mirror of
https://github.com/nod-ai/AMD-SHARK-Studio.git
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Studio2/SD/UI: Improve various parts of the UI for Stable Diffusion (#2074)
* Studio2/SD/UI: Improve various parts of the UI of Shark 2 * Update Gradio pin to 4.15.0. * Port workarounds for Gradio >4.8.0 main container sizing from Shark 1.0. * Move nod Logo out of the SD tab and onto the top right of the main tab bar. * Set nod logo icon as the favicon (as current Shark 1.0). * Create a tabbed right hand panel within the SD UI sized to the viewport height. * Make Input Image tab 1 in the right hand panel. * Make output images, generation log, and generation buttons, tab 2 in the right hand panel * Make config JSON display, with config load, save and clear, tab 3 in the right hand panel * Make gallery area of the Output tab take up all vertical space the other controls on the tab do not. * Tidy up the controls on the Config tab somewhat. * Studio2/SD/UI: Reorganise inputs on Left Panel of SD tab * Rename previously added Right Panel Output tab to 'Generate'. * Move Batch Count, Batch Size, and Repeatable Seeds, off of Left Panel and onto 'Generate' Tab. * On 'Generate' tab, rename 'Generate Image(s)' button to 'Start', and 'Stop Batch' button to 'Stop'. They are now below the Batch inputs on a Generate tab so don't need the specificity. * Move Device, Low VRAM, and Precision inputs into their own 'Device Settings' Accordion control. (starts closed) * Rename 'Custom Weights Checkpoint' to 'Checkpoint Weights' * Move Checkpoint Weights, VAE Model, Standalone Lora Weights, and Embeddings Options controls, into their own 'Model Weights' Accordion control. (starts closed) * Move Denoising Strength, and Resample Type controls into their own 'Input Image Processing' Accordion. (starts closed) * Move any remaining controls in the 'Advanced Options' Accorion directly onto the left panel, and remove then Accordion. * Enable the copy button for all text boxes on the SD tab. * Add emoji/unicode glphs to all top level controls and Accordions on the SD Left Panel. * Start with the 'Generate' as the initially selected tab in the SD Right Panel, working around Gradio issue #7805 * Tweaks to SD Right Tab Panel vertical height. * Studio2/SD/UI: Sizing tweaks for Right Panel, and >1920 width * Set height of right panel using vmin rather than vh, with explicit affordances for fixed areas above and below. * Port >1920 width Gradio >4.8 CSS workaround from Shark 1.0.
This commit is contained in:
Stefan Kapusniak
@@ -1,4 +1,6 @@
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from multiprocessing import Process, freeze_support
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from PIL import Image
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import os
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import time
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import sys
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@@ -71,6 +73,10 @@ def launch_webui(address):
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def webui():
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from apps.shark_studio.modules.shared_cmd_opts import cmd_opts
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from apps.shark_studio.web.ui.utils import (
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nodicon_loc,
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nodlogo_loc,
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)
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launch_api = cmd_opts.api
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initialize.initialize()
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@@ -134,6 +140,7 @@ def webui():
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return os.path.join(base_path, relative_path)
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dark_theme = resource_path("ui/css/sd_dark_theme.css")
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gradio_workarounds = resource_path("ui/js/sd_gradio_workarounds.js")
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# from apps.shark_studio.web.ui import load_ui_from_script
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@@ -158,8 +165,19 @@ def webui():
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)
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with gr.Blocks(
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css=dark_theme, analytics_enabled=False, title="Shark Studio 2.0 Beta"
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css=dark_theme,
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js=gradio_workarounds,
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analytics_enabled=False,
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title="Shark Studio 2.0 Beta",
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) as studio_web:
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nod_logo = Image.open(nodlogo_loc)
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gr.Image(
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value=nod_logo,
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show_label=False,
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interactive=False,
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elem_id="tab_bar_logo",
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show_download_button=False,
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)
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with gr.Tabs() as tabs:
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# NOTE: If adding, removing, or re-ordering tabs, make sure that they
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# have a unique id that doesn't clash with any of the other tabs,
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@@ -189,6 +207,7 @@ def webui():
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inbrowser=True,
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server_name="0.0.0.0",
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server_port=cmd_opts.server_port,
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favicon_path=nodicon_loc,
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)
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@@ -117,7 +117,7 @@ body {
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height: 100% !important;
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}
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/* display in full width for desktop devices */
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/* display in full width for desktop devices, but see below */
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@media (min-width: 1536px)
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{
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.gradio-container {
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@@ -125,6 +125,15 @@ body {
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}
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}
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/* media rules in custom css are don't appear to be applied in
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gradio versions > 4.7, so we have to define a class which
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we will manually need add and remove using javascript.
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Remove this once this fixed in gradio.
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*/
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.gradio-container-size-full {
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max-width: var(--size-full) !important;
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}
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.gradio-container .contain {
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padding: 0 var(--size-4) !important;
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}
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@@ -182,6 +191,7 @@ footer {
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aspect-ratio: unset;
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max-height: calc(55vh - (2 * var(--spacing-lg)));
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}
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/* fix width and height of gallery items when on very large desktop screens, but see below */
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@media (min-width: 1921px) {
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/* Force a 768px_height + 4px_margin_height + navbar_height for the gallery */
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#gallery .grid-wrap, #gallery .preview{
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@@ -193,6 +203,20 @@ footer {
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max-height: 770px !important;
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}
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}
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/* media rules in custom css are don't appear to be applied in
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gradio versions > 4.7, so we have to define classes which
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we will manually need add and remove using javascript.
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Remove this once this fixed in gradio.
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*/
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.gallery-force-height768 .grid-wrap, .gallery-force-height768 .preview {
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min-height: calc(768px + 4px + var(--size-14)) !important;
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max-height: calc(768px + 4px + var(--size-14)) !important;
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}
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.gallery-limit-height768 .thumbnail-item.thumbnail-lg {
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max-height: 770px !important;
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}
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/* Don't upscale when viewing in solo image mode */
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#gallery .preview img {
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object-fit: scale-down;
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@@ -303,6 +327,15 @@ footer {
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min-height: 89vh !important;
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}
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.sd-right-panel {
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height: calc(100vmin - var(--size-32) - var(--size-10)) !important;
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overflow-y: scroll;
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}
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.sd-right-panel .fill {
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flex: 1;
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}
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/* don't stretch non-square images to be square, breaking their aspect ratio */
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#outputgallery_gallery .thumbnail-item.thumbnail-lg > img {
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object-fit: contain !important;
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@@ -314,7 +347,7 @@ footer {
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width: 100%;
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}
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#top_logo.logo_centered img{
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#top_logo.logo_centered img {
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object-fit: scale-down;
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position: absolute;
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width: 80%;
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@@ -322,3 +355,19 @@ footer {
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left: 50%;
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transform: translate(-50%, -50%);
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}
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#tab_bar_logo {
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overflow: visible !important;
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border-width: 0 !important;
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height: 0px !important;
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padding: 0;
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margin: 0;
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}
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#tab_bar_logo .image-container {
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object-fit: scale-down;
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position: absolute !important;
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top: 14px;
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right: 0px;
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height: 36px;
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}
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49
apps/shark_studio/web/ui/js/sd_gradio_workarounds.js
Normal file
49
apps/shark_studio/web/ui/js/sd_gradio_workarounds.js
Normal file
@@ -0,0 +1,49 @@
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// workaround gradio after 4.7, not applying any @media rules form the custom .css file
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() => {
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console.log(`innerWidth: ${window.innerWidth}` )
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// 1536px rules
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const mediaQuery1536 = window.matchMedia('(min-width: 1536px)')
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function handleWidth1536(event) {
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// display in full width for desktop devices
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document.querySelectorAll(".gradio-container")
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.forEach( (node) => {
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if (event.matches) {
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node.classList.add("gradio-container-size-full");
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} else {
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node.classList.remove("gradio-container-size-full")
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}
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});
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}
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mediaQuery1536.addEventListener("change", handleWidth1536);
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mediaQuery1536.dispatchEvent(new MediaQueryListEvent("change", {matches: window.innerWidth >= 1536}));
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// 1921px rules
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const mediaQuery1921 = window.matchMedia('(min-width: 1921px)')
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function handleWidth1921(event) {
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/* Force a 768px_height + 4px_margin_height + navbar_height for the gallery */
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/* Limit height to 768px_height + 2px_margin_height for the thumbnails */
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document.querySelectorAll("#gallery")
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.forEach( (node) => {
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if (event.matches) {
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node.classList.add("gallery-force-height768");
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node.classList.add("gallery-limit-height768");
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} else {
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node.classList.remove("gallery-force-height768");
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node.classList.remove("gallery-limit-height768");
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}
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});
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}
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mediaQuery1921.addEventListener("change", handleWidth1921);
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mediaQuery1921.dispatchEvent(new MediaQueryListEvent("change", {matches: window.innerWidth >= 1921}));
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}
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@@ -31,9 +31,6 @@ from apps.shark_studio.modules.img_processing import (
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resize_stencil,
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)
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from apps.shark_studio.modules.shared_cmd_opts import cmd_opts
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from apps.shark_studio.web.ui.utils import (
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nodlogo_loc,
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)
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from apps.shark_studio.web.utils.state import (
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status_label,
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)
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@@ -238,39 +235,63 @@ def base_model_changed(base_model_id):
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with gr.Blocks(title="Stable Diffusion") as sd_element:
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with gr.Row(elem_id="ui_title"):
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nod_logo = Image.open(nodlogo_loc)
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with gr.Row(variant="compact", equal_height=True):
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with gr.Column(
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scale=1,
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elem_id="demo_title_outer",
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):
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gr.Image(
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value=nod_logo,
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show_label=False,
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interactive=False,
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elem_id="top_logo",
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width=150,
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height=50,
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show_download_button=False,
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)
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with gr.Column(elem_id="ui_body"):
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with gr.Row():
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with gr.Column(scale=2, min_width=600):
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with gr.Row(equal_height=True):
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with gr.Column(scale=3):
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sd_model_info = (
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f"Checkpoint Path: {str(get_checkpoints_path())}"
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with gr.Accordion(
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label="\U0001F4D0\U0000FE0F Device Settings", open=False
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):
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device = gr.Dropdown(
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elem_id="device",
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label="Device",
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value=global_obj.get_device_list()[0],
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choices=global_obj.get_device_list(),
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allow_custom_value=False,
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)
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with gr.Row():
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ondemand = gr.Checkbox(
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value=cmd_opts.lowvram,
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label="Low VRAM",
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interactive=True,
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)
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base_model_id = gr.Dropdown(
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label="Base Model",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="stabilityai/stable-diffusion-2-1-base",
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choices=sd_default_models,
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) # base_model_id
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precision = gr.Radio(
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label="Precision",
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value=cmd_opts.precision,
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choices=[
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"fp16",
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"fp32",
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],
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visible=True,
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)
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sd_model_info = f"Checkpoint Path: {str(get_checkpoints_path())}"
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base_model_id = gr.Dropdown(
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label="\U000026F0\U0000FE0F Base Model",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="stabilityai/stable-diffusion-2-1-base",
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choices=sd_default_models,
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) # base_model_id
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with gr.Row():
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height = gr.Slider(
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384,
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768,
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value=cmd_opts.height,
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step=8,
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label="\U00002195\U0000FE0F Height",
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)
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width = gr.Slider(
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384,
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768,
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value=cmd_opts.width,
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step=8,
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label="\U00002194\U0000FE0F Width",
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)
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with gr.Accordion(
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label="\U00002696\U0000FE0F Model Weights", open=False
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):
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with gr.Column():
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custom_weights = gr.Dropdown(
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label="Custom Weights Checkpoint",
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label="Checkpoint Weights",
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info="Select or enter HF model ID",
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elem_id="custom_model",
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value="None",
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@@ -283,13 +304,12 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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inputs=[base_model_id],
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outputs=[custom_weights],
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)
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with gr.Column(scale=2):
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sd_vae_info = (str(get_checkpoints_path("vae"))).replace(
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"\\", "\n\\"
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)
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sd_vae_info = f"VAE Path: {sd_vae_info}"
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custom_vae = gr.Dropdown(
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label=f"Custom VAE Models",
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label=f"VAE Model",
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info=sd_vae_info,
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elem_id="custom_model",
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value=(
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@@ -301,49 +321,9 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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allow_custom_value=True,
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scale=1,
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)
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with gr.Row():
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ondemand = gr.Checkbox(
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value=cmd_opts.lowvram,
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label="Low VRAM",
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interactive=True,
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)
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precision = gr.Radio(
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label="Precision",
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value=cmd_opts.precision,
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choices=[
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"fp16",
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"fp32",
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],
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visible=True,
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)
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with gr.Group(elem_id="prompt_box_outer"):
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prompt = gr.Textbox(
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label="Prompt",
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value=cmd_opts.prompt[0],
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lines=2,
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elem_id="prompt_box",
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)
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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value=cmd_opts.negative_prompt[0],
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lines=2,
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elem_id="negative_prompt_box",
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)
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with gr.Accordion(label="Input Image", open=False):
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# TODO: make this import image prompt info if it exists
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sd_init_image = gr.Image(
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label="Input Image",
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type="pil",
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height=300,
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interactive=True,
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)
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with gr.Accordion(label="Embeddings options", open=True, render=True):
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sd_lora_info = (str(get_checkpoints_path("loras"))).replace(
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"\\", "\n\\"
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)
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with gr.Row():
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embeddings_config = gr.JSON(min_width=50, scale=1)
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sd_lora_info = (str(get_checkpoints_path("loras"))).replace(
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"\\", "\n\\"
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)
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lora_opt = gr.Dropdown(
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allow_custom_value=True,
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label=f"Standalone LoRA Weights",
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@@ -358,106 +338,83 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
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value="<div><i>No LoRA selected</i></div>",
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elem_classes="lora-tags",
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)
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gr.on(
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triggers=[lora_opt.change],
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fn=lora_changed,
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inputs=[lora_opt],
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outputs=[lora_tags],
|
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queue=True,
|
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show_progress=False,
|
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).then(
|
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fn=update_embeddings_json,
|
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inputs=[lora_opt],
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outputs=[embeddings_config],
|
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show_progress=False,
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embeddings_config = gr.JSON(
|
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label="Embeddings Options", min_width=50, scale=1
|
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)
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gr.on(
|
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triggers=[lora_opt.change],
|
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fn=lora_changed,
|
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inputs=[lora_opt],
|
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outputs=[lora_tags],
|
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queue=True,
|
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show_progress=False,
|
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).then(
|
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fn=update_embeddings_json,
|
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inputs=[lora_opt],
|
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outputs=[embeddings_config],
|
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show_progress=False,
|
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)
|
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with gr.Accordion(
|
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label="\U0001F9EA\U0000FE0F Input Image Processing", open=False
|
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):
|
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strength = gr.Slider(
|
||||
0,
|
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1,
|
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value=cmd_opts.strength,
|
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step=0.01,
|
||||
label="Denoising Strength",
|
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)
|
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with gr.Accordion(label="Advanced Options", open=True):
|
||||
with gr.Row():
|
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scheduler = gr.Dropdown(
|
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elem_id="scheduler",
|
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label="Scheduler",
|
||||
value="EulerDiscrete",
|
||||
choices=scheduler_model_map.keys(),
|
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allow_custom_value=False,
|
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)
|
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height = gr.Slider(
|
||||
384,
|
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768,
|
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value=cmd_opts.height,
|
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step=8,
|
||||
label="Height",
|
||||
)
|
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width = gr.Slider(
|
||||
384,
|
||||
768,
|
||||
value=cmd_opts.width,
|
||||
step=8,
|
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label="Width",
|
||||
)
|
||||
with gr.Row():
|
||||
with gr.Column(scale=3):
|
||||
steps = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.steps,
|
||||
step=1,
|
||||
label="Steps",
|
||||
)
|
||||
batch_count = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.batch_count,
|
||||
step=1,
|
||||
label="Batch Count",
|
||||
interactive=True,
|
||||
)
|
||||
batch_size = gr.Slider(
|
||||
1,
|
||||
4,
|
||||
value=cmd_opts.batch_size,
|
||||
step=1,
|
||||
label="Batch Size",
|
||||
interactive=True,
|
||||
visible=True,
|
||||
)
|
||||
repeatable_seeds = gr.Checkbox(
|
||||
cmd_opts.repeatable_seeds,
|
||||
label="Repeatable Seeds",
|
||||
)
|
||||
with gr.Column(scale=3):
|
||||
strength = gr.Slider(
|
||||
0,
|
||||
1,
|
||||
value=cmd_opts.strength,
|
||||
step=0.01,
|
||||
label="Denoising Strength",
|
||||
)
|
||||
resample_type = gr.Dropdown(
|
||||
value=cmd_opts.resample_type,
|
||||
choices=resampler_list,
|
||||
label="Resample Type",
|
||||
allow_custom_value=True,
|
||||
)
|
||||
guidance_scale = gr.Slider(
|
||||
0,
|
||||
50,
|
||||
value=cmd_opts.guidance_scale,
|
||||
step=0.1,
|
||||
label="CFG Scale",
|
||||
)
|
||||
with gr.Row():
|
||||
resample_type = gr.Dropdown(
|
||||
value=cmd_opts.resample_type,
|
||||
choices=resampler_list,
|
||||
label="Resample Type",
|
||||
allow_custom_value=True,
|
||||
)
|
||||
with gr.Group(elem_id="prompt_box_outer"):
|
||||
prompt = gr.Textbox(
|
||||
label="\U00002795\U0000FE0F Prompt",
|
||||
value=cmd_opts.prompt[0],
|
||||
lines=2,
|
||||
elem_id="prompt_box",
|
||||
show_copy_button=True,
|
||||
)
|
||||
negative_prompt = gr.Textbox(
|
||||
label="\U00002796\U0000FE0F Negative Prompt",
|
||||
value=cmd_opts.negative_prompt[0],
|
||||
lines=2,
|
||||
elem_id="negative_prompt_box",
|
||||
show_copy_button=True,
|
||||
)
|
||||
with gr.Row(equal_height=True):
|
||||
seed = gr.Textbox(
|
||||
value=cmd_opts.seed,
|
||||
label="Seed",
|
||||
label="\U0001F331\U0000FE0F Seed",
|
||||
info="An integer or a JSON list of integers, -1 for random",
|
||||
show_copy_button=True,
|
||||
)
|
||||
device = gr.Dropdown(
|
||||
elem_id="device",
|
||||
label="Device",
|
||||
value=global_obj.get_device_list()[0],
|
||||
choices=global_obj.get_device_list(),
|
||||
scheduler = gr.Dropdown(
|
||||
elem_id="scheduler",
|
||||
label="\U0001F4C5\U0000FE0F Scheduler",
|
||||
info="\U000E0020", # forces same height as seed
|
||||
value="EulerDiscrete",
|
||||
choices=scheduler_model_map.keys(),
|
||||
allow_custom_value=False,
|
||||
)
|
||||
with gr.Row():
|
||||
steps = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.steps,
|
||||
step=1,
|
||||
label="\U0001F3C3\U0000FE0F Steps",
|
||||
)
|
||||
guidance_scale = gr.Slider(
|
||||
0,
|
||||
50,
|
||||
value=cmd_opts.guidance_scale,
|
||||
step=0.1,
|
||||
label="\U0001F5C3\U0000FE0F CFG Scale",
|
||||
)
|
||||
with gr.Accordion(
|
||||
label="Controlnet Options",
|
||||
open=False,
|
||||
@@ -547,16 +504,6 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
"Submit",
|
||||
size="sm",
|
||||
)
|
||||
use_input_img.click(
|
||||
fn=import_original,
|
||||
inputs=[
|
||||
sd_init_image,
|
||||
canvas_width,
|
||||
canvas_height,
|
||||
],
|
||||
outputs=[cnet_input],
|
||||
queue=False,
|
||||
)
|
||||
make_canvas.click(
|
||||
fn=create_canvas,
|
||||
inputs=[canvas_width, canvas_height],
|
||||
@@ -589,156 +536,219 @@ with gr.Blocks(title="Stable Diffusion") as sd_element:
|
||||
queue=False,
|
||||
)
|
||||
with gr.Column(scale=3, min_width=600):
|
||||
with gr.Group():
|
||||
sd_gallery = gr.Gallery(
|
||||
label="Generated images",
|
||||
show_label=False,
|
||||
elem_id="gallery",
|
||||
columns=2,
|
||||
object_fit="fit",
|
||||
preview=True,
|
||||
with gr.Tabs() as sd_tabs:
|
||||
sd_element.load(
|
||||
# Workaround for Gradio issue #7085
|
||||
# TODO: revert to setting selected= in gr.Tabs declaration
|
||||
# once this is resolved in Gradio
|
||||
lambda: gr.Tabs(selected=101),
|
||||
outputs=[sd_tabs],
|
||||
)
|
||||
std_output = gr.Textbox(
|
||||
value=f"{sd_model_info}\n"
|
||||
f"Images will be saved at "
|
||||
f"{get_generated_imgs_path()}",
|
||||
lines=2,
|
||||
elem_id="std_output",
|
||||
show_label=False,
|
||||
)
|
||||
sd_element.load(logger.read_sd_logs, None, std_output, every=1)
|
||||
sd_status = gr.Textbox(visible=False)
|
||||
with gr.Row():
|
||||
stable_diffusion = gr.Button("Generate Image(s)")
|
||||
random_seed = gr.Button("Randomize Seed")
|
||||
random_seed.click(
|
||||
lambda: -1,
|
||||
inputs=[],
|
||||
outputs=[seed],
|
||||
queue=False,
|
||||
show_progress=False,
|
||||
)
|
||||
stop_batch = gr.Button("Stop Batch")
|
||||
with gr.Group():
|
||||
with gr.Column(scale=3):
|
||||
sd_json = gr.JSON(
|
||||
value=view_json_file(
|
||||
os.path.join(
|
||||
get_configs_path(),
|
||||
"default_sd_config.json",
|
||||
with gr.Tab(label="Input Image", id=100) as sd_tab_init_image:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
# TODO: make this import image prompt info if it exists
|
||||
sd_init_image = gr.Image(
|
||||
type="pil",
|
||||
interactive=True,
|
||||
show_label=False,
|
||||
)
|
||||
use_input_img.click(
|
||||
fn=import_original,
|
||||
inputs=[
|
||||
sd_init_image,
|
||||
canvas_width,
|
||||
canvas_height,
|
||||
],
|
||||
outputs=[cnet_input],
|
||||
queue=False,
|
||||
)
|
||||
with gr.Tab(label="Generate Images", id=101) as sd_tab_gallery:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
sd_gallery = gr.Gallery(
|
||||
label="Generated images",
|
||||
show_label=False,
|
||||
elem_id="gallery",
|
||||
columns=2,
|
||||
object_fit="fit",
|
||||
preview=True,
|
||||
)
|
||||
with gr.Row():
|
||||
std_output = gr.Textbox(
|
||||
value=f"{sd_model_info}\n"
|
||||
f"Images will be saved at "
|
||||
f"{get_generated_imgs_path()}",
|
||||
lines=2,
|
||||
elem_id="std_output",
|
||||
show_label=True,
|
||||
label="Log",
|
||||
show_copy_button=True,
|
||||
)
|
||||
sd_element.load(
|
||||
logger.read_sd_logs, None, std_output, every=1
|
||||
)
|
||||
sd_status = gr.Textbox(visible=False)
|
||||
with gr.Row():
|
||||
batch_count = gr.Slider(
|
||||
1,
|
||||
100,
|
||||
value=cmd_opts.batch_count,
|
||||
step=1,
|
||||
label="Batch Count",
|
||||
interactive=True,
|
||||
)
|
||||
batch_size = gr.Slider(
|
||||
1,
|
||||
4,
|
||||
value=cmd_opts.batch_size,
|
||||
step=1,
|
||||
label="Batch Size",
|
||||
interactive=True,
|
||||
visible=True,
|
||||
)
|
||||
repeatable_seeds = gr.Checkbox(
|
||||
cmd_opts.repeatable_seeds,
|
||||
label="Use Repeatable Seeds for Batches",
|
||||
)
|
||||
with gr.Row():
|
||||
stable_diffusion = gr.Button("Start")
|
||||
random_seed = gr.Button("Randomize Seed")
|
||||
random_seed.click(
|
||||
lambda: -1,
|
||||
inputs=[],
|
||||
outputs=[seed],
|
||||
queue=False,
|
||||
show_progress=False,
|
||||
)
|
||||
stop_batch = gr.Button("Stop")
|
||||
with gr.Tab(label="Config", id=102) as sd_tab_config:
|
||||
with gr.Column(elem_classes=["sd-right-panel"]):
|
||||
with gr.Row(elem_classes=["fill"]):
|
||||
sd_json = gr.JSON(
|
||||
elem_classes=["fill"],
|
||||
value=view_json_file(
|
||||
os.path.join(
|
||||
get_configs_path(),
|
||||
"default_sd_config.json",
|
||||
)
|
||||
),
|
||||
)
|
||||
with gr.Row():
|
||||
with gr.Column(scale=3):
|
||||
load_sd_config = gr.FileExplorer(
|
||||
label="Load Config",
|
||||
file_count="single",
|
||||
root=(
|
||||
cmd_opts.configs_path
|
||||
if cmd_opts.configs_path
|
||||
else get_configs_path()
|
||||
),
|
||||
height=75,
|
||||
)
|
||||
with gr.Column(scale=1):
|
||||
save_sd_config = gr.Button(
|
||||
value="Save Config", size="sm"
|
||||
)
|
||||
clear_sd_config = gr.ClearButton(
|
||||
value="Clear Config",
|
||||
size="sm",
|
||||
components=sd_json,
|
||||
)
|
||||
with gr.Row():
|
||||
sd_config_name = gr.Textbox(
|
||||
value="Config Name",
|
||||
info="Name of the file this config will be saved to.",
|
||||
interactive=True,
|
||||
show_label=False,
|
||||
)
|
||||
load_sd_config.change(
|
||||
fn=load_sd_cfg,
|
||||
inputs=[sd_json, load_sd_config],
|
||||
outputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
ondemand,
|
||||
repeatable_seeds,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
save_sd_config.click(
|
||||
fn=save_sd_cfg,
|
||||
inputs=[sd_json, sd_config_name],
|
||||
outputs=[sd_config_name],
|
||||
)
|
||||
)
|
||||
)
|
||||
with gr.Column(scale=1):
|
||||
clear_sd_config = gr.ClearButton(
|
||||
value="Clear Config", size="sm", components=sd_json
|
||||
)
|
||||
with gr.Row():
|
||||
save_sd_config = gr.Button(value="Save Config", size="sm")
|
||||
sd_config_name = gr.Textbox(
|
||||
value="Config Name",
|
||||
info="Name of the file this config will be saved to.",
|
||||
interactive=True,
|
||||
)
|
||||
load_sd_config = gr.FileExplorer(
|
||||
label="Load Config",
|
||||
file_count="single",
|
||||
root=(
|
||||
cmd_opts.configs_path
|
||||
if cmd_opts.configs_path
|
||||
else get_configs_path()
|
||||
),
|
||||
height=75,
|
||||
)
|
||||
load_sd_config.change(
|
||||
fn=load_sd_cfg,
|
||||
inputs=[sd_json, load_sd_config],
|
||||
outputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
ondemand,
|
||||
repeatable_seeds,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
save_sd_config.click(
|
||||
fn=save_sd_cfg,
|
||||
inputs=[sd_json, sd_config_name],
|
||||
outputs=[sd_config_name],
|
||||
)
|
||||
|
||||
pull_kwargs = dict(
|
||||
fn=pull_sd_configs,
|
||||
inputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
ondemand,
|
||||
repeatable_seeds,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
],
|
||||
outputs=[
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
pull_kwargs = dict(
|
||||
fn=pull_sd_configs,
|
||||
inputs=[
|
||||
prompt,
|
||||
negative_prompt,
|
||||
sd_init_image,
|
||||
height,
|
||||
width,
|
||||
steps,
|
||||
strength,
|
||||
guidance_scale,
|
||||
seed,
|
||||
batch_count,
|
||||
batch_size,
|
||||
scheduler,
|
||||
base_model_id,
|
||||
custom_weights,
|
||||
custom_vae,
|
||||
precision,
|
||||
device,
|
||||
ondemand,
|
||||
repeatable_seeds,
|
||||
resample_type,
|
||||
cnet_config,
|
||||
embeddings_config,
|
||||
],
|
||||
outputs=[
|
||||
sd_json,
|
||||
],
|
||||
)
|
||||
|
||||
status_kwargs = dict(
|
||||
fn=lambda bc, bs: status_label("Stable Diffusion", 0, bc, bs),
|
||||
inputs=[batch_count, batch_size],
|
||||
outputs=sd_status,
|
||||
)
|
||||
status_kwargs = dict(
|
||||
fn=lambda bc, bs: status_label("Stable Diffusion", 0, bc, bs),
|
||||
inputs=[batch_count, batch_size],
|
||||
outputs=sd_status,
|
||||
)
|
||||
|
||||
gen_kwargs = dict(
|
||||
fn=shark_sd_fn_dict_input,
|
||||
inputs=[sd_json],
|
||||
outputs=[
|
||||
sd_gallery,
|
||||
sd_status,
|
||||
],
|
||||
)
|
||||
gen_kwargs = dict(
|
||||
fn=shark_sd_fn_dict_input,
|
||||
inputs=[sd_json],
|
||||
outputs=[
|
||||
sd_gallery,
|
||||
sd_status,
|
||||
],
|
||||
)
|
||||
|
||||
prompt_submit = prompt.submit(**status_kwargs).then(**pull_kwargs)
|
||||
neg_prompt_submit = negative_prompt.submit(**status_kwargs).then(**pull_kwargs)
|
||||
generate_click = (
|
||||
stable_diffusion.click(**status_kwargs)
|
||||
.then(**pull_kwargs)
|
||||
.then(**gen_kwargs)
|
||||
)
|
||||
stop_batch.click(
|
||||
fn=cancel_sd,
|
||||
cancels=[prompt_submit, neg_prompt_submit, generate_click],
|
||||
)
|
||||
prompt_submit = prompt.submit(**status_kwargs).then(**pull_kwargs)
|
||||
neg_prompt_submit = negative_prompt.submit(**status_kwargs).then(**pull_kwargs)
|
||||
generate_click = (
|
||||
stable_diffusion.click(**status_kwargs).then(**pull_kwargs).then(**gen_kwargs)
|
||||
)
|
||||
stop_batch.click(
|
||||
fn=cancel_sd,
|
||||
cancels=[prompt_submit, neg_prompt_submit, generate_click],
|
||||
)
|
||||
|
||||
@@ -26,7 +26,7 @@ parameterized
|
||||
accelerate
|
||||
scipy
|
||||
ftfy
|
||||
gradio==4.8.0
|
||||
gradio==4.15.0
|
||||
altair
|
||||
omegaconf
|
||||
# 0.3.2 doesn't have binaries for arm64
|
||||
|
||||
Reference in New Issue
Block a user