remaining med value features

backend/nodes/template_match.py

@@ -0,0 +1,52 @@
+from __future__ import annotations
+
+import numpy as np
+
+from backend.data_types import DataField
+from backend.node_registry import register_node
+
+
+@register_node(display_name="Template Match")
+class TemplateMatch:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("DATA_FIELD",),
+                "template": ("DATA_FIELD",),
+                "threshold": (
+                    "FLOAT",
+                    {"default": 0.8, "min": 0.0, "max": 1.0, "step": 0.05},
+                ),
+            }
+        }
+
+    OUTPUTS = (
+        ('DATA_FIELD', 'score'),
+        ('IMAGE', 'detections'),
+    )
+    FUNCTION = "process"
+
+    DESCRIPTION = (
+        "Find a template pattern within a larger data field using normalised cross-correlation. "
+        "The score output shows match quality (1 = perfect match). Detections mask marks positions "
+        "above the threshold. Equivalent to Gwyddion maskcor.c."
+    )
+
+    def process(
+        self,
+        image: DataField,
+        template: DataField,
+        threshold: float,
+    ) -> tuple:
+        from skimage.feature import match_template
+
+        score = match_template(image.data, template.data, pad_input=True)
+
+        # Clip to [0, 1] for display (match_template returns values in [-1, 1])
+        score_clipped = np.clip(score, 0.0, 1.0)
+
+        detections = (score_clipped >= float(threshold)).astype(np.uint8) * 255
+
+        score_field = image.replace(data=score_clipped)
+        return (score_field, detections)