Add pixel width to seam mask node

Author: ProGamerGov

nodes.py

@@ -897,14 +897,15 @@ def run(
 
 
 def _create_center_seam_mask(
-    x: torch.Tensor, frac_width: float = 0.10, feather: int = 0
+    x: torch.Tensor, frac_width: float = 0.10, pixel_width: int = 0, feather: int = 0
 ) -> torch.Tensor:
     """
     For a ComfyUI-style mask: shape [B, H, W], values 0 or 1, with optional feathering.
 
     Args:
         x (torch.Tensor): input tensor with shape [B, H, W, C].
         frac_width (float, optional): fraction of input width for the vertical strip.
+        pixel_width (int, optional): width of the seam in pixels (if > 0).
         feather (int, optional): pixel size of feathering on both sides of the mask.
 
     Returns:
@@ -913,7 +914,12 @@ def _create_center_seam_mask(
     # Extract batch, height, and width from x
     B, H, W, *_ = x.shape
 
-    strip = max(1, int(W * frac_width))
+    # Determine strip width
+    if pixel_width > 0:
+        strip = pixel_width
+    else:
+        strip = max(1, int(W * frac_width))
+
     x0 = (W - strip) // 2
     x1 = x0 + strip
 
@@ -970,7 +976,15 @@ def INPUT_TYPES(s) -> Dict:
         return {
             "required": {
                 "image": ("IMAGE", {"default": None}),
-                "seam_mask_width": ("FLOAT", {"default": 0.10}),
+                "frac_width": ("FLOAT", {"default": 0.10}),
+                "pixel_width": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "tooltip": "Width of the seam in pixels."
+                        + " If > 0, frac_width is ignored in favour of width_pixel.",
+                    },
+                ),
                 "feather": (
                     "INT",
                     {"default": 0, "tooltip": "Pixel size of the feathering."},
@@ -996,15 +1010,16 @@ def INPUT_TYPES(s) -> Dict:
     def run(
         self,
         image: torch.Tensor,
-        seam_mask_width: float = 0.10,
+        frac_width: float = 0.10,
+        pixel_width: int = 0,
         feather: int = 0,
         roll_x_by_50_percent: bool = False,
     ) -> Tuple[torch.Tensor]:
         assert image.dim() == 4, "Image should have 4 dimensions"
         _, H, W, _ = image.shape
         px_half = W // 2
         seam_mask = _create_center_seam_mask(
-            image, frac_width=seam_mask_width, feather=feather
+            image, frac_width=frac_width, pixel_width=pixel_width, feather=feather
         )
 
         if roll_x_by_50_percent:
@@ -1147,7 +1162,7 @@ def INPUT_TYPES(s) -> Dict:
         }
 
     RETURN_TYPES = ("MASK",)
-    RETURN_NAMES = ("Seam Mask",)
+    RETURN_NAMES = ("Pole Mask",)
 
     FUNCTION = "run"
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-pytorch360convert"
 description = "A collection of custom nodes for working with and converting between and working with 360 degree equirectangular images, cubemap, and perspective images. Also includes Circular padding Conv2d options for models and VAEs, along with nodes to fix seams and polar artifacts. Panoramic 360 images are also sometimes known as VR photography (virtual reality), HDRI environments (ex: skyboxes), image spheres, spherical images, 360 pano."
-version = "1.1.1"
+version = "1.1.2"
 license = {file = "LICENSE"}
 dependencies = ["pytorch360convert"]