Add temporary Engine enum and use in dlc_processor

Introduce a temporary dlclivegui.temp package with an Engine enum to detect model engines. engine.py provides Engine.TENSORFLOW and Engine.PYTORCH plus helpers from_model_type and from_model_path (checks extensions/pose_cfg.yaml and existence). Add __init__.py and update dlclivegui/services/dlc_processor.py to import Engine from dlclivegui.temp (with a TODO to switch to the upstream dlclive package when available).

Author: C-Achard

dlclivegui/services/dlc_processor.py

@@ -28,8 +28,8 @@
 try:  # pragma: no cover - optional dependency
     from dlclive import (
         DLCLive,  # type: ignore
-        Engine,  # type: ignore
     )
+    from dlclivegui.temp import Engine  # type: ignore # TODO use main package one when released
 except Exception as e:  # pragma: no cover - handled gracefully
     logger.error(f"dlclive package could not be imported: {e}")
     DLCLive = None  # type: ignore[assignment]

dlclivegui/temp/__init__.py

@@ -0,0 +1,33 @@
+from enum import Enum
+from pathlib import Path
+
+class Engine(Enum):
+    TENSORFLOW = "tensorflow"
+    PYTORCH = "pytorch"
+
+    @classmethod
+    def from_model_type(cls, model_type: str) -> "Engine":
+        if model_type.lower() == "pytorch":
+            return cls.PYTORCH
+        elif model_type.lower() in ("tensorflow", "base", "tensorrt", "lite"):
+            return cls.TENSORFLOW
+        else:
+            raise ValueError(f"Unknown model type: {model_type}")
+
+    @classmethod
+    def from_model_path(cls, model_path: str | Path) -> "Engine":
+        path = Path(model_path)
+
+        if not path.exists():
+            raise FileNotFoundError(f"Model path does not exist: {model_path}")
+
+        if path.is_dir():
+            has_cfg = (path / "pose_cfg.yaml").is_file()
+            has_pb = any(p.suffix == ".pb" for p in path.glob("*.pb"))
+            if has_cfg and has_pb:
+                return cls.TENSORFLOW
+        elif path.is_file():
+            if path.suffix == ".pt":
+                return cls.PYTORCH
+
+        raise ValueError(f"Could not determine engine from model path: {model_path}")