Tea Picking Action Recognition Dataset

The current agricultural sector faces challenges such as low efficiency and high labor costs in the tea picking process. Traditional picking methods rely on labor, making automation and precision difficult to achieve. Existing solutions often lack precise recognition of picking actions, failing to meet the development needs of smart agriculture. This dataset aims to solve the problem of accurately recognizing tea picking actions through computer vision technology, promoting the development of agricultural automation. The dataset contains 5000 high-quality images of tea picking, captured using professional equipment in real environments to ensure the authenticity and diversity of the data. In terms of quality control, a combination of multi-round annotation and expert review ensures data consistency and accuracy. The data storage format is JPEG, using a standard file organization method for convenient subsequent data processing and analysis.