Loading modules/img2img.py +2 −1 Original line number Diff line number Diff line Loading @@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): processed_image.save(os.path.join(output_dir, filename)) def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) is_batch = mode == 5 Loading Loading @@ -156,6 +156,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s inpainting_mask_invert=inpainting_mask_invert, override_settings=override_settings, enable_karras=enable_k_sched, k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho Loading modules/processing.py +3 −1 Original line number Diff line number Diff line Loading @@ -106,7 +106,7 @@ class StableDiffusionProcessing: """ The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing """ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, k_sched_type: str = "karras", sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) Loading Loading @@ -147,6 +147,7 @@ class StableDiffusionProcessing: self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option self.s_noise = s_noise or opts.s_noise self.enable_karras = enable_karras self.k_sched_type = k_sched_type self.sigma_max = sigma_max self.sigma_min = sigma_min self.rho = rho Loading Loading @@ -563,6 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Steps": p.steps, "Sampler": p.sampler_name, "Enable Custom Karras Schedule": p.enable_karras, "Karras Scheduler Type": p.k_sched_type, "Karras Scheduler sigma_max": p.sigma_max, "Karras Scheduler sigma_min": p.sigma_min, "Karras Scheduler rho": p.rho, Loading modules/sd_samplers_kdiffusion.py +15 −4 Original line number Diff line number Diff line Loading @@ -44,6 +44,12 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } k_diffusion_scheduler = { 'karras': k_diffusion.sampling.get_sigmas_karras, 'exponential': k_diffusion.sampling.get_sigmas_exponential, 'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential } class CFGDenoiser(torch.nn.Module): """ Loading Loading @@ -305,10 +311,15 @@ class KDiffusionSampler: if p.sampler_noise_scheduler_override: sigmas = p.sampler_noise_scheduler_override(steps) elif p.enable_karras: sigma_max = p.sigma_max sigma_min = p.sigma_min rho = p.rho sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, device=shared.device) print(p.k_sched_type, p.sigma_min, p.sigma_max, p.rho) sigmas_func = k_diffusion_scheduler[p.k_sched_type] sigmas_kwargs = { 'sigma_min': p.sigma_min, 'sigma_max': p.sigma_max } if p.k_sched_type != 'exponential': sigmas_kwargs['rho'] = p.rho sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device) elif self.config is not None and self.config.options.get('scheduler', None) == 'karras': sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) Loading modules/txt2img.py +2 −1 Original line number Diff line number Diff line Loading @@ -7,7 +7,7 @@ from modules.ui import plaintext_to_html def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.StableDiffusionProcessingTxt2Img( Loading Loading @@ -44,6 +44,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, enable_karras=enable_k_sched, k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho Loading modules/ui.py +16 −10 Original line number Diff line number Diff line Loading @@ -514,9 +514,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="txt2img_karras_scheduler") as t2i_k_sched_options: with FormRow(elem_id="txt2img_karras_scheduler_row1", variant="compact"): t2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") t2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") t2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") t2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: Loading Loading @@ -587,8 +588,9 @@ def create_ui(): hr_negative_prompt, override_settings, t2i_enable_k_sched, t2i_k_sched_sigma_max, t2i_k_sched_type, t2i_k_sched_sigma_min, t2i_k_sched_sigma_max, t2i_k_sched_rho ] + custom_inputs, Loading Loading @@ -675,6 +677,7 @@ def create_ui(): (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()), (t2i_enable_k_sched, "Enable Custom Karras Schedule"), (t2i_k_sched_type, "Karras Scheduler Type"), (t2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (t2i_k_sched_rho, "Karras Scheduler rho"), Loading Loading @@ -874,9 +877,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="img2img_karras_scheduler") as i2i_k_sched_options: with FormRow(elem_id="img2img_karras_scheduler_row1", variant="compact"): i2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") i2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") i2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") i2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: Loading Loading @@ -981,8 +985,9 @@ def create_ui(): img2img_batch_inpaint_mask_dir, override_settings, i2i_enable_k_sched, i2i_k_sched_sigma_max, i2i_k_sched_type, i2i_k_sched_sigma_min, i2i_k_sched_sigma_max, i2i_k_sched_rho ] + custom_inputs, outputs=[ Loading Loading @@ -1085,7 +1090,8 @@ def create_ui(): (steps, "Steps"), (sampler_index, "Sampler"), (restore_faces, "Face restoration"), (i2i_enable_k_sched, "Enable Karras Schedule"), (i2i_enable_k_sched, "Enable Custom Karras Schedule"), (i2i_k_sched_type, "Karras Scheduler Type"), (i2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (i2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (i2i_k_sched_rho, "Karras Scheduler rho"), Loading Loading
modules/img2img.py +2 −1 Original line number Diff line number Diff line Loading @@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): processed_image.save(os.path.join(output_dir, filename)) def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) is_batch = mode == 5 Loading Loading @@ -156,6 +156,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s inpainting_mask_invert=inpainting_mask_invert, override_settings=override_settings, enable_karras=enable_k_sched, k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho Loading
modules/processing.py +3 −1 Original line number Diff line number Diff line Loading @@ -106,7 +106,7 @@ class StableDiffusionProcessing: """ The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing """ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_karras: bool = False, k_sched_type: str = "karras", sigma_min: float=0.1, sigma_max: float=10.0, rho: float=7.0): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) Loading Loading @@ -147,6 +147,7 @@ class StableDiffusionProcessing: self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option self.s_noise = s_noise or opts.s_noise self.enable_karras = enable_karras self.k_sched_type = k_sched_type self.sigma_max = sigma_max self.sigma_min = sigma_min self.rho = rho Loading Loading @@ -563,6 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Steps": p.steps, "Sampler": p.sampler_name, "Enable Custom Karras Schedule": p.enable_karras, "Karras Scheduler Type": p.k_sched_type, "Karras Scheduler sigma_max": p.sigma_max, "Karras Scheduler sigma_min": p.sigma_min, "Karras Scheduler rho": p.rho, Loading
modules/sd_samplers_kdiffusion.py +15 −4 Original line number Diff line number Diff line Loading @@ -44,6 +44,12 @@ sampler_extra_params = { 'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'], } k_diffusion_scheduler = { 'karras': k_diffusion.sampling.get_sigmas_karras, 'exponential': k_diffusion.sampling.get_sigmas_exponential, 'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential } class CFGDenoiser(torch.nn.Module): """ Loading Loading @@ -305,10 +311,15 @@ class KDiffusionSampler: if p.sampler_noise_scheduler_override: sigmas = p.sampler_noise_scheduler_override(steps) elif p.enable_karras: sigma_max = p.sigma_max sigma_min = p.sigma_min rho = p.rho sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho, device=shared.device) print(p.k_sched_type, p.sigma_min, p.sigma_max, p.rho) sigmas_func = k_diffusion_scheduler[p.k_sched_type] sigmas_kwargs = { 'sigma_min': p.sigma_min, 'sigma_max': p.sigma_max } if p.k_sched_type != 'exponential': sigmas_kwargs['rho'] = p.rho sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device) elif self.config is not None and self.config.options.get('scheduler', None) == 'karras': sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item()) Loading
modules/txt2img.py +2 −1 Original line number Diff line number Diff line Loading @@ -7,7 +7,7 @@ from modules.ui import plaintext_to_html def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, sigma_min, sigma_max, rho, *args): def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, enable_k_sched, k_sched_type, sigma_min, sigma_max, rho, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.StableDiffusionProcessingTxt2Img( Loading Loading @@ -44,6 +44,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, enable_karras=enable_k_sched, k_sched_type=k_sched_type, sigma_min=sigma_min, sigma_max=sigma_max, rho=rho Loading
modules/ui.py +16 −10 Original line number Diff line number Diff line Loading @@ -514,9 +514,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="txt2img_karras_scheduler") as t2i_k_sched_options: with FormRow(elem_id="txt2img_karras_scheduler_row1", variant="compact"): t2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") t2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") t2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") t2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: Loading Loading @@ -587,8 +588,9 @@ def create_ui(): hr_negative_prompt, override_settings, t2i_enable_k_sched, t2i_k_sched_sigma_max, t2i_k_sched_type, t2i_k_sched_sigma_min, t2i_k_sched_sigma_max, t2i_k_sched_rho ] + custom_inputs, Loading Loading @@ -675,6 +677,7 @@ def create_ui(): (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()), (t2i_enable_k_sched, "Enable Custom Karras Schedule"), (t2i_k_sched_type, "Karras Scheduler Type"), (t2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (t2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (t2i_k_sched_rho, "Karras Scheduler rho"), Loading Loading @@ -874,9 +877,10 @@ def create_ui(): elif category == "karras_scheduler": with FormGroup(visible=False, elem_id="img2img_karras_scheduler") as i2i_k_sched_options: with FormRow(elem_id="img2img_karras_scheduler_row1", variant="compact"): i2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") i2i_k_sched_sigma_min = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") i2i_k_sched_rho = gr.Slider(minimum=3.0, maximum=10.0, step=0.5, label='rho', value=7.0, elem_id="txt2img_rho") i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras') i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min") i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max") i2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho") elif category == "batch": if not opts.dimensions_and_batch_together: Loading Loading @@ -981,8 +985,9 @@ def create_ui(): img2img_batch_inpaint_mask_dir, override_settings, i2i_enable_k_sched, i2i_k_sched_sigma_max, i2i_k_sched_type, i2i_k_sched_sigma_min, i2i_k_sched_sigma_max, i2i_k_sched_rho ] + custom_inputs, outputs=[ Loading Loading @@ -1085,7 +1090,8 @@ def create_ui(): (steps, "Steps"), (sampler_index, "Sampler"), (restore_faces, "Face restoration"), (i2i_enable_k_sched, "Enable Karras Schedule"), (i2i_enable_k_sched, "Enable Custom Karras Schedule"), (i2i_k_sched_type, "Karras Scheduler Type"), (i2i_k_sched_sigma_max, "Karras Scheduler sigma_max"), (i2i_k_sched_sigma_min, "Karras Scheduler sigma_min"), (i2i_k_sched_rho, "Karras Scheduler rho"), Loading
