Add ONNX model inference implementations for MoGe-2, BEN2, and DA3

- Introduced `onnx_moge2.py` for MoGe-2 ONNX inference with NumPy post-processing.
- Added `onnx_ben2.py` for BEN2 ONNX inference with Pillow and NumPy preprocessing.
- Created `onnx_da3.py` for Depth Anything 3 inference with ONNX Runtime and NumPy.
- Implemented shared ONNX Runtime session helpers in `onnx_runtime.py`.
- Developed unit tests for server functionalities in `test_server.py`, including model caching and job management.
- Enhanced job server to handle frame extraction without requiring models.

tests/test_models.py

@@ -21,7 +21,7 @@ class ModelTest(unittest.TestCase):
     def setUpClass(cls):
         cls.models = load_module(
             "snapform_models",
-            "src/snapform/models.py",
+            "src/snapform/server/model_catalog.py",
         )
 
     def test_base_model_is_default_friendly_apache_model(self):