Plankton was sampled with a Continuous Underway Fish Egg Sampler (CUFES, 315µm mesh size) at 4 m below the surface, and a WP2 net (200µm mesh size) from 100m to the surface, or 5 m above the sea floor to the surface when the depth was < 100 m, in the Bay of Biscay. The full images were processed with the ZooCAM software and the embedded Matrox Imaging Library (Colas et a., 2018) which generated regions of interest (ROIs) around each individual object and a set of features measured on the object. The same objects were re-processed to compute features with the scikit-image library http://scikit-image.org. The 1, 286, 590 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 93 taxa, using the web application EcoTaxa http://ecotaxa.obs-vlfr.fr. For the purpose of training machine learning classifiers, the images in each class were split into training, validation, and test sets, with proportions 70%, 15% and 15%.

The archive contains :

taxa.csv.gz
Table of the classification of each object in the dataset, with columns :

• objid : unique object identifier in EcoTaxa (integer number).
• taxon_level1 : taxonomic name corresponding to the level 1 classification
• lineage_level1 : taxonomic lineage corresponding to the level 1 classification
• taxon_level2 : name of the taxon corresponding to the level 2 classification 
• plankton : if the object is a plankton or not (boolean)
• set : class of the image corresponding to the taxon (train : training, val : validation, or test)
• img_path : local path of the image corresponding to the taxon (of level 1), named according to the object id

features_native.csv.gz
Table of morphological features computed by ZooCAM. All features are computed on the object only, not the background. All area/length measures are in pixels. All grey levels are in encoded in 8 bits (0=black, 255=white). With columns :

• area : object's surface
• area_exc : object surface excluding white pixels
• area_based_diameter : object's Area Based Diameter: 2 * (object_area/pi)^(1/2)
• meangreyobjet : mean image grey level
• modegreyobjet : modal object grey level
• sigmagrey : object grey level standard deviation
• mingrey : minimum object grey level
• maxgrey : maximum object grey level
• sumgrey : object grey level integrated density: object_mean*object_area
• breadth : breadth of the object along the best fitting ellipsoid minor axis
• length : breadth of the object along the best fitting ellipsoid majorr axis
• elongation : elongation index: object_length/object_breadth
• perim : object's perimeter
• minferetdiam : minimum object's feret diameter
• maxferetdiam : maximum object's feret diameter
• meanferetdiam : average object's feret diameter
• feretelongation : elongation index: object_maxferetdiam/object_minferetdiam
• compactness : Isoperimetric quotient: the ration of the object's area to the area of a circle having the same perimeter
• intercept0, intercept45 , intercept90, intercept135 : the number of times that a transition from background to foreground occurs a the angle 0ø, 45ø, 90ø and 135ø for the entire object
• convexhullarea : area of the convex hull of the object
• convexhullfillratio : ratio object_area/convexhullarea
• convexperimeter : perimeter of the convex hull of the object
• n_number_of_runs : number of horizontal strings of consecutive foreground pixels in the object
• n_chained_pixels : number of chained pixels in the object
• n_convex_hull_points : number of summits of the object's convex hull polygon
• n_number_of_holes : number of holes (as closed white pixel area) in the object
• roughness : measure of small scale variations of amplitude in the object's grey levels
• rectangularity : ratio of the object's area over its best bounding rectangle's area
• skewness : skewness of the object's grey level distribution
• kurtosis : kurtosis of the object's grey level distribution
• fractal_box : fractal dimension of the object's perimeter
• hist25, hist50, hist75 : grey level value at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram
• valhist25, valhist50, valhist75 : sum of grey levels at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogram
• nobj25, nobj50, nobj75 : number of objects after thresholding at the object_valhist25, object_valhist50 and object_valhist75 grey level
• symetrieh :index of horizontal symmetry
• symetriev : index of vertical symmetry
• skelarea : area of the object skeleton
• thick_r : maximum object's thickness/mean object's thickness
• cdist : distance between the mass and the grey level object's centroids

features_skimage.csv.gz

Table of morphological features recomputed with skimage.measure.regionprops on the ROIs produced by ZooCAM. See http://scikit-image.org/docs/dev/api/skimage.measure.html#skimage.measure.regionprops for documentation.

inventory.tsv

Tree view of the taxonomy and number of images in each taxon, displayed as text. With columns :

• lineage_level1 : taxonomic lineage corresponding to the level 1 classification
• taxon_level1 : name of the taxon corresponding to the level 1 classification
• n : number of objects in each taxon group

map.png

Map of the sampling locations, to give an idea of the diversity sampled in this dataset.

imgs

Directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.