diff --git a/configs/sd_xl_inpaint.yaml b/configs/sd_xl_inpaint.yaml new file mode 100644 index 000000000..3bad37218 --- /dev/null +++ b/configs/sd_xl_inpaint.yaml @@ -0,0 +1,98 @@ +model: + target: sgm.models.diffusion.DiffusionEngine + params: + scale_factor: 0.13025 + disable_first_stage_autocast: True + + denoiser_config: + target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser + params: + num_idx: 1000 + + weighting_config: + target: sgm.modules.diffusionmodules.denoiser_weighting.EpsWeighting + scaling_config: + target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling + discretization_config: + target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization + + network_config: + target: sgm.modules.diffusionmodules.openaimodel.UNetModel + params: + adm_in_channels: 2816 + num_classes: sequential + use_checkpoint: True + in_channels: 9 + out_channels: 4 + model_channels: 320 + attention_resolutions: [4, 2] + num_res_blocks: 2 + channel_mult: [1, 2, 4] + num_head_channels: 64 + use_spatial_transformer: True + use_linear_in_transformer: True + transformer_depth: [1, 2, 10] # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16 + context_dim: 2048 + spatial_transformer_attn_type: softmax-xformers + legacy: False + + conditioner_config: + target: sgm.modules.GeneralConditioner + params: + emb_models: + # crossattn cond + - is_trainable: False + input_key: txt + target: sgm.modules.encoders.modules.FrozenCLIPEmbedder + params: + layer: hidden + layer_idx: 11 + # crossattn and vector cond + - is_trainable: False + input_key: txt + target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2 + params: + arch: ViT-bigG-14 + version: laion2b_s39b_b160k + freeze: True + layer: penultimate + always_return_pooled: True + legacy: False + # vector cond + - is_trainable: False + input_key: original_size_as_tuple + target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND + params: + outdim: 256 # multiplied by two + # vector cond + - is_trainable: False + input_key: crop_coords_top_left + target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND + params: + outdim: 256 # multiplied by two + # vector cond + - is_trainable: False + input_key: target_size_as_tuple + target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND + params: + outdim: 256 # multiplied by two + + first_stage_config: + target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + attn_type: vanilla-xformers + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: [1, 2, 4, 4] + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py index 985b2753b..72ebd6241 100644 --- a/extensions-builtin/Lora/networks.py +++ b/extensions-builtin/Lora/networks.py @@ -1,3 +1,4 @@ +import gradio as gr import logging import os import re @@ -314,7 +315,12 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No emb_db.skipped_embeddings[name] = embedding if failed_to_load_networks: - sd_hijack.model_hijack.comments.append("Networks not found: " + ", ".join(failed_to_load_networks)) + lora_not_found_message = f'Lora not found: {", ".join(failed_to_load_networks)}' + sd_hijack.model_hijack.comments.append(lora_not_found_message) + if shared.opts.lora_not_found_warning_console: + print(f'\n{lora_not_found_message}\n') + if shared.opts.lora_not_found_gradio_warning: + gr.Warning(lora_not_found_message) purge_networks_from_memory() diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py index ef23968c5..1518f7e5c 100644 --- a/extensions-builtin/Lora/scripts/lora_script.py +++ b/extensions-builtin/Lora/scripts/lora_script.py @@ -39,6 +39,8 @@ shared.options_templates.update(shared.options_section(('extra_networks', "Extra "lora_show_all": shared.OptionInfo(False, "Always show all networks on the Lora page").info("otherwise, those detected as for incompatible version of Stable Diffusion will be hidden"), "lora_hide_unknown_for_versions": shared.OptionInfo([], "Hide networks of unknown versions for model versions", gr.CheckboxGroup, {"choices": ["SD1", "SD2", "SDXL"]}), "lora_in_memory_limit": shared.OptionInfo(0, "Number of Lora networks to keep cached in memory", gr.Number, {"precision": 0}), + "lora_not_found_warning_console": shared.OptionInfo(False, "Lora not found warning in console"), + "lora_not_found_gradio_warning": shared.OptionInfo(False, "Lora not found warning popup in webui"), })) diff --git a/modules/api/api.py b/modules/api/api.py index 45c5c5077..2f718ec26 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -317,8 +317,13 @@ class Api: script_args[script.args_from:script.args_to] = ui_default_values return script_args - def init_script_args(self, request, default_script_args, selectable_scripts, selectable_idx, script_runner): + def init_script_args(self, request, default_script_args, selectable_scripts, selectable_idx, script_runner, *, input_script_args=None): script_args = default_script_args.copy() + + if input_script_args is not None: + for index, value in input_script_args.items(): + script_args[index] = value + # position 0 in script_arg is the idx+1 of the selectable script that is going to be run when using scripts.scripts_*2img.run() if selectable_scripts: script_args[selectable_scripts.args_from:selectable_scripts.args_to] = request.script_args @@ -340,14 +345,88 @@ class Api: script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx] return script_args + def apply_infotext(self, request, tabname, *, script_runner=None, mentioned_script_args=None): + """Processes `infotext` field from the `request`, and sets other fields of the `request` accoring to what's in infotext. + + If request already has a field set, and that field is encountered in infotext too, the value from infotext is ignored. + + Additionally, fills `mentioned_script_args` dict with index: value pairs for script arguments read from infotext. + """ + + if not request.infotext: + return {} + + possible_fields = generation_parameters_copypaste.paste_fields[tabname]["fields"] + set_fields = request.model_dump(exclude_unset=True) if hasattr(request, "request") else request.dict(exclude_unset=True) # pydantic v1/v2 have differenrt names for this + params = generation_parameters_copypaste.parse_generation_parameters(request.infotext) + + def get_field_value(field, params): + value = field.function(params) if field.function else params.get(field.label) + if value is None: + return None + + if field.api in request.__fields__: + target_type = request.__fields__[field.api].type_ + else: + target_type = type(field.component.value) + + if target_type == type(None): + return None + + if isinstance(value, dict) and value.get('__type__') == 'generic_update': # this is a gradio.update rather than a value + value = value.get('value') + + if value is not None and not isinstance(value, target_type): + value = target_type(value) + + return value + + for field in possible_fields: + if not field.api: + continue + + if field.api in set_fields: + continue + + value = get_field_value(field, params) + if value is not None: + setattr(request, field.api, value) + + if request.override_settings is None: + request.override_settings = {} + + overriden_settings = generation_parameters_copypaste.get_override_settings(params) + for _, setting_name, value in overriden_settings: + if setting_name not in request.override_settings: + request.override_settings[setting_name] = value + + if script_runner is not None and mentioned_script_args is not None: + indexes = {v: i for i, v in enumerate(script_runner.inputs)} + script_fields = ((field, indexes[field.component]) for field in possible_fields if field.component in indexes) + + for field, index in script_fields: + value = get_field_value(field, params) + + if value is None: + continue + + mentioned_script_args[index] = value + + return params + def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI): task_id = txt2imgreq.force_task_id or create_task_id("txt2img") script_runner = scripts.scripts_txt2img + with self.txt2img_script_arg_init_lock: if not script_runner.scripts: script_runner.initialize_scripts(False) ui.create_ui() + + infotext_script_args = {} + self.apply_infotext(txt2imgreq, "txt2img", script_runner=script_runner, mentioned_script_args=infotext_script_args) + if not self.default_script_arg_txt2img: self.default_script_arg_txt2img = self.init_default_script_args(script_runner) selectable_scripts, selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner) @@ -364,8 +443,9 @@ class Api: args.pop('script_name', None) args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them args.pop('alwayson_scripts', None) + args.pop('infotext', None) - script_args = self.init_script_args(txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner) + script_args = self.init_script_args(txt2imgreq, self.default_script_arg_txt2img, selectable_scripts, selectable_script_idx, script_runner, input_script_args=infotext_script_args) send_images = args.pop('send_images', True) args.pop('save_images', None) @@ -409,10 +489,15 @@ class Api: mask = decode_base64_to_image(mask) script_runner = scripts.scripts_img2img + with self.img2img_script_arg_init_lock: if not script_runner.scripts: script_runner.initialize_scripts(True) ui.create_ui() + + infotext_script_args = {} + self.apply_infotext(img2imgreq, "img2img", script_runner=script_runner, mentioned_script_args=infotext_script_args) + if not self.default_script_arg_img2img: self.default_script_arg_img2img = self.init_default_script_args(script_runner) selectable_scripts, selectable_script_idx = self.get_selectable_script(img2imgreq.script_name, script_runner) @@ -432,7 +517,7 @@ class Api: args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them args.pop('alwayson_scripts', None) - script_args = self.init_script_args(img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner) + script_args = self.init_script_args(img2imgreq, self.default_script_arg_img2img, selectable_scripts, selectable_script_idx, script_runner, input_script_args=infotext_script_args) send_images = args.pop('send_images', True) args.pop('save_images', None) diff --git a/modules/api/models.py b/modules/api/models.py index 58083a34f..16edf11cf 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -108,6 +108,7 @@ StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator( {"key": "save_images", "type": bool, "default": False}, {"key": "alwayson_scripts", "type": dict, "default": {}}, {"key": "force_task_id", "type": str, "default": None}, + {"key": "infotext", "type": str, "default": None}, ] ).generate_model() @@ -126,6 +127,7 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator( {"key": "save_images", "type": bool, "default": False}, {"key": "alwayson_scripts", "type": dict, "default": {}}, {"key": "force_task_id", "type": str, "default": None}, + {"key": "infotext", "type": str, "default": None}, ] ).generate_model() diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index dbffe4949..86a36c327 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -28,6 +28,19 @@ class ParamBinding: self.paste_field_names = paste_field_names or [] +class PasteField(tuple): + def __new__(cls, component, target, *, api=None): + return super().__new__(cls, (component, target)) + + def __init__(self, component, target, *, api=None): + super().__init__() + + self.api = api + self.component = component + self.label = target if isinstance(target, str) else None + self.function = target if callable(target) else None + + paste_fields: dict[str, dict] = {} registered_param_bindings: list[ParamBinding] = [] @@ -84,6 +97,12 @@ def image_from_url_text(filedata): def add_paste_fields(tabname, init_img, fields, override_settings_component=None): + + if fields: + for i in range(len(fields)): + if not isinstance(fields[i], PasteField): + fields[i] = PasteField(*fields[i]) + paste_fields[tabname] = {"init_img": init_img, "fields": fields, "override_settings_component": override_settings_component} # backwards compatibility for existing extensions @@ -371,6 +390,48 @@ def create_override_settings_dict(text_pairs): return res +def get_override_settings(params, *, skip_fields=None): + """Returns a list of settings overrides from the infotext parameters dictionary. + + This function checks the `params` dictionary for any keys that correspond to settings in `shared.opts` and returns + a list of tuples containing the parameter name, setting name, and new value cast to correct type. + + It checks for conditions before adding an override: + - ignores settings that match the current value + - ignores parameter keys present in skip_fields argument. + + Example input: + {"Clip skip": "2"} + + Example output: + [("Clip skip", "CLIP_stop_at_last_layers", 2)] + """ + + res = [] + + mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] + for param_name, setting_name in mapping + infotext_to_setting_name_mapping: + if param_name in (skip_fields or {}): + continue + + v = params.get(param_name, None) + if v is None: + continue + + if setting_name == "sd_model_checkpoint" and shared.opts.disable_weights_auto_swap: + continue + + v = shared.opts.cast_value(setting_name, v) + current_value = getattr(shared.opts, setting_name, None) + + if v == current_value: + continue + + res.append((param_name, setting_name, v)) + + return res + + def connect_paste(button, paste_fields, input_comp, override_settings_component, tabname): def paste_func(prompt): if not prompt and not shared.cmd_opts.hide_ui_dir_config: @@ -412,29 +473,9 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, already_handled_fields = {key: 1 for _, key in paste_fields} def paste_settings(params): - vals = {} + vals = get_override_settings(params, skip_fields=already_handled_fields) - mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] - for param_name, setting_name in mapping + infotext_to_setting_name_mapping: - if param_name in already_handled_fields: - continue - - v = params.get(param_name, None) - if v is None: - continue - - if setting_name == "sd_model_checkpoint" and shared.opts.disable_weights_auto_swap: - continue - - v = shared.opts.cast_value(setting_name, v) - current_value = getattr(shared.opts, setting_name, None) - - if v == current_value: - continue - - vals[param_name] = v - - vals_pairs = [f"{k}: {v}" for k, v in vals.items()] + vals_pairs = [f"{infotext_text}: {value}" for infotext_text, setting_name, value in vals] return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=bool(vals_pairs)) diff --git a/modules/paths_internal.py b/modules/paths_internal.py index 89131a54f..b86ecd7f1 100644 --- a/modules/paths_internal.py +++ b/modules/paths_internal.py @@ -28,5 +28,6 @@ models_path = os.path.join(data_path, "models") extensions_dir = os.path.join(data_path, "extensions") extensions_builtin_dir = os.path.join(script_path, "extensions-builtin") config_states_dir = os.path.join(script_path, "config_states") +default_output_dir = os.path.join(data_path, "output") roboto_ttf_file = os.path.join(modules_path, 'Roboto-Regular.ttf') diff --git a/modules/processing.py b/modules/processing.py index 9351e3fb0..7789f9a42 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -113,6 +113,21 @@ def txt2img_image_conditioning(sd_model, x, width, height): return x.new_zeros(x.shape[0], 2*sd_model.noise_augmentor.time_embed.dim, dtype=x.dtype, device=x.device) else: + sd = sd_model.model.state_dict() + diffusion_model_input = sd.get('diffusion_model.input_blocks.0.0.weight', None) + if diffusion_model_input is not None: + if diffusion_model_input.shape[1] == 9: + # The "masked-image" in this case will just be all 0.5 since the entire image is masked. + image_conditioning = torch.ones(x.shape[0], 3, height, width, device=x.device) * 0.5 + image_conditioning = images_tensor_to_samples(image_conditioning, + approximation_indexes.get(opts.sd_vae_encode_method)) + + # Add the fake full 1s mask to the first dimension. + image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0) + image_conditioning = image_conditioning.to(x.dtype) + + return image_conditioning + # Dummy zero conditioning if we're not using inpainting or unclip models. # Still takes up a bit of memory, but no encoder call. # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size. @@ -371,6 +386,12 @@ class StableDiffusionProcessing: if self.sampler.conditioning_key == "crossattn-adm": return self.unclip_image_conditioning(source_image) + sd = self.sampler.model_wrap.inner_model.model.state_dict() + diffusion_model_input = sd.get('diffusion_model.input_blocks.0.0.weight', None) + if diffusion_model_input is not None: + if diffusion_model_input.shape[1] == 9: + return self.inpainting_image_conditioning(source_image, latent_image, image_mask=image_mask) + # Dummy zero conditioning if we're not using inpainting or depth model. return latent_image.new_zeros(latent_image.shape[0], 5, 1, 1) @@ -1135,7 +1156,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: - if self.hr_checkpoint_name: + if self.hr_checkpoint_name and self.hr_checkpoint_name != 'Use same checkpoint': self.hr_checkpoint_info = sd_models.get_closet_checkpoint_match(self.hr_checkpoint_name) if self.hr_checkpoint_info is None: @@ -1482,7 +1503,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): # Save init image if opts.save_init_img: self.init_img_hash = hashlib.md5(img.tobytes()).hexdigest() - images.save_image(img, path=opts.outdir_init_images, basename=None, forced_filename=self.init_img_hash, save_to_dirs=False) + images.save_image(img, path=opts.outdir_init_images, basename=None, forced_filename=self.init_img_hash, save_to_dirs=False, existing_info=img.info) image = images.flatten(img, opts.img2img_background_color) diff --git a/modules/processing_scripts/refiner.py b/modules/processing_scripts/refiner.py index 29ccb78f9..cefad32b7 100644 --- a/modules/processing_scripts/refiner.py +++ b/modules/processing_scripts/refiner.py @@ -1,6 +1,7 @@ import gradio as gr from modules import scripts, sd_models +from modules.generation_parameters_copypaste import PasteField from modules.ui_common import create_refresh_button from modules.ui_components import InputAccordion @@ -31,9 +32,9 @@ class ScriptRefiner(scripts.ScriptBuiltinUI): return None if info is None else info.title self.infotext_fields = [ - (enable_refiner, lambda d: 'Refiner' in d), - (refiner_checkpoint, lambda d: lookup_checkpoint(d.get('Refiner'))), - (refiner_switch_at, 'Refiner switch at'), + PasteField(enable_refiner, lambda d: 'Refiner' in d), + PasteField(refiner_checkpoint, lambda d: lookup_checkpoint(d.get('Refiner')), api="refiner_checkpoint"), + PasteField(refiner_switch_at, 'Refiner switch at', api="refiner_switch_at"), ] return enable_refiner, refiner_checkpoint, refiner_switch_at diff --git a/modules/processing_scripts/seed.py b/modules/processing_scripts/seed.py index dc9c2da50..a3e16a12e 100644 --- a/modules/processing_scripts/seed.py +++ b/modules/processing_scripts/seed.py @@ -3,6 +3,7 @@ import json import gradio as gr from modules import scripts, ui, errors +from modules.generation_parameters_copypaste import PasteField from modules.shared import cmd_opts from modules.ui_components import ToolButton @@ -51,12 +52,12 @@ class ScriptSeed(scripts.ScriptBuiltinUI): seed_checkbox.change(lambda x: gr.update(visible=x), show_progress=False, inputs=[seed_checkbox], outputs=[seed_extras]) self.infotext_fields = [ - (self.seed, "Seed"), - (seed_checkbox, lambda d: "Variation seed" in d or "Seed resize from-1" in d), - (subseed, "Variation seed"), - (subseed_strength, "Variation seed strength"), - (seed_resize_from_w, "Seed resize from-1"), - (seed_resize_from_h, "Seed resize from-2"), + PasteField(self.seed, "Seed", api="seed"), + PasteField(seed_checkbox, lambda d: "Variation seed" in d or "Seed resize from-1" in d), + PasteField(subseed, "Variation seed", api="subseed"), + PasteField(subseed_strength, "Variation seed strength", api="subseed_strength"), + PasteField(seed_resize_from_w, "Seed resize from-1", api="seed_resize_from_h"), + PasteField(seed_resize_from_h, "Seed resize from-2", api="seed_resize_from_w"), ] self.on_after_component(lambda x: connect_reuse_seed(self.seed, reuse_seed, x.component, False), elem_id=f'generation_info_{self.tabname}') diff --git a/modules/scripts.py b/modules/scripts.py index b6fcf96e0..3a7669118 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -566,7 +566,12 @@ class ScriptRunner: auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data() for script_data in auto_processing_scripts + scripts_data: - script = script_data.script_class() + try: + script = script_data.script_class() + except Exception: + errors.report(f"Error # failed to initialize Script {script_data.module}: ", exc_info=True) + continue + script.filename = script_data.path script.is_txt2img = not is_img2img script.is_img2img = is_img2img diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index deab2f6e2..b38137eb5 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -15,6 +15,7 @@ config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml") config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml") config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml") config_sdxl_refiner = os.path.join(sd_xl_repo_configs_path, "sd_xl_refiner.yaml") +config_sdxl_inpainting = os.path.join(sd_configs_path, "sd_xl_inpaint.yaml") config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml") config_unclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-l-inference.yaml") config_unopenclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-h-inference.yaml") @@ -71,7 +72,10 @@ def guess_model_config_from_state_dict(sd, filename): sd2_variations_weight = sd.get('embedder.model.ln_final.weight', None) if sd.get('conditioner.embedders.1.model.ln_final.weight', None) is not None: - return config_sdxl + if diffusion_model_input.shape[1] == 9: + return config_sdxl_inpainting + else: + return config_sdxl if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None: return config_sdxl_refiner elif sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None: diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index 11259a369..1de31b0da 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -34,6 +34,12 @@ def get_learned_conditioning(self: sgm.models.diffusion.DiffusionEngine, batch: def apply_model(self: sgm.models.diffusion.DiffusionEngine, x, t, cond): + sd = self.model.state_dict() + diffusion_model_input = sd.get('diffusion_model.input_blocks.0.0.weight', None) + if diffusion_model_input is not None: + if diffusion_model_input.shape[1] == 9: + x = torch.cat([x] + cond['c_concat'], dim=1) + return self.model(x, t, cond) diff --git a/modules/shared_options.py b/modules/shared_options.py index fa542ba8c..752a4f125 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -1,7 +1,8 @@ +import os import gradio as gr -from modules import localization, ui_components, shared_items, shared, interrogate, shared_gradio_themes -from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 +from modules import localization, ui_components, shared_items, shared, interrogate, shared_gradio_themes, util +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir, default_output_dir # noqa: F401 from modules.shared_cmd_options import cmd_opts from modules.options import options_section, OptionInfo, OptionHTML, categories @@ -74,14 +75,14 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" options_templates.update(options_section(('saving-paths', "Paths for saving", "saving"), { "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs), - "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs), - "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs), - "outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs), + "outdir_txt2img_samples": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'txt2img-images')), 'Output directory for txt2img images', component_args=hide_dirs), + "outdir_img2img_samples": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'img2img-images')), 'Output directory for img2img images', component_args=hide_dirs), + "outdir_extras_samples": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'extras-images')), 'Output directory for images from extras tab', component_args=hide_dirs), "outdir_grids": OptionInfo("", "Output directory for grids; if empty, defaults to two directories below", component_args=hide_dirs), - "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs), - "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs), - "outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs), - "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs), + "outdir_txt2img_grids": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'txt2img-grids')), 'Output directory for txt2img grids', component_args=hide_dirs), + "outdir_img2img_grids": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'img2img-grids')), 'Output directory for img2img grids', component_args=hide_dirs), + "outdir_save": OptionInfo(util.truncate_path(os.path.join(data_path, 'log', 'images')), "Directory for saving images using the Save button", component_args=hide_dirs), + "outdir_init_images": OptionInfo(util.truncate_path(os.path.join(default_output_dir, 'init-images')), "Directory for saving init images when using img2img", component_args=hide_dirs), })) options_templates.update(options_section(('saving-to-dirs', "Saving to a directory", "saving"), { diff --git a/modules/ui.py b/modules/ui.py index d80486dd4..9db2407ed 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -28,7 +28,7 @@ import modules.textual_inversion.textual_inversion as textual_inversion import modules.shared as shared from modules import prompt_parser from modules.sd_hijack import model_hijack -from modules.generation_parameters_copypaste import image_from_url_text +from modules.generation_parameters_copypaste import image_from_url_text, PasteField create_setting_component = ui_settings.create_setting_component @@ -436,28 +436,28 @@ def create_ui(): ) txt2img_paste_fields = [ - (toprow.prompt, "Prompt"), - (toprow.negative_prompt, "Negative prompt"), - (steps, "Steps"), - (sampler_name, "Sampler"), - (cfg_scale, "CFG scale"), - (width, "Size-1"), - (height, "Size-2"), - (batch_size, "Batch size"), - (toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), - (denoising_strength, "Denoising strength"), - (enable_hr, lambda d: "Denoising strength" in d and ("Hires upscale" in d or "Hires upscaler" in d or "Hires resize-1" in d)), - (hr_scale, "Hires upscale"), - (hr_upscaler, "Hires upscaler"), - (hr_second_pass_steps, "Hires steps"), - (hr_resize_x, "Hires resize-1"), - (hr_resize_y, "Hires resize-2"), - (hr_checkpoint_name, "Hires checkpoint"), - (hr_sampler_name, "Hires sampler"), - (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" or d.get("Hires checkpoint", "Use same checkpoint") != "Use same checkpoint" else gr.update()), - (hr_prompt, "Hires prompt"), - (hr_negative_prompt, "Hires negative prompt"), - (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), + PasteField(toprow.prompt, "Prompt", api="prompt"), + PasteField(toprow.negative_prompt, "Negative prompt", api="negative_prompt"), + PasteField(steps, "Steps", api="steps"), + PasteField(sampler_name, "Sampler", api="sampler_name"), + PasteField(cfg_scale, "CFG scale", api="cfg_scale"), + PasteField(width, "Size-1", api="width"), + PasteField(height, "Size-2", api="height"), + PasteField(batch_size, "Batch size", api="batch_size"), + PasteField(toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update(), api="styles"), + PasteField(denoising_strength, "Denoising strength", api="denoising_strength"), + PasteField(enable_hr, lambda d: "Denoising strength" in d and ("Hires upscale" in d or "Hires upscaler" in d or "Hires resize-1" in d), api="enable_hr"), + PasteField(hr_scale, "Hires upscale", api="hr_scale"), + PasteField(hr_upscaler, "Hires upscaler", api="hr_upscaler"), + PasteField(hr_second_pass_steps, "Hires steps", api="hr_second_pass_steps"), + PasteField(hr_resize_x, "Hires resize-1", api="hr_resize_x"), + PasteField(hr_resize_y, "Hires resize-2", api="hr_resize_y"), + PasteField(hr_checkpoint_name, "Hires checkpoint", api="hr_checkpoint_name"), + PasteField(hr_sampler_name, "Hires sampler", api="hr_sampler_name"), + PasteField(hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" or d.get("Hires checkpoint", "Use same checkpoint") != "Use same checkpoint" else gr.update()), + PasteField(hr_prompt, "Hires prompt", api="hr_prompt"), + PasteField(hr_negative_prompt, "Hires negative prompt", api="hr_negative_prompt"), + PasteField(hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), *scripts.scripts_txt2img.infotext_fields ] parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings) diff --git a/modules/ui_gradio_extensions.py b/modules/ui_gradio_extensions.py index 0d368f8b2..a86c368ef 100644 --- a/modules/ui_gradio_extensions.py +++ b/modules/ui_gradio_extensions.py @@ -1,17 +1,12 @@ import os import gradio as gr -from modules import localization, shared, scripts -from modules.paths import script_path, data_path, cwd +from modules import localization, shared, scripts, util +from modules.paths import script_path, data_path def webpath(fn): - if fn.startswith(cwd): - web_path = os.path.relpath(fn, cwd) - else: - web_path = os.path.abspath(fn) - - return f'file={web_path}?{os.path.getmtime(fn)}' + return f'file={util.truncate_path(fn)}?{os.path.getmtime(fn)}' def javascript_html(): diff --git a/modules/util.py b/modules/util.py index 60afc0670..4861bcb08 100644 --- a/modules/util.py +++ b/modules/util.py @@ -2,7 +2,7 @@ import os import re from modules import shared -from modules.paths_internal import script_path +from modules.paths_internal import script_path, cwd def natural_sort_key(s, regex=re.compile('([0-9]+)')): @@ -56,3 +56,13 @@ def ldm_print(*args, **kwargs): return print(*args, **kwargs) + + +def truncate_path(target_path, base_path=cwd): + abs_target, abs_base = os.path.abspath(target_path), os.path.abspath(base_path) + try: + if os.path.commonpath([abs_target, abs_base]) == abs_base: + return os.path.relpath(abs_target, abs_base) + except ValueError: + pass + return abs_target diff --git a/scripts/postprocessing_caption.py b/scripts/postprocessing_caption.py index 9482a03ca..5592a8987 100644 --- a/scripts/postprocessing_caption.py +++ b/scripts/postprocessing_caption.py @@ -4,7 +4,7 @@ import gradio as gr class ScriptPostprocessingCeption(scripts_postprocessing.ScriptPostprocessing): name = "Caption" - order = 4000 + order = 4040 def ui(self): with ui_components.InputAccordion(False, label="Caption") as enable: diff --git a/scripts/postprocessing_create_flipped_copies.py b/scripts/postprocessing_create_flipped_copies.py index 3425571dc..b673003b6 100644 --- a/scripts/postprocessing_create_flipped_copies.py +++ b/scripts/postprocessing_create_flipped_copies.py @@ -6,7 +6,7 @@ import gradio as gr class ScriptPostprocessingCreateFlippedCopies(scripts_postprocessing.ScriptPostprocessing): name = "Create flipped copies" - order = 4000 + order = 4030 def ui(self): with ui_components.InputAccordion(False, label="Create flipped copies") as enable: diff --git a/scripts/postprocessing_focal_crop.py b/scripts/postprocessing_focal_crop.py index d3baf2987..cff1dbc54 100644 --- a/scripts/postprocessing_focal_crop.py +++ b/scripts/postprocessing_focal_crop.py @@ -7,7 +7,7 @@ from modules.textual_inversion import autocrop class ScriptPostprocessingFocalCrop(scripts_postprocessing.ScriptPostprocessing): name = "Auto focal point crop" - order = 4000 + order = 4010 def ui(self): with ui_components.InputAccordion(False, label="Auto focal point crop") as enable: diff --git a/scripts/processing_autosized_crop.py b/scripts/processing_autosized_crop.py index c09802264..7e6749898 100644 --- a/scripts/processing_autosized_crop.py +++ b/scripts/processing_autosized_crop.py @@ -28,7 +28,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr class ScriptPostprocessingAutosizedCrop(scripts_postprocessing.ScriptPostprocessing): name = "Auto-sized crop" - order = 4000 + order = 4020 def ui(self): with ui_components.InputAccordion(False, label="Auto-sized crop") as enable: diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index b2250c04d..e5083874a 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -476,6 +476,8 @@ class Script(scripts.Script): fill_z_button.click(fn=fill, inputs=[z_type, csv_mode], outputs=[z_values, z_values_dropdown]) def select_axis(axis_type, axis_values, axis_values_dropdown, csv_mode): + axis_type = axis_type or 0 # if axle type is None set to 0 + choices = self.current_axis_options[axis_type].choices has_choices = choices is not None @@ -526,6 +528,8 @@ class Script(scripts.Script): 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, 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, margin_size, csv_mode): + 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: modules.processing.fix_seed(p) diff --git a/webui.py b/webui.py index 9ed20b306..2c417168a 100644 --- a/webui.py +++ b/webui.py @@ -39,7 +39,7 @@ def api_only(): print(f"Startup time: {startup_timer.summary()}.") api.launch( - server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", + server_name=initialize_util.gradio_server_name(), port=cmd_opts.port if cmd_opts.port else 7861, root_path=f"/{cmd_opts.subpath}" if cmd_opts.subpath else "" )