Enhance HVideoTool with background processing and device detection: implemented a background job system for detection and restoration tasks, updated the UI to display CUDA/CPU status, and improved device diagnostics. Documentation in README and CLAUDE.md reflects these changes.

hvideotool/core/detection/yolo.py

@@ -54,15 +54,20 @@ class YoloDetector(Detector):
                 "(и PyTorch с CUDA отдельно — см. README)."
             ) from exc
 
-        # Resolve the device: explicit override, else CUDA when available.
+        # Resolve the device: CUDA only when actually available, else CPU. A CPU-only
+        # torch build raises "Torch not compiled with CUDA enabled" if asked for cuda,
+        # so we never request it without a working GPU (even on an explicit override).
+        try:
+            import torch
+
+            cuda_ok = torch.cuda.is_available()
+        except Exception:  # noqa: BLE001
+            cuda_ok = False
         device = self.cfg.yolo_device
         if device is None:
-            try:
-                import torch
-
-                device = "cuda" if torch.cuda.is_available() else "cpu"
-            except Exception:  # noqa: BLE001
-                device = "cpu"
+            device = "cuda" if cuda_ok else "cpu"
+        elif "cuda" in str(device) and not cuda_ok:
+            device = "cpu"
         self._device = device
         self._model = YOLO(model_path)