Dataset ZooScanNet Plankton Images Dataset

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%.

• Original dataset available online at: https://www.seanoe.org/data/00446/55741/.
• Original dataset license: <cc-by-nc-4.0>.

Details

• train split means (RGB): [0.929428561717876]
• train split standard deviations (RGB): [0.16058646124175738]

Samples per class for split train

0: Acartiidae                      ▇▇▇▇▇▇▇▇▇▇ 59018.00
1: Actiniaria                       140.00
2: Actinopterygii                   1925.00
3: Aglaura                          3033.00
4: Amphipoda                        833.00
5: Annelida                         2325.00
6: Atlanta                          447.00
7: Bassia                           95.00
8: Bivalvia                        ▇ 5178.00
9: Calanidae                       ▇▇▇▇▇▇▇ 41264.00
10: Calanoida                      ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 151417.00
11: Calocalanus pavo                469.00
12: Candaciidae                    ▇▇ 11776.00
13: Cavolinia inflexa              ▇ 4408.00
14: Centropagidae                  ▇▇▇▇▇▇▇ 45930.00
15: Chaetognatha                   ▇▇▇▇▇▇▇▇ 52390.00
16: Copilia                         657.00
17: Corycaeidae                    ▇▇▇▇ 23834.00
18: Coscinodiscus                  ▇ 7163.00
19: Creseidae                      ▇ 5111.00
20: Creseidae acicula              ▇ 8621.00
21: Ctenophora                      910.00
22: Cumacea                         515.00
23: Cymbulia peroni                 93.00
24: Doliolida                      ▇▇ 9738.00
25: Eucalanidae                     1216.00
26: Euchaetidae                    ▇ 6790.00
27: Eumalacostraca                 ▇▇▇▇ 23015.00
28: Evadne                         ▇▇▇▇▇ 33348.00
29: Foraminifera                   ▇ 3126.00
30: Fritillariidae                 ▇▇ 12132.00
31: Gymnosomata                     522.00
32: Haloptilus                      2713.00
33: Harosa                          1624.00
34: Harpacticoida                  ▇ 5545.00
35: Heterorhabdidae                 2364.00
36: Hydrozoa                       ▇ 3859.00
37: Hyperiidea                      1923.00
38: Insecta                         1122.00
39: Isopoda                         552.00
40: Limacinidae                    ▇▇ 14084.00
41: Liriope                         224.00
42: Metridinidae                   ▇▇▇ 16254.00
43: Mysida                          798.00
44: Neoceratium                     348.00
45: Noctiluca                      ▇ 6527.00
46: Obelia                          974.00
47: Oikopleuridae                  ▇▇▇▇▇ 33108.00
48: Oithonidae                     ▇▇▇▇▇▇▇▇▇▇▇ 65646.00
49: Oncaeidae                      ▇▇▇ 20463.00
50: Ostracoda                      ▇ 7789.00
51: Penilia                        ▇▇▇▇ 23945.00
52: Phaeodaria                     ▇▇▇▇▇▇▇▇▇ 54036.00
53: Physonectae                     105.00
54: Podon                           1943.00
55: Pontellidae                    ▇ 7196.00
56: Pyrosomatida                    497.00
57: Rhincalanidae                   228.00
58: Rhopalonema velatum             2484.00
59: Salpida                        ▇▇▇ 16399.00
60: Sapphirinidae                   1078.00
61: Solmundella bitentaculata       372.00
62: Temoridae                      ▇▇▇▇▇ 30326.00
63: Tomopteridae                    550.00
64: actinula                        125.00
65: artefact                       ▇▇▇▇▇▇▇▇ 51452.00
66: badfocus                       ▇▇▇▇▇▇▇ 40301.00
67: bract_Abylopsis tetragona       1232.00
68: bract_Diphyidae                ▇▇ 14566.00
69: bubble                         ▇▇▇ 16208.00
70: calyptopsis                    ▇ 8028.00
71: cirrus                          397.00
72: cyphonaute                     ▇ 8888.00
73: cypris                          975.00
74: detritus                       ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 241731.00
75: egg_Actinopterygii             ▇ 4587.00
76: egg_Mollusca                    858.00
77: endostyle                       896.00
78: ephyra                          1190.00
79: eudoxie_Abylopsis tetragona     649.00
80: eudoxie_Diphyidae              ▇ 3498.00
81: fiber                          ▇▇▇▇▇▇▇ 44716.00
82: gonophore_Abylopsis tetragona   1324.00
83: gonophore_Diphyidae            ▇▇▇ 16398.00
84: head_Chaetognatha               1266.00
85: juvenile_Salpida                441.00
86: larvae_Annelida                 328.00
87: larvae_Echinodermata            505.00
88: larvae_Luciferidae              650.00
89: larvae_Mysida                   90.00
90: larvae_Porcellanidae           ▇ 4986.00
91: larvae_Stomatopoda              1629.00
92: megalopa                        1417.00
93: metanauplii_Crustacea           241.00
94: nauplii_Cirripedia             ▇ 4321.00
95: nauplii_Crustacea              ▇ 5633.00
96: nectophore_Abylopsis tetragona  1149.00
97: nectophore_Diphyidae           ▇▇▇▇▇ 29440.00
98: nectophore_Hippopodiidae        108.00
99: nectophore_Physonectae         ▇ 9235.00
100: nucleus                        1477.00
101: other_egg                     ▇▇ 13431.00
102: other_living                   261.00
103: part_Annelida                  989.00
104: part_Cnidaria                  832.00
105: part_Crustacea                ▇▇▇ 20429.00
106: part_Mollusca                  1698.00
107: part_Siphonophorae             2741.00
108: pluteus_Echinoidea             2406.00
109: pluteus_Ophiuroidea           ▇ 3610.00
110: protozoea_Eumalacostraca       1498.00
111: protozoea_Penaeidae            392.00
112: protozoea_Sergestidae          593.00
113: seaweed                       ▇ 8475.00
114: siphonula                      956.00
115: tail_Appendicularia           ▇ 8284.00
116: tail_Chaetognatha             ▇ 3695.00
117: trunk_Appendicularia           1283.00
118: zoea_Brachyura                ▇▇ 11663.00
119: zoea_Galatheidae              ▇ 5059.00

Reference

Elineau, A., Desnos, C., Jalabert, L., Olivier, M., Romagnan, J.-B., Costa Brandao, M., Lombard, F., Llopis, N., Courboulès, J., Caray-Counil, L., Serranito, B., Irisson, J.-O., Picheral, M., Gorsky, G., & Stemmann, L. (2017). ZooScanNet: plankton images captured with the ZooScan. SEANOE. https://doi.org/10.17882/55741

BibTEX

@article{dataset:zooscannet,
  title      = {ZooScanNet: plankton images captured with the ZooScan},
  author     = {
    Elineau, Amanda and Desnos, Corinne and Jalabert, Laetitia and Olivier,
    Marion and Romagnan, Jean-Baptiste and Costa Brandao, Manoela and Lombard,
    Fabien and Llopis, Natalia and Courboul\`{e}s, Justine and Caray-Counil,
    Louis and Serranito, Bruno and Irisson, Jean-Olivier and Picheral, Marc and
    Gorsky, Gaby and Stemmann, Lars
  },
  year       = 2017,
  journal    = {SEANOE},
  doi        = {10.17882/55741},
  affiliation = {Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France}
}

Usage

from datasets import load_dataset

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