---
license: cc
task_categories:
- zero-shot-classification
language:
- en
tags:
- biodiverstiy
- cryptic species
- fine-grained image recognition
- vision-language
- multimodal dataset
pretty_name: A Large Multimodal Dataset for Visually Confusing Biodiversity
size_categories:
- 100M<n<1B
---

# CrypticBio: A Large Multimodal Dataset for Visually Confusing Biodiversity

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## Description

[CrypticBio](https://georgianagmanolache.github.io/crypticbio/) comprises metadata including species scientific and multicultural vernacular terminology, image URL, taxonomic hierarchy, spatiotemporal context, and cryptic species group. Cryptic species are groups of two or more taxa that are nearly indistinguishable based on visual characteristics alone. 

## CrypticBio Dataset
We present CrypticBio, the largest publicly available multimodal dataset of visually confusing species groups, specifically curated to support the development of AI models in the context of biodiversity identification applications.
Curated from real-world trends in species misidentification among community annotators of iNaturalist, CrypticBio contains 67K cryptic species groups spanning 52K species, represented in 166 million images. 

## New Benchmark Datasets
We created four new benchmark datasets for fine-grained image classification of cryptic species. 

### CrypticBio-Commom
We curate a common species from Arachnida, Aves, Insecta, Plantae, Fungi, Mollusca, and Reptilia and associated cryptic group, spanning n=158 species. We randomly select 100 samples from each species in a cryptic group where there are more than 150 observation per species.

### CrypticBio-CommonUnseen
To assess zero-shot performance on common species from CrypticBio-Common not encountered during training of state-of-the-art models, we specifically curate a subset spanning data from 01-09-2024 to 01-04-2025.  We randomly select 100 samples from each species in a cryptic group where there are more than 150 observation per species, spanning n=133 species.

### CrypticBio-Endagered
We propose a cryptic species subset of endangered species according to global IUCN Red List. We randomly select 30 samples from Arachnida, Aves, Insecta, Plantae, Fungi, Mollusca, and Reptilia and associated cryptic groups spanning n=37 species, filtering out taxa where there are less than 150 observation.

### CrypticBio-Invasive
We also propose a cryptic species subset of invasive alien species (IAS) according to global the Global Invasive Species Database (GISD). IAS are a significant concern for biodiversity as their records appear to be exponentially rising across the Earth. We randomly select 100 samples from each invasive species cryptic group spanning n=72 species, filtering out taxa where there are less than 150 observation. 

## Dataset Information

### Directory
```plaintext
main/
├── CrypticBio/
│   ├── part_0.csv
│   ├── part_0.parquet
│   ├── part_1.parquet
│   ├── .
│   ├── .
│   ├── .
│   └── part_626.parquet
├── CrypticBio-benchmarks/
│   ├── CrypticBio-Common.csv
│   ├── CrypticBio-CommonUnseen.csv
│   ├── CrypticBio-Endangered.csv
│   └── CrypticBio-Invasive.csv
├──README.md
└──.gitattributes
```

The data and the code are publicly available at [georgianagmanolache.github.io/crypticbio](https://georgianagmanolache.github.io/crypticbio/)