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/ui/image_view.py

@@ -8,6 +8,8 @@ what the detector found.
 
 from __future__ import annotations
 
+import zlib
+
 import cv2
 import numpy as np
 from PySide6.QtCore import QPointF, QRectF, Qt
@@ -15,7 +17,7 @@ from PySide6.QtGui import QBrush, QColor, QFont, QImage, QPainter, QPen, QPolygo
 from PySide6.QtWidgets import QWidget
 
 from ..config import OverlayConfig
-from ..core.detection.types import CensorType, Detection
+from ..core.detection.types import Detection
 
 
 class ImageView(QWidget):
@@ -50,9 +52,13 @@ class ImageView(QWidget):
         self.update()
 
     # ------------------------------------------------------------------ paint
-    def _color(self, ctype: CensorType) -> QColor:
-        r, g, b = self._cfg.colors.get(ctype.value, (255, 0, 0))
-        return QColor(r, g, b)
+    def _color(self, key: str) -> QColor:
+        """Colour for a detection category — fixed if configured, else a stable palette pick."""
+        rgb = self._cfg.colors.get(key)
+        if rgb is None:
+            palette = self._cfg.palette
+            rgb = palette[zlib.crc32(key.encode("utf-8")) % len(palette)]
+        return QColor(*rgb)
 
     def paintEvent(self, event) -> None:
         painter = QPainter(self)
@@ -87,7 +93,7 @@ class ImageView(QWidget):
         self, painter: QPainter, d: Detection, ox: float, oy: float,
         scale: float, highlighted: bool, dim: bool,
     ) -> None:
-        color = self._color(d.type)
+        color = self._color(d.display)
         width = self._cfg.line_width * (2 if highlighted else 1)
         pen_color = QColor(color)
         if dim:
@@ -103,7 +109,7 @@ class ImageView(QWidget):
 
         if self._cfg.show_labels and not dim:
             x, y, _w, _h = d.bbox
-            self._draw_label(painter, f"{d.type.value} {d.score:.2f}", ox + x * scale, oy + y * scale, color)
+            self._draw_label(painter, f"{d.display} {d.score:.2f}", ox + x * scale, oy + y * scale, color)
 
     @staticmethod
     def _bbox_points(bbox: tuple[int, int, int, int]) -> list[tuple[int, int]]: