DOI: 10.17882/55741
title: ZooScanNet: plankton images captured with the ZooScan

description: Plankton was sampled with various nets, from bottom or 500m depth to the surface, in many oceans of the world. Samples were imaged with a ZooScan. The full images were processed with ZooProcess which generated regions of interest (ROIs) around each individual object and a set of associated features measured on the object (see Gorsky et al 2010 for more information). The same objects were re-processed to compute features with the scikit-image toolbox http://scikit-image.org. The 1,451,745 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 98 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 folder ZooScanNet_data.tar 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 metadata of each object including the different features processed by ZooProcess. 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:
 - objid: unique object identifier in EcoTaxa (integer number) And 48 features:
 - area
 - mean
 - stddev
 - mode
 - min/max
 - perim.
 - width,height 
 - major,minor
 - circ.
 - feret
 - intden
 - median
 - skew,kurt
 - %area
 - area_exc
 - fractal
 - skelarea
 - slope
 - histcum1,2,3
 - nb1,2,3
 - symetrieh,symetriev
 - symetriehc,symetrievc
 - convperim,convarea
 - fcons
 - thickr: 
 - esd
 - elongation
 - range
 - centroids
 - sr
 - perimareaexc
 - feretareaexc
 - perimferet/perimmajor
 - circex
 - cdexc
See the “ZooScan” sheet - OBJECT metadata, annotation and measurements - , at https://doi.org/10.5281/zenodo.14704250 for definitions.
features_skimage.csv.gz
Table of morphological features recomputed with skimage.measure.regionprops on the ROIs produced by ZooProcess. 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 class 
 
      2. Second folder ZooScanNet_imgs.tar contains :
imgs
Directory containing images of each object, named according to the object id objid and sorted in subdirectories according to their taxon.
 
      3. And :
map.png
Map of the sampling locations, to give an idea of the diversity sampled in this dataset.