adding more nodes

backend/nodes/grain_edge.py

@@ -0,0 +1,51 @@
+"""Grain edge detection — detect grain boundaries using Laplacian edge detection."""
+
+from __future__ import annotations
+
+import numpy as np
+from scipy.ndimage import label
+
+from backend.node_registry import register_node
+from backend.data_types import DataField
+from backend.nodes.helpers import mask_to_bool, bool_to_mask
+
+
+@register_node(display_name="Grain Edge")
+class GrainEdge:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field": ("DATA_FIELD",),
+                "mask": ("IMAGE",),
+                "width": ("INT", {"default": 1, "min": 1, "max": 10, "step": 1}),
+            }
+        }
+
+    OUTPUTS = (
+        ('IMAGE', 'edge_mask'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Detect grain boundaries from a binary grain mask. Outputs a mask "
+        "of pixels at grain edges (where grain meets non-grain). Width "
+        "controls the boundary thickness in pixels. "
+    )
+
+    def process(self, field: DataField, mask: np.ndarray, width: int) -> tuple:
+        grain = mask_to_bool(mask)
+
+        # Find boundary: grain pixels with at least one non-grain 4-neighbour
+        padded = np.pad(grain, 1, mode='constant', constant_values=False)
+        interior = (padded[:-2, 1:-1] & padded[2:, 1:-1] &
+                    padded[1:-1, :-2] & padded[1:-1, 2:])
+        boundary = grain & ~interior
+
+        # Expand boundary by width
+        if width > 1:
+            from scipy.ndimage import binary_dilation
+            struct = np.ones((2 * width - 1, 2 * width - 1), dtype=bool)
+            boundary = binary_dilation(boundary, structure=struct) & grain
+
+        return (bool_to_mask(boundary),)