Tomato Peduncle Keypoint Dataset

In the current agricultural industry, the demand for precise monitoring of plant growth is increasing with the development of smart agriculture. However, existing monitoring techniques often rely on manual recognition, which is inefficient and prone to errors. To address this challenge, the Tomato Peduncle Keypoint Dataset aims to provide high-quality data support for target detection and key point recognition, aiding the development and application of automated monitoring systems. The dataset contains 5000 annotated images of tomato peduncles, all captured from real agricultural environments using high-definition cameras, ensuring data quality. Data quality control measures include multiple rounds of annotation and expert review to ensure the consistency and accuracy of the annotation results. The data is stored in JPG format, organized in a folder structure for ease of subsequent processing and use.