Pre-release cleanup for PySide6 GUI

.github/workflows/testing-ci.yml

@@ -4,6 +4,10 @@ on:
   pull_request:
     types: [opened, synchronize, reopened]
 
+concurrency:
+  group: ci-${{ github.workflow }}-pr-${{ github.event.pull_request.number }}
+  cancel-in-progress: true
+
 jobs:
   unit:
     name: Unit + Smoke (no hardware) • ${{ matrix.os }} • py${{ matrix.python }}
@@ -38,6 +42,17 @@ jobs:
           python -m pip install -U pip wheel
           python -m pip install -U tox tox-gh-actions
 
+      - name: Install Qt/OpenGL runtime deps (Ubuntu)
+        if: startsWith(matrix.os, 'ubuntu')
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y \
+            libegl1 \
+            libgl1 \
+            libopengl0 \
+            libxkbcommon-x11-0 \
+            libxcb-cursor0
+
       - name: Run tests (exclude hardware) with coverage via tox
         run: |
           tox -q
@@ -54,6 +69,7 @@ jobs:
           echo '```' >> "$GITHUB_STEP_SUMMARY"
 
       - name: Upload coverage to Codecov
+        if: github.event_name == 'pull_request' && (github.base_ref == 'main' || github.base_ref == 'master')
         uses: codecov/codecov-action@v5
         with:
           files: ./coverage.xml

dlclivegui/__init__.py

@@ -7,21 +7,13 @@
     MultiCameraSettings,
     RecordingSettings,
 )
-from .gui.camera_config.camera_config_dialog import CameraConfigDialog
-from .gui.main_window import DLCLiveMainWindow
 from .main import main
-from .services.multi_camera_controller import MultiCameraController, MultiFrameData
 
 __all__ = [
     "ApplicationSettings",
     "CameraSettings",
     "DLCProcessorSettings",
     "MultiCameraSettings",
     "RecordingSettings",
-    "DLCLiveMainWindow",
-    "MultiCameraController",
-    "MultiFrameData",
-    "CameraConfigDialog",
     "main",
 ]
-__version__ = "2.0.0rc0"  # PLACEHOLDER

dlclivegui/cameras/backends/opencv_backend.py

@@ -25,7 +25,6 @@
 )
 
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.DEBUG)  # FIXME @C-Achard remove before release
 
 if TYPE_CHECKING:
     from dlclivegui.config import CameraSettings
@@ -169,7 +168,7 @@ def open(self) -> None:
                     ns["device_pid"] = int(chosen.pid)
                 if chosen.name:
                     ns["device_name"] = chosen.name
-                logger.info("Persisted OpenCV device_id=%s", chosen.stable_id)
+                logger.debug("Persisted OpenCV device_id=%s", chosen.stable_id)
 
         self._capture, spec = open_with_fallbacks(index, backend_flag)
 
@@ -399,7 +398,7 @@ def _configure_capture(self) -> None:
             self._actual_fps = float(self._capture.get(cv2.CAP_PROP_FPS) or 0.0)
 
             # For clarity in logs
-            logger.info("Resolution requested=Auto, actual=%sx%s", self._actual_width, self._actual_height)
+            logger.debug("Resolution requested=Auto, actual=%sx%s", self._actual_width, self._actual_height)
 
         elif not self._fast_start:
             # Verified, robust path (tries candidates + verifies)
@@ -432,7 +431,7 @@ def _configure_capture(self) -> None:
         if (self._actual_width or 0) > 0 and (self._actual_height or 0) > 0:
             actual_res = (int(self._actual_width), int(self._actual_height))
 
-        logger.info(
+        logger.debug(
             "Resolution requested=%s, actual=%s",
             f"{req_w}x{req_h}" if (req_w > 0 and req_h > 0) else "Auto",
             f"{actual_res[0]}x{actual_res[1]}" if actual_res else "unknown",

dlclivegui/config.py

@@ -2,6 +2,7 @@
 from __future__ import annotations
 
 import json
+from enum import Enum
 from pathlib import Path
 from typing import Any, Literal
 
@@ -10,6 +11,7 @@
 Rotation = Literal[0, 90, 180, 270]
 TileLayout = Literal["auto", "2x2", "1x4", "4x1"]
 Precision = Literal["FP32", "FP16"]
+ModelType = Literal["pytorch", "tensorflow"]
 
 
 class CameraSettings(BaseModel):
@@ -239,14 +241,46 @@ class DLCProcessorSettings(BaseModel):
     resize: float = Field(default=1.0, gt=0)
     precision: Precision = "FP32"
     additional_options: dict[str, Any] = Field(default_factory=dict)
-    model_type: Literal["pytorch"] = "pytorch"
+    model_type: ModelType = "pytorch"
     single_animal: bool = True
 
     @field_validator("dynamic", mode="before")
     @classmethod
     def _coerce_dynamic(cls, v):
         return DynamicCropModel.from_tupleish(v)
 
+    @field_validator("model_type", mode="before")
+    @classmethod
+    def _coerce_model_type(cls, v):
+        """
+        Accept:
+          - "pytorch"/"tensorflow"/etc as strings
+          - Enum instances (e.g. Engine.PYTORCH) and store their .value
+        Always return a lowercase string.
+        """
+        if v is None or v == "":
+            return "pytorch"
+
+        # If caller passed Engine enum or any Enum, use its value
+        if isinstance(v, Enum):
+            v = v.value
+
+        # If caller passed something with a `.value` attribute (defensive)
+        if not isinstance(v, str) and hasattr(v, "value"):
+            v = v.value
+
+        if not isinstance(v, str):
+            raise TypeError(f"model_type must be a string or Enum, got {type(v)!r}")
+
+        v = v.strip().lower()
+
+        # Optional: enforce allowed values
+        allowed = {"pytorch", "tensorflow"}
+        if v not in allowed:
+            raise ValueError(f"Unknown model type: {v!r}. Allowed: {sorted(allowed)}")
+
+        return v
+
 
 class BoundingBoxSettings(BaseModel):
     enabled: bool = False