diff --git a/args_manager.py b/args_manager.py index 6a3ae9dc..e023da27 100644 --- a/args_manager.py +++ b/args_manager.py @@ -31,6 +31,9 @@ args_parser.parser.add_argument("--disable-metadata", action='store_true', args_parser.parser.add_argument("--disable-preset-download", action='store_true', help="Disables downloading models for presets", default=False) +args_parser.parser.add_argument("--enable-describe-uov-image", action='store_true', + help="Disables automatic description of uov images when prompt is empty", default=False) + args_parser.parser.add_argument("--always-download-new-model", action='store_true', help="Always download newer models ", default=False) diff --git a/css/style.css b/css/style.css index c702a725..b9e6e2ce 100644 --- a/css/style.css +++ b/css/style.css @@ -391,6 +391,6 @@ progress::after { background-color: #fff8; font-family: monospace; text-align: center; - border-radius-top: 5px; + border-radius: 5px 5px 0px 0px; display: none; /* remove this to enable tooltip in preview image */ } \ No newline at end of file diff --git a/docker.md b/docker.md index 36cfa632..1939d6fc 100644 --- a/docker.md +++ b/docker.md @@ -54,6 +54,7 @@ Docker specified environments are there. They are used by 'entrypoint.sh' |CMDARGS|Arguments for [entry_with_update.py](entry_with_update.py) which is called by [entrypoint.sh](entrypoint.sh)| |config_path|'config.txt' location| |config_example_path|'config_modification_tutorial.txt' location| +|HF_MIRROR| huggingface mirror site domain| You can also use the same json key names and values explained in the 'config_modification_tutorial.txt' as the environments. See examples in the [docker-compose.yml](docker-compose.yml) diff --git a/extras/vae_interpose.py b/extras/vae_interpose.py index 72fb09a4..d407ca83 100644 --- a/extras/vae_interpose.py +++ b/extras/vae_interpose.py @@ -1,69 +1,85 @@ # https://github.com/city96/SD-Latent-Interposer/blob/main/interposer.py import os -import torch -import safetensors.torch as sf -import torch.nn as nn -import ldm_patched.modules.model_management +import safetensors.torch as sf +import torch +import torch.nn as nn + +import ldm_patched.modules.model_management from ldm_patched.modules.model_patcher import ModelPatcher from modules.config import path_vae_approx -class Block(nn.Module): - def __init__(self, size): +class ResBlock(nn.Module): + """Block with residuals""" + + def __init__(self, ch): super().__init__() self.join = nn.ReLU() + self.norm = nn.BatchNorm2d(ch) self.long = nn.Sequential( - nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1), - nn.LeakyReLU(0.1), - nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1), - nn.LeakyReLU(0.1), - nn.Conv2d(size, size, kernel_size=3, stride=1, padding=1), + nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1), + nn.SiLU(), + nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1), + nn.SiLU(), + nn.Conv2d(ch, ch, kernel_size=3, stride=1, padding=1), + nn.Dropout(0.1) ) def forward(self, x): - y = self.long(x) - z = self.join(y + x) - return z + x = self.norm(x) + return self.join(self.long(x) + x) -class Interposer(nn.Module): - def __init__(self): +class ExtractBlock(nn.Module): + """Increase no. of channels by [out/in]""" + + def __init__(self, ch_in, ch_out): super().__init__() - self.chan = 4 - self.hid = 128 - - self.head_join = nn.ReLU() - self.head_short = nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1) - self.head_long = nn.Sequential( - nn.Conv2d(self.chan, self.hid, kernel_size=3, stride=1, padding=1), - nn.LeakyReLU(0.1), - nn.Conv2d(self.hid, self.hid, kernel_size=3, stride=1, padding=1), - nn.LeakyReLU(0.1), - nn.Conv2d(self.hid, self.hid, kernel_size=3, stride=1, padding=1), - ) - self.core = nn.Sequential( - Block(self.hid), - Block(self.hid), - Block(self.hid), - ) - self.tail = nn.Sequential( - nn.ReLU(), - nn.Conv2d(self.hid, self.chan, kernel_size=3, stride=1, padding=1) + self.join = nn.ReLU() + self.short = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1) + self.long = nn.Sequential( + nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=1, padding=1), + nn.SiLU(), + nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1), + nn.SiLU(), + nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1), + nn.Dropout(0.1) ) def forward(self, x): - y = self.head_join( - self.head_long(x) + - self.head_short(x) + return self.join(self.long(x) + self.short(x)) + + +class InterposerModel(nn.Module): + """Main neural network""" + + def __init__(self, ch_in=4, ch_out=4, ch_mid=64, scale=1.0, blocks=12): + super().__init__() + self.ch_in = ch_in + self.ch_out = ch_out + self.ch_mid = ch_mid + self.blocks = blocks + self.scale = scale + + self.head = ExtractBlock(self.ch_in, self.ch_mid) + self.core = nn.Sequential( + nn.Upsample(scale_factor=self.scale, mode="nearest"), + *[ResBlock(self.ch_mid) for _ in range(blocks)], + nn.BatchNorm2d(self.ch_mid), + nn.SiLU(), ) + self.tail = nn.Conv2d(self.ch_mid, self.ch_out, kernel_size=3, stride=1, padding=1) + + def forward(self, x): + y = self.head(x) z = self.core(y) return self.tail(z) vae_approx_model = None -vae_approx_filename = os.path.join(path_vae_approx, 'xl-to-v1_interposer-v3.1.safetensors') +vae_approx_filename = os.path.join(path_vae_approx, 'xl-to-v1_interposer-v4.0.safetensors') def parse(x): @@ -72,7 +88,7 @@ def parse(x): x_origin = x.clone() if vae_approx_model is None: - model = Interposer() + model = InterposerModel() model.eval() sd = sf.load_file(vae_approx_filename) model.load_state_dict(sd) diff --git a/javascript/script.js b/javascript/script.js index 9aa0b5c1..d379a783 100644 --- a/javascript/script.js +++ b/javascript/script.js @@ -122,6 +122,43 @@ document.addEventListener("DOMContentLoaded", function() { initStylePreviewOverlay(); }); +var onAppend = function(elem, f) { + var observer = new MutationObserver(function(mutations) { + mutations.forEach(function(m) { + if (m.addedNodes.length) { + f(m.addedNodes); + } + }); + }); + observer.observe(elem, {childList: true}); +} + +function addObserverIfDesiredNodeAvailable(querySelector, callback) { + var elem = document.querySelector(querySelector); + if (!elem) { + window.setTimeout(() => addObserverIfDesiredNodeAvailable(querySelector, callback), 1000); + return; + } + + onAppend(elem, callback); +} + +/** + * Show reset button on toast "Connection errored out." + */ +addObserverIfDesiredNodeAvailable(".toast-wrap", function(added) { + added.forEach(function(element) { + if (element.innerText.includes("Connection errored out.")) { + window.setTimeout(function() { + document.getElementById("reset_button").classList.remove("hidden"); + document.getElementById("generate_button").classList.add("hidden"); + document.getElementById("skip_button").classList.add("hidden"); + document.getElementById("stop_button").classList.add("hidden"); + }); + } + }); +}); + /** * Add a ctrl+enter as a shortcut to start a generation */ diff --git a/language/en.json b/language/en.json index d420a6ab..3eb5d5e2 100644 --- a/language/en.json +++ b/language/en.json @@ -4,6 +4,7 @@ "Generate": "Generate", "Skip": "Skip", "Stop": "Stop", + "Reconnect": "Reconnect", "Input Image": "Input Image", "Advanced": "Advanced", "Upscale or Variation": "Upscale or Variation", @@ -59,6 +60,7 @@ "\ud83d\udcda History Log": "\uD83D\uDCDA History Log", "Image Style": "Image Style", "Fooocus V2": "Fooocus V2", + "Random Style": "Random Style", "Default (Slightly Cinematic)": "Default (Slightly Cinematic)", "Fooocus Masterpiece": "Fooocus Masterpiece", "Fooocus Photograph": "Fooocus Photograph", @@ -341,6 +343,8 @@ "sgm_uniform": "sgm_uniform", "simple": "simple", "ddim_uniform": "ddim_uniform", + "VAE": "VAE", + "Default (model)": "Default (model)", "Forced Overwrite of Sampling Step": "Forced Overwrite of Sampling Step", "Set as -1 to disable. For developer debugging.": "Set as -1 to disable. For developer debugging.", "Forced Overwrite of Refiner Switch Step": "Forced Overwrite of Refiner Switch Step", diff --git a/launch.py b/launch.py index afa66705..5d40cc5b 100644 --- a/launch.py +++ b/launch.py @@ -62,8 +62,8 @@ def prepare_environment(): vae_approx_filenames = [ ('xlvaeapp.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/xlvaeapp.pth'), ('vaeapp_sd15.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/vaeapp_sd15.pt'), - ('xl-to-v1_interposer-v3.1.safetensors', - 'https://huggingface.co/lllyasviel/misc/resolve/main/xl-to-v1_interposer-v3.1.safetensors') + ('xl-to-v1_interposer-v4.0.safetensors', + 'https://huggingface.co/mashb1t/misc/resolve/main/xl-to-v1_interposer-v4.0.safetensors') ] @@ -80,6 +80,10 @@ if args.gpu_device_id is not None: os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id) print("Set device to:", args.gpu_device_id) +if args.hf_mirror is not None : + os.environ['HF_MIRROR'] = str(args.hf_mirror) + print("Set hf_mirror to:", args.hf_mirror) + from modules import config os.environ['GRADIO_TEMP_DIR'] = config.temp_path diff --git a/ldm_patched/modules/args_parser.py b/ldm_patched/modules/args_parser.py index 0c6165a7..bf873783 100644 --- a/ldm_patched/modules/args_parser.py +++ b/ldm_patched/modules/args_parser.py @@ -37,6 +37,7 @@ parser.add_argument("--listen", type=str, default="127.0.0.1", metavar="IP", nar parser.add_argument("--port", type=int, default=8188) parser.add_argument("--disable-header-check", type=str, default=None, metavar="ORIGIN", nargs="?", const="*") parser.add_argument("--web-upload-size", type=float, default=100) +parser.add_argument("--hf-mirror", type=str, default=None) parser.add_argument("--external-working-path", type=str, default=None, metavar="PATH", nargs='+', action='append') parser.add_argument("--output-path", type=str, default=None) diff --git a/ldm_patched/modules/sd.py b/ldm_patched/modules/sd.py index e197c39c..282f2559 100644 --- a/ldm_patched/modules/sd.py +++ b/ldm_patched/modules/sd.py @@ -427,12 +427,13 @@ def load_checkpoint(config_path=None, ckpt_path=None, output_vae=True, output_cl return (ldm_patched.modules.model_patcher.ModelPatcher(model, load_device=model_management.get_torch_device(), offload_device=offload_device), clip, vae) -def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True): +def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True, vae_filename_param=None): sd = ldm_patched.modules.utils.load_torch_file(ckpt_path) sd_keys = sd.keys() clip = None clipvision = None vae = None + vae_filename = None model = None model_patcher = None clip_target = None @@ -462,8 +463,12 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o model.load_model_weights(sd, "model.diffusion_model.") if output_vae: - vae_sd = ldm_patched.modules.utils.state_dict_prefix_replace(sd, {"first_stage_model.": ""}, filter_keys=True) - vae_sd = model_config.process_vae_state_dict(vae_sd) + if vae_filename_param is None: + vae_sd = ldm_patched.modules.utils.state_dict_prefix_replace(sd, {"first_stage_model.": ""}, filter_keys=True) + vae_sd = model_config.process_vae_state_dict(vae_sd) + else: + vae_sd = ldm_patched.modules.utils.load_torch_file(vae_filename_param) + vae_filename = vae_filename_param vae = VAE(sd=vae_sd) if output_clip: @@ -485,7 +490,7 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o print("loaded straight to GPU") model_management.load_model_gpu(model_patcher) - return (model_patcher, clip, vae, clipvision) + return model_patcher, clip, vae, vae_filename, clipvision def load_unet_state_dict(sd): #load unet in diffusers format diff --git a/modules/async_worker.py b/modules/async_worker.py index fa10ff8a..6f0b30a9 100644 --- a/modules/async_worker.py +++ b/modules/async_worker.py @@ -44,7 +44,7 @@ def worker(): import args_manager from extras.censor import censor_batch, censor_single - from modules.sdxl_styles import apply_style, apply_wildcards, fooocus_expansion, apply_arrays + from modules.sdxl_styles import apply_style, get_random_style, apply_wildcards, fooocus_expansion, apply_arrays, random_style_name from modules.private_logger import log from extras.expansion import safe_str from modules.util import remove_empty_str, HWC3, resize_image, get_image_shape_ceil, set_image_shape_ceil, \ @@ -172,6 +172,7 @@ def worker(): adaptive_cfg = args.pop() sampler_name = args.pop() scheduler_name = args.pop() + vae_name = args.pop() overwrite_step = args.pop() overwrite_switch = args.pop() overwrite_width = args.pop() @@ -434,7 +435,7 @@ def worker(): progressbar(async_task, 3, 'Loading models ...') pipeline.refresh_everything(refiner_model_name=refiner_model_name, base_model_name=base_model_name, loras=loras, base_model_additional_loras=base_model_additional_loras, - use_synthetic_refiner=use_synthetic_refiner) + use_synthetic_refiner=use_synthetic_refiner, vae_name=vae_name) progressbar(async_task, 3, 'Processing prompts ...') tasks = [] @@ -455,8 +456,12 @@ def worker(): positive_basic_workloads = [] negative_basic_workloads = [] + task_styles = style_selections.copy() if use_style: - for s in style_selections: + for i, s in enumerate(task_styles): + if s == random_style_name: + s = get_random_style(task_rng) + task_styles[i] = s p, n = apply_style(s, positive=task_prompt) positive_basic_workloads = positive_basic_workloads + p negative_basic_workloads = negative_basic_workloads + n @@ -484,6 +489,7 @@ def worker(): negative_top_k=len(negative_basic_workloads), log_positive_prompt='\n'.join([task_prompt] + task_extra_positive_prompts), log_negative_prompt='\n'.join([task_negative_prompt] + task_extra_negative_prompts), + styles=task_styles )) if use_expansion: @@ -856,7 +862,7 @@ def worker(): d = [('Prompt', 'prompt', task['log_positive_prompt']), ('Negative Prompt', 'negative_prompt', task['log_negative_prompt']), ('Fooocus V2 Expansion', 'prompt_expansion', task['expansion']), - ('Styles', 'styles', str(raw_style_selections)), + ('Styles', 'styles', str(task['styles'] if not use_expansion else [fooocus_expansion] + task['styles'])), ('Performance', 'performance', performance_selection.value)] if performance_selection.steps() != steps: @@ -883,6 +889,7 @@ def worker(): d.append(('Sampler', 'sampler', sampler_name)) d.append(('Scheduler', 'scheduler', scheduler_name)) + d.append(('VAE', 'vae', vae_name)) d.append(('Seed', 'seed', str(task['task_seed']))) if freeu_enabled: @@ -897,10 +904,10 @@ def worker(): metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme) metadata_parser.set_data(task['log_positive_prompt'], task['positive'], task['log_negative_prompt'], task['negative'], - steps, base_model_name, refiner_model_name, loras) + steps, base_model_name, refiner_model_name, loras, vae_name) d.append(('Metadata Scheme', 'metadata_scheme', metadata_scheme.value if save_metadata_to_images else save_metadata_to_images)) d.append(('Version', 'version', 'Fooocus v' + fooocus_version.version)) - img_paths.append(log(x, d, metadata_parser, output_format)) + img_paths.append(log(x, d, metadata_parser, output_format, task)) yield_result(async_task, img_paths, black_out_nsfw, False, do_not_show_finished_images=len(tasks) == 1 or disable_intermediate_results) except ldm_patched.modules.model_management.InterruptProcessingException as e: diff --git a/modules/config.py b/modules/config.py index 73e33e4a..ffb74a23 100644 --- a/modules/config.py +++ b/modules/config.py @@ -189,6 +189,7 @@ paths_checkpoints = get_dir_or_set_default('path_checkpoints', ['../models/check paths_loras = get_dir_or_set_default('path_loras', ['../models/loras/'], True) path_embeddings = get_dir_or_set_default('path_embeddings', '../models/embeddings/') path_vae_approx = get_dir_or_set_default('path_vae_approx', '../models/vae_approx/') +path_vae = get_dir_or_set_default('path_vae', '../models/vae/') path_upscale_models = get_dir_or_set_default('path_upscale_models', '../models/upscale_models/') path_inpaint = get_dir_or_set_default('path_inpaint', '../models/inpaint/') path_controlnet = get_dir_or_set_default('path_controlnet', '../models/controlnet/') @@ -347,6 +348,11 @@ default_scheduler = get_config_item_or_set_default( default_value='karras', validator=lambda x: x in modules.flags.scheduler_list ) +default_vae = get_config_item_or_set_default( + key='default_vae', + default_value=modules.flags.default_vae, + validator=lambda x: isinstance(x, str) +) default_styles = get_config_item_or_set_default( key='default_styles', default_value=[ @@ -541,6 +547,7 @@ with open(config_example_path, "w", encoding="utf-8") as json_file: model_filenames = [] lora_filenames = [] +vae_filenames = [] wildcard_filenames = [] sdxl_lcm_lora = 'sdxl_lcm_lora.safetensors' @@ -552,15 +559,20 @@ def get_model_filenames(folder_paths, extensions=None, name_filter=None): if extensions is None: extensions = ['.pth', '.ckpt', '.bin', '.safetensors', '.fooocus.patch'] files = [] + + if not isinstance(folder_paths, list): + folder_paths = [folder_paths] for folder in folder_paths: files += get_files_from_folder(folder, extensions, name_filter) + return files def update_files(): - global model_filenames, lora_filenames, wildcard_filenames, available_presets + global model_filenames, lora_filenames, vae_filenames, wildcard_filenames, available_presets model_filenames = get_model_filenames(paths_checkpoints) lora_filenames = get_model_filenames(paths_loras) + vae_filenames = get_model_filenames(path_vae) wildcard_filenames = get_files_from_folder(path_wildcards, ['.txt']) available_presets = get_presets() return diff --git a/modules/core.py b/modules/core.py index 38ee8e8d..3ca4cc5b 100644 --- a/modules/core.py +++ b/modules/core.py @@ -35,12 +35,13 @@ opModelSamplingDiscrete = ModelSamplingDiscrete() class StableDiffusionModel: - def __init__(self, unet=None, vae=None, clip=None, clip_vision=None, filename=None): + def __init__(self, unet=None, vae=None, clip=None, clip_vision=None, filename=None, vae_filename=None): self.unet = unet self.vae = vae self.clip = clip self.clip_vision = clip_vision self.filename = filename + self.vae_filename = vae_filename self.unet_with_lora = unet self.clip_with_lora = clip self.visited_loras = '' @@ -142,9 +143,10 @@ def apply_controlnet(positive, negative, control_net, image, strength, start_per @torch.no_grad() @torch.inference_mode() -def load_model(ckpt_filename): - unet, clip, vae, clip_vision = load_checkpoint_guess_config(ckpt_filename, embedding_directory=path_embeddings) - return StableDiffusionModel(unet=unet, clip=clip, vae=vae, clip_vision=clip_vision, filename=ckpt_filename) +def load_model(ckpt_filename, vae_filename=None): + unet, clip, vae, vae_filename, clip_vision = load_checkpoint_guess_config(ckpt_filename, embedding_directory=path_embeddings, + vae_filename_param=vae_filename) + return StableDiffusionModel(unet=unet, clip=clip, vae=vae, clip_vision=clip_vision, filename=ckpt_filename, vae_filename=vae_filename) @torch.no_grad() diff --git a/modules/default_pipeline.py b/modules/default_pipeline.py index 190601ec..38f914c5 100644 --- a/modules/default_pipeline.py +++ b/modules/default_pipeline.py @@ -3,6 +3,7 @@ import os import torch import modules.patch import modules.config +import modules.flags import ldm_patched.modules.model_management import ldm_patched.modules.latent_formats import modules.inpaint_worker @@ -58,17 +59,21 @@ def assert_model_integrity(): @torch.no_grad() @torch.inference_mode() -def refresh_base_model(name): +def refresh_base_model(name, vae_name=None): global model_base filename = get_file_from_folder_list(name, modules.config.paths_checkpoints) - if model_base.filename == filename: + vae_filename = None + if vae_name is not None and vae_name != modules.flags.default_vae: + vae_filename = get_file_from_folder_list(vae_name, modules.config.path_vae) + + if model_base.filename == filename and model_base.vae_filename == vae_filename: return - model_base = core.StableDiffusionModel() - model_base = core.load_model(filename) + model_base = core.load_model(filename, vae_filename) print(f'Base model loaded: {model_base.filename}') + print(f'VAE loaded: {model_base.vae_filename}') return @@ -216,7 +221,7 @@ def prepare_text_encoder(async_call=True): @torch.no_grad() @torch.inference_mode() def refresh_everything(refiner_model_name, base_model_name, loras, - base_model_additional_loras=None, use_synthetic_refiner=False): + base_model_additional_loras=None, use_synthetic_refiner=False, vae_name=None): global final_unet, final_clip, final_vae, final_refiner_unet, final_refiner_vae, final_expansion final_unet = None @@ -227,11 +232,11 @@ def refresh_everything(refiner_model_name, base_model_name, loras, if use_synthetic_refiner and refiner_model_name == 'None': print('Synthetic Refiner Activated') - refresh_base_model(base_model_name) + refresh_base_model(base_model_name, vae_name) synthesize_refiner_model() else: refresh_refiner_model(refiner_model_name) - refresh_base_model(base_model_name) + refresh_base_model(base_model_name, vae_name) refresh_loras(loras, base_model_additional_loras=base_model_additional_loras) assert_model_integrity() @@ -254,7 +259,8 @@ def refresh_everything(refiner_model_name, base_model_name, loras, refresh_everything( refiner_model_name=modules.config.default_refiner_model_name, base_model_name=modules.config.default_base_model_name, - loras=get_enabled_loras(modules.config.default_loras) + loras=get_enabled_loras(modules.config.default_loras), + vae_name=modules.config.default_vae, ) diff --git a/modules/flags.py b/modules/flags.py index c9d13fd8..9f2aefb3 100644 --- a/modules/flags.py +++ b/modules/flags.py @@ -53,6 +53,8 @@ SAMPLER_NAMES = KSAMPLER_NAMES + list(SAMPLER_EXTRA.keys()) sampler_list = SAMPLER_NAMES scheduler_list = SCHEDULER_NAMES +default_vae = 'Default (model)' + refiner_swap_method = 'joint' cn_ip = "ImagePrompt" diff --git a/modules/meta_parser.py b/modules/meta_parser.py index 70ab8860..84032e82 100644 --- a/modules/meta_parser.py +++ b/modules/meta_parser.py @@ -46,6 +46,7 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool): get_float('refiner_switch', 'Refiner Switch', loaded_parameter_dict, results) get_str('sampler', 'Sampler', loaded_parameter_dict, results) get_str('scheduler', 'Scheduler', loaded_parameter_dict, results) + get_str('vae', 'VAE', loaded_parameter_dict, results) get_seed('seed', 'Seed', loaded_parameter_dict, results) if is_generating: @@ -253,6 +254,7 @@ class MetadataParser(ABC): self.refiner_model_name: str = '' self.refiner_model_hash: str = '' self.loras: list = [] + self.vae_name: str = '' @abstractmethod def get_scheme(self) -> MetadataScheme: @@ -267,7 +269,7 @@ class MetadataParser(ABC): raise NotImplementedError def set_data(self, raw_prompt, full_prompt, raw_negative_prompt, full_negative_prompt, steps, base_model_name, - refiner_model_name, loras): + refiner_model_name, loras, vae_name): self.raw_prompt = raw_prompt self.full_prompt = full_prompt self.raw_negative_prompt = raw_negative_prompt @@ -289,6 +291,7 @@ class MetadataParser(ABC): lora_path = get_file_from_folder_list(lora_name, modules.config.paths_loras) lora_hash = get_sha256(lora_path) self.loras.append((Path(lora_name).stem, lora_weight, lora_hash)) + self.vae_name = Path(vae_name).stem @staticmethod def remove_special_loras(lora_filenames): @@ -310,6 +313,7 @@ class A1111MetadataParser(MetadataParser): 'steps': 'Steps', 'sampler': 'Sampler', 'scheduler': 'Scheduler', + 'vae': 'VAE', 'guidance_scale': 'CFG scale', 'seed': 'Seed', 'resolution': 'Size', @@ -397,13 +401,12 @@ class A1111MetadataParser(MetadataParser): data['sampler'] = k break - for key in ['base_model', 'refiner_model']: + for key in ['base_model', 'refiner_model', 'vae']: if key in data: - for filename in modules.config.model_filenames: - path = Path(filename) - if data[key] == path.stem: - data[key] = filename - break + if key == 'vae': + self.add_extension_to_filename(data, modules.config.vae_filenames, 'vae') + else: + self.add_extension_to_filename(data, modules.config.model_filenames, key) lora_data = '' if 'lora_weights' in data and data['lora_weights'] != '': @@ -433,6 +436,7 @@ class A1111MetadataParser(MetadataParser): sampler = data['sampler'] scheduler = data['scheduler'] + if sampler in SAMPLERS and SAMPLERS[sampler] != '': sampler = SAMPLERS[sampler] if sampler not in CIVITAI_NO_KARRAS and scheduler == 'karras': @@ -451,6 +455,7 @@ class A1111MetadataParser(MetadataParser): self.fooocus_to_a1111['performance']: data['performance'], self.fooocus_to_a1111['scheduler']: scheduler, + self.fooocus_to_a1111['vae']: Path(data['vae']).stem, # workaround for multiline prompts self.fooocus_to_a1111['raw_prompt']: self.raw_prompt, self.fooocus_to_a1111['raw_negative_prompt']: self.raw_negative_prompt, @@ -491,6 +496,14 @@ class A1111MetadataParser(MetadataParser): negative_prompt_text = f"\nNegative prompt: {negative_prompt_resolved}" if negative_prompt_resolved else "" return f"{positive_prompt_resolved}{negative_prompt_text}\n{generation_params_text}".strip() + @staticmethod + def add_extension_to_filename(data, filenames, key): + for filename in filenames: + path = Path(filename) + if data[key] == path.stem: + data[key] = filename + break + class FooocusMetadataParser(MetadataParser): def get_scheme(self) -> MetadataScheme: @@ -499,6 +512,7 @@ class FooocusMetadataParser(MetadataParser): def parse_json(self, metadata: dict) -> dict: model_filenames = modules.config.model_filenames.copy() lora_filenames = modules.config.lora_filenames.copy() + vae_filenames = modules.config.vae_filenames.copy() self.remove_special_loras(lora_filenames) for key, value in metadata.items(): if value in ['', 'None']: @@ -507,6 +521,8 @@ class FooocusMetadataParser(MetadataParser): metadata[key] = self.replace_value_with_filename(key, value, model_filenames) elif key.startswith('lora_combined_'): metadata[key] = self.replace_value_with_filename(key, value, lora_filenames) + elif key == 'vae': + metadata[key] = self.replace_value_with_filename(key, value, vae_filenames) else: continue @@ -533,6 +549,7 @@ class FooocusMetadataParser(MetadataParser): res['refiner_model'] = self.refiner_model_name res['refiner_model_hash'] = self.refiner_model_hash + res['vae'] = self.vae_name res['loras'] = self.loras if modules.config.metadata_created_by != '': diff --git a/modules/model_loader.py b/modules/model_loader.py index 8ba336a9..1143f75e 100644 --- a/modules/model_loader.py +++ b/modules/model_loader.py @@ -14,6 +14,8 @@ def load_file_from_url( Returns the path to the downloaded file. """ + domain = os.environ.get("HF_MIRROR", "https://huggingface.co").rstrip('/') + url = str.replace(url, "https://huggingface.co", domain, 1) os.makedirs(model_dir, exist_ok=True) if not file_name: parts = urlparse(url) diff --git a/modules/private_logger.py b/modules/private_logger.py index edd9457d..eb8f0cc5 100644 --- a/modules/private_logger.py +++ b/modules/private_logger.py @@ -21,7 +21,7 @@ def get_current_html_path(output_format=None): return html_name -def log(img, metadata, metadata_parser: MetadataParser | None = None, output_format=None) -> str: +def log(img, metadata, metadata_parser: MetadataParser | None = None, output_format=None, task=None) -> str: path_outputs = modules.config.temp_path if args_manager.args.disable_image_log else modules.config.path_outputs output_format = output_format if output_format else modules.config.default_output_format date_string, local_temp_filename, only_name = generate_temp_filename(folder=path_outputs, extension=output_format) @@ -111,9 +111,15 @@ def log(img, metadata, metadata_parser: MetadataParser | None = None, output_for for label, key, value in metadata: value_txt = str(value).replace('\n', '
') item += f"{label}{value_txt}\n" + + if task is not None and 'positive' in task and 'negative' in task: + full_prompt_details = f"""
Positive{', '.join(task['positive'])}
+
Negative{', '.join(task['negative'])}
""" + item += f"Full raw prompt{full_prompt_details}\n" + item += "" - js_txt = urllib.parse.quote(json.dumps({k: v for _, k, v in metadata}, indent=0), safe='') + js_txt = urllib.parse.quote(json.dumps({k: v for _, k, v, in metadata}, indent=0), safe='') item += f"
" item += "" diff --git a/modules/sdxl_styles.py b/modules/sdxl_styles.py index 77ad6b57..5b6afb59 100644 --- a/modules/sdxl_styles.py +++ b/modules/sdxl_styles.py @@ -5,6 +5,7 @@ import math import modules.config from modules.util import get_files_from_folder +from random import Random # cannot use modules.config - validators causing circular imports styles_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../sdxl_styles/')) @@ -50,8 +51,13 @@ for styles_file in styles_files: print(f'Failed to load style file {styles_file}') style_keys = list(styles.keys()) -fooocus_expansion = "Fooocus V2" -legal_style_names = [fooocus_expansion] + style_keys +fooocus_expansion = 'Fooocus V2' +random_style_name = 'Random Style' +legal_style_names = [fooocus_expansion, random_style_name] + style_keys + + +def get_random_style(rng: Random) -> str: + return rng.choice(list(styles.items()))[0] def apply_style(style, positive): diff --git a/modules/ui_gradio_extensions.py b/modules/ui_gradio_extensions.py index bebf9f8c..409c7e33 100644 --- a/modules/ui_gradio_extensions.py +++ b/modules/ui_gradio_extensions.py @@ -39,7 +39,7 @@ def javascript_html(): head += f'\n' head += f'\n' head += f'\n' - head += f'\n' + head += f'\n' if args_manager.args.theme: head += f'\n' diff --git a/modules/util.py b/modules/util.py index 9e0fb294..d2feecb6 100644 --- a/modules/util.py +++ b/modules/util.py @@ -371,6 +371,9 @@ def is_json(data: str) -> bool: def get_file_from_folder_list(name, folders): + if not isinstance(folders, list): + folders = [folders] + for folder in folders: filename = os.path.abspath(os.path.realpath(os.path.join(folder, name))) if os.path.isfile(filename): diff --git a/readme.md b/readme.md index 5f66e02a..0ec06f19 100644 --- a/readme.md +++ b/readme.md @@ -368,6 +368,7 @@ A safer way is just to try "run_anime.bat" or "run_realistic.bat" - they should entry_with_update.py [-h] [--listen [IP]] [--port PORT] [--disable-header-check [ORIGIN]] [--web-upload-size WEB_UPLOAD_SIZE] + [--hf-mirror HF_MIRROR] [--external-working-path PATH [PATH ...]] [--output-path OUTPUT_PATH] [--temp-path TEMP_PATH] [--cache-path CACHE_PATH] [--in-browser] diff --git a/sdxl_styles/samples/random_style.jpg b/sdxl_styles/samples/random_style.jpg new file mode 100644 index 00000000..9f685108 Binary files /dev/null and b/sdxl_styles/samples/random_style.jpg differ diff --git a/webui.py b/webui.py index ab6ad091..55f3102c 100644 --- a/webui.py +++ b/webui.py @@ -123,8 +123,9 @@ with shared.gradio_root: with gr.Column(scale=3, min_width=0): generate_button = gr.Button(label="Generate", value="Generate", elem_classes='type_row', elem_id='generate_button', visible=True) + reset_button = gr.Button(label="Reconnect", value="Reconnect", elem_classes='type_row', elem_id='reset_button', visible=False) load_parameter_button = gr.Button(label="Load Parameters", value="Load Parameters", elem_classes='type_row', elem_id='load_parameter_button', visible=False) - skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', visible=False) + skip_button = gr.Button(label="Skip", value="Skip", elem_classes='type_row_half', elem_id='skip_button', visible=False) stop_button = gr.Button(label="Stop", value="Stop", elem_classes='type_row_half', elem_id='stop_button', visible=False) def stop_clicked(currentTask): @@ -406,6 +407,8 @@ with shared.gradio_root: value=modules.config.default_sampler) scheduler_name = gr.Dropdown(label='Scheduler', choices=flags.scheduler_list, value=modules.config.default_scheduler) + vae_name = gr.Dropdown(label='VAE', choices=[modules.flags.default_vae] + modules.config.vae_filenames, + value=modules.config.default_vae, show_label=True) generate_image_grid = gr.Checkbox(label='Generate Image Grid for Each Batch', info='(Experimental) This may cause performance problems on some computers and certain internet conditions.', @@ -538,6 +541,7 @@ with shared.gradio_root: modules.config.update_files() results = [gr.update(choices=modules.config.model_filenames)] results += [gr.update(choices=['None'] + modules.config.model_filenames)] + results += [gr.update(choices=['None'] + modules.config.vae_filenames)] if not args_manager.args.disable_preset_selection: results += [gr.update(choices=modules.config.available_presets)] for i in range(modules.config.default_max_lora_number): @@ -545,7 +549,7 @@ with shared.gradio_root: gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()] return results - refresh_files_output = [base_model, refiner_model] + refresh_files_output = [base_model, refiner_model, vae_name] if not args_manager.args.disable_preset_selection: refresh_files_output += [preset_selection] refresh_files.click(refresh_files_clicked, [], refresh_files_output + lora_ctrls, @@ -557,8 +561,8 @@ with shared.gradio_root: performance_selection, overwrite_step, overwrite_switch, aspect_ratios_selection, overwrite_width, overwrite_height, guidance_scale, sharpness, adm_scaler_positive, adm_scaler_negative, adm_scaler_end, refiner_swap_method, adaptive_cfg, base_model, - refiner_model, refiner_switch, sampler_name, scheduler_name, seed_random, image_seed, - generate_button, load_parameter_button] + freeu_ctrls + lora_ctrls + refiner_model, refiner_switch, sampler_name, scheduler_name, vae_name, seed_random, + image_seed, generate_button, load_parameter_button] + freeu_ctrls + lora_ctrls if not args_manager.args.disable_preset_selection: def preset_selection_change(preset, is_generating): @@ -644,7 +648,7 @@ with shared.gradio_root: ctrls += [outpaint_selections, inpaint_input_image, inpaint_additional_prompt, inpaint_mask_image] ctrls += [disable_preview, disable_intermediate_results, disable_seed_increment, black_out_nsfw] ctrls += [adm_scaler_positive, adm_scaler_negative, adm_scaler_end, adaptive_cfg] - ctrls += [sampler_name, scheduler_name] + ctrls += [sampler_name, scheduler_name, vae_name] ctrls += [overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength] ctrls += [overwrite_upscale_strength, mixing_image_prompt_and_vary_upscale, mixing_image_prompt_and_inpaint] ctrls += [debugging_cn_preprocessor, skipping_cn_preprocessor, canny_low_threshold, canny_high_threshold] @@ -698,6 +702,14 @@ with shared.gradio_root: .then(fn=update_history_link, outputs=history_link) \ .then(fn=lambda: None, _js='playNotification').then(fn=lambda: None, _js='refresh_grid_delayed') + reset_button.click(lambda: [worker.AsyncTask(args=[]), False, gr.update(visible=True, interactive=True)] + + [gr.update(visible=False)] * 6 + + [gr.update(visible=True, value=[])], + outputs=[currentTask, state_is_generating, generate_button, + reset_button, stop_button, skip_button, + progress_html, progress_window, progress_gallery, gallery], + queue=False) + for notification_file in ['notification.ogg', 'notification.mp3']: if os.path.exists(notification_file): gr.Audio(interactive=False, value=notification_file, elem_id='audio_notification', visible=False) @@ -715,6 +727,15 @@ with shared.gradio_root: desc_btn.click(trigger_describe, inputs=[desc_method, desc_input_image], outputs=[prompt, style_selections], show_progress=True, queue=True) + if args_manager.args.enable_describe_uov_image: + def trigger_uov_describe(mode, img, prompt): + # keep prompt if not empty + if prompt == '': + return trigger_describe(mode, img) + return gr.update(), gr.update() + + uov_input_image.upload(trigger_uov_describe, inputs=[desc_method, uov_input_image, prompt], + outputs=[prompt, style_selections], show_progress=True, queue=True) def dump_default_english_config(): from modules.localization import dump_english_config