test mask with Juggernaut-XL-v9

app_masked.py

@@ -24,7 +24,7 @@ DEFAULT_CATEGORY = "hair"
 basepipeline = DiffusionPipeline.from_pretrained(
     BASE_MODEL,
     torch_dtype=torch.float16,
-    use_safetensors=True,
+    # use_safetensors=True,
     custom_pipeline="./pipelines/masked_stable_diffusion_xl_img2img.py",
 )
 

pipelines/masked_stable_diffusion_xl_img2img.py

@@ -212,9 +212,9 @@ class MaskedStableDiffusionXLImg2ImgPipeline(StableDiffusionXLImg2ImgPipeline):
             pil_mask = mask
         if pil_mask.mode != "L":
             pil_mask = pil_mask.convert("L")
-        mask_blur = self.blur_mask(pil_mask, blur)
-        mask_compose = self.blur_mask(pil_mask, blur_compose)
-        mask_compose = (mask_blur + mask_compose) / 2
+        # mask_blur = self.blur_mask(pil_mask, blur)
+        # mask_compose = self.blur_mask(pil_mask, blur_compose)
+        mask_compose = self.blur_mask(pil_mask, blur)
 
         if original_image is None:
             original_image = image