Skip to main content
Fig. 1 | Plant Methods

Fig. 1

From: Accurate machine learning-based germination detection, prediction and quality assessment of three grain crops

Fig. 1

Illustration of image collection, annotation and dataset generation module. a Setup for capturing images of the germination process of seeds within petri dishes. Subsequently, images have been cropped to only contain one petri dish per image. b Example of annotated images, where seeds have been marked with a bounding box and a class label (non-germinated in orange, germinated in blue). c Longitudinal images of a custom seed for 48 h. Orange frames around the images indicate that the seed is not germinated, gray indicates a difficult to label transition phase and blue indicates that the seed is clearly germinated. d The dataset was randomly split into a training, validation and test set, stratified by petri dishes. This ensures that seeds of the same petri dish are either in the training, validation or test set. In addition, it also ensures that a petri dish at different time points only appears in one of the sets

Back to article page
\