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_moge_onnx.py

@@ -12,8 +12,8 @@ PROJECT_ROOT = Path(__file__).resolve().parents[1]
 
 def load_module():
     specification = importlib.util.spec_from_file_location(
-        "snapform_moge_onnx",
-        PROJECT_ROOT / "src" / "snapform" / "ai_service" / "moge_onnx.py",
+        "snapform_onnx_moge2",
+        PROJECT_ROOT / "src" / "snapform" / "server" / "onnx_moge2.py",
     )
     module = importlib.util.module_from_spec(specification)
     specification.loader.exec_module(module)