Datasets:
metadata
license: cc-by-nc-4.0
task_categories:
- image-classification
paperswithcode_id: isiisnet
pretty_name: >-
ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton
Imaging System)
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Acantharea
'1': Actinopterygii
'2': Annelida
'3': Appendicularia
'4': Appendicularia_body
'5': Appendicularia_like_body
'6': Aulacanthidae
'7': Bacillariophyceae
'8': Chaetognatha
'9': Cnidaria
'10': Copepoda
'11': Crustacea
'12': Ctenophora
'13': Doliolida
'14': Eumalacostraca
'15': Harpacticoida
'16': Mollusca
'17': Pyrocystis
'18': Rhizaria
'19': Rhopalonematidae
'20': Siphonophorae
'21': colonial_colodaria
'22': detritus
'23': ephyra
'24': house
'25': like_Acantharea
'26': like_Copepoda
'27': other_living
'28': part_Cnidaria
'29': solitaryblack
'30': streak
'31': vertical line
splits:
- name: train
num_bytes: 173351907
num_examples: 408166
download_size: 145223471
dataset_size: 173351907
description: >
Plankton was imaged with an In Situ Ichthyoplankton Imaging System, between
surface and ~100m, over 10 days
in July 2016, in the North Western Mediterranean Sea. This deployment was
the core of the VISUFRONT cruise.
The image generated by the linescan, shadowgraph camera of ISIIS were
processed with the custom software apeep
and regions of interest, targeted to be planktonic organisms by a deep
segmenter, were extracted. The 408,166
resulting objects were sorted by a limited number of operators, following a
common taxonomic guide, into 32
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%.
dataset_name: >-
ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton
Imaging System)
citation: |-
@article{dataset:isiisnet,
title = {ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton Imaging System)},
author = {Panaïotis, Thelma and Caray-Counil, Louis
and Jalabert, Laetitia and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101950},
affiliation = {Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France.
Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.}
}
homepage: https://www.seanoe.org/data/00908/101950/
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_description: >
Plankton was imaged with an In Situ Ichthyoplankton Imaging System, between
surface and ~100m, over 10 days
in July 2016, in the North Western Mediterranean Sea. This deployment was the
core of the VISUFRONT cruise.
The image generated by the linescan, shadowgraph camera of ISIIS were
processed with the custom software apeep
and regions of interest, targeted to be planktonic organisms by a deep
segmenter, were extracted. The 408,166
resulting objects were sorted by a limited number of operators, following a
common taxonomic guide, into 32
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%.
source_url: https://www.seanoe.org/data/00908/101950/
citation_bibtex: |-
@article{dataset:isiisnet,
title = {ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton Imaging System)},
author = {Panaïotis, Thelma and Caray-Counil, Louis
and Jalabert, Laetitia and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101950},
affiliation = {Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France.
Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.}
}
citation_apa: >
Panaïotis, T., Caray-Counil, L., Jalabert, L., & Irisson, J.-O. (2024).
ISIISNet: plankton images captured with the ISIIS
(In-situ Ichthyoplankton Imaging System). SEANOE.
https://doi.org/10.17882/101950
hf_dataset_name: isiisnet
hf_org_name: project-oceania
report_markdown: >
**Samples per class for split `train`**
```──────────────────────── Label histogram for train split ─────────────────────────
0: Acantharea 2110.00
1: Actinopterygii 276.00
2: Annelida 130.00
3: Appendicularia 419.00
4: Appendicularia_body 3265.00
5: Appendicularia_like_body 835.00
6: Aulacanthidae 1952.00
7: Bacillariophyceae 1859.00
8: Chaetognatha 240.00
9: Cnidaria 130.00
10: Copepoda ▇▇ 12073.00
11: Crustacea 981.00
12: Ctenophora 1362.00
13: Doliolida ▇ 7079.00
14: Eumalacostraca 95.00
15: Harpacticoida 646.00
16: Mollusca 186.00
17: Pyrocystis 2567.00
18: Rhizaria 2064.00
19: Rhopalonematidae 423.00
20: Siphonophorae 1699.00
21: colonial_colodaria 290.00
22: detritus ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
321335.00
23: ephyra 480.00
24: house 92.00
25: like_Acantharea 89.00
26: like_Copepoda ▇▇▇ 19196.00
27: other_living 987.00
28: part_Cnidaria 1281.00
29: solitaryblack 454.00
30: streak ▇▇▇ 23501.00
31: vertical line 70.00
```
dataset_means: '[0.9464540308383366]'
dataset_stds: '[0.16473865521613654]'
Dataset ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton Imaging System)
Plankton was imaged with an In Situ Ichthyoplankton Imaging System, between surface and ~100m, over 10 days in July 2016, in the North Western Mediterranean Sea. This deployment was the core of the VISUFRONT cruise. The image generated by the linescan, shadowgraph camera of ISIIS were processed with the custom software apeep and regions of interest, targeted to be planktonic organisms by a deep segmenter, were extracted. The 408,166 resulting objects were sorted by a limited number of operators, following a common taxonomic guide, into 32 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/00908/101950/.
- Original dataset license: <cc-by-nc-4.0>.
Details
- train split means (RGB): [0.9464540308383366]
- train split standard deviations (RGB): [0.16473865521613654]
Samples per class for split train
0: Acantharea 2110.00
1: Actinopterygii 276.00
2: Annelida 130.00
3: Appendicularia 419.00
4: Appendicularia_body 3265.00
5: Appendicularia_like_body 835.00
6: Aulacanthidae 1952.00
7: Bacillariophyceae 1859.00
8: Chaetognatha 240.00
9: Cnidaria 130.00
10: Copepoda ▇▇ 12073.00
11: Crustacea 981.00
12: Ctenophora 1362.00
13: Doliolida ▇ 7079.00
14: Eumalacostraca 95.00
15: Harpacticoida 646.00
16: Mollusca 186.00
17: Pyrocystis 2567.00
18: Rhizaria 2064.00
19: Rhopalonematidae 423.00
20: Siphonophorae 1699.00
21: colonial_colodaria 290.00
22: detritus ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 321335.00
23: ephyra 480.00
24: house 92.00
25: like_Acantharea 89.00
26: like_Copepoda ▇▇▇ 19196.00
27: other_living 987.00
28: part_Cnidaria 1281.00
29: solitaryblack 454.00
30: streak ▇▇▇ 23501.00
31: vertical line 70.00
Reference
Panaïotis, T., Caray-Counil, L., Jalabert, L., & Irisson, J.-O. (2024). ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton Imaging System). SEANOE. https://doi.org/10.17882/101950
BibTEX
@article{dataset:isiisnet,
title = {ISIISNet: plankton images captured with the ISIIS (In-situ Ichthyoplankton Imaging System)},
author = {Panaïotis, Thelma and Caray-Counil, Louis
and Jalabert, Laetitia and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101950},
affiliation = {Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France.
Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.}
}
Usage
from datasets import load_dataset
dataset = load_dataset("project-oceania/isiisnet")