Switch to a continous blend for cond. image.

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
+            # Smoothly interpolate between the masked and unmasked latent conditioning image.
-            if getattr(self, "inpainting_mask_image", shared.opts.inpainting_mask_image):
+            conditioning_image = torch.lerp(
-                conditioning_image = conditioning_image * (1.0 - conditioning_mask)                
+                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))
 

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}),
 }))
 
 

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),
 ]