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/support/blender.py

@@ -164,6 +164,12 @@ class BlenderTestCase(unittest.TestCase):
 
 
     def setUp(self):
+        timer_callbacks = set()
+        self.fake_bpy.app.timers = SimpleNamespace(
+            is_registered=timer_callbacks.__contains__,
+            register=lambda callback, **options: timer_callbacks.add(callback),
+            unregister=timer_callbacks.remove,
+        )
         preferences = SimpleNamespace(
             storage_root="",
             device="CUDA",