The invention discloses a deep neural network and clustering algorithm combined large infusion liquid medicine foreign matter target detection method. The method comprises the following steps: firstly, carrying out simple preprocessing on an image, and then detecting a foreign matter target in large infusion liquid medicine by combining a deep neural network for detecting and positioning a small target and a clustering algorithm and adopting a processing method of combining a single-frame image and a multi-frame image. Firstly,the FasterR-CNN deep neural network is used for detecting a single-frame image, and then hierarchical clustering and a K-means++ clustering algorithm are used to cluster the position coordinate points of all suspected foreign matter targets in the eight frames of detected images; therefore, the motion trail of each foreign matter target and the motion trail of the noise point can be recorded, the motion trail of each foreign matter target and the motion trail ofthe noise point can be conveniently distinguished, and the detection accuracy is greatly improved. The visual detection method is accurate and stable and meets the online detection requirement of a general production line.