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