1 files changed, 135 insertions, 0 deletions
diff --git a/Biz/Kidcam/Detector.py b/Biz/Kidcam/Detector.py
new file mode 100755
index 0000000..f2af9ad
--- /dev/null
+++ b/Biz/Kidcam/Detector.py
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+#!/usr/bin/env run.sh
+"""Person detection module for Kidcam using YOLOv8-nano."""
+
+# : out kidcam-detector
+# : dep opencv-python
+# : dep ultralytics
+# : dep numpy
+# : dep pytest
+import cv2 as cv
+import numpy as np
+import sys
+
+
+class PersonDetector:
+    """Detect persons in video frames using YOLOv8-nano."""
+
+    def __init__(
+        self,
+        model_path: str,
+        confidence_threshold: float = 0.5,
+    ) -> None:
+        """Initialize person detector.
+
+        Args:
+            model_path: Path to YOLOv8 model file
+            confidence_threshold: Minimum confidence for detection (0.0-1.0)
+        """
+        try:
+            import ultralytics as ul
+
+            self.model = ul.YOLO(model_path)
+            self.confidence_threshold = confidence_threshold
+            self.last_bbox: tuple[int, int, int, int] | None = None
+        except ImportError as e:
+            msg = "ultralytics library required for YOLOv8"
+            raise ImportError(msg) from e
+
+    def detect_person(self, frame: np.ndarray) -> bool:
+        """Detect if person is present in frame.
+
+        Args:
+            frame: BGR image from OpenCV
+
+        Returns:
+            True if person detected above confidence threshold
+        """
+        results = self.model(frame, verbose=False)
+        self.last_bbox = None
+
+        for result in results:
+            boxes = result.boxes
+            for box in boxes:
+                class_id = int(box.cls[0])
+                confidence = float(box.conf[0])
+
+                if class_id == 0 and confidence >= self.confidence_threshold:
+                    x1, y1, x2, y2 = box.xyxy[0].cpu().numpy()
+                    self.last_bbox = (int(x1), int(y1), int(x2), int(y2))
+                    return True
+
+        return False
+
+    def get_last_detection_bbox(
+        self,
+    ) -> tuple[int, int, int, int] | None:
+        """Get bounding box from last detection.
+
+        Returns:
+            Tuple of (x1, y1, x2, y2) or None if no recent detection
+        """
+        return self.last_bbox
+
+
+def main() -> None:
+    """Test person detection with webcam."""
+    if "test" in sys.argv:
+        test()
+        return
+
+    try:
+        cap = cv.VideoCapture("/dev/video0")
+        if not cap.isOpened():
+            sys.exit(1)
+
+        detector = PersonDetector("yolov8n.pt", confidence_threshold=0.5)
+
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            if detector.detect_person(frame):
+                bbox = detector.get_last_detection_bbox()
+                if bbox:
+                    x1, y1, x2, y2 = bbox
+                    cv.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+
+            cv.imshow("Kidcam - Person Detection", frame)
+
+            if cv.waitKey(1) & 0xFF == ord("q"):
+                break
+
+    except FileNotFoundError:
+        sys.exit(1)
+    except Exception:
+        sys.exit(1)
+    finally:
+        if "cap" in locals():
+            cap.release()
+        cv.destroyAllWindows()
+
+
+def test() -> None:
+    """Basic unit tests for PersonDetector."""
+    test_frame = np.zeros((480, 640, 3), dtype=np.uint8)
+
+    try:
+        detector = PersonDetector("yolov8n.pt", confidence_threshold=0.5)
+        assert detector.confidence_threshold == 0.5
+        assert detector.get_last_detection_bbox() is None
+
+        result = detector.detect_person(test_frame)
+        assert isinstance(result, bool)
+
+        bbox = detector.get_last_detection_bbox()
+        assert bbox is None or (isinstance(bbox, tuple) and len(bbox) == 4)
+
+    except ImportError:
+        pass
+    except Exception:
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()