Add image selection refinement functionality with BEN2 integration

- Implemented viewport.py for handling 3D view projections, gestures, and overlay drawing.
- Created refine_image_selection.py to manage the refinement of gesture masks and output image bounds.
- Added selection module with refine_selection.py to process and crop images based on alpha channel visibility.
- Introduced __init__.py for selection module to expose refine_selection function.

src/anyimage/server/models/geometry.py

@@ -4,8 +4,29 @@ from dataclasses import dataclass
 @dataclass
 class GeometryFrame:
     depth: object
-    points: object | None
+    validity: object
     intrinsics: object
-    valid_mask: object
-    confidence: object | None = None
-    model_mask: object | None = None
+    normal: object | None = None
+    points: object | None = None
+
+    def __post_init__(self):
+        import numpy as np
+
+        depth = np.asarray(self.depth)
+        validity = np.asarray(self.validity)
+        intrinsics = np.asarray(self.intrinsics)
+        if depth.dtype != np.float32 or depth.ndim != 2:
+            raise ValueError("Geometry depth must be a 2D float32 field")
+        if validity.dtype != np.float32 or validity.shape != depth.shape:
+            raise ValueError("Geometry validity must match the depth as float32")
+        if intrinsics.dtype != np.float32 or intrinsics.shape != (3, 3):
+            raise ValueError("Geometry intrinsics must be a 3x3 float32 matrix")
+        for name in ("normal", "points"):
+            value = getattr(self, name)
+            if value is None:
+                continue
+            field = np.asarray(value)
+            if field.dtype != np.float32 or field.shape != (*depth.shape, 3):
+                raise ValueError(
+                    f"Geometry {name} must match the depth as three-channel float32"
+                )