refactor nodes into standalone file

backend/nodes/mask_combine.py

@@ -0,0 +1,62 @@
+from __future__ import annotations
+import numpy as np
+from backend.node_registry import register_node
+from backend.data_types import DataField, encode_preview
+from backend.nodes.helpers import _mask_overlay
+
+
+@register_node(display_name="Mask Combine")
+class MaskCombine:
+    _CUSTOM_PREVIEW = True
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "mask_a": ("IMAGE",),
+                "mask_b": ("IMAGE",),
+                "operation": (["and", "or", "xor", "subtract"],),
+            },
+            "optional": {
+                "field": ("DATA_FIELD",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("mask",)
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Combine two binary masks with a boolean operation. "
+        "AND keeps overlap, OR merges, XOR keeps non-overlapping regions, "
+        "subtract removes mask_b from mask_a."
+    )
+
+    _broadcast_fn = None
+    _current_node_id: str = ""
+
+    def process(self, mask_a: np.ndarray, mask_b: np.ndarray, operation: str,
+                field: DataField | None = None) -> tuple:
+        a = mask_a > 127
+        b = mask_b > 127
+
+        if operation == "and":
+            result = a & b
+        elif operation == "or":
+            result = a | b
+        elif operation == "xor":
+            result = a ^ b
+        elif operation == "subtract":
+            result = a & ~b
+        else:
+            raise ValueError(f"Unknown mask operation: {operation}")
+
+        out = result.astype(np.uint8) * 255
+
+        if field is not None and MaskCombine._broadcast_fn is not None:
+            overlay = _mask_overlay(field, out)
+            MaskCombine._broadcast_fn(
+                MaskCombine._current_node_id, encode_preview(overlay),
+            )
+
+        return (out,)