diff --git a/CODEOWNERS b/CODEOWNERS index 7438c9bc6..4eb946b00 100644 --- a/CODEOWNERS +++ b/CODEOWNERS @@ -1,12 +1 @@ -* @AUTOMATIC1111 - -# if you were managing a localization and were removed from this file, this is because -# the intended way to do localizations now is via extensions. See: -# https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Developing-extensions -# Make a repo with your localization and since you are still listed as a collaborator -# you can add it to the wiki page yourself. This change is because some people complained -# the git commit log is cluttered with things unrelated to almost everyone and -# because I believe this is the best overall for the project to handle localizations almost -# entirely without my oversight. - - +* @AUTOMATIC1111 @w-e-w @catboxanon diff --git a/README.md b/README.md index bc62945c0..007f590d2 100644 --- a/README.md +++ b/README.md @@ -148,6 +148,7 @@ python_cmd="python3.11" 2. Navigate to the directory you would like the webui to be installed and execute the following command: ```bash wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh +chmod +x webui.sh ``` Or just clone the repo wherever you want: ```bash diff --git a/configs/sd_xl_v.yaml b/configs/sd_xl_v.yaml new file mode 100644 index 000000000..c755dc74f --- /dev/null +++ b/configs/sd_xl_v.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.VScaling + 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: 4 + 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/javascript/imageviewer.js b/javascript/imageviewer.js index 9b23f4700..979d05de5 100644 --- a/javascript/imageviewer.js +++ b/javascript/imageviewer.js @@ -13,6 +13,7 @@ function showModal(event) { if (modalImage.style.display === 'none') { lb.style.setProperty('background-image', 'url(' + source.src + ')'); } + updateModalImage(); lb.style.display = "flex"; lb.focus(); @@ -31,21 +32,26 @@ function negmod(n, m) { return ((n % m) + m) % m; } +function updateModalImage() { + const modalImage = gradioApp().getElementById("modalImage"); + let currentButton = selected_gallery_button(); + let preview = gradioApp().querySelectorAll('.livePreview > img'); + if (opts.js_live_preview_in_modal_lightbox && preview.length > 0) { + // show preview image if available + modalImage.src = preview[preview.length - 1].src; + } else if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) { + modalImage.src = currentButton.children[0].src; + if (modalImage.style.display === 'none') { + const modal = gradioApp().getElementById("lightboxModal"); + modal.style.setProperty('background-image', `url(${modalImage.src})`); + } + } +} + function updateOnBackgroundChange() { const modalImage = gradioApp().getElementById("modalImage"); if (modalImage && modalImage.offsetParent) { - let currentButton = selected_gallery_button(); - let preview = gradioApp().querySelectorAll('.livePreview > img'); - if (opts.js_live_preview_in_modal_lightbox && preview.length > 0) { - // show preview image if available - modalImage.src = preview[preview.length - 1].src; - } else if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) { - modalImage.src = currentButton.children[0].src; - if (modalImage.style.display === 'none') { - const modal = gradioApp().getElementById("lightboxModal"); - modal.style.setProperty('background-image', `url(${modalImage.src})`); - } - } + updateModalImage(); } } diff --git a/modules/extras.py b/modules/extras.py index 1144c7c0b..32da3d3ec 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -69,7 +69,7 @@ def run_pnginfo(image): for key, text in items.items(): info += f""" -
+

{plaintext_to_html(str(key))}

{plaintext_to_html(str(text))}

diff --git a/modules/sd_models.py b/modules/sd_models.py index 55bd9ca5e..167d4ff36 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -159,7 +159,7 @@ def list_models(): model_url = None expected_sha256 = None else: - model_url = f"{shared.hf_endpoint}/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors" + model_url = f"{shared.hf_endpoint}/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors" expected_sha256 = '6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa' model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"], download_name="v1-5-pruned-emaonly.safetensors", ext_blacklist=[".vae.ckpt", ".vae.safetensors"], hash_prefix=expected_sha256) @@ -783,7 +783,7 @@ def get_obj_from_str(string, reload=False): return getattr(importlib.import_module(module, package=None), cls) -def load_model(checkpoint_info=None, already_loaded_state_dict=None): +def load_model(checkpoint_info=None, already_loaded_state_dict=None, checkpoint_config=None): from modules import sd_hijack checkpoint_info = checkpoint_info or select_checkpoint() @@ -801,7 +801,8 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): else: state_dict = get_checkpoint_state_dict(checkpoint_info, timer) - checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) + if not checkpoint_config: + checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) clip_is_included_into_sd = any(x for x in [sd1_clip_weight, sd2_clip_weight, sdxl_clip_weight, sdxl_refiner_clip_weight] if x in state_dict) timer.record("find config") @@ -974,7 +975,7 @@ def reload_model_weights(sd_model=None, info=None, forced_reload=False): if sd_model is not None: send_model_to_trash(sd_model) - load_model(checkpoint_info, already_loaded_state_dict=state_dict) + load_model(checkpoint_info, already_loaded_state_dict=state_dict, checkpoint_config=checkpoint_config) return model_data.sd_model try: diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index fb44c5a8d..3c1e4a151 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -14,6 +14,7 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml") 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_sdxlv = os.path.join(sd_configs_path, "sd_xl_v.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") @@ -81,6 +82,9 @@ def guess_model_config_from_state_dict(sd, filename): if diffusion_model_input.shape[1] == 9: return config_sdxl_inpainting else: + if ('v_pred' in sd): + del sd['v_pred'] + return config_sdxlv return config_sdxl if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None: diff --git a/modules/shared_options.py b/modules/shared_options.py index 9f4520274..efede7067 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -231,7 +231,7 @@ options_templates.update(options_section(('img2img', "img2img", "sd"), { options_templates.update(options_section(('optimizations', "Optimizations", "sd"), { "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}), - "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}, infotext='NGMS').link("PR", "https://github.com/AUTOMATIC1111/stablediffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), + "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}, infotext='NGMS').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), "s_min_uncond_all": OptionInfo(False, "Negative Guidance minimum sigma all steps", infotext='NGMS all steps').info("By default, NGMS above skips every other step; this makes it skip all steps"), "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}, infotext='Token merging ratio').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), "token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"), @@ -404,7 +404,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"), 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'), 'sd_noise_schedule': OptionInfo("Default", "Noise schedule for sampling", gr.Radio, {"choices": ["Default", "Zero Terminal SNR"]}, infotext="Noise Schedule").info("for use with zero terminal SNR trained models"), - 'skip_early_cond': OptionInfo(0.0, "Ignore negative prompt during early sampling", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext="Skip Early CFG").info("disables CFG on a proportion of steps at the beginning of generation; 0=skip none; 1=skip all; can both improve sample diversity/quality and speed up sampling"), + 'skip_early_cond': OptionInfo(0.0, "Ignore negative prompt during early sampling", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext="Skip Early CFG").info("disables CFG on a proportion of steps at the beginning of generation; 0=skip none; 1=skip all; can both improve sample diversity/quality and speed up sampling; XYZ plot: Skip Early CFG"), 'beta_dist_alpha': OptionInfo(0.6, "Beta scheduler - alpha", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler alpha').info('Default = 0.6; the alpha parameter of the beta distribution used in Beta sampling'), 'beta_dist_beta': OptionInfo(0.6, "Beta scheduler - beta", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler beta').info('Default = 0.6; the beta parameter of the beta distribution used in Beta sampling'), })) diff --git a/modules/ui.py b/modules/ui.py index f48638f69..9a76b5fcd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -44,6 +44,9 @@ mimetypes.add_type('application/javascript', '.mjs') mimetypes.add_type('image/webp', '.webp') mimetypes.add_type('image/avif', '.avif') +# override potentially incorrect mimetypes +mimetypes.add_type('text/css', '.css') + if not cmd_opts.share and not cmd_opts.listen: # fix gradio phoning home gradio.utils.version_check = lambda: None diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 6a42a04d9..c60dd6dda 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -259,6 +259,7 @@ axis_options = [ AxisOption("Schedule min sigma", float, apply_override("sigma_min")), AxisOption("Schedule max sigma", float, apply_override("sigma_max")), AxisOption("Schedule rho", float, apply_override("rho")), + AxisOption("Skip Early CFG", float, apply_override('skip_early_cond')), AxisOption("Beta schedule alpha", float, apply_override("beta_dist_alpha")), AxisOption("Beta schedule beta", float, apply_override("beta_dist_beta")), AxisOption("Eta", float, apply_field("eta")),