Dataset UVP6Net: plankton images captured with the UVP6

Plankton was imaged with UVP6 in contrasted oceanic regions. The full images were processed by the UVP6 firmware and the regions of interest (ROIs) around each individual object were recorded. A set of associated features were measured on the objects (see Picheral et al. 2021, doi:10.1002/lom3.10475, for more information). All objects were classified by a limited number of operators into 110 different classes using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). The following dataset corresponds to the 634 459 objects that have an area superior to 73 pixels (equivalent spherical diameter of 9.8 pixels, corresponding to the default size limit of 620µm in the UVP6 configuration). The different files provide information about the features of the objects, their taxonomic identification as well as the raw images. 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%.

An additional folder is provided, which includes the subset of images used to train the unique embedded classification model of the UVP6 actually deployed on the NKE CTS5 floats (10.5281/zenodo.10694203). These images correspond to UVP6Net objects filtered to retain only those with a size of 79 pixels to fit with the 645µm class from EcoPart, resulting in a total of 595,595 objects. The taxonomic identification was also made coarser (from 110 classes to 20) to ensure adequate performance of the classification model on power-constrained hardware. Images in this subset display objects as shades of grey/white on a black background.

• Original dataset available online at: https://www.seanoe.org/data/00908/101948/.
• Original dataset license: <cc-by-nc-4.0>.

Details

• train split means (RGB): [0.9460734817311702]
• train split standard deviations (RGB): [0.1208790275683871]

Samples per class for split train

0: Actinopterygii         110.00
1: Amphipoda              182.00
2: Annelida               247.00
3: Appendicularia         144.00
4: Aulacanthidae          295.00
5: Aulatractus            111.00
6: Aulosphaeridae         364.00
7: Calanidae              877.00
8: Calanoida             ▇ 13506.00
9: Chaetognatha           572.00
10: Coelodendridae        211.00
11: Collodaria            658.00
12: Copepoda             ▇ 6119.00
13: Creseis acicula       153.00
14: Ctenophora            204.00
15: Echinodermata         104.00
16: Eumalacostraca        1311.00
17: Foraminifera          188.00
18: Hyperiidea            90.00
19: Narcomedusae          113.00
20: Ostracoda             541.00
21: Phyllodocida          129.00
22: Rhizaria              2202.00
23: Salpida               207.00
24: Siphonophorae         122.00
25: Swima                 236.00
26: Thecosomata           185.00
27: Trachymedusae         87.00
28: artefact             ▇▇▇ 30139.00
29: chain<Salpida         153.00
30: cloud                 242.00
31: copepoda_eggs         195.00
32: crystal               3770.00
33: darksphere            340.00
34: dead<house            909.00
35: detritus             ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 508817.00
36: fiber                ▇▇▇ 32592.00
37: filament              3306.00
38: fuzzy                 184.00
39: like<Copepoda         2717.00
40: like<Rhizaria         545.00
41: other<Cnidaria        412.00
42: other<living          1583.00
43: puff                 ▇ 7427.00
44: reflection            4593.00
45: small<Cnidaria        927.00
46: solitaryblack         149.00
47: solitaryglobule       247.00
48: spiky<Acantharia      201.00
49: spiky<Coelodendridae  109.00
50: star<Acantharia       411.00
51: t004                  249.00
52: t011                  111.00
53: tuff                  4863.00

Reference

Picheral, M., Jalabert, L., Motreuil, S., Courchet, L., Carray-Counil, L., Ricour, F., Panaiotis, T., Petit, F., & Elineau, A. (2024). UVP6Net: plankton images captured with the UVP6. SEANOE. https://doi.org/10.17882/101948

BibTEX

@article{dataset:uvp6net,
  title      = {UVP6Net: plankton images captured with the UVP6},
  author     = {Picheral, Marc and Jalabert, Laetitia and Motreuil, Solène
                and Courchet, Lucas and Carray-Counil, Louis and Ricour, Florian
                and Panaiotis, Thelma and Petit, Flavien and Elineau, Amanda},
  year       = 2024,
  journal    = {SEANOE},
  doi        = {10.17882/101948},
  affiliation = {Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France.
  Sorbonne Université, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.
  Freshwater and OCeanic science Unit of reSearch (FOCUS), University of Liège, Liège, Belgium.}
}

Usage

from datasets import load_dataset

dataset = load_dataset("project-oceania/uvp6net")