  Recent years have witnessed the advancement of deep learning vision
technologies and applications in the medical industry. Intelligent devices for
special medication management are in great need of, which requires more precise
detection algorithms to identify the specifications and locations. In this
work, YOLO (You only look once) based object detectors are tailored for toxic
and narcotic medications detection tasks. Specifically, a more flexible
annotation with rotated degree ranging from $0^\circ$ to $90^\circ$ and a
mask-mapping-based non-maximum suppression method are proposed to achieve a
feasible and efficient medication detector aiming at arbitrarily oriented
bounding boxes. Extensive experiments demonstrate that the rotated YOLO
detectors are more suitable for identifying densely arranged drugs. The best
shot mean average precision of the proposed network reaches 0.811 while the
inference time is less than 300ms.
