mirror of
https://github.com/vladmandic/automatic
synced 2026-09-20 01:31:13 +02:00
fix prompts from file
This commit is contained in:
Vladimir Mandic
@@ -4,9 +4,9 @@
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<div class='actions'>
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<div class='additional'>
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<ul>
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<li><a href="#" title="replace preview image with currently selected in gallery" onclick={save_card_preview}>replace preview</a></li>
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<li><a href="#" title="replace preview description with currently selected in gallery" onclick={save_card_description}>replace description</a></li>
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<li><a href="#" title="read description" onclick={read_card_description}>read description</a></li>
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<li><a href="#" title="replace preview image with currently selected in gallery" onclick={save_card_preview}>Replace preview</a></li>
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<li><a href="#" title="replace preview description with currently selected in gallery" onclick={save_card_description}>Replace description</a></li>
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<li><a href="#" title="read description" onclick={read_card_description}>Read description</a></li>
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</ul>
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<span style="display:none" class='search_term'>{search_term}</span>
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</div>
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@@ -14,4 +14,3 @@
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<span class='description'>{description}</span>
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</div>
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</div>
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+5
-22
@@ -971,9 +971,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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img2img_sampler_name = self.sampler_name
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force_latent_upscaler = shared.opts.data.get('xyz_fallback_sampler')
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if self.sampler_name in ['PLMS'] or force_latent_upscaler is not None:
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# PLMS does not support img2img, use fallback instead
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img2img_sampler_name = force_latent_upscaler or shared.opts.fallback_sampler
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if self.sampler_name in ['PLMS'] or (force_latent_upscaler is not None and force_latent_upscaler != 'None'):
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img2img_sampler_name = force_latent_upscaler or shared.opts.fallback_sampler # PLMS does not support img2img, use fallback instead
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self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model)
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samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
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@@ -1026,29 +1025,24 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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self.image_conditioning = None
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def init(self, all_prompts, all_seeds, all_subseeds):
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if self.sampler_name in ['PLMS', 'UniPC']: # PLMS/UniPC do not support img2img so we just silently switch to DDIM
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self.sampler_name = shared.opts.fallback_sampler
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force_latent_upscaler = shared.opts.data.get('xyz_fallback_sampler')
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if self.sampler_name in ['PLMS'] or (force_latent_upscaler is not None and force_latent_upscaler != 'None'):
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self.sampler_name = force_latent_upscaler or shared.opts.fallback_sampler # PLMS does not support img2img, use fallback instead
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self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
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crop_region = None
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image_mask = self.image_mask
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if image_mask is not None:
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image_mask = image_mask.convert('L')
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if self.inpainting_mask_invert:
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image_mask = ImageOps.invert(image_mask)
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if self.mask_blur > 0:
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image_mask = image_mask.filter(ImageFilter.GaussianBlur(self.mask_blur))
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if self.inpaint_full_res:
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self.mask_for_overlay = image_mask
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mask = image_mask.convert('L')
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crop_region = masking.get_crop_region(np.array(mask), self.inpaint_full_res_padding)
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crop_region = masking.expand_crop_region(crop_region, self.width, self.height, mask.width, mask.height)
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x1, y1, x2, y2 = crop_region
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mask = mask.crop(crop_region)
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image_mask = images.resize_image(2, mask, self.width, self.height)
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self.paste_to = (x1, y1, x2-x1, y2-y1)
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@@ -1057,42 +1051,31 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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np_mask = np.array(image_mask)
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np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8)
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self.mask_for_overlay = Image.fromarray(np_mask)
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self.overlay_images = []
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latent_mask = self.latent_mask if self.latent_mask is not None else image_mask
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add_color_corrections = opts.img2img_color_correction and self.color_corrections is None
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if add_color_corrections:
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self.color_corrections = []
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imgs = []
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for img in self.init_images:
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image = images.flatten(img, opts.img2img_background_color)
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if crop_region is None and self.resize_mode != 3:
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image = images.resize_image(self.resize_mode, image, self.width, self.height)
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if image_mask is not None:
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image_masked = Image.new('RGBa', (image.width, image.height))
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image_masked.paste(image.convert("RGBA").convert("RGBa"), mask=ImageOps.invert(self.mask_for_overlay.convert('L')))
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self.overlay_images.append(image_masked.convert('RGBA'))
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# crop_region is not None if we are doing inpaint full res
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if crop_region is not None:
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image = image.crop(crop_region)
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image = images.resize_image(2, image, self.width, self.height)
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if image_mask is not None:
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if self.inpainting_fill != 1:
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image = masking.fill(image, latent_mask)
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if add_color_corrections:
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self.color_corrections.append(setup_color_correction(image))
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image = np.array(image).astype(np.float32) / 255.0
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image = np.moveaxis(image, 2, 0)
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imgs.append(image)
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if len(imgs) == 1:
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+1
-1
@@ -417,7 +417,7 @@ options_templates.update(options_section(('ui', "Live previews"), {
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options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
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"show_samplers": OptionInfo(["Euler a", "UniPC", "DDIM", "DPM++ SDE", "DPM++ SDE", "DPM2 Karras", "DPM++ 2M Karras"], "Show samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}),
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"fallback_sampler": OptionInfo("Euler a", "Fallback sampler if primary sampler is not compatible", gr.Dropdown, lambda: {"choices": [x.name for x in list_samplers()]}),
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"fallback_sampler": OptionInfo("Euler a", "Fallback sampler if primary sampler is not compatible", gr.Dropdown, lambda: {"choices": ["None"] + [x.name for x in list_samplers()]}),
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"eta_ancestral": OptionInfo(1.0, "Noise multiplier for ancestral samplers (eta)", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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"eta_ddim": OptionInfo(0.0, "Noise multiplier for DDIM (eta)", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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"ddim_discretize": OptionInfo('uniform', "DDIM discretize img2img", gr.Radio, {"choices": ['uniform', 'quad']}),
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@@ -66,10 +66,12 @@ def save_files(js_data, images, do_make_zip, index):
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for image_index, filedata in enumerate(images, start_index):
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image = image_from_url_text(filedata)
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is_grid = image_index < p.index_of_first_image
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i = 0 if is_grid else (image_index - p.index_of_first_image)
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if len(p.all_seeds) <= i:
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p.all_seeds.append(p.seed)
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if len(p.all_prompts) <= i:
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p.all_prompts.append(p.prompt)
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fullfn, txt_fullfn = modules.images.save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
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filename = os.path.relpath(fullfn, path)
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+23
-33
@@ -1,26 +1,18 @@
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import re
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import csv
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import random
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from collections import namedtuple
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from copy import copy
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from itertools import permutations, chain
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import random
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import csv
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from io import StringIO
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from PIL import Image
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import numpy as np
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import modules.scripts as scripts
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import gradio as gr
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from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
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from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
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from modules.shared import opts, cmd_opts, state
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import modules.scripts as scripts
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import modules.shared as shared
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import modules.sd_samplers
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import modules.sd_models
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import modules.sd_vae
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import glob
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import os
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import re
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from modules import images, sd_samplers, processing, sd_models, sd_vae
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from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
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from modules.shared import opts, state
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from modules.ui_components import ToolButton
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fill_values_symbol = "\U0001f4d2" # 📒
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@@ -83,15 +75,15 @@ def confirm_samplers(p, xs):
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def apply_checkpoint(p, x, xs):
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info = modules.sd_models.get_closet_checkpoint_match(x)
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info = sd_models.get_closet_checkpoint_match(x)
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if info is None:
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raise RuntimeError(f"Unknown checkpoint: {x}")
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modules.sd_models.reload_model_weights(shared.sd_model, info)
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sd_models.reload_model_weights(shared.sd_model, info)
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def confirm_checkpoints(p, xs):
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for x in xs:
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if modules.sd_models.get_closet_checkpoint_match(x) is None:
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if sd_models.get_closet_checkpoint_match(x) is None:
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raise RuntimeError(f"Unknown checkpoint: {x}")
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@@ -108,20 +100,20 @@ def apply_upscale_latent_space(p, x, xs):
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def find_vae(name: str):
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if name.lower() in ['auto', 'automatic']:
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return modules.sd_vae.unspecified
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return sd_vae.unspecified
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if name.lower() == 'none':
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return None
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else:
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choices = [x for x in sorted(modules.sd_vae.vae_dict, key=lambda x: len(x)) if name.lower().strip() in x.lower()]
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choices = [x for x in sorted(sd_vae.vae_dict, key=lambda x: len(x)) if name.lower().strip() in x.lower()]
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if len(choices) == 0:
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print(f"No VAE found for {name}; using automatic")
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return modules.sd_vae.unspecified
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return sd_vae.unspecified
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else:
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return modules.sd_vae.vae_dict[choices[0]]
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return sd_vae.vae_dict[choices[0]]
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def apply_vae(p, x, xs):
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modules.sd_vae.reload_vae_weights(shared.sd_model, vae_file=find_vae(x))
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sd_vae.reload_vae_weights(shared.sd_model, vae_file=find_vae(x))
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def apply_styles(p: StableDiffusionProcessingTxt2Img, x: str, _):
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@@ -341,7 +333,6 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
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if draw_legend:
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z_grid = images.draw_grid_annotations(z_grid, sub_grid_size[0], sub_grid_size[1], title_texts, [[images.GridAnnotation()]])
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processed_result.images.insert(0, z_grid)
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#TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
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#processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
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#processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
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processed_result.infotexts.insert(0, processed_result.infotexts[0])
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@@ -354,12 +345,12 @@ class SharedSettingsStackHelper(object):
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self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
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self.vae = opts.sd_vae
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self.uni_pc_order = opts.uni_pc_order
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def __exit__(self, exc_type, exc_value, tb):
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opts.data["sd_vae"] = self.vae
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opts.data["uni_pc_order"] = self.uni_pc_order
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modules.sd_models.reload_model_weights()
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modules.sd_vae.reload_vae_weights()
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sd_models.reload_model_weights()
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sd_vae.reload_vae_weights()
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opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
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@@ -407,7 +398,7 @@ class Script(scripts.Script):
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include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
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with gr.Column():
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margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
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with gr.Row(variant="compact", elem_id="swap_axes"):
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swap_xy_axes_button = gr.Button(value="Swap X/Y axes", elem_id="xy_grid_swap_axes_button")
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swap_yz_axes_button = gr.Button(value="Swap Y/Z axes", elem_id="yz_grid_swap_axes_button")
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@@ -468,7 +459,7 @@ class Script(scripts.Script):
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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, margin_size):
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if not no_fixed_seeds:
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modules.processing.fix_seed(p)
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processing.fix_seed(p)
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if not opts.return_grid:
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p.batch_size = 1
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@@ -498,7 +489,7 @@ class Script(scripts.Script):
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start = int(mc.group(1))
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end = int(mc.group(2))
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num = int(mc.group(3)) if mc.group(3) is not None else 1
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valslist_ext += [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()]
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else:
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valslist_ext.append(val)
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@@ -520,7 +511,7 @@ class Script(scripts.Script):
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start = float(mc.group(1))
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end = float(mc.group(2))
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num = int(mc.group(3)) if mc.group(3) is not None else 1
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valslist_ext += np.linspace(start=start, stop=end, num=num).tolist()
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else:
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valslist_ext.append(val)
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@@ -708,13 +699,12 @@ class Script(scripts.Script):
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# Auto-save main and sub-grids:
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grid_count = z_count + 1 if z_count > 1 else 1
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for g in range(grid_count):
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#TODO: See previous comment about intentional data misalignment.
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adj_g = g-1 if g > 0 else g
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images.save_image(processed.images[g], p.outpath_grids, "xyz_grid", info=processed.infotexts[g], extension=opts.grid_format, prompt=processed.all_prompts[adj_g], seed=processed.all_seeds[adj_g], grid=True, p=processed)
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if not include_sub_grids:
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# Done with sub-grids, drop all related information:
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for sg in range(z_count):
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for _sg in range(z_count):
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del processed.images[1]
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del processed.all_prompts[1]
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del processed.all_seeds[1]
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@@ -679,10 +679,6 @@ footer {
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margin-left: 0.5em;
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}
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.extra-network-cards .card .metadata-button:before, .extra-network-thumbs .card .metadata-button:before{
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content: "🛈";
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}
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.extra-network-cards .card .metadata-button, .extra-network-thumbs .card .metadata-button{
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display: none;
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position: absolute;
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@@ -696,11 +692,11 @@ footer {
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.extra-network-cards .card:hover .metadata-button, .extra-network-thumbs .card:hover .metadata-button{
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display: inline-block;
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}
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.extra-network-cards .card .metadata-button:hover, .extra-network-thumbs .card .metadata-button:hover{
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color: red;
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}
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.extra-network-thumbs {
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display: flex;
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flex-flow: row wrap;
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@@ -708,8 +704,9 @@ footer {
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}
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.extra-network-thumbs .card {
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height: 6em;
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width: 6em;
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display: inline-block;
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height: 9em;
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width: 9em;
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cursor: pointer;
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background-image: url('./file=html/card-no-preview.png');
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background-size: cover;
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@@ -717,23 +714,13 @@ footer {
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position: relative;
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}
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.extra-network-thumbs .card:hover .additional a {
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display: inline-block;
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.extra-network-thumbs .card .additional, .extra-network-thumbs .card .additional {
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white-space: nowrap;
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overflow: hidden;
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}
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.extra-network-thumbs .actions .additional a {
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background-image: url('./file=html/image-update.svg');
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background-repeat: no-repeat;
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background-size: cover;
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background-position: center center;
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position: absolute;
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top: 0;
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left: 0;
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width: 24px;
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height: 24px;
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display: none;
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font-size: 0;
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text-align: -9999;
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.extra-network-thumbs .card:hover .additional a {
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display: inline-block;
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}
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.extra-network-thumbs .actions .name {
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@@ -762,12 +749,10 @@ footer {
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box-shadow: 0 0 5px rgba(128, 128, 128, 0.5);
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border-radius: 0.2em;
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position: relative;
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background-size: auto 100%;
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background-position: center;
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overflow: hidden;
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cursor: pointer;
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background-image: url('./file=html/card-no-preview.png')
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}
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Reference in New Issue
Block a user