diff options
| -rw-r--r-- | extensions-builtin/extra-options-section/scripts/extra_options_section.py | 13 | ||||
| -rw-r--r-- | javascript/extraNetworks.js | 6 | ||||
| -rw-r--r-- | modules/devices.py | 2 | ||||
| -rw-r--r-- | modules/generation_parameters_copypaste.py | 13 | ||||
| -rw-r--r-- | modules/gradio_extensons.py | 10 | ||||
| -rw-r--r-- | modules/mac_specific.py | 15 | ||||
| -rw-r--r-- | modules/processing.py | 4 | ||||
| -rw-r--r-- | modules/sd_hijack.py | 9 | ||||
| -rw-r--r-- | modules/sd_models.py | 17 | ||||
| -rw-r--r-- | modules/shared_items.py | 16 | ||||
| -rw-r--r-- | modules/shared_options.py | 77 | ||||
| -rw-r--r-- | modules/textual_inversion/autocrop.py | 239 | ||||
| -rw-r--r-- | modules/textual_inversion/preprocess.py | 4 | ||||
| -rw-r--r-- | style.css | 2 |
14 files changed, 258 insertions, 169 deletions
diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index 983f87ff..a903df62 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -64,11 +64,14 @@ class ExtraOptionsSection(scripts.Script): p.override_settings[name] = value
-shared.options_templates.update(shared.options_section(('ui', "User interface"), {
- "extra_options_txt2img": shared.OptionInfo([], "Options in main UI - txt2img", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img interfaces").needs_reload_ui(),
- "extra_options_img2img": shared.OptionInfo([], "Options in main UI - img2img", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in img2img interfaces").needs_reload_ui(),
- "extra_options_cols": shared.OptionInfo(1, "Options in main UI - number of columns", gr.Number, {"precision": 0}).needs_reload_ui(),
- "extra_options_accordion": shared.OptionInfo(False, "Options in main UI - place into an accordion").needs_reload_ui()
+shared.options_templates.update(shared.options_section(('settings_in_ui', "Settings in UI", "ui"), {
+ "settings_in_ui": shared.OptionHTML("""
+This page allows you to add some settings to the main interface of txt2img and img2img tabs.
+"""),
+ "extra_options_txt2img": shared.OptionInfo([], "Settings for txt2img", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img interfaces").needs_reload_ui(),
+ "extra_options_img2img": shared.OptionInfo([], "Settings for img2img", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in img2img interfaces").needs_reload_ui(),
+ "extra_options_cols": shared.OptionInfo(1, "Number of columns for added settings", gr.Number, {"precision": 0}).needs_reload_ui(),
+ "extra_options_accordion": shared.OptionInfo(False, "Place added settings into an accordion").needs_reload_ui()
}))
diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js index a787372c..98a7abb7 100644 --- a/javascript/extraNetworks.js +++ b/javascript/extraNetworks.js @@ -392,3 +392,9 @@ function extraNetworksRefreshSingleCard(page, tabname, name) { } }); } + +window.addEventListener("keydown", function(event) { + if (event.key == "Escape") { + closePopup(); + } +}); diff --git a/modules/devices.py b/modules/devices.py index 1d4eb563..f97f9cfb 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -38,7 +38,7 @@ def get_optimal_device(): def get_device_for(task): - if task in shared.cmd_opts.use_cpu: + if task in shared.cmd_opts.use_cpu or "all" in shared.cmd_opts.use_cpu: return cpu return get_optimal_device() diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 0a606515..4efe53e0 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -1,3 +1,4 @@ +from __future__ import annotations
import base64
import io
import json
@@ -15,9 +16,6 @@ re_imagesize = re.compile(r"^(\d+)x(\d+)$") re_hypernet_hash = re.compile("\(([0-9a-f]+)\)$")
type_of_gr_update = type(gr.update())
-paste_fields = {}
-registered_param_bindings = []
-
class ParamBinding:
def __init__(self, paste_button, tabname, source_text_component=None, source_image_component=None, source_tabname=None, override_settings_component=None, paste_field_names=None):
@@ -30,6 +28,10 @@ class ParamBinding: self.paste_field_names = paste_field_names or []
+paste_fields: dict[str, dict] = {}
+registered_param_bindings: list[ParamBinding] = []
+
+
def reset():
paste_fields.clear()
registered_param_bindings.clear()
@@ -113,7 +115,6 @@ def register_paste_params_button(binding: ParamBinding): def connect_paste_params_buttons():
- binding: ParamBinding
for binding in registered_param_bindings:
destination_image_component = paste_fields[binding.tabname]["init_img"]
fields = paste_fields[binding.tabname]["fields"]
@@ -313,6 +314,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "VAE Decoder" not in res:
res["VAE Decoder"] = "Full"
+ skip = set(shared.opts.infotext_skip_pasting)
+ res = {k: v for k, v in res.items() if k not in skip}
+
return res
@@ -443,3 +447,4 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, outputs=[],
show_progress=False,
)
+
diff --git a/modules/gradio_extensons.py b/modules/gradio_extensons.py index e6b6835a..7d88dc98 100644 --- a/modules/gradio_extensons.py +++ b/modules/gradio_extensons.py @@ -47,10 +47,20 @@ def Block_get_config(self): def BlockContext_init(self, *args, **kwargs):
+ if scripts.scripts_current is not None:
+ scripts.scripts_current.before_component(self, **kwargs)
+
+ scripts.script_callbacks.before_component_callback(self, **kwargs)
+
res = original_BlockContext_init(self, *args, **kwargs)
add_classes_to_gradio_component(self)
+ scripts.script_callbacks.after_component_callback(self, **kwargs)
+
+ if scripts.scripts_current is not None:
+ scripts.scripts_current.after_component(self, **kwargs)
+
return res
diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 89256c5b..d96d86d7 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -1,6 +1,7 @@ import logging import torch +from torch import Tensor import platform from modules.sd_hijack_utils import CondFunc from packaging import version @@ -51,6 +52,17 @@ def cumsum_fix(input, cumsum_func, *args, **kwargs): return cumsum_func(input, *args, **kwargs) +# MPS workaround for https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14046 +def interpolate_with_fp32_fallback(orig_func, *args, **kwargs) -> Tensor: + try: + return orig_func(*args, **kwargs) + except RuntimeError as e: + if "not implemented for" in str(e) and "Half" in str(e): + input_tensor = args[0] + return orig_func(input_tensor.to(torch.float32), *args[1:], **kwargs).to(input_tensor.dtype) + else: + print(f"An unexpected RuntimeError occurred: {str(e)}") + if has_mps: if platform.mac_ver()[0].startswith("13.2."): # MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124) @@ -77,6 +89,9 @@ if has_mps: # MPS workaround for https://github.com/pytorch/pytorch/issues/96113 CondFunc('torch.nn.functional.layer_norm', lambda orig_func, x, normalized_shape, weight, bias, eps, **kwargs: orig_func(x.float(), normalized_shape, weight.float() if weight is not None else None, bias.float() if bias is not None else bias, eps).to(x.dtype), lambda _, input, *args, **kwargs: len(args) == 4 and input.device.type == 'mps') + # MPS workaround for https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14046 + CondFunc('torch.nn.functional.interpolate', interpolate_with_fp32_fallback, None) + # MPS workaround for https://github.com/pytorch/pytorch/issues/92311 if platform.processor() == 'i386': for funcName in ['torch.argmax', 'torch.Tensor.argmax']: diff --git a/modules/processing.py b/modules/processing.py index ac58ef86..5ab6ddde 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -679,8 +679,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Size": f"{p.width}x{p.height}",
"Model hash": p.sd_model_hash if opts.add_model_hash_to_info else None,
"Model": p.sd_model_name if opts.add_model_name_to_info else None,
- "VAE hash": p.sd_vae_hash if opts.add_model_hash_to_info else None,
- "VAE": p.sd_vae_name if opts.add_model_name_to_info else None,
+ "VAE hash": p.sd_vae_hash if opts.add_vae_hash_to_info else None,
+ "VAE": p.sd_vae_name if opts.add_vae_name_to_info else None,
"Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
"Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 0157e19f..3d340fc9 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -38,9 +38,6 @@ ldm.models.diffusion.ddpm.print = shared.ldm_print optimizers = []
current_optimizer: sd_hijack_optimizations.SdOptimization = None
-ldm_original_forward = patches.patch(__file__, ldm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
-sgm_original_forward = patches.patch(__file__, sgm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
-
def list_optimizers():
new_optimizers = script_callbacks.list_optimizers_callback()
@@ -258,6 +255,9 @@ class StableDiffusionModelHijack: import modules.models.diffusion.ddpm_edit
+ ldm_original_forward = patches.patch(__file__, ldm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
+ sgm_original_forward = patches.patch(__file__, sgm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
+
if isinstance(m, ldm.models.diffusion.ddpm.LatentDiffusion):
sd_unet.original_forward = ldm_original_forward
elif isinstance(m, modules.models.diffusion.ddpm_edit.LatentDiffusion):
@@ -303,6 +303,9 @@ class StableDiffusionModelHijack: self.layers = None
self.clip = None
+ patches.undo(__file__, ldm.modules.diffusionmodules.openaimodel.UNetModel, "forward")
+ patches.undo(__file__, sgm.modules.diffusionmodules.openaimodel.UNetModel, "forward")
+
sd_unet.original_forward = None
diff --git a/modules/sd_models.py b/modules/sd_models.py index 841402e8..9355f1e1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -230,15 +230,19 @@ def select_checkpoint(): return checkpoint_info
-checkpoint_dict_replacements = {
+checkpoint_dict_replacements_sd1 = {
'cond_stage_model.transformer.embeddings.': 'cond_stage_model.transformer.text_model.embeddings.',
'cond_stage_model.transformer.encoder.': 'cond_stage_model.transformer.text_model.encoder.',
'cond_stage_model.transformer.final_layer_norm.': 'cond_stage_model.transformer.text_model.final_layer_norm.',
}
+checkpoint_dict_replacements_sd2_turbo = { # Converts SD 2.1 Turbo from SGM to LDM format.
+ 'conditioner.embedders.0.': 'cond_stage_model.',
+}
+
-def transform_checkpoint_dict_key(k):
- for text, replacement in checkpoint_dict_replacements.items():
+def transform_checkpoint_dict_key(k, replacements):
+ for text, replacement in replacements.items():
if k.startswith(text):
k = replacement + k[len(text):]
@@ -249,9 +253,14 @@ def get_state_dict_from_checkpoint(pl_sd): pl_sd = pl_sd.pop("state_dict", pl_sd)
pl_sd.pop("state_dict", None)
+ is_sd2_turbo = 'conditioner.embedders.0.model.ln_final.weight' in pl_sd and pl_sd['conditioner.embedders.0.model.ln_final.weight'].size()[0] == 1024
+
sd = {}
for k, v in pl_sd.items():
- new_key = transform_checkpoint_dict_key(k)
+ if is_sd2_turbo:
+ new_key = transform_checkpoint_dict_key(k, checkpoint_dict_replacements_sd2_turbo)
+ else:
+ new_key = transform_checkpoint_dict_key(k, checkpoint_dict_replacements_sd1)
if new_key is not None:
sd[new_key] = v
diff --git a/modules/shared_items.py b/modules/shared_items.py index 5024b426..991971ad 100644 --- a/modules/shared_items.py +++ b/modules/shared_items.py @@ -66,6 +66,22 @@ def reload_hypernetworks(): shared.hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
+def get_infotext_names():
+ from modules import generation_parameters_copypaste, shared
+ res = {}
+
+ for info in shared.opts.data_labels.values():
+ if info.infotext:
+ res[info.infotext] = 1
+
+ for tab_data in generation_parameters_copypaste.paste_fields.values():
+ for _, name in tab_data.get("fields") or []:
+ if isinstance(name, str):
+ res[name] = 1
+
+ return list(res)
+
+
ui_reorder_categories_builtin_items = [
"prompt",
"image",
diff --git a/modules/shared_options.py b/modules/shared_options.py index 04e68a71..1390152d 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -46,8 +46,6 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "grid_text_inactive_color": OptionInfo("#999999", "Inactive text color for image grids", ui_components.FormColorPicker, {}),
"grid_background_color": OptionInfo("#ffffff", "Background color for image grids", ui_components.FormColorPicker, {}),
- "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
- "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
"save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
"save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
@@ -252,47 +250,64 @@ 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),
}))
-options_templates.update(options_section(('ui', "User interface", "ui"), {
- "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_reload_ui(),
- "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
- "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"),
- "gallery_height": OptionInfo("", "Gallery height", gr.Textbox).info("an be any valid CSS value").needs_reload_ui(),
- "return_grid": OptionInfo(True, "Show grid in results for web"),
- "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
- "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
- "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
- "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
- "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
- "js_modal_lightbox_gamepad": OptionInfo(False, "Navigate image viewer with gamepad"),
- "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"),
- "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
+options_templates.update(options_section(('ui_prompt_editing', "Prompt editing", "ui"), {
+ "keyedit_precision_attention": OptionInfo(0.1, "Precision for (attention:1.1) when editing the prompt with Ctrl+up/down", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
+ "keyedit_precision_extra": OptionInfo(0.05, "Precision for <extra networks:0.9> when editing the prompt with Ctrl+up/down", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
+ "keyedit_delimiters": OptionInfo(r".,\/!?%^*;:{}=`~() ", "Word delimiters when editing the prompt with Ctrl+up/down"),
+ "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_reload_ui(),
+}))
+
+options_templates.update(options_section(('ui_gallery', "Gallery", "ui"), {
+ "return_grid": OptionInfo(True, "Show grid in gallery"),
+ "do_not_show_images": OptionInfo(False, "Do not show any images in gallery"),
+ "js_modal_lightbox": OptionInfo(True, "Full page image viewer: enable"),
+ "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Full page image viewer: show images zoomed in by default"),
+ "js_modal_lightbox_gamepad": OptionInfo(False, "Full page image viewer: navigate with gamepad"),
+ "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Full page image viewer: gamepad repeat period").info("in milliseconds"),
+ "gallery_height": OptionInfo("", "Gallery height", gr.Textbox).info("can be any valid CSS value, for example 768px or 20em").needs_reload_ui(),
+}))
+
+options_templates.update(options_section(('ui_alternatives', "UI alternatives", "ui"), {
+ "compact_prompt_box": OptionInfo(False, "Compact prompt layout").info("puts prompt and negative prompt inside the Generate tab, leaving more vertical space for the image on the right").needs_reload_ui(),
"samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group").needs_reload_ui(),
"dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_reload_ui(),
- "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
- "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
- "keyedit_delimiters": OptionInfo(r".,\/!?%^*;:{}=`~() ", "Ctrl+up/down word delimiters"),
- "keyedit_delimiters_whitespace": OptionInfo(["Tab", "Carriage Return", "Line Feed"], "Ctrl+up/down whitespace delimiters", gr.CheckboxGroup, lambda: {"choices": ["Tab", "Carriage Return", "Line Feed"]}),
- "keyedit_move": OptionInfo(True, "Alt+left/right moves prompt elements"),
- "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(),
- "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(),
- "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(),
- "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_reload_ui(),
"sd_checkpoint_dropdown_use_short": OptionInfo(False, "Checkpoint dropdown: use filenames without paths").info("models in subdirectories like photo/sd15.ckpt will be listed as just sd15.ckpt"),
"hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(),
"hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(),
- "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_reload_ui(),
"txt2img_settings_accordion": OptionInfo(False, "Settings in txt2img hidden under Accordion").needs_reload_ui(),
"img2img_settings_accordion": OptionInfo(False, "Settings in img2img hidden under Accordion").needs_reload_ui(),
- "compact_prompt_box": OptionInfo(False, "Compact prompt layout").info("puts prompt and negative prompt inside the Generate tab, leaving more vertical space for the image on the right").needs_reload_ui(),
+}))
+
+options_templates.update(options_section(('ui', "User interface", "ui"), {
+ "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_reload_ui(),
+ "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(),
+ "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(),
+ "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(),
+ "ui_reorder_list": OptionInfo([], "UI item order for txt2img/img2img tabs", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_reload_ui(),
+ "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
+ "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"),
+ "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
+ "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
+ "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
}))
options_templates.update(options_section(('infotext', "Infotext", "ui"), {
- "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
- "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
- "add_user_name_to_info": OptionInfo(False, "Add user name to generation information when authenticated"),
- "add_version_to_infotext": OptionInfo(True, "Add program version to generation information"),
+ "infotext_explanation": OptionHTML("""
+Infotext is what this software calls the text that contains generation parameters and can be used to generate the same picture again.
+It is displayed in UI below the image. To use infotext, paste it into the prompt and click the ↙️ paste button.
+"""),
+ "enable_pnginfo": OptionInfo(True, "Write infotext to metadata of the generated image"),
+ "save_txt": OptionInfo(False, "Create a text file with infotext next to every generated image"),
+
+ "add_model_name_to_info": OptionInfo(True, "Add model name to infotext"),
+ "add_model_hash_to_info": OptionInfo(True, "Add model hash to infotext"),
+ "add_vae_name_to_info": OptionInfo(True, "Add VAE name to infotext"),
+ "add_vae_hash_to_info": OptionInfo(True, "Add VAE hash to infotext"),
+ "add_user_name_to_info": OptionInfo(False, "Add user name to infotext when authenticated"),
+ "add_version_to_infotext": OptionInfo(True, "Add program version to infotext"),
"disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"),
+ "infotext_skip_pasting": OptionInfo([], "Disregard fields from pasted infotext", ui_components.DropdownMulti, lambda: {"choices": shared_items.get_infotext_names()}),
"infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""<ul style='margin-left: 1.5em'>
<li>Ignore: keep prompt and styles dropdown as it is.</li>
<li>Apply: remove style text from prompt, always replace styles dropdown value with found styles (even if none are found).</li>
diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 1675e39a..e223a2e0 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -3,6 +3,8 @@ import requests import os
import numpy as np
from PIL import ImageDraw
+from modules import paths_internal
+from pkg_resources import parse_version
GREEN = "#0F0"
BLUE = "#00F"
@@ -25,7 +27,6 @@ def crop_image(im, settings): elif is_portrait(settings.crop_width, settings.crop_height):
scale_by = settings.crop_height / im.height
-
im = im.resize((int(im.width * scale_by), int(im.height * scale_by)))
im_debug = im.copy()
@@ -69,6 +70,7 @@ def crop_image(im, settings): return results
+
def focal_point(im, settings):
corner_points = image_corner_points(im, settings) if settings.corner_points_weight > 0 else []
entropy_points = image_entropy_points(im, settings) if settings.entropy_points_weight > 0 else []
@@ -78,118 +80,120 @@ def focal_point(im, settings): weight_pref_total = 0
if corner_points:
- weight_pref_total += settings.corner_points_weight
+ weight_pref_total += settings.corner_points_weight
if entropy_points:
- weight_pref_total += settings.entropy_points_weight
+ weight_pref_total += settings.entropy_points_weight
if face_points:
- weight_pref_total += settings.face_points_weight
+ weight_pref_total += settings.face_points_weight
corner_centroid = None
if corner_points:
- corner_centroid = centroid(corner_points)
- corner_centroid.weight = settings.corner_points_weight / weight_pref_total
- pois.append(corner_centroid)
+ corner_centroid = centroid(corner_points)
+ corner_centroid.weight = settings.corner_points_weight / weight_pref_total
+ pois.append(corner_centroid)
entropy_centroid = None
if entropy_points:
- entropy_centroid = centroid(entropy_points)
- entropy_centroid.weight = settings.entropy_points_weight / weight_pref_total
- pois.append(entropy_centroid)
+ entropy_centroid = centroid(entropy_points)
+ entropy_centroid.weight = settings.entropy_points_weight / weight_pref_total
+ pois.append(entropy_centroid)
face_centroid = None
if face_points:
- face_centroid = centroid(face_points)
- face_centroid.weight = settings.face_points_weight / weight_pref_total
- pois.append(face_centroid)
+ face_centroid = centroid(face_points)
+ face_centroid.weight = settings.face_points_weight / weight_pref_total
+ pois.append(face_centroid)
average_point = poi_average(pois, settings)
if settings.annotate_image:
- d = ImageDraw.Draw(im)
- max_size = min(im.width, im.height) * 0.07
- if corner_centroid is not None:
- color = BLUE
- box = corner_centroid.bounding(max_size * corner_centroid.weight)
- d.text((box[0], box[1]-15), f"Edge: {corner_centroid.weight:.02f}", fill=color)
- d.ellipse(box, outline=color)
- if len(corner_points) > 1:
- for f in corner_points:
- d.rectangle(f.bounding(4), outline=color)
- if entropy_centroid is not None:
- color = "#ff0"
- box = entropy_centroid.bounding(max_size * entropy_centroid.weight)
- d.text((box[0], box[1]-15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color)
- d.ellipse(box, outline=color)
- if len(entropy_points) > 1:
- for f in entropy_points:
- d.rectangle(f.bounding(4), outline=color)
- if face_centroid is not None:
- color = RED
- box = face_centroid.bounding(max_size * face_centroid.weight)
- d.text((box[0], box[1]-15), f"Face: {face_centroid.weight:.02f}", fill=color)
- d.ellipse(box, outline=color)
- if len(face_points) > 1:
- for f in face_points:
- d.rectangle(f.bounding(4), outline=color)
-
- d.ellipse(average_point.bounding(max_size), outline=GREEN)
+ d = ImageDraw.Draw(im)
+ max_size = min(im.width, im.height) * 0.07
+ if corner_centroid is not None:
+ color = BLUE
+ box = corner_centroid.bounding(max_size * corner_centroid.weight)
+ d.text((box[0], box[1] - 15), f"Edge: {corner_centroid.weight:.02f}", fill=color)
+ d.ellipse(box, outline=color)
+ if len(corner_points) > 1:
+ for f in corner_points:
+ d.rectangle(f.bounding(4), outline=color)
+ if entropy_centroid is not None:
+ color = "#ff0"
+ box = entropy_centroid.bounding(max_size * entropy_centroid.weight)
+ d.text((box[0], box[1] - 15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color)
+ d.ellipse(box, outline=color)
+ if len(entropy_points) > 1:
+ for f in entropy_points:
+ d.rectangle(f.bounding(4), outline=color)
+ if face_centroid is not None:
+ color = RED
+ box = face_centroid.bounding(max_size * face_centroid.weight)
+ d.text((box[0], box[1] - 15), f"Face: {face_centroid.weight:.02f}", fill=color)
+ d.ellipse(box, outline=color)
+ if len(face_points) > 1:
+ for f in face_points:
+ d.rectangle(f.bounding(4), outline=color)
+
+ d.ellipse(average_point.bounding(max_size), outline=GREEN)
return average_point
def image_face_points(im, settings):
if settings.dnn_model_path is not None:
- detector = cv2.FaceDetectorYN.create(
- settings.dnn_model_path,
- "",
- (im.width, im.height),
- 0.9, # score threshold
- 0.3, # nms threshold
- 5000 # keep top k before nms
- )
- faces = detector.detect(np.array(im))
- results = []
- if faces[1] is not None:
- for face in faces[1]:
- x = face[0]
- y = face[1]
- w = face[2]
- h = face[3]
- results.append(
- PointOfInterest(
- int(x + (w * 0.5)), # face focus left/right is center
- int(y + (h * 0.33)), # face focus up/down is close to the top of the head
- size = w,
- weight = 1/len(faces[1])
- )
- )
- return results
+ detector = cv2.FaceDetectorYN.create(
+ settings.dnn_model_path,
+ "",
+ (im.width, im.height),
+ 0.9, # score threshold
+ 0.3, # nms threshold
+ 5000 # keep top k before nms
+ )
+ faces = detector.detect(np.array(im))
+ results = []
+ if faces[1] is not None:
+ for face in faces[1]:
+ x = face[0]
+ y = face[1]
+ w = face[2]
+ h = face[3]
+ results.append(
+ PointOfInterest(
+ int(x + (w * 0.5)), # face focus left/right is center
+ int(y + (h * 0.33)), # face focus up/down is close to the top of the head
+ size=w,
+ weight=1 / len(faces[1])
+ )
+ )
+ return results
else:
- np_im = np.array(im)
- gray = cv2.cvtColor(np_im, cv2.COLOR_BGR2GRAY)
-
- tries = [
- [ f'{cv2.data.haarcascades}haarcascade_eye.xml', 0.01 ],
- [ f'{cv2.data.haarcascades}haarcascade_frontalface_default.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_profileface.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_frontalface_alt.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_frontalface_alt2.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_frontalface_alt_tree.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_eye_tree_eyeglasses.xml', 0.05 ],
- [ f'{cv2.data.haarcascades}haarcascade_upperbody.xml', 0.05 ]
- ]
- for t in tries:
- classifier = cv2.CascadeClassifier(t[0])
- minsize = int(min(im.width, im.height) * t[1]) # at least N percent of the smallest side
- try:
- faces = classifier.detectMultiScale(gray, scaleFactor=1.1,
- minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE)
- except Exception:
- continue
-
- if faces:
- rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces]
- return [PointOfInterest((r[0] +r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0]-r[2]), weight=1/len(rects)) for r in rects]
+ np_im = np.array(im)
+ gray = cv2.cvtColor(np_im, cv2.COLOR_BGR2GRAY)
+
+ tries = [
+ [f'{cv2.data.haarcascades}haarcascade_eye.xml', 0.01],
+ [f'{cv2.data.haarcascades}haarcascade_frontalface_default.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_profileface.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_frontalface_alt.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_frontalface_alt2.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_frontalface_alt_tree.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_eye_tree_eyeglasses.xml', 0.05],
+ [f'{cv2.data.haarcascades}haarcascade_upperbody.xml', 0.05]
+ ]
+ for t in tries:
+ classifier = cv2.CascadeClassifier(t[0])
+ minsize = int(min(im.width, im.height) * t[1]) # at least N percent of the smallest side
+ try:
+ faces = classifier.detectMultiScale(gray, scaleFactor=1.1,
+ minNeighbors=7, minSize=(minsize, minsize),
+ flags=cv2.CASCADE_SCALE_IMAGE)
+ except Exception:
+ continue
+
+ if faces:
+ rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces]
+ return [PointOfInterest((r[0] + r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0] - r[2]),
+ weight=1 / len(rects)) for r in rects]
return []
@@ -198,7 +202,7 @@ def image_corner_points(im, settings): # naive attempt at preventing focal points from collecting at watermarks near the bottom
gd = ImageDraw.Draw(grayscale)
- gd.rectangle([0, im.height*.9, im.width, im.height], fill="#999")
+ gd.rectangle([0, im.height * .9, im.width, im.height], fill="#999")
np_im = np.array(grayscale)
@@ -206,7 +210,7 @@ def image_corner_points(im, settings): np_im,
maxCorners=100,
qualityLevel=0.04,
- minDistance=min(grayscale.width, grayscale.height)*0.06,
+ minDistance=min(grayscale.width, grayscale.height) * 0.06,
useHarrisDetector=False,
)
@@ -215,8 +219,8 @@ def image_corner_points(im, settings): focal_points = []
for point in points:
- x, y = point.ravel()
- focal_points.append(PointOfInterest(x, y, size=4, weight=1/len(points)))
+ x, y = point.ravel()
+ focal_points.append(PointOfInterest(x, y, size=4, weight=1 / len(points)))
return focal_points
@@ -225,13 +229,13 @@ def image_entropy_points(im, settings): landscape = im.height < im.width
portrait = im.height > im.width
if landscape:
- move_idx = [0, 2]
- move_max = im.size[0]
+ move_idx = [0, 2]
+ move_max = im.size[0]
elif portrait:
- move_idx = [1, 3]
- move_max = im.size[1]
+ move_idx = [1, 3]
+ move_max = im.size[1]
else:
- return []
+ return []
e_max = 0
crop_current = [0, 0, settings.crop_width, settings.crop_height]
@@ -241,14 +245,14 @@ def image_entropy_points(im, settings): e = image_entropy(crop)
if (e > e_max):
- e_max = e
- crop_best = list(crop_current)
+ e_max = e
+ crop_best = list(crop_current)
crop_current[move_idx[0]] += 4
crop_current[move_idx[1]] += 4
- x_mid = int(crop_best[0] + settings.crop_width/2)
- y_mid = int(crop_best[1] + settings.crop_height/2)
+ x_mid = int(crop_best[0] + settings.crop_width / 2)
+ y_mid = int(crop_best[1] + settings.crop_height / 2)
return [PointOfInterest(x_mid, y_mid, size=25, weight=1.0)]
@@ -294,22 +298,23 @@ def is_square(w, h): return w == h
-def download_and_cache_models(dirname):
- download_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
- model_file_name = 'face_detection_yunet.onnx'
+model_dir_opencv = os.path.join(paths_internal.models_path, 'opencv')
+if parse_version(cv2.__version__) >= parse_version('4.8'):
+ model_file_path = os.path.join(model_dir_opencv, 'face_detection_yunet_2023mar.onnx')
+ model_url = 'https://github.com/opencv/opencv_zoo/blob/b6e370b10f641879a87890d44e42173077154a05/models/face_detection_yunet/face_detection_yunet_2023mar.onnx?raw=true'
+else:
+ model_file_path = os.path.join(model_dir_opencv, 'face_detection_yunet.onnx')
+ model_url = 'https://github.com/opencv/opencv_zoo/blob/91fb0290f50896f38a0ab1e558b74b16bc009428/models/face_detection_yunet/face_detection_yunet_2022mar.onnx?raw=true'
- os.makedirs(dirname, exist_ok=True)
- cache_file = os.path.join(dirname, model_file_name)
- if not os.path.exists(cache_file):
- print(f"downloading face detection model from '{download_url}' to '{cache_file}'")
- response = requests.get(download_url)
- with open(cache_file, "wb") as f:
+def download_and_cache_models():
+ if not os.path.exists(model_file_path):
+ os.makedirs(model_dir_opencv, exist_ok=True)
+ print(f"downloading face detection model from '{model_url}' to '{model_file_path}'")
+ response = requests.get(model_url)
+ with open(model_file_path, "wb") as f:
f.write(response.content)
-
- if os.path.exists(cache_file):
- return cache_file
- return None
+ return model_file_path
class PointOfInterest:
diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index dbd856bd..789fa083 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -3,7 +3,7 @@ from PIL import Image, ImageOps import math
import tqdm
-from modules import paths, shared, images, deepbooru
+from modules import shared, images, deepbooru
from modules.textual_inversion import autocrop
@@ -196,7 +196,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre dnn_model_path = None
try:
- dnn_model_path = autocrop.download_and_cache_models(os.path.join(paths.models_path, "opencv"))
+ dnn_model_path = autocrop.download_and_cache_models()
except Exception as e:
print("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", e)
@@ -646,6 +646,8 @@ table.popup-table .link{ margin: auto;
padding: 2em;
z-index: 1001;
+ max-height: 90%;
+ max-width: 90%;
}
/* fullpage image viewer */
|