diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 01221b898..7616fdedd 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -138,7 +138,7 @@ def samples_to_image_grid(samples, approximation=None): def store_latent(decoded): state.current_latent = decoded - if opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0: + if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0: if not shared.parallel_processing_allowed: shared.state.current_image = sample_to_image(decoded) @@ -243,7 +243,7 @@ class VanillaStableDiffusionSampler: self.nmask = p.nmask if hasattr(p, 'nmask') else None def adjust_steps_if_invalid(self, p, num_steps): - if (self.config.name == 'DDIM' and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): + if (self.config.name == 'DDIM' and p.ddim_discretize == 'uniform') or (self.config.name == 'PLMS'): valid_step = 999 / (1000 // num_steps) if valid_step == floor(valid_step): return int(valid_step) + 1 @@ -266,8 +266,7 @@ class VanillaStableDiffusionSampler: if image_conditioning is not None: conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]} unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} - - + samples = self.launch_sampling(t_enc + 1, lambda: self.sampler.decode(x1, conditioning, t_enc, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning)) return samples @@ -352,6 +351,11 @@ class CFGDenoiser(torch.nn.Module): x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]}) + if opts.live_preview_content == "Prompt": + store_latent(x_out[0:uncond.shape[0]]) + elif opts.live_preview_content == "Negative prompt": + store_latent(x_out[-uncond.shape[0]:]) + denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale) if self.mask is not None: @@ -423,7 +427,8 @@ class KDiffusionSampler: def callback_state(self, d): step = d['i'] latent = d["denoised"] - store_latent(latent) + if opts.live_preview_content == "Combined": + store_latent(latent) self.last_latent = latent if self.stop_at is not None and step > self.stop_at: diff --git a/modules/shared.py b/modules/shared.py index c9988d4d8..e0ec3136d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -176,7 +176,7 @@ class State: self.interrupted = True def nextjob(self): - if opts.show_progress_every_n_steps == -1: + if opts.live_previews_enable and opts.show_progress_every_n_steps == -1: self.do_set_current_image() self.job_no += 1 @@ -224,7 +224,7 @@ class State: if not parallel_processing_allowed: return - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.show_progress_every_n_steps > 0: + if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable: self.do_set_current_image() def do_set_current_image(self): @@ -423,8 +423,6 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"), options_templates.update(options_section(('ui', "User interface"), { "show_progressbar": OptionInfo(True, "Show progressbar"), - "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set to 0 to disable. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), - "show_progress_type": OptionInfo("Full", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), @@ -444,6 +442,13 @@ options_templates.update(options_section(('ui', "User interface"), { 'localization': OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), })) +options_templates.update(options_section(('ui', "Live previews"), { + "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), + "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), + "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), + "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), +})) + options_templates.update(options_section(('sampler-params', "Sampler parameters"), { "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}), "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), diff --git a/modules/ui_progress.py b/modules/ui_progress.py index 592fda55b..7cd312e4a 100644 --- a/modules/ui_progress.py +++ b/modules/ui_progress.py @@ -52,7 +52,7 @@ def check_progress_call(id_part): image = gr.update(visible=False) preview_visibility = gr.update(visible=False) - if opts.show_progress_every_n_steps != 0: + if opts.live_previews_enable: shared.state.set_current_image() image = shared.state.current_image