Add new tests and functionality for image processing and geometry handling

- Introduced color_image.py for preparing standalone color images for tests.
- Added hdr_image.py to create HDR textures for testing.
- Implemented test_image_depth_panorama.py to evaluate panorama topology, UVs, and depth discontinuities.
- Created test_shadeless.py to validate the opacity and HDR color endpoints of the Shadeless group.
- Developed moge3_export.py for exporting dynamic MoGe-3 backbone and ONNX graphs.
- Added material.py to inherit material slots onto generated geometry.
- Built image_depth_panorama.py to construct a quad panorama with depth separation and sampling.

tests/support/color_image.py

@@ -0,0 +1,11 @@
+"""Prepare a standalone color image for material and geometry tests."""
+
+from anyimage.common.color_image import prepare_material_color_input, load_material_color_image, cleanup_material_color_input
+
+
+def color_image(source, bounds=None, rgba=None):
+    path = prepare_material_color_input(source, bounds, rgba)
+    try:
+        return load_material_color_image(path)
+    finally:
+        cleanup_material_color_input(path)

tests/support/hdr_image.py

@@ -0,0 +1,15 @@
+import bpy
+import numpy as np
+import pytest
+
+
+@pytest.fixture
+def hdr_texture(texture):
+    image = bpy.data.images.new("HDR source", width=4, height=3, alpha=True, float_buffer=True)
+    image.alpha_mode = "PREMUL"
+    rgba = np.tile([4.0, 2.0, -0.25, 0.5], (3, 4, 1)).astype(np.float32)
+    rgba[0, 0] = [9, 3, -0.5, 0]
+    rgba[2, 3] = [25, 12, 6, 1]
+    image.pixels.foreach_set(np.flipud(rgba).ravel())
+    texture.image = image
+    return texture

tests/support/image_objects.py

@@ -7,6 +7,7 @@ from anyimage.common import object as object_data
 from anyimage.common.selection import SelectionMask
 from anyimage.operators.cutout_tool import geometry as cutout_geometry
 from anyimage.operators.cutout_tool import object as cutout_object
+from tests.support.color_image import color_image as prepared_color_image
 
 
 def _inputs(group):
@@ -43,8 +44,8 @@ def _create_cutout_shape(
         selection_values = np.ones((bottom - top, right - left), dtype=np.float32)
     selection_mask = SelectionMask(selection_values, bounds)
     source_rgba = image_data.image_rgba(source.data)
-    color_image = cutout_object.create_cropped_color_image(
-        source,
+    color_image = prepared_color_image(
+        source.data,
         selection_mask.bounds,
         source_rgba,
     )