change base model

app_masked.py

@@ -12,7 +12,7 @@ from diffusers import (
     DiffusionPipeline,
 )
 
-BASE_MODEL = "stabilityai/stable-diffusion-xl-base-1.0"
+BASE_MODEL = "RunDiffusion/Juggernaut-XL-v9"
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -48,15 +48,12 @@ def image_to_image(
     time_cost_str = ''
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
 
-    gray_image = input_image.convert("L")
-    gray_image = Image.merge("RGB", (gray_image, gray_image, gray_image))
-
     generator = torch.Generator(device=DEVICE).manual_seed(seed)
     generated_image = basepipeline(
         generator=generator,
         prompt=edit_prompt,
         negative_prompt=DEFAULT_NEGATIVE_PROMPT,
-        original_image=gray_image,
+        original_image=input_image,
         mask=mask_image,
         guidance_scale=guidance_scale,
         num_inference_steps=num_steps,

pipelines/masked_stable_diffusion_xl_img2img.py

@@ -214,6 +214,8 @@ class MaskedStableDiffusionXLImg2ImgPipeline(StableDiffusionXLImg2ImgPipeline):
             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
+
         if original_image is None:
             original_image = image
         if prompt is not None and isinstance(prompt, str):