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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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Merge branch 'dev' into m9-240816-pnginfo-text-copy
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w-e-w
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commit
400dd32769
10 changed files with 134 additions and 31 deletions
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@ -69,7 +69,7 @@ def run_pnginfo(image):
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for key, text in items.items():
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info += f"""
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<div>
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<div class="infotext">
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<p><b>{plaintext_to_html(str(key))}</b></p>
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<p>{plaintext_to_html(str(text))}</p>
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</div>
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@ -159,7 +159,7 @@ def list_models():
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model_url = None
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expected_sha256 = None
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else:
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model_url = f"{shared.hf_endpoint}/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors"
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model_url = f"{shared.hf_endpoint}/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors"
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expected_sha256 = '6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa'
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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)
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@ -783,7 +783,7 @@ def get_obj_from_str(string, reload=False):
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return getattr(importlib.import_module(module, package=None), cls)
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def load_model(checkpoint_info=None, already_loaded_state_dict=None):
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def load_model(checkpoint_info=None, already_loaded_state_dict=None, checkpoint_config=None):
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from modules import sd_hijack
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checkpoint_info = checkpoint_info or select_checkpoint()
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@ -801,7 +801,8 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
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else:
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state_dict = get_checkpoint_state_dict(checkpoint_info, timer)
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checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
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if not checkpoint_config:
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checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
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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)
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timer.record("find config")
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@ -974,7 +975,7 @@ def reload_model_weights(sd_model=None, info=None, forced_reload=False):
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if sd_model is not None:
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send_model_to_trash(sd_model)
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load_model(checkpoint_info, already_loaded_state_dict=state_dict)
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load_model(checkpoint_info, already_loaded_state_dict=state_dict, checkpoint_config=checkpoint_config)
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return model_data.sd_model
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try:
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@ -14,6 +14,7 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
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config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
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config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml")
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config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml")
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config_sdxlv = os.path.join(sd_configs_path, "sd_xl_v.yaml")
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config_sdxl_refiner = os.path.join(sd_xl_repo_configs_path, "sd_xl_refiner.yaml")
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config_sdxl_inpainting = os.path.join(sd_configs_path, "sd_xl_inpaint.yaml")
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config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")
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@ -81,6 +82,9 @@ def guess_model_config_from_state_dict(sd, filename):
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if diffusion_model_input.shape[1] == 9:
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return config_sdxl_inpainting
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else:
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if ('v_pred' in sd):
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del sd['v_pred']
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return config_sdxlv
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return config_sdxl
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if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None:
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@ -231,7 +231,7 @@ options_templates.update(options_section(('img2img', "img2img", "sd"), {
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options_templates.update(options_section(('optimizations', "Optimizations", "sd"), {
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"cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}),
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"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"),
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"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"),
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"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"),
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"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"),
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"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"),
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@ -404,7 +404,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
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'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"),
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'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'),
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'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"),
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'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"),
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'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"),
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'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'),
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'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'),
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}))
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@ -44,6 +44,9 @@ mimetypes.add_type('application/javascript', '.mjs')
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mimetypes.add_type('image/webp', '.webp')
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mimetypes.add_type('image/avif', '.avif')
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# override potentially incorrect mimetypes
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mimetypes.add_type('text/css', '.css')
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if not cmd_opts.share and not cmd_opts.listen:
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# fix gradio phoning home
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gradio.utils.version_check = lambda: None
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