Organized the settings and UI of soft inpainting to allow for toggling the feature, and centralizes default values to reduce the amount of copy-pasta.

modules/img2img.py

@@ -15,6 +15,7 @@ import modules.shared as shared
 import modules.processing as processing
 from modules.ui import plaintext_to_html
 import modules.scripts
+import modules.soft_inpainting as si
 
 
 def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=False, scale_by=1.0, use_png_info=False, png_info_props=None, png_info_dir=None):
@@ -162,6 +163,7 @@ def img2img(id_task: str,
             sampler_name: str,
             mask_blur: int,
             mask_alpha: float,
+            mask_blend_enabled: bool,
             mask_blend_power: float,
             mask_blend_scale: float,
             inpaint_detail_preservation: float,
@@ -227,6 +229,9 @@ def img2img(id_task: str,
 
     assert 0. <= denoising_strength <= 1., 'can only work with strength in [0.0, 1.0]'
 
+    soft_inpainting = si.SoftInpaintingSettings(mask_blend_power, mask_blend_scale, inpaint_detail_preservation) \
+        if mask_blend_enabled else None
+
     p = StableDiffusionProcessingImg2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_img2img_samples,
@@ -244,9 +249,7 @@ def img2img(id_task: str,
         init_images=[image],
         mask=mask,
         mask_blur=mask_blur,
-        mask_blend_power=mask_blend_power,
-        mask_blend_scale=mask_blend_scale,
-        inpaint_detail_preservation=inpaint_detail_preservation,
+        soft_inpainting=soft_inpainting,
         inpainting_fill=inpainting_fill,
         resize_mode=resize_mode,
         denoising_strength=denoising_strength,
@@ -267,9 +270,8 @@ def img2img(id_task: str,
 
     if mask:
         p.extra_generation_params["Mask blur"] = mask_blur
-        p.extra_generation_params["Mask blending bias"] = mask_blend_power
-        p.extra_generation_params["Mask blending preservation"] = mask_blend_scale
-        p.extra_generation_params["Mask blending contrast boost"] = inpaint_detail_preservation
+        if soft_inpainting is not None:
+            soft_inpainting.add_generation_params(p.extra_generation_params)
 
     with closing(p):
         if is_batch:

modules/processing.py

@@ -30,6 +30,7 @@ import modules.sd_models as sd_models
 import modules.sd_vae as sd_vae
 from ldm.data.util import AddMiDaS
 from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion
+import modules.soft_inpainting as si
 
 from einops import repeat, rearrange
 from blendmodes.blend import blendLayers, BlendType
@@ -1425,9 +1426,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
     mask_blur_x: int = 4
     mask_blur_y: int = 4
     mask_blur: int = None
-    mask_blend_power: float = 1
-    mask_blend_scale: float = 0.5
-    inpaint_detail_preservation: float = 4
+    soft_inpainting: si.SoftInpaintingParameters = si.default
     inpainting_fill: int = 0
     inpaint_full_res: bool = True
     inpaint_full_res_padding: int = 0

modules/sd_samplers_cfg_denoiser.py

@@ -6,6 +6,7 @@ import modules.shared as shared
 from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
 from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
 from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback
+import modules.soft_inpainting as si
 
 
 def catenate_conds(conds):
@@ -43,9 +44,7 @@ class CFGDenoiser(torch.nn.Module):
         self.model_wrap = None
         self.mask = None
         self.nmask = None
-        self.mask_blend_power = 1
-        self.mask_blend_scale = 0.5
-        self.inpaint_detail_preservation = 4
+        self.soft_inpainting: si.SoftInpaintingParameters = None
         self.init_latent = None
         self.steps = None
         """number of steps as specified by user in UI"""
@@ -95,7 +94,8 @@ class CFGDenoiser(torch.nn.Module):
         self.sampler.sampler_extra_args['uncond'] = uc
 
     def forward(self, x, sigma, uncond, cond, cond_scale, s_min_uncond, image_cond):
-        def latent_blend(a, b, t):
+        def latent_blend(a, b, t, one_minus_t=None):
+
             """
             Interpolates two latent image representations according to the parameter t,
             where the interpolated vectors' magnitudes are also interpolated separately.
@@ -104,7 +104,11 @@ class CFGDenoiser(torch.nn.Module):
             """
             # NOTE: We use inplace operations wherever possible.
 
-            one_minus_t = 1 - t
+            if one_minus_t is None:
+                one_minus_t = 1 - t
+
+            if self.soft_inpainting is None:
+                return a * one_minus_t + b * t
 
             # Linearly interpolate the image vectors.
             a_scaled = a * one_minus_t
@@ -119,10 +123,10 @@ class CFGDenoiser(torch.nn.Module):
             current_magnitude = torch.norm(image_interp, p=2, dim=1).to(torch.float64).add_(0.00001)
 
             # Interpolate the powered magnitudes, then un-power them (bring them back to a power of 1).
-            a_magnitude = torch.norm(a, p=2, dim=1).to(torch.float64).pow_(self.inpaint_detail_preservation) * one_minus_t
-            b_magnitude = torch.norm(b, p=2, dim=1).to(torch.float64).pow_(self.inpaint_detail_preservation) * t
+            a_magnitude = torch.norm(a, p=2, dim=1).to(torch.float64).pow_(self.soft_inpainting.inpaint_detail_preservation) * one_minus_t
+            b_magnitude = torch.norm(b, p=2, dim=1).to(torch.float64).pow_(self.soft_inpainting.inpaint_detail_preservation) * t
             desired_magnitude = a_magnitude
-            desired_magnitude.add_(b_magnitude).pow_(1 / self.inpaint_detail_preservation)
+            desired_magnitude.add_(b_magnitude).pow_(1 / self.soft_inpainting.inpaint_detail_preservation)
             del a_magnitude, b_magnitude, one_minus_t
 
             # Change the linearly interpolated image vectors' magnitudes to the value we want.
@@ -156,7 +160,10 @@ class CFGDenoiser(torch.nn.Module):
 
             NOTE: "mask" is not used
             """
-            return torch.pow(nmask, (_sigma ** self.mask_blend_power) * self.mask_blend_scale)
+            if self.soft_inpainting is None:
+                return nmask
+
+            return torch.pow(nmask, (_sigma ** self.soft_inpainting.mask_blend_power) * self.soft_inpainting.mask_blend_scale)
 
         if state.interrupted or state.skipped:
             raise sd_samplers_common.InterruptedException
@@ -176,7 +183,10 @@ class CFGDenoiser(torch.nn.Module):
 
         # Blend in the original latents (before)
         if self.mask_before_denoising and self.mask is not None:
-            x = latent_blend(self.init_latent, x, get_modified_nmask(self.nmask, sigma))
+            if self.soft_inpainting is None:
+                x = latent_blend(self.init_latent, x, self.nmask, self.mask)
+            else:
+                x = latent_blend(self.init_latent, x, get_modified_nmask(self.nmask, sigma))
 
         batch_size = len(conds_list)
         repeats = [len(conds_list[i]) for i in range(batch_size)]
@@ -279,7 +289,10 @@ class CFGDenoiser(torch.nn.Module):
 
         # Blend in the original latents (after)
         if not self.mask_before_denoising and self.mask is not None:
-            denoised = latent_blend(self.init_latent, denoised, get_modified_nmask(self.nmask, sigma))
+            if self.soft_inpainting is None:
+                denoised = latent_blend(self.init_latent, denoised, self.nmask, self.mask)
+            else:
+                denoised = latent_blend(self.init_latent, denoised, get_modified_nmask(self.nmask, sigma))
 
         self.sampler.last_latent = self.get_pred_x0(torch.cat([x_in[i:i + 1] for i in denoised_image_indexes]), torch.cat([x_out[i:i + 1] for i in denoised_image_indexes]), sigma)
 

modules/sd_samplers_common.py

@@ -277,9 +277,7 @@ class Sampler:
         self.model_wrap_cfg.p = p
         self.model_wrap_cfg.mask = p.mask if hasattr(p, 'mask') else None
         self.model_wrap_cfg.nmask = p.nmask if hasattr(p, 'nmask') else None
-        self.model_wrap_cfg.mask_blend_power = p.mask_blend_power if hasattr(p, 'mask_blend_power') else None
-        self.model_wrap_cfg.mask_blend_scale = p.mask_blend_scale if hasattr(p, 'mask_blend_scale') else None
-        self.model_wrap_cfg.inpaint_detail_preservation = p.inpaint_detail_preservation if hasattr(p, 'inpaint_detail_preservation') else None
+        self.model_wrap_cfg.soft_inpainting = p.soft_inpainting if hasattr(p, 'soft_inpainting') else None
         self.model_wrap_cfg.step = 0
         self.model_wrap_cfg.image_cfg_scale = getattr(p, 'image_cfg_scale', None)
         self.eta = p.eta if p.eta is not None else getattr(opts, self.eta_option_field, 0.0)

modules/soft_inpainting.py

@@ -0,0 +1,133 @@
+class SoftInpaintingSettings:
+    def __init__(self, mask_blend_power, mask_blend_scale, inpaint_detail_preservation):
+        self.mask_blend_power = mask_blend_power
+        self.mask_blend_scale = mask_blend_scale
+        self.inpaint_detail_preservation = inpaint_detail_preservation
+
+    def get_paste_fields(self):
+        return [
+            (self.mask_blend_power, gen_param_labels.mask_blend_power),
+            (self.mask_blend_scale, gen_param_labels.mask_blend_scale),
+            (self.inpaint_detail_preservation, gen_param_labels.inpaint_detail_preservation),
+        ]
+
+    def add_generation_params(self, dest):
+        dest[enabled_gen_param_label] = True
+        dest[gen_param_labels.mask_blend_power] = self.mask_blend_power
+        dest[gen_param_labels.mask_blend_scale] = self.mask_blend_scale
+        dest[gen_param_labels.inpaint_detail_preservation] = self.inpaint_detail_preservation
+
+
+enabled_ui_label = "Soft inpainting"
+enabled_gen_param_label = "Soft inpainting enabled"
+enabled_el_id = "soft_inpainting_enabled"
+
+default = SoftInpaintingSettings(1, 0.5, 4)
+ui_labels = SoftInpaintingSettings("Schedule bias", "Preservation strength", "Transition contrast boost")
+
+ui_info = SoftInpaintingSettings(
+    mask_blend_power="Shifts when preservation of original content occurs during denoising.",
+                     # "Below 1: Stronger preservation near the end (with low sigma)\n"
+                     # "1: Balanced (proportional to sigma)\n"
+                     # "Above 1: Stronger preservation in the beginning (with high sigma)",
+    mask_blend_scale="How strongly partially masked content should be preserved.",
+                     # "Low values: Favors generated content.\n"
+                     # "High values: Favors original content.",
+    inpaint_detail_preservation="Amplifies the contrast that may be lost in partially masked regions.")
+
+gen_param_labels = SoftInpaintingSettings("Soft inpainting schedule bias", "Soft inpainting preservation strength", "Soft inpainting transition contrast boost")
+el_ids = SoftInpaintingSettings("mask_blend_power", "mask_blend_scale", "inpaint_detail_preservation")
+
+
+def gradio_ui():
+    import gradio as gr
+    from modules.ui_components import InputAccordion
+    """
+            with InputAccordion(False, label="Refiner", elem_id=self.elem_id("enable")) as enable_refiner:
+            with gr.Row():
+                refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=sd_models.checkpoint_tiles(), value='', tooltip="switch to another model in the middle of generation")
+                create_refresh_button(refiner_checkpoint, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, self.elem_id("checkpoint_refresh"))
+
+                refiner_switch_at = gr.Slider(value=0.8, label="Switch at", minimum=0.01, maximum=1.0, step=0.01, elem_id=self.elem_id("switch_at"), tooltip="fraction of sampling steps when the switch to refiner model should happen; 1=never, 0.5=switch in the middle of generation")
+
+    """
+    with InputAccordion(False, label=enabled_ui_label, elem_id=enabled_el_id) as soft_inpainting_enabled:
+        with gr.Group():
+            gr.Markdown(
+                """
+                Soft inpainting allows you to **seamlessly blend original content with inpainted content** according to the mask opacity.
+                **High _Mask blur_** values are recommended!
+                """)
+
+            result = SoftInpaintingSettings(
+                gr.Slider(label=ui_labels.mask_blend_power,
+                          info=ui_info.mask_blend_power,
+                          minimum=0,
+                          maximum=8,
+                          step=0.1,
+                          value=default.mask_blend_power,
+                          elem_id=el_ids.mask_blend_power),
+                gr.Slider(label=ui_labels.mask_blend_scale,
+                          info=ui_info.mask_blend_scale,
+                          minimum=0,
+                          maximum=8,
+                          step=0.05,
+                          value=default.mask_blend_scale,
+                          elem_id=el_ids.mask_blend_scale),
+                gr.Slider(label=ui_labels.inpaint_detail_preservation,
+                          info=ui_info.inpaint_detail_preservation,
+                          minimum=1,
+                          maximum=32,
+                          step=0.5,
+                          value=default.inpaint_detail_preservation,
+                          elem_id=el_ids.inpaint_detail_preservation))
+
+            with gr.Accordion("Help", open=False):
+                gr.Markdown(
+                    f"""
+                    ### {ui_labels.mask_blend_power}
+                    
+                    The blending strength of original content is scaled proportionally with the decreasing noise level values at each step (sigmas).
+                    This ensures that the influence of the denoiser and original content preservation is roughly balanced at each step.
+                    This balance can be shifted using this parameter, controlling whether earlier or later steps have stronger preservation.
+                    
+                    - **Below 1**: Stronger preservation near the end (with low sigma)
+                    - **1**: Balanced (proportional to sigma)
+                    - **Above 1**: Stronger preservation in the beginning (with high sigma)
+                    """)
+                gr.Markdown(
+                    f"""
+                    ### {ui_labels.mask_blend_scale}
+                    
+                    Skews whether partially masked image regions should be more likely to preserve the original content or favor inpainted content.
+                    This may need to be adjusted depending on the {ui_labels.mask_blend_power}, CFG Scale, prompt and Denoising strength.
+                    
+                    - **Low values**: Favors generated content.
+                    - **High values**: Favors original content.
+                    """)
+                gr.Markdown(
+                    f"""
+                    ### {ui_labels.inpaint_detail_preservation}
+                    
+                    This parameter controls how the original latent vectors and denoised latent vectors are interpolated.
+                    With higher values, the magnitude of the resulting blended vector will be closer to the maximum of the two interpolated vectors.
+                    This can prevent the loss of contrast that occurs with linear interpolation.
+                    
+                    - **Low values**: Softer blending, details may fade.
+                    - **High values**: Stronger contrast, may over-saturate colors.
+                    """)
+
+    return (
+        [
+            soft_inpainting_enabled,
+            result.mask_blend_power,
+            result.mask_blend_scale,
+            result.inpaint_detail_preservation
+        ],
+        [
+            (soft_inpainting_enabled, enabled_gen_param_label),
+            (result.mask_blend_power, gen_param_labels.mask_blend_power),
+            (result.mask_blend_scale, gen_param_labels.mask_blend_scale),
+            (result.inpaint_detail_preservation, gen_param_labels.inpaint_detail_preservation)
+        ]
+    )

modules/ui.py

@@ -29,6 +29,7 @@ import modules.shared as shared
 from modules import prompt_parser
 from modules.sd_hijack import model_hijack
 from modules.generation_parameters_copypaste import image_from_url_text
+import modules.soft_inpainting as si
 
 create_setting_component = ui_settings.create_setting_component
 
@@ -678,9 +679,16 @@ def create_ui():
                             with FormRow():
                                 mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id="img2img_mask_blur")
                                 mask_alpha = gr.Slider(label="Mask transparency", visible=False, elem_id="img2img_mask_alpha")
+
+                            with FormRow():
+                                soft_inpainting = si.gradio_ui()
+
+
+                            """
                                 mask_blend_power = gr.Slider(label='Blending bias', minimum=0, maximum=8, step=0.1, value=1, elem_id="img2img_mask_blend_power")
                                 mask_blend_scale = gr.Slider(label='Blending preservation', minimum=0, maximum=8, step=0.05, value=0.5, elem_id="img2img_mask_blend_scale")
                                 inpaint_detail_preservation = gr.Slider(label='Blending contrast boost', minimum=1, maximum=32, step=0.5, value=4, elem_id="img2img_mask_blend_offset")
+                            """
 
                             with FormRow():
                                 inpainting_mask_invert = gr.Radio(label='Mask mode', choices=['Inpaint masked', 'Inpaint not masked'], value='Inpaint masked', type="index", elem_id="img2img_mask_mode")
@@ -736,9 +744,7 @@ def create_ui():
                     sampler_name,
                     mask_blur,
                     mask_alpha,
-                    mask_blend_power,
-                    mask_blend_scale,
-                    inpaint_detail_preservation,
+                    *(soft_inpainting[0]),
                     inpainting_fill,
                     batch_count,
                     batch_size,
@@ -837,11 +843,10 @@ def create_ui():
                 (toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()),
                 (denoising_strength, "Denoising strength"),
                 (mask_blur, "Mask blur"),
-                (mask_blend_power, "Mask blending bias"),
-                (mask_blend_scale, "Mask blending preservation"),
-                (inpaint_detail_preservation, "Mask blending contrast boost"),
+                *(soft_inpainting[1]),
                 *scripts.scripts_img2img.infotext_fields
             ]
+
             parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields, override_settings)
             parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields, override_settings)
             parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding(

scripts/outpainting_mk_2.py

@@ -10,6 +10,7 @@ from PIL import Image, ImageDraw
 from modules import images
 from modules.processing import Processed, process_images
 from modules.shared import opts, state
+import modules.soft_inpainting as si
 
 
 # this function is taken from https://github.com/parlance-zz/g-diffuser-bot
@@ -133,16 +134,14 @@ class Script(scripts.Script):
 
         pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=self.elem_id("pixels"))
         mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8, elem_id=self.elem_id("mask_blur"))
-        mask_blend_power = gr.Slider(label='Blending bias', minimum=0, maximum=8, step=0.1, value=1, elem_id=self.elem_id("mask_blend_power"))
-        mask_blend_scale = gr.Slider(label='Blending preservation', minimum=0, maximum=8, step=0.05, value=0.5, elem_id=self.elem_id("mask_blend_scale"))
-        inpaint_detail_preservation = gr.Slider(label='Blending contrast boost', minimum=1, maximum=32, step=0.5, value=4, elem_id=self.elem_id("inpaint_detail_preservation"))
+        soft_inpainting = si.gradio_ui()[0]
         direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'], elem_id=self.elem_id("direction"))
         noise_q = gr.Slider(label="Fall-off exponent (lower=higher detail)", minimum=0.0, maximum=4.0, step=0.01, value=1.0, elem_id=self.elem_id("noise_q"))
         color_variation = gr.Slider(label="Color variation", minimum=0.0, maximum=1.0, step=0.01, value=0.05, elem_id=self.elem_id("color_variation"))
 
-        return [info, pixels, mask_blur, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, direction, noise_q, color_variation]
+        return [info, pixels, mask_blur, *soft_inpainting, direction, noise_q, color_variation]
 
-    def run(self, p, _, pixels, mask_blur, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, direction, noise_q, color_variation):
+    def run(self, p, _, pixels, mask_blur, mask_blend_enabled, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, direction, noise_q, color_variation):
         initial_seed_and_info = [None, None]
 
         process_width = p.width
@@ -170,9 +169,9 @@ class Script(scripts.Script):
 
         p.mask_blur_x = mask_blur_x*4
         p.mask_blur_y = mask_blur_y*4
-        p.mask_blend_power = mask_blend_power
-        p.mask_blend_scale = mask_blend_scale
-        p.inpaint_detail_preservation = inpaint_detail_preservation
+
+        p.soft_inpainting = si.SoftInpaintingSettings(mask_blend_power, mask_blend_scale, inpaint_detail_preservation) \
+            if mask_blend_enabled else None
 
         init_img = p.init_images[0]
         target_w = math.ceil((init_img.width + left + right) / 64) * 64

scripts/poor_mans_outpainting.py

@@ -7,6 +7,7 @@ from PIL import Image, ImageDraw
 from modules import images, devices
 from modules.processing import Processed, process_images
 from modules.shared import opts, state
+import modules.soft_inpainting as si
 
 
 class Script(scripts.Script):
@@ -22,23 +23,19 @@ class Script(scripts.Script):
 
         pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=self.elem_id("pixels"))
         mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id=self.elem_id("mask_blur"))
-        mask_blend_power = gr.Slider(label='Blending bias', minimum=0, maximum=8, step=0.1, value=1, elem_id=self.elem_id("mask_blend_power"))
-        mask_blend_scale = gr.Slider(label='Blending preservation', minimum=0, maximum=8, step=0.05, value=0.5, elem_id=self.elem_id("mask_blend_scale"))
-        inpaint_detail_preservation = gr.Slider(label='Blending contrast boost', minimum=1, maximum=32, step=0.5, value=4, elem_id=self.elem_id("inpaint_detail_preservation"))
+        soft_inpainting = si.gradio_ui()[0]
         inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", elem_id=self.elem_id("inpainting_fill"))
         direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'], elem_id=self.elem_id("direction"))
 
-        return [pixels, mask_blur, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, inpainting_fill, direction]
+        return [pixels, mask_blur, *soft_inpainting, inpainting_fill, direction]
 
-    def run(self, p, pixels, mask_blur, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, inpainting_fill, direction):
+    def run(self, p, pixels, mask_blur, mask_blend_enabled, mask_blend_power, mask_blend_scale, inpaint_detail_preservation, inpainting_fill, direction):
         initial_seed = None
         initial_info = None
 
         p.mask_blur = mask_blur * 2
-        p.mask_blend_power = mask_blend_power
-        p.mask_blend_scale = mask_blend_scale
-        p.inpaint_detail_preservation = inpaint_detail_preservation
-
+        p.soft_inpainting = si.SoftInpaintingSettings(mask_blend_power, mask_blend_scale, inpaint_detail_preservation) \
+            if mask_blend_enabled else None
         p.inpainting_fill = inpainting_fill
         p.inpaint_full_res = False
 

test/test_img2img.py

@@ -1,6 +1,7 @@
 
 import pytest
 import requests
+import modules.soft_inpainting as si
 
 
 @pytest.fixture()
@@ -24,9 +25,10 @@ def simple_img2img_request(img2img_basic_image_base64):
         "inpainting_mask_invert": False,
         "mask": None,
         "mask_blur": 4,
-        "mask_blend_power": 1,
-        "mask_blend_scale": 0.5,
-        "inpaint_detail_preservation": 4,
+        "mask_blend_enabled": True,
+        "mask_blend_power": si.default.mask_blend_power,
+        "mask_blend_scale": si.default.mask_blend_scale,
+        "inpaint_detail_preservation": si.default.inpaint_detail_preservation,
         "n_iter": 1,
         "negative_prompt": "",
         "override_settings": {},