gr.Row():
|
||||
image = gr.Image(image_mode='RGB', label='Image', source='upload', type='pil', width=512)
|
||||
@@ -50,6 +50,8 @@ class Script(scripts.Script):
|
||||
def process(self, p: processing.StableDiffusionProcessing, adapter, scale, image): # pylint: disable=arguments-differ
|
||||
from transformers import CLIPVisionModelWithProjection
|
||||
# overrides
|
||||
adapter = ADAPTERS[adapter]
|
||||
print('HERE', adapter)
|
||||
if hasattr(p, 'ip_adapter_name'):
|
||||
adapter = p.ip_adapter_name
|
||||
if hasattr(p, 'ip_adapter_scale'):
|
||||
@@ -96,6 +98,7 @@ class Script(scripts.Script):
|
||||
|
||||
# main code
|
||||
subfolder = 'models' if 'sd15' in adapter else 'sdxl_models'
|
||||
print('HERE2', subfolder)
|
||||
if adapter != loaded or getattr(shared.sd_model.unet.config, 'encoder_hid_dim_type', None) is None:
|
||||
t0 = time.time()
|
||||
if loaded is not None:
|
||||
|
||||
Reference in New Issue
Block a user