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 &lt; 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.gzTable 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 classificationlineage_level1 : taxonomic lineage corresponding to the level 1 classificationtaxon_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 idfeatures_native.csv.gzTable 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 surfacearea_exc : object surface excluding white pixelsarea_based_diameter : object's Area Based Diameter: 2 * (object_area/pi)^(1/2)meangreyobjet : mean image grey levelmodegreyobjet : modal object grey levelsigmagrey : object grey level standard deviationmingrey : minimum object grey levelmaxgrey : maximum object grey levelsumgrey : object grey level integrated density: object_mean*object_areabreadth : breadth of the object along the best fitting ellipsoid minor axislength : breadth of the object along the best fitting ellipsoid majorr axiselongation : elongation index: object_length/object_breadthperim : object's perimeterminferetdiam : minimum object's feret diametermaxferetdiam : maximum object's feret diametermeanferetdiam : average object's feret diameterferetelongation : elongation index: object_maxferetdiam/object_minferetdiamcompactness : Isoperimetric quotient: the ration of the object's area to the area of a circle having the same perimeterintercept0, 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 objectconvexhullarea : area of the convex hull of the objectconvexhullfillratio : ratio object_area/convexhullareaconvexperimeter : perimeter of the convex hull of the objectn_number_of_runs : number of horizontal strings of consecutive foreground pixels in the objectn_chained_pixels : number of chained pixels in the objectn_convex_hull_points : number of summits of the object's convex hull polygonn_number_of_holes : number of holes (as closed white pixel area) in the objectroughness : measure of small scale variations of amplitude in the object's grey levelsrectangularity : ratio of the object's area over its best bounding rectangle's areaskewness : skewness of the object's grey level distributionkurtosis : kurtosis of the object's grey level distributionfractal_box : fractal dimension of the object's perimeterhist25, hist50, hist75 : grey level value at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogramvalhist25, valhist50, valhist75 : sum of grey levels at quantile 0.25, 0.5 and 0.75 of the object's grey levels normalized cumulative histogramnobj25, nobj50, nobj75 : number of objects after thresholding at the object_valhist25, object_valhist50 and object_valhist75 grey levelsymetrieh :index of horizontal symmetrysymetriev : index of vertical symmetryskelarea : area of the object skeletonthick_r : maximum object's thickness/mean object's thicknesscdist : distance between the mass and the grey level object's centroidsfeatures_skimage.csv.gzTable 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.tsvTree 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 classificationtaxon_level1 : name of the taxon corresponding to the level 1 classificationn : number of objects in each taxon groupmap.pngMap of the sampling locations, to give an idea of the diversity sampled in this dataset.imgsDirectory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.< Leer menos