mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2026-02-01 05:11:19 -08:00
Merge branch 'dev' into pr/15530
This commit is contained in:
w-e-w
commit
ab4a5378c6
32 changed files with 330 additions and 138 deletions
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@ -10,7 +10,7 @@ model:
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num_idx: 1000
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weighting_config:
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target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting
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target: sgm.modules.diffusionmodules.denoiser_weighting.VWeighting
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scaling_config:
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target: sgm.modules.diffusionmodules.denoiser_scaling.VScaling
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discretization_config:
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@ -21,7 +21,7 @@ model:
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params:
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adm_in_channels: 2816
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num_classes: sequential
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use_checkpoint: True
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use_checkpoint: False
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in_channels: 4
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out_channels: 4
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model_channels: 320
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@ -816,7 +816,7 @@ onUiLoaded(async() => {
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// Increase or decrease brush size based on scroll direction
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adjustBrushSize(elemId, e.deltaY);
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}
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});
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}, {passive: false});
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// Handle the move event for pan functionality. Updates the panX and panY variables and applies the new transform to the target element.
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function handleMoveKeyDown(e) {
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@ -1,7 +1,7 @@
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"""
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Hypertile module for splitting attention layers in SD-1.5 U-Net and SD-1.5 VAE
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Warn: The patch works well only if the input image has a width and height that are multiples of 128
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Original author: @tfernd Github: https://github.com/tfernd/HyperTile
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Original author: @tfernd GitHub: https://github.com/tfernd/HyperTile
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"""
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from __future__ import annotations
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@ -34,14 +34,14 @@ class ScriptPostprocessingAutosizedCrop(scripts_postprocessing.ScriptPostprocess
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with ui_components.InputAccordion(False, label="Auto-sized crop") as enable:
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gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
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with gr.Row():
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mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="postprocess_multicrop_mindim")
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maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="postprocess_multicrop_maxdim")
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mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id=self.elem_id_suffix("postprocess_multicrop_mindim"))
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maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id=self.elem_id_suffix("postprocess_multicrop_maxdim"))
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with gr.Row():
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minarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area lower bound", value=64 * 64, elem_id="postprocess_multicrop_minarea")
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maxarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area upper bound", value=640 * 640, elem_id="postprocess_multicrop_maxarea")
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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"))
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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"))
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with gr.Row():
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objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="postprocess_multicrop_objective")
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threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="postprocess_multicrop_threshold")
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objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id=self.elem_id_suffix("postprocess_multicrop_objective"))
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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"))
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return {
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"enable": enable,
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@ -11,10 +11,10 @@ class ScriptPostprocessingFocalCrop(scripts_postprocessing.ScriptPostprocessing)
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def ui(self):
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with ui_components.InputAccordion(False, label="Auto focal point crop") as enable:
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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")
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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")
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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")
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debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
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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"))
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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"))
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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"))
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debug = gr.Checkbox(label='Create debug image', elem_id=self.elem_id_suffix("train_process_focal_crop_debug"))
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return {
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"enable": enable,
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@ -35,8 +35,8 @@ class ScriptPostprocessingSplitOversized(scripts_postprocessing.ScriptPostproces
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def ui(self):
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with ui_components.InputAccordion(False, label="Split oversized images") as enable:
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with gr.Row():
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split_threshold = gr.Slider(label='Threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_split_threshold")
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overlap_ratio = gr.Slider(label='Overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="postprocess_overlap_ratio")
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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"))
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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"))
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return {
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"enable": enable,
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@ -1,7 +1,7 @@
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<div>
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<a href="{api_docs}">API</a>
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•
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<a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">Github</a>
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<a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">GitHub</a>
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•
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<a href="https://gradio.app">Gradio</a>
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•
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@ -104,7 +104,7 @@ var contextMenuInit = function() {
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e.preventDefault();
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}
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});
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});
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}, {passive: false});
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});
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eventListenerApplied = true;
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@ -29,10 +29,11 @@ const EXTRA_NETWORKS_INIT_DATA_TIMEOUT_MS = 60000;
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const EXTRA_NETWORKS_FETCH_DATA_TIMEOUT_MS = 60000;
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const EXTRA_NETWORKS_SETUP_DEBOUNCE_TIME_MS = 1000;
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const re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/;
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const re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/s;
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const re_extranet_g = /<([^:^>]+:[^:]+):[\d.]+>/g;
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const re_extranet_neg = /\(([^:^>]+:[\d.]+)\)/;
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const re_extranet_g_neg = /\(([^:^>]+:[\d.]+)\)/g;
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var globalPopup = null;
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var globalPopupInner = null;
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const storedPopupIds = {};
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@ -79,11 +79,12 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
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var wakeLock = null;
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var requestWakeLock = async function() {
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if (!opts.prevent_screen_sleep_during_generation || wakeLock) return;
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if (!opts.prevent_screen_sleep_during_generation || wakeLock !== null) return;
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try {
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wakeLock = await navigator.wakeLock.request('screen');
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} catch (err) {
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console.error('Wake Lock is not supported.');
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wakeLock = false;
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}
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};
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@ -127,7 +127,7 @@
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} else {
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R.screenX = evt.changedTouches[0].screenX;
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}
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});
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}, {passive: false});
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});
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resizeHandle.addEventListener('dblclick', onDoubleClick);
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@ -1,7 +1,7 @@
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import os
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from modules import modelloader, errors
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from modules.shared import cmd_opts, opts
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from modules.shared import cmd_opts, opts, hf_endpoint
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from modules.upscaler import Upscaler, UpscalerData
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from modules.upscaler_utils import upscale_with_model
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@ -49,7 +49,18 @@ class UpscalerDAT(Upscaler):
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scaler.local_data_path = modelloader.load_file_from_url(
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scaler.data_path,
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model_dir=self.model_download_path,
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hash_prefix=scaler.sha256,
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)
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if os.path.getsize(scaler.local_data_path) < 200:
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# Re-download if the file is too small, probably an LFS pointer
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scaler.local_data_path = modelloader.load_file_from_url(
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scaler.data_path,
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model_dir=self.model_download_path,
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hash_prefix=scaler.sha256,
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re_download=True,
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)
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if not os.path.exists(scaler.local_data_path):
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raise FileNotFoundError(f"DAT data missing: {scaler.local_data_path}")
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return scaler
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@ -60,20 +71,23 @@ def get_dat_models(scaler):
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return [
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UpscalerData(
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name="DAT x2",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x2.pth",
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path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x2.pth",
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scale=2,
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upscaler=scaler,
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sha256='7760aa96e4ee77e29d4f89c3a4486200042e019461fdb8aa286f49aa00b89b51',
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),
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UpscalerData(
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name="DAT x3",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x3.pth",
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path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x3.pth",
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scale=3,
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upscaler=scaler,
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sha256='581973e02c06f90d4eb90acf743ec9604f56f3c2c6f9e1e2c2b38ded1f80d197',
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),
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UpscalerData(
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name="DAT x4",
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path="https://github.com/n0kovo/dat_upscaler_models/raw/main/DAT/DAT_x4.pth",
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path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x4.pth",
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scale=4,
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upscaler=scaler,
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sha256='391a6ce69899dff5ea3214557e9d585608254579217169faf3d4c353caff049e',
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),
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]
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@ -10,6 +10,7 @@ import torch
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from modules import shared
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from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone
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from modules.util import load_file_from_url # noqa, backwards compatibility
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if TYPE_CHECKING:
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import spandrel
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@ -17,30 +18,6 @@ if TYPE_CHECKING:
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logger = logging.getLogger(__name__)
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def load_file_from_url(
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url: str,
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*,
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model_dir: str,
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progress: bool = True,
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file_name: str | None = None,
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hash_prefix: str | None = None,
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) -> str:
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"""Download a file from `url` into `model_dir`, using the file present if possible.
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Returns the path to the downloaded file.
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"""
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os.makedirs(model_dir, exist_ok=True)
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if not file_name:
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parts = urlparse(url)
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file_name = os.path.basename(parts.path)
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cached_file = os.path.abspath(os.path.join(model_dir, file_name))
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if not os.path.exists(cached_file):
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print(f'Downloading: "{url}" to {cached_file}\n')
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from torch.hub import download_url_to_file
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download_url_to_file(url, cached_file, progress=progress, hash_prefix=hash_prefix)
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return cached_file
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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:
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"""
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A one-and done loader to try finding the desired models in specified directories.
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|
|
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@ -24,7 +24,7 @@ class SafetensorsMapping(typing.Mapping):
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return self.file.get_tensor(key)
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CLIPL_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors"
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CLIPL_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors"
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CLIPL_CONFIG = {
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"hidden_act": "quick_gelu",
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"hidden_size": 768,
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@ -33,7 +33,7 @@ CLIPL_CONFIG = {
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"num_hidden_layers": 12,
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}
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CLIPG_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors"
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CLIPG_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors"
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CLIPG_CONFIG = {
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"hidden_act": "gelu",
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"hidden_size": 1280,
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@ -43,7 +43,7 @@ CLIPG_CONFIG = {
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"textual_inversion_key": "clip_g",
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}
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|
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T5_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors"
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T5_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors"
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T5_CONFIG = {
|
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"d_ff": 10240,
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"d_model": 4096,
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|
|
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|
@ -1259,7 +1259,10 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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if self.hr_checkpoint_info is None:
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raise Exception(f'Could not find checkpoint with name {self.hr_checkpoint_name}')
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self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title
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if shared.sd_model.sd_checkpoint_info == self.hr_checkpoint_info:
|
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self.hr_checkpoint_info = None
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else:
|
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self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title
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||||
|
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if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name:
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self.extra_generation_params["Hires sampler"] = self.hr_sampler_name
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|
|
|
|||
|
|
@ -13,6 +13,7 @@ class ScriptPostprocessingForMainUI(scripts.Script):
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return scripts.AlwaysVisible
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||||
|
||||
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:
|
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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
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||||
|
||||
constructor = lambda s=script: ScriptPostprocessingForMainUI(s.script_class())
|
||||
|
|
|
|||
|
|
@ -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])
|
||||
|
|
|
|||
|
|
@ -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:
|
||||
|
|
|
|||
|
|
@ -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():
|
||||
|
|
|
|||
|
|
@ -301,6 +301,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks", "s
|
|||
"sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *shared.hypernetworks]}, refresh=shared_items.reload_hypernetworks),
|
||||
"extra_networks_long_press_time_ms": OptionInfo(800, "Hold time required to register a long click").info("in milliseconds").info("default 800"),
|
||||
"extra_networks_dbl_press_time_ms": OptionInfo(500, "Time between clicks to register a double click").info("in milliseconds").info("default 500"),
|
||||
"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"), {
|
||||
|
|
@ -420,9 +421,9 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
|
|||
}))
|
||||
|
||||
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"),
|
||||
}))
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -91,6 +91,7 @@ class InputAccordion(gr.Checkbox):
|
|||
Actually just a hidden checkbox, but creates an accordion that follows and is followed by the state of the checkbox.
|
||||
"""
|
||||
|
||||
accordion_id_set = set()
|
||||
global_index = 0
|
||||
|
||||
def __init__(self, value, **kwargs):
|
||||
|
|
@ -99,6 +100,18 @@ class InputAccordion(gr.Checkbox):
|
|||
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",
|
||||
|
|
@ -143,3 +156,7 @@ class InputAccordion(gr.Checkbox):
|
|||
def get_block_name(self):
|
||||
return "checkbox"
|
||||
|
||||
@classmethod
|
||||
def reset(cls):
|
||||
cls.global_index = 0
|
||||
cls.accordion_id_set.clear()
|
||||
|
|
|
|||
|
|
@ -1321,10 +1321,8 @@ def add_pages_to_demo(app):
|
|||
app.add_api_route("/sd_extra_networks/get-model-details", get_model_details, 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)
|
||||
|
||||
|
||||
def initialize():
|
||||
|
|
|
|||
|
|
@ -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
|
||||
|
|
|
|||
|
|
@ -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}>"
|
||||
|
|
|
|||
|
|
@ -211,3 +211,80 @@ 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())
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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,
|
||||
|
|
|
|||
|
|
@ -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():
|
||||
|
|
|
|||
|
|
@ -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" # 📒
|
||||
|
||||
|
|
@ -285,7 +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]
|
||||
|
|
@ -370,29 +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
|
||||
|
||||
|
|
@ -442,7 +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.")
|
||||
|
|
@ -450,9 +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"):
|
||||
|
|
@ -534,9 +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:
|
||||
|
|
@ -781,7 +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:
|
||||
|
|
@ -790,14 +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):
|
||||
|
|
@ -807,7 +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]
|
||||
|
|
|
|||
11
webui.bat
11
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")
|
||||
|
||||
|
|
|
|||
40
webui.py
40
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()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue