Data from: Investigating human repeatability of a computer vision based task to identify meristems on a potato plant (Solanum tuberosum)

Labelled training data in artificial intelligence (AI) is used to teach
so-called 'supervised learning models'. However, such data may
contain error or bias, which can impact model prediction accuracy. Thus,
obtaining accurate training data is of high importance. In applications of
AI, such as in classification and detection problems, raw training data is
not always made available in published research. Likewise, the process of
obtaining labelled data is not always documented well enough to enable
reproducibility. This training data set captures a repeatability exercise
in AI training data collection for a task that is difficult for humans to
perform, delineating a bounding box in a two-dimensional image of a
growing apical meristem in potato plants.