diff options
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/sd_samplers.py | 15 | ||||
| -rw-r--r-- | modules/shared.py | 13 | ||||
| -rw-r--r-- | modules/ui_progress.py | 2 |
3 files changed, 20 insertions, 10 deletions
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 01221b89..7616fded 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 c9988d4d..e0ec3136 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 592fda55..7cd312e4 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
|