Implement multi-model detection in HVideoTool: updated the detection system to support multiple YOLO models simultaneously, enhancing detection capabilities. Reflected changes in the UI with a new model selection menu and updated documentation in README and CLAUDE.md to guide users on model management and configuration.

hvideotool/core/detection/multi.py

@@ -0,0 +1,31 @@
+"""Run several detectors over a frame and merge their detections.
+
+Used for the multi-model (ADetailer-style) setup: each ticked ``models/yolo/<cat>/*.pt``
+becomes a :class:`~.yolo.YoloDetector` (tagged with its category), and this detector
+concatenates all their results. Detections keep their own ``label`` (category), so the
+overlay/table show every model's output together — no cross-model dedup (different
+categories are meant to coexist).
+"""
+
+from __future__ import annotations
+
+from ..video.frame import Frame
+from .base import Detector
+from .types import Detection
+
+
+class MultiYoloDetector(Detector):
+    def __init__(self, detectors: list[Detector]) -> None:
+        if not detectors:
+            raise ValueError("MultiYoloDetector requires at least one detector")
+        self._detectors = detectors
+
+    @property
+    def name(self) -> str:
+        return "Multi(" + " + ".join(d.name for d in self._detectors) + ")"
+
+    def detect(self, frame: Frame) -> list[Detection]:
+        out: list[Detection] = []
+        for d in self._detectors:
+            out.extend(d.detect(frame))
+        return out