adding more nodes

backend/nodes/zero_crossing.py

@@ -0,0 +1,60 @@
+"""Zero crossing detection — edge detection via LoG zero crossings."""
+
+from __future__ import annotations
+
+import numpy as np
+from scipy.ndimage import gaussian_laplace
+
+from backend.node_registry import register_node
+from backend.data_types import DataField
+
+
+@register_node(display_name="Zero Crossing")
+class ZeroCrossing:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "field": ("DATA_FIELD",),
+                "sigma": ("FLOAT", {"default": 2.0, "min": 0.5, "max": 20.0, "step": 0.1}),
+                "threshold": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01}),
+            }
+        }
+
+    OUTPUTS = (
+        ('DATA_FIELD', 'edges'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Detect edges by finding zero crossings of the Laplacian of Gaussian "
+        "(LoG). Sigma controls the Gaussian smoothing scale. Threshold filters "
+        "out weak edges (relative to the LoG range). "
+    )
+
+    def process(self, field: DataField, sigma: float, threshold: float) -> tuple:
+        data = np.asarray(field.data, dtype=np.float64)
+
+        # Compute LoG
+        log = gaussian_laplace(data, sigma=sigma)
+
+        # Find zero crossings: adjacent pixels with opposite signs
+        edges = np.zeros_like(data)
+
+        # Horizontal crossings
+        sign_diff_x = log[:, :-1] * log[:, 1:]
+        cross_x = sign_diff_x < 0
+        strength_x = np.abs(log[:, :-1] - log[:, 1:])
+
+        # Vertical crossings
+        sign_diff_y = log[:-1, :] * log[1:, :]
+        cross_y = sign_diff_y < 0
+        strength_y = np.abs(log[:-1, :] - log[1:, :])
+
+        # Apply threshold
+        max_strength = max(strength_x.max(), strength_y.max(), 1e-30)
+        edges[:, :-1] += cross_x & (strength_x > threshold * max_strength)
+        edges[:-1, :] += cross_y & (strength_y > threshold * max_strength)
+
+        result = (edges > 0).astype(np.float64)
+        return (field.replace(data=result, si_unit_z=""),)