Merge branch 'master' into remove-watermark-option

.github/workflows/run_tests.yaml

@@ -18,7 +18,7 @@ jobs:
           cache-dependency-path: |
             **/requirements*txt
       - name: Run tests
-        run: python launch.py --tests --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test
+        run: python launch.py --tests test --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test
       - name: Upload main app stdout-stderr
         uses: actions/upload-artifact@v3
         if: always()

README.md

@@ -13,9 +13,9 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Prompt Matrix
 - Stable Diffusion Upscale
 - Attention, specify parts of text that the model should pay more attention to
-    - a man in a ((tuxedo)) - will pay more attention to tuxedo
-    - a man in a (tuxedo:1.21) - alternative syntax
-    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)
+    - a man in a `((tuxedo))` - will pay more attention to tuxedo
+    - a man in a `(tuxedo:1.21)` - alternative syntax
+    - select text and press `Ctrl+Up` or `Ctrl+Down` to automatically adjust attention to selected text (code contributed by anonymous user)
 - Loopback, run img2img processing multiple times
 - X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters
 - Textual Inversion
@@ -28,7 +28,7 @@ A browser interface based on Gradio library for Stable Diffusion.
     - CodeFormer, face restoration tool as an alternative to GFPGAN
     - RealESRGAN, neural network upscaler
     - ESRGAN, neural network upscaler with a lot of third party models
-    - SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
+    - SwinIR and Swin2SR ([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
     - LDSR, Latent diffusion super resolution upscaling
 - Resizing aspect ratio options
 - Sampling method selection
@@ -46,7 +46,7 @@ A browser interface based on Gradio library for Stable Diffusion.
      - drag and drop an image/text-parameters to promptbox
 - Read Generation Parameters Button, loads parameters in promptbox to UI
 - Settings page
-- Running arbitrary python code from UI (must run with --allow-code to enable)
+- Running arbitrary python code from UI (must run with `--allow-code` to enable)
 - Mouseover hints for most UI elements
 - Possible to change defaults/mix/max/step values for UI elements via text config
 - Tiling support, a checkbox to create images that can be tiled like textures
@@ -69,7 +69,7 @@ A browser interface based on Gradio library for Stable Diffusion.
      - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
 - No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
 - DeepDanbooru integration, creates danbooru style tags for anime prompts
-- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)
+- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add `--xformers` to commandline args)
 - via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
 - Generate forever option
 - Training tab
@@ -78,11 +78,11 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Clip skip
 - Hypernetworks
 - Loras (same as Hypernetworks but more pretty)
-- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt. 
+- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt 
 - Can select to load a different VAE from settings screen
 - Estimated completion time in progress bar
 - API
-- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.
+- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML
 - via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
 - [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
 - [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions
@@ -91,7 +91,6 @@ A browser interface based on Gradio library for Stable Diffusion.
 - Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64
 - Now with a license!
 - Reorder elements in the UI from settings screen
-- 
 
 ## Installation and Running
 Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
@@ -101,7 +100,7 @@ Alternatively, use online services (like Google Colab):
 - [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
 
 ### Automatic Installation on Windows
-1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH"
+1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH".
 2. Install [git](https://git-scm.com/download/win).
 3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.
 4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.

extensions-builtin/Lora/scripts/lora_script.py

@@ -9,7 +9,11 @@ from modules import script_callbacks, ui_extra_networks, extra_networks, shared
 
 def unload():
     torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora
+    torch.nn.Linear._load_from_state_dict = torch.nn.Linear_load_state_dict_before_lora
     torch.nn.Conv2d.forward = torch.nn.Conv2d_forward_before_lora
+    torch.nn.Conv2d._load_from_state_dict = torch.nn.Conv2d_load_state_dict_before_lora
+    torch.nn.MultiheadAttention.forward = torch.nn.MultiheadAttention_forward_before_lora
+    torch.nn.MultiheadAttention._load_from_state_dict = torch.nn.MultiheadAttention_load_state_dict_before_lora
 
 
 def before_ui():
@@ -20,11 +24,27 @@ def before_ui():
 if not hasattr(torch.nn, 'Linear_forward_before_lora'):
     torch.nn.Linear_forward_before_lora = torch.nn.Linear.forward
 
+if not hasattr(torch.nn, 'Linear_load_state_dict_before_lora'):
+    torch.nn.Linear_load_state_dict_before_lora = torch.nn.Linear._load_from_state_dict
+
 if not hasattr(torch.nn, 'Conv2d_forward_before_lora'):
     torch.nn.Conv2d_forward_before_lora = torch.nn.Conv2d.forward
 
+if not hasattr(torch.nn, 'Conv2d_load_state_dict_before_lora'):
+    torch.nn.Conv2d_load_state_dict_before_lora = torch.nn.Conv2d._load_from_state_dict
+
+if not hasattr(torch.nn, 'MultiheadAttention_forward_before_lora'):
+    torch.nn.MultiheadAttention_forward_before_lora = torch.nn.MultiheadAttention.forward
+
+if not hasattr(torch.nn, 'MultiheadAttention_load_state_dict_before_lora'):
+    torch.nn.MultiheadAttention_load_state_dict_before_lora = torch.nn.MultiheadAttention._load_from_state_dict
+
 torch.nn.Linear.forward = lora.lora_Linear_forward
+torch.nn.Linear._load_from_state_dict = lora.lora_Linear_load_state_dict
 torch.nn.Conv2d.forward = lora.lora_Conv2d_forward
+torch.nn.Conv2d._load_from_state_dict = lora.lora_Conv2d_load_state_dict
+torch.nn.MultiheadAttention.forward = lora.lora_MultiheadAttention_forward
+torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention_load_state_dict
 
 script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules)
 script_callbacks.on_script_unloaded(unload)
@@ -33,6 +53,4 @@ script_callbacks.on_before_ui(before_ui)
 
 shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
     "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
-    "lora_apply_to_outputs": shared.OptionInfo(False, "Apply Lora to outputs rather than inputs when possible (experimental)"),
-
 }))

extensions-builtin/prompt-bracket-checker/javascript/prompt-bracket-checker.js

@@ -89,22 +89,15 @@ function checkBrackets(evt, textArea, counterElt) {
 function setupBracketChecking(id_prompt, id_counter){
     var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");
     var counter = gradioApp().getElementById(id_counter)
+
     textarea.addEventListener("input", function(evt){
         checkBrackets(evt, textarea, counter)
     });
 }
 
-var shadowRootLoaded = setInterval(function() {
-    var shadowRoot = document.querySelector('gradio-app').shadowRoot;
-    if(! shadowRoot)  return false;
-
-    var shadowTextArea = shadowRoot.querySelectorAll('#txt2img_prompt > label > textarea');
-    if(shadowTextArea.length < 1)  return false;
-
-    clearInterval(shadowRootLoaded);
-
+onUiLoaded(function(){
     setupBracketChecking('txt2img_prompt', 'txt2img_token_counter')
     setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter')
-    setupBracketChecking('img2img_prompt', 'imgimg_token_counter')
+    setupBracketChecking('img2img_prompt', 'img2img_token_counter')
     setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter')
-}, 1000);
+})
\ No newline at end of file

html/extra-networks-card.html

-<div class='card' {preview_html} onclick={card_clicked}>
+<div class='card' style={style} onclick={card_clicked}>
 	{metadata_button}
 
 	<div class='actions'>

html/licenses.html

@@ -636,3 +636,29 @@ SOFTWARE.
    See the License for the specific language governing permissions and
    limitations under the License.
 </pre>
+
+<h2><a href="https://github.com/explosion/curated-transformers/blob/main/LICENSE">Curated transformers</a></h2>
+<small>The MPS workaround for nn.Linear on macOS 13.2.X is based on the MPS workaround for nn.Linear created by danieldk for Curated transformers</small>
+<pre>
+The MIT License (MIT)
+
+Copyright (C) 2021 ExplosionAI GmbH
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
+</pre>
\ No newline at end of file

javascript/aspectRatioOverlay.js

@@ -12,7 +12,7 @@ function dimensionChange(e, is_width, is_height){
 		currentHeight = e.target.value*1.0
 	}
 
-	var inImg2img   = Boolean(gradioApp().querySelector("button.rounded-t-lg.border-gray-200"))
+	var inImg2img = gradioApp().querySelector("#tab_img2img").style.display == "block";
 
 	if(!inImg2img){
 		return;
@@ -22,7 +22,7 @@ function dimensionChange(e, is_width, is_height){
 
     var tabIndex = get_tab_index('mode_img2img')
 	if(tabIndex == 0){ // img2img
-		targetElement = gradioApp().querySelector('div[data-testid=image] img');
+		targetElement = gradioApp().querySelector('#img2img_image div[data-testid=image] img');
 	} else if(tabIndex == 1){ //Sketch
 		targetElement = gradioApp().querySelector('#img2img_sketch div[data-testid=image] img');
 	} else if(tabIndex == 2){ // Inpaint
@@ -38,7 +38,7 @@ function dimensionChange(e, is_width, is_height){
 		if(!arPreviewRect){
 		    arPreviewRect = document.createElement('div')
 		    arPreviewRect.id = "imageARPreview";
-		    gradioApp().getRootNode().appendChild(arPreviewRect)
+		    gradioApp().appendChild(arPreviewRect)
 		}
 
 
@@ -91,7 +91,9 @@ onUiUpdate(function(){
 	if(arPreviewRect){
 		arPreviewRect.style.display = 'none';
 	}
-	var inImg2img   = Boolean(gradioApp().querySelector("button.rounded-t-lg.border-gray-200"))
+    var tabImg2img = gradioApp().querySelector("#tab_img2img");
+    if (tabImg2img) {
+        var inImg2img = tabImg2img.style.display == "block";
         if(inImg2img){
             let inputs = gradioApp().querySelectorAll('input');
             inputs.forEach(function(e){
@@ -110,4 +112,5 @@ onUiUpdate(function(){
                 }
             })
         }
+    }
 });

javascript/contextMenus.js

@@ -43,7 +43,7 @@ contextMenuInit = function(){
 
     })
 
-    gradioApp().getRootNode().appendChild(contextMenu)
+    gradioApp().appendChild(contextMenu)
 
     let menuWidth = contextMenu.offsetWidth + 4;
     let menuHeight = contextMenu.offsetHeight + 4;

javascript/edit-attention.js

 function keyupEditAttention(event){
 	let target = event.originalTarget || event.composedPath()[0];
-	if (!target.matches("[id*='_toprow'] textarea.gr-text-input[placeholder]")) return;
+	if (! target.matches("[id*='_toprow'] [id*='_prompt'] textarea")) return;
 	if (! (event.metaKey || event.ctrlKey)) return;
 
 	let isPlus = event.key == "ArrowUp"

javascript/extraNetworks.js

@@ -139,3 +139,41 @@ function extraNetworksShowMetadata(text){
 
     popup(elem);
 }
+
+function requestGet(url, data, handler, errorHandler){
+    var xhr = new XMLHttpRequest();
+    var args = Object.keys(data).map(function(k){ return encodeURIComponent(k) + '=' + encodeURIComponent(data[k]) }).join('&')
+    xhr.open("GET", url + "?" + args, true);
+
+    xhr.onreadystatechange = function () {
+        if (xhr.readyState === 4) {
+            if (xhr.status === 200) {
+                try {
+                    var js = JSON.parse(xhr.responseText);
+                    handler(js)
+                } catch (error) {
+                    console.error(error);
+                    errorHandler()
+                }
+            } else{
+                errorHandler()
+            }
+        }
+    };
+    var js = JSON.stringify(data);
+    xhr.send(js);
+}
+
+function extraNetworksRequestMetadata(event, extraPage, cardName){
+    showError = function(){ extraNetworksShowMetadata("there was an error getting metadata"); }
+
+    requestGet("./sd_extra_networks/metadata", {"page": extraPage, "item": cardName}, function(data){
+        if(data && data.metadata){
+            extraNetworksShowMetadata(data.metadata)
+        } else{
+            showError()
+        }
+    }, showError)
+
+    event.stopPropagation()
+}

javascript/hints.js

@@ -18,11 +18,10 @@ titles = {
     "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.",
     "\u{1f4c2}": "Open images output directory",
     "\u{1f4be}": "Save style",
-    "\u{1f5d1}": "Clear prompt",
+    "\u{1f5d1}\ufe0f": "Clear prompt",
     "\u{1f4cb}": "Apply selected styles to current prompt",
     "\u{1f4d2}": "Paste available values into the field",
-    "\u{1f3b4}": "Show extra networks",
-
+    "\u{1f3b4}": "Show/hide extra networks",
 
     "Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
     "SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
@@ -40,7 +39,6 @@ titles = {
     "Inpaint at full resolution": "Upscale masked region to target resolution, do inpainting, downscale back and paste into original image",
 
     "Denoising strength": "Determines how little respect the algorithm should have for image's content. At 0, nothing will change, and at 1 you'll get an unrelated image. With values below 1.0, processing will take less steps than the Sampling Steps slider specifies.",
-    "Denoising strength change factor": "In loopback mode, on each loop the denoising strength is multiplied by this value. <1 means decreasing variety so your sequence will converge on a fixed picture. >1 means increasing variety so your sequence will become more and more chaotic.",
     
     "Skip": "Stop processing current image and continue processing.",
     "Interrupt": "Stop processing images and return any results accumulated so far.",
@@ -71,8 +69,10 @@ titles = {
     "Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg],[prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime<Format>], [datetime<Format><Time Zone>], [job_timestamp]; leave empty for default.",
     "Max prompt words": "Set the maximum number of words to be used in the [prompt_words] option; ATTENTION: If the words are too long, they may exceed the maximum length of the file path that the system can handle",
 
-    "Loopback": "Process an image, use it as an input, repeat.",
-    "Loops": "How many times to repeat processing an image and using it as input for the next iteration",
+    "Loopback": "Performs img2img processing multiple times. Output images are used as input for the next loop.",
+    "Loops": "How many times to process an image. Each output is used as the input of the next loop. If set to 1, behavior will be as if this script were not used.",
+    "Final denoising strength": "The denoising strength for the final loop of each image in the batch.",
+    "Denoising strength curve": "The denoising curve controls the rate of denoising strength change each loop. Aggressive: Most of the change will happen towards the start of the loops. Linear: Change will be constant through all loops. Lazy: Most of the change will happen towards the end of the loops.",
 
     "Style 1": "Style to apply; styles have components for both positive and negative prompts and apply to both",
     "Style 2": "Style to apply; styles have components for both positive and negative prompts and apply to both",

javascript/imageviewer.js

@@ -32,13 +32,7 @@ function negmod(n, m) {
 function updateOnBackgroundChange() {
     const modalImage = gradioApp().getElementById("modalImage")
     if (modalImage && modalImage.offsetParent) {
-        let allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
-        let currentButton = null
-        allcurrentButtons.forEach(function(elem) {
-            if (elem.parentElement.offsetParent) {
-                currentButton = elem;
-            }
-        })
+        let currentButton = selected_gallery_button();
 
         if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
             modalImage.src = currentButton.children[0].src;
@@ -50,22 +44,10 @@ function updateOnBackgroundChange() {
 }
 
 function modalImageSwitch(offset) {
-    var allgalleryButtons = gradioApp().querySelectorAll(".gallery-item.transition-all")
-    var galleryButtons = []
-    allgalleryButtons.forEach(function(elem) {
-        if (elem.parentElement.offsetParent) {
-            galleryButtons.push(elem);
-        }
-    })
+    var galleryButtons = all_gallery_buttons();
 
     if (galleryButtons.length > 1) {
-        var allcurrentButtons = gradioApp().querySelectorAll(".gallery-item.transition-all.\\!ring-2")
-        var currentButton = null
-        allcurrentButtons.forEach(function(elem) {
-            if (elem.parentElement.offsetParent) {
-                currentButton = elem;
-            }
-        })
+        var currentButton = selected_gallery_button();
 
         var result = -1
         galleryButtons.forEach(function(v, i) {
@@ -136,20 +118,15 @@ function modalKeyHandler(event) {
     }
 }
 
-function showGalleryImage() {
-    setTimeout(function() {
-        fullImg_preview = gradioApp().querySelectorAll('img.w-full.object-contain')
-
-        if (fullImg_preview != null) {
-            fullImg_preview.forEach(function function_name(e) {
+function setupImageForLightbox(e) {
 	if (e.dataset.modded)
 		return;
+
 	e.dataset.modded = true;
-                if(e && e.parentElement.tagName == 'DIV'){
 	e.style.cursor='pointer'
 	e.style.userSelect='none'
 
-                    var isFirefox = isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1
+	var isFirefox = navigator.userAgent.toLowerCase().indexOf('firefox') > -1
 
 	// For Firefox, listening on click first switched to next image then shows the lightbox.
 	// If you know how to fix this without switching to mousedown event, please.
@@ -158,15 +135,12 @@ function showGalleryImage() {
 
 	e.addEventListener(event, function (evt) {
 		if(!opts.js_modal_lightbox || evt.button != 0) return;
+
 		modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)
 		evt.preventDefault()
 		showModal(evt)
 	}, true);
-                }
-            });
-        }
 
-    }, 100);
 }
 
 function modalZoomSet(modalImage, enable) {
@@ -199,21 +173,21 @@ function modalTileImageToggle(event) {
 }
 
 function galleryImageHandler(e) {
-    if (e && e.parentElement.tagName == 'BUTTON') {
+    //if (e && e.parentElement.tagName == 'BUTTON') {
         e.onclick = showGalleryImage;
-    }
+    //}
 }
 
 onUiUpdate(function() {
-    fullImg_preview = gradioApp().querySelectorAll('img.w-full')
+    fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img')
     if (fullImg_preview != null) {
-        fullImg_preview.forEach(galleryImageHandler);
+        fullImg_preview.forEach(setupImageForLightbox);
     }
     updateOnBackgroundChange();
 })
 
 document.addEventListener("DOMContentLoaded", function() {
-    const modalFragment = document.createDocumentFragment();
+    //const modalFragment = document.createDocumentFragment();
     const modal = document.createElement('div')
     modal.onclick = closeModal;
     modal.id = "lightboxModal";
@@ -277,9 +251,9 @@ document.addEventListener("DOMContentLoaded", function() {
 
     modal.appendChild(modalNext)
 
+    gradioApp().appendChild(modal)
 
-    gradioApp().getRootNode().appendChild(modal)
 
-    document.body.appendChild(modalFragment);
+    document.body.appendChild(modal);
 
 });

javascript/notification.js

@@ -15,7 +15,7 @@ onUiUpdate(function(){
         }
     }
 
-    const galleryPreviews = gradioApp().querySelectorAll('div[id^="tab_"][style*="display: block"] div[id$="_results"] img.h-full.w-full.overflow-hidden');
+    const galleryPreviews = gradioApp().querySelectorAll('div[id^="tab_"][style*="display: block"] div[id$="_results"] .thumbnail-item > img');
 
     if (galleryPreviews == null) return;
 

javascript/progressbar.js

 // code related to showing and updating progressbar shown as the image is being made
 
-
-galleries = {}
-storedGallerySelections = {}
-galleryObservers = {}
-
 function rememberGallerySelection(id_gallery){
-    storedGallerySelections[id_gallery] = getGallerySelectedIndex(id_gallery)
+
 }
 
 function getGallerySelectedIndex(id_gallery){
-    let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
-    let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
-
-     let currentlySelectedIndex = -1
-     galleryButtons.forEach(function(v, i){ if(v==galleryBtnSelected) { currentlySelectedIndex = i } })
-
-     return currentlySelectedIndex
-}
 
-// this is a workaround for https://github.com/gradio-app/gradio/issues/2984
-function check_gallery(id_gallery){
-    let gallery = gradioApp().getElementById(id_gallery)
-    // if gallery has no change, no need to setting up observer again.
-    if (gallery && galleries[id_gallery] !== gallery){
-        galleries[id_gallery] = gallery;
-        if(galleryObservers[id_gallery]){
-            galleryObservers[id_gallery].disconnect();
-        }
-
-        storedGallerySelections[id_gallery] = -1
-
-        galleryObservers[id_gallery] = new MutationObserver(function (){
-            let galleryButtons = gradioApp().querySelectorAll('#'+id_gallery+' .gallery-item')
-            let galleryBtnSelected = gradioApp().querySelector('#'+id_gallery+' .gallery-item.\\!ring-2')
-            let currentlySelectedIndex = getGallerySelectedIndex(id_gallery)
-            prevSelectedIndex = storedGallerySelections[id_gallery]
-            storedGallerySelections[id_gallery] = -1
-
-            if (prevSelectedIndex !== -1 && galleryButtons.length>prevSelectedIndex && !galleryBtnSelected) {
-                // automatically re-open previously selected index (if exists)
-                activeElement = gradioApp().activeElement;
-                let scrollX = window.scrollX;
-                let scrollY = window.scrollY;
-
-                galleryButtons[prevSelectedIndex].click();
-                showGalleryImage();
-
-                // When the gallery button is clicked, it gains focus and scrolls itself into view
-                // We need to scroll back to the previous position
-                setTimeout(function (){
-                    window.scrollTo(scrollX, scrollY);
-                }, 50);
-
-                if(activeElement){
-                    // i fought this for about an hour; i don't know why the focus is lost or why this helps recover it
-                    // if someone has a better solution please by all means
-                    setTimeout(function (){
-                        activeElement.focus({
-                            preventScroll: true // Refocus the element that was focused before the gallery was opened without scrolling to it
-                        })
-                    }, 1);
-                }
-            }
-        })
-        galleryObservers[id_gallery].observe( gallery, { childList:true, subtree:false })
-    }
 }
 
-onUiUpdate(function(){
-    check_gallery('txt2img_gallery')
-    check_gallery('img2img_gallery')
-})
-
 function request(url, data, handler, errorHandler){
     var xhr = new XMLHttpRequest();
     var url = url;

javascript/ui.js

@@ -7,9 +7,31 @@ function set_theme(theme){
     }
 }
 
+function all_gallery_buttons() {
+    var allGalleryButtons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery].gradio-gallery .thumbnails > .thumbnail-item.thumbnail-small');
+    var visibleGalleryButtons = [];
+    allGalleryButtons.forEach(function(elem) {
+        if (elem.parentElement.offsetParent) {
+            visibleGalleryButtons.push(elem);
+        }
+    })
+    return visibleGalleryButtons;
+}
+
+function selected_gallery_button() {
+    var allCurrentButtons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery].gradio-gallery .thumbnail-item.thumbnail-small.selected');
+    var visibleCurrentButton = null;
+    allCurrentButtons.forEach(function(elem) {
+        if (elem.parentElement.offsetParent) {
+            visibleCurrentButton = elem;
+        }
+    })
+    return visibleCurrentButton;
+}
+
 function selected_gallery_index(){
-    var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item')
-    var button = gradioApp().querySelector('[style="display: block;"].tabitem div[id$=_gallery] .gallery-item.\\!ring-2')
+    var buttons = all_gallery_buttons();
+    var button = selected_gallery_button();
 
     var result = -1
     buttons.forEach(function(v, i){ if(v==button) { result = i } })
@@ -18,14 +40,18 @@ function selected_gallery_index(){
 }
 
 function extract_image_from_gallery(gallery){
-    if(gallery.length == 1){
-        return [gallery[0]]
+    if (gallery.length == 0){
+        return [null];
+    }
+    if (gallery.length == 1){
+        return [gallery[0]];
     }
 
     index = selected_gallery_index()
 
     if (index < 0 || index >= gallery.length){
-        return [null]
+        // Use the first image in the gallery as the default
+        index = 0;
     }
 
     return [gallery[index]];
@@ -86,7 +112,7 @@ function get_tab_index(tabId){
     var res = 0
 
     gradioApp().getElementById(tabId).querySelector('div').querySelectorAll('button').forEach(function(button, i){
-        if(button.className.indexOf('bg-white') != -1)
+        if(button.className.indexOf('selected') != -1)
             res = i
     })
 
@@ -255,7 +281,6 @@ onUiUpdate(function(){
         }
 
         prompt.parentElement.insertBefore(counter, prompt)
-        counter.classList.add("token-counter")
         prompt.parentElement.style.position = "relative"
 
 		promptTokecountUpdateFuncs[id] = function(){ update_token_counter(id_button); }

launch.py

@@ -5,24 +5,25 @@ import sys
 import importlib.util
 import shlex
 import platform
-import argparse
 import json
 
-parser = argparse.ArgumentParser(add_help=False)
-parser.add_argument("--ui-settings-file", type=str, default='config.json')
-parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.realpath(__file__)))
-args, _ = parser.parse_known_args(sys.argv)
+from modules import cmd_args
+from modules.paths_internal import script_path, extensions_dir
 
-script_path = os.path.dirname(__file__)
-data_path = os.getcwd()
+commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
+sys.argv += shlex.split(commandline_args)
+
+args, _ = cmd_args.parser.parse_known_args()
 
-dir_repos = "repositories"
-dir_extensions = "extensions"
 python = sys.executable
 git = os.environ.get('GIT', "git")
 index_url = os.environ.get('INDEX_URL', "")
 stored_commit_hash = None
 skip_install = False
+dir_repos = "repositories"
+
+if 'GRADIO_ANALYTICS_ENABLED' not in os.environ:
+    os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
 
 
 def check_python_version():
@@ -70,23 +71,6 @@ def commit_hash():
     return stored_commit_hash
 
 
-def extract_arg(args, name):
-    return [x for x in args if x != name], name in args
-
-
-def extract_opt(args, name):
-    opt = None
-    is_present = False
-    if name in args:
-        is_present = True
-        idx = args.index(name)
-        del args[idx]
-        if idx < len(args) and args[idx][0] != "-":
-            opt = args[idx]
-            del args[idx]
-    return args, is_present, opt
-
-
 def run(command, desc=None, errdesc=None, custom_env=None, live=False):
     if desc is not None:
         print(desc)
@@ -223,15 +207,15 @@ def list_extensions(settings_file):
 
     disabled_extensions = set(settings.get('disabled_extensions', []))
 
-    return [x for x in os.listdir(os.path.join(data_path, dir_extensions)) if x not in disabled_extensions]
+    return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions]
 
 
 def run_extensions_installers(settings_file):
-    if not os.path.isdir(dir_extensions):
+    if not os.path.isdir(extensions_dir):
         return
 
     for dirname_extension in list_extensions(settings_file):
-        run_extension_installer(os.path.join(dir_extensions, dirname_extension))
+        run_extension_installer(os.path.join(extensions_dir, dirname_extension))
 
 
 def prepare_environment():
@@ -239,7 +223,6 @@ def prepare_environment():
 
     torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
-    commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
 
     xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.16rc425')
     gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
@@ -258,21 +241,7 @@ def prepare_environment():
     codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
     blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
-    sys.argv += shlex.split(commandline_args)
-
-    sys.argv, _ = extract_arg(sys.argv, '-f')
-    sys.argv, update_all_extensions = extract_arg(sys.argv, '--update-all-extensions')
-    sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test')
-    sys.argv, skip_python_version_check = extract_arg(sys.argv, '--skip-python-version-check')
-    sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
-    sys.argv, reinstall_torch = extract_arg(sys.argv, '--reinstall-torch')
-    sys.argv, update_check = extract_arg(sys.argv, '--update-check')
-    sys.argv, run_tests, test_dir = extract_opt(sys.argv, '--tests')
-    sys.argv, skip_install = extract_arg(sys.argv, '--skip-install')
-    xformers = '--xformers' in sys.argv
-    ngrok = '--ngrok' in sys.argv
-
-    if not skip_python_version_check:
+    if not args.skip_python_version_check:
         check_python_version()
 
     commit = commit_hash()
@@ -280,10 +249,10 @@ def prepare_environment():
     print(f"Python {sys.version}")
     print(f"Commit hash: {commit}")
 
-    if reinstall_torch or not is_installed("torch") or not is_installed("torchvision"):
+    if args.reinstall_torch or not is_installed("torch") or not is_installed("torchvision"):
         run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True)
 
-    if not skip_torch_cuda_test:
+    if not args.skip_torch_cuda_test:
         run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
 
     if not is_installed("gfpgan"):
@@ -295,7 +264,7 @@ def prepare_environment():
     if not is_installed("open_clip"):
         run_pip(f"install {openclip_package}", "open_clip")
 
-    if (not is_installed("xformers") or reinstall_xformers) and xformers:
+    if (not is_installed("xformers") or args.reinstall_xformers) and args.xformers:
         if platform.system() == "Windows":
             if platform.python_version().startswith("3.10"):
                 run_pip(f"install -U -I --no-deps {xformers_package}", "xformers")
@@ -307,7 +276,7 @@ def prepare_environment():
         elif platform.system() == "Linux":
             run_pip(f"install {xformers_package}", "xformers")
 
-    if not is_installed("pyngrok") and ngrok:
+    if not is_installed("pyngrok") and args.ngrok:
         run_pip("install pyngrok", "ngrok")
 
     os.makedirs(os.path.join(script_path, dir_repos), exist_ok=True)
@@ -327,18 +296,18 @@ def prepare_environment():
 
     run_extensions_installers(settings_file=args.ui_settings_file)
 
-    if update_check:
+    if args.update_check:
         version_check(commit)
 
-    if update_all_extensions:
-        git_pull_recursive(os.path.join(data_path, dir_extensions))
+    if args.update_all_extensions:
+        git_pull_recursive(extensions_dir)
     
     if "--exit" in sys.argv:
         print("Exiting because of --exit argument")
         exit(0)
 
-    if run_tests:
-        exitcode = tests(test_dir)
+    if args.tests and not args.no_tests:
+        exitcode = tests(args.tests)
         exit(exitcode)
 
 
@@ -352,6 +321,8 @@ def tests(test_dir):
         sys.argv.append("--skip-torch-cuda-test")
     if "--disable-nan-check" not in sys.argv:
         sys.argv.append("--disable-nan-check")
+    if "--no-tests" not in sys.argv:
+        sys.argv.append("--no-tests")
 
     print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}")
 

modules/api/api.py

@@ -3,11 +3,15 @@ import io
 import time
 import datetime
 import uvicorn
+import gradio as gr
 from threading import Lock
 from io import BytesIO
 from gradio.processing_utils import decode_base64_to_file
-from fastapi import APIRouter, Depends, FastAPI, HTTPException, Request, Response
+from fastapi import APIRouter, Depends, FastAPI, Request, Response
 from fastapi.security import HTTPBasic, HTTPBasicCredentials
+from fastapi.exceptions import HTTPException
+from fastapi.responses import JSONResponse
+from fastapi.encoders import jsonable_encoder
 from secrets import compare_digest
 
 import modules.shared as shared
@@ -18,7 +22,7 @@ from modules.textual_inversion.textual_inversion import create_embedding, train_
 from modules.textual_inversion.preprocess import preprocess
 from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork
 from PIL import PngImagePlugin,Image
-from modules.sd_models import checkpoints_list
+from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights
 from modules.sd_models_config import find_checkpoint_config_near_filename
 from modules.realesrgan_model import get_realesrgan_models
 from modules import devices
@@ -90,6 +94,16 @@ def encode_pil_to_base64(image):
     return base64.b64encode(bytes_data)
 
 def api_middleware(app: FastAPI):
+    rich_available = True
+    try:
+        import anyio # importing just so it can be placed on silent list
+        import starlette # importing just so it can be placed on silent list
+        from rich.console import Console
+        console = Console()
+    except:
+        import traceback
+        rich_available = False
+
     @app.middleware("http")
     async def log_and_time(req: Request, call_next):
         ts = time.time()
@@ -110,6 +124,36 @@ def api_middleware(app: FastAPI):
             ))
         return res
 
+    def handle_exception(request: Request, e: Exception):
+        err = {
+            "error": type(e).__name__,
+            "detail": vars(e).get('detail', ''),
+            "body": vars(e).get('body', ''),
+            "errors": str(e),
+        }
+        print(f"API error: {request.method}: {request.url} {err}")
+        if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions
+            if rich_available:
+                console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200]))
+            else:
+                traceback.print_exc()
+        return JSONResponse(status_code=vars(e).get('status_code', 500), content=jsonable_encoder(err))
+
+    @app.middleware("http")
+    async def exception_handling(request: Request, call_next):
+        try:
+            return await call_next(request)
+        except Exception as e:
+            return handle_exception(request, e)
+
+    @app.exception_handler(Exception)
+    async def fastapi_exception_handler(request: Request, e: Exception):
+        return handle_exception(request, e)
+
+    @app.exception_handler(HTTPException)
+    async def http_exception_handler(request: Request, e: HTTPException):
+        return handle_exception(request, e)
+
 
 class Api:
     def __init__(self, app: FastAPI, queue_lock: Lock):
@@ -150,8 +194,13 @@ class Api:
         self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
         self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
         self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
+        self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
+        self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
 
+        self.default_script_arg_txt2img = []
+        self.default_script_arg_img2img = []
+
     def add_api_route(self, path: str, endpoint, **kwargs):
         if shared.cmd_opts.api_auth:
             return self.app.add_api_route(path, endpoint, dependencies=[Depends(self.auth)], **kwargs)
@@ -185,7 +234,7 @@ class Api:
         script_idx = script_name_to_index(script_name, script_runner.scripts)
         return script_runner.scripts[script_idx]
 
-    def init_script_args(self, request, selectable_scripts, selectable_idx, script_runner):
+    def init_default_script_args(self, script_runner):
         #find max idx from the scripts in runner and generate a none array to init script_args
         last_arg_index = 1
         for script in script_runner.scripts:
@@ -193,13 +242,24 @@ class Api:
                 last_arg_index = script.args_to
         # None everywhere except position 0 to initialize script args
         script_args = [None]*last_arg_index
+        script_args[0] = 0
+
+        # get default values
+        with gr.Blocks(): # will throw errors calling ui function without this
+            for script in script_runner.scripts:
+                if script.ui(script.is_img2img):
+                    ui_default_values = []
+                    for elem in script.ui(script.is_img2img):
+                        ui_default_values.append(elem.value)
+                    script_args[script.args_from:script.args_to] = ui_default_values
+        return script_args
+
+    def init_script_args(self, request, default_script_args, selectable_scripts, selectable_idx, script_runner):
+        script_args = default_script_args.copy()
         # position 0 in script_arg is the idx+1 of the selectable script that is going to be run when using scripts.scripts_*2img.run()
         if selectable_scripts:
             script_args[selectable_scripts.args_from:selectable_scripts.args_to] = request.script_args
             script_args[0] = selectable_idx + 1
-        else:
-            # when [0] = 0 no selectable script to run
-            script_args[0] = 0
 
         # Now check for always on scripts
         if request.alwayson_scripts and (len(request.alwayson_scripts) > 0):
@@ -220,6 +280,8 @@ class Api:
         if not script_runner.scripts:
             script_runner.initialize_scripts(False)
             ui.create_ui()
+        if not self.default_script_arg_txt2img:
+            self.default_script_arg_txt2img = self.init_default_script_args(script_runner)
         selectable_scripts, selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner)
 
         populate = txt2imgreq.copy(update={  # Override __init__ params
@@ -235,7 +297,7 @@ class Api:
         args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
         args.pop('alwayson_scripts', None)
 
-        script_args = self.init_script_args(txt2imgreq, selectable_scripts, selectable_script_idx, script_runner)
+        script_args = self.init_script_args(txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner)
 
         send_images = args.pop('send_images', True)
         args.pop('save_images', None)
@@ -272,6 +334,8 @@ class Api:
         if not script_runner.scripts:
             script_runner.initialize_scripts(True)
             ui.create_ui()
+        if not self.default_script_arg_img2img:
+            self.default_script_arg_img2img = self.init_default_script_args(script_runner)
         selectable_scripts, selectable_script_idx = self.get_selectable_script(img2imgreq.script_name, script_runner)
 
         populate = img2imgreq.copy(update={  # Override __init__ params
@@ -289,7 +353,7 @@ class Api:
         args.pop('script_args', None)  # will refeed them to the pipeline directly after initializing them
         args.pop('alwayson_scripts', None)
 
-        script_args = self.init_script_args(img2imgreq, selectable_scripts, selectable_script_idx, script_runner)
+        script_args = self.init_script_args(img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner)
 
         send_images = args.pop('send_images', True)
         args.pop('save_images', None)
@@ -412,6 +476,16 @@ class Api:
 
         return {}
 
+    def unloadapi(self):
+        unload_model_weights()
+
+        return {}
+
+    def reloadapi(self):
+        reload_model_weights()
+
+        return {}
+
     def skip(self):
         shared.state.skip()
 

modules/extensions.py

@@ -5,15 +5,15 @@ import traceback
 import time
 import git
 
-from modules import paths, shared
+from modules import shared
+from modules.paths_internal import extensions_dir, extensions_builtin_dir
 
 extensions = []
-extensions_dir = os.path.join(paths.data_path, "extensions")
-extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin")
 
 if not os.path.exists(extensions_dir):
     os.makedirs(extensions_dir)
 
+
 def active():
     return [x for x in extensions if x.enabled]
 
@@ -27,21 +27,29 @@ class Extension:
         self.can_update = False
         self.is_builtin = is_builtin
         self.version = ''
+        self.remote = None
+        self.have_info_from_repo = False
+
+    def read_info_from_repo(self):
+        if self.have_info_from_repo:
+            return
+
+        self.have_info_from_repo = True
 
         repo = None
         try:
-            if os.path.exists(os.path.join(path, ".git")):
-                repo = git.Repo(path)
+            if os.path.exists(os.path.join(self.path, ".git")):
+                repo = git.Repo(self.path)
         except Exception:
-            print(f"Error reading github repository info from {path}:", file=sys.stderr)
+            print(f"Error reading github repository info from {self.path}:", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
 
         if repo is None or repo.bare:
             self.remote = None
         else:
             try:
-                self.remote = next(repo.remote().urls, None)
                 self.status = 'unknown'
+                self.remote = next(repo.remote().urls, None)
                 head = repo.head.commit
                 ts = time.asctime(time.gmtime(repo.head.commit.committed_date))
                 self.version = f'{head.hexsha[:8]} ({ts})'
@@ -89,7 +97,7 @@ def list_extensions():
     if not os.path.isdir(extensions_dir):
         return
 
-    paths = []
+    extension_paths = []
     for dirname in [extensions_dir, extensions_builtin_dir]:
         if not os.path.isdir(dirname):
             return
@@ -99,9 +107,9 @@ def list_extensions():
             if not os.path.isdir(path):
                 continue
 
-            paths.append((extension_dirname, path, dirname == extensions_builtin_dir))
+            extension_paths.append((extension_dirname, path, dirname == extensions_builtin_dir))
 
-    for dirname, path, is_builtin in paths:
+    for dirname, path, is_builtin in extension_paths:
         extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin)
         extensions.append(extension)
 

modules/generation_parameters_copypaste.py

@@ -401,9 +401,14 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
 
     button.click(
         fn=paste_func,
-        _js=f"recalculate_prompts_{tabname}",
         inputs=[input_comp],
         outputs=[x[0] for x in paste_fields],
     )
+    button.click(
+        fn=None,
+        _js=f"recalculate_prompts_{tabname}",
+        inputs=[],
+        outputs=[],
+    )
 
 

modules/images.py

@@ -261,9 +261,12 @@ def resize_image(resize_mode, im, width, height, upscaler_name=None):
 
         if scale > 1.0:
             upscalers = [x for x in shared.sd_upscalers if x.name == upscaler_name]
-            assert len(upscalers) > 0, f"could not find upscaler named {upscaler_name}"
-
+            if len(upscalers) == 0:
+                upscaler = shared.sd_upscalers[0]
+                print(f"could not find upscaler named {upscaler_name or '<empty string>'}, using {upscaler.name} as a fallback")
+            else:
                 upscaler = upscalers[0]
+
             im = upscaler.scaler.upscale(im, scale, upscaler.data_path)
 
         if im.width != w or im.height != h:
@@ -645,6 +648,8 @@ Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}
 
 
 def image_data(data):
+    import gradio as gr
+
     try:
         image = Image.open(io.BytesIO(data))
         textinfo, _ = read_info_from_image(image)
@@ -660,7 +665,7 @@ def image_data(data):
     except Exception:
         pass
 
-    return '', None
+    return gr.update(), None
 
 
 def flatten(img, bgcolor):

modules/mac_specific.py

 import torch
+import platform
 from modules import paths
 from modules.sd_hijack_utils import CondFunc
 from packaging import version
@@ -32,6 +33,10 @@ if has_mps:
     # MPS fix for randn in torchsde
     CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'mps')
 
+    if platform.mac_ver()[0].startswith("13.2."):
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124)
+        CondFunc('torch.nn.functional.linear', lambda _, input, weight, bias: (torch.matmul(input, weight.t()) + bias) if bias is not None else torch.matmul(input, weight.t()), lambda _, input, weight, bias: input.numel() > 10485760)
+
     if version.parse(torch.__version__) < version.parse("1.13"):
         # PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working
 
@@ -49,4 +54,6 @@ if has_mps:
         CondFunc('torch.cumsum', cumsum_fix_func, None)
         CondFunc('torch.Tensor.cumsum', cumsum_fix_func, None)
         CondFunc('torch.narrow', lambda orig_func, *args, **kwargs: orig_func(*args, **kwargs).clone(), None)
-
+    if version.parse(torch.__version__) == version.parse("2.0"):
+        # MPS workaround for https://github.com/pytorch/pytorch/issues/96113
+        CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda *args, **kwargs: len(args) == 6)

modules/modelloader.py

@@ -4,7 +4,6 @@ import shutil
 import importlib
 from urllib.parse import urlparse
 
-from basicsr.utils.download_util import load_file_from_url
 from modules import shared
 from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone
 from modules.paths import script_path, models_path
@@ -59,6 +58,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
 
         if model_url is not None and len(output) == 0:
             if download_name is not None:
+                from basicsr.utils.download_util import load_file_from_url
                 dl = load_file_from_url(model_url, model_path, True, download_name)
                 output.append(dl)
             else:

modules/paths.py

-import argparse
 import os
 import sys
-import modules.safe
+from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir
 
-script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+import modules.safe
 
-# Parse the --data-dir flag first so we can use it as a base for our other argument default values
-parser = argparse.ArgumentParser(add_help=False)
-parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
-cmd_opts_pre = parser.parse_known_args()[0]
-data_path = cmd_opts_pre.data_dir
-models_path = os.path.join(data_path, "models")
 
 # data_path = cmd_opts_pre.data
 sys.path.insert(0, script_path)

modules/paths_internal.py

+"""this module defines internal paths used by program and is safe to import before dependencies are installed in launch.py"""
+
+import argparse
+import os
+
+script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+
+sd_configs_path = os.path.join(script_path, "configs")
+sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml")
+sd_model_file = os.path.join(script_path, 'model.ckpt')
+default_sd_model_file = sd_model_file
+
+# Parse the --data-dir flag first so we can use it as a base for our other argument default values
+parser_pre = argparse.ArgumentParser(add_help=False)
+parser_pre.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
+cmd_opts_pre = parser_pre.parse_known_args()[0]
+
+data_path = cmd_opts_pre.data_dir
+
+models_path = os.path.join(data_path, "models")
+extensions_dir = os.path.join(data_path, "extensions")
+extensions_builtin_dir = os.path.join(script_path, "extensions-builtin")

modules/processing.py

@@ -689,6 +689,22 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                     image.info["parameters"] = text
                 output_images.append(image)
 
+                if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay:
+                    image_mask = p.mask_for_overlay.convert('RGB')
+                    image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), p.mask_for_overlay.convert('L')).convert('RGBA')
+
+                    if opts.save_mask:
+                        images.save_image(image_mask, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask")
+
+                    if opts.save_mask_composite:
+                        images.save_image(image_mask_composite, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite")
+
+                    if opts.return_mask:
+                        output_images.append(image_mask)
+                    
+                    if opts.return_mask_composite:
+                        output_images.append(image_mask_composite)
+
             del x_samples_ddim
 
             devices.torch_gc()

modules/scripts.py

@@ -239,7 +239,15 @@ def load_scripts():
             elif issubclass(script_class, scripts_postprocessing.ScriptPostprocessing):
                 postprocessing_scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))
 
-    for scriptfile in sorted(scripts_list):
+    def orderby(basedir):
+        # 1st webui, 2nd extensions-builtin, 3rd extensions
+        priority = {os.path.join(paths.script_path, "extensions-builtin"):1, paths.script_path:0}
+        for key in priority:
+            if basedir.startswith(key):
+                return priority[key]
+        return 9999
+
+    for scriptfile in sorted(scripts_list, key=lambda x: [orderby(x.basedir), x]):
         try:
             if scriptfile.basedir != paths.script_path:
                 sys.path = [scriptfile.basedir] + sys.path
@@ -513,6 +521,18 @@ def reload_scripts():
     scripts_postproc = scripts_postprocessing.ScriptPostprocessingRunner()
 
 
+def add_classes_to_gradio_component(comp):
+    """
+    this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others
+    """
+
+    comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])]
+
+    if getattr(comp, 'multiselect', False):
+        comp.elem_classes.append('multiselect')
+
+
+
 def IOComponent_init(self, *args, **kwargs):
     if scripts_current is not None:
         scripts_current.before_component(self, **kwargs)
@@ -521,6 +541,8 @@ def IOComponent_init(self, *args, **kwargs):
 
     res = original_IOComponent_init(self, *args, **kwargs)
 
+    add_classes_to_gradio_component(self)
+
     script_callbacks.after_component_callback(self, **kwargs)
 
     if scripts_current is not None:
@@ -531,3 +553,15 @@ def IOComponent_init(self, *args, **kwargs):
 
 original_IOComponent_init = gr.components.IOComponent.__init__
 gr.components.IOComponent.__init__ = IOComponent_init
+
+
+def BlockContext_init(self, *args, **kwargs):
+    res = original_BlockContext_init(self, *args, **kwargs)
+
+    add_classes_to_gradio_component(self)
+
+    return res
+
+
+original_BlockContext_init = gr.blocks.BlockContext.__init__
+gr.blocks.BlockContext.__init__ = BlockContext_init

modules/scripts_postprocessing.py

@@ -109,7 +109,7 @@ class ScriptPostprocessingRunner:
         inputs = []
 
         for script in self.scripts_in_preferred_order():
-            with gr.Box() as group:
+            with gr.Row() as group:
                 self.create_script_ui(script, inputs)
 
             script.group = group

modules/sd_hijack_optimizations.py

@@ -337,7 +337,7 @@ def xformers_attention_forward(self, x, context=None, mask=None):
 
     dtype = q.dtype
     if shared.opts.upcast_attn:
-        q, k = q.float(), k.float()
+        q, k, v = q.float(), k.float(), v.float()
 
     out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=get_xformers_flash_attention_op(q, k, v))
 
@@ -372,7 +372,7 @@ def scaled_dot_product_attention_forward(self, x, context=None, mask=None):
 
     dtype = q.dtype
     if shared.opts.upcast_attn:
-        q, k = q.float(), k.float()
+        q, k, v = q.float(), k.float(), v.float()
 
     # the output of sdp = (batch, num_heads, seq_len, head_dim)
     hidden_states = torch.nn.functional.scaled_dot_product_attention(

modules/sd_hijack_unet.py

@@ -67,7 +67,7 @@ def hijack_ddpm_edit():
 unet_needs_upcast = lambda *args, **kwargs: devices.unet_needs_upcast
 CondFunc('ldm.models.diffusion.ddpm.LatentDiffusion.apply_model', apply_model, unet_needs_upcast)
 CondFunc('ldm.modules.diffusionmodules.openaimodel.timestep_embedding', lambda orig_func, timesteps, *args, **kwargs: orig_func(timesteps, *args, **kwargs).to(torch.float32 if timesteps.dtype == torch.int64 else devices.dtype_unet), unet_needs_upcast)
-if version.parse(torch.__version__) <= version.parse("1.13.1"):
+if version.parse(torch.__version__) <= version.parse("1.13.2") or torch.cuda.is_available():
     CondFunc('ldm.modules.diffusionmodules.util.GroupNorm32.forward', lambda orig_func, self, *args, **kwargs: orig_func(self.float(), *args, **kwargs), unet_needs_upcast)
     CondFunc('ldm.modules.attention.GEGLU.forward', lambda orig_func, self, x: orig_func(self.float(), x.float()).to(devices.dtype_unet), unet_needs_upcast)
     CondFunc('open_clip.transformer.ResidualAttentionBlock.__init__', lambda orig_func, *args, **kwargs: kwargs.update({'act_layer': GELUHijack}) and False or orig_func(*args, **kwargs), lambda _, *args, **kwargs: kwargs.get('act_layer') is None or kwargs['act_layer'] == torch.nn.GELU)

modules/sd_models.py

@@ -178,7 +178,7 @@ def select_checkpoint():
     return checkpoint_info
 
 
-chckpoint_dict_replacements = {
+checkpoint_dict_replacements = {
     'cond_stage_model.transformer.embeddings.': 'cond_stage_model.transformer.text_model.embeddings.',
     'cond_stage_model.transformer.encoder.': 'cond_stage_model.transformer.text_model.encoder.',
     'cond_stage_model.transformer.final_layer_norm.': 'cond_stage_model.transformer.text_model.final_layer_norm.',
@@ -186,7 +186,7 @@ chckpoint_dict_replacements = {
 
 
 def transform_checkpoint_dict_key(k):
-    for text, replacement in chckpoint_dict_replacements.items():
+    for text, replacement in checkpoint_dict_replacements.items():
         if k.startswith(text):
             k = replacement + k[len(text):]
 
@@ -494,7 +494,7 @@ def reload_model_weights(sd_model=None, info=None):
     if sd_model is None or checkpoint_config != sd_model.used_config:
         del sd_model
         checkpoints_loaded.clear()
-        load_model(checkpoint_info, already_loaded_state_dict=state_dict, time_taken_to_load_state_dict=timer.records["load weights from disk"])
+        load_model(checkpoint_info, already_loaded_state_dict=state_dict)
         return shared.sd_model
 
     try:
@@ -517,3 +517,23 @@ def reload_model_weights(sd_model=None, info=None):
     print(f"Weights loaded in {timer.summary()}.")
 
     return sd_model
+
+def unload_model_weights(sd_model=None, info=None):
+    from modules import lowvram, devices, sd_hijack
+    timer = Timer()
+
+    if shared.sd_model:
+
+        # shared.sd_model.cond_stage_model.to(devices.cpu)
+        # shared.sd_model.first_stage_model.to(devices.cpu)
+        shared.sd_model.to(devices.cpu)
+        sd_hijack.model_hijack.undo_hijack(shared.sd_model)
+        shared.sd_model = None
+        sd_model = None
+        gc.collect()
+        devices.torch_gc()
+        torch.cuda.empty_cache()
+
+    print(f"Unloaded weights {timer.summary()}.")
+
+    return sd_model
\ No newline at end of file

modules/textual_inversion/textual_inversion.py

@@ -152,7 +152,11 @@ class EmbeddingDatabase:
                 name = data.get('name', name)
             else:
                 data = extract_image_data_embed(embed_image)
+                if data:
                     name = data.get('name', name)
+                else:
+                    # if data is None, means this is not an embeding, just a preview image
+                    return
         elif ext in ['.BIN', '.PT']:
             data = torch.load(path, map_location="cpu")
         elif ext in ['.SAFETENSORS']:

modules/ui_common.py

@@ -129,8 +129,8 @@ Requested path was: {f}
 
         generation_info = None
         with gr.Column():
-            with gr.Row(elem_id=f"image_buttons_{tabname}"):
-                open_folder_button = gr.Button(folder_symbol, elem_id="hidden_element" if shared.cmd_opts.hide_ui_dir_config else f'open_folder_{tabname}')
+            with gr.Row(elem_id=f"image_buttons_{tabname}", elem_classes="image-buttons"):
+                open_folder_button = gr.Button(folder_symbol, visible=not shared.cmd_opts.hide_ui_dir_config)
 
                 if tabname != "extras":
                     save = gr.Button('Save', elem_id=f'save_{tabname}')
@@ -145,11 +145,10 @@ Requested path was: {f}
             )
 
             if tabname != "extras":
-                with gr.Row():
                 download_files = gr.File(None, file_count="multiple", interactive=False, show_label=False, visible=False, elem_id=f'download_files_{tabname}')
 
                 with gr.Group():
-                    html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                    html_info = gr.HTML(elem_id=f'html_info_{tabname}', elem_classes="infotext")
                     html_log = gr.HTML(elem_id=f'html_log_{tabname}')
 
                     generation_info = gr.Textbox(visible=False, elem_id=f'generation_info_{tabname}')
@@ -160,6 +159,7 @@ Requested path was: {f}
                             _js="function(x, y, z){ return [x, y, selected_gallery_index()] }",
                             inputs=[generation_info, html_info, html_info],
                             outputs=[html_info, html_info],
+                            show_progress=False,
                         )
 
                     save.click(
@@ -195,7 +195,7 @@ Requested path was: {f}
 
             else:
                 html_info_x = gr.HTML(elem_id=f'html_info_x_{tabname}')
-                html_info = gr.HTML(elem_id=f'html_info_{tabname}')
+                html_info = gr.HTML(elem_id=f'html_info_{tabname}', elem_classes="infotext")
                 html_log = gr.HTML(elem_id=f'html_log_{tabname}')
 
             paste_field_names = []

modules/ui_components.py

 import gradio as gr
 
 
-class ToolButton(gr.Button, gr.components.FormComponent):
-    """Small button with single emoji as text, fits inside gradio forms"""
+class FormComponent:
+    def get_expected_parent(self):
+        return gr.components.Form
 
-    def __init__(self, **kwargs):
-        super().__init__(variant="tool", **kwargs)
 
-    def get_block_name(self):
-        return "button"
+gr.Dropdown.get_expected_parent = FormComponent.get_expected_parent
 
 
-class ToolButtonTop(gr.Button, gr.components.FormComponent):
-    """Small button with single emoji as text, with extra margin at top, fits inside gradio forms"""
+class ToolButton(FormComponent, gr.Button):
+    """Small button with single emoji as text, fits inside gradio forms"""
 
-    def __init__(self, **kwargs):
-        super().__init__(variant="tool-top", **kwargs)
+    def __init__(self, *args, **kwargs):
+        classes = kwargs.pop("elem_classes", [])
+        super().__init__(*args, elem_classes=["tool", *classes], **kwargs)
 
     def get_block_name(self):
         return "button"
 
 
-class FormRow(gr.Row, gr.components.FormComponent):
+class FormRow(FormComponent, gr.Row):
     """Same as gr.Row but fits inside gradio forms"""
 
     def get_block_name(self):
         return "row"
 
 
-class FormGroup(gr.Group, gr.components.FormComponent):
+class FormColumn(FormComponent, gr.Column):
+    """Same as gr.Column but fits inside gradio forms"""
+
+    def get_block_name(self):
+        return "column"
+
+
+class FormGroup(FormComponent, gr.Group):
     """Same as gr.Row but fits inside gradio forms"""
 
     def get_block_name(self):
         return "group"
 
 
-class FormHTML(gr.HTML, gr.components.FormComponent):
+class FormHTML(FormComponent, gr.HTML):
     """Same as gr.HTML but fits inside gradio forms"""
 
     def get_block_name(self):
         return "html"
 
 
-class FormColorPicker(gr.ColorPicker, gr.components.FormComponent):
+class FormColorPicker(FormComponent, gr.ColorPicker):
     """Same as gr.ColorPicker but fits inside gradio forms"""
 
     def get_block_name(self):
         return "colorpicker"
 
 
-class DropdownMulti(gr.Dropdown):
+class DropdownMulti(FormComponent, gr.Dropdown):
     """Same as gr.Dropdown but always multiselect"""
     def __init__(self, **kwargs):
         super().__init__(multiselect=True, **kwargs)

modules/ui_extensions.py

 import json
 import os.path
-import shutil
 import sys
 import time
 import traceback
@@ -64,6 +63,9 @@ def check_updates(id_task, disable_list):
 
         try:
             ext.check_updates()
+        except FileNotFoundError as e:
+            if 'FETCH_HEAD' not in str(e):
+                raise
         except Exception:
             print(f"Error checking updates for {ext.name}:", file=sys.stderr)
             print(traceback.format_exc(), file=sys.stderr)
@@ -88,6 +90,8 @@ def extension_table():
     """
 
     for ext in extensions.extensions:
+        ext.read_info_from_repo()
+
         remote = f"""<a href="{html.escape(ext.remote or '')}" target="_blank">{html.escape("built-in" if ext.is_builtin else ext.remote or '')}</a>"""
 
         if ext.can_update:
@@ -141,22 +145,20 @@ def install_extension_from_url(dirname, url):
 
     try:
         shutil.rmtree(tmpdir, True)
-
-        repo = git.Repo.clone_from(url, tmpdir)
+        with git.Repo.clone_from(url, tmpdir) as repo:
             repo.remote().fetch()
-
+            for submodule in repo.submodules:
+                submodule.update()
         try:
             os.rename(tmpdir, target_dir)
         except OSError as err:
-            # TODO what does this do on windows? I think it'll be a different error code but I don't have a system to check it
-            # Shouldn't cause any new issues at least but we probably want to handle it there too.
             if err.errno == errno.EXDEV:
                 # Cross device link, typical in docker or when tmp/ and extensions/ are on different file systems
                 # Since we can't use a rename, do the slower but more versitile shutil.move()
                 shutil.move(tmpdir, target_dir)
             else:
                 # Something else, not enough free space, permissions, etc.  rethrow it so that it gets handled.
-                raise(err)
+                raise err
 
         import launch
         launch.run_extension_installer(target_dir)
@@ -167,12 +169,12 @@ def install_extension_from_url(dirname, url):
         shutil.rmtree(tmpdir, True)
 
 
-def install_extension_from_index(url, hide_tags, sort_column):
+def install_extension_from_index(url, hide_tags, sort_column, filter_text):
     ext_table, message = install_extension_from_url(None, url)
 
-    code, _ = refresh_available_extensions_from_data(hide_tags, sort_column)
+    code, _ = refresh_available_extensions_from_data(hide_tags, sort_column, filter_text)
 
-    return code, ext_table, message
+    return code, ext_table, message, ''
 
 
 def refresh_available_extensions(url, hide_tags, sort_column):
@@ -186,11 +188,17 @@ def refresh_available_extensions(url, hide_tags, sort_column):
 
     code, tags = refresh_available_extensions_from_data(hide_tags, sort_column)
 
-    return url, code, gr.CheckboxGroup.update(choices=tags), ''
+    return url, code, gr.CheckboxGroup.update(choices=tags), '', ''
+
+
+def refresh_available_extensions_for_tags(hide_tags, sort_column, filter_text):
+    code, _ = refresh_available_extensions_from_data(hide_tags, sort_column, filter_text)
+
+    return code, ''
 
 
-def refresh_available_extensions_for_tags(hide_tags, sort_column):
-    code, _ = refresh_available_extensions_from_data(hide_tags, sort_column)
+def search_extensions(filter_text, hide_tags, sort_column):
+    code, _ = refresh_available_extensions_from_data(hide_tags, sort_column, filter_text)
 
     return code, ''
 
@@ -205,7 +213,7 @@ sort_ordering = [
 ]
 
 
-def refresh_available_extensions_from_data(hide_tags, sort_column):
+def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=""):
     extlist = available_extensions["extensions"]
     installed_extension_urls = {normalize_git_url(extension.remote): extension.name for extension in extensions.extensions}
 
@@ -244,7 +252,12 @@ def refresh_available_extensions_from_data(hide_tags, sort_column):
             hidden += 1
             continue
 
-        install_code = f"""<input onclick="install_extension_from_index(this, '{html.escape(url)}')" type="button" value="{"Install" if not existing else "Installed"}" {"disabled=disabled" if existing else ""} class="gr-button gr-button-lg gr-button-secondary">"""
+        if filter_text and filter_text.strip():
+            if filter_text.lower() not in html.escape(name).lower() and filter_text.lower() not in html.escape(description).lower():
+                hidden += 1
+                continue
+
+        install_code = f"""<button onclick="install_extension_from_index(this, '{html.escape(url)}')" {"disabled=disabled" if existing else ""} class="lg secondary gradio-button custom-button">{"Install" if not existing else "Installed"}</button>"""
 
         tags_text = ", ".join([f"<span class='extension-tag' title='{tags.get(x, '')}'>{x}</span>" for x in extension_tags])
 
@@ -312,30 +325,39 @@ def create_ui():
                     hide_tags = gr.CheckboxGroup(value=["ads", "localization", "installed"], label="Hide extensions with tags", choices=["script", "ads", "localization", "installed"])
                     sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order", ], type="index")
 
+                with gr.Row(): 
+                    search_extensions_text = gr.Text(label="Search").style(container=False)
+                   
                 install_result = gr.HTML()
                 available_extensions_table = gr.HTML()
 
                 refresh_available_extensions_button.click(
                     fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update()]),
                     inputs=[available_extensions_index, hide_tags, sort_column],
-                    outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result],
+                    outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result, search_extensions_text],
                 )
 
                 install_extension_button.click(
                     fn=modules.ui.wrap_gradio_call(install_extension_from_index, extra_outputs=[gr.update(), gr.update()]),
-                    inputs=[extension_to_install, hide_tags, sort_column],
+                    inputs=[extension_to_install, hide_tags, sort_column, search_extensions_text],
                     outputs=[available_extensions_table, extensions_table, install_result],
                 )
 
+                search_extensions_text.change(
+                    fn=modules.ui.wrap_gradio_call(search_extensions, extra_outputs=[gr.update()]),
+                    inputs=[search_extensions_text, hide_tags, sort_column],
+                    outputs=[available_extensions_table, install_result],
+                )
+
                 hide_tags.change(
                     fn=modules.ui.wrap_gradio_call(refresh_available_extensions_for_tags, extra_outputs=[gr.update()]),
-                    inputs=[hide_tags, sort_column],
+                    inputs=[hide_tags, sort_column, search_extensions_text],
                     outputs=[available_extensions_table, install_result]
                 )
 
                 sort_column.change(
                     fn=modules.ui.wrap_gradio_call(refresh_available_extensions_for_tags, extra_outputs=[gr.update()]),
-                    inputs=[hide_tags, sort_column],
+                    inputs=[hide_tags, sort_column, search_extensions_text],
                     outputs=[available_extensions_table, install_result]
                 )
 

modules/ui_extra_networks.py

@@ -2,8 +2,10 @@ import glob
 import os.path
 import urllib.parse
 from pathlib import Path
+from PIL import PngImagePlugin
 
 from modules import shared
+from modules.images import read_info_from_image
 import gradio as gr
 import json
 import html
@@ -22,8 +24,7 @@ def register_page(page):
     allowed_dirs.update(set(sum([x.allowed_directories_for_previews() for x in extra_pages], [])))
 
 
-def add_pages_to_demo(app):
-    def fetch_file(filename: str = ""):
+def fetch_file(filename: str = ""):
     from starlette.responses import FileResponse
 
     if not any([Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs]):
@@ -36,7 +37,24 @@ def add_pages_to_demo(app):
     # would profit from returning 304
     return FileResponse(filename, headers={"Accept-Ranges": "bytes"})
 
+
+def get_metadata(page: str = "", item: str = ""):
+    from starlette.responses import JSONResponse
+
+    page = next(iter([x for x in extra_pages if x.name == page]), None)
+    if page is None:
+        return JSONResponse({})
+
+    metadata = page.metadata.get(item)
+    if metadata is None:
+        return JSONResponse({})
+
+    return JSONResponse({"metadata": metadata})
+
+
+def add_pages_to_demo(app):
     app.add_api_route("/sd_extra_networks/thumb", fetch_file, methods=["GET"])
+    app.add_api_route("/sd_extra_networks/metadata", get_metadata, methods=["GET"])
 
 
 class ExtraNetworksPage:
@@ -45,6 +63,7 @@ class ExtraNetworksPage:
         self.name = title.lower()
         self.card_page = shared.html("extra-networks-card.html")
         self.allow_negative_prompt = False
+        self.metadata = {}
 
     def refresh(self):
         pass
@@ -66,6 +85,8 @@ class ExtraNetworksPage:
         view = shared.opts.extra_networks_default_view
         items_html = ''
 
+        self.metadata = {}
+
         subdirs = {}
         for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]:
             for x in glob.glob(os.path.join(parentdir, '**/*'), recursive=True):
@@ -86,12 +107,16 @@ class ExtraNetworksPage:
             subdirs = {"": 1, **subdirs}
 
         subdirs_html = "".join([f"""
-<button class='gr-button gr-button-lg gr-button-secondary{" search-all" if subdir=="" else ""}' onclick='extraNetworksSearchButton("{tabname}_extra_tabs", event)'>
+<button class='lg secondary gradio-button custom-button{" search-all" if subdir=="" else ""}' onclick='extraNetworksSearchButton("{tabname}_extra_tabs", event)'>
 {html.escape(subdir if subdir!="" else "all")}
 </button>
 """ for subdir in subdirs])
 
         for item in self.list_items():
+            metadata = item.get("metadata")
+            if metadata:
+                self.metadata[item["name"]] = metadata
+
             items_html += self.create_html_for_item(item, tabname)
 
         if items_html == '':
@@ -124,14 +149,16 @@ class ExtraNetworksPage:
         if onclick is None:
             onclick = '"' + html.escape(f"""return cardClicked({json.dumps(tabname)}, {item["prompt"]}, {"true" if self.allow_negative_prompt else "false"})""") + '"'
 
+        height = f"height: {shared.opts.extra_networks_card_height}px;" if shared.opts.extra_networks_card_height else ''
+        width = f"width: {shared.opts.extra_networks_card_width}px;" if shared.opts.extra_networks_card_width else ''
+        background_image = f"background-image: url(\"{html.escape(preview)}\");" if preview else ''
         metadata_button = ""
         metadata = item.get("metadata")
         if metadata:
-            metadata_onclick = '"' + html.escape(f"""extraNetworksShowMetadata({json.dumps(metadata)}); return false;""") + '"'
-            metadata_button = f"<div class='metadata-button' title='Show metadata' onclick={metadata_onclick}></div>"
+            metadata_button = f"<div class='metadata-button' title='Show metadata' onclick='extraNetworksRequestMetadata(event, {json.dumps(self.name)}, {json.dumps(item['name'])})'></div>"
 
         args = {
-            "preview_html": "style='background-image: url(\"" + html.escape(preview) + "\")'" if preview else '',
+            "style": f"'{height}{width}{background_image}'",
             "prompt": item.get("prompt", None),
             "tabname": json.dumps(tabname),
             "local_preview": json.dumps(item["local_preview"]),
@@ -215,6 +242,7 @@ def create_ui(container, button, tabname):
     with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs:
         for page in ui.stored_extra_pages:
             with gr.Tab(page.title):
+
                 page_elem = gr.HTML(page.create_html(ui.tabname))
                 ui.pages.append(page_elem)
 
@@ -226,10 +254,10 @@ def create_ui(container, button, tabname):
 
     def toggle_visibility(is_visible):
         is_visible = not is_visible
-        return is_visible, gr.update(visible=is_visible)
+        return is_visible, gr.update(visible=is_visible), gr.update(variant=("secondary-down" if is_visible else "secondary"))
 
     state_visible = gr.State(value=False)
-    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container])
+    button.click(fn=toggle_visibility, inputs=[state_visible], outputs=[state_visible, container, button])
 
     def refresh():
         res = []
@@ -264,6 +292,7 @@ def setup_ui(ui, gallery):
 
         img_info = images[index if index >= 0 else 0]
         image = image_from_url_text(img_info)
+        geninfo, items = read_info_from_image(image)
 
         is_allowed = False
         for extra_page in ui.stored_extra_pages:
@@ -273,6 +302,11 @@ def setup_ui(ui, gallery):
 
         assert is_allowed, f'writing to {filename} is not allowed'
 
+        if geninfo:
+            pnginfo_data = PngImagePlugin.PngInfo()
+            pnginfo_data.add_text('parameters', geninfo)
+            image.save(filename, pnginfo=pnginfo_data)
+        else:
             image.save(filename)
 
         return [page.create_html(ui.tabname) for page in ui.stored_extra_pages]

requirements.txt

@@ -4,7 +4,7 @@ basicsr
 fonts
 font-roboto
 gfpgan
-gradio==3.16.2
+gradio==3.23
 numpy
 omegaconf
 opencv-contrib-python
@@ -29,3 +29,4 @@ GitPython
 torchsde
 safetensors
 psutil
+rich

requirements_versions.txt

@@ -3,13 +3,13 @@ transformers==4.25.1
 accelerate==0.12.0
 basicsr==1.4.2
 gfpgan==1.3.8
-gradio==3.16.2
+gradio==3.23
 numpy==1.23.3
 Pillow==9.4.0
 realesrgan==0.3.0
 torch
 omegaconf==2.2.3
-pytorch_lightning==1.7.6
+pytorch_lightning==1.9.4
 scikit-image==0.19.2
 fonts
 font-roboto
@@ -25,6 +25,6 @@ lark==1.1.2
 inflection==0.5.1
 GitPython==3.1.30
 torchsde==0.2.5
-safetensors==0.2.7
+safetensors==0.3.0
 httpcore<=0.15
 fastapi==0.94.0

script.js

 function gradioApp() {
     const elems = document.getElementsByTagName('gradio-app')
-    const gradioShadowRoot = elems.length == 0 ? null : elems[0].shadowRoot
-    return !!gradioShadowRoot ? gradioShadowRoot : document;
+    const elem = elems.length == 0 ? document : elems[0]
+
+    if (elem !== document) elem.getElementById = function(id){ return document.getElementById(id) }
+    return elem.shadowRoot ? elem.shadowRoot : elem
 }
 
 function get_uiCurrentTab() {

scripts/img2imgalt.py

@@ -6,23 +6,21 @@ from tqdm import trange
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import processing, shared, sd_samplers, prompt_parser, sd_samplers_common
-from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules import processing, shared, sd_samplers, sd_samplers_common
 
 import torch
 import k_diffusion as K
 
-from PIL import Image
-from torch import autocast
-from einops import rearrange, repeat
-
-
 def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
     x = p.init_latent
 
     s_in = x.new_ones([x.shape[0]])
+    if shared.sd_model.parameterization == "v":
+        dnw = K.external.CompVisVDenoiser(shared.sd_model)
+        skip = 1
+    else:
         dnw = K.external.CompVisDenoiser(shared.sd_model)
+        skip = 0
     sigmas = dnw.get_sigmas(steps).flip(0)
 
     shared.state.sampling_steps = steps
@@ -37,7 +35,7 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
         image_conditioning = torch.cat([p.image_conditioning] * 2)
         cond_in = {"c_concat": [image_conditioning], "c_crossattn": [cond_in]}
 
-        c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
+        c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)[skip:]]
         t = dnw.sigma_to_t(sigma_in)
 
         eps = shared.sd_model.apply_model(x_in * c_in, t, cond=cond_in)
@@ -69,7 +67,12 @@ def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
     x = p.init_latent
 
     s_in = x.new_ones([x.shape[0]])
+    if shared.sd_model.parameterization == "v":
+        dnw = K.external.CompVisVDenoiser(shared.sd_model)
+        skip = 1
+    else:
         dnw = K.external.CompVisDenoiser(shared.sd_model)
+        skip = 0
     sigmas = dnw.get_sigmas(steps).flip(0)
 
     shared.state.sampling_steps = steps
@@ -84,7 +87,7 @@ def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
         image_conditioning = torch.cat([p.image_conditioning] * 2)
         cond_in = {"c_concat": [image_conditioning], "c_crossattn": [cond_in]}
 
-        c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
+        c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)[skip:]]
 
         if i == 1:
             t = dnw.sigma_to_t(torch.cat([sigmas[i] * s_in] * 2))
@@ -213,4 +216,3 @@ class Script(scripts.Script):
         processed = processing.process_images(p)
 
         return processed
-

scripts/loopback.py

-import numpy as np
-from tqdm import trange
+import math
 
-import modules.scripts as scripts
 import gradio as gr
-
-from modules import processing, shared, sd_samplers, images
+import modules.scripts as scripts
+from modules import deepbooru, images, processing, shared
 from modules.processing import Processed
-from modules.sd_samplers import samplers
-from modules.shared import opts, cmd_opts, state
-from modules import deepbooru
+from modules.shared import opts, state
 
 
 class Script(scripts.Script):
@@ -20,39 +16,65 @@ class Script(scripts.Script):
 
     def ui(self, is_img2img):        
         loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=self.elem_id("loops"))
-        denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, elem_id=self.elem_id("denoising_strength_change_factor"))
+        final_denoising_strength = gr.Slider(minimum=0, maximum=1, step=0.01, label='Final denoising strength', value=0.5, elem_id=self.elem_id("final_denoising_strength"))
+        denoising_curve = gr.Dropdown(label="Denoising strength curve", choices=["Aggressive", "Linear", "Lazy"], value="Linear")
         append_interrogation = gr.Dropdown(label="Append interrogated prompt at each iteration", choices=["None", "CLIP", "DeepBooru"], value="None")
 
-        return [loops, denoising_strength_change_factor, append_interrogation]
+        return [loops, final_denoising_strength, denoising_curve, append_interrogation]
 
-    def run(self, p, loops, denoising_strength_change_factor, append_interrogation):
+    def run(self, p, loops, final_denoising_strength, denoising_curve, append_interrogation):
         processing.fix_seed(p)
         batch_count = p.n_iter
         p.extra_generation_params = {
-            "Denoising strength change factor": denoising_strength_change_factor,
+            "Final denoising strength": final_denoising_strength,
+            "Denoising curve": denoising_curve
         }
 
         p.batch_size = 1
         p.n_iter = 1
 
-        output_images, info = None, None
+        info = None
         initial_seed = None
         initial_info = None
+        initial_denoising_strength = p.denoising_strength
 
         grids = []
         all_images = []
         original_init_image = p.init_images
         original_prompt = p.prompt
+        original_inpainting_fill = p.inpainting_fill
         state.job_count = loops * batch_count
 
         initial_color_corrections = [processing.setup_color_correction(p.init_images[0])]
 
-        for n in range(batch_count):
+        def calculate_denoising_strength(loop):
+            strength = initial_denoising_strength
+
+            if loops == 1:
+                return strength
+
+            progress = loop / (loops - 1)
+            if denoising_curve == "Aggressive":
+                strength = math.sin((progress) * math.pi * 0.5)
+            elif denoising_curve == "Lazy":
+                strength = 1 - math.cos((progress) * math.pi * 0.5)
+            else:
+                strength = progress
+
+            change = (final_denoising_strength - initial_denoising_strength) * strength
+            return initial_denoising_strength + change
+
         history = []
 
+        for n in range(batch_count):
             # Reset to original init image at the start of each batch
             p.init_images = original_init_image
 
+            # Reset to original denoising strength
+            p.denoising_strength = initial_denoising_strength
+
+            last_image = None
+
             for i in range(loops):
                 p.n_iter = 1
                 p.batch_size = 1
@@ -72,25 +94,45 @@ class Script(scripts.Script):
 
                 processed = processing.process_images(p)
 
+                # Generation cancelled.
+                if state.interrupted:
+                    break
+
                 if initial_seed is None:
                     initial_seed = processed.seed
                     initial_info = processed.info
 
-                init_img = processed.images[0]
-
-                p.init_images = [init_img]
                 p.seed = processed.seed + 1
-                p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
-                history.append(processed.images[0])
+                p.denoising_strength = calculate_denoising_strength(i + 1)
+                
+                if state.skipped:
+                    break
+
+                last_image = processed.images[0]
+                p.init_images = [last_image]
+                p.inpainting_fill = 1 # Set "masked content" to "original" for next loop.
+
+                if batch_count == 1:
+                    history.append(last_image)
+                    all_images.append(last_image)
 
+            if batch_count > 1 and not state.skipped and not state.interrupted:
+                history.append(last_image)
+                all_images.append(last_image)
+
+            p.inpainting_fill = original_inpainting_fill
+                
+            if state.interrupted:
+                    break
+
+        if len(history) > 1:
             grid = images.image_grid(history, rows=1)
             if opts.grid_save:
                 images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
 
+            if opts.return_grid:
                 grids.append(grid)
-            all_images += history
                 
-        if opts.return_grid:
         all_images = grids + all_images
 
         processed = Processed(p, all_images, initial_seed, initial_info)

scripts/postprocessing_upscale.py

@@ -17,6 +17,8 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
     def ui(self):
         selected_tab = gr.State(value=0)
 
+        with gr.Column():
+            with FormRow():
                 with gr.Tabs(elem_id="extras_resize_mode"):
                     with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
                         upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")

scripts/xyz_grid.py

@@ -247,7 +247,7 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
 
         state.job = f"{index(ix, iy, iz) + 1} out of {list_size}"
 
-        processed: Processed = cell(x, y, z)
+        processed: Processed = cell(x, y, z, ix, iy, iz)
 
         if processed_result is None:
             # Use our first processed result object as a template container to hold our full results
@@ -515,6 +515,7 @@ class Script(scripts.Script):
         zs = process_axis(z_opt, z_values)
 
         # this could be moved to common code, but unlikely to be ever triggered anywhere else
+        Image.MAX_IMAGE_PIXELS = None # disable check in Pillow and rely on check below to allow large custom image sizes
         grid_mp = round(len(xs) * len(ys) * len(zs) * p.width * p.height / 1000000)
         assert grid_mp < opts.img_max_size_mp, f'Error: Resulting grid would be too large ({grid_mp} MPixels) (max configured size is {opts.img_max_size_mp} MPixels)'
 
@@ -558,8 +559,6 @@ class Script(scripts.Script):
         print(f"X/Y/Z plot will create {len(xs) * len(ys) * len(zs) * image_cell_count} images on {len(zs)} {len(xs)}x{len(ys)} grid{plural_s}{cell_console_text}. (Total steps to process: {total_steps})")
         shared.total_tqdm.updateTotal(total_steps)
 
-        grid_infotext = [None]
-
         state.xyz_plot_x = AxisInfo(x_opt, xs)
         state.xyz_plot_y = AxisInfo(y_opt, ys)
         state.xyz_plot_z = AxisInfo(z_opt, zs)
@@ -588,7 +587,9 @@ class Script(scripts.Script):
             else:
                 second_axes_processed = 'y'
 
-        def cell(x, y, z):
+        grid_infotext = [None] * (1 + len(zs))
+
+        def cell(x, y, z, ix, iy, iz):
             if shared.state.interrupted:
                 return Processed(p, [], p.seed, "")
 
@@ -600,7 +601,9 @@ class Script(scripts.Script):
 
             res = process_images(pc)
 
-            if grid_infotext[0] is None:
+            # Sets subgrid infotexts
+            subgrid_index = 1 + iz
+            if grid_infotext[subgrid_index] is None and ix == 0 and iy == 0:
                 pc.extra_generation_params = copy(pc.extra_generation_params)
                 pc.extra_generation_params['Script'] = self.title()
 
@@ -616,6 +619,12 @@ class Script(scripts.Script):
                     if y_opt.label in ["Seed", "Var. seed"] and not no_fixed_seeds:
                         pc.extra_generation_params["Fixed Y Values"] = ", ".join([str(y) for y in ys])
 
+                grid_infotext[subgrid_index] = processing.create_infotext(pc, pc.all_prompts, pc.all_seeds, pc.all_subseeds)
+
+            # Sets main grid infotext
+            if grid_infotext[0] is None and ix == 0 and iy == 0 and iz == 0:
+                pc.extra_generation_params = copy(pc.extra_generation_params)
+
                 if z_opt.label != 'Nothing':
                     pc.extra_generation_params["Z Type"] = z_opt.label
                     pc.extra_generation_params["Z Values"] = z_values
@@ -650,6 +659,9 @@ class Script(scripts.Script):
 
         z_count = len(zs)
 
+        # Set the grid infotexts to the real ones with extra_generation_params (1 main grid + z_count sub-grids)
+        processed.infotexts[:1+z_count] = grid_infotext[:1+z_count]
+
         if not include_lone_images:
             # Don't need sub-images anymore, drop from list:
             processed.images = processed.images[:z_count+1]

webui.py

@@ -4,6 +4,7 @@ import time
 import importlib
 import signal
 import re
+import warnings
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
@@ -17,6 +18,8 @@ from modules import paths, timer, import_hook, errors
 startup_timer = timer.Timer()
 
 import torch
+import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
+warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
 startup_timer.record("import torch")
 
 import gradio
@@ -240,7 +243,7 @@ def webui():
         shared.demo = modules.ui.create_ui()
         startup_timer.record("create ui")
 
-        if cmd_opts.gradio_queue:
+        if not cmd_opts.no_gradio_queue:
             shared.demo.queue(64)
 
         gradio_auth_creds = []