In modern industry, polymer materials are widely used in various fields due to their unique physical and chemical properties. Object detection technology, especially the YOLOv5 algorithm, has become an important tool in materials science due to its advantages in real-time and accuracy. YOLOv5, as the latest version of the You Only Look Once (YOLO) series, significantly improves the speed and accuracy of object detection through its advanced deep learning architecture. The article reviews the application of YOLOv5 in the field of polymer materials, including material defect detection, classification and identification, performance prediction, and material characterization and analysis. The above applications not only improve the quality and efficiency of material production, but also provide new perspectives for material research and development. With the continuous advancement of technology, YOLOv5 has broad application prospects in the field of polymer materials, and is expected to further promote the development of intelligent manufacturing and automation.