diff options
38 files changed, 434 insertions, 301 deletions
diff --git a/.github/workflows/on_pull_request.yaml b/.github/workflows/on_pull_request.yaml index 7b7219fd..8ebf5918 100644 --- a/.github/workflows/on_pull_request.yaml +++ b/.github/workflows/on_pull_request.yaml @@ -18,7 +18,7 @@ jobs: # not to have GHA download an (at the time of writing) 4 GB cache # of PyTorch and other dependencies. - name: Install Ruff - run: pip install ruff==0.0.265 + run: pip install ruff==0.0.272 - name: Run Ruff run: ruff . lint-js: diff --git a/.github/workflows/run_tests.yaml b/.github/workflows/run_tests.yaml index 226cf759..96546011 100644 --- a/.github/workflows/run_tests.yaml +++ b/.github/workflows/run_tests.yaml @@ -50,7 +50,7 @@ jobs: python -m pytest -vv --junitxml=test/results.xml --cov . --cov-report=xml --verify-base-url test - name: Kill test server if: always() - run: curl -vv -XPOST http://127.0.0.1:7860/_stop && sleep 10 + run: curl -vv -XPOST http://127.0.0.1:7860/sdapi/v1/server-stop && sleep 10 - name: Show coverage run: | python -m coverage combine .coverage* diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index dbd6d331..bd78dece 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -1,7 +1,6 @@ import os -from basicsr.utils.download_util import load_file_from_url - +from modules.modelloader import load_file_from_url from modules.upscaler import Upscaler, UpscalerData from ldsr_model_arch import LDSR from modules import shared, script_callbacks, errors @@ -43,20 +42,17 @@ class UpscalerLDSR(Upscaler): if local_safetensors_path is not None and os.path.exists(local_safetensors_path): model = local_safetensors_path else: - model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="model.ckpt", progress=True) + model = local_ckpt_path or load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name="model.ckpt") - yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml", progress=True) + yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml") - try: - return LDSR(model, yaml) - except Exception: - errors.report("Error importing LDSR", exc_info=True) - return None + return LDSR(model, yaml) def do_upscale(self, img, path): - ldsr = self.load_model(path) - if ldsr is None: - print("NO LDSR!") + try: + ldsr = self.load_model(path) + except Exception: + errors.report(f"Failed loading LDSR model {path}", exc_info=True) return img ddim_steps = shared.opts.ldsr_steps return ldsr.super_resolution(img, ddim_steps, self.scale) diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 85b4505f..ffef26b2 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -1,4 +1,3 @@ -import os.path import sys import PIL.Image @@ -6,12 +5,11 @@ import numpy as np import torch from tqdm import tqdm -from basicsr.utils.download_util import load_file_from_url - import modules.upscaler from modules import devices, modelloader, script_callbacks, errors -from scunet_model_arch import SCUNet as net +from scunet_model_arch import SCUNet +from modules.modelloader import load_file_from_url from modules.shared import opts @@ -28,7 +26,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): scalers = [] add_model2 = True for file in model_paths: - if "http" in file: + if file.startswith("http"): name = self.model_name else: name = modelloader.friendly_name(file) @@ -89,9 +87,10 @@ class UpscalerScuNET(modules.upscaler.Upscaler): torch.cuda.empty_cache() - model = self.load_model(selected_file) - if model is None: - print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr) + try: + model = self.load_model(selected_file) + except Exception as e: + print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr) return img device = devices.get_device_for('scunet') @@ -119,15 +118,12 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def load_model(self, path: str): device = devices.get_device_for('scunet') - if "http" in path: - filename = load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="%s.pth" % self.name, progress=True) + if path.startswith("http"): + # TODO: this doesn't use `path` at all? + filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth") else: filename = path - if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None: - print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr) - return None - - model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) + model = SCUNet(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) model.load_state_dict(torch.load(filename), strict=True) model.eval() for _, v in model.named_parameters(): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 1c7bf325..c6bc53a8 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -1,17 +1,17 @@ -import os +import sys import numpy as np import torch from PIL import Image -from basicsr.utils.download_util import load_file_from_url from tqdm import tqdm from modules import modelloader, devices, script_callbacks, shared from modules.shared import opts, state -from swinir_model_arch import SwinIR as net -from swinir_model_arch_v2 import Swin2SR as net2 +from swinir_model_arch import SwinIR +from swinir_model_arch_v2 import Swin2SR from modules.upscaler import Upscaler, UpscalerData +SWINIR_MODEL_URL = "https://github.com/JingyunLiang/SwinIR/releases/download/v0.0/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth" device_swinir = devices.get_device_for('swinir') @@ -19,16 +19,14 @@ device_swinir = devices.get_device_for('swinir') class UpscalerSwinIR(Upscaler): def __init__(self, dirname): self.name = "SwinIR" - self.model_url = "https://github.com/JingyunLiang/SwinIR/releases/download/v0.0" \ - "/003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR" \ - "-L_x4_GAN.pth " + self.model_url = SWINIR_MODEL_URL self.model_name = "SwinIR 4x" self.user_path = dirname super().__init__() scalers = [] model_files = self.find_models(ext_filter=[".pt", ".pth"]) for model in model_files: - if "http" in model: + if model.startswith("http"): name = self.model_name else: name = modelloader.friendly_name(model) @@ -37,8 +35,10 @@ class UpscalerSwinIR(Upscaler): self.scalers = scalers def do_upscale(self, img, model_file): - model = self.load_model(model_file) - if model is None: + try: + model = self.load_model(model_file) + except Exception as e: + print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr) return img model = model.to(device_swinir, dtype=devices.dtype) img = upscale(img, model) @@ -49,30 +49,31 @@ class UpscalerSwinIR(Upscaler): return img def load_model(self, path, scale=4): - if "http" in path: - dl_name = "%s%s" % (self.model_name.replace(" ", "_"), ".pth") - filename = load_file_from_url(url=path, model_dir=self.model_download_path, file_name=dl_name, progress=True) + if path.startswith("http"): + filename = modelloader.load_file_from_url( + url=path, + model_dir=self.model_download_path, + file_name=f"{self.model_name.replace(' ', '_')}.pth", + ) else: filename = path - if filename is None or not os.path.exists(filename): - return None if filename.endswith(".v2.pth"): - model = net2( - upscale=scale, - in_chans=3, - img_size=64, - window_size=8, - img_range=1.0, - depths=[6, 6, 6, 6, 6, 6], - embed_dim=180, - num_heads=[6, 6, 6, 6, 6, 6], - mlp_ratio=2, - upsampler="nearest+conv", - resi_connection="1conv", + model = Swin2SR( + upscale=scale, + in_chans=3, + img_size=64, + window_size=8, + img_range=1.0, + depths=[6, 6, 6, 6, 6, 6], + embed_dim=180, + num_heads=[6, 6, 6, 6, 6, 6], + mlp_ratio=2, + upsampler="nearest+conv", + resi_connection="1conv", ) params = None else: - model = net( + model = SwinIR( upscale=scale, in_chans=3, img_size=64, diff --git a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js index 4ecb3d36..5ebd2073 100644 --- a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js +++ b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js @@ -4,12 +4,12 @@ onUiLoaded(async() => { inpaint: "#img2maskimg", inpaintSketch: "#inpaint_sketch", rangeGroup: "#img2img_column_size", - sketch: "#img2img_sketch", + sketch: "#img2img_sketch" }; const tabNameToElementId = { "Inpaint sketch": elementIDs.inpaintSketch, "Inpaint": elementIDs.inpaint, - "Sketch": elementIDs.sketch, + "Sketch": elementIDs.sketch }; // Helper functions @@ -42,43 +42,110 @@ onUiLoaded(async() => { } } - // Check is hotkey valid - function isSingleLetter(value) { + // Function for defining the "Ctrl", "Shift" and "Alt" keys + function isModifierKey(event, key) { + switch (key) { + case "Ctrl": + return event.ctrlKey; + case "Shift": + return event.shiftKey; + case "Alt": + return event.altKey; + default: + return false; + } + } + + // Check if hotkey is valid + function isValidHotkey(value) { + const specialKeys = ["Ctrl", "Alt", "Shift", "Disable"]; return ( - typeof value === "string" && value.length === 1 && /[a-z]/i.test(value) + (typeof value === "string" && + value.length === 1 && + /[a-z]/i.test(value)) || + specialKeys.includes(value) ); } - // Create hotkeyConfig from opts + // Normalize hotkey + function normalizeHotkey(hotkey) { + return hotkey.length === 1 ? "Key" + hotkey.toUpperCase() : hotkey; + } + + // Format hotkey for display + function formatHotkeyForDisplay(hotkey) { + return hotkey.startsWith("Key") ? hotkey.slice(3) : hotkey; + } + + // Create hotkey configuration with the provided options function createHotkeyConfig(defaultHotkeysConfig, hotkeysConfigOpts) { - const result = {}; - const usedKeys = new Set(); + const result = {}; // Resulting hotkey configuration + const usedKeys = new Set(); // Set of used hotkeys + // Iterate through defaultHotkeysConfig keys for (const key in defaultHotkeysConfig) { - if (typeof hotkeysConfigOpts[key] === "boolean") { - result[key] = hotkeysConfigOpts[key]; - continue; - } + const userValue = hotkeysConfigOpts[key]; // User-provided hotkey value + const defaultValue = defaultHotkeysConfig[key]; // Default hotkey value + + // Apply appropriate value for undefined, boolean, or object userValue if ( - hotkeysConfigOpts[key] && - isSingleLetter(hotkeysConfigOpts[key]) && - !usedKeys.has(hotkeysConfigOpts[key].toUpperCase()) + userValue === undefined || + typeof userValue === "boolean" || + typeof userValue === "object" || + userValue === "disable" ) { - // If the property passed the test and has not yet been used, add 'Key' before it and save it - result[key] = "Key" + hotkeysConfigOpts[key].toUpperCase(); - usedKeys.add(hotkeysConfigOpts[key].toUpperCase()); + result[key] = + userValue === undefined ? defaultValue : userValue; + } else if (isValidHotkey(userValue)) { + const normalizedUserValue = normalizeHotkey(userValue); + + // Check for conflicting hotkeys + if (!usedKeys.has(normalizedUserValue)) { + usedKeys.add(normalizedUserValue); + result[key] = normalizedUserValue; + } else { + console.error( + `Hotkey: ${formatHotkeyForDisplay( + userValue + )} for ${key} is repeated and conflicts with another hotkey. The default hotkey is used: ${formatHotkeyForDisplay( + defaultValue + )}` + ); + result[key] = defaultValue; + } } else { - // If the property does not pass the test or has already been used, we keep the default value console.error( - `Hotkey: ${hotkeysConfigOpts[key]} for ${key} is repeated and conflicts with another hotkey or is not 1 letter. The default hotkey is used: ${defaultHotkeysConfig[key][3]}` + `Hotkey: ${formatHotkeyForDisplay( + userValue + )} for ${key} is not valid. The default hotkey is used: ${formatHotkeyForDisplay( + defaultValue + )}` ); - result[key] = defaultHotkeysConfig[key]; + result[key] = defaultValue; } } return result; } + // Disables functions in the config object based on the provided list of function names + function disableFunctions(config, disabledFunctions) { + // Bind the hasOwnProperty method to the functionMap object to avoid errors + const hasOwnProperty = + Object.prototype.hasOwnProperty.bind(functionMap); + + // Loop through the disabledFunctions array and disable the corresponding functions in the config object + disabledFunctions.forEach(funcName => { + if (hasOwnProperty(funcName)) { + const key = functionMap[funcName]; + config[key] = "disable"; + } + }); + + // Return the updated config object + 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 @@ -100,7 +167,9 @@ onUiLoaded(async() => { imageARPreview.style.transform = ""; if (parseFloat(mainTab.style.width) > 865) { const transformString = mainTab.style.transform; - const scaleMatch = transformString.match(/scale\(([-+]?[0-9]*\.?[0-9]+)\)/); + const scaleMatch = transformString.match( + /scale\(([-+]?[0-9]*\.?[0-9]+)\)/ + ); let zoom = 1; // default zoom if (scaleMatch && scaleMatch[1]) { @@ -124,31 +193,52 @@ onUiLoaded(async() => { // Default config const defaultHotkeysConfig = { + canvas_hotkey_zoom: "Alt", + canvas_hotkey_adjust: "Ctrl", canvas_hotkey_reset: "KeyR", canvas_hotkey_fullscreen: "KeyS", canvas_hotkey_move: "KeyF", canvas_hotkey_overlap: "KeyO", - canvas_show_tooltip: true, - canvas_swap_controls: false + canvas_disabled_functions: [], + canvas_show_tooltip: true }; - // swap the actions for ctr + wheel and shift + wheel - const hotkeysConfig = createHotkeyConfig( + + const functionMap = { + "Zoom": "canvas_hotkey_zoom", + "Adjust brush size": "canvas_hotkey_adjust", + "Moving canvas": "canvas_hotkey_move", + "Fullscreen": "canvas_hotkey_fullscreen", + "Reset Zoom": "canvas_hotkey_reset", + "Overlap": "canvas_hotkey_overlap" + }; + + // Loading the configuration from opts + const preHotkeysConfig = createHotkeyConfig( defaultHotkeysConfig, hotkeysConfigOpts ); + // Disable functions that are not needed by the user + const hotkeysConfig = disableFunctions( + preHotkeysConfig, + preHotkeysConfig.canvas_disabled_functions + ); + let isMoving = false; let mouseX, mouseY; let activeElement; - const elements = Object.fromEntries(Object.keys(elementIDs).map((id) => [ - id, - gradioApp().querySelector(elementIDs[id]), - ])); + const elements = Object.fromEntries( + Object.keys(elementIDs).map(id => [ + id, + gradioApp().querySelector(elementIDs[id]) + ]) + ); 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")) : + const rangeInputs = elements.rangeGroup ? + Array.from(elements.rangeGroup.querySelectorAll("input")) : [ gradioApp().querySelector("#img2img_width input[type='range']"), gradioApp().querySelector("#img2img_height input[type='range']") @@ -180,38 +270,56 @@ onUiLoaded(async() => { const toolTipElemnt = targetElement.querySelector(".image-container"); const tooltip = document.createElement("div"); - tooltip.className = "tooltip"; + tooltip.className = "canvas-tooltip"; // Creating an item of information const info = document.createElement("i"); - info.className = "tooltip-info"; + info.className = "canvas-tooltip-info"; info.textContent = ""; // Create a container for the contents of the tooltip const tooltipContent = document.createElement("div"); - tooltipContent.className = "tooltip-content"; - - // Add info about hotkeys - const zoomKey = hotkeysConfig.canvas_swap_controls ? "Ctrl" : "Shift"; - const adjustKey = hotkeysConfig.canvas_swap_controls ? "Shift" : "Ctrl"; + tooltipContent.className = "canvas-tooltip-content"; - const hotkeys = [ - {key: `${zoomKey} + wheel`, action: "Zoom canvas"}, - {key: `${adjustKey} + wheel`, action: "Adjust brush size"}, + // Define an array with hotkey information and their actions + const hotkeysInfo = [ { - key: hotkeysConfig.canvas_hotkey_reset.charAt(hotkeysConfig.canvas_hotkey_reset.length - 1), - action: "Reset zoom" + configKey: "canvas_hotkey_zoom", + action: "Zoom canvas", + keySuffix: " + wheel" }, { - key: hotkeysConfig.canvas_hotkey_fullscreen.charAt(hotkeysConfig.canvas_hotkey_fullscreen.length - 1), - action: "Fullscreen mode" + configKey: "canvas_hotkey_adjust", + action: "Adjust brush size", + keySuffix: " + wheel" }, + {configKey: "canvas_hotkey_reset", action: "Reset zoom"}, { - key: hotkeysConfig.canvas_hotkey_move.charAt(hotkeysConfig.canvas_hotkey_move.length - 1), - action: "Move canvas" - } + configKey: "canvas_hotkey_fullscreen", + action: "Fullscreen mode" + }, + {configKey: "canvas_hotkey_move", action: "Move canvas"}, + {configKey: "canvas_hotkey_overlap", action: "Overlap"} ]; + + // Create hotkeys array with disabled property based on the config values + const hotkeys = hotkeysInfo.map(info => { + const configValue = hotkeysConfig[info.configKey]; + const key = info.keySuffix ? + `${configValue}${info.keySuffix}` : + configValue.charAt(configValue.length - 1); + return { + key, + action: info.action, + disabled: configValue === "disable" + }; + }); + for (const hotkey of hotkeys) { + if (hotkey.disabled) { + continue; + } + const p = document.createElement("p"); p.innerHTML = `<b>${hotkey.key}</b> - ${hotkey.action}`; tooltipContent.appendChild(p); @@ -346,10 +454,7 @@ onUiLoaded(async() => { // Change the zoom level based on user interaction function changeZoomLevel(operation, e) { - if ( - (!hotkeysConfig.canvas_swap_controls && e.shiftKey) || - (hotkeysConfig.canvas_swap_controls && e.ctrlKey) - ) { + if (isModifierKey(e, hotkeysConfig.canvas_hotkey_zoom)) { e.preventDefault(); let zoomPosX, zoomPosY; @@ -514,6 +619,13 @@ onUiLoaded(async() => { event.preventDefault(); action(event); } + + if ( + isModifierKey(event, hotkeysConfig.canvas_hotkey_zoom) || + isModifierKey(event, hotkeysConfig.canvas_hotkey_adjust) + ) { + event.preventDefault(); + } } // Get Mouse position @@ -564,11 +676,7 @@ onUiLoaded(async() => { changeZoomLevel(operation, e); // Handle brush size adjustment with ctrl key pressed - if ( - (hotkeysConfig.canvas_swap_controls && e.shiftKey) || - (!hotkeysConfig.canvas_swap_controls && - (e.ctrlKey || e.metaKey)) - ) { + if (isModifierKey(e, hotkeysConfig.canvas_hotkey_adjust)) { e.preventDefault(); // Increase or decrease brush size based on scroll direction diff --git a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py index d83e14da..1b6683aa 100644 --- a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py +++ b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py @@ -1,10 +1,13 @@ +import gradio as gr from modules import shared shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas Hotkeys"), { - "canvas_hotkey_move": shared.OptionInfo("F", "Moving the canvas"), + "canvas_hotkey_zoom": shared.OptionInfo("Alt", "Zoom canvas", gr.Radio, {"choices": ["Shift","Ctrl", "Alt"]}).info("If you choose 'Shift' you cannot scroll horizontally, 'Alt' can cause a little trouble in firefox"), + "canvas_hotkey_adjust": shared.OptionInfo("Ctrl", "Adjust brush size", gr.Radio, {"choices": ["Shift","Ctrl", "Alt"]}).info("If you choose 'Shift' you cannot scroll horizontally, 'Alt' can cause a little trouble in firefox"), + "canvas_hotkey_move": shared.OptionInfo("F", "Moving the canvas").info("To work correctly in firefox, turn off 'Automatically search the page text when typing' in the browser settings"), "canvas_hotkey_fullscreen": shared.OptionInfo("S", "Fullscreen Mode, maximizes the picture so that it fits into the screen and stretches it to its full width "), "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"), - "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap ( Technical button, neededs for testing )"), + "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, neededs for testing"), "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"), - "canvas_swap_controls": shared.OptionInfo(False, "Swap hotkey combinations for Zoom and Adjust brush resize"), + "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size", "Moving canvas","Fullscreen","Reset Zoom","Overlap"]}), })) diff --git a/extensions-builtin/canvas-zoom-and-pan/style.css b/extensions-builtin/canvas-zoom-and-pan/style.css index 5b131d50..6bcc9570 100644 --- a/extensions-builtin/canvas-zoom-and-pan/style.css +++ b/extensions-builtin/canvas-zoom-and-pan/style.css @@ -1,4 +1,4 @@ -.tooltip-info { +.canvas-tooltip-info { position: absolute; top: 10px; left: 10px; @@ -15,7 +15,7 @@ z-index: 100; } -.tooltip-info::after { +.canvas-tooltip-info::after { content: ''; display: block; width: 2px; @@ -24,7 +24,7 @@ margin-top: 2px; } -.tooltip-info::before { +.canvas-tooltip-info::before { content: ''; display: block; width: 2px; @@ -32,7 +32,7 @@ background-color: white; } -.tooltip-content { +.canvas-tooltip-content { display: none; background-color: #f9f9f9; color: #333; @@ -50,7 +50,7 @@ z-index: 100; } -.tooltip:hover .tooltip-content { +.canvas-tooltip:hover .canvas-tooltip-content { display: block; animation: fadeIn 0.5s; opacity: 1; diff --git a/javascript/extensions.js b/javascript/extensions.js index efeaf3a5..1f7254c5 100644 --- a/javascript/extensions.js +++ b/javascript/extensions.js @@ -72,3 +72,21 @@ function config_state_confirm_restore(_, config_state_name, config_restore_type) } return [confirmed, config_state_name, config_restore_type]; } + +function toggle_all_extensions(event) { + gradioApp().querySelectorAll('#extensions .extension_toggle').forEach(function(checkbox_el) { + checkbox_el.checked = event.target.checked; + }); +} + +function toggle_extension() { + let all_extensions_toggled = true; + for (const checkbox_el of gradioApp().querySelectorAll('#extensions .extension_toggle')) { + if (!checkbox_el.checked) { + all_extensions_toggled = false; + break; + } + } + + gradioApp().querySelector('#extensions .all_extensions_toggle').checked = all_extensions_toggled; +} diff --git a/javascript/hints.js b/javascript/hints.js index 05ae5f22..dc75ce31 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -15,7 +15,7 @@ var titles = { "CFG Scale": "Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results", "Seed": "A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result", "\u{1f3b2}\ufe0f": "Set seed to -1, which will cause a new random number to be used every time", - "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomed", + "\u267b\ufe0f": "Reuse seed from last generation, mostly useful if it was randomized", "\u2199\ufe0f": "Read generation parameters from prompt or last generation if prompt is empty into user interface.", "\u{1f4c2}": "Open images output directory", "\u{1f4be}": "Save style", @@ -112,7 +112,7 @@ var titles = { "Resize height to": "Resizes image to this height. If 0, height is inferred from either of two nearby sliders.", "Multiplier for extra networks": "When adding extra network such as Hypernetwork or Lora to prompt, use this multiplier for it.", "Discard weights with matching name": "Regular expression; if weights's name matches it, the weights is not written to the resulting checkpoint. Use ^model_ema to discard EMA weights.", - "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order lsited.", + "Extra networks tab order": "Comma-separated list of tab names; tabs listed here will appear in the extra networks UI first and in order listed.", "Negative Guidance minimum sigma": "Skip negative prompt for steps where image is already mostly denoised; the higher this value, the more skips there will be; provides increased performance in exchange for minor quality reduction." }; diff --git a/modules/api/api.py b/modules/api/api.py index 2e49526e..279c384a 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -14,7 +14,7 @@ from fastapi.encoders import jsonable_encoder from secrets import compare_digest import modules.shared as shared -from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors +from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart from modules.api import models from modules.shared import opts from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images @@ -22,7 +22,7 @@ from modules.textual_inversion.textual_inversion import create_embedding, train_ from modules.textual_inversion.preprocess import preprocess from modules.hypernetworks.hypernetwork import create_hypernetwork, train_hypernetwork from PIL import PngImagePlugin,Image -from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights +from modules.sd_models import checkpoints_list, unload_model_weights, reload_model_weights, checkpoint_alisases from modules.sd_vae import vae_dict from modules.sd_models_config import find_checkpoint_config_near_filename from modules.realesrgan_model import get_realesrgan_models @@ -32,13 +32,6 @@ import piexif import piexif.helper -def upscaler_to_index(name: str): - try: - return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except Exception as e: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") from e - - def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) @@ -209,6 +202,11 @@ class Api: self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList) self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo]) + if shared.cmd_opts.add_stop_route: + self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"]) + self.add_api_route("/sdapi/v1/server-restart", self.restart_webui, methods=["POST"]) + self.add_api_route("/sdapi/v1/server-stop", self.stop_webui, methods=["POST"]) + self.default_script_arg_txt2img = [] self.default_script_arg_img2img = [] @@ -517,6 +515,10 @@ class Api: return options def set_config(self, req: Dict[str, Any]): + checkpoint_name = req.get("sd_model_checkpoint", None) + if checkpoint_name is not None and checkpoint_name not in checkpoint_alisases: + raise RuntimeError(f"model {checkpoint_name!r} not found") + for k, v in req.items(): shared.opts.set(k, v) @@ -715,3 +717,15 @@ class Api: def launch(self, server_name, port): self.app.include_router(self.router) uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=0) + + def kill_webui(self): + restart.stop_program() + + def restart_webui(self): + if restart.is_restartable(): + restart.restart_program() + return Response(status_code=501) + + def stop_webui(request): + shared.state.server_command = "stop" + return Response("Stopping.") diff --git a/modules/api/models.py b/modules/api/models.py index b3a745f0..b5683071 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -274,10 +274,6 @@ class PromptStyleItem(BaseModel): prompt: Optional[str] = Field(title="Prompt") negative_prompt: Optional[str] = Field(title="Negative Prompt") -class ArtistItem(BaseModel): - name: str = Field(title="Name") - score: float = Field(title="Score") - category: str = Field(title="Category") class EmbeddingItem(BaseModel): step: Optional[int] = Field(title="Step", description="The number of steps that were used to train this embedding, if available") diff --git a/modules/call_queue.py b/modules/call_queue.py index 1b5e5273..69bf63d2 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -1,3 +1,4 @@ +from functools import wraps
import html
import threading
import time
@@ -18,6 +19,7 @@ def wrap_queued_call(func): def wrap_gradio_gpu_call(func, extra_outputs=None):
+ @wraps(func)
def f(*args, **kwargs):
# if the first argument is a string that says "task(...)", it is treated as a job id
@@ -45,6 +47,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def wrap_gradio_call(func, extra_outputs=None, add_stats=False):
+ @wraps(func)
def f(*args, extra_outputs_array=extra_outputs, **kwargs):
run_memmon = shared.opts.memmon_poll_rate > 0 and not shared.mem_mon.disabled and add_stats
if run_memmon:
diff --git a/modules/cmd_args.py b/modules/cmd_args.py index de905caa..624dcb4f 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -106,4 +106,4 @@ parser.add_argument("--skip-version-check", action='store_true', help="Do not ch parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
-parser.add_argument('--add-stop-route', action='store_true', help='add /_stop route to stop server')
+parser.add_argument('--add-stop-route', action='store_true', help='enable server stop/restart/kill via api')
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 4260b016..f293acf5 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -15,14 +15,11 @@ model_dir = "Codeformer" model_path = os.path.join(models_path, model_dir)
model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth'
-have_codeformer = False
codeformer = None
def setup_model(dirname):
- global model_path
- if not os.path.exists(model_path):
- os.makedirs(model_path)
+ os.makedirs(model_path, exist_ok=True)
path = modules.paths.paths.get("CodeFormer", None)
if path is None:
@@ -125,9 +122,6 @@ def setup_model(dirname): return restored_img
- global have_codeformer
- have_codeformer = True
-
global codeformer
codeformer = FaceRestorerCodeFormer(dirname)
shared.face_restorers.append(codeformer)
diff --git a/modules/devices.py b/modules/devices.py index 1ed6ffdc..620ed1a6 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -15,13 +15,6 @@ def has_mps() -> bool: else: return mac_specific.has_mps -def extract_device_id(args, name): - for x in range(len(args)): - if name in args[x]: - return args[x + 1] - - return None - def get_cuda_device_string(): from modules import shared diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 2fced999..02a1727d 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -1,15 +1,13 @@ -import os
+import sys
import numpy as np
import torch
from PIL import Image
-from basicsr.utils.download_util import load_file_from_url
import modules.esrgan_model_arch as arch
from modules import modelloader, images, devices
-from modules.upscaler import Upscaler, UpscalerData
from modules.shared import opts
-
+from modules.upscaler import Upscaler, UpscalerData
def mod2normal(state_dict):
@@ -134,7 +132,7 @@ class UpscalerESRGAN(Upscaler): scaler_data = UpscalerData(self.model_name, self.model_url, self, 4)
scalers.append(scaler_data)
for file in model_paths:
- if "http" in file:
+ if file.startswith("http"):
name = self.model_name
else:
name = modelloader.friendly_name(file)
@@ -143,26 +141,25 @@ class UpscalerESRGAN(Upscaler): self.scalers.append(scaler_data)
def do_upscale(self, img, selected_model):
- model = self.load_model(selected_model)
- if model is None:
+ try:
+ model = self.load_model(selected_model)
+ except Exception as e:
+ print(f"Unable to load ESRGAN model {selected_model}: {e}", file=sys.stderr)
return img
model.to(devices.device_esrgan)
img = esrgan_upscale(model, img)
return img
def load_model(self, path: str):
- if "http" in path:
- filename = load_file_from_url(
+ if path.startswith("http"):
+ # TODO: this doesn't use `path` at all?
+ filename = modelloader.load_file_from_url(
url=self.model_url,
model_dir=self.model_download_path,
file_name=f"{self.model_name}.pth",
- progress=True,
)
else:
filename = path
- if not os.path.exists(filename) or filename is None:
- print(f"Unable to load {self.model_path} from {filename}")
- return None
state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None)
diff --git a/modules/extensions.py b/modules/extensions.py index 8608584b..abc6e2b1 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -7,8 +7,7 @@ from modules.paths_internal import extensions_dir, extensions_builtin_dir, scrip extensions = []
-if not os.path.exists(extensions_dir):
- os.makedirs(extensions_dir)
+os.makedirs(extensions_dir, exist_ok=True)
def active():
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a638f912..a3448be9 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -174,31 +174,6 @@ def send_image_and_dimensions(x): return img, w, h
-
-def find_hypernetwork_key(hypernet_name, hypernet_hash=None):
- """Determines the config parameter name to use for the hypernet based on the parameters in the infotext.
-
- Example: an infotext provides "Hypernet: ke-ta" and "Hypernet hash: 1234abcd". For the "Hypernet" config
- parameter this means there should be an entry that looks like "ke-ta-10000(1234abcd)" to set it to.
-
- If the infotext has no hash, then a hypernet with the same name will be selected instead.
- """
- hypernet_name = hypernet_name.lower()
- if hypernet_hash is not None:
- # Try to match the hash in the name
- for hypernet_key in shared.hypernetworks.keys():
- result = re_hypernet_hash.search(hypernet_key)
- if result is not None and result[1] == hypernet_hash:
- return hypernet_key
- else:
- # Fall back to a hypernet with the same name
- for hypernet_key in shared.hypernetworks.keys():
- if hypernet_key.lower().startswith(hypernet_name):
- return hypernet_key
-
- return None
-
-
def restore_old_hires_fix_params(res):
"""for infotexts that specify old First pass size parameter, convert it into
width, height, and hr scale"""
@@ -332,10 +307,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model return res
-settings_map = {}
-
-
-
infotext_to_setting_name_mapping = [
('Clip skip', 'CLIP_stop_at_last_layers', ),
('Conditional mask weight', 'inpainting_mask_weight'),
@@ -357,6 +328,7 @@ infotext_to_setting_name_mapping = [ ('Token merging ratio hr', 'token_merging_ratio_hr'),
('RNG', 'randn_source'),
('NGMS', 's_min_uncond'),
+ ('Pad conds', 'pad_cond_uncond'),
]
diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index e239a09d..8e0f13bd 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -25,7 +25,7 @@ def gfpgann(): return None
models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN")
- if len(models) == 1 and "http" in models[0]:
+ if len(models) == 1 and models[0].startswith("http"):
model_file = models[0]
elif len(models) != 0:
latest_file = max(models, key=os.path.getctime)
@@ -70,11 +70,8 @@ gfpgan_constructor = None def setup_model(dirname):
- global model_path
- if not os.path.exists(model_path):
- os.makedirs(model_path)
-
try:
+ os.makedirs(model_path, exist_ok=True)
from gfpgan import GFPGANer
from facexlib import detection, parsing # noqa: F401
global user_path
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 5d12b449..51941c11 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -353,17 +353,6 @@ def load_hypernetworks(names, multipliers=None): shared.loaded_hypernetworks.append(hypernetwork)
-def find_closest_hypernetwork_name(search: str):
- if not search:
- return None
- search = search.lower()
- applicable = [name for name in shared.hypernetworks if search in name.lower()]
- if not applicable:
- return None
- applicable = sorted(applicable, key=lambda name: len(name))
- return applicable[0]
-
-
def apply_single_hypernetwork(hypernetwork, context_k, context_v, layer=None):
hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context_k.shape[2], None)
@@ -446,18 +435,6 @@ def statistics(data): return total_information, recent_information
-def report_statistics(loss_info:dict):
- keys = sorted(loss_info.keys(), key=lambda x: sum(loss_info[x]) / len(loss_info[x]))
- for key in keys:
- try:
- print("Loss statistics for file " + key)
- info, recent = statistics(list(loss_info[key]))
- print(info)
- print(recent)
- except Exception as e:
- print(e)
-
-
def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None):
# Remove illegal characters from name.
name = "".join( x for x in name if (x.isalnum() or x in "._- "))
@@ -770,7 +747,6 @@ Last saved image: {html.escape(last_saved_image)}<br/> pbar.leave = False
pbar.close()
hypernetwork.eval()
- #report_statistics(loss_dict)
sd_hijack_checkpoint.remove()
diff --git a/modules/images.py b/modules/images.py index 7bbfc3e0..1906e2ab 100644 --- a/modules/images.py +++ b/modules/images.py @@ -372,8 +372,8 @@ class FilenameGenerator: 'hasprompt': lambda self, *args: self.hasprompt(*args), # accepts formats:[hasprompt<prompt1|default><prompt2>..]
'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
'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(),
-
}
default_time_format = '%Y%m%d%H%M%S'
diff --git a/modules/img2img.py b/modules/img2img.py index 2c497020..b07d7f2f 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -3,6 +3,7 @@ from pathlib import Path import numpy as np
from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
+import gradio as gr
from modules import sd_samplers
from modules.generation_parameters_copypaste import create_override_settings_dict
@@ -97,7 +98,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal processed_image.save(os.path.join(output_dir, filename))
-def img2img(id_task: str, 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, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, 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, *args):
+def img2img(id_task: str, 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, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, 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, request: gr.Request, *args):
override_settings = create_override_settings_dict(override_settings_texts)
is_batch = mode == 5
@@ -180,6 +181,8 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s p.scripts = modules.scripts.scripts_img2img
p.script_args = args
+ p.user = request.username
+
if shared.cmd_opts.enable_console_prompts:
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 609a181e..97539e68 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -147,10 +147,10 @@ def git_clone(url, dir, name, commithash=None): return
run(f'"{git}" -C "{dir}" fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}")
- run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}")
+ run(f'"{git}" -C "{dir}" checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
return
- run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}")
+ run(f'"{git}" clone "{url}" "{dir}"', f"Cloning {name} into {dir}...", f"Couldn't clone {name}", live=True)
if commithash is not None:
run(f'"{git}" -C "{dir}" checkout {commithash}', None, "Couldn't checkout {name}'s hash: {commithash}")
diff --git a/modules/modelloader.py b/modules/modelloader.py index be23071a..098bcb79 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import shutil import importlib @@ -8,6 +10,29 @@ from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, Upscale from modules.paths import script_path, models_path +def load_file_from_url( + url: str, + *, + model_dir: str, + progress: bool = True, + file_name: 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) + 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) -> list: """ A one-and done loader to try finding the desired models in specified directories. @@ -46,9 +71,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None if model_url is not None and len(output) == 0: if download_name is not None: - from basicsr.utils.download_util import load_file_from_url - dl = load_file_from_url(model_url, places[0], True, download_name) - output.append(dl) + output.append(load_file_from_url(model_url, model_dir=places[0], file_name=download_name)) else: output.append(model_url) @@ -59,7 +82,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None def friendly_name(file: str): - if "http" in file: + if file.startswith("http"): file = urlparse(file).path file = os.path.basename(file) @@ -95,8 +118,7 @@ def cleanup_models(): def move_files(src_path: str, dest_path: str, ext_filter: str = None): try: - if not os.path.exists(dest_path): - os.makedirs(dest_path) + os.makedirs(dest_path, exist_ok=True) if os.path.exists(src_path): for file in os.listdir(src_path): fullpath = os.path.join(src_path, file) diff --git a/modules/paths.py b/modules/paths.py index 5171df4f..bada804e 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -38,17 +38,3 @@ for d, must_exist, what, options in path_dirs: else:
sys.path.append(d)
paths[what] = d
-
-
-class Prioritize:
- def __init__(self, name):
- self.name = name
- self.path = None
-
- def __enter__(self):
- self.path = sys.path.copy()
- sys.path = [paths[self.name]] + sys.path
-
- def __exit__(self, exc_type, exc_val, exc_tb):
- sys.path = self.path
- self.path = None
diff --git a/modules/processing.py b/modules/processing.py index 8da73884..85e104aa 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -184,6 +184,8 @@ class StableDiffusionProcessing: self.uc = None
self.c = None
+ self.user = None
+
@property
def sd_model(self):
return shared.sd_model
@@ -549,7 +551,7 @@ def program_version(): return res
-def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0):
+def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0, use_main_prompt=False):
index = position_in_batch + iteration * p.batch_size
clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
@@ -585,13 +587,15 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
**p.extra_generation_params,
"Version": program_version() if opts.add_version_to_infotext else None,
+ "User": p.user if opts.add_user_name_to_info else None,
}
generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
+ prompt_text = p.prompt if use_main_prompt else all_prompts[index]
negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""
- return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip()
+ return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip()
def process_images(p: StableDiffusionProcessing) -> Processed:
@@ -663,8 +667,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: else:
p.all_subseeds = [int(subseed) + x for x in range(len(p.all_prompts))]
- def infotext(iteration=0, position_in_batch=0):
- return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch)
+ def infotext(iteration=0, position_in_batch=0, use_main_prompt=False):
+ return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch, use_main_prompt)
if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
model_hijack.embedding_db.load_textual_inversion_embeddings()
@@ -824,7 +828,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: grid = images.image_grid(output_images, p.batch_size)
if opts.return_grid:
- text = infotext()
+ text = infotext(use_main_prompt=True)
infotexts.insert(0, text)
if opts.enable_pnginfo:
grid.info["parameters"] = text
@@ -832,7 +836,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: index_of_first_image = 1
if opts.grid_save:
- images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
+ images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(use_main_prompt=True), short_filename=not opts.grid_extended_filename, p=p, grid=True)
if not p.disable_extra_networks and p.extra_network_data:
extra_networks.deactivate(p, p.extra_network_data)
diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 2d27b321..0700b853 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -2,7 +2,6 @@ import os import numpy as np
from PIL import Image
-from basicsr.utils.download_util import load_file_from_url
from realesrgan import RealESRGANer
from modules.upscaler import Upscaler, UpscalerData
@@ -43,9 +42,10 @@ class UpscalerRealESRGAN(Upscaler): if not self.enable:
return img
- info = self.load_model(path)
- if not os.path.exists(info.local_data_path):
- print(f"Unable to load RealESRGAN model: {info.name}")
+ try:
+ info = self.load_model(path)
+ except Exception:
+ errors.report(f"Unable to load RealESRGAN model {path}", exc_info=True)
return img
upsampler = RealESRGANer(
@@ -63,20 +63,17 @@ class UpscalerRealESRGAN(Upscaler): return image
def load_model(self, path):
- try:
- info = next(iter([scaler for scaler in self.scalers if scaler.data_path == path]), None)
-
- if info is None:
- print(f"Unable to find model info: {path}")
- return None
-
- if info.local_data_path.startswith("http"):
- info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_download_path, progress=True)
-
- return info
- except Exception:
- errors.report("Error making Real-ESRGAN models list", exc_info=True)
- return None
+ for scaler in self.scalers:
+ if scaler.data_path == path:
+ if scaler.local_data_path.startswith("http"):
+ scaler.local_data_path = modelloader.load_file_from_url(
+ scaler.data_path,
+ model_dir=self.model_download_path,
+ )
+ if not os.path.exists(scaler.local_data_path):
+ raise FileNotFoundError(f"RealESRGAN data missing: {scaler.local_data_path}")
+ return scaler
+ raise ValueError(f"Unable to find model info: {path}")
def load_models(self, _):
return get_realesrgan_models(self)
diff --git a/modules/scripts.py b/modules/scripts.py index 99bf836a..49e4a611 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -1,6 +1,7 @@ import os
import re
import sys
+import inspect
from collections import namedtuple
import gradio as gr
@@ -249,7 +250,7 @@ def load_scripts(): def register_scripts_from_module(module):
for script_class in module.__dict__.values():
- if type(script_class) != type:
+ if not inspect.isclass(script_class):
continue
if issubclass(script_class, Script):
diff --git a/modules/sd_models.py b/modules/sd_models.py index 918f6fd6..f65f4e36 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -95,8 +95,7 @@ except Exception: def setup_model():
- if not os.path.exists(model_path):
- os.makedirs(model_path)
+ os.makedirs(model_path, exist_ok=True)
enable_midas_autodownload()
@@ -248,7 +247,12 @@ def read_state_dict(checkpoint_file, print_global_state=False, map_location=None _, extension = os.path.splitext(checkpoint_file)
if extension.lower() == ".safetensors":
device = map_location or shared.weight_load_location or devices.get_optimal_device_name()
- pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
+
+ if not shared.opts.disable_mmap_load_safetensors:
+ pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
+ else:
+ pl_sd = safetensors.torch.load(open(checkpoint_file, 'rb').read())
+ pl_sd = {k: v.to(device) for k, v in pl_sd.items()}
else:
pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index f8a0c7ba..71581b76 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -69,6 +69,7 @@ class CFGDenoiser(torch.nn.Module): self.init_latent = None
self.step = 0
self.image_cfg_scale = None
+ self.padded_cond_uncond = False
def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
denoised_uncond = x_out[-uncond.shape[0]:]
@@ -133,15 +134,17 @@ class CFGDenoiser(torch.nn.Module): x_in = x_in[:-batch_size]
sigma_in = sigma_in[:-batch_size]
- # TODO add infotext entry
+ self.padded_cond_uncond = False
if shared.opts.pad_cond_uncond and tensor.shape[1] != uncond.shape[1]:
empty = shared.sd_model.cond_stage_model_empty_prompt
num_repeats = (tensor.shape[1] - uncond.shape[1]) // empty.shape[1]
if num_repeats < 0:
tensor = torch.cat([tensor, empty.repeat((tensor.shape[0], -num_repeats, 1))], axis=1)
+ self.padded_cond_uncond = True
elif num_repeats > 0:
uncond = torch.cat([uncond, empty.repeat((uncond.shape[0], num_repeats, 1))], axis=1)
+ self.padded_cond_uncond = True
if tensor.shape[1] == uncond.shape[1] or skip_uncond:
if is_edit_model:
@@ -405,6 +408,9 @@ class KDiffusionSampler: samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
+ if self.model_wrap_cfg.padded_cond_uncond:
+ p.extra_generation_params["Pad conds"] = True
+
return samples
def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
@@ -438,5 +444,8 @@ class KDiffusionSampler: 's_min_uncond': self.s_min_uncond
}, disable=False, callback=self.callback_state, **extra_params_kwargs))
+ if self.model_wrap_cfg.padded_cond_uncond:
+ p.extra_generation_params["Pad conds"] = True
+
return samples
diff --git a/modules/shared.py b/modules/shared.py index 91c31d55..203ee1b9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -376,6 +376,7 @@ options_templates.update(options_section(('system', "System"), { "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
"print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."),
"list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""),
+ "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"),
}))
options_templates.update(options_section(('training', "Training"), {
@@ -409,7 +410,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"),
"enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
"comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"),
- "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP nrtwork; 1 ignores none, 2 ignores one layer"),
+ "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"),
"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
"randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"),
}))
@@ -493,6 +494,7 @@ options_templates.update(options_section(('ui', "User interface"), { options_templates.update(options_section(('infotext', "Infotext"), {
"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
"add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
+ "add_user_name_to_info": OptionInfo(False, "Add user name to generation information when authenticated"),
"add_version_to_infotext": OptionInfo(True, "Add program version to generation information"),
"disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"),
"infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""<ul style='margin-left: 1.5em'>
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 75705459..1675e39a 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -298,8 +298,7 @@ def download_and_cache_models(dirname): download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
model_file_name = 'face_detection_yunet.onnx'
- if not os.path.exists(dirname):
- os.makedirs(dirname)
+ os.makedirs(dirname, exist_ok=True)
cache_file = os.path.join(dirname, model_file_name)
if not os.path.exists(cache_file):
diff --git a/modules/textual_inversion/logging.py b/modules/textual_inversion/logging.py index 734a4b6f..45823eb1 100644 --- a/modules/textual_inversion/logging.py +++ b/modules/textual_inversion/logging.py @@ -2,11 +2,51 @@ import datetime import json
import os
-saved_params_shared = {"model_name", "model_hash", "initial_step", "num_of_dataset_images", "learn_rate", "batch_size", "clip_grad_mode", "clip_grad_value", "gradient_step", "data_root", "log_directory", "training_width", "training_height", "steps", "create_image_every", "template_file", "gradient_step", "latent_sampling_method"}
-saved_params_ti = {"embedding_name", "num_vectors_per_token", "save_embedding_every", "save_image_with_stored_embedding"}
-saved_params_hypernet = {"hypernetwork_name", "layer_structure", "activation_func", "weight_init", "add_layer_norm", "use_dropout", "save_hypernetwork_every"}
+saved_params_shared = {
+ "batch_size",
+ "clip_grad_mode",
+ "clip_grad_value",
+ "create_image_every",
+ "data_root",
+ "gradient_step",
+ "initial_step",
+ "latent_sampling_method",
+ "learn_rate",
+ "log_directory",
+ "model_hash",
+ "model_name",
+ "num_of_dataset_images",
+ "steps",
+ "template_file",
+ "training_height",
+ "training_width",
+}
+saved_params_ti = {
+ "embedding_name",
+ "num_vectors_per_token",
+ "save_embedding_every",
+ "save_image_with_stored_embedding",
+}
+saved_params_hypernet = {
+ "activation_func",
+ "add_layer_norm",
+ "hypernetwork_name",
+ "layer_structure",
+ "save_hypernetwork_every",
+ "use_dropout",
+ "weight_init",
+}
saved_params_all = saved_params_shared | saved_params_ti | saved_params_hypernet
-saved_params_previews = {"preview_prompt", "preview_negative_prompt", "preview_steps", "preview_sampler_index", "preview_cfg_scale", "preview_seed", "preview_width", "preview_height"}
+saved_params_previews = {
+ "preview_cfg_scale",
+ "preview_height",
+ "preview_negative_prompt",
+ "preview_prompt",
+ "preview_sampler_index",
+ "preview_seed",
+ "preview_steps",
+ "preview_width",
+}
def save_settings_to_file(log_directory, all_params):
diff --git a/modules/txt2img.py b/modules/txt2img.py index 2e7d202d..6aa79f23 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -4,10 +4,10 @@ from modules.generation_parameters_copypaste import create_override_settings_dic from modules.shared import opts, cmd_opts
import modules.shared as shared
from modules.ui import plaintext_to_html
+import gradio as gr
-
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args):
override_settings = create_override_settings_dict(override_settings_texts)
p = processing.StableDiffusionProcessingTxt2Img(
@@ -48,6 +48,8 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step p.scripts = modules.scripts.scripts_txt2img
p.script_args = args
+ p.user = request.username
+
if cmd_opts.enable_console_prompts:
print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
diff --git a/modules/ui.py b/modules/ui.py index e2e3b6da..e3c8e43a 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -773,7 +773,7 @@ def create_ui(): selected_scale_tab = gr.State(value=0)
with gr.Tabs():
- with gr.Tab(label="Resize to") as tab_scale_to:
+ with gr.Tab(label="Resize to", elem_id="img2img_tab_resize_to") as tab_scale_to:
with FormRow():
with gr.Column(elem_id="img2img_column_size", scale=4):
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
@@ -782,7 +782,7 @@ def create_ui(): res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
- with gr.Tab(label="Resize by") as tab_scale_by:
+ with gr.Tab(label="Resize by", elem_id="img2img_tab_resize_by") as tab_scale_by:
scale_by = gr.Slider(minimum=0.05, maximum=4.0, step=0.05, label="Scale", value=1.0, elem_id="img2img_scale")
with FormRow():
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 4379a641..278bf5e4 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -138,7 +138,10 @@ def extension_table(): <table id="extensions">
<thead>
<tr>
- <th><abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr></th>
+ <th>
+ <input class="gr-check-radio gr-checkbox all_extensions_toggle" type="checkbox" {'checked="checked"' if all(ext.enabled for ext in extensions.extensions) else ''} onchange="toggle_all_extensions(event)" />
+ <abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr>
+ </th>
<th>URL</th>
<th>Branch</th>
<th>Version</th>
@@ -170,7 +173,7 @@ def extension_table(): code += f"""
<tr>
- <td><label{style}><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
+ <td><label{style}><input class="gr-check-radio gr-checkbox extension_toggle" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''} onchange="toggle_extension(event)" />{html.escape(ext.name)}</label></td>
<td>{remote}</td>
<td>{ext.branch}</td>
<td>{version_link}</td>
@@ -325,6 +328,11 @@ def normalize_git_url(url): def install_extension_from_url(dirname, url, branch_name=None):
check_access()
+ if isinstance(dirname, str):
+ dirname = dirname.strip()
+ if isinstance(url, str):
+ url = url.strip()
+
assert url, 'No URL specified'
if dirname is None or dirname == "":
@@ -563,9 +571,9 @@ def create_ui(): available_extensions_table = gr.HTML()
refresh_available_extensions_button.click(
- fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update()]),
+ fn=modules.ui.wrap_gradio_call(refresh_available_extensions, extra_outputs=[gr.update(), gr.update(), gr.update(), gr.update()]),
inputs=[available_extensions_index, hide_tags, sort_column],
- outputs=[available_extensions_index, available_extensions_table, hide_tags, install_result, search_extensions_text],
+ outputs=[available_extensions_index, available_extensions_table, hide_tags, search_extensions_text, install_result],
)
install_extension_button.click(
@@ -11,7 +11,7 @@ import json from threading import Thread
from typing import Iterable
-from fastapi import FastAPI, Response
+from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
from packaging import version
@@ -362,11 +362,6 @@ def api_only(): api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861)
-def stop_route(request):
- shared.state.server_command = "stop"
- return Response("Stopping.")
-
-
def webui():
launch_api = cmd_opts.api
initialize()
@@ -404,8 +399,6 @@ def webui(): "redoc_url": "/redoc",
},
)
- if cmd_opts.add_stop_route:
- app.add_route("/_stop", stop_route, methods=["POST"])
# after initial launch, disable --autolaunch for subsequent restarts
cmd_opts.autolaunch = False
|