feat(node_assets): add image plane geometry nodes and validation scripts

- Implemented `image_plane.py` to build the Image Plane Geometry Nodes group with customizable parameters for geometry, subdivide, and thickness.
- Created `image_plane_validation.py` to validate the functionality of the image plane, ensuring correct geometry generation and material assignment.
- Developed `material_layers.py` to construct shader node groups for image materials, including depth and normal handling.
- Authored `plane_layouts.py` to define node arrangements for image geometry assets.
- Introduced `shadeless.py` to create a shadeless shader node group that displays color without scene lighting while preserving shadows and reflections.

tests/test_model_geometry.py

@@ -0,0 +1,73 @@
+
+
+import sys
+from pathlib import Path
+from unittest.mock import patch
+import numpy as np
+
+SOURCE_ROOT = Path(__file__).parents[1] / "src"
+
+sys.path.insert(0, str(SOURCE_ROOT))
+
+
+from anyimage.server.models import moge2 as moge2_model
+from anyimage.server.models.geometry import GeometryFrame
+
+
+def test_geometry_frame_requires_matching_float32_fields():
+    with np.testing.assert_raises_regex(ValueError, "validity"):
+        GeometryFrame(
+            depth=np.ones((2, 2), dtype=np.float32),
+            validity=np.ones((1, 2), dtype=np.float32),
+            intrinsics=np.eye(3, dtype=np.float32),
+        )
+    with np.testing.assert_raises_regex(ValueError, "normal"):
+        GeometryFrame(
+            depth=np.ones((2, 2), dtype=np.float32),
+            validity=np.ones((2, 2), dtype=np.float32),
+            intrinsics=np.eye(3, dtype=np.float32),
+            normal=np.ones((2, 2, 2), dtype=np.float32),
+        )
+
+
+def test_moge_infer_returns_geometry_frames_with_model_validity():
+    mask = np.asarray(((True, False), (True, True)))
+    prediction = {
+        "depth": np.ones((2, 2), dtype=np.float32),
+        "normal": np.zeros((2, 2, 3), dtype=np.float32),
+        "mask": mask,
+        "intrinsics": np.asarray(
+            ((1.0, 0.0, 0.5), (0.0, 1.0, 0.5), (0.0, 0.0, 1.0)),
+            dtype=np.float32,
+        ),
+        "points": np.ones((2, 2, 3), dtype=np.float32),
+    }
+
+    with patch.object(moge2_model, "infer_one", return_value=prediction):
+        frames = moge2_model.infer(None, {}, ["image"], include_points=True)
+
+    assert len(frames) == 1
+    frame = frames[0]
+    assert np.array_equal(frame.validity, mask.astype(np.float32))
+    assert np.array_equal(frame.normal, prediction["normal"])
+    assert np.array_equal(frame.points, prediction["points"])
+    assert np.array_equal(
+        frame.intrinsics,
+        np.asarray(((2.0, 0.0, 1.0), (0.0, 2.0, 1.0), (0.0, 0.0, 1.0))),
+    )
+
+
+def test_moge_z_depth_frame_does_not_require_points():
+    prediction = {
+        "depth": np.ones((2, 2), dtype=np.float32),
+        "normal": np.zeros((2, 2, 3), dtype=np.float32),
+        "mask": np.ones((2, 2), dtype=bool),
+        "intrinsics": np.eye(3, dtype=np.float32),
+        "points": np.ones((2, 2, 3), dtype=np.float32),
+    }
+
+    with patch.object(moge2_model, "infer_one", return_value=prediction):
+        frame = moge2_model.infer(None, {}, ["image"], include_points=False)[0]
+
+    assert frame.points is None
+    assert frame.validity.all()