datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
BioTrove
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity
Description
See the BioTrove-Train dataset card on HuggingFace to access the samller BioTrove-Train dataset (40M)
BioTrove comprises well-processed metadata with full taxa information and URLs pointing to image files. The metadata can be used to filter specific categories, visualize data distribution, and manage imbalance effectively. We provide a collection of… See the full description on the dataset page: https://huggingface.co/datasets/BGLab/BioTrove.BioTrove-Train
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity
Description
See the BioTrove dataset card on HuggingFace to access the main BioTrove dataset (161.9M)
BioTrove comprises well-processed metadata with full taxa information and URLs pointing to image files. The metadata can be used to filter specific categories, visualize data distribution, and manage imbalance effectively. We provide a collection of software… See the full description on the dataset page: https://huggingface.co/datasets/BGLab/BioTrove-Train.Biomedica2025EvalSet
Biomedica 2025 Eval Set
Unified test snapshot of the BioMedica 2025 vision–language evaluation
suites used in AMInZeroShotOpenEvalAllTasks. Every row is a single image
with closed-ended options, the gold answer, and provenance fields that
point back to the original dataset.
Images are stored as original JPEG/PNG bytes (or JPEG-encoded arrays) inside
parquet so the Hugging Face dataset viewer is enabled
(~1959 MB download, 89941 examples).
Suites
config… See the full description on the dataset page: https://huggingface.co/datasets/Alejandro98/Biomedica2025EvalSet.bioscan-traits
Dataset Card for BIOSCAN-Traits
Dataset Details
Dataset Description
BIOSCAN-Traits is a trait-level annotation dataset for fine-grained insect imagery. Derived from BIOSCAN-5M, it provides morphology-centric natural language trait descriptions automatically generated by a two-stage pipeline: (1) a Sparse Autoencoder (SAE) trained on DINOv2 visual features identifies species-level salient visual parts (wings, legs, antennae, etc.), and (2) a Multimodal LLM… See the full description on the dataset page: https://huggingface.co/datasets/osunlp/bioscan-traits.NIH-CXR14-BiomedCLIP-Features
NIH-CXR14-BiomedCLIP-Features Dataset
This dataset is derived from the NIH Chest X-ray Dataset (NIH-CXR14) and processed using the BiomedCLIP-PubMedBERT_256-vit_base_patch16_224 model from Microsoft. It contains image and text features extracted from chest X-ray images and their corresponding textual findings.
Dataset Description
The original NIH-CXR14 dataset comprises 112,120 chest X-ray images with disease labels from 30,805 unique patients. This processed dataset… See the full description on the dataset page: https://huggingface.co/datasets/Yasintuncer/NIH-CXR14-BiomedCLIP-Features.schulz_bank_biotopes
Summary
Image classification dataset with biotope labels extracted from Meyer et al., 2022.
Images were extracted from six remotely operated vehicle (ROV) dives during two SponGES cruises conducted in the summers of 2017 and 2018. The ROV dives were performed by Ægir 6000 and the cruises were conducted on the RV G.O. Sars. The ROV dives traversed across various regions on the seamount, from the base of the seamount at 2700 m depth to the summit at 580 m depth. 600 images were… See the full description on the dataset page: https://huggingface.co/datasets/CGame1/schulz_bank_biotopes.biometric
DepositPhotos Biometric & Human Features Dataset (Sample)
Overview
This dataset is a curated sample of high-resolution Biometric, Facial, and Human Feature images sourced from the DepositPhotos library. This subset is designed for training, testing, and evaluating Computer Vision models for facial recognition, identity verification, emotional analysis, and healthcare AI applications.
This sample demonstrates the exact quality, diversity, and structural consistency… See the full description on the dataset page: https://huggingface.co/datasets/Depositphotos/biometric.