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--- |
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annotations_creators: |
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- expert-generated |
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language: |
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- en |
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license: cc-by-4.0 |
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pretty_name: IFCB Plankton Labeled (Cluster-Sorted) |
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task_categories: |
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- image-classification |
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tags: |
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- plankton |
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- microscopy |
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- ifcb |
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- clustering |
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- manual-sorting |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': Akashiwo |
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'1': Asterionellopsis |
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'2': Centric |
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'3': Ceratium |
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'4': Chaetoceros |
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'5': Ciliates |
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'6': Detonula |
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'7': Diatom_aggregate |
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'8': Dictyocha |
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'9': Dinophysis |
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'10': Ditylum |
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'11': Eucampia |
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'12': Guinardia |
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'13': Gymnodinium |
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'14': Gyrodinium |
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'15': Heterocapsa |
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'16': Lauderia_Hemiaulus |
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'17': Leptocylindrus |
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'18': NanoPlankton |
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'19': Pennate |
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'20': Phaeocystis |
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'21': Prorocentrum |
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'22': Protoperidinium |
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'23': Psuedo-nitzschia |
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'24': Rhizosolenia_Proboscia |
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'25': Skeletonema |
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'26': Stephanopyxis |
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'27': Thalassionema |
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'28': Thalassiosira |
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'29': Tintinnid |
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'30': Unknown_detritus |
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'31': Unknown_full_image |
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'32': Unknown_phyto |
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- name: group |
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dtype: string |
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- name: filename |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 286871203.36 |
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num_examples: 7895 |
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download_size: 291443502 |
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dataset_size: 286871203.36 |
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--- |
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# IFCB Plankton Labeled (Cluster-Sorted) |
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This dataset contains labeled images of phytoplankton collected with the **Planktivore Imaging System**. Images were preprocessed with a zero-padding and resized to the standard size used for `ViT_b_16` |
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The dataset was originally constructed by clustering unlabeled ROI images using deep features from a ViT model. |
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Clusters were then **saved locally** and **manually curated** into taxonomic labels and higher-order groups. |
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## Dataset Summary |
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- **Modality**: Images (PNG) |
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- **Source**: Planktivore ROI captures |
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- **Curation process**: |
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1. Extracted deep features with a ViT backbone. |
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2. Applied clustering (UMAP + HDBSCAN) to group morphologically similar images. |
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3. Exported clusters to local folders. |
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4. **Manually reviewed and sorted** each cluster into taxonomic categories (`label`) and broader groups (`group`). |
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### Columns |
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- `image`: The plankton ROI image. |
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- `label`: Fine-grained label (taxon). |
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- `group`: Higher-order grouping (e.g. diatoms, dinoflagellates, ciliates). |
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### Example |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("patcdaniel/synchro-April2025-cluster-labeled-highMag") |
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sample = ds["train"][0] |
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sample["image"].show() |
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print("Label:", ds["train"].features["label"].int2str(sample["label"])) |
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print("Group:", ds["train"].features["group"].int2str(sample["group"])) |
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``` |
