add an option to choose what you want to see in live preview (Live preview subject) and moves live preview settings to its own tab

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:

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}),

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