use cu126 for 10 series and older GPUs

CUDA Compute Capability change for RTX 5000 series

.eslintrc.js

@@ -88,6 +88,7 @@ module.exports = {
         // imageviewer.js
         modalPrevImage: "readonly",
         modalNextImage: "readonly",
+        updateModalImageIfVisible: "readonly",
         // localStorage.js
         localSet: "readonly",
         localGet: "readonly",

.github/workflows/on_pull_request.yaml

@@ -22,7 +22,7 @@ jobs:
       - name: Install Ruff
         run: pip install ruff==0.3.3
       - name: Run Ruff
-        run: ruff .
+        run: ruff check .
   lint-js:
     name: eslint
     runs-on: ubuntu-latest

CODEOWNERS

@@ -1,12 +1 @@
-*       @AUTOMATIC1111
-
-# if you were managing a localization and were removed from this file, this is because
-# the intended way to do localizations now is via extensions. See:
-# https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Developing-extensions
-# Make a repo with your localization and since you are still listed as a collaborator
-# you can add it to the wiki page yourself. This change is because some people complained
-# the git commit log is cluttered with things unrelated to almost everyone and
-# because I believe this is the best overall for the project to handle localizations almost
-# entirely without my oversight.
-
-
+*       @AUTOMATIC1111 @w-e-w @catboxanon

README.md

@@ -133,7 +133,7 @@ If your system is very new, you need to install python3.11 or python3.10:
 # Ubuntu 24.04
 sudo add-apt-repository ppa:deadsnakes/ppa
 sudo apt update
-sudo apt install python3.11
+sudo apt install python3.11 python3.11-venv
 
 # Manjaro/Arch
 sudo pacman -S yay
@@ -148,6 +148,7 @@ python_cmd="python3.11"
 2. Navigate to the directory you would like the webui to be installed and execute the following command:
 ```bash
 wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh
+chmod +x webui.sh
 ```
 Or just clone the repo wherever you want:
 ```bash

configs/sd_xl_v.yaml

@@ -0,0 +1,98 @@
+model:
+  target: sgm.models.diffusion.DiffusionEngine
+  params:
+    scale_factor: 0.13025
+    disable_first_stage_autocast: True
+
+    denoiser_config:
+      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
+      params:
+        num_idx: 1000
+
+        weighting_config:
+          target: sgm.modules.diffusionmodules.denoiser_weighting.VWeighting
+        scaling_config:
+          target: sgm.modules.diffusionmodules.denoiser_scaling.VScaling
+        discretization_config:
+          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+
+    network_config:
+      target: sgm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        adm_in_channels: 2816
+        num_classes: sequential
+        use_checkpoint: False
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [4, 2]
+        num_res_blocks: 2
+        channel_mult: [1, 2, 4]
+        num_head_channels: 64
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: [1, 2, 10]  # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
+        context_dim: 2048
+        spatial_transformer_attn_type: softmax-xformers
+        legacy: False
+
+    conditioner_config:
+      target: sgm.modules.GeneralConditioner
+      params:
+        emb_models:
+          # crossattn cond
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
+            params:
+              layer: hidden
+              layer_idx: 11
+          # crossattn and vector cond
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
+            params:
+              arch: ViT-bigG-14
+              version: laion2b_s39b_b160k
+              freeze: True
+              layer: penultimate
+              always_return_pooled: True
+              legacy: False
+          # vector cond
+          - is_trainable: False
+            input_key: original_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256  # multiplied by two
+          # vector cond
+          - is_trainable: False
+            input_key: crop_coords_top_left
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256  # multiplied by two
+          # vector cond
+          - is_trainable: False
+            input_key: target_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256  # multiplied by two
+
+    first_stage_config:
+      target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          attn_type: vanilla-xformers
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult: [1, 2, 4, 4]
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity

extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js

@@ -16,20 +16,6 @@ onUiLoaded(async() => {
     // Helper functions
     // Get active tab
 
-    function debounce(func, wait) {
-        let timeout;
-
-        return function executedFunction(...args) {
-            const later = () => {
-                clearTimeout(timeout);
-                func(...args);
-            };
-
-            clearTimeout(timeout);
-            timeout = setTimeout(later, wait);
-        };
-    }
-
     /**
      * Waits for an element to be present in the DOM.
      */
@@ -72,30 +58,6 @@ onUiLoaded(async() => {
         }
     }
 
-    // // Hack to make the cursor always be the same size
-    function fixCursorSize() {
-        window.scrollBy(0, 1);
-    }
-
-    function copySpecificStyles(sourceElement, targetElement, zoomLevel = 1) {
-        const stylesToCopy = ['top', 'left', 'width', 'height'];
-
-        stylesToCopy.forEach(styleName => {
-            if (sourceElement.style[styleName]) {
-                // Convert style value to number and multiply by zoomLevel.
-                let adjustedStyleValue = parseFloat(sourceElement.style[styleName]) / zoomLevel;
-
-                // Set the adjusted style value back to target element's style.
-                // Important: this will work fine for top and left styles as they are usually in px.
-                // But be careful with other units like em or % that might need different handling.
-                targetElement.style[styleName] = `${adjustedStyleValue}px`;
-            }
-        });
-
-        targetElement.style["opacity"] = sourceElement.style["opacity"];
-    }
-
-
     // Detect whether the element has a horizontal scroll bar
     function hasHorizontalScrollbar(element) {
         return element.scrollWidth > element.clientWidth;
@@ -205,6 +167,48 @@ onUiLoaded(async() => {
         return config;
     }
 
+    /**
+     * The restoreImgRedMask function displays a red mask around an image to indicate the aspect ratio.
+     * If the image display property is set to 'none', the mask breaks. To fix this, the function
+     * temporarily sets the display property to 'block' and then hides the mask again after 300 milliseconds
+     * to avoid breaking the canvas. Additionally, the function adjusts the mask to work correctly on
+     * very long images.
+     */
+    function restoreImgRedMask(elements) {
+        const mainTabId = getTabId(elements);
+
+        if (!mainTabId) return;
+
+        const mainTab = gradioApp().querySelector(mainTabId);
+        const img = mainTab.querySelector("img");
+        const imageARPreview = gradioApp().querySelector("#imageARPreview");
+
+        if (!img || !imageARPreview) return;
+
+        imageARPreview.style.transform = "";
+        if (parseFloat(mainTab.style.width) > 865) {
+            const transformString = mainTab.style.transform;
+            const scaleMatch = transformString.match(
+                /scale\(([-+]?[0-9]*\.?[0-9]+)\)/
+            );
+            let zoom = 1; // default zoom
+
+            if (scaleMatch && scaleMatch[1]) {
+                zoom = Number(scaleMatch[1]);
+            }
+
+            imageARPreview.style.transformOrigin = "0 0";
+            imageARPreview.style.transform = `scale(${zoom})`;
+        }
+
+        if (img.style.display !== "none") return;
+
+        img.style.display = "block";
+
+        setTimeout(() => {
+            img.style.display = "none";
+        }, 400);
+    }
 
     const hotkeysConfigOpts = await waitForOpts();
 
@@ -220,6 +224,7 @@ onUiLoaded(async() => {
         canvas_hotkey_grow_brush: "KeyW",
         canvas_disabled_functions: [],
         canvas_show_tooltip: true,
+        canvas_auto_expand: true,
         canvas_blur_prompt: false,
     };
 
@@ -259,6 +264,18 @@ onUiLoaded(async() => {
     );
     const elemData = {};
 
+    // Apply functionality to the range inputs. Restore redmask and correct for long images.
+    const rangeInputs = elements.rangeGroup ?
+        Array.from(elements.rangeGroup.querySelectorAll("input")) :
+        [
+            gradioApp().querySelector("#img2img_width input[type='range']"),
+            gradioApp().querySelector("#img2img_height input[type='range']")
+        ];
+
+    for (const input of rangeInputs) {
+        input?.addEventListener("input", () => restoreImgRedMask(elements));
+    }
+
     function applyZoomAndPan(elemId, isExtension = true) {
         const targetElement = gradioApp().querySelector(elemId);
 
@@ -272,118 +289,14 @@ onUiLoaded(async() => {
         elemData[elemId] = {
             zoom: 1,
             panX: 0,
-            panY: 0,
+            panY: 0
         };
-
         let fullScreenMode = false;
 
-
-        // Cursor manipulation script for a painting application.
-        // The purpose of this code is to create custom cursors (for painting and erasing)
-        // that can change depending on which button the user presses.
-        // When the mouse moves over the canvas, the appropriate custom cursor also moves,
-        // replicating its appearance dynamically based on various CSS properties.
-
-        // This is done because the original cursor is tied to the size of the kanvas, it can not be changed, so I came up with a hack that creates an exact copy that works properly
-
-        const eraseButton = targetElement.querySelector(`button[aria-label='Erase button']`);
-        const paintButton = targetElement.querySelector(`button[aria-label='Draw button']`);
-
-        const canvasCursors = targetElement.querySelectorAll("span.svelte-btgkrd");
-        const paintCursorCopy = canvasCursors[0].cloneNode(true);
-        const eraserCursorCopy = canvasCursors[1].cloneNode(true);
-
-        canvasCursors.forEach(cursor => cursor.style.display = "none");
-
-        canvasCursors[0].parentNode.insertBefore(paintCursorCopy, canvasCursors[0].nextSibling);
-        canvasCursors[1].parentNode.insertBefore(eraserCursorCopy, canvasCursors[1].nextSibling);
-
-
-        // targetElement.appendChild(paintCursorCopy);
-        // paintCursorCopy.style.display = "none";
-
-        // targetElement.appendChild(eraserCursorCopy);
-        // eraserCursorCopy.style.display = "none";
-
-        let activeCursor;
-
-        paintButton.addEventListener('click', () => {
-            activateTool(paintButton, eraseButton, paintCursorCopy);
-        });
-
-        eraseButton.addEventListener('click', () => {
-            activateTool(eraseButton, paintButton, eraserCursorCopy);
-        });
-
-        function activateTool(activeButton, inactiveButton, activeCursorCopy) {
-            activeButton.classList.add("active");
-            inactiveButton.classList.remove("active");
-
-            // canvasCursors.forEach(cursor => cursor.style.display = "none");
-
-            if (activeCursor) {
-                activeCursor.style.display = "none";
-            }
-
-            activeCursor = activeCursorCopy;
-            // activeCursor.style.display = "none";
-            activeCursor.style.position = "absolute";
-        }
-
-        const canvasAreaEventsHandler = e => {
-
-            canvasCursors.forEach(cursor => cursor.style.display = "none");
-
-            if (!activeCursor) return;
-
-            const cursorNum = eraseButton.classList.contains("active") ? 1 : 0;
-
-            if (elemData[elemId].zoomLevel != 1) {
-                copySpecificStyles(canvasCursors[cursorNum], activeCursor, elemData[elemId].zoomLevel);
-            } else {
-                // Update the styles of the currently active cursor
-                copySpecificStyles(canvasCursors[cursorNum], activeCursor);
-            }
-
-            let offsetXAdjusted = e.offsetX;
-            let offsetYAdjusted = e.offsetY;
-
-            // Position the cursor based on the current mouse coordinates within target element.
-            activeCursor.style.transform =
-           `translate(${offsetXAdjusted}px, ${offsetYAdjusted}px)`;
-        };
-
-        const canvasAreaLeaveHandler = () => {
-            if (activeCursor) {
-                // activeCursor.style.opacity = 0
-                activeCursor.style.display = "none";
-            }
-        };
-
-        const canvasAreaEnterHandler = () => {
-            if (activeCursor) {
-                // activeCursor.style.opacity = 1
-                activeCursor.style.display = "block";
-            }
-        };
-
-        const canvasArea = targetElement.querySelector("canvas");
-
-        // Attach event listeners to the target element and canvas area
-        targetElement.addEventListener("mousemove", canvasAreaEventsHandler);
-        canvasArea.addEventListener("mouseout", canvasAreaLeaveHandler);
-        canvasArea.addEventListener("mouseenter", canvasAreaEnterHandler);
-
-        // Additional listener for handling zoom or other transformations which might affect visual representation
-        targetElement.addEventListener("wheel", canvasAreaEventsHandler);
-
-        // Remove border, cause bags
-        const canvasBorder = targetElement.querySelector(".border");
-        canvasBorder.style.display = "none";
-
         // Create tooltip
         function createTooltip() {
-            const toolTipElement = targetElement.querySelector(".image-container");
+            const toolTipElement =
+                targetElement.querySelector(".image-container");
             const tooltip = document.createElement("div");
             tooltip.className = "canvas-tooltip";
 
@@ -446,15 +359,25 @@ onUiLoaded(async() => {
 
             // Add a hint element to the target element
             toolTipElement.appendChild(tooltip);
-
-            return tooltip;
         }
 
         //Show tool tip if setting enable
-        const canvasTooltip = createTooltip();
+        if (hotkeysConfig.canvas_show_tooltip) {
+            createTooltip();
+        }
 
-        if (!hotkeysConfig.canvas_show_tooltip) {
-            canvasTooltip.style.display = "none";
+        // In the course of research, it was found that the tag img is very harmful when zooming and creates white canvases. This hack allows you to almost never think about this problem, it has no effect on webui.
+        function fixCanvas() {
+            const activeTab = getActiveTab(elements)?.textContent.trim();
+
+            if (activeTab && activeTab !== "img2img") {
+                const img = targetElement.querySelector(`${elemId} img`);
+
+                if (img && img.style.display !== "none") {
+                    img.style.display = "none";
+                    img.style.visibility = "hidden";
+                }
+            }
         }
 
         // Reset the zoom level and pan position of the target element to their initial values
@@ -462,7 +385,7 @@ onUiLoaded(async() => {
             elemData[elemId] = {
                 zoomLevel: 1,
                 panX: 0,
-                panY: 0,
+                panY: 0
             };
 
             if (isExtension) {
@@ -471,22 +394,45 @@ onUiLoaded(async() => {
 
             targetElement.isZoomed = false;
 
+            fixCanvas();
             targetElement.style.transform = `scale(${elemData[elemId].zoomLevel}) translate(${elemData[elemId].panX}px, ${elemData[elemId].panY}px)`;
 
             const canvas = gradioApp().querySelector(
-                `${elemId} canvas`
+                `${elemId} canvas[key="interface"]`
             );
 
             toggleOverlap("off");
             fullScreenMode = false;
 
-            const closeBtn = targetElement.querySelector("button[aria-label='Clear canvas']");
+            const closeBtn = targetElement.querySelector("button[aria-label='Remove Image']");
             if (closeBtn) {
                 closeBtn.addEventListener("click", resetZoom);
             }
 
+            if (canvas && isExtension) {
+                const parentElement = targetElement.closest('[id^="component-"]');
+                if (
+                    canvas &&
+                    parseFloat(canvas.style.width) > parentElement.offsetWidth &&
+                    parseFloat(targetElement.style.width) > parentElement.offsetWidth
+                ) {
+                    fitToElement();
+                    return;
+                }
+
+            }
+
+            if (
+                canvas &&
+                !isExtension &&
+                parseFloat(canvas.style.width) > 865 &&
+                parseFloat(targetElement.style.width) > 865
+            ) {
+                fitToElement();
+                return;
+            }
+
             targetElement.style.width = "";
-            fixCursorSize();
         }
 
         // Toggle the zIndex of the target element between two values, allowing it to overlap or be overlapped by other elements
@@ -513,10 +459,10 @@ onUiLoaded(async() => {
         ) {
             const input =
                 gradioApp().querySelector(
-                    `${elemId} input[type='range']`
+                    `${elemId} input[aria-label='Brush radius']`
                 ) ||
                 gradioApp().querySelector(
-                    `${elemId} button[aria-label="Size button"]`
+                    `${elemId} button[aria-label="Use brush"]`
                 );
 
             if (input) {
@@ -536,15 +482,10 @@ onUiLoaded(async() => {
 
         // Reset zoom when uploading a new image
         const fileInput = gradioApp().querySelector(
-            `${elemId} .upload-container input[type="file"][accept="image/*"]`
+            `${elemId} input[type="file"][accept="image/*"].svelte-116rqfv`
         );
-
         fileInput.addEventListener("click", resetZoom);
 
-        // Create clickble area
-        const inputCanvas = targetElement.querySelector("canvas");
-
-
         // Update the zoom level and pan position of the target element based on the values of the zoomLevel, panX and panY variables
         function updateZoom(newZoomLevel, mouseX, mouseY) {
             newZoomLevel = Math.max(0.1, Math.min(newZoomLevel, 15));
@@ -562,9 +503,6 @@ onUiLoaded(async() => {
                 targetElement.style.overflow = "visible";
             }
 
-            // Hack to make the cursor always be the same size
-            fixCursorSize();
-
             return newZoomLevel;
         }
 
@@ -600,6 +538,67 @@ onUiLoaded(async() => {
             }
         }
 
+        /**
+         * This function fits the target element to the screen by calculating
+         * the required scale and offsets. It also updates the global variables
+         * zoomLevel, panX, and panY to reflect the new state.
+         */
+
+        function fitToElement() {
+            //Reset Zoom
+            targetElement.style.transform = `translate(${0}px, ${0}px) scale(${1})`;
+
+            let parentElement;
+
+            if (isExtension) {
+                parentElement = targetElement.closest('[id^="component-"]');
+            } else {
+                parentElement = targetElement.parentElement;
+            }
+
+
+            // Get element and screen dimensions
+            const elementWidth = targetElement.offsetWidth;
+            const elementHeight = targetElement.offsetHeight;
+
+            const screenWidth = parentElement.clientWidth;
+            const screenHeight = parentElement.clientHeight;
+
+            // Get element's coordinates relative to the parent element
+            const elementRect = targetElement.getBoundingClientRect();
+            const parentRect = parentElement.getBoundingClientRect();
+            const elementX = elementRect.x - parentRect.x;
+
+            // Calculate scale and offsets
+            const scaleX = screenWidth / elementWidth;
+            const scaleY = screenHeight / elementHeight;
+            const scale = Math.min(scaleX, scaleY);
+
+            const transformOrigin =
+                window.getComputedStyle(targetElement).transformOrigin;
+            const [originX, originY] = transformOrigin.split(" ");
+            const originXValue = parseFloat(originX);
+            const originYValue = parseFloat(originY);
+
+            const offsetX =
+                (screenWidth - elementWidth * scale) / 2 -
+                originXValue * (1 - scale);
+            const offsetY =
+                (screenHeight - elementHeight * scale) / 2.5 -
+                originYValue * (1 - scale);
+
+            // Apply scale and offsets to the element
+            targetElement.style.transform = `translate(${offsetX}px, ${offsetY}px) scale(${scale})`;
+
+            // Update global variables
+            elemData[elemId].zoomLevel = scale;
+            elemData[elemId].panX = offsetX;
+            elemData[elemId].panY = offsetY;
+
+            fullScreenMode = false;
+            toggleOverlap("off");
+        }
+
         /**
          * This function fits the target element to the screen by calculating
          * the required scale and offsets. It also updates the global variables
@@ -609,11 +608,9 @@ onUiLoaded(async() => {
         // Fullscreen mode
         function fitToScreen() {
             const canvas = gradioApp().querySelector(
-                `${elemId} canvas`
+                `${elemId} canvas[key="interface"]`
             );
 
-            // print(canvas)
-
             if (!canvas) return;
 
             if (canvas.offsetWidth > 862 || isExtension) {
@@ -624,7 +621,6 @@ onUiLoaded(async() => {
                 targetElement.style.overflow = "visible";
             }
 
-            fixCursorSize();
             if (fullScreenMode) {
                 resetZoom();
                 fullScreenMode = false;
@@ -732,7 +728,7 @@ onUiLoaded(async() => {
 
         targetElement.isExpanded = false;
         function autoExpand() {
-            const canvas = document.querySelector(`${elemId} canvas`);
+            const canvas = document.querySelector(`${elemId} canvas[key="interface"]`);
             if (canvas) {
                 if (hasHorizontalScrollbar(targetElement) && targetElement.isExpanded === false) {
                     targetElement.style.visibility = "hidden";
@@ -748,6 +744,26 @@ onUiLoaded(async() => {
 
         targetElement.addEventListener("mousemove", getMousePosition);
 
+        //observers
+        // Creating an observer with a callback function to handle DOM changes
+        const observer = new MutationObserver((mutationsList, observer) => {
+            for (let mutation of mutationsList) {
+                // If the style attribute of the canvas has changed, by observation it happens only when the picture changes
+                if (mutation.type === 'attributes' && mutation.attributeName === 'style' &&
+                    mutation.target.tagName.toLowerCase() === 'canvas') {
+                    targetElement.isExpanded = false;
+                    setTimeout(resetZoom, 10);
+                }
+            }
+        });
+
+        // Apply auto expand if enabled
+        if (hotkeysConfig.canvas_auto_expand) {
+            targetElement.addEventListener("mousemove", autoExpand);
+            // Set up an observer to track attribute changes
+            observer.observe(targetElement, {attributes: true, childList: true, subtree: true});
+        }
+
         // Handle events only inside the targetElement
         let isKeyDownHandlerAttached = false;
 
@@ -774,7 +790,15 @@ onUiLoaded(async() => {
         targetElement.addEventListener("mouseleave", handleMouseLeave);
 
         // Reset zoom when click on another tab
-        elements.img2imgTabs.addEventListener("click", resetZoom);
+        if (elements.img2imgTabs) {
+            elements.img2imgTabs.addEventListener("click", resetZoom);
+            elements.img2imgTabs.addEventListener("click", () => {
+                // targetElement.style.width = "";
+                if (parseInt(targetElement.style.width) > 865) {
+                    setTimeout(fitToElement, 0);
+                }
+            });
+        }
 
         targetElement.addEventListener("wheel", e => {
             // change zoom level
@@ -792,7 +816,7 @@ onUiLoaded(async() => {
                 // Increase or decrease brush size based on scroll direction
                 adjustBrushSize(elemId, e.deltaY);
             }
-        });
+        }, {passive: false});
 
         // Handle the move event for pan functionality. Updates the panX and panY variables and applies the new transform to the target element.
         function handleMoveKeyDown(e) {
@@ -854,7 +878,6 @@ onUiLoaded(async() => {
             elemData[elemId].panY += movementY * panSpeed;
 
             // Delayed redraw of an element
-            const canvas = targetElement.querySelector("canvas");
             requestAnimationFrame(() => {
                 targetElement.style.transform = `translate(${elemData[elemId].panX}px, ${elemData[elemId].panY}px) scale(${elemData[elemId].zoomLevel})`;
                 toggleOverlap("on");
@@ -913,6 +936,7 @@ onUiLoaded(async() => {
 
         gradioApp().addEventListener("mousemove", handleMoveByKey);
 
+
     }
 
     applyZoomAndPan(elementIDs.sketch, false);
@@ -942,30 +966,9 @@ onUiLoaded(async() => {
     };
 
     window.applyZoomAndPan = applyZoomAndPan; // Only 1 elements, argument elementID, for example applyZoomAndPan("#txt2img_controlnet_ControlNet_input_image")
+
     window.applyZoomAndPanIntegration = applyZoomAndPanIntegration; // for any extension
 
-
-    // Return zoom functionality when send img via buttons
-    const img2imgArea = document.querySelector("#img2img_settings");
-    const checkForTooltip = (e) => {
-        const tabId = getTabId(elements); // Make sure that the item is passed correctly to determine the tabId
-
-        if (tabId === "#img2img_sketch" || tabId === "#inpaint_sketch" || tabId === "#img2maskimg") {
-            const zoomTooltip = document.querySelector(`${tabId} .canvas-tooltip`);
-
-            if (!zoomTooltip) {
-                applyZoomAndPan(tabId, false);
-                // resetZoom()
-            }
-        }
-    };
-
-    // Wrapping your function through debounce to reduce the number of calls
-    const debouncedCheckForTooltip = debounce(checkForTooltip, 20);
-
-    // Assigning an event handler
-    img2imgArea.addEventListener("mousemove", debouncedCheckForTooltip);
-
     /*
         The function `applyZoomAndPanIntegration` takes two arguments:
 

extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py

@@ -11,6 +11,7 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas
     "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas position"),
     "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, needed for testing"),
     "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"),
+    "canvas_auto_expand": shared.OptionInfo(True, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"),
     "canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"),
     "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size","Hotkey enlarge brush","Hotkey shrink brush","Moving canvas","Fullscreen","Reset Zoom","Overlap"]}),
 }))

extensions-builtin/hypertile/hypertile.py

@@ -1,7 +1,7 @@
 """
 Hypertile module for splitting attention layers in SD-1.5 U-Net and SD-1.5 VAE
 Warn: The patch works well only if the input image has a width and height that are multiples of 128
-Original author: @tfernd Github: https://github.com/tfernd/HyperTile
+Original author: @tfernd GitHub: https://github.com/tfernd/HyperTile
 """
 
 from __future__ import annotations

extensions-builtin/postprocessing-for-training/scripts/postprocessing_autosized_crop.py

@@ -34,14 +34,14 @@ class ScriptPostprocessingAutosizedCrop(scripts_postprocessing.ScriptPostprocess
         with ui_components.InputAccordion(False, label="Auto-sized crop") as enable:
             gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
             with gr.Row():
-                mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="postprocess_multicrop_mindim")
-                maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="postprocess_multicrop_maxdim")
+                mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id=self.elem_id_suffix("postprocess_multicrop_mindim"))
+                maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id=self.elem_id_suffix("postprocess_multicrop_maxdim"))
             with gr.Row():
-                minarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area lower bound", value=64 * 64, elem_id="postprocess_multicrop_minarea")
-                maxarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area upper bound", value=640 * 640, elem_id="postprocess_multicrop_maxarea")
+                minarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area lower bound", value=64 * 64, elem_id=self.elem_id_suffix("postprocess_multicrop_minarea"))
+                maxarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area upper bound", value=640 * 640, elem_id=self.elem_id_suffix("postprocess_multicrop_maxarea"))
             with gr.Row():
-                objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="postprocess_multicrop_objective")
-                threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="postprocess_multicrop_threshold")
+                objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id=self.elem_id_suffix("postprocess_multicrop_objective"))
+                threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id=self.elem_id_suffix("postprocess_multicrop_threshold"))
 
         return {
             "enable": enable,

extensions-builtin/postprocessing-for-training/scripts/postprocessing_focal_crop.py

@@ -11,10 +11,10 @@ class ScriptPostprocessingFocalCrop(scripts_postprocessing.ScriptPostprocessing)
 
     def ui(self):
         with ui_components.InputAccordion(False, label="Auto focal point crop") as enable:
-            face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_face_weight")
-            entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_entropy_weight")
-            edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_edges_weight")
-            debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
+            face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id=self.elem_id_suffix("postprocess_focal_crop_face_weight"))
+            entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id=self.elem_id_suffix("postprocess_focal_crop_entropy_weight"))
+            edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id=self.elem_id_suffix("postprocess_focal_crop_edges_weight"))
+            debug = gr.Checkbox(label='Create debug image', elem_id=self.elem_id_suffix("train_process_focal_crop_debug"))
 
         return {
             "enable": enable,

extensions-builtin/postprocessing-for-training/scripts/postprocessing_split_oversized.py

@@ -35,8 +35,8 @@ class ScriptPostprocessingSplitOversized(scripts_postprocessing.ScriptPostproces
     def ui(self):
         with ui_components.InputAccordion(False, label="Split oversized images") as enable:
             with gr.Row():
-                split_threshold = gr.Slider(label='Threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_split_threshold")
-                overlap_ratio = gr.Slider(label='Overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="postprocess_overlap_ratio")
+                split_threshold = gr.Slider(label='Threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id=self.elem_id_suffix("postprocess_split_threshold"))
+                overlap_ratio = gr.Slider(label='Overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id=self.elem_id_suffix("postprocess_overlap_ratio"))
 
         return {
             "enable": enable,

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

@@ -1,36 +1,69 @@
-// Stable Diffusion WebUI - Bracket checker
-// By Hingashi no Florin/Bwin4L & @akx
+// Stable Diffusion WebUI - Bracket Checker
+// By @Bwin4L, @akx, @w-e-w, @Haoming02
 // Counts open and closed brackets (round, square, curly) in the prompt and negative prompt text boxes in the txt2img and img2img tabs.
-// If there's a mismatch, the keyword counter turns red and if you hover on it, a tooltip tells you what's wrong.
+// If there's a mismatch, the keyword counter turns red, and if you hover on it, a tooltip tells you what's wrong.
 
-function checkBrackets(textArea, counterElt) {
-    var counts = {};
-    (textArea.value.match(/[(){}[\]]/g) || []).forEach(bracket => {
-        counts[bracket] = (counts[bracket] || 0) + 1;
-    });
-    var errors = [];
+function checkBrackets(textArea, counterElem) {
+    const pairs = [
+        ['(', ')', 'round brackets'],
+        ['[', ']', 'square brackets'],
+        ['{', '}', 'curly brackets']
+    ];
 
-    function checkPair(open, close, kind) {
-        if (counts[open] !== counts[close]) {
-            errors.push(
-                `${open}...${close} - Detected ${counts[open] || 0} opening and ${counts[close] || 0} closing ${kind}.`
-            );
+    const counts = {};
+    const errors = new Set();
+    let i = 0;
+
+    while (i < textArea.value.length) {
+        let char = textArea.value[i];
+        let escaped = false;
+        while (char === '\\' && i + 1 < textArea.value.length) {
+            escaped = !escaped;
+            i++;
+            char = textArea.value[i];
+        }
+
+        if (escaped) {
+            i++;
+            continue;
+        }
+
+        for (const [open, close, label] of pairs) {
+            if (char === open) {
+                counts[label] = (counts[label] || 0) + 1;
+            } else if (char === close) {
+                counts[label] = (counts[label] || 0) - 1;
+                if (counts[label] < 0) {
+                    errors.add(`Incorrect order of ${label}.`);
+                }
+            }
+        }
+
+        i++;
+    }
+
+    for (const [open, close, label] of pairs) {
+        if (counts[label] == undefined) {
+            continue;
+        }
+
+        if (counts[label] > 0) {
+            errors.add(`${open} ... ${close} - Detected ${counts[label]} more opening than closing ${label}.`);
+        } else if (counts[label] < 0) {
+            errors.add(`${open} ... ${close} - Detected ${-counts[label]} more closing than opening ${label}.`);
         }
     }
 
-    checkPair('(', ')', 'round brackets');
-    checkPair('[', ']', 'square brackets');
-    checkPair('{', '}', 'curly brackets');
-    counterElt.title = errors.join('\n');
-    counterElt.classList.toggle('error', errors.length !== 0);
+    counterElem.title = [...errors].join('\n');
+    counterElem.classList.toggle('error', errors.size !== 0);
 }
 
 function setupBracketChecking(id_prompt, id_counter) {
-    var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");
-    var counter = gradioApp().getElementById(id_counter);
+    const textarea = gradioApp().querySelector(`#${id_prompt} > label > textarea`);
+    const counter = gradioApp().getElementById(id_counter);
 
     if (textarea && counter) {
-        textarea.addEventListener("input", () => checkBrackets(textarea, counter));
+        onEdit(`${id_prompt}_BracketChecking`, textarea, 400, () => checkBrackets(textarea, counter));
     }
 }
 

html/footer.html

@@ -1,7 +1,7 @@
 <div>
-        <a href="{api_docs}">API</a>
+        <a href="{api_docs}" target="_blank">API</a>
          • 
-        <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">Github</a>
+        <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">GitHub</a>
          • 
         <a href="https://gradio.app">Gradio</a>
          • 

javascript/aspectRatioOverlay.js

@@ -1,8 +1,10 @@
-let currentWidth;
-let currentHeight;
-let arFrameTimeout;
+
+let currentWidth = null;
+let currentHeight = null;
+let arFrameTimeout = setTimeout(function() {}, 0);
 
 function dimensionChange(e, is_width, is_height) {
+
     if (is_width) {
         currentWidth = e.target.value * 1.0;
     }
@@ -20,18 +22,18 @@ function dimensionChange(e, is_width, is_height) {
 
     var tabIndex = get_tab_index('mode_img2img');
     if (tabIndex == 0) { // img2img
-        targetElement = gradioApp().querySelector('#img2img_image div[data-testid=image] canvas');
+        targetElement = gradioApp().querySelector('#img2img_image div[data-testid=image] img');
     } else if (tabIndex == 1) { //Sketch
-        targetElement = gradioApp().querySelector('#img2img_sketch div[data-testid=image] canvas');
+        targetElement = gradioApp().querySelector('#img2img_sketch div[data-testid=image] img');
     } else if (tabIndex == 2) { // Inpaint
-        targetElement = gradioApp().querySelector('#img2maskimg div[data-testid=image] canvas');
+        targetElement = gradioApp().querySelector('#img2maskimg div[data-testid=image] img');
     } else if (tabIndex == 3) { // Inpaint sketch
-        targetElement = gradioApp().querySelector('#inpaint_sketch div[data-testid=image] canvas');
-    } else if (tabIndex == 4) { // Inpaint upload
-        targetElement = gradioApp().querySelector('#img_inpaint_base div[data-testid=image] img');
+        targetElement = gradioApp().querySelector('#inpaint_sketch div[data-testid=image] img');
     }
 
+
     if (targetElement) {
+
         var arPreviewRect = gradioApp().querySelector('#imageARPreview');
         if (!arPreviewRect) {
             arPreviewRect = document.createElement('div');
@@ -39,11 +41,14 @@ function dimensionChange(e, is_width, is_height) {
             gradioApp().appendChild(arPreviewRect);
         }
 
-        var viewportOffset = targetElement.getBoundingClientRect();
-        var viewportscale = Math.min(targetElement.clientWidth / targetElement.width, targetElement.clientHeight / targetElement.height);
 
-        var scaledx = targetElement.width * viewportscale;
-        var scaledy = targetElement.height * viewportscale;
+
+        var viewportOffset = targetElement.getBoundingClientRect();
+
+        var viewportscale = Math.min(targetElement.clientWidth / targetElement.naturalWidth, targetElement.clientHeight / targetElement.naturalHeight);
+
+        var scaledx = targetElement.naturalWidth * viewportscale;
+        var scaledy = targetElement.naturalHeight * viewportscale;
 
         var clientRectTop = (viewportOffset.top + window.scrollY);
         var clientRectLeft = (viewportOffset.left + window.scrollX);
@@ -70,18 +75,21 @@ function dimensionChange(e, is_width, is_height) {
         }, 2000);
 
         arPreviewRect.style.display = 'block';
+
     }
+
 }
 
+
 onAfterUiUpdate(function() {
     var arPreviewRect = gradioApp().querySelector('#imageARPreview');
     if (arPreviewRect) {
         arPreviewRect.style.display = 'none';
     }
-
     var tabImg2img = gradioApp().querySelector("#tab_img2img");
     if (tabImg2img) {
-        if (tabImg2img.style.display == "block") {
+        var inImg2img = tabImg2img.style.display == "block";
+        if (inImg2img) {
             let inputs = gradioApp().querySelectorAll('input');
             inputs.forEach(function(e) {
                 var is_width = e.parentElement.id == "img2img_width";

javascript/contextMenus.js

@@ -104,7 +104,7 @@ var contextMenuInit = function() {
                         e.preventDefault();
                     }
                 });
-            });
+            }, {passive: false});
         });
         eventListenerApplied = true;
 

javascript/extraNetworks.js

@@ -201,7 +201,7 @@ function setupExtraNetworks() {
     setupExtraNetworksForTab('img2img');
 }
 
-var re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/;
+var re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/s;
 var re_extranet_g = /<([^:^>]+:[^:]+):[\d.]+>/g;
 
 var re_extranet_neg = /\(([^:^>]+:[\d.]+)\)/;

javascript/gradio.js

@@ -1,7 +0,0 @@
-
-// added to fix a weird error in gradio 4.19 at page load
-Object.defineProperty(Array.prototype, 'toLowerCase', {
-    value: function() {
-        return this;
-    }
-});

javascript/imageviewer.js

@@ -13,6 +13,7 @@ function showModal(event) {
     if (modalImage.style.display === 'none') {
         lb.style.setProperty('background-image', 'url(' + source.src + ')');
     }
+    updateModalImage();
     lb.style.display = "flex";
     lb.focus();
 
@@ -31,24 +32,30 @@ function negmod(n, m) {
     return ((n % m) + m) % m;
 }
 
-function updateOnBackgroundChange() {
+function updateModalImage() {
     const modalImage = gradioApp().getElementById("modalImage");
-    if (modalImage && modalImage.offsetParent) {
-        let currentButton = selected_gallery_button();
-        let preview = gradioApp().querySelectorAll('.livePreview > img');
-        if (opts.js_live_preview_in_modal_lightbox && preview.length > 0) {
-            // show preview image if available
-            modalImage.src = preview[preview.length - 1].src;
-        } else if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
-            modalImage.src = currentButton.children[0].src;
-            if (modalImage.style.display === 'none') {
-                const modal = gradioApp().getElementById("lightboxModal");
-                modal.style.setProperty('background-image', `url(${modalImage.src})`);
-            }
+    let currentButton = selected_gallery_button();
+    let preview = gradioApp().querySelectorAll('.livePreview > img');
+    if (opts.js_live_preview_in_modal_lightbox && preview.length > 0) {
+        // show preview image if available
+        modalImage.src = preview[preview.length - 1].src;
+    } else if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
+        modalImage.src = currentButton.children[0].src;
+        if (modalImage.style.display === 'none') {
+            const modal = gradioApp().getElementById("lightboxModal");
+            modal.style.setProperty('background-image', `url(${modalImage.src})`);
         }
     }
 }
 
+function updateOnBackgroundChange() {
+    const modalImage = gradioApp().getElementById("modalImage");
+    if (modalImage && modalImage.offsetParent) {
+        updateModalImage();
+    }
+}
+const updateModalImageIfVisible = updateOnBackgroundChange;
+
 function modalImageSwitch(offset) {
     var galleryButtons = all_gallery_buttons();
 
@@ -158,6 +165,7 @@ function modalLivePreviewToggle(event) {
     const modalToggleLivePreview = gradioApp().getElementById("modal_toggle_live_preview");
     opts.js_live_preview_in_modal_lightbox = !opts.js_live_preview_in_modal_lightbox;
     modalToggleLivePreview.innerHTML = opts.js_live_preview_in_modal_lightbox ? "🗇" : "🗆";
+    updateModalImageIfVisible();
     event.stopPropagation();
 }
 
@@ -177,7 +185,7 @@ function modalTileImageToggle(event) {
 }
 
 onAfterUiUpdate(function() {
-    var fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > button > button > img');
+    var fullImg_preview = gradioApp().querySelectorAll('.gradio-gallery > div > img');
     if (fullImg_preview != null) {
         fullImg_preview.forEach(setupImageForLightbox);
     }

javascript/progressbar.js

@@ -79,11 +79,12 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
     var wakeLock = null;
 
     var requestWakeLock = async function() {
-        if (!opts.prevent_screen_sleep_during_generation || wakeLock) return;
+        if (!opts.prevent_screen_sleep_during_generation || wakeLock !== null) return;
         try {
             wakeLock = await navigator.wakeLock.request('screen');
         } catch (err) {
             console.error('Wake Lock is not supported.');
+            wakeLock = false;
         }
     };
 
@@ -189,7 +190,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
                         livePreview.className = 'livePreview';
                         gallery.insertBefore(livePreview, gallery.firstElementChild);
                     }
-
+                    updateModalImageIfVisible();
                     livePreview.appendChild(img);
                     if (livePreview.childElementCount > 2) {
                         livePreview.removeChild(livePreview.firstElementChild);

javascript/resizeHandle.js

@@ -124,7 +124,7 @@
                 } else {
                     R.screenX = evt.changedTouches[0].screenX;
                 }
-            });
+            }, {passive: false});
         });
 
         resizeHandle.addEventListener('dblclick', onDoubleClick);

javascript/ui.js

@@ -38,6 +38,9 @@ function extract_image_from_gallery(gallery) {
     if (gallery.length == 0) {
         return [null];
     }
+    if (gallery.length == 1) {
+        return [gallery[0]];
+    }
 
     var index = selected_gallery_index();
 
@@ -46,7 +49,7 @@ function extract_image_from_gallery(gallery) {
         index = 0;
     }
 
-    return [[gallery[index]]];
+    return [gallery[index]];
 }
 
 window.args_to_array = Array.from; // Compatibility with e.g. extensions that may expect this to be around
@@ -113,6 +116,14 @@ function get_img2img_tab_index() {
 function create_submit_args(args) {
     var res = Array.from(args);
 
+    // As it is currently, txt2img and img2img send back the previous output args (txt2img_gallery, generation_info, html_info) whenever you generate a new image.
+    // This can lead to uploading a huge gallery of previously generated images, which leads to an unnecessary delay between submitting and beginning to generate.
+    // I don't know why gradio is sending outputs along with inputs, but we can prevent sending the image gallery here, which seems to be an issue for some.
+    // If gradio at some point stops sending outputs, this may break something
+    if (Array.isArray(res[res.length - 3])) {
+        res[res.length - 3] = null;
+    }
+
     return res;
 }
 
@@ -178,6 +189,7 @@ function submit_img2img() {
     var res = create_submit_args(arguments);
 
     res[0] = id;
+    res[1] = get_tab_index('mode_img2img');
 
     return res;
 }
@@ -195,6 +207,7 @@ function submit_extras() {
 
     res[0] = id;
 
+    console.log(res);
     return res;
 }
 
@@ -363,9 +376,9 @@ function selectCheckpoint(name) {
     gradioApp().getElementById('change_checkpoint').click();
 }
 
-function currentImg2imgSourceResolution(w, h, r) {
-    var img = gradioApp().querySelector('#mode_img2img > div[style="display: block;"] :is(img, canvas)');
-    return img ? [img.naturalWidth || img.width, img.naturalHeight || img.height, r] : [0, 0, r];
+function currentImg2imgSourceResolution(w, h, scaleBy) {
+    var img = gradioApp().querySelector('#mode_img2img > div[style="display: block;"] img');
+    return img ? [img.naturalWidth, img.naturalHeight, scaleBy] : [0, 0, scaleBy];
 }
 
 function updateImg2imgResizeToTextAfterChangingImage() {

javascript/ui_settings_hints.js

@@ -14,16 +14,10 @@ onOptionsChanged(function() {
         if (!commentBefore && !commentAfter) return;
 
         var span = null;
-        if (div.classList.contains('gradio-checkbox')) {
-            span = div.querySelector('label span');
-        } else if (div.classList.contains('gradio-checkboxgroup')) {
-            span = div.querySelector('span').firstChild;
-        } else if (div.classList.contains('gradio-radio')) {
-            span = div.querySelector('span').firstChild;
-        } else {
-            var elem = div.querySelector('label span');
-            if (elem) span = elem.firstChild;
-        }
+        if (div.classList.contains('gradio-checkbox')) span = div.querySelector('label span');
+        else if (div.classList.contains('gradio-checkboxgroup')) span = div.querySelector('span').firstChild;
+        else if (div.classList.contains('gradio-radio')) span = div.querySelector('span').firstChild;
+        else span = div.querySelector('label span').firstChild;
 
         if (!span) return;
 

launch.py

@@ -6,6 +6,11 @@ git = launch_utils.git
 index_url = launch_utils.index_url
 dir_repos = launch_utils.dir_repos
 
+if args.uv:
+    from modules.uv_hook import patch
+    patch()
+
+
 commit_hash = launch_utils.commit_hash
 git_tag = launch_utils.git_tag
 

modules/api/api.py

@@ -122,7 +122,7 @@ def encode_pil_to_base64(image):
             if opts.samples_format.lower() in ("jpg", "jpeg"):
                 image.save(output_bytes, format="JPEG", exif = exif_bytes, quality=opts.jpeg_quality)
             else:
-                image.save(output_bytes, format="WEBP", exif = exif_bytes, quality=opts.jpeg_quality)
+                image.save(output_bytes, format="WEBP", exif = exif_bytes, quality=opts.jpeg_quality, lossless=opts.webp_lossless)
 
         else:
             raise HTTPException(status_code=500, detail="Invalid image format")
@@ -207,7 +207,7 @@ class Api:
         self.router = APIRouter()
         self.app = app
         self.queue_lock = queue_lock
-        #api_middleware(self.app)  # XXX this will have to be fixed
+        api_middleware(self.app)
         self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse)
         self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse)
         self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse)

modules/api/models.py

@@ -1,6 +1,6 @@
 import inspect
 
-from pydantic import BaseModel, Field, create_model, ConfigDict
+from pydantic import BaseModel, Field, create_model
 from typing import Any, Optional, Literal
 from inflection import underscore
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
@@ -92,7 +92,9 @@ class PydanticModelGenerator:
         fields = {
             d.field: (d.field_type, Field(default=d.field_value, alias=d.field_alias, exclude=d.field_exclude)) for d in self._model_def
         }
-        DynamicModel = create_model(self._model_name, __config__=ConfigDict(populate_by_name=True, frozen=False), **fields)
+        DynamicModel = create_model(self._model_name, **fields)
+        DynamicModel.__config__.allow_population_by_field_name = True
+        DynamicModel.__config__.allow_mutation = True
         return DynamicModel
 
 StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
@@ -100,13 +102,13 @@ StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
     StableDiffusionProcessingTxt2Img,
     [
         {"key": "sampler_index", "type": str, "default": "Euler"},
-        {"key": "script_name", "type": str | None, "default": None},
+        {"key": "script_name", "type": str, "default": None},
         {"key": "script_args", "type": list, "default": []},
         {"key": "send_images", "type": bool, "default": True},
         {"key": "save_images", "type": bool, "default": False},
         {"key": "alwayson_scripts", "type": dict, "default": {}},
-        {"key": "force_task_id", "type": str | None, "default": None},
-        {"key": "infotext", "type": str | None, "default": None},
+        {"key": "force_task_id", "type": str, "default": None},
+        {"key": "infotext", "type": str, "default": None},
     ]
 ).generate_model()
 
@@ -115,27 +117,27 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
     StableDiffusionProcessingImg2Img,
     [
         {"key": "sampler_index", "type": str, "default": "Euler"},
-        {"key": "init_images", "type": list | None, "default": None},
+        {"key": "init_images", "type": list, "default": None},
         {"key": "denoising_strength", "type": float, "default": 0.75},
-        {"key": "mask", "type": str | None, "default": None},
+        {"key": "mask", "type": str, "default": None},
         {"key": "include_init_images", "type": bool, "default": False, "exclude" : True},
-        {"key": "script_name", "type": str | None, "default": None},
+        {"key": "script_name", "type": str, "default": None},
         {"key": "script_args", "type": list, "default": []},
         {"key": "send_images", "type": bool, "default": True},
         {"key": "save_images", "type": bool, "default": False},
         {"key": "alwayson_scripts", "type": dict, "default": {}},
-        {"key": "force_task_id", "type": str | None, "default": None},
-        {"key": "infotext", "type": str | None, "default": None},
+        {"key": "force_task_id", "type": str, "default": None},
+        {"key": "infotext", "type": str, "default": None},
     ]
 ).generate_model()
 
 class TextToImageResponse(BaseModel):
-    images: list[str] | None = Field(default=None, title="Image", description="The generated image in base64 format.")
+    images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: dict
     info: str
 
 class ImageToImageResponse(BaseModel):
-    images: list[str] | None = Field(default=None, title="Image", description="The generated image in base64 format.")
+    images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: dict
     info: str
 
@@ -161,7 +163,7 @@ class ExtrasSingleImageRequest(ExtrasBaseRequest):
     image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
 
 class ExtrasSingleImageResponse(ExtraBaseResponse):
-    image: str | None = Field(default=None, title="Image", description="The generated image in base64 format.")
+    image: str = Field(default=None, title="Image", description="The generated image in base64 format.")
 
 class FileData(BaseModel):
     data: str = Field(title="File data", description="Base64 representation of the file")
@@ -188,15 +190,15 @@ class ProgressResponse(BaseModel):
     progress: float = Field(title="Progress", description="The progress with a range of 0 to 1")
     eta_relative: float = Field(title="ETA in secs")
     state: dict = Field(title="State", description="The current state snapshot")
-    current_image: str | None = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
-    textinfo: str | None = Field(default=None, title="Info text", description="Info text used by WebUI.")
+    current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
+    textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
 
 class InterrogateRequest(BaseModel):
     image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
     model: str = Field(default="clip", title="Model", description="The interrogate model used.")
 
 class InterrogateResponse(BaseModel):
-    caption: str | None = Field(default=None, title="Caption", description="The generated caption for the image.")
+    caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")
 
 class TrainResponse(BaseModel):
     info: str = Field(title="Train info", description="Response string from train embedding or hypernetwork task.")
@@ -221,7 +223,7 @@ _options = vars(parser)['_option_string_actions']
 for key in _options:
     if(_options[key].dest != 'help'):
         flag = _options[key]
-        _type = str | None
+        _type = str
         if _options[key].default is not None:
             _type = type(_options[key].default)
         flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))})
@@ -231,7 +233,7 @@ FlagsModel = create_model("Flags", **flags)
 class SamplerItem(BaseModel):
     name: str = Field(title="Name")
     aliases: list[str] = Field(title="Aliases")
-    options: dict[str, Any] = Field(title="Options")
+    options: dict[str, str] = Field(title="Options")
 
 class SchedulerItem(BaseModel):
     name: str = Field(title="Name")
@@ -241,9 +243,6 @@ class SchedulerItem(BaseModel):
     need_inner_model: Optional[bool] = Field(title="Needs Inner Model")
 
 class UpscalerItem(BaseModel):
-    class Config:
-        protected_namespaces = ()
-
     name: str = Field(title="Name")
     model_name: Optional[str] = Field(title="Model Name")
     model_path: Optional[str] = Field(title="Path")
@@ -254,9 +253,6 @@ class LatentUpscalerModeItem(BaseModel):
     name: str = Field(title="Name")
 
 class SDModelItem(BaseModel):
-    class Config:
-        protected_namespaces = ()
-
     title: str = Field(title="Title")
     model_name: str = Field(title="Model Name")
     hash: Optional[str] = Field(title="Short hash")
@@ -265,9 +261,6 @@ class SDModelItem(BaseModel):
     config: Optional[str] = Field(title="Config file")
 
 class SDVaeItem(BaseModel):
-    class Config:
-        protected_namespaces = ()
-
     model_name: str = Field(title="Model Name")
     filename: str = Field(title="Filename")
 
@@ -307,12 +300,12 @@ class MemoryResponse(BaseModel):
 
 
 class ScriptsList(BaseModel):
-    txt2img: list | None = Field(default=None, title="Txt2img", description="Titles of scripts (txt2img)")
-    img2img: list | None = Field(default=None, title="Img2img", description="Titles of scripts (img2img)")
+    txt2img: list = Field(default=None, title="Txt2img", description="Titles of scripts (txt2img)")
+    img2img: list = Field(default=None, title="Img2img", description="Titles of scripts (img2img)")
 
 
 class ScriptArg(BaseModel):
-    label: str | None = Field(default=None, title="Label", description="Name of the argument in UI")
+    label: str = Field(default=None, title="Label", description="Name of the argument in UI")
     value: Optional[Any] = Field(default=None, title="Value", description="Default value of the argument")
     minimum: Optional[Any] = Field(default=None, title="Minimum", description="Minimum allowed value for the argumentin UI")
     maximum: Optional[Any] = Field(default=None, title="Minimum", description="Maximum allowed value for the argumentin UI")
@@ -321,9 +314,9 @@ class ScriptArg(BaseModel):
 
 
 class ScriptInfo(BaseModel):
-    name: str | None = Field(default=None, title="Name", description="Script name")
-    is_alwayson: bool | None = Field(default=None, title="IsAlwayson", description="Flag specifying whether this script is an alwayson script")
-    is_img2img: bool | None = Field(default=None, title="IsImg2img", description="Flag specifying whether this script is an img2img script")
+    name: str = Field(default=None, title="Name", description="Script name")
+    is_alwayson: bool = Field(default=None, title="IsAlwayson", description="Flag specifying whether this script is an alwayson script")
+    is_img2img: bool = Field(default=None, title="IsImg2img", description="Flag specifying whether this script is an img2img script")
     args: list[ScriptArg] = Field(title="Arguments", description="List of script's arguments")
 
 class ExtensionItem(BaseModel):

modules/cmd_args.py

@@ -126,3 +126,4 @@ parser.add_argument("--skip-load-model-at-start", action='store_true', help="if
 parser.add_argument("--unix-filenames-sanitization", action='store_true', help="allow any symbols except '/' in filenames. May conflict with your browser and file system")
 parser.add_argument("--filenames-max-length", type=int, default=128, help='maximal length of filenames of saved images. If you override it, it can conflict with your file system')
 parser.add_argument("--no-prompt-history", action='store_true', help="disable read prompt from last generation feature; settings this argument will not create '--data_path/params.txt' file")
+parser.add_argument("--uv", action='store_true', help="use the uv package manager")

modules/dat_model.py

@@ -1,7 +1,7 @@
 import os
 
 from modules import modelloader, errors
-from modules.shared import cmd_opts, opts
+from modules.shared import cmd_opts, opts, hf_endpoint
 from modules.upscaler import Upscaler, UpscalerData
 from modules.upscaler_utils import upscale_with_model
 
@@ -49,7 +49,18 @@ class UpscalerDAT(Upscaler):
                     scaler.local_data_path = modelloader.load_file_from_url(
                         scaler.data_path,
                         model_dir=self.model_download_path,
+                        hash_prefix=scaler.sha256,
                     )
+
+                    if os.path.getsize(scaler.local_data_path) < 200:
+                        # Re-download if the file is too small, probably an LFS pointer
+                        scaler.local_data_path = modelloader.load_file_from_url(
+                            scaler.data_path,
+                            model_dir=self.model_download_path,
+                            hash_prefix=scaler.sha256,
+                            re_download=True,
+                        )
+
                 if not os.path.exists(scaler.local_data_path):
                     raise FileNotFoundError(f"DAT data missing: {scaler.local_data_path}")
                 return scaler
@@ -60,20 +71,23 @@ def get_dat_models(scaler):
     return [
         UpscalerData(
             name="DAT x2",
-            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x2.pth",
+            path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x2.pth",
             scale=2,
             upscaler=scaler,
+            sha256='7760aa96e4ee77e29d4f89c3a4486200042e019461fdb8aa286f49aa00b89b51',
         ),
         UpscalerData(
             name="DAT x3",
-            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x3.pth",
+            path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x3.pth",
             scale=3,
             upscaler=scaler,
+            sha256='581973e02c06f90d4eb90acf743ec9604f56f3c2c6f9e1e2c2b38ded1f80d197',
         ),
         UpscalerData(
             name="DAT x4",
-            path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x4.pth",
+            path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x4.pth",
             scale=4,
             upscaler=scaler,
+            sha256='391a6ce69899dff5ea3214557e9d585608254579217169faf3d4c353caff049e',
         ),
     ]

modules/errors.py

@@ -109,7 +109,7 @@ def check_versions():
 
     expected_torch_version = "2.1.2"
     expected_xformers_version = "0.0.23.post1"
-    expected_gradio_version = "4.38.1"
+    expected_gradio_version = "3.41.2"
 
     if version.parse(torch.__version__) < version.parse(expected_torch_version):
         print_error_explanation(f"""

modules/extras.py

@@ -23,7 +23,7 @@ def run_pnginfo(image):
     info = ''
     for key, text in items.items():
         info += f"""
-<div>
+<div class="infotext">
 <p><b>{plaintext_to_html(str(key))}</b></p>
 <p>{plaintext_to_html(str(text))}</p>
 </div>

modules/gradio_extensions.py

@@ -1,166 +0,0 @@
-import inspect
-import warnings
-from functools import wraps
-
-import gradio as gr
-import gradio.component_meta
-
-
-from modules import scripts, ui_tempdir, patches
-
-
-class GradioDeprecationWarning(DeprecationWarning):
-    pass
-
-
-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 = [f"gradio-{comp.get_block_name()}", *(getattr(comp, 'elem_classes', None) or [])]
-
-    if getattr(comp, 'multiselect', False):
-        comp.elem_classes.append('multiselect')
-
-
-def IOComponent_init(self, *args, **kwargs):
-    self.webui_tooltip = kwargs.pop('tooltip', None)
-
-    if scripts.scripts_current is not None:
-        scripts.scripts_current.before_component(self, **kwargs)
-
-    scripts.script_callbacks.before_component_callback(self, **kwargs)
-
-    res = original_IOComponent_init(self, *args, **kwargs)
-
-    add_classes_to_gradio_component(self)
-
-    scripts.script_callbacks.after_component_callback(self, **kwargs)
-
-    if scripts.scripts_current is not None:
-        scripts.scripts_current.after_component(self, **kwargs)
-
-    return res
-
-
-def Block_get_config(self):
-    config = original_Block_get_config(self)
-
-    webui_tooltip = getattr(self, 'webui_tooltip', None)
-    if webui_tooltip:
-        config["webui_tooltip"] = webui_tooltip
-
-    config.pop('example_inputs', None)
-
-    return config
-
-
-def BlockContext_init(self, *args, **kwargs):
-    if scripts.scripts_current is not None:
-        scripts.scripts_current.before_component(self, **kwargs)
-
-    scripts.script_callbacks.before_component_callback(self, **kwargs)
-
-    res = original_BlockContext_init(self, *args, **kwargs)
-
-    add_classes_to_gradio_component(self)
-
-    scripts.script_callbacks.after_component_callback(self, **kwargs)
-
-    if scripts.scripts_current is not None:
-        scripts.scripts_current.after_component(self, **kwargs)
-
-    return res
-
-
-def Blocks_get_config_file(self, *args, **kwargs):
-    config = original_Blocks_get_config_file(self, *args, **kwargs)
-
-    for comp_config in config["components"]:
-        if "example_inputs" in comp_config:
-            comp_config["example_inputs"] = {"serialized": []}
-
-    return config
-
-
-original_IOComponent_init = patches.patch(__name__, obj=gr.components.Component, field="__init__", replacement=IOComponent_init)
-original_Block_get_config = patches.patch(__name__, obj=gr.blocks.Block, field="get_config", replacement=Block_get_config)
-original_BlockContext_init = patches.patch(__name__, obj=gr.blocks.BlockContext, field="__init__", replacement=BlockContext_init)
-original_Blocks_get_config_file = patches.patch(__name__, obj=gr.blocks.Blocks, field="get_config_file", replacement=Blocks_get_config_file)
-
-
-ui_tempdir.install_ui_tempdir_override()
-
-
-def gradio_component_meta_create_or_modify_pyi(component_class, class_name, events):
-    if hasattr(component_class, 'webui_do_not_create_gradio_pyi_thank_you'):
-        return
-
-    gradio_component_meta_create_or_modify_pyi_original(component_class, class_name, events)
-
-
-# this prevents creation of .pyi files in webui dir
-gradio_component_meta_create_or_modify_pyi_original = patches.patch(__file__, gradio.component_meta, 'create_or_modify_pyi', gradio_component_meta_create_or_modify_pyi)
-
-# this function is broken and does not seem to do anything useful
-gradio.component_meta.updateable = lambda x: x
-
-def repair(grclass):
-    if not getattr(grclass, 'EVENTS', None):
-        return
-
-    @wraps(grclass.__init__)
-    def __repaired_init__(self, *args, tooltip=None, source=None, original=grclass.__init__, **kwargs):
-        if source:
-            kwargs["sources"] = [source]
-
-        allowed_kwargs = inspect.signature(original).parameters
-        fixed_kwargs = {}
-        for k, v in kwargs.items():
-            if k in allowed_kwargs:
-                fixed_kwargs[k] = v
-            else:
-                warnings.warn(f"unexpected argument for {grclass.__name__}: {k}", GradioDeprecationWarning, stacklevel=2)
-
-        original(self, *args, **fixed_kwargs)
-
-        self.webui_tooltip = tooltip
-
-        for event in self.EVENTS:
-            replaced_event = getattr(self, str(event))
-
-            def fun(*xargs, _js=None, replaced_event=replaced_event, **xkwargs):
-                if _js:
-                    xkwargs['js'] = _js
-
-                return replaced_event(*xargs, **xkwargs)
-
-            setattr(self, str(event), fun)
-
-    grclass.__init__ = __repaired_init__
-    grclass.update = gr.update
-
-
-for component in set(gr.components.__all__ + gr.layouts.__all__):
-    repair(getattr(gr, component, None))
-
-
-class Dependency(gr.events.Dependency):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-
-        def then(*xargs, _js=None, **xkwargs):
-            if _js:
-                xkwargs['js'] = _js
-
-            return original_then(*xargs, **xkwargs)
-
-        original_then = self.then
-        self.then = then
-
-
-gr.events.Dependency = Dependency
-
-gr.Box = gr.Group
-

modules/gradio_extensons.py

@@ -0,0 +1,83 @@
+import gradio as gr
+
+from modules import scripts, ui_tempdir, patches
+
+
+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 = [f"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):
+    self.webui_tooltip = kwargs.pop('tooltip', None)
+
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.before_component(self, **kwargs)
+
+    scripts.script_callbacks.before_component_callback(self, **kwargs)
+
+    res = original_IOComponent_init(self, *args, **kwargs)
+
+    add_classes_to_gradio_component(self)
+
+    scripts.script_callbacks.after_component_callback(self, **kwargs)
+
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.after_component(self, **kwargs)
+
+    return res
+
+
+def Block_get_config(self):
+    config = original_Block_get_config(self)
+
+    webui_tooltip = getattr(self, 'webui_tooltip', None)
+    if webui_tooltip:
+        config["webui_tooltip"] = webui_tooltip
+
+    config.pop('example_inputs', None)
+
+    return config
+
+
+def BlockContext_init(self, *args, **kwargs):
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.before_component(self, **kwargs)
+
+    scripts.script_callbacks.before_component_callback(self, **kwargs)
+
+    res = original_BlockContext_init(self, *args, **kwargs)
+
+    add_classes_to_gradio_component(self)
+
+    scripts.script_callbacks.after_component_callback(self, **kwargs)
+
+    if scripts.scripts_current is not None:
+        scripts.scripts_current.after_component(self, **kwargs)
+
+    return res
+
+
+def Blocks_get_config_file(self, *args, **kwargs):
+    config = original_Blocks_get_config_file(self, *args, **kwargs)
+
+    for comp_config in config["components"]:
+        if "example_inputs" in comp_config:
+            comp_config["example_inputs"] = {"serialized": []}
+
+    return config
+
+
+original_IOComponent_init = patches.patch(__name__, obj=gr.components.IOComponent, field="__init__", replacement=IOComponent_init)
+original_Block_get_config = patches.patch(__name__, obj=gr.blocks.Block, field="get_config", replacement=Block_get_config)
+original_BlockContext_init = patches.patch(__name__, obj=gr.blocks.BlockContext, field="__init__", replacement=BlockContext_init)
+original_Blocks_get_config_file = patches.patch(__name__, obj=gr.blocks.Blocks, field="get_config_file", replacement=Blocks_get_config_file)
+
+
+ui_tempdir.install_ui_tempdir_override()

modules/hashes.py

@@ -1,7 +1,7 @@
 import hashlib
 import os.path
 
-from modules import shared
+from modules import shared, errors
 import modules.cache
 
 dump_cache = modules.cache.dump_cache
@@ -32,7 +32,7 @@ def sha256_from_cache(filename, title, use_addnet_hash=False):
     cached_sha256 = hashes[title].get("sha256", None)
     cached_mtime = hashes[title].get("mtime", 0)
 
-    if ondisk_mtime > cached_mtime or cached_sha256 is None:
+    if ondisk_mtime != cached_mtime or cached_sha256 is None:
         return None
 
     return cached_sha256
@@ -82,3 +82,31 @@ def addnet_hash_safetensors(b):
 
     return hash_sha256.hexdigest()
 
+
+def partial_hash_from_cache(filename, *, ignore_cache: bool = False, digits: int = 8):
+    """old hash that only looks at a small part of the file and is prone to collisions
+    kept for compatibility, don't use this for new things
+    """
+    try:
+        filename = str(filename)
+        mtime = os.path.getmtime(filename)
+        hashes = cache('partial-hash')
+        cache_entry = hashes.get(filename, {})
+        cache_mtime = cache_entry.get("mtime", 0)
+        cache_hash = cache_entry.get("hash", None)
+        if mtime == cache_mtime and cache_hash and not ignore_cache:
+            return cache_hash[0:digits]
+
+        with open(filename, 'rb') as file:
+            m = hashlib.sha256()
+            file.seek(0x100000)
+            m.update(file.read(0x10000))
+            partial_hash = m.hexdigest()
+            hashes[filename] = {'mtime': mtime, 'hash': partial_hash}
+            return partial_hash[0:digits]
+
+    except FileNotFoundError:
+        pass
+    except Exception:
+        errors.report(f'Error calculating partial hash for {filename}', exc_info=True)
+    return 'NOFILE'

modules/images.py

@@ -409,6 +409,7 @@ class FilenameGenerator:
         'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if (self.p.n_iter == 1 and self.p.batch_size == 1) or self.zip else self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
         'hasprompt': lambda self, *args: self.hasprompt(*args),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
         'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
+        'randn_source': lambda self: opts.data["randn_source"],
         'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
         'user': lambda self: self.p.user,
         'vae_filename': lambda self: self.get_vae_filename(),

modules/img2img.py

@@ -2,6 +2,7 @@ import os
 from contextlib import closing
 from pathlib import Path
 
+import numpy as np
 from PIL import Image, ImageOps, ImageFilter, ImageEnhance, UnidentifiedImageError
 import gradio as gr
 
@@ -148,24 +149,25 @@ def process_batch(p, input, output_dir, inpaint_mask_dir, args, to_scale=False,
     return batch_results
 
 
-def img2img(id_task: str, request: gr.Request, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, init_img_inpaint, init_mask_inpaint, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, img2img_batch_source_type: str, img2img_batch_upload: list, *args):
+def img2img(id_task: str, request: gr.Request, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, img2img_batch_source_type: str, img2img_batch_upload: list, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
 
     if mode == 0:  # img2img
-        image = init_img["composite"]
+        image = init_img
         mask = None
     elif mode == 1:  # img2img sketch
-        image = sketch["composite"]
+        image = sketch
         mask = None
     elif mode == 2:  # inpaint
-        image, mask = init_img_with_mask["background"], init_img_with_mask["layers"][0]
+        image, mask = init_img_with_mask["image"], init_img_with_mask["mask"]
         mask = processing.create_binary_mask(mask)
     elif mode == 3:  # inpaint sketch
-        image = inpaint_color_sketch["composite"]
-        orig = inpaint_color_sketch["background"]
-        mask = inpaint_color_sketch["layers"][0].getchannel("A")
+        image = inpaint_color_sketch
+        orig = inpaint_color_sketch_orig or inpaint_color_sketch
+        pred = np.any(np.array(image) != np.array(orig), axis=-1)
+        mask = Image.fromarray(pred.astype(np.uint8) * 255, "L")
         mask = ImageEnhance.Brightness(mask).enhance(1 - mask_alpha / 100)
         blur = ImageFilter.GaussianBlur(mask_blur)
         image = Image.composite(image.filter(blur), orig, mask.filter(blur))

modules/infotext_utils.py

@@ -74,38 +74,29 @@ def image_from_url_text(filedata):
     if filedata is None:
         return None
 
-    if isinstance(filedata, list):
-        if len(filedata) == 0:
-            return None
-
+    if type(filedata) == list and filedata and type(filedata[0]) == dict and filedata[0].get("is_file", False):
         filedata = filedata[0]
 
-    if isinstance(filedata, dict) and filedata.get("is_file", False):
-        filedata = filedata
-
-    filename = None
     if type(filedata) == dict and filedata.get("is_file", False):
         filename = filedata["name"]
-
-    elif isinstance(filedata, tuple) and len(filedata) == 2:  # gradio 4.16 sends images from gallery as a list of tuples
-        return filedata[0]
-
-    if filename:
         is_in_right_dir = ui_tempdir.check_tmp_file(shared.demo, filename)
         assert is_in_right_dir, 'trying to open image file outside of allowed directories'
 
         filename = filename.rsplit('?', 1)[0]
         return images.read(filename)
 
-    if isinstance(filedata, str):
-        if filedata.startswith("data:image/png;base64,"):
-            filedata = filedata[len("data:image/png;base64,"):]
+    if type(filedata) == list:
+        if len(filedata) == 0:
+            return None
 
-        filedata = base64.decodebytes(filedata.encode('utf-8'))
-        image = images.read(io.BytesIO(filedata))
-        return image
+        filedata = filedata[0]
 
-    return None
+    if filedata.startswith("data:image/png;base64,"):
+        filedata = filedata[len("data:image/png;base64,"):]
+
+    filedata = base64.decodebytes(filedata.encode('utf-8'))
+    image = images.read(io.BytesIO(filedata))
+    return image
 
 
 def add_paste_fields(tabname, init_img, fields, override_settings_component=None):
@@ -195,8 +186,6 @@ def connect_paste_params_buttons():
 def send_image_and_dimensions(x):
     if isinstance(x, Image.Image):
         img = x
-    elif isinstance(x, list) and isinstance(x[0], tuple):
-        img = x[0][0]
     else:
         img = image_from_url_text(x)
 
@@ -424,9 +413,6 @@ def create_override_settings_dict(text_pairs):
 
     res = {}
 
-    if not text_pairs:
-        return res
-
     params = {}
     for pair in text_pairs:
         k, v = pair.split(":", maxsplit=1)

modules/initialize.py

@@ -36,7 +36,7 @@ def imports():
     shared_init.initialize()
     startup_timer.record("initialize shared")
 
-    from modules import processing, gradio_extensions, ui  # noqa: F401
+    from modules import processing, gradio_extensons, ui  # noqa: F401
     startup_timer.record("other imports")
 
 

modules/initialize_util.py

@@ -4,8 +4,6 @@ import signal
 import sys
 import re
 
-import starlette
-
 from modules.timer import startup_timer
 
 
@@ -194,7 +192,8 @@ def configure_opts_onchange():
 def setup_middleware(app):
     from starlette.middleware.gzip import GZipMiddleware
 
-    app.user_middleware.insert(0, starlette.middleware.Middleware(GZipMiddleware, minimum_size=1000))
+    app.middleware_stack = None  # reset current middleware to allow modifying user provided list
+    app.add_middleware(GZipMiddleware, minimum_size=1000)
     configure_cors_middleware(app)
     app.build_middleware_stack()  # rebuild middleware stack on-the-fly
 
@@ -212,6 +211,5 @@ def configure_cors_middleware(app):
         cors_options["allow_origins"] = cmd_opts.cors_allow_origins.split(',')
     if cmd_opts.cors_allow_origins_regex:
         cors_options["allow_origin_regex"] = cmd_opts.cors_allow_origins_regex
-
-    app.user_middleware.insert(0, starlette.middleware.Middleware(CORSMiddleware, **cors_options))
+    app.add_middleware(CORSMiddleware, **cors_options)
 

modules/launch_utils.py

@@ -43,9 +43,7 @@ def check_python_version():
         supported_minors = [7, 8, 9, 10, 11]
 
     if not (major == 3 and minor in supported_minors):
-        import modules.errors
-
-        modules.errors.print_error_explanation(f"""
+        errors.print_error_explanation(f"""
 INCOMPATIBLE PYTHON VERSION
 
 This program is tested with 3.10.6 Python, but you have {major}.{minor}.{micro}.
@@ -315,9 +313,56 @@ def requirements_met(requirements_file):
     return True
 
 
+def get_cuda_comp_cap():
+    """
+    Returns float of CUDA Compute Capability using nvidia-smi
+    Returns 0.0 on error
+    CUDA Compute Capability
+    ref https://developer.nvidia.com/cuda-gpus
+    ref https://en.wikipedia.org/wiki/CUDA
+    Blackwell consumer GPUs should return 12.0 data-center GPUs should return 10.0
+    """
+    try:
+        return max(map(float, subprocess.check_output(['nvidia-smi', '--query-gpu=compute_cap', '--format=noheader,csv'], text=True).splitlines()))
+    except Exception as _:
+        return 0.0
+
+
+def early_access_blackwell_wheels():
+    """For Blackwell GPUs, use Early Access PyTorch Wheels provided by Nvidia"""
+    print('deprecated early_access_blackwell_wheels')
+    if all([
+            os.environ.get('TORCH_INDEX_URL') is None,
+            sys.version_info.major == 3,
+            sys.version_info.minor in (10, 11, 12),
+            platform.system() == "Windows",
+            get_cuda_comp_cap() >= 10,  # Blackwell
+    ]):
+        base_repo = 'https://huggingface.co/w-e-w/torch-2.6.0-cu128.nv/resolve/main/'
+        ea_whl = {
+            10: f'{base_repo}torch-2.6.0+cu128.nv-cp310-cp310-win_amd64.whl#sha256=fef3de7ce8f4642e405576008f384304ad0e44f7b06cc1aa45e0ab4b6e70490d {base_repo}torchvision-0.20.0a0+cu128.nv-cp310-cp310-win_amd64.whl#sha256=50841254f59f1db750e7348b90a8f4cd6befec217ab53cbb03780490b225abef',
+            11: f'{base_repo}torch-2.6.0+cu128.nv-cp311-cp311-win_amd64.whl#sha256=6665c36e6a7e79e7a2cb42bec190d376be9ca2859732ed29dd5b7b5a612d0d26 {base_repo}torchvision-0.20.0a0+cu128.nv-cp311-cp311-win_amd64.whl#sha256=bbc0ee4938e35fe5a30de3613bfcd2d8ef4eae334cf8d49db860668f0bb47083',
+            12: f'{base_repo}torch-2.6.0+cu128.nv-cp312-cp312-win_amd64.whl#sha256=a3197f72379d34b08c4a4bcf49ea262544a484e8702b8c46cbcd66356c89def6 {base_repo}torchvision-0.20.0a0+cu128.nv-cp312-cp312-win_amd64.whl#sha256=235e7be71ac4e75b0f8e817bae4796d7bac8a67146d2037ab96394f2bdc63e6c'
+        }
+        return f'pip install {ea_whl.get(sys.version_info.minor)}'
+
+
+def get_default_torch_index_url():
+    """Choose default torch index url based on GPU CUDA Compute Capability (CC)
+    Use cu126 for CC <= 7.2, cu128 for CC > 7.2
+    PyTorch have dropped support for older GPUs on their cu128 and above wheels,
+    For Nvidia 10 series and older GPUs (CC < 7.0) should use cu126 wheels
+    Since GPUs with CC <= 7.2 are considered legacy by Nvidia
+        ref 2025-11-07 https://developer.nvidia.com/cuda-legacy-gpus
+    """
+    if get_cuda_comp_cap() <= 7.2:
+        return "https://download.pytorch.org/whl/cu126"
+    return "https://download.pytorch.org/whl/cu128"
+
+
 def prepare_environment():
-    torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu121")
-    torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.1.2 torchvision==0.16.2 --extra-index-url {torch_index_url}")
+    torch_index_url = os.environ.get('TORCH_INDEX_URL', get_default_torch_index_url())
+    torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.7.0 torchvision==0.22.0 --extra-index-url {torch_index_url}")
     if args.use_ipex:
         if platform.system() == "Windows":
             # The "Nuullll/intel-extension-for-pytorch" wheels were built from IPEX source for Intel Arc GPU: https://github.com/intel/intel-extension-for-pytorch/tree/xpu-main
@@ -341,7 +386,7 @@ def prepare_environment():
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     requirements_file_for_npu = os.environ.get('REQS_FILE_FOR_NPU', "requirements_npu.txt")
 
-    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.23.post1')
+    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.30')
     clip_package = os.environ.get('CLIP_PACKAGE', "https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip")
     openclip_package = os.environ.get('OPENCLIP_PACKAGE', "https://github.com/mlfoundations/open_clip/archive/bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b.zip")
 

modules/modelloader.py

@@ -10,6 +10,7 @@ import torch
 
 from modules import shared
 from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone
+from modules.util import load_file_from_url  # noqa, backwards compatibility
 
 if TYPE_CHECKING:
     import spandrel
@@ -17,30 +18,6 @@ if TYPE_CHECKING:
 logger = logging.getLogger(__name__)
 
 
-def load_file_from_url(
-    url: str,
-    *,
-    model_dir: str,
-    progress: bool = True,
-    file_name: str | None = None,
-    hash_prefix: str | None = None,
-) -> str:
-    """Download a file from `url` into `model_dir`, using the file present if possible.
-
-    Returns the path to the downloaded file.
-    """
-    os.makedirs(model_dir, exist_ok=True)
-    if not file_name:
-        parts = urlparse(url)
-        file_name = os.path.basename(parts.path)
-    cached_file = os.path.abspath(os.path.join(model_dir, file_name))
-    if not os.path.exists(cached_file):
-        print(f'Downloading: "{url}" to {cached_file}\n')
-        from torch.hub import download_url_to_file
-        download_url_to_file(url, cached_file, progress=progress, hash_prefix=hash_prefix)
-    return cached_file
-
-
 def load_models(model_path: str, model_url: str = None, command_path: str = None, ext_filter=None, download_name=None, ext_blacklist=None, hash_prefix=None) -> list:
     """
     A one-and done loader to try finding the desired models in specified directories.

modules/models/sd3/sd3_cond.py

@@ -24,7 +24,7 @@ class SafetensorsMapping(typing.Mapping):
         return self.file.get_tensor(key)
 
 
-CLIPL_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors"
+CLIPL_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors"
 CLIPL_CONFIG = {
     "hidden_act": "quick_gelu",
     "hidden_size": 768,
@@ -33,7 +33,7 @@ CLIPL_CONFIG = {
     "num_hidden_layers": 12,
 }
 
-CLIPG_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors"
+CLIPG_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors"
 CLIPG_CONFIG = {
     "hidden_act": "gelu",
     "hidden_size": 1280,
@@ -43,7 +43,7 @@ CLIPG_CONFIG = {
     "textual_inversion_key": "clip_g",
 }
 
-T5_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors"
+T5_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors"
 T5_CONFIG = {
     "d_ff": 10240,
     "d_model": 4096,

modules/postprocessing.py

@@ -13,9 +13,6 @@ def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir,
 
     outputs = []
 
-    if isinstance(image, dict):
-        image = image["composite"]
-
     def get_images(extras_mode, image, image_folder, input_dir):
         if extras_mode == 1:
             for img in image_folder:

modules/processing.py

@@ -1259,7 +1259,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
                 if self.hr_checkpoint_info is None:
                     raise Exception(f'Could not find checkpoint with name {self.hr_checkpoint_name}')
 
-                self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title
+                if shared.sd_model.sd_checkpoint_info == self.hr_checkpoint_info:
+                    self.hr_checkpoint_info = None
+                else:
+                    self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title
 
             if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name:
                 self.extra_generation_params["Hires sampler"] = self.hr_sampler_name

modules/processing_scripts/refiner.py

@@ -22,7 +22,7 @@ class ScriptRefiner(scripts.ScriptBuiltinUI):
     def ui(self, is_img2img):
         with InputAccordion(False, label="Refiner", elem_id=self.elem_id("enable")) as enable_refiner:
             with gr.Row():
-                refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=["", *sd_models.checkpoint_tiles()], value='', tooltip="switch to another model in the middle of generation")
+                refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=sd_models.checkpoint_tiles(), value='', tooltip="switch to another model in the middle of generation")
                 create_refresh_button(refiner_checkpoint, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, self.elem_id("checkpoint_refresh"))
 
                 refiner_switch_at = gr.Slider(value=0.8, label="Switch at", minimum=0.01, maximum=1.0, step=0.01, elem_id=self.elem_id("switch_at"), tooltip="fraction of sampling steps when the switch to refiner model should happen; 1=never, 0.5=switch in the middle of generation")

modules/processing_scripts/seed.py

@@ -34,7 +34,7 @@ class ScriptSeed(scripts.ScriptBuiltinUI):
             random_seed = ToolButton(ui.random_symbol, elem_id=self.elem_id("random_seed"), tooltip="Set seed to -1, which will cause a new random number to be used every time")
             reuse_seed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_seed"), tooltip="Reuse seed from last generation, mostly useful if it was randomized")
 
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id=self.elem_id("subseed_show"), value=False, scale=0, min_width=60)
+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=self.elem_id("subseed_show"), value=False)
 
         with gr.Group(visible=False, elem_id=self.elem_id("seed_extras")) as seed_extras:
             with gr.Row(elem_id=self.elem_id("subseed_row")):

modules/progress.py

@@ -1,4 +1,3 @@
-from __future__ import annotations
 import base64
 import io
 import time
@@ -67,11 +66,11 @@ class ProgressResponse(BaseModel):
     active: bool = Field(title="Whether the task is being worked on right now")
     queued: bool = Field(title="Whether the task is in queue")
     completed: bool = Field(title="Whether the task has already finished")
-    progress: float | None = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
-    eta: float | None = Field(default=None, title="ETA in secs")
-    live_preview: str | None = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
-    id_live_preview: int | None = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image")
-    textinfo: str | None = Field(default=None, title="Info text", description="Info text used by WebUI.")
+    progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
+    eta: float = Field(default=None, title="ETA in secs")
+    live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
+    id_live_preview: int = Field(default=None, title="Live preview image ID", description="Send this together with next request to prevent receiving same image")
+    textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
 
 
 def setup_progress_api(app):

modules/scripts_auto_postprocessing.py

@@ -13,6 +13,7 @@ class ScriptPostprocessingForMainUI(scripts.Script):
         return scripts.AlwaysVisible
 
     def ui(self, is_img2img):
+        self.script.tab_name = '_img2img' if is_img2img else '_txt2img'
         self.postprocessing_controls = self.script.ui()
         return self.postprocessing_controls.values()
 
@@ -33,7 +34,7 @@ def create_auto_preprocessing_script_data():
 
     for name in shared.opts.postprocessing_enable_in_main_ui:
         script = next(iter([x for x in scripts.postprocessing_scripts_data if x.script_class.name == name]), None)
-        if script is None:
+        if script is None or script.script_class.extra_only:
             continue
 
         constructor = lambda s=script: ScriptPostprocessingForMainUI(s.script_class())

modules/scripts_postprocessing.py

@@ -1,3 +1,4 @@
+import re
 import dataclasses
 import os
 import gradio as gr
@@ -59,6 +60,10 @@ class ScriptPostprocessing:
     args_from = None
     args_to = None
 
+    # define if the script should be used only in extras or main UI
+    extra_only = None
+    main_ui_only = None
+
     order = 1000
     """scripts will be ordred by this value in postprocessing UI"""
 
@@ -97,6 +102,31 @@ class ScriptPostprocessing:
     def image_changed(self):
         pass
 
+    tab_name = ''  # used by ScriptPostprocessingForMainUI
+    replace_pattern = re.compile(r'\s')
+    rm_pattern = re.compile(r'[^a-z_0-9]')
+
+    def elem_id(self, item_id):
+        """
+        Helper function to generate id for a HTML element
+        constructs final id out of script name and user-supplied item_id
+        'script_extras_{self.name.lower()}_{item_id}'
+        {tab_name} will append to the end of the id if set
+        tab_name will be set to '_img2img' or '_txt2img' if use by ScriptPostprocessingForMainUI
+
+        Extensions should use this function to generate element IDs
+        """
+        return self.elem_id_suffix(f'extras_{self.name.lower()}_{item_id}')
+
+    def elem_id_suffix(self, base_id):
+        """
+        Append tab_name to the base_id
+
+        Extensions that already have specific there element IDs and wish to keep their IDs the same when possible should use this function
+        """
+        base_id = self.rm_pattern.sub('', self.replace_pattern.sub('_', base_id))
+        return f'{base_id}{self.tab_name}'
+
 
 def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
     try:
@@ -119,10 +149,6 @@ class ScriptPostprocessingRunner:
         for script_data in scripts_data:
             script: ScriptPostprocessing = script_data.script_class()
             script.filename = script_data.path
-
-            if script.name == "Simple Upscale":
-                continue
-
             self.scripts.append(script)
 
     def create_script_ui(self, script, inputs):
@@ -152,7 +178,7 @@ class ScriptPostprocessingRunner:
 
             return len(self.scripts)
 
-        filtered_scripts = [script for script in self.scripts if script.name not in scripts_filter_out]
+        filtered_scripts = [script for script in self.scripts if script.name not in scripts_filter_out and not script.main_ui_only]
         script_scores = {script.name: (script_score(script.name), script.order, script.name, original_index) for original_index, script in enumerate(filtered_scripts)}
 
         return sorted(filtered_scripts, key=lambda x: script_scores[x.name])

modules/sd_disable_initialization.py

@@ -76,7 +76,7 @@ class DisableInitialization(ReplaceHelper):
         def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs):
 
             # this file is always 404, prevent making request
-            if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json':
+            if url == f'{shared.hf_endpoint}/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json':
                 return None
 
             try:

modules/sd_hijack_optimizations.py

@@ -54,7 +54,7 @@ class SdOptimizationXformers(SdOptimization):
     priority = 100
 
     def is_available(self):
-        return shared.cmd_opts.force_enable_xformers or (shared.xformers_available and torch.cuda.is_available() and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0))
+        return shared.cmd_opts.force_enable_xformers or (shared.xformers_available and torch.cuda.is_available() and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (12, 0))
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = xformers_attention_forward

modules/sd_models.py

@@ -13,6 +13,7 @@ from urllib import request
 import ldm.modules.midas as midas
 
 from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache, extra_networks, processing, lowvram, sd_hijack, patches
+from modules.hashes import partial_hash_from_cache as model_hash  # noqa: F401 for backwards compatibility
 from modules.timer import Timer
 from modules.shared import opts
 import tomesd
@@ -87,7 +88,7 @@ class CheckpointInfo:
         self.name = name
         self.name_for_extra = os.path.splitext(os.path.basename(filename))[0]
         self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
-        self.hash = model_hash(filename)
+        self.hash = hashes.partial_hash_from_cache(filename)
 
         self.sha256 = hashes.sha256_from_cache(self.filename, f"checkpoint/{name}")
         self.shorthash = self.sha256[0:10] if self.sha256 else None
@@ -159,7 +160,7 @@ def list_models():
         model_url = None
         expected_sha256 = None
     else:
-        model_url = f"{shared.hf_endpoint}/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors"
+        model_url = f"{shared.hf_endpoint}/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors"
         expected_sha256 = '6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa'
 
     model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"], download_name="v1-5-pruned-emaonly.safetensors", ext_blacklist=[".vae.ckpt", ".vae.safetensors"], hash_prefix=expected_sha256)
@@ -200,21 +201,6 @@ def get_closet_checkpoint_match(search_string):
     return None
 
 
-def model_hash(filename):
-    """old hash that only looks at a small part of the file and is prone to collisions"""
-
-    try:
-        with open(filename, "rb") as file:
-            import hashlib
-            m = hashlib.sha256()
-
-            file.seek(0x100000)
-            m.update(file.read(0x10000))
-            return m.hexdigest()[0:8]
-    except FileNotFoundError:
-        return 'NOFILE'
-
-
 def select_checkpoint():
     """Raises `FileNotFoundError` if no checkpoints are found."""
     model_checkpoint = shared.opts.sd_model_checkpoint
@@ -423,6 +409,10 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
 
     set_model_type(model, state_dict)
     set_model_fields(model)
+    if 'ztsnr' in state_dict:
+        model.ztsnr = True
+    else:
+        model.ztsnr = False
 
     if model.is_sdxl:
         sd_models_xl.extend_sdxl(model)
@@ -661,7 +651,7 @@ def apply_alpha_schedule_override(sd_model, p=None):
             p.extra_generation_params['Downcast alphas_cumprod'] = opts.use_downcasted_alpha_bar
         sd_model.alphas_cumprod = sd_model.alphas_cumprod.half().to(shared.device)
 
-    if opts.sd_noise_schedule == "Zero Terminal SNR":
+    if opts.sd_noise_schedule == "Zero Terminal SNR" or (hasattr(sd_model, 'ztsnr') and sd_model.ztsnr):
         if p is not None:
             p.extra_generation_params['Noise Schedule'] = opts.sd_noise_schedule
         sd_model.alphas_cumprod = rescale_zero_terminal_snr_abar(sd_model.alphas_cumprod).to(shared.device)
@@ -783,7 +773,7 @@ def get_obj_from_str(string, reload=False):
     return getattr(importlib.import_module(module, package=None), cls)
 
 
-def load_model(checkpoint_info=None, already_loaded_state_dict=None):
+def load_model(checkpoint_info=None, already_loaded_state_dict=None, checkpoint_config=None):
     from modules import sd_hijack
     checkpoint_info = checkpoint_info or select_checkpoint()
 
@@ -801,7 +791,8 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
     else:
         state_dict = get_checkpoint_state_dict(checkpoint_info, timer)
 
-    checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
+    if not checkpoint_config:
+        checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
     clip_is_included_into_sd = any(x for x in [sd1_clip_weight, sd2_clip_weight, sdxl_clip_weight, sdxl_refiner_clip_weight] if x in state_dict)
 
     timer.record("find config")
@@ -974,7 +965,7 @@ def reload_model_weights(sd_model=None, info=None, forced_reload=False):
         if sd_model is not None:
             send_model_to_trash(sd_model)
 
-        load_model(checkpoint_info, already_loaded_state_dict=state_dict)
+        load_model(checkpoint_info, already_loaded_state_dict=state_dict, checkpoint_config=checkpoint_config)
         return model_data.sd_model
 
     try:

modules/sd_models_config.py

@@ -14,6 +14,7 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
 config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
 config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml")
 config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml")
+config_sdxlv = os.path.join(sd_configs_path, "sd_xl_v.yaml")
 config_sdxl_refiner = os.path.join(sd_xl_repo_configs_path, "sd_xl_refiner.yaml")
 config_sdxl_inpainting = os.path.join(sd_configs_path, "sd_xl_inpaint.yaml")
 config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")
@@ -81,6 +82,9 @@ def guess_model_config_from_state_dict(sd, filename):
         if diffusion_model_input.shape[1] == 9:
             return config_sdxl_inpainting
         else:
+            if ('v_pred' in sd):
+                del sd['v_pred']
+                return config_sdxlv
             return config_sdxl
 
     if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None:

modules/sd_schedulers.py

@@ -117,12 +117,15 @@ def ddim_scheduler(n, sigma_min, sigma_max, inner_model, device):
 
 
 def beta_scheduler(n, sigma_min, sigma_max, inner_model, device):
-    # From "Beta Sampling is All You Need" [arXiv:2407.12173] (Lee et. al, 2024) """
+    # From "Beta Sampling is All You Need" [arXiv:2407.12173] (Lee et. al, 2024)
     alpha = shared.opts.beta_dist_alpha
     beta = shared.opts.beta_dist_beta
-    timesteps = 1 - np.linspace(0, 1, n)
-    timesteps = [stats.beta.ppf(x, alpha, beta) for x in timesteps]
-    sigmas = [sigma_min + (x * (sigma_max-sigma_min)) for x in timesteps]
+    curve = [stats.beta.ppf(x, alpha, beta) for x in np.linspace(1, 0, n)]
+
+    start = inner_model.sigma_to_t(torch.tensor(sigma_max))
+    end = inner_model.sigma_to_t(torch.tensor(sigma_min))
+    timesteps = [end + x * (start - end) for x in curve]
+    sigmas = [inner_model.t_to_sigma(ts) for ts in timesteps]
     sigmas += [0.0]
     return torch.FloatTensor(sigmas).to(device)
 

modules/shared_items.py

@@ -16,10 +16,12 @@ def dat_models_names():
     return [x.name for x in modules.dat_model.get_dat_models(None)]
 
 
-def postprocessing_scripts():
+def postprocessing_scripts(filter_out_extra_only=False, filter_out_main_ui_only=False):
     import modules.scripts
-
-    return modules.scripts.scripts_postproc.scripts
+    return list(filter(
+        lambda s: (not filter_out_extra_only or not s.extra_only) and (not filter_out_main_ui_only or not s.main_ui_only),
+        modules.scripts.scripts_postproc.scripts,
+    ))
 
 
 def sd_vae_items():
@@ -123,7 +125,7 @@ def ui_reorder_categories():
 
 def callbacks_order_settings():
     options = {
-        "sd_vae_explanation": OptionHTML("""
+        "callbacks_order_explanation": OptionHTML("""
     For categories below, callbacks added to dropdowns happen before others, in order listed.
     """),
 

modules/shared_options.py

@@ -33,12 +33,12 @@ categories.register_category("training", "Training")
 
 options_templates.update(options_section(('saving-images', "Saving images/grids", "saving"), {
     "samples_save": OptionInfo(True, "Always save all generated images"),
-    "samples_format": OptionInfo('png', 'File format for images'),
+    "samples_format": OptionInfo('png', 'File format for images', ui_components.DropdownEditable, {"choices": ("png", "jpg", "jpeg", "webp", "avif")}).info("manual input of <a href='https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html' target='_blank'>other formats</a> is possible, but compatibility is not guaranteed"),
     "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"),
     "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
     "save_images_replace_action": OptionInfo("Replace", "Saving the image to an existing file", gr.Radio, {"choices": ["Replace", "Add number suffix"], **hide_dirs}),
     "grid_save": OptionInfo(True, "Always save all generated image grids"),
-    "grid_format": OptionInfo('png', 'File format for grids'),
+    "grid_format": OptionInfo('png', 'File format for grids', ui_components.DropdownEditable, {"choices": ("png", "jpg", "jpeg", "webp", "avif")}).info("manual input of <a href='https://pillow.readthedocs.io/en/stable/handbook/image-file-formats.html' target='_blank'>other formats</a> is possible, but compatibility is not guaranteed"),
     "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
     "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
     "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"),
@@ -128,6 +128,7 @@ options_templates.update(options_section(('system', "System", "system"), {
     "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"),
     "hide_ldm_prints": OptionInfo(True, "Prevent Stability-AI's ldm/sgm modules from printing noise to console."),
     "dump_stacks_on_signal": OptionInfo(False, "Print stack traces before exiting the program with ctrl+c."),
+    "concurrent_git_fetch_limit": OptionInfo(16, "Number of simultaneous extension update checks ", gr.Slider, {"step": 1, "minimum": 1, "maximum": 100}).info("reduce extension update check time"),
 }))
 
 options_templates.update(options_section(('profiler', "Profiler", "system"), {
@@ -219,6 +220,7 @@ options_templates.update(options_section(('img2img', "img2img", "sd"), {
     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"),
     "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill transparent parts of the input image with this color.", ui_components.FormColorPicker, {}),
+    "img2img_editor_height": OptionInfo(720, "Height of the image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_reload_ui(),
     "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_reload_ui(),
     "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker,  {}).info("brush color of inpaint mask").needs_reload_ui(),
     "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "Inpaint sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_reload_ui(),
@@ -230,7 +232,7 @@ options_templates.update(options_section(('img2img', "img2img", "sd"), {
 
 options_templates.update(options_section(('optimizations', "Optimizations", "sd"), {
     "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}),
-    "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}, infotext='NGMS').link("PR", "https://github.com/AUTOMATIC1111/stablediffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"),
+    "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}, infotext='NGMS').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"),
     "s_min_uncond_all": OptionInfo(False, "Negative Guidance minimum sigma all steps", infotext='NGMS all steps').info("By default, NGMS above skips every other step; this makes it skip all steps"),
     "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}, infotext='Token merging ratio').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"),
     "token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"),
@@ -290,6 +292,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks", "s
     "textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"),
     "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"),
     "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *shared.hypernetworks]}, refresh=shared_items.reload_hypernetworks),
+    "textual_inversion_image_embedding_data_cache": OptionInfo(False, 'Cache the data of image embeddings').info('potentially increase TI load time at the cost some disk space'),
 }))
 
 options_templates.update(options_section(('ui_prompt_editing', "Prompt editing", "ui"), {
@@ -403,15 +406,15 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"),
     'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'),
     'sd_noise_schedule': OptionInfo("Default", "Noise schedule for sampling", gr.Radio, {"choices": ["Default", "Zero Terminal SNR"]}, infotext="Noise Schedule").info("for use with zero terminal SNR trained models"),
-    'skip_early_cond': OptionInfo(0.0, "Ignore negative prompt during early sampling", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext="Skip Early CFG").info("disables CFG on a proportion of steps at the beginning of generation; 0=skip none; 1=skip all; can both improve sample diversity/quality and speed up sampling"),
-    'beta_dist_alpha': OptionInfo(0.6, "Beta scheduler - alpha", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler alpha').info('Default = 0.6; the alpha parameter of the beta distribution used in Beta sampling'),
-    'beta_dist_beta': OptionInfo(0.6, "Beta scheduler - beta", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler beta').info('Default = 0.6; the beta parameter of the beta distribution used in Beta sampling'),
+    'skip_early_cond': OptionInfo(0.0, "Ignore negative prompt during early sampling", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext="Skip Early CFG").info("disables CFG on a proportion of steps at the beginning of generation; 0=skip none; 1=skip all; can both improve sample diversity/quality and speed up sampling; XYZ plot: Skip Early CFG"),
+    'beta_dist_alpha': OptionInfo(0.6, "Beta scheduler - alpha", gr.Slider, {"minimum": 0.01, "maximum": 5.0, "step": 0.01}, infotext='Beta scheduler alpha').info('Default = 0.6; the alpha parameter of the beta distribution used in Beta sampling'),
+    'beta_dist_beta': OptionInfo(0.6, "Beta scheduler - beta", gr.Slider, {"minimum": 0.01, "maximum": 5.0, "step": 0.01}, infotext='Beta scheduler beta').info('Default = 0.6; the beta parameter of the beta distribution used in Beta sampling'),
 }))
 
 options_templates.update(options_section(('postprocessing', "Postprocessing", "postprocessing"), {
-    'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'postprocessing_disable_in_extras': OptionInfo([], "Disable postprocessing operations in extras tab", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
+    'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts(filter_out_extra_only=True)]}),
+    'postprocessing_disable_in_extras': OptionInfo([], "Disable postprocessing operations in extras tab", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts(filter_out_main_ui_only=True)]}),
+    'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts(filter_out_main_ui_only=True)]}),
     'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     'postprocessing_existing_caption_action': OptionInfo("Ignore", "Action for existing captions", gr.Radio, {"choices": ["Ignore", "Keep", "Prepend", "Append"]}).info("when generating captions using postprocessing; Ignore = use generated; Keep = use original; Prepend/Append = combine both"),
 }))

modules/textual_inversion/textual_inversion.py

@@ -12,7 +12,7 @@ import safetensors.torch
 import numpy as np
 from PIL import Image, PngImagePlugin
 
-from modules import shared, devices, sd_hijack, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors, hashes
+from modules import shared, devices, sd_hijack, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors, hashes, cache
 import modules.textual_inversion.dataset
 from modules.textual_inversion.learn_schedule import LearnRateScheduler
 
@@ -116,6 +116,7 @@ class EmbeddingDatabase:
         self.expected_shape = -1
         self.embedding_dirs = {}
         self.previously_displayed_embeddings = ()
+        self.image_embedding_cache = cache.cache('image-embedding')
 
     def add_embedding_dir(self, path):
         self.embedding_dirs[path] = DirWithTextualInversionEmbeddings(path)
@@ -154,6 +155,31 @@ class EmbeddingDatabase:
         vec = shared.sd_model.cond_stage_model.encode_embedding_init_text(",", 1)
         return vec.shape[1]
 
+    def read_embedding_from_image(self, path, name):
+        try:
+            ondisk_mtime = os.path.getmtime(path)
+
+            if (cache_embedding := self.image_embedding_cache.get(path)) and ondisk_mtime == cache_embedding.get('mtime', 0):
+                # cache will only be used if the file has not been modified time matches
+                return cache_embedding.get('data', None), cache_embedding.get('name', None)
+
+            embed_image = Image.open(path)
+            if hasattr(embed_image, 'text') and 'sd-ti-embedding' in embed_image.text:
+                data = embedding_from_b64(embed_image.text['sd-ti-embedding'])
+                name = data.get('name', name)
+            elif data := extract_image_data_embed(embed_image):
+                name = data.get('name', name)
+
+            if data is None or shared.opts.textual_inversion_image_embedding_data_cache:
+                # data of image embeddings only will be cached if the option textual_inversion_image_embedding_data_cache is enabled
+                # results of images that are not embeddings will allways be cached to reduce unnecessary future disk reads
+                self.image_embedding_cache[path] = {'data': data, 'name': None if data is None else name, 'mtime': ondisk_mtime}
+
+            return data, name
+        except Exception:
+            errors.report(f"Error loading embedding {path}", exc_info=True)
+        return None, None
+
     def load_from_file(self, path, filename):
         name, ext = os.path.splitext(filename)
         ext = ext.upper()
@@ -163,17 +189,10 @@ class EmbeddingDatabase:
             if second_ext.upper() == '.PREVIEW':
                 return
 
-            embed_image = Image.open(path)
-            if hasattr(embed_image, 'text') and 'sd-ti-embedding' in embed_image.text:
-                data = embedding_from_b64(embed_image.text['sd-ti-embedding'])
-                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 embedding, just a preview image
-                    return
+            data, name = self.read_embedding_from_image(path, name)
+            if data is None:
+                return
+
         elif ext in ['.BIN', '.PT']:
             data = torch.load(path, map_location="cpu")
         elif ext in ['.SAFETENSORS']:
@@ -191,7 +210,6 @@ class EmbeddingDatabase:
         else:
             print(f"Unable to load Textual inversion embedding due to data issue: '{name}'.")
 
-
     def load_from_dir(self, embdir):
         if not os.path.isdir(embdir.path):
             return

modules/ui.py

@@ -8,10 +8,11 @@ from contextlib import ExitStack
 
 import gradio as gr
 import gradio.utils
+import numpy as np
 from PIL import Image, PngImagePlugin  # noqa: F401
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call, wrap_gradio_call_no_job # noqa: F401
 
-from modules import gradio_extensions, sd_schedulers  # noqa: F401
+from modules import gradio_extensons, sd_schedulers  # noqa: F401
 from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, scripts, sd_samplers, processing, ui_extra_networks, ui_toprow, launch_utils
 from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML, InputAccordion, ResizeHandleRow
 from modules.paths import script_path
@@ -32,7 +33,7 @@ from modules.infotext_utils import image_from_url_text, PasteField
 create_setting_component = ui_settings.create_setting_component
 
 warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
-warnings.filterwarnings("default" if opts.show_gradio_deprecation_warnings else "ignore", category=gradio_extensions.GradioDeprecationWarning)
+warnings.filterwarnings("default" if opts.show_gradio_deprecation_warnings else "ignore", category=gr.deprecation.GradioDeprecationWarning)
 
 # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI
 mimetypes.init()
@@ -43,6 +44,9 @@ mimetypes.add_type('application/javascript', '.mjs')
 mimetypes.add_type('image/webp', '.webp')
 mimetypes.add_type('image/avif', '.avif')
 
+# override potentially incorrect mimetypes
+mimetypes.add_type('text/css', '.css')
+
 if not cmd_opts.share and not cmd_opts.listen:
     # fix gradio phoning home
     gradio.utils.version_check = lambda: None
@@ -100,8 +104,8 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
 
 
 def resize_from_to_html(width, height, scale_by):
-    target_width = int(float(width) * scale_by)
-    target_height = int(float(height) * scale_by)
+    target_width = int(width * scale_by)
+    target_height = int(height * scale_by)
 
     if not target_width or not target_height:
         return "no image selected"
@@ -110,11 +114,10 @@ def resize_from_to_html(width, height, scale_by):
 
 
 def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_dir, *ii_singles):
-    mode = int(mode)
-    if mode in (0, 1, 3, 4):
-        return [interrogation_function(ii_singles[mode]["composite"]), None]
+    if mode in {0, 1, 3, 4}:
+        return [interrogation_function(ii_singles[mode]), None]
     elif mode == 2:
-        return [interrogation_function(ii_singles[mode]["composite"]), None]
+        return [interrogation_function(ii_singles[mode]["image"]), None]
     elif mode == 5:
         assert not shared.cmd_opts.hide_ui_dir_config, "Launched with --hide-ui-dir-config, batch img2img disabled"
         images = shared.listfiles(ii_input_dir)
@@ -267,8 +270,7 @@ def create_ui():
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         toprow = ui_toprow.Toprow(is_img2img=False, is_compact=shared.opts.compact_prompt_box)
 
-        dummy_component = gr.Textbox(visible=False)
-        dummy_component_number = gr.Number(visible=False)
+        dummy_component = gr.Label(visible=False)
 
         extra_tabs = gr.Tabs(elem_id="txt2img_extra_tabs", elem_classes=["extra-networks"])
         extra_tabs.__enter__()
@@ -311,7 +313,7 @@ def create_ui():
                         with gr.Row(elem_id="txt2img_accordions", elem_classes="accordions"):
                             with InputAccordion(False, label="Hires. fix", elem_id="txt2img_hr") as enable_hr:
                                 with enable_hr.extra():
-                                    hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution")
+                                    hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False, min_width=0)
 
                                 with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"):
                                     hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
@@ -425,7 +427,7 @@ def create_ui():
             output_panel.button_upscale.click(
                 fn=wrap_gradio_gpu_call(modules.txt2img.txt2img_upscale, extra_outputs=[None, '', '']),
                 _js="submit_txt2img_upscale",
-                inputs=txt2img_inputs[0:1] + [output_panel.gallery, dummy_component_number, output_panel.generation_info] + txt2img_inputs[1:],
+                inputs=txt2img_inputs[0:1] + [output_panel.gallery, dummy_component, output_panel.generation_info] + txt2img_inputs[1:],
                 outputs=txt2img_outputs,
                 show_progress=False,
             )
@@ -539,21 +541,31 @@ def create_ui():
                             img2img_selected_tab = gr.Number(value=0, visible=False)
 
                             with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img:
-                                init_img = gr.ImageEditor(label="Image for img2img", elem_id="img2img_image", show_label=False, interactive=True, type="pil", image_mode="RGBA")
+                                init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA", height=opts.img2img_editor_height)
                                 add_copy_image_controls('img2img', init_img)
 
                             with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch:
-                                sketch = gr.ImageEditor(label="Image for img2img", elem_id="img2img_sketch", show_label=False, interactive=True, type="pil", image_mode="RGBA", brush=gr.Brush(default_color=opts.img2img_sketch_default_brush_color))
+                                sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGB", height=opts.img2img_editor_height, brush_color=opts.img2img_sketch_default_brush_color)
                                 add_copy_image_controls('sketch', sketch)
 
                             with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint:
-                                init_img_with_mask = gr.ImageEditor(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", brush=gr.Brush(colors=[opts.img2img_inpaint_mask_brush_color], color_mode="fixed"), interactive=True, type="pil", image_mode="RGBA", layers=False)
+                                init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_mask_brush_color)
                                 add_copy_image_controls('inpaint', init_img_with_mask)
 
                             with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color:
-                                inpaint_color_sketch = gr.ImageEditor(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", brush=gr.Brush(default_color=opts.img2img_inpaint_sketch_default_brush_color), interactive=True, type="pil", image_mode="RGBA", layers=False)
+                                inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGB", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_sketch_default_brush_color)
+                                inpaint_color_sketch_orig = gr.State(None)
                                 add_copy_image_controls('inpaint_sketch', inpaint_color_sketch)
 
+                                def update_orig(image, state):
+                                    if image is not None:
+                                        same_size = state is not None and state.size == image.size
+                                        has_exact_match = np.any(np.all(np.array(image) == np.array(state), axis=-1))
+                                        edited = same_size and has_exact_match
+                                        return image if not edited or state is None else state
+
+                                inpaint_color_sketch.change(update_orig, [inpaint_color_sketch, inpaint_color_sketch_orig], inpaint_color_sketch_orig)
+
                             with gr.TabItem('Inpaint upload', id='inpaint_upload', elem_id="img2img_inpaint_upload_tab") as tab_inpaint_upload:
                                 init_img_inpaint = gr.Image(label="Image for img2img", show_label=False, source="upload", interactive=True, type="pil", elem_id="img_inpaint_base")
                                 init_mask_inpaint = gr.Image(label="Mask", source="upload", interactive=True, type="pil", image_mode="RGBA", elem_id="img_inpaint_mask")
@@ -586,14 +598,20 @@ def create_ui():
                             for i, tab in enumerate(img2img_tabs):
                                 tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab])
 
+                        def copy_image(img):
+                            if isinstance(img, dict) and 'image' in img:
+                                return img['image']
+
+                            return img
+
                         for button, name, elem in copy_image_buttons:
                             button.click(
-                                fn=lambda img: img,
+                                fn=copy_image,
                                 inputs=[elem],
                                 outputs=[copy_image_destinations[name]],
                             )
                             button.click(
-                                fn=None,
+                                fn=lambda: None,
                                 _js=f"switch_to_{name.replace(' ', '_')}",
                                 inputs=[],
                                 outputs=[],
@@ -696,6 +714,12 @@ def create_ui():
                     if category not in {"accordions"}:
                         scripts.scripts_img2img.setup_ui_for_section(category)
 
+            # the code below is meant to update the resolution label after the image in the image selection UI has changed.
+            # as it is now the event keeps firing continuously for inpaint edits, which ruins the page with constant requests.
+            # I assume this must be a gradio bug and for now we'll just do it for non-inpaint inputs.
+            for component in [init_img, sketch]:
+                component.change(fn=lambda: None, _js="updateImg2imgResizeToTextAfterChangingImage", inputs=[], outputs=[], show_progress=False)
+
             def select_img2img_tab(tab):
                 return gr.update(visible=tab in [2, 3, 4]), gr.update(visible=tab == 3),
 
@@ -713,7 +737,7 @@ def create_ui():
                 _js="submit_img2img",
                 inputs=[
                     dummy_component,
-                    img2img_selected_tab,
+                    dummy_component,
                     toprow.prompt,
                     toprow.negative_prompt,
                     toprow.ui_styles.dropdown,
@@ -721,6 +745,7 @@ def create_ui():
                     sketch,
                     init_img_with_mask,
                     inpaint_color_sketch,
+                    inpaint_color_sketch_orig,
                     init_img_inpaint,
                     init_mask_inpaint,
                     mask_blur,
@@ -779,9 +804,9 @@ def create_ui():
             res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('img2img')}", inputs=None, outputs=None, show_progress=False)
 
             detect_image_size_btn.click(
-                fn=lambda w, h: (w or gr.update(), h or gr.update()),
+                fn=lambda w, h, _: (w or gr.update(), h or gr.update()),
                 _js="currentImg2imgSourceResolution",
-                inputs=[dummy_component, dummy_component],
+                inputs=[dummy_component, dummy_component, dummy_component],
                 outputs=[width, height],
                 show_progress=False,
             )

modules/ui_common.py

@@ -8,6 +8,7 @@ from contextlib import nullcontext
 import gradio as gr
 
 from modules import call_queue, shared, ui_tempdir, util
+from modules.infotext_utils import image_from_url_text
 import modules.images
 from modules.ui_components import ToolButton
 import modules.infotext_utils as parameters_copypaste
@@ -114,8 +115,10 @@ def save_files(js_data, images, do_make_zip, index):
                 writer.writerow(fields)
 
         for image_index, filedata in enumerate(images, start_index):
-            image = filedata[0]
+            image = image_from_url_text(filedata)
+
             is_grid = image_index < p.index_of_first_image
+
             p.batch_index = image_index-1
 
             parameters = parameters_copypaste.parse_generation_parameters(data["infotexts"][image_index], [])
@@ -181,7 +184,7 @@ def create_output_panel(tabname, outdir, toprow=None):
 
         with gr.Column(variant='panel', elem_id=f"{tabname}_results_panel"):
             with gr.Group(elem_id=f"{tabname}_gallery_container"):
-                res.gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery", columns=4, preview=True, height=shared.opts.gallery_height or None, interactive=False, type="pil")
+                res.gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery", columns=4, preview=True, height=shared.opts.gallery_height or None)
 
             with gr.Row(elem_id=f"image_buttons_{tabname}", elem_classes="image-buttons"):
                 open_folder_button = ToolButton(folder_symbol, elem_id=f'{tabname}_open_folder', visible=not shared.cmd_opts.hide_ui_dir_config, tooltip="Open images output directory.")

modules/ui_components.py

@@ -1,12 +1,7 @@
-from functools import wraps
-
 import gradio as gr
-from modules import gradio_extensions  # noqa: F401
 
 
 class FormComponent:
-    webui_do_not_create_gradio_pyi_thank_you = True
-
     def get_expected_parent(self):
         return gr.components.Form
 
@@ -14,13 +9,12 @@ class FormComponent:
 gr.Dropdown.get_expected_parent = FormComponent.get_expected_parent
 
 
-class ToolButton(gr.Button, FormComponent):
+class ToolButton(FormComponent, gr.Button):
     """Small button with single emoji as text, fits inside gradio forms"""
 
-    @wraps(gr.Button.__init__)
-    def __init__(self, value="", *args, elem_classes=None, **kwargs):
-        elem_classes = elem_classes or []
-        super().__init__(*args, elem_classes=["tool", *elem_classes], value=value, **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"
@@ -28,9 +22,7 @@ class ToolButton(gr.Button, FormComponent):
 
 class ResizeHandleRow(gr.Row):
     """Same as gr.Row but fits inside gradio forms"""
-    webui_do_not_create_gradio_pyi_thank_you = True
 
-    @wraps(gr.Row.__init__)
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
 
@@ -40,92 +32,92 @@ class ResizeHandleRow(gr.Row):
         return "row"
 
 
-class FormRow(gr.Row, FormComponent):
+class FormRow(FormComponent, gr.Row):
     """Same as gr.Row but fits inside gradio forms"""
 
     def get_block_name(self):
         return "row"
 
 
-class FormColumn(gr.Column, FormComponent):
+class FormColumn(FormComponent, gr.Column):
     """Same as gr.Column but fits inside gradio forms"""
 
     def get_block_name(self):
         return "column"
 
 
-class FormGroup(gr.Group, FormComponent):
+class FormGroup(FormComponent, gr.Group):
     """Same as gr.Group but fits inside gradio forms"""
 
     def get_block_name(self):
         return "group"
 
 
-class FormHTML(gr.HTML, 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, 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, FormComponent):
+class DropdownMulti(FormComponent, gr.Dropdown):
     """Same as gr.Dropdown but always multiselect"""
-
-    @wraps(gr.Dropdown.__init__)
     def __init__(self, **kwargs):
-        kwargs['multiselect'] = True
-        super().__init__(**kwargs)
+        super().__init__(multiselect=True, **kwargs)
 
     def get_block_name(self):
         return "dropdown"
 
 
-class DropdownEditable(gr.Dropdown, FormComponent):
+class DropdownEditable(FormComponent, gr.Dropdown):
     """Same as gr.Dropdown but allows editing value"""
-
-    @wraps(gr.Dropdown.__init__)
     def __init__(self, **kwargs):
-        kwargs['allow_custom_value'] = True
-        super().__init__(**kwargs)
+        super().__init__(allow_custom_value=True, **kwargs)
 
     def get_block_name(self):
         return "dropdown"
 
 
-class InputAccordionImpl(gr.Checkbox):
+class InputAccordion(gr.Checkbox):
     """A gr.Accordion that can be used as an input - returns True if open, False if closed.
 
     Actually just a hidden checkbox, but creates an accordion that follows and is followed by the state of the checkbox.
     """
 
-    webui_do_not_create_gradio_pyi_thank_you = True
-
+    accordion_id_set = set()
     global_index = 0
 
-    @wraps(gr.Checkbox.__init__)
-    def __init__(self, value=None, setup=False, **kwargs):
-        if not setup:
-            super().__init__(value=value, **kwargs)
-            return
-
+    def __init__(self, value, **kwargs):
         self.accordion_id = kwargs.get('elem_id')
         if self.accordion_id is None:
-            self.accordion_id = f"input-accordion-{InputAccordionImpl.global_index}"
-            InputAccordionImpl.global_index += 1
+            self.accordion_id = f"input-accordion-{InputAccordion.global_index}"
+            InputAccordion.global_index += 1
+
+        if not InputAccordion.accordion_id_set:
+            from modules import script_callbacks
+            script_callbacks.on_script_unloaded(InputAccordion.reset)
+
+        if self.accordion_id in InputAccordion.accordion_id_set:
+            count = 1
+            while (unique_id := f'{self.accordion_id}-{count}') in InputAccordion.accordion_id_set:
+                count += 1
+            self.accordion_id = unique_id
+
+        InputAccordion.accordion_id_set.add(self.accordion_id)
 
         kwargs_checkbox = {
             **kwargs,
             "elem_id": f"{self.accordion_id}-checkbox",
             "visible": False,
         }
-        super().__init__(value=value, **kwargs_checkbox)
+        super().__init__(value, **kwargs_checkbox)
 
         self.change(fn=None, _js='function(checked){ inputAccordionChecked("' + self.accordion_id + '", checked); }', inputs=[self])
 
@@ -136,7 +128,6 @@ class InputAccordionImpl(gr.Checkbox):
             "elem_classes": ['input-accordion'],
             "open": value,
         }
-
         self.accordion = gr.Accordion(**kwargs_accordion)
 
     def extra(self):
@@ -165,6 +156,7 @@ class InputAccordionImpl(gr.Checkbox):
     def get_block_name(self):
         return "checkbox"
 
-
-def InputAccordion(value=None, **kwargs):
-    return InputAccordionImpl(value=value, setup=True, **kwargs)
+    @classmethod
+    def reset(cls):
+        cls.global_index = 0
+        cls.accordion_id_set.clear()

modules/ui_extensions.py

@@ -1,5 +1,6 @@
 import json
 import os
+from concurrent.futures import ThreadPoolExecutor
 import threading
 import time
 from datetime import datetime, timezone
@@ -106,18 +107,24 @@ def check_updates(id_task, disable_list):
     exts = [ext for ext in extensions.extensions if ext.remote is not None and ext.name not in disabled]
     shared.state.job_count = len(exts)
 
-    for ext in exts:
-        shared.state.textinfo = ext.name
+    lock = threading.Lock()
 
+    def _check_update(ext):
         try:
             ext.check_updates()
         except FileNotFoundError as e:
             if 'FETCH_HEAD' not in str(e):
                 raise
         except Exception:
-            errors.report(f"Error checking updates for {ext.name}", exc_info=True)
+            with lock:
+                errors.report(f"Error checking updates for {ext.name}", exc_info=True)
+        with lock:
+            shared.state.textinfo = ext.name
+            shared.state.nextjob()
 
-        shared.state.nextjob()
+    with ThreadPoolExecutor(max_workers=max(1, int(shared.opts.concurrent_git_fetch_limit))) as executor:
+        for ext in exts:
+            executor.submit(_check_update, ext)
 
     return extension_table(), ""
 
@@ -688,7 +695,7 @@ def create_ui():
 
                 config_save_button.click(fn=save_config_state, inputs=[config_save_name], outputs=[config_states_list, config_states_info])
 
-                dummy_component = gr.State()
+                dummy_component = gr.Label(visible=False)
                 config_restore_button.click(fn=restore_config_state, _js="config_state_confirm_restore", inputs=[dummy_component, config_states_list, config_restore_type], outputs=[config_states_info])
 
                 config_states_list.change(

modules/ui_extra_networks.py

@@ -177,10 +177,8 @@ def add_pages_to_demo(app):
     app.add_api_route("/sd_extra_networks/get-single-card", get_single_card, methods=["GET"])
 
 
-def quote_js(s):
-    s = s.replace('\\', '\\\\')
-    s = s.replace('"', '\\"')
-    return f'"{s}"'
+def quote_js(s: str):
+    return json.dumps(s, ensure_ascii=False)
 
 
 class ExtraNetworksPage:
@@ -750,11 +748,9 @@ def create_ui(interface: gr.Blocks, unrelated_tabs, tabname):
             elem_id = f"{tabname}_{page.extra_networks_tabname}_cards_html"
             page_elem = gr.HTML(page.create_html(tabname, empty=True), elem_id=elem_id)
             ui.pages.append(page_elem)
-
             editor = page.create_user_metadata_editor(ui, tabname)
             editor.create_ui()
             ui.user_metadata_editors.append(editor)
-
             related_tabs.append(tab)
 
     ui.button_save_preview = gr.Button('Save preview', elem_id=f"{tabname}_save_preview", visible=False)

modules/ui_loadsave.py

@@ -176,7 +176,7 @@ class UiLoadsave:
             if new_value == old_value:
                 continue
 
-            if old_value is None and new_value == '' or new_value == []:
+            if old_value is None and (new_value == '' or new_value == []):
                 continue
 
             yield path, old_value, new_value

modules/ui_postprocessing.py

@@ -5,14 +5,14 @@ from modules.ui_components import ResizeHandleRow
 
 
 def create_ui():
-    dummy_component = gr.Textbox(visible=False)
-    tab_index = gr.State(0)
+    dummy_component = gr.Label(visible=False)
+    tab_index = gr.Number(value=0, visible=False)
 
     with ResizeHandleRow(equal_height=False, variant='compact'):
         with gr.Column(variant='compact'):
             with gr.Tabs(elem_id="mode_extras"):
                 with gr.TabItem('Single Image', id="single_image", elem_id="extras_single_tab") as tab_single:
-                    extras_image = gr.ImageEditor(label="Source", interactive=True, type="pil", elem_id="extras_image", image_mode="RGBA")
+                    extras_image = gr.Image(label="Source", source="upload", interactive=True, type="pil", elem_id="extras_image", image_mode="RGBA")
 
                 with gr.TabItem('Batch Process', id="batch_process", elem_id="extras_batch_process_tab") as tab_batch:
                     image_batch = gr.Files(label="Batch Process", interactive=True, elem_id="extras_image_batch")

modules/ui_tempdir.py

@@ -4,7 +4,6 @@ from collections import namedtuple
 from pathlib import Path
 
 import gradio.components
-import gradio as gr
 
 from PIL import PngImagePlugin
 
@@ -14,35 +13,25 @@ from modules import shared
 Savedfile = namedtuple("Savedfile", ["name"])
 
 
-def register_tmp_file(gradio_app, filename):
-    if hasattr(gradio_app, 'temp_file_sets'):  # gradio 3.15
-        if hasattr(gr.utils, 'abspath'):  # gradio 4.19
-            filename = gr.utils.abspath(filename)
-        else:
-            filename = os.path.abspath(filename)
+def register_tmp_file(gradio, filename):
+    if hasattr(gradio, 'temp_file_sets'):  # gradio 3.15
+        gradio.temp_file_sets[0] = gradio.temp_file_sets[0] | {os.path.abspath(filename)}
 
-        gradio_app.temp_file_sets[0] = gradio_app.temp_file_sets[0] | {filename}
-
-    if hasattr(gradio_app, 'temp_dirs'):  # gradio 3.9
-        gradio_app.temp_dirs = gradio_app.temp_dirs | {os.path.abspath(os.path.dirname(filename))}
+    if hasattr(gradio, 'temp_dirs'):  # gradio 3.9
+        gradio.temp_dirs = gradio.temp_dirs | {os.path.abspath(os.path.dirname(filename))}
 
 
-def check_tmp_file(gradio_app, filename):
-    if hasattr(gradio_app, 'temp_file_sets'):
-        if hasattr(gr.utils, 'abspath'):  # gradio 4.19
-            filename = gr.utils.abspath(filename)
-        else:
-            filename = os.path.abspath(filename)
+def check_tmp_file(gradio, filename):
+    if hasattr(gradio, 'temp_file_sets'):
+        return any(filename in fileset for fileset in gradio.temp_file_sets)
 
-        return any(filename in fileset for fileset in gradio_app.temp_file_sets)
-
-    if hasattr(gradio_app, 'temp_dirs'):
-        return any(Path(temp_dir).resolve() in Path(filename).resolve().parents for temp_dir in gradio_app.temp_dirs)
+    if hasattr(gradio, 'temp_dirs'):
+        return any(Path(temp_dir).resolve() in Path(filename).resolve().parents for temp_dir in gradio.temp_dirs)
 
     return False
 
 
-def save_pil_to_file(pil_image, cache_dir=None, format="png"):
+def save_pil_to_file(self, pil_image, dir=None, format="png"):
     already_saved_as = getattr(pil_image, 'already_saved_as', None)
     if already_saved_as and os.path.isfile(already_saved_as):
         register_tmp_file(shared.demo, already_saved_as)
@@ -50,10 +39,9 @@ def save_pil_to_file(pil_image, cache_dir=None, format="png"):
         register_tmp_file(shared.demo, filename_with_mtime)
         return filename_with_mtime
 
-    if shared.opts.temp_dir:
+    if shared.opts.temp_dir != "":
         dir = shared.opts.temp_dir
     else:
-        dir = cache_dir
         os.makedirs(dir, exist_ok=True)
 
     use_metadata = False
@@ -68,96 +56,9 @@ def save_pil_to_file(pil_image, cache_dir=None, format="png"):
     return file_obj.name
 
 
-async def async_move_files_to_cache(data, block, postprocess=False, check_in_upload_folder=False, keep_in_cache=False):
-    """Move any files in `data` to cache and (optionally), adds URL prefixes (/file=...) needed to access the cached file.
-    Also handles the case where the file is on an external Gradio app (/proxy=...).
-
-    Runs after .postprocess() and before .preprocess().
-
-    Copied from gradio's processing_utils.py
-
-    Args:
-        data: The input or output data for a component. Can be a dictionary or a dataclass
-        block: The component whose data is being processed
-        postprocess: Whether its running from postprocessing
-        check_in_upload_folder: If True, instead of moving the file to cache, checks if the file is in already in cache (exception if not).
-        keep_in_cache: If True, the file will not be deleted from cache when the server is shut down.
-    """
-
-    from gradio import FileData
-    from gradio.data_classes import GradioRootModel
-    from gradio.data_classes import GradioModel
-    from gradio_client import utils as client_utils
-    from gradio.utils import get_upload_folder, is_in_or_equal, is_static_file
-
-    async def _move_to_cache(d: dict):
-        payload = FileData(**d)
-
-        # EDITED
-        payload.path = payload.path.rsplit('?', 1)[0]
-
-        # If the gradio app developer is returning a URL from
-        # postprocess, it means the component can display a URL
-        # without it being served from the gradio server
-        # This makes it so that the URL is not downloaded and speeds up event processing
-        if payload.url and postprocess and client_utils.is_http_url_like(payload.url):
-            payload.path = payload.url
-        elif is_static_file(payload):
-            pass
-        elif not block.proxy_url:
-            # EDITED
-            if check_tmp_file(shared.demo, payload.path):
-                temp_file_path = payload.path
-            else:
-                # If the file is on a remote server, do not move it to cache.
-                if check_in_upload_folder and not client_utils.is_http_url_like(
-                    payload.path
-                ):
-                    path = os.path.abspath(payload.path)
-                    if not is_in_or_equal(path, get_upload_folder()):
-                        raise ValueError(
-                            f"File {path} is not in the upload folder and cannot be accessed."
-                        )
-                if not payload.is_stream:
-                    temp_file_path = await block.async_move_resource_to_block_cache(
-                        payload.path
-                    )
-                    if temp_file_path is None:
-                        raise ValueError("Did not determine a file path for the resource.")
-                    payload.path = temp_file_path
-                    if keep_in_cache:
-                        block.keep_in_cache.add(payload.path)
-
-        url_prefix = "/stream/" if payload.is_stream else "/file="
-        if block.proxy_url:
-            proxy_url = block.proxy_url.rstrip("/")
-            url = f"/proxy={proxy_url}{url_prefix}{payload.path}"
-        elif client_utils.is_http_url_like(payload.path) or payload.path.startswith(
-            f"{url_prefix}"
-        ):
-            url = payload.path
-        else:
-            url = f"{url_prefix}{payload.path}"
-        payload.url = url
-
-        return payload.model_dump()
-
-    if isinstance(data, (GradioRootModel, GradioModel)):
-        data = data.model_dump()
-
-    return await client_utils.async_traverse(
-        data, _move_to_cache, client_utils.is_file_obj
-    )
-
-
 def install_ui_tempdir_override():
-    """
-    override save to file function so that it also writes PNG info.
-    override gradio4's move_files_to_cache function to prevent it from writing a copy into a temporary directory.
-    """
-
-    gradio.processing_utils.save_pil_to_cache = save_pil_to_file
-    gradio.processing_utils.async_move_files_to_cache = async_move_files_to_cache
+    """override save to file function so that it also writes PNG info"""
+    gradio.components.IOComponent.pil_to_temp_file = save_pil_to_file
 
 
 def on_tmpdir_changed():

modules/upscaler.py

@@ -93,13 +93,14 @@ class UpscalerData:
     scaler: Upscaler = None
     model: None
 
-    def __init__(self, name: str, path: str, upscaler: Upscaler = None, scale: int = 4, model=None):
+    def __init__(self, name: str, path: str, upscaler: Upscaler = None, scale: int = 4, model=None, sha256: str = None):
         self.name = name
         self.data_path = path
         self.local_data_path = path
         self.scaler = upscaler
         self.scale = scale
         self.model = model
+        self.sha256 = sha256
 
     def __repr__(self):
         return f"<UpscalerData name={self.name} path={self.data_path} scale={self.scale}>"

modules/util.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 import os
 import re
 
@@ -211,3 +212,80 @@ Requested path was: {path}
         subprocess.Popen(["explorer.exe", subprocess.check_output(["wslpath", "-w", path])])
     else:
         subprocess.Popen(["xdg-open", path])
+
+
+def load_file_from_url(
+    url: str,
+    *,
+    model_dir: str,
+    progress: bool = True,
+    file_name: str | None = None,
+    hash_prefix: str | None = None,
+    re_download: bool = False,
+) -> str:
+    """Download a file from `url` into `model_dir`, using the file present if possible.
+    Returns the path to the downloaded file.
+
+    file_name: if specified, it will be used as the filename, otherwise the filename will be extracted from the url.
+        file is downloaded to {file_name}.tmp then moved to the final location after download is complete.
+    hash_prefix: sha256 hex string, if provided, the hash of the downloaded file will be checked against this prefix.
+        if the hash does not match, the temporary file is deleted and a ValueError is raised.
+    re_download: forcibly re-download the file even if it already exists.
+    """
+    from urllib.parse import urlparse
+    import requests
+    try:
+        from tqdm import tqdm
+    except ImportError:
+        class tqdm:
+            def __init__(self, *args, **kwargs):
+                pass
+
+            def update(self, n=1, *args, **kwargs):
+                pass
+
+            def __enter__(self):
+                return self
+
+            def __exit__(self, exc_type, exc_val, exc_tb):
+                pass
+
+    if not file_name:
+        parts = urlparse(url)
+        file_name = os.path.basename(parts.path)
+
+    cached_file = os.path.abspath(os.path.join(model_dir, file_name))
+
+    if re_download or not os.path.exists(cached_file):
+        os.makedirs(model_dir, exist_ok=True)
+        temp_file = os.path.join(model_dir, f"{file_name}.tmp")
+        print(f'\nDownloading: "{url}" to {cached_file}')
+        response = requests.get(url, stream=True)
+        response.raise_for_status()
+        total_size = int(response.headers.get('content-length', 0))
+        with tqdm(total=total_size, unit='B', unit_scale=True, desc=file_name, disable=not progress) as progress_bar:
+            with open(temp_file, 'wb') as file:
+                for chunk in response.iter_content(chunk_size=1024):
+                    if chunk:
+                        file.write(chunk)
+                        progress_bar.update(len(chunk))
+
+        if hash_prefix and not compare_sha256(temp_file, hash_prefix):
+            print(f"Hash mismatch for {temp_file}. Deleting the temporary file.")
+            os.remove(temp_file)
+            raise ValueError(f"File hash does not match the expected hash prefix {hash_prefix}!")
+
+        os.rename(temp_file, cached_file)
+    return cached_file
+
+
+def compare_sha256(file_path: str, hash_prefix: str) -> bool:
+    """Check if the SHA256 hash of the file matches the given prefix."""
+    import hashlib
+    hash_sha256 = hashlib.sha256()
+    blksize = 1024 * 1024
+
+    with open(file_path, "rb") as f:
+        for chunk in iter(lambda: f.read(blksize), b""):
+            hash_sha256.update(chunk)
+    return hash_sha256.hexdigest().startswith(hash_prefix.strip().lower())

modules/uv_hook.py

@@ -0,0 +1,50 @@
+import sys
+import copy
+import shlex
+import subprocess
+from functools import wraps
+
+BAD_FLAGS = ("--prefer-binary", '-I', '--ignore-installed')
+
+
+def patch():
+    if hasattr(subprocess, "__original_run"):
+        return
+
+    print("using uv")
+    try:
+        subprocess.run(['uv', '-V'])
+    except FileNotFoundError:
+        subprocess.run([sys.executable, '-m', 'pip', 'install', 'uv'])
+
+    subprocess.__original_run = subprocess.run
+
+    @wraps(subprocess.__original_run)
+    def patched_run(*args, **kwargs):
+        _kwargs = copy.copy(kwargs)
+        if args:
+            command, *_args = args
+        else:
+            command, _args = _kwargs.pop("args", ""), ()
+
+        if isinstance(command, str):
+            command = shlex.split(command)
+        else:
+            command = [arg.strip() for arg in command]
+
+        if not isinstance(command, list) or "pip" not in command:
+            return subprocess.__original_run(*args, **kwargs)
+
+        cmd = command[command.index("pip") + 1:]
+
+        cmd = [arg for arg in cmd if arg not in BAD_FLAGS]
+
+        modified_command = ["uv", "pip", *cmd]
+
+        cmd_str = shlex.join([*modified_command, *_args])
+        result = subprocess.__original_run(cmd_str, **_kwargs)
+        if result.returncode != 0:
+            return subprocess.__original_run(*args, **kwargs)
+        return result
+
+    subprocess.run = patched_run

requirements.txt

@@ -8,7 +8,7 @@ diskcache
 einops
 facexlib
 fastapi>=0.90.1
-gradio==4.38.1
+gradio==3.41.2
 inflection
 jsonmerge
 kornia

requirements_versions.txt

@@ -7,8 +7,8 @@ clean-fid==0.1.35
 diskcache==5.6.3
 einops==0.4.1
 facexlib==0.3.0
-fastapi==0.104.1
-gradio==4.38.1
+fastapi==0.94.0
+gradio==3.41.2
 httpcore==0.15
 inflection==0.5.1
 jsonmerge==1.8.0
@@ -22,7 +22,7 @@ protobuf==3.20.0
 psutil==5.9.5
 pytorch_lightning==1.9.4
 resize-right==0.0.2
-safetensors==0.4.2
+safetensors==0.4.5
 scikit-image==0.21.0
 spandrel==0.3.4
 spandrel-extra-arches==0.1.1

script.js

@@ -182,7 +182,7 @@ document.addEventListener('keydown', function(e) {
         const lightboxModal = document.querySelector('#lightboxModal');
         if (!globalPopup || globalPopup.style.display === 'none') {
             if (document.activeElement === lightboxModal) return;
-            if (interruptButton.style.display === 'block') {
+            if (interruptButton?.style.display === 'block') {
                 interruptButton.click();
                 e.preventDefault();
             }

scripts/postprocessing_codeformer.py

@@ -12,8 +12,8 @@ class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing
     def ui(self):
         with ui_components.InputAccordion(False, label="CodeFormer") as enable:
             with gr.Row():
-                codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_codeformer_visibility")
-                codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id="extras_codeformer_weight")
+                codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id=self.elem_id_suffix("extras_codeformer_visibility"))
+                codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id=self.elem_id_suffix("extras_codeformer_weight"))
 
         return {
             "enable": enable,
@@ -29,6 +29,10 @@ class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing
         res = Image.fromarray(restored_img)
 
         if codeformer_visibility < 1.0:
+            if pp.image.size != res.size:
+                res = res.resize(pp.image.size)
+            if pp.image.mode != res.mode:
+                res = res.convert(pp.image.mode)
             res = Image.blend(pp.image, res, codeformer_visibility)
 
         pp.image = res

scripts/postprocessing_gfpgan.py

@@ -11,7 +11,7 @@ class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostprocessing):
 
     def ui(self):
         with ui_components.InputAccordion(False, label="GFPGAN") as enable:
-            gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_gfpgan_visibility")
+            gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id=self.elem_id_suffix("extras_gfpgan_visibility"))
 
         return {
             "enable": enable,
@@ -26,6 +26,10 @@ class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostprocessing):
         res = Image.fromarray(restored_img)
 
         if gfpgan_visibility < 1.0:
+            if pp.image.size != res.size:
+                res = res.resize(pp.image.size)
+            if pp.image.mode != res.mode:
+                res = res.convert(pp.image.mode)
             res = Image.blend(pp.image, res, gfpgan_visibility)
 
         pp.image = res

scripts/postprocessing_upscale.py

@@ -30,31 +30,31 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
     def ui(self):
         selected_tab = gr.Number(value=0, visible=False)
 
-        with InputAccordion(True, label="Upscale", elem_id="extras_upscale") as upscale_enabled:
+        with InputAccordion(True, label="Upscale", elem_id=self.elem_id_suffix("extras_upscale")) as upscale_enabled:
             with FormRow():
-                extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
+                extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id=self.elem_id_suffix("extras_upscaler_1"), choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
 
             with FormRow():
-                extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
-                extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")
+                extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id=self.elem_id_suffix("extras_upscaler_2"), choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
+                extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id=self.elem_id_suffix("extras_upscaler_2_visibility"))
 
             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:
+                with gr.Tabs(elem_id=self.elem_id_suffix("extras_resize_mode")):
+                    with gr.TabItem('Scale by', elem_id=self.elem_id_suffix("extras_scale_by_tab")) as tab_scale_by:
                         with gr.Row():
                             with gr.Column(scale=4):
-                                upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
+                                upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id=self.elem_id_suffix("extras_upscaling_resize"))
                             with gr.Column(scale=1, min_width=160):
-                                max_side_length = gr.Number(label="Max side length", value=0, elem_id="extras_upscale_max_side_length", tooltip="If any of two sides of the image ends up larger than specified, will downscale it to fit. 0 = no limit.", min_width=160, step=8, minimum=0)
+                                max_side_length = gr.Number(label="Max side length", value=0, elem_id=self.elem_id_suffix("extras_upscale_max_side_length"), tooltip="If any of two sides of the image ends up larger than specified, will downscale it to fit. 0 = no limit.", min_width=160, step=8, minimum=0)
 
-                    with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
+                    with gr.TabItem('Scale to', elem_id=self.elem_id_suffix("extras_scale_to_tab")) as tab_scale_to:
                         with FormRow():
-                            with gr.Column(elem_id="upscaling_column_size", scale=4):
-                                upscaling_resize_w = gr.Slider(minimum=64, maximum=8192, step=8, label="Width", value=512, elem_id="extras_upscaling_resize_w")
-                                upscaling_resize_h = gr.Slider(minimum=64, maximum=8192, step=8, label="Height", value=512, elem_id="extras_upscaling_resize_h")
-                            with gr.Column(elem_id="upscaling_dimensions_row", scale=1, elem_classes="dimensions-tools"):
-                                upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn", tooltip="Switch width/height")
-                                upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
+                            with gr.Column(elem_id=self.elem_id_suffix("upscaling_column_size"), scale=4):
+                                upscaling_resize_w = gr.Slider(minimum=64, maximum=8192, step=8, label="Width", value=512, elem_id=self.elem_id_suffix("extras_upscaling_resize_w"))
+                                upscaling_resize_h = gr.Slider(minimum=64, maximum=8192, step=8, label="Height", value=512, elem_id=self.elem_id_suffix("extras_upscaling_resize_h"))
+                            with gr.Column(elem_id=self.elem_id_suffix("upscaling_dimensions_row"), scale=1, elem_classes="dimensions-tools"):
+                                upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id=self.elem_id_suffix("upscaling_res_switch_btn"), tooltip="Switch width/height")
+                                upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id=self.elem_id_suffix("extras_upscaling_crop"))
 
         def on_selected_upscale_method(upscale_method):
             if not shared.opts.set_scale_by_when_changing_upscaler:
@@ -169,6 +169,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
 class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale):
     name = "Simple Upscale"
     order = 900
+    main_ui_only = True
 
     def ui(self):
         with FormRow():

scripts/xyz_grid.py

@@ -20,7 +20,7 @@ import modules.sd_models
 import modules.sd_vae
 import re
 
-from modules.ui_components import ToolButton
+from modules.ui_components import ToolButton, InputAccordion
 
 fill_values_symbol = "\U0001f4d2"  # 📒
 
@@ -259,6 +259,7 @@ axis_options = [
     AxisOption("Schedule min sigma", float, apply_override("sigma_min")),
     AxisOption("Schedule max sigma", float, apply_override("sigma_max")),
     AxisOption("Schedule rho", float, apply_override("rho")),
+    AxisOption("Skip Early CFG", float, apply_override('skip_early_cond')),
     AxisOption("Beta schedule alpha", float, apply_override("beta_dist_alpha")),
     AxisOption("Beta schedule beta", float, apply_override("beta_dist_beta")),
     AxisOption("Eta", float, apply_field("eta")),
@@ -284,7 +285,7 @@ axis_options = [
 ]
 
 
-def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend, include_lone_images, include_sub_grids, first_axes_processed, second_axes_processed, margin_size):
+def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend, include_lone_images, include_sub_grids, first_axes_processed, second_axes_processed, margin_size, draw_grid):
     hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
     ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
     title_texts = [[images.GridAnnotation(z)] for z in z_labels]
@@ -369,29 +370,30 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
         print("Unexpected error: draw_xyz_grid failed to return even a single processed image")
         return Processed(p, [])
 
-    z_count = len(zs)
+    if draw_grid:
+        z_count = len(zs)
 
-    for i in range(z_count):
-        start_index = (i * len(xs) * len(ys)) + i
-        end_index = start_index + len(xs) * len(ys)
-        grid = images.image_grid(processed_result.images[start_index:end_index], rows=len(ys))
+        for i in range(z_count):
+            start_index = (i * len(xs) * len(ys)) + i
+            end_index = start_index + len(xs) * len(ys)
+            grid = images.image_grid(processed_result.images[start_index:end_index], rows=len(ys))
+            if draw_legend:
+                grid_max_w, grid_max_h = map(max, zip(*(img.size for img in processed_result.images[start_index:end_index])))
+                grid = images.draw_grid_annotations(grid, grid_max_w, grid_max_h, hor_texts, ver_texts, margin_size)
+            processed_result.images.insert(i, grid)
+            processed_result.all_prompts.insert(i, processed_result.all_prompts[start_index])
+            processed_result.all_seeds.insert(i, processed_result.all_seeds[start_index])
+            processed_result.infotexts.insert(i, processed_result.infotexts[start_index])
+
+        z_grid = images.image_grid(processed_result.images[:z_count], rows=1)
+        z_sub_grid_max_w, z_sub_grid_max_h = map(max, zip(*(img.size for img in processed_result.images[:z_count])))
         if draw_legend:
-            grid_max_w, grid_max_h = map(max, zip(*(img.size for img in processed_result.images[start_index:end_index])))
-            grid = images.draw_grid_annotations(grid, grid_max_w, grid_max_h, hor_texts, ver_texts, margin_size)
-        processed_result.images.insert(i, grid)
-        processed_result.all_prompts.insert(i, processed_result.all_prompts[start_index])
-        processed_result.all_seeds.insert(i, processed_result.all_seeds[start_index])
-        processed_result.infotexts.insert(i, processed_result.infotexts[start_index])
-
-    z_grid = images.image_grid(processed_result.images[:z_count], rows=1)
-    z_sub_grid_max_w, z_sub_grid_max_h = map(max, zip(*(img.size for img in processed_result.images[:z_count])))
-    if draw_legend:
-        z_grid = images.draw_grid_annotations(z_grid, z_sub_grid_max_w, z_sub_grid_max_h, title_texts, [[images.GridAnnotation()]])
-    processed_result.images.insert(0, z_grid)
-    # TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
-    # processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
-    # processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
-    processed_result.infotexts.insert(0, processed_result.infotexts[0])
+            z_grid = images.draw_grid_annotations(z_grid, z_sub_grid_max_w, z_sub_grid_max_h, title_texts, [[images.GridAnnotation()]])
+        processed_result.images.insert(0, z_grid)
+        # TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
+        # processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
+        # processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
+        processed_result.infotexts.insert(0, processed_result.infotexts[0])
 
     return processed_result
 
@@ -441,7 +443,6 @@ class Script(scripts.Script):
 
         with gr.Row(variant="compact", elem_id="axis_options"):
             with gr.Column():
-                draw_legend = gr.Checkbox(label='Draw legend', value=True, elem_id=self.elem_id("draw_legend"))
                 no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False, elem_id=self.elem_id("no_fixed_seeds"))
                 with gr.Row():
                     vary_seeds_x = gr.Checkbox(label='Vary seeds for X', value=False, min_width=80, elem_id=self.elem_id("vary_seeds_x"), tooltip="Use different seeds for images along X axis.")
@@ -449,9 +450,12 @@ class Script(scripts.Script):
                     vary_seeds_z = gr.Checkbox(label='Vary seeds for Z', value=False, min_width=80, elem_id=self.elem_id("vary_seeds_z"), tooltip="Use different seeds for images along Z axis.")
             with gr.Column():
                 include_lone_images = gr.Checkbox(label='Include Sub Images', value=False, elem_id=self.elem_id("include_lone_images"))
-                include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
                 csv_mode = gr.Checkbox(label='Use text inputs instead of dropdowns', value=False, elem_id=self.elem_id("csv_mode"))
-            with gr.Column():
+
+        with InputAccordion(True, label='Draw grid', elem_id=self.elem_id('draw_grid')) as draw_grid:
+            with gr.Row():
+                include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
+                draw_legend = gr.Checkbox(label='Draw legend', value=True, elem_id=self.elem_id("draw_legend"))
                 margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
 
         with gr.Row(variant="compact", elem_id="swap_axes"):
@@ -533,9 +537,9 @@ class Script(scripts.Script):
             (z_values_dropdown, lambda params: get_dropdown_update_from_params("Z", params)),
         )
 
-        return [x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size, csv_mode]
+        return [x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size, csv_mode, draw_grid]
 
-    def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size, csv_mode):
+    def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size, csv_mode, draw_grid):
         x_type, y_type, z_type = x_type or 0, y_type or 0, z_type or 0  # if axle type is None set to 0
 
         if not no_fixed_seeds:
@@ -780,7 +784,8 @@ class Script(scripts.Script):
                 include_sub_grids=include_sub_grids,
                 first_axes_processed=first_axes_processed,
                 second_axes_processed=second_axes_processed,
-                margin_size=margin_size
+                margin_size=margin_size,
+                draw_grid=draw_grid,
             )
 
         if not processed.images:
@@ -789,14 +794,15 @@ 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 draw_grid:
+            # 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]
+            processed.images = processed.images[:z_count + 1] if draw_grid else []
 
-        if opts.grid_save:
+        if draw_grid and opts.grid_save:
             # Auto-save main and sub-grids:
             grid_count = z_count + 1 if z_count > 1 else 1
             for g in range(grid_count):
@@ -806,7 +812,7 @@ class Script(scripts.Script):
                 if not include_sub_grids:  # if not include_sub_grids then skip saving after the first grid
                     break
 
-        if not include_sub_grids:
+        if draw_grid and not include_sub_grids:
             # Done with sub-grids, drop all related information:
             for _ in range(z_count):
                 del processed.images[1]

style.css

@@ -2,6 +2,14 @@
 
 @import url('webui-assets/css/sourcesanspro.css');
 
+
+/* temporary fix to hide gradio crop tool until it's fixed https://github.com/gradio-app/gradio/issues/3810 */
+
+div.gradio-image button[aria-label="Edit"] {
+    display: none;
+}
+
+
 /* general gradio fixes */
 
 :root, .dark{
@@ -129,10 +137,6 @@ div.gradio-html.min{
     background: var(--input-background-fill);
 }
 
-.gradio-gallery > button.preview{
-    width: 100%;
-}
-
 .gradio-container .prose a, .gradio-container .prose a:visited{
     color: unset;
     text-decoration: none;
@@ -143,15 +147,6 @@ a{
     cursor: pointer;
 }
 
-.upload-container {
-    width: 100%;
-    max-width: 100%;
-}
-
-.layer-wrap > ul {
-    background: var(--background-fill-primary) !important;
-}
-
 /* gradio 3.39 puts a lot of overflow: hidden all over the place for an unknown reason. */
 div.gradio-container, .block.gradio-textbox, div.gradio-group, div.gradio-dropdown{
     overflow: visible !important;
@@ -403,7 +398,7 @@ div#extras_scale_to_tab div.form{
     z-index: 5;
 }
 
-.image-buttons{
+.image-buttons > .form{
     justify-content: center;
 }
 
@@ -485,8 +480,10 @@ div.toprow-compact-tools{
 }
 
 #settings_result{
-    height: 1.4em;
+    min-height: 1.4em;
     margin: 0 1.2em;
+    max-height: calc(var(--text-md) * var(--line-sm) * 5);
+    overflow-y: auto;
 }
 
 table.popup-table{
@@ -605,6 +602,7 @@ table.popup-table .link{
     background: var(--background-fill-primary);
     width: 100%;
     height: 100%;
+    pointer-events: none;
 }
 
 .livePreview img{
@@ -1103,9 +1101,9 @@ footer {
     height:100%;
 }
 
-.edit-user-metadata {
+div.block.gradio-box.edit-user-metadata {
     width: 56em;
-    background: var(--body-background-fill) !important;
+    background: var(--body-background-fill);
     padding: 2em !important;
 }
 
@@ -1139,12 +1137,16 @@ footer {
     margin-top: 1.5em;
 }
 
-.popup-dialog {
+div.block.gradio-box.popup-dialog, .popup-dialog {
     width: 56em;
-    background: var(--body-background-fill) !important;
+    background: var(--body-background-fill);
     padding: 2em !important;
 }
 
+div.block.gradio-box.popup-dialog > div:last-child, .popup-dialog > div:last-child{
+    margin-top: 1em;
+}
+
 div.block.input-accordion{
 
 }

webui.bat

@@ -4,7 +4,16 @@ if exist webui.settings.bat (
     call webui.settings.bat
 )
 
-if not defined PYTHON (set PYTHON=python)
+if not defined PYTHON (
+  for /f "delims=" %%A in ('where python ^| findstr /n . ^| findstr ^^1:') do (
+    if /i "%%~xA" == ".exe" (
+      set PYTHON=python
+    ) else (
+      set PYTHON=call python
+    )
+  )
+)
+
 if defined GIT (set "GIT_PYTHON_GIT_EXECUTABLE=%GIT%")
 if not defined VENV_DIR (set "VENV_DIR=%~dp0%venv")
 

webui.py

@@ -45,6 +45,44 @@ def api_only():
     )
 
 
+def warning_if_invalid_install_dir():
+    """
+    Shows a warning if the webui is installed under a path that contains a leading dot in any of its parent directories.
+
+    Gradio '/file=' route will block access to files that have a leading dot in the path segments.
+    We use this route to serve files such as JavaScript and CSS to the webpage,
+    if those files are blocked, the webpage will not function properly.
+    See https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/13292
+
+    This is a security feature was added to Gradio 3.32.0 and is removed in later versions,
+    this function replicates Gradio file access blocking logic.
+
+    This check should be removed when it's no longer applicable.
+    """
+    from packaging.version import parse
+    from pathlib import Path
+    import gradio
+
+    if parse('3.32.0') <= parse(gradio.__version__) < parse('4'):
+
+        def abspath(path):
+            """modified from Gradio 3.41.2 gradio.utils.abspath()"""
+            if path.is_absolute():
+                return path
+            is_symlink = path.is_symlink() or any(parent.is_symlink() for parent in path.parents)
+            return Path.cwd() / path if (is_symlink or path == path.resolve()) else path.resolve()
+
+        webui_root = Path(__file__).parent
+        if any(part.startswith(".") for part in abspath(webui_root).parts):
+            print(f'''{"!"*25} Warning {"!"*25}
+WebUI is installed in a directory that has a leading dot (.) in one of its parent directories.
+This will prevent WebUI from functioning properly.
+Please move the installation to a different directory.
+Current path: "{webui_root}"
+For more information see: https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/13292
+{"!"*25} Warning {"!"*25}''')
+
+
 def webui():
     from modules.shared_cmd_options import cmd_opts
 
@@ -53,6 +91,8 @@ def webui():
 
     from modules import shared, ui_tempdir, script_callbacks, ui, progress, ui_extra_networks
 
+    warning_if_invalid_install_dir()
+
     while 1:
         if shared.opts.clean_temp_dir_at_start:
             ui_tempdir.cleanup_tmpdr()

webui.sh

@@ -127,7 +127,7 @@ then
 fi
 
 # Check prerequisites
-gpu_info=$(lspci 2>/dev/null | grep -E "VGA|Display")
+gpu_info=$(lspci 2>/dev/null | grep -E "VGA|Display|CMP")
 case "$gpu_info" in
     *"Navi 1"*)
         export HSA_OVERRIDE_GFX_VERSION=10.3.0