Merge branch 'master' into esrgan_mod
This commit is contained in:
commit
53154ba10a
6 changed files with 13 additions and 10 deletions
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@ -49,15 +49,18 @@ def list_hypernetworks(path):
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def load_hypernetwork(filename):
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def load_hypernetwork(filename):
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print(f"Loading hypernetwork {filename}")
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path = shared.hypernetworks.get(filename, None)
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path = shared.hypernetworks.get(filename, None)
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if (path is not None):
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if path is not None:
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print(f"Loading hypernetwork {filename}")
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try:
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try:
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shared.loaded_hypernetwork = Hypernetwork(path)
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shared.loaded_hypernetwork = Hypernetwork(path)
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except Exception:
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except Exception:
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print(f"Error loading hypernetwork {path}", file=sys.stderr)
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print(f"Error loading hypernetwork {path}", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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else:
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else:
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if shared.loaded_hypernetwork is not None:
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print(f"Unloading hypernetwork")
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shared.loaded_hypernetwork = None
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shared.loaded_hypernetwork = None
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@ -284,6 +284,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
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"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
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"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
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"Size": f"{p.width}x{p.height}",
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"Size": f"{p.width}x{p.height}",
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"Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
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"Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
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"Model": (None if not opts.add_model_name_to_info or not shared.sd_model.sd_checkpoint_info.model_name else shared.sd_model.sd_checkpoint_info.model_name.replace(',', '').replace(':', '')),
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"Hypernet": (None if shared.loaded_hypernetwork is None else shared.loaded_hypernetwork.name.replace(',', '').replace(':', '')),
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"Batch size": (None if p.batch_size < 2 else p.batch_size),
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"Batch size": (None if p.batch_size < 2 else p.batch_size),
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"Batch pos": (None if p.batch_size < 2 else position_in_batch),
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"Batch pos": (None if p.batch_size < 2 else position_in_batch),
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"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
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"Variation seed": (None if p.subseed_strength == 0 else all_subseeds[index]),
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@ -5,7 +5,6 @@ from collections import namedtuple
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import torch
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import torch
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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from ldm.util import instantiate_from_config
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from ldm.util import instantiate_from_config
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from modules import shared, modelloader, devices
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from modules import shared, modelloader, devices
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@ -242,6 +242,7 @@ options_templates.update(options_section(('ui', "User interface"), {
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"return_grid": OptionInfo(True, "Show grid in results for web"),
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"return_grid": OptionInfo(True, "Show grid in results for web"),
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"do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
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"do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
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"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
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"add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
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"add_model_name_to_info": OptionInfo(False, "Add model name to generation information"),
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"font": OptionInfo("", "Font for image grids that have text"),
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"font": OptionInfo("", "Font for image grids that have text"),
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"js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
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"js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
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"js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
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"js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
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@ -37,7 +37,7 @@ class Upscaler:
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self.pre_pad = 0
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self.pre_pad = 0
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self.mod_scale = None
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self.mod_scale = None
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if self.model_path is not None and self.name:
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if self.model_path is None and self.name:
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self.model_path = os.path.join(models_path, self.name)
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self.model_path = os.path.join(models_path, self.name)
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if self.model_path and create_dirs:
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if self.model_path and create_dirs:
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os.makedirs(self.model_path, exist_ok=True)
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os.makedirs(self.model_path, exist_ok=True)
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@ -10,7 +10,7 @@ import numpy as np
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import modules.scripts as scripts
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import modules.scripts as scripts
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import gradio as gr
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import gradio as gr
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from modules import images
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from modules import images, hypernetwork
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from modules.processing import process_images, Processed, get_correct_sampler
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from modules.processing import process_images, Processed, get_correct_sampler
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from modules.shared import opts, cmd_opts, state
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from modules.shared import opts, cmd_opts, state
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import modules.shared as shared
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import modules.shared as shared
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@ -80,8 +80,7 @@ def apply_checkpoint(p, x, xs):
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def apply_hypernetwork(p, x, xs):
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def apply_hypernetwork(p, x, xs):
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hn = shared.hypernetworks.get(x, None)
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hypernetwork.load_hypernetwork(x)
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opts.data["sd_hypernetwork"] = hn.name if hn is not None else 'None'
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def format_value_add_label(p, opt, x):
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def format_value_add_label(p, opt, x):
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@ -203,8 +202,6 @@ class Script(scripts.Script):
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p.batch_size = 1
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p.batch_size = 1
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initial_hn = opts.sd_hypernetwork
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def process_axis(opt, vals):
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def process_axis(opt, vals):
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if opt.label == 'Nothing':
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if opt.label == 'Nothing':
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return [0]
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return [0]
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@ -262,6 +259,7 @@ class Script(scripts.Script):
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# Confirm options are valid before starting
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# Confirm options are valid before starting
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if opt.label == "Sampler":
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if opt.label == "Sampler":
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samplers_dict = build_samplers_dict(p)
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for sampler_val in valslist:
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for sampler_val in valslist:
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if sampler_val.lower() not in samplers_dict.keys():
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if sampler_val.lower() not in samplers_dict.keys():
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raise RuntimeError(f"Unknown sampler: {sampler_val}")
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raise RuntimeError(f"Unknown sampler: {sampler_val}")
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@ -321,6 +319,6 @@ class Script(scripts.Script):
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# restore checkpoint in case it was changed by axes
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# restore checkpoint in case it was changed by axes
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modules.sd_models.reload_model_weights(shared.sd_model)
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modules.sd_models.reload_model_weights(shared.sd_model)
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opts.data["sd_hypernetwork"] = initial_hn
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hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
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return processed
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return processed
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