Training dataset The images were collected in the framework of the Belgian Lifewatch Research Infrastructure. During multidisciplinary campaigns, a number of fixed stations in the Belgian Part of the North Sea (BPNS) are visited on a monthly (onshore stations) or seasonal (offshore stations) basis. Samples are taken using a 55µm mesh size Apstein net and fixed in Lugol's iodine solution. In the lab, the samples are processed using a VS-4 FlowCAM model at 4X magnification targeting a particle size range of 55-300µm. The identification of the image data is done with the use of a CNN and followed by a manual validation step. Since May 2017, this dataset has provided micro- and phytoplankton observations, mainly covering diatoms, dinoflagellates and cilliates, for the Belgian Part of the North Sea (BPNS). This dataset comprises a trainings datasplit of 337,613 images distributed across 95 classes, with each class containing a minimum of 100 and a maximum of 10,000 images. The goal of this dataset is to be able ... : The phytoplankton annotated dataset is a product of the "Flowcam plankton identification Use Case" within the "iMagine project" with founding from the European Union's Horizon Europe research and innovation programme. The authors express their gratitude to the project managers and all partners involved for fostering the creation of open-access image repositories for AI-based image analysis services. Special thanks are extended to the researchers that contributed to the phytoplankton dataset, which forms the foundation for phytoplankton annotated labels. ...