Add comprehensive tests for edge depth extension, empty image edits, and material view adaptation

- Introduced `test_edge_depth.py` to validate the functionality of edge depth extension, ensuring core alpha preservation, proper depth handling, and edge padding behavior.
- Created `test_empty_image_edits.py` to verify the behavior of image edits in Blender, focusing on shared edits, preservation of image properties, and handling of failed operations.
- Developed `test_material_view_adaptation.py` to test material adaptation preferences, ensuring color space and alpha settings are correctly applied and preserved across various scenarios.

src/anyimage/server/geometry/edge_depth.py

@@ -0,0 +1,78 @@
+"""Extend reliable Cutout depth along each visible component's silhouette."""
+
+from dataclasses import replace
+
+
+def extend_edge_depth(frame, alpha, alpha_threshold=0.9):
+    """Return edge-corrected geometry while preserving reliable camera points."""
+    import numpy as np
+    from scipy import ndimage
+
+    from ..models.onnx_moge2 import depth_to_points
+
+    depth = frame.depth
+    alpha = np.asarray(alpha, dtype=np.float32)
+    if alpha.shape != depth.shape:
+        raise ValueError("Edge Alpha must match the depth dimensions")
+    if np.all(alpha == 1.0):
+        return frame
+
+    visible = (alpha > 0.0) & (alpha >= alpha_threshold)
+    candidates = (
+        visible
+        & (alpha >= 0.95)
+        & (frame.validity > 0.0)
+        & np.isfinite(depth)
+        & (depth > 0.0)
+    )
+    if not candidates.any():
+        return frame
+    interior_distance = ndimage.distance_transform_edt(
+        np.pad(candidates, 3, mode="edge")
+    )[3:-3, 3:-3]
+    core = candidates & (interior_distance > 2.0)
+    del interior_distance
+    labels, _ = ndimage.label(visible, structure=np.ones((3, 3), dtype=bool))
+    corrected = depth.copy()
+    background_distance = np.full(depth.shape, np.inf, dtype=np.float32)
+
+    for component_id, bounds in enumerate(ndimage.find_objects(labels), start=1):
+        region = tuple(
+            slice(max(0, bound.start - 7), min(size, bound.stop + 7))
+            for bound, size in zip(bounds, depth.shape)
+        )
+        component = labels[region] == component_id
+        donors = core[region] & component
+        if not donors.any():
+            donors = candidates[region] & component
+        if not donors.any():
+            continue
+
+        indices = ndimage.distance_transform_edt(
+            ~donors, return_distances=False, return_indices=True
+        )
+        extended = depth[region][tuple(indices)]
+        smoothed = ndimage.gaussian_filter(extended, sigma=0.8, radius=3)
+        distance = ndimage.distance_transform_edt(~component)
+        background = (
+            ~visible[region]
+            & (distance <= 4.0)
+            & (distance < background_distance[region])
+        )
+        target = (component & ~donors) | background
+        corrected[region][target] = smoothed[target]
+        background_distance[region][background] = distance[background]
+
+    changed = corrected != depth
+    if not changed.any():
+        return frame
+    points = frame.points
+    if points is not None:
+        height, width = depth.shape
+        intrinsics = frame.intrinsics.copy()
+        intrinsics[0] /= width
+        intrinsics[1] /= height
+        projected = depth_to_points(corrected, intrinsics)
+        points = points.copy()
+        points[changed] = projected[changed]
+    return replace(frame, depth=corrected, points=points)