datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fish-vista
Dataset Card for Fish-Visual Trait Analysis (Fish-Vista)
Note that the '</Use this dataset>' option will only load the CSV files. To download the entire dataset, including all processed images and segmentation annotations, refer to Instructions for downloading dataset and images.
See Example Code to Use the Segmentation Dataset
Figure 1. A schematic representation of the different tasks in Fish-Vista Dataset.
Instructions for downloading dataset… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/fish-vista.image-as-an-imu-finetuning
Image as an IMU: Real-world Finetuning Dataset
Official real-world finetuning dataset from Image as an IMU: Estimating Camera Motion from a Single Motion-Blurred Image (ICCV 2025 Oral).
[arXiv] [Webpage] [GitHub]
PIXL, University of Oxford
Jerred Chen, Ronald Clark
Dataset Details
This dataset consists of 32 sequences of real-world motion-blurred videos in various indoor scenes, captured using the iPhone 13 camera.
dataset_train_real-world.csv and… See the full description on the dataset page: https://huggingface.co/datasets/jerredchen00/image-as-an-imu-finetuning.Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-DatasetTunisian Proverbs with Image Associations: A Cultural and Linguistic Dataset
Description
This dataset explores the rich oral tradition of Tunisian proverbs mapped into text format, pairing each with contextual explanations, English translations both word-to-word and it's equivalent Target Language dynamic, Automated prompt and AI-generated visual interpretations.
It bridges linguistic, cultural, and visual modalities making it valuable for tasks in cross-cultural NLP, generative… See the full description on the dataset page: https://huggingface.co/datasets/HabibaAbderrahim/Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-Dataset.VLM4Bio
Dataset Card for VLM4Bio
Instructions for downloading the dataset
Install Git LFS
Git clone the VLM4Bio repository to download all metadata and associated files
Run the following commands in a terminal:
git clone https://huggingface.co/datasets/imageomics/VLM4Bio
cd VLM4Bio
Downloading and processing bird images
To download the bird images, run the following command:
bash download_bird_images.sh
This should download the bird images inside datasets/Bird/images… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/VLM4Bio.KABR
Dataset Card for KABR: In-Situ Dataset for Kenyan Animal Behavior Recognition from Drone Videos
Dataset Summary
We present a novel high-quality dataset for animal behavior recognition from drone videos.
The dataset is focused on Kenyan wildlife and contains behaviors of giraffes, plains zebras, and Grevy's zebras.
The dataset consists of more than 10 hours of annotated videos, and it includes eight different classes, encompassing seven types of animal behavior and an… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/KABR.questFish2024
Dataset Card for QUEST Fish 2024
Images collected by teachers during a QUEST workshop. In 2024, the images were of fish collected from bodies of water near Princeton University.
Dataset Details
Dataset Structure
/dataset/
<folder>/
<img_id 1>.png
<img_id 2>.png
...
<img_id n>.png
...
<img_id 1>.png
<img_id 2>.png
...
<img_id n>.png
fieldData2024.csv
Data Instances… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/questFish2024.Heliconius-Collection_Cambridge-Butterfly
Dataset Card for Heliconius Collection (Cambridge Butterfly)
Dataset Description
Dataset Summary
Subset of the collection records from Chris Jiggins' research group at the University of Cambridge, collection covers nearly 20 years of field studies.
This subset contains approximately 36,189 RGB images of 11,962 specimens (29,134 images of 10,086 specimens across all Heliconius). Many records have both images and locality data.
Most images were… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly.BaboonLand
Dataset Card for BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos
Dataset Summary
BaboonLand is an aerial drone video dataset of wild olive baboons (Papio anubis) collected over 21 consecutive days in Laikipia (Mpala Research Centre), Kenya, following three troops during morning and evening movements to and from sleeping sites. The dataset contains UAV footage across diverse environments (e.g., sleeping tree, river… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/BaboonLand.crowdsourced-sea-images-v2crowdsourced-sea-images
Dataset Card for Dataset Name
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More Information Needed]
Demo [optional]: [More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/SEA-AI/crowdsourced-sea-images.text-to-image-prompts
The dataset of the most popular text-to-image prompts.
Dataset Details
Dataset Description
Curated by: kazimir.ai
Funded by [optional]: [More Information Needed]
Shared by [optional]: https://kazimir.ai
License: apache-2.0
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More Information Needed]
Demo [optional]: [More Information Needed]
Uses
Free to use.
Dataset Structure
CSV file… See the full description on the dataset page: https://huggingface.co/datasets/Kazimir-ai/text-to-image-prompts.Whole_Slide_Imageskabr-methodology
Dataset Card for kabr-tools Methodology Dataset
Dataset Details
A curated collection of CSV and XML files describing time-budget data, focal observations, scan samples, and object-detection annotations for African ungulates—including Grevy’s zebras, plains zebras, and giraffes—recorded both from the ground and from drones. This dataset complements the original KABR Mini-Scene Dataset, providing ground-based sampling to correspond with a subset of the published… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/kabr-methodology.char-sim-data
Dataset Card for Character Similarity Dataset
Dataset Details
The Character Similarity Dataset is a collection of textual trait descriptions along with the corresponding ontology based similarity measures between trait description pairs. The distance is estimated using the Phenoscape Knowledgebase as the ontology. The Knowledgebase is built upon a number of OBO ontologies, most importantly the Uberon anatomy ontology.
The Character Similarity Dataset is a collection of… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/char-sim-data.KABR-telemetry
Dataset Card for KABR Telemetry: In-Situ Dataset for Kenyan Animal Behavior Recognition from Drone Videos
Dataset Details
Dataset Description
This dataset contains the drone telemetry data associated with the KABR dataset. The KABR dataset contains annotated video behavior of zebras and giraffes at the Mpala Research Centre. This telemetry dataset contains information about the status drone during the missions, including location and altitude, along with the… See the full description on the dataset page: https://huggingface.co/datasets/imageomics/KABR-telemetry.Product-Search-Images-v0.1fusion-image-to-latex-datasets
Collects and builds the largest dataset to date from online sources, creating a robust and generalizable dataset. This dataset includes approximately 3.4 million image-text pairs, including both handwritten mathematical expressions (200,330 examples) and printed mathematical expressions (3,237,250 examples). Due to the large dataset and the fact that the same mathematical formula can be represented in different LaTeX string formats in an image, it is easy to cause polymorphic ambiguity. To… See the full description on the dataset page: https://huggingface.co/datasets/hoang-quoc-trung/fusion-image-to-latex-datasets.tgk-ai-image-generators-2026
We Tested 10 AI Image Generators on Faces, Text and Ads
Most AI image-generator comparisons reduce the models to a score. We wanted to see the mistakes.
These Guys Know gave ten current models the same three practical briefs in August 2026: a close-up face, exact medical text inside a photographed hospital monitor, and a luxury fragrance advertisement where the person, bottle, label and location needed to look believable together.
We kept the first valid output for every… See the full description on the dataset page: https://huggingface.co/datasets/These-Guys-Know/tgk-ai-image-generators-2026.image-preference-demo
Image dataset for preference aquisition demo
This dataset provides the files used to run the example that we use in this blog post to illustrate how easily
you can set up and run the annotation process to collect a huge preference dataset using Rapidata's API.
The goal is to collect human preferences based on pairwise image matchups.
The dataset contains:
Generated images: A selection of example images generated using Flux.1 and Stable Diffusion. The images are provided in a .zip… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/image-preference-demo.ImageNet_TA_IA
Library: https://github.com/lucasdegeorge/T2I-ImageNet
How far can we go with ImageNet for Text-to-Image generation?
Lucas Degeorge, Arijit Ghosh, Nicolas Dufour, David Picard, Vicky Kalogeiton
This dataset has the captions used during the training of the models from the paper "How far can we go with ImageNet for Text-to-Image generation?"
The core idea is that text-to-image generation models typically rely on vast datasets, prioritizing quantity over quality. The usual… See the full description on the dataset page: https://huggingface.co/datasets/Lucasdegeorge/ImageNet_TA_IA.Image-Gen-or-Image-Editing
Image Gen or Image Editing
This dataset is designed for text classification of prompts provided by users. It determines whether a prompt is intended for image generation or image editing.
txt-image-bias-dataset
Dataset Card: txt-image-bias-dataset
Dataset Summary
The txt-image-bias-dataset is a collection of text prompts categorized based on potential societal biases related to religion, race, and gender. The dataset aims to facilitate research on bias mitigation in text-to-image models by identifying prompts that may lead to biased or stereotypical representations in generated images.
Dataset Structure
The dataset consists of two columns:
prompt: A text description… See the full description on the dataset page: https://huggingface.co/datasets/enkryptai/txt-image-bias-dataset.imagebench
ImageBench — 50 Text-to-Image Models Judged by VLMs on 192 Prompts
Reproducibility dataset for imagebench.ai: the 192-prompt V1.2 benchmark, per-(model, prompt) VLM verdicts, and per-model aggregate scores for 50 text-to-image models.
Live leaderboard + every generated image: https://imagebench.ai
Methodology: https://imagebench.ai/methodology-v1
Reproducibility repo: https://github.com/dh7/image-bench-ai
What's in this dataset
File
Rows
Description… See the full description on the dataset page: https://huggingface.co/datasets/dh7/imagebench.FashionGEN_images_datawikipedia-image-requests
Daily image-request counts for Wikipedia article images
Daily counts of how often each of ~1.19 million Wikipedia article images was requested from
Wikimedia's image servers, attributed to the wiki whose page the request came from, together with
the article each image appears on.
406,263,728 daily observations covering 1,186,150 image files across 534,067 articles in
nine Wikipedias, from 2025-09-01 to 2026-09-05 (370 days).
Every file in the set appears on exactly one… See the full description on the dataset page: https://huggingface.co/datasets/lgelauff/wikipedia-image-requests.japanese-image-classification-evaluation-dataset
recruit-jp/japanese-image-classification-evaluation-dataset
Overview
Developed by: Recruit Co., Ltd.
Dataset type: Image Classification
Language(s): Japanese
LICENSE: CC-BY-4.0
More details are described in our tech blog post.
日本語CLIP学習済みモデルとその評価用データセットの公開
Dataset Details
This dataset is comprised of four image classification tasks related to concepts and things unique to Japan. Specifically, is consists of the following tasks.
jafood101: Image… See the full description on the dataset page: https://huggingface.co/datasets/recruit-jp/japanese-image-classification-evaluation-dataset.ImageHeterogeneity
Replication Data for: Image-based Treatment Effect Heterogeneity
Details: UgandaDataProcessed.csv contains individual-level data from the YOP experiment. In the dataset, geo_long and geo_lat refer to the approximate geo-referenced long/lat of experimental units. The variable, geo_long_lat_key, refers to the image key associated with each location. Experimental outcomes are stored in Yobs. Treatment variable is stored in Wobs. See the tutorial for more information.
UgandaGeoKeyMat.csv… See the full description on the dataset page: https://huggingface.co/datasets/cjerzak/ImageHeterogeneity.Crop-Disease-Image-Eval-Synthetic
Crop, Category, Disease and Pest Test Set
11,057 smallholder-farmer photographs sent to FarmerChat from Ethiopia, India, Kenya and Nigeria, each
labelled with the crop, whether the problem is a disease or a pest, and which one. This is the held-out
test split of a four-head classification benchmark, restricted to the rows whose labels came from an
independent model council rather than from the production vendor.
Why 11,057 and not 16,275
The full held-out split is… See the full description on the dataset page: https://huggingface.co/datasets/DigiGreen/Crop-Disease-Image-Eval-Synthetic.imagenet-12k-metadata
ImageNet-12k Split Metadata
Metadata files defining the splits for ImageNet-12k subset of fall11_whole.tar (2011 ImageNet full release) used in some timm models (see dataset building code in https://github.com/rwightman/imagenet-12k).
ambient-o-clip-iqa-patches-imagenet
Ambient Diffusion Omni (Ambient-o): Training Good Models with Bad Data
Dataset Description
Ambient Diffusion Omni (Ambient-o) is a framework for using low-quality, synthetic, and out-of-distribution images to improve the quality of diffusion models. Unlike traditional approaches that rely on highly curated datasets, Ambient-o extracts valuable signal from all available images during training, including data typically discarded as "low-quality."
This dataset card is for… See the full description on the dataset page: https://huggingface.co/datasets/adrianrm/ambient-o-clip-iqa-patches-imagenet.