Datasets:
metadata
license: cc-by-4.0
task_categories:
- image-classification
pretty_name: ZooLake Plankton Dataset
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': aphanizomenon
'1': asplanchna
'2': asterionella
'3': bosmina
'4': brachionus
'5': ceratium
'6': chaoborus
'7': conochilus
'8': copepod_skins
'9': cyclops
'10': daphnia
'11': daphnia_skins
'12': diaphanosoma
'13': diatom_chain
'14': dinobryon
'15': dirt
'16': eudiaptomus
'17': filament
'18': fish
'19': fragilaria
'20': hydra
'21': kellicottia
'22': keratella_cochlearis
'23': keratella_quadrata
'24': leptodora
'25': maybe_cyano
'26': nauplius
'27': paradileptus
'28': polyarthra
'29': rotifers
'30': synchaeta
'31': trichocerca
'32': unknown
'33': unknown_plankton
'34': uroglena
splits:
- name: train
num_bytes: 27604906.949
num_examples: 12559
- name: validation
num_bytes: 10401586.405
num_examples: 2691
- name: test
num_bytes: 10875089.144
num_examples: 2692
download_size: 59414182
dataset_size: 48881582.498
description: >-
Plankton images annotated into 35 classes over 17900 images of zooplankton
and large phytoplankton colonies, detected in Lake Greifensee (Switzerland)
with the Dual Scripps Plankton Camera.
dataset_name: ZooLake Plankton Dataset
citation: |-
@article{dataset:zoolake,
title = {Deep learning classification of lake zooplankton},
author = {Kyathanahally, S.P. and Hardeman, T. and Merz, E. and Bulas, T. and Reyes, M. and Isles, P. and Pomati, F. and Baity-Jesi, M.},
journal = {Frontiers in Microbiology},
volume = {12},
year = {2021},
doi = {10.3389/fmicb.2021.746297},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2021.746297}
}
homepage: >-
https://opendata.eawag.ch/dataset/52b6ba86-5ecb-448c-8c01-eec7cb209dc7/resource/1cc785fa-36c2-447d-bb11-92ce1d1f3f2d/download/data.zip
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_description: >-
Plankton images annotated into 35 classes over 17900 images of zooplankton and
large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with
the Dual Scripps Plankton Camera.
citation_bibtex: |-
@article{dataset:zoolake,
title = {Deep learning classification of lake zooplankton},
author = {Kyathanahally, S.P. and Hardeman, T. and Merz, E. and Bulas, T. and Reyes, M. and Isles, P. and Pomati, F. and Baity-Jesi, M.},
journal = {Frontiers in Microbiology},
volume = {12},
year = {2021},
doi = {10.3389/fmicb.2021.746297},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2021.746297}
}
citation_apa: >
Kyathanahally, S. P., Hardeman, T., Merz, E., Bulas, T., Reyes, M., Isles, P.,
Pomati, F., & Baity-Jesi, M. (2021).
Deep learning classification of lake zooplankton. Frontiers in Microbiology,
12. https://doi.org/10.3389/fmicb.2021.746297
hf_dataset_name: zoolake
hf_org_name: project-oceania
source_url: >-
https://opendata.eawag.ch/dataset/52b6ba86-5ecb-448c-8c01-eec7cb209dc7/resource/1cc785fa-36c2-447d-bb11-92ce1d1f3f2d/download/data.zip
report_markdown: >
**Samples per class for split `train`**
```──────────────────────── Label histogram for train split ─────────────────────────
0: aphanizomenon ▇▇▇▇ 164.00
1: asplanchna ▇▇▇▇▇▇▇▇▇ 410.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 735.00
3: bosmina ▇ 51.00
4: brachionus ▇▇ 93.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇ 558.00
6: chaoborus 7.00
7: conochilus ▇▇▇▇ 189.00
8: copepod_skins ▇ 24.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇ 591.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇▇ 510.00
11: daphnia_skins ▇ 39.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 769.00
13: diatom_chain 12.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
2366.00
15: dirt ▇▇ 91.00
16: eudiaptomus ▇▇▇▇▇▇▇▇ 375.00
17: filament ▇▇▇▇▇▇ 276.00
18: fish ▇▇▇ 155.00
19: fragilaria ▇▇▇▇▇ 215.00
20: hydra 15.00
21: kellicottia ▇▇▇▇▇▇▇▇ 375.00
22: keratella_cochlearis ▇▇ 84.00
23: keratella_quadrata ▇▇▇▇▇▇ 285.00
24: leptodora ▇▇▇ 144.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 958.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 1044.00
27: paradileptus ▇▇▇▇▇▇ 291.00
28: polyarthra ▇ 57.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇▇▇ 535.00
30: synchaeta ▇▇ 90.00
31: trichocerca ▇▇▇▇ 174.00
32: unknown ▇▇▇▇ 176.00
33: unknown_plankton ▇ 49.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 652.00
```
**Samples per class for split `validation`**
```────────────────────── Label histogram for validation split ──────────────────────
0: aphanizomenon ▇▇▇ 33.00
1: asplanchna ▇▇▇▇▇▇▇▇▇▇▇ 103.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 154.00
3: bosmina ▇▇ 15.00
4: brachionus ▇▇ 23.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇▇ 126.00
6: chaoborus 1.00
7: conochilus ▇▇▇ 33.00
8: copepod_skins 3.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇ 127.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇ 99.00
11: daphnia_skins 2.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 159.00
13: diatom_chain 2.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
510.00
15: dirt ▇▇ 18.00
16: eudiaptomus ▇▇▇▇▇▇▇▇▇ 87.00
17: filament ▇▇▇▇▇▇▇ 64.00
18: fish ▇▇▇ 29.00
19: fragilaria ▇▇▇▇▇▇ 56.00
20: hydra 2.00
21: kellicottia ▇▇▇▇▇▇▇▇ 79.00
22: keratella_cochlearis ▇▇ 15.00
23: keratella_quadrata ▇▇▇▇▇▇▇ 70.00
24: leptodora ▇▇▇ 26.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 202.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 222.00
27: paradileptus ▇▇▇▇▇▇▇ 72.00
28: polyarthra ▇ 10.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇ 100.00
30: synchaeta ▇▇ 23.00
31: trichocerca ▇▇▇▇ 44.00
32: unknown ▇▇▇ 26.00
33: unknown_plankton ▇ 11.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 145.00
```
**Samples per class for split `test`**
```───────────────────────── Label histogram for test split ─────────────────────────
0: aphanizomenon ▇▇▇ 28.00
1: asplanchna ▇▇▇▇▇▇▇▇▇▇▇ 93.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 165.00
3: bosmina ▇▇ 14.00
4: brachionus ▇▇ 21.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 130.00
6: chaoborus 2.00
7: conochilus ▇▇▇▇▇ 42.00
8: copepod_skins ▇ 6.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 148.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇▇▇▇ 112.00
11: daphnia_skins ▇ 5.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 161.00
13: diatom_chain 3.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
446.00
15: dirt ▇▇▇ 22.00
16: eudiaptomus ▇▇▇▇▇▇▇▇▇ 75.00
17: filament ▇▇▇▇▇▇▇▇ 65.00
18: fish ▇▇▇▇ 38.00
19: fragilaria ▇▇▇▇ 35.00
20: hydra 1.00
21: kellicottia ▇▇▇▇▇▇▇▇ 65.00
22: keratella_cochlearis ▇▇ 13.00
23: keratella_quadrata ▇▇▇▇▇▇▇▇ 65.00
24: leptodora ▇▇▇▇ 33.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 204.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 241.00
27: paradileptus ▇▇▇▇▇▇▇ 61.00
28: polyarthra ▇ 12.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇▇▇▇ 110.00
30: synchaeta ▇▇▇ 29.00
31: trichocerca ▇▇▇▇ 37.00
32: unknown ▇▇▇▇▇ 43.00
33: unknown_plankton ▇ 11.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 156.00
```
dataset_means: '[0.05492783056776769, 0.050561395292361595, 0.04523793400099787]'
dataset_stds: '[0.1515838323231226, 0.14021859660251165, 0.12578012700158586]'
Dataset ZooLake Plankton Dataset
Plankton images annotated into 35 classes over 17900 images of zooplankton and large phytoplankton colonies, detected in Lake Greifensee (Switzerland) with the Dual Scripps Plankton Camera.
- Original dataset available online at: https://opendata.eawag.ch/dataset/52b6ba86-5ecb-448c-8c01-eec7cb209dc7/resource/1cc785fa-36c2-447d-bb11-92ce1d1f3f2d/download/data.zip.
- Original dataset license: <cc-by-4.0>.
Details
- train split means (RGB): [0.05492783056776769, 0.050561395292361595, 0.04523793400099787]
- train split standard deviations (RGB): [0.1515838323231226, 0.14021859660251165, 0.12578012700158586]
Samples per class for split train
0: aphanizomenon ▇▇▇▇ 164.00
1: asplanchna ▇▇▇▇▇▇▇▇▇ 410.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 735.00
3: bosmina ▇ 51.00
4: brachionus ▇▇ 93.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇ 558.00
6: chaoborus 7.00
7: conochilus ▇▇▇▇ 189.00
8: copepod_skins ▇ 24.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇ 591.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇▇ 510.00
11: daphnia_skins ▇ 39.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 769.00
13: diatom_chain 12.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 2366.00
15: dirt ▇▇ 91.00
16: eudiaptomus ▇▇▇▇▇▇▇▇ 375.00
17: filament ▇▇▇▇▇▇ 276.00
18: fish ▇▇▇ 155.00
19: fragilaria ▇▇▇▇▇ 215.00
20: hydra 15.00
21: kellicottia ▇▇▇▇▇▇▇▇ 375.00
22: keratella_cochlearis ▇▇ 84.00
23: keratella_quadrata ▇▇▇▇▇▇ 285.00
24: leptodora ▇▇▇ 144.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 958.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 1044.00
27: paradileptus ▇▇▇▇▇▇ 291.00
28: polyarthra ▇ 57.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇▇▇ 535.00
30: synchaeta ▇▇ 90.00
31: trichocerca ▇▇▇▇ 174.00
32: unknown ▇▇▇▇ 176.00
33: unknown_plankton ▇ 49.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 652.00
Samples per class for split validation
0: aphanizomenon ▇▇▇ 33.00
1: asplanchna ▇▇▇▇▇▇▇▇▇▇▇ 103.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 154.00
3: bosmina ▇▇ 15.00
4: brachionus ▇▇ 23.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇▇ 126.00
6: chaoborus 1.00
7: conochilus ▇▇▇ 33.00
8: copepod_skins 3.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇ 127.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇ 99.00
11: daphnia_skins 2.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 159.00
13: diatom_chain 2.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 510.00
15: dirt ▇▇ 18.00
16: eudiaptomus ▇▇▇▇▇▇▇▇▇ 87.00
17: filament ▇▇▇▇▇▇▇ 64.00
18: fish ▇▇▇ 29.00
19: fragilaria ▇▇▇▇▇▇ 56.00
20: hydra 2.00
21: kellicottia ▇▇▇▇▇▇▇▇ 79.00
22: keratella_cochlearis ▇▇ 15.00
23: keratella_quadrata ▇▇▇▇▇▇▇ 70.00
24: leptodora ▇▇▇ 26.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 202.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 222.00
27: paradileptus ▇▇▇▇▇▇▇ 72.00
28: polyarthra ▇ 10.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇ 100.00
30: synchaeta ▇▇ 23.00
31: trichocerca ▇▇▇▇ 44.00
32: unknown ▇▇▇ 26.00
33: unknown_plankton ▇ 11.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 145.00
Samples per class for split test
0: aphanizomenon ▇▇▇ 28.00
1: asplanchna ▇▇▇▇▇▇▇▇▇▇▇ 93.00
2: asterionella ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 165.00
3: bosmina ▇▇ 14.00
4: brachionus ▇▇ 21.00
5: ceratium ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 130.00
6: chaoborus 2.00
7: conochilus ▇▇▇▇▇ 42.00
8: copepod_skins ▇ 6.00
9: cyclops ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 148.00
10: daphnia ▇▇▇▇▇▇▇▇▇▇▇▇▇ 112.00
11: daphnia_skins ▇ 5.00
12: diaphanosoma ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 161.00
13: diatom_chain 3.00
14: dinobryon ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 446.00
15: dirt ▇▇▇ 22.00
16: eudiaptomus ▇▇▇▇▇▇▇▇▇ 75.00
17: filament ▇▇▇▇▇▇▇▇ 65.00
18: fish ▇▇▇▇ 38.00
19: fragilaria ▇▇▇▇ 35.00
20: hydra 1.00
21: kellicottia ▇▇▇▇▇▇▇▇ 65.00
22: keratella_cochlearis ▇▇ 13.00
23: keratella_quadrata ▇▇▇▇▇▇▇▇ 65.00
24: leptodora ▇▇▇▇ 33.00
25: maybe_cyano ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 204.00
26: nauplius ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 241.00
27: paradileptus ▇▇▇▇▇▇▇ 61.00
28: polyarthra ▇ 12.00
29: rotifers ▇▇▇▇▇▇▇▇▇▇▇▇▇ 110.00
30: synchaeta ▇▇▇ 29.00
31: trichocerca ▇▇▇▇ 37.00
32: unknown ▇▇▇▇▇ 43.00
33: unknown_plankton ▇ 11.00
34: uroglena ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 156.00
Reference
Kyathanahally, S. P., Hardeman, T., Merz, E., Bulas, T., Reyes, M., Isles, P., Pomati, F., & Baity-Jesi, M. (2021). Deep learning classification of lake zooplankton. Frontiers in Microbiology, 12. https://doi.org/10.3389/fmicb.2021.746297
BibTEX
@article{dataset:zoolake,
title = {Deep learning classification of lake zooplankton},
author = {Kyathanahally, S.P. and Hardeman, T. and Merz, E. and Bulas, T. and Reyes, M. and Isles, P. and Pomati, F. and Baity-Jesi, M.},
journal = {Frontiers in Microbiology},
volume = {12},
year = {2021},
doi = {10.3389/fmicb.2021.746297},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2021.746297}
}
Usage
from datasets import load_dataset
dataset = load_dataset("project-oceania/zoolake")