renamed Inpainting strength infotext to Conditional mask weight, made it only appear if using inpainting model, made it possible to read the setting from it using the blue arrow button

2 files changed, 9 insertions, 1 deletions

diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index 985ec95e..1408ea05 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/modules/generation_parameters_copypaste.py
@@ -73,6 +73,7 @@ def integrate_settings_paste_fields(component_dict):
         'sd_hypernetwork': 'Hypernet',

         'sd_hypernetwork_strength': 'Hypernet strength',

         'CLIP_stop_at_last_layers': 'Clip skip',

+        'inpainting_mask_weight': 'Conditional mask weight',

         'sd_model_checkpoint': 'Model hash',

     }

     settings_paste_fields = [

diff --git a/modules/processing.py b/modules/processing.py
index fb30aa81..def95846 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -113,6 +113,7 @@ 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.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}

+        self.is_using_inpainting_conditioning = False

 

         if not seed_enable_extras:

             self.subseed = -1

@@ -133,6 +134,8 @@ class StableDiffusionProcessing():
             # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size.

             return x.new_zeros(x.shape[0], 5, 1, 1)

 

+        self.is_using_inpainting_conditioning = True

+

         height = height or self.height

         width = width or self.width

 

@@ -151,6 +154,8 @@ class StableDiffusionProcessing():
             # Dummy zero conditioning if we're not using inpainting model.

             return latent_image.new_zeros(latent_image.shape[0], 5, 1, 1)

 

+        self.is_using_inpainting_conditioning = True

+

         # Handle the different mask inputs

         if image_mask is not None:

             if torch.is_tensor(image_mask):

@@ -234,6 +239,7 @@ class Processed:
         self.negative_prompt = self.negative_prompt if type(self.negative_prompt) != list else self.negative_prompt[0]

         self.seed = int(self.seed if type(self.seed) != list else self.seed[0]) if self.seed is not None else -1

         self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1

+        self.is_using_inpainting_conditioning = p.is_using_inpainting_conditioning

 

         self.all_prompts = all_prompts or [self.prompt]

         self.all_seeds = all_seeds or [self.seed]

@@ -268,6 +274,7 @@ class Processed:
             "styles": self.styles,

             "job_timestamp": self.job_timestamp,

             "clip_skip": self.clip_skip,

+            "is_using_inpainting_conditioning": self.is_using_inpainting_conditioning,

         }

 

         return json.dumps(obj)

@@ -394,7 +401,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
         "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),

         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),

         "Denoising strength": getattr(p, 'denoising_strength', None),

-        "Inpainting strength": (None if getattr(p, 'denoising_strength', None) is None else getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight)),

+        "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,

         "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),

         "Clip skip": None if clip_skip <= 1 else clip_skip,

         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,