Industrial Packaging Sealing Action Recognition Dataset

The current industrial packaging field faces challenges due to the lack of standardization in action detection, with many companies lacking effective monitoring methods to ensure the compliance of the packaging process. Existing solutions often rely on manual observation, which can lead to errors and omissions. This dataset aims to provide companies with a high-quality video dataset to support the development of automated monitoring and action recognition technologies. Data collection is conducted using high-definition camera equipment and recorded in typical packaging production environments to ensure high video quality. The data annotation team underwent multiple rounds of annotation and consistency checks to ensure the accuracy of labels. Data is stored in MP4 format, organized sequentially by video ID for easy retrieval and analysis. The core advantage of this dataset lies in its high annotation accuracy and consistency, with an annotation error rate below 2%. It employs innovative deep learning algorithms for action recognition, resulting in a 20% improvement in recognition accuracy. This dataset can significantly enhance the level of automation on packaging lines, reducing labor costs and quality risks.