SMHI IFCB Plankton Image Reference Library

This repository includes four datasets of manually annotated plankton images by phytoplankton experts at the Swedish Meteorological and Hydrological Institute (SMHI). These images can be used for training automatic image 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 27,118 annotated images across 61 different classes.<b>smhi_</b><b>ifcb_svea_skagerrak_kattegat</b>: Images were also collected during the 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 (Skagerrak). This dataset contains 43,828 annotated images from 39 different classes.<b>smhi_</b><b>ifcb_iRfcb</b>: This subset of the smhi_ifcb_svea_skagerrak_kattegat dataset can be used for user and unit tests for the iRfcb R package.Datasets 1-3 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 a random forest image classifier using the MATLAB code from the ifcb-analysis repository. Dataset 4 only comprise of a MATLAB data package.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. If you find any mislabeled images, please contact the authors.<b>Version history</b>Version 4 (2024-11-04): 76,032 annotated images. Corrected class names to better match WoRMS, and continued quality control of images in the Tångesund dataset.Version 3 (2024-08-05): 72,086 annotated images. Added iRfcb dataset for user and unit testing.Version 2 (2024-06-03): 71,525 annotated images. Updated class names and corrected manual files in the Tångesund dataset. Continued quality control of images in the Tångesund dataset.Version 1 (2024-05-31): 65,435 annotated images<br>

本仓库包含瑞典气象水文研究所（SMHI）的浮游植物专家人工标注的四组浮游生物图像数据集。这些图像可用于训练自动图像分类器，以识别不同种类的浮游生物。图像由成像流式细胞仪（IFCB，McLane Research Laboratories）拍摄，采集地点涵盖斯卡格拉克海峡、卡特加特海峡及波罗的海主海的不同区域，时间跨度覆盖多个季节。三组数据集的具体信息如下：<br><b>smhi_ifcb_svea_baltic_proper</b>：图像采集于2022年至2024年的月度监测巡航期间，使用安装在R/V Svea号调查船实时FerryBox系统上的IFCB设备。该数据集包含61个类别共27,118张标注图像。<b>smhi_ifcb_svea_skagerrak_kattegat</b>：图像同样采集于2022年至2024年的常规监测巡航期间。该数据集包含83个类别共5,086张标注图像。<b>smhi_ifcb_tångesund</b>：2016年，IFCB设备部署于斯卡格拉克海峡内Mollösund地区Tångesund的一个贻贝养殖场附近，深度介于3至18米之间。该数据集包含39个类别共43,828张标注图像。<b>smhi_ifcb_iRfcb</b>：该数据集是smhi_ifcb_svea_skagerrak_kattegat数据集的子集，可用于iRfcb R包的用户测试和单元测试。数据集1-3包含两个压缩包：一个（annotated_images）包含按类别分文件夹组织的.png图像；另一个（matlab_files）包含原始数据文件（.roi、.hdr、.adc）及.mat文件，可用于利用ifcb-analysis仓库中的MATLAB代码开发随机森林图像分类器。数据集4仅包含一个MATLAB数据包。本数据集的图像持续接受质量控制，且新图像会定期添加。因此，该数据集将定期更新。若发现任何标注错误的图像，请联系作者。<b>版本历史</b>版本4（2024-11-04）：76,032张标注图像。修正类别名称以更匹配WoRMS，并持续对Tångesund数据集的图像进行质量控制。版本3（2024-08-05）：72,086张标注图像。新增iRfcb数据集用于用户测试和单元测试。版本2（2024-06-03）：71,525张标注图像。更新类别名称并修正Tångesund数据集的手动文件，同时持续对该数据集的图像进行质量控制。版本1（2024-05-31）：65,435张标注图像<br>