Datasets:
metadata
license: cc-by-nc-4.0
task_categories:
- image-classification
paperswithcode_id: flowcamnet
pretty_name: 'FlowCAMNet: plankton images captured with the FlowCAM'
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Acantharia
'1': Amphorides
'2': Calanoida
'3': Cladopyxis
'4': Climacodium inter. Crocosphaera
'5': Codonaria
'6': Dictyocysta
'7': Ditylum
'8': Eutintinnus
'9': Foraminifera
'10': Fragilariopsis
'11': Katagnymene spiralis
'12': Metacylis
'13': Nitzschia
'14': Ornithocercus
'15': Oxytoxum
'16': Planktoniella sol
'17': Podolampas
'18': Protoperidinium
'19': Rhabdonellidae
'20': Rhizosoleniaceae
'21': Spumellaria
'22': Thalassionematales
'23': Undellidae
'24': Xystonellidae
'25': artefact
'26': badfocus
'27': chainlarge
'28': cyano a
'29': cyano b
'30': dark
'31': darkrods
'32': darksphere
'33': detritus
'34': nauplii
'35': other_egg
'36': part_Ciliophora
'37': transparent_u
splits:
- name: train
num_bytes: 1019454648.649
num_examples: 141013
download_size: 283069024
dataset_size: 1019454648.649
description: >
Plankton was imaged with Flowcam in contrasted oceanic regions. The full
images were processed with the ImageJ
software and the regions of interest (ROIs) around each individual object
were recorded. A set of associated
features were measured on the objects. All objects were classified by a
limited number of operators into 167
different classes using the web application EcoTaxa
(http://ecotaxa.obs-vlfr.fr). The following dataset
corresponds to the 301,247 objects and their calculated features. The
different files provide information about
the features of the objects, their taxonomic identification as well as the
raw images.
dataset_name: 'FlowCAMNet: plankton images captured with the FlowCAM'
citation: |-
@article{dataset:flowcamnet,
title = {FlowCAMNet: plankton images captured with the FlowCAM},
author = {Jalabert, Laetitia and Signoret, Guillaume and Caray-Counil, Louis
and Vilain, Marion and Martins, Emmanuelle and Lombard, Fabien
and Picheral, Marc and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101961},
affiliation = {Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.
Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France}
}
homepage: https://www.seanoe.org/data/00908/101961/
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_description: >
Plankton was imaged with Flowcam in contrasted oceanic regions. The full
images were processed with the ImageJ
software and the regions of interest (ROIs) around each individual object were
recorded. A set of associated
features were measured on the objects. All objects were classified by a
limited number of operators into 167
different classes using the web application EcoTaxa
(http://ecotaxa.obs-vlfr.fr). The following dataset
corresponds to the 301,247 objects and their calculated features. The
different files provide information about
the features of the objects, their taxonomic identification as well as the raw
images.
source_url: https://www.seanoe.org/data/00908/101961/
citation_bibtex: |-
@article{dataset:flowcamnet,
title = {FlowCAMNet: plankton images captured with the FlowCAM},
author = {Jalabert, Laetitia and Signoret, Guillaume and Caray-Counil, Louis
and Vilain, Marion and Martins, Emmanuelle and Lombard, Fabien
and Picheral, Marc and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101961},
affiliation = {Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.
Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefanche, LOV, 06230 Villefranche-sur-mer, France}
}
citation_apa: >
Jalabert, L., Signoret, G., Caray-Counil, L., Vilain, M., Martins, E.,
Lombard, F., Picheral, M., & Irisson, J.-O. (2024).
FlowCAMNet: plankton images captured with the FlowCAM. SEANOE.
https://doi.org/10.17882/101961
hf_dataset_name: flowcamnet
hf_org_name: project-oceania
report_markdown: >
**Samples per class for split `train`**
```──────────────────────── Label histogram for train split ─────────────────────────
0: Acantharia 79.00
1: Amphorides 129.00
2: Calanoida 282.00
3: Cladopyxis 81.00
4: Climacodium inter. Crocosphaera 345.00
5: Codonaria 82.00
6: Dictyocysta 229.00
7: Ditylum 817.00
8: Eutintinnus 682.00
9: Foraminifera 231.00
10: Fragilariopsis 80.00
11: Katagnymene spiralis 102.00
12: Metacylis 86.00
13: Nitzschia 167.00
14: Ornithocercus 234.00
15: Oxytoxum 116.00
16: Planktoniella sol ▇ 1207.00
17: Podolampas 309.00
18: Protoperidinium 643.00
19: Rhabdonellidae ▇ 1088.00
20: Rhizosoleniaceae ▇▇▇ 5524.00
21: Spumellaria 229.00
22: Thalassionematales ▇ 868.00
23: Undellidae 685.00
24: Xystonellidae 356.00
25: artefact ▇▇ 2843.00
26: badfocus 431.00
27: chainlarge 422.00
28: cyano a ▇▇▇▇ 7301.00
29: cyano b ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 36215.00
30: dark ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
69085.00
31: darkrods 841.00
32: darksphere ▇ 1704.00
33: detritus ▇ 1700.00
34: nauplii ▇▇▇ 5347.00
35: other_egg 163.00
36: part_Ciliophora 148.00
37: transparent_u 162.00
```
dataset_means: '[0.9206037913052166]'
dataset_stds: '[0.20063320130738121]'
Dataset FlowCAMNet: plankton images captured with the FlowCAM
Plankton was imaged with Flowcam in contrasted oceanic regions. The full images were processed with the ImageJ software and the regions of interest (ROIs) around each individual object were recorded. A set of associated features were measured on the objects. All objects were classified by a limited number of operators into 167 different classes using the web application EcoTaxa (http://ecotaxa.obs-vlfr.fr). The following dataset corresponds to the 301,247 objects and their calculated features. The different files provide information about the features of the objects, their taxonomic identification as well as the raw images.
- Original dataset available online at: https://www.seanoe.org/data/00908/101961/.
- Original dataset license: <cc-by-nc-4.0>.
Details
- train split means (RGB): [0.9206037913052166]
- train split standard deviations (RGB): [0.20063320130738121]
Samples per class for split train
0: Acantharia 79.00
1: Amphorides 129.00
2: Calanoida 282.00
3: Cladopyxis 81.00
4: Climacodium inter. Crocosphaera 345.00
5: Codonaria 82.00
6: Dictyocysta 229.00
7: Ditylum 817.00
8: Eutintinnus 682.00
9: Foraminifera 231.00
10: Fragilariopsis 80.00
11: Katagnymene spiralis 102.00
12: Metacylis 86.00
13: Nitzschia 167.00
14: Ornithocercus 234.00
15: Oxytoxum 116.00
16: Planktoniella sol ▇ 1207.00
17: Podolampas 309.00
18: Protoperidinium 643.00
19: Rhabdonellidae ▇ 1088.00
20: Rhizosoleniaceae ▇▇▇ 5524.00
21: Spumellaria 229.00
22: Thalassionematales ▇ 868.00
23: Undellidae 685.00
24: Xystonellidae 356.00
25: artefact ▇▇ 2843.00
26: badfocus 431.00
27: chainlarge 422.00
28: cyano a ▇▇▇▇ 7301.00
29: cyano b ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 36215.00
30: dark ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 69085.00
31: darkrods 841.00
32: darksphere ▇ 1704.00
33: detritus ▇ 1700.00
34: nauplii ▇▇▇ 5347.00
35: other_egg 163.00
36: part_Ciliophora 148.00
37: transparent_u 162.00
Reference
Jalabert, L., Signoret, G., Caray-Counil, L., Vilain, M., Martins, E., Lombard, F., Picheral, M., & Irisson, J.-O. (2024). FlowCAMNet: plankton images captured with the FlowCAM. SEANOE. https://doi.org/10.17882/101961
BibTEX
@article{dataset:flowcamnet,
title = {FlowCAMNet: plankton images captured with the FlowCAM},
author = {Jalabert, Laetitia and Signoret, Guillaume and Caray-Counil, Louis
and Vilain, Marion and Martins, Emmanuelle and Lombard, Fabien
and Picheral, Marc and Irisson, Jean-Olivier},
year = 2024,
journal = {SEANOE},
doi = {10.17882/101961},
affiliation = {Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, 06230 Villefranche-sur-Mer, France.
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/flowcamnet")