Implement BiRefNet and HAT Sharper models with background removal capabilities

- Added validation documentation for AI model tiers.
- Introduced `background.py` for background removal logic, including inference functions for alpha and foreground extraction.
- Created `onnx_birefnet.py` to handle BiRefNet model sessions and alpha inference.
- Developed tests for background models, ensuring proper dispatch and session reuse.
- Added tests for BiRefNet ONNX model to validate alpha output and error handling for invalid values.
- Implemented model export scripts for BiRefNet and HAT Sharper, ensuring proper weight compression and licensing.
- Created `deform_sampling.py` for deformable convolution operations used in BiRefNet.
- Added utility functions for compressing ONNX weights without altering graph arithmetic.
- Introduced a reference plane node for depth field adjustments in geometry processing.

tests/anyimage/operators/test_cutout_operators.py

@@ -249,7 +249,7 @@ class CutoutOperatorsTest(BlenderTestCase):
         operator.color_path = __file__
         operator.source_object_name = "Source"
         operator.shape = "DEPTH_SOLID"
-        operator.model = self.anyimage.properties.DEFAULT_MOGE2_MODEL_KEY
+        operator.model = self.anyimage.preferences.DEFAULT_GEOMETRY_MODEL_KEY
         operator.resolution_level = 5
         operator.max_ai_input_size = 2048
         operator.generate_normal = True
@@ -288,10 +288,8 @@ class CutoutOperatorsTest(BlenderTestCase):
             geometry_model="MOGE2_VITB_NORMAL",
             geometry_resolution_level=7,
         )
-        with patch.object(
-            self.cutout_main,
-            "addon_preferences",
-            return_value=preferences,
+        with patch.object(self.cutout_main, "addon_preferences", return_value=preferences), patch.object(
+            self.anyimage.preferences, "addon_preferences", return_value=preferences
         ):
             settings = self.cutout_main.cutout_geometry_settings(None)