add blur strength in inputs

app.py

@@ -45,7 +45,7 @@ stable_diffusion_negative_prompt = ("low quality, unformed, ugly, low resolution
                           depth_backbone="vitb_rn50_384")
 
 
-@spaces.GPU(duration=120)
+@spaces.GPU(duration=180)
 def greet(material_exemplar: Image.Image,
           raw_cloth: Image.Image = None,
           _controlnet_conditioning_scale=0.9,
@@ -55,7 +55,8 @@ def greet(material_exemplar: Image.Image,
           occasion=None,
           clothing_type=None,
           cloth_attrs=None,
-          mask_padding=5):
+          mask_padding=0,
+          blur_mask=3):
     """
     Compute depth map from input_image
     """
@@ -91,7 +92,7 @@ def greet(material_exemplar: Image.Image,
 
         depth_map = create_depth_map(img, model)
 
-        mask = create_mask(raw_cloth, padding=mask_padding)
+        mask = create_mask(raw_cloth, blur=blur_mask, padding=mask_padding)
 
         """
         Process material exemplar and resize all images
@@ -141,9 +142,12 @@ def get_tab(gender: Literal["Male", "Female", "Unisex"]):
                         guidance_scale = gr.Slider(minimum=0, maximum=15, step=0.1, value=7.5,
                                                    label="Guidance Scale",
                                                    interactive=True)
-                        mask_padding = gr.Slider(minimum=0, maximum=15, step=1, value=5,
+                        mask_padding = gr.Slider(minimum=-15, maximum=15, step=1, value=0,
                                                  label="Mask Padding",
                                                  interactive=True)
+                        blur_mask = gr.Slider(minimum=0, maximum=15, step=1, value=3,
+                                              label="Mask Blur",
+                                              interactive=True)
                     with gr.Column():
                         material_image = gr.Image(type="pil", label="material examplar")
                         raw_image_input = gr.Image(type="pil", label="raw image")
@@ -189,7 +193,8 @@ def get_tab(gender: Literal["Male", "Female", "Unisex"]):
                                                  occasion,
                                                  clothing_type_input,
                                                  state,
-                                                 mask_padding],
+                                                 mask_padding,
+                                                 blur_mask],
                                          outputs=[raw_image, output_image, mask_image, depth_image, credits])
 
 

processing/mask.py

@@ -8,7 +8,7 @@ from torchvision.transforms import Compose
 from DPT.dpt.transforms import PrepareForNet, NormalizeImage, Resize
 
 
-def create_mask(image, blur=False, padding=0):
+def create_mask(image, blur=0, padding=0):
     rm_bg = remove(np.array(image), post_process_mask=True, only_mask=True)
     rm_bg = Image.fromarray((rm_bg * 255).astype(np.uint8))
     rm_bg = rm_bg.resize(image.size, resample=Image.BILINEAR)
@@ -17,8 +17,8 @@ def create_mask(image, blur=False, padding=0):
 
     # Convert mask back to uint8 for PIL compatibility
     pil_mask = Image.fromarray((padded_mask * 255).astype(np.uint8))
-    if blur:
-        pil_mask = pil_mask.filter(ImageFilter.GaussianBlur(3))
+    if blur > 0:
+        pil_mask = pil_mask.filter(ImageFilter.GaussianBlur(blur))
     return pil_mask.resize((1024, 1024))
 
 

processing/mask.pyi

@@ -3,11 +3,11 @@ import torch
 from PIL.Image import Image
 
 
-def create_mask(image: Image, blur: bool = ..., padding: int = ...) -> Image:
+def create_mask(image: Image, blur: int = ..., padding: int = ...) -> Image:
     """
         Create a mask from the input image.
         :param image: The input image.
-        :param blur: Whether to blur the mask. Default is True.
+        :param blur: Blur strength. Default is 0.
         :param padding: The padding around the object in the mask. Default is 0.
     """
     ...