Manually annotated IFCB plankton images from the Skagerrak, Kattegat, and Baltic Proper by SMHI

This repository includes three datasets of manually annotated plankton images by phytoplankton experts at the Swedish Meteorological and Hydrological Institute (SMHI). These images can be used for training classifiers to identify various plankton species. The images were captured using an Imaging FlowCytobot (IFCB, McLane Research Laboratories) from different locations and seasons in the Skagerrak, Kattegat, and Baltic Proper. The specifics of the three datasets are as follows:<br><b>smhi_ifcb_svea_baltic_proper</b>: Images were gathered during monthly monitoring cruises from 2022 to 2024, utilizing an IFCB mounted as part of the underway FerryBox system on the R/V Svea. This collection consists of 18,421 annotated images across 48 different classes.<b>smhi_</b><b>ifcb_svea_skagerrak_kattegat</b>: Images were collected during regular monitoring cruises from 2022 to 2024. This archive comprises of 5,086 annotated images from 83 distinct classes.<b>smhi_</b><b>ifcb_tångesund</b>: In 2016, the IFCB was deployed in situ at depths between 3 and 18 meters, near a mussel farm in Tångesund, Mollösund. This dataset contains 41,928 annotated images from 27 different classes.Each dataset comprises two zip archives: one (annotated_images) containing .png images organized into subfolders for each class, and another (matlab_files) including raw data files (.roi, .hdr, .adc) and .mat-files for developing an image classifier using the MATLAB code available at https://github.com/hsosik/ifcb-analysis.The images in this dataset undergo continuous quality control, and new images are regularly added. Consequently, this dataset will be updated on a regular basis.