diff --git a/modules/processing.py b/modules/processing.py index 23ee5e02..02292bdc 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -769,9 +769,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): # Create another latent image, this time with a masked version of the original input. conditioning_mask = conditioning_mask.to(image.device) - conditioning_image = image - if getattr(self, "inpainting_mask_image", shared.opts.inpainting_mask_image): - conditioning_image = conditioning_image * (1.0 - conditioning_mask) + # Smoothly interpolate between the masked and unmasked latent conditioning image. + conditioning_image = torch.lerp( + image, + image * (1.0 - conditioning_mask), + getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) + ) conditioning_image = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(conditioning_image)) diff --git a/modules/shared.py b/modules/shared.py index 1d0ff1a1..e0ffb824 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -320,7 +320,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), - "inpainting_mask_image": OptionInfo(True, "Mask original image for conditioning used by inpainting model."), + "inpainting_mask_weight": OptionInfo(1.0, "Blend betweeen an unmasked and masked conditioning image for inpainting models.", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), })) diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 0843adcc..f5255786 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -153,9 +153,6 @@ def str_permutations(x): """dummy function for specifying it in AxisOption's type when you want to get a list of permutations""" return x -def str_to_bool(x): - return "true" in x.lower().strip() - AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value", "confirm"]) AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value", "confirm"]) @@ -180,7 +177,7 @@ axis_options = [ AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None), AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None), AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None), - AxisOption("Mask Conditioning Image", str_to_bool, apply_field("inpainting_mask_image"), format_value_add_label, None), + AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight"), format_value_add_label, None), ]