datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
waterborne-coated-wood-defects
Waterborne Coated Wood Surface Defects
Mirror of a public image dataset of surface defects of waterborne paint sprayed on wood
products. Staged as a proxy/pretraining dataset for CoRe's Situational Control paint-inspection
work (core-lab/situational-control) — painted/coated surface captured on a real production
conveyor, though substrate is wood not metal.
Source
Paper: Nature Scientific Data, https://www.nature.com/articles/s41597-025-06443-1
Data: Zenodo… See the full description on the dataset page: https://huggingface.co/datasets/imaadd05/waterborne-coated-wood-defects.watercolour-reference-pool
Watercolour reference pool
The reference paintings that define the reward in the watercolour RL environment: an
agent writes a p5.brush sketch, the sketch is
rendered, and a vision judge compares the render against paintings sampled from this pool.
What the pool contains is the reward function. Replace it and you have changed what
the environment rewards, without touching a line of code.
178 paintings in two tiers, each with the JavaScript source that produced it.
tier… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/watercolour-reference-pool.watercolour-rollouts-judge-led
Watercolour rollouts, judge-led run
Browse these paintings in the gallery Space, by step and by reward, with the sketch that made each one.
Every rollout from a GRPO run that taught Qwen/Qwen3.5-35B-A3B to paint watercolours by
writing p5.brush sketches. 861 paintings, the
sketch that produced each one, and the reward it earned, indexed by training step. This
is the run with the original reward mix from the write-up, where the pairwise judge and
its hand-rated pool carry most… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/watercolour-rollouts-judge-led.watercolour-rollouts-hps-only
Watercolour rollouts, HPS-only run
Browse these paintings in the gallery Space, by step and by reward, with the sketch that made each one.
Every rollout from a GRPO run that taught Qwen/Qwen3.5-35B-A3B to paint watercolours by
writing p5.brush sketches. 470 paintings, the
sketch that produced each one, and the reward it earned, indexed by training step.
The point of the dataset is that it holds the whole run, not the good bits. Step 0 and
step 59 are both here, with the… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/watercolour-rollouts-hps-only.amfitrite-inland-waters-hab-sentinel2
Dataset Card for Amfitrite-Inland-Waters-HAB-Sentinel2
This dataset contains multispectral Sentinel-2 satellite imagery tiles focused on inland water bodies, classified by the severity of Harmful Algal Blooms (HABs).
It is designed to train Deep Learning models (like CNNs) for environmental monitoring.
Dataset Details
Dataset Description
Amfitrite-Inland-Waters-HAB-Sentinel2 is a specialized dataset designed for the detection and classification of… See the full description on the dataset page: https://huggingface.co/datasets/kostaspic/amfitrite-inland-waters-hab-sentinel2.waterbirds
Dataset Card for Waterbirds
The Waterbirds dataset is constructed by cropping out birds from photos in the Caltech-UCSD Birds-200-2011 (CUB) dataset (Wah et al., 2011) and transferring them onto backgrounds from the Places dataset (Zhou et al., 2017).
The original instructions and data from which this dataset and its card have been created can be found here.
Dataset Details
Dataset Description
The official train-test split of the CUB dataset is used, randomly… See the full description on the dataset page: https://huggingface.co/datasets/grodino/waterbirds.watercolour-rollouts-hps-led
Watercolour rollouts, hps-led run
Browse these paintings in the gallery Space, by step and by reward, with the sketch that made each one.
Every rollout from a GRPO run that taught Qwen/Qwen3.5-35B-A3B to paint watercolours by
writing p5.brush sketches. 872 paintings, the
sketch that produced each one, and the reward it earned, indexed by training step. This
is the middle point of the project's three reward mixes: the generic preference model
holds most of the weight, the… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/watercolour-rollouts-hps-led.water-hyacinth-flowers-floating-pond
Water Hyacinth Flowers — Khurushkul Pond, Bangladesh
150 ground-level photographs of water hyacinth (Eichhornia crassipes) blooming in a freshwater pond near Khurushkul, Cox's Bazar, Bangladesh. All frames were captured in a single session on 9 August 2026 (16:31–16:45 local time) during the monsoon season.
This is a follow-up survey of the same pond documented in the June 2026 water lily / water hyacinth dataset by the same photographer.
Contents
150 JPG images… See the full description on the dataset page: https://huggingface.co/datasets/golamrob/water-hyacinth-flowers-floating-pond.waterbirds
Waterbirds (OCCAM layout)
This repository hosts the Waterbirds image files used in the
OCCAM codebase (arXiv),
laid out for experiments on robust classification evaluation.
Original data and credit
The images come from the Waterbirds benchmark introduced with the group
distributionally robust optimization in:
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang,
Distributionally Robust Neural Networks for Group Shifts: On the Importance of… See the full description on the dataset page: https://huggingface.co/datasets/arubique/waterbirds.Watermark-or-Not-20K
Watermark-or-Not-20K Dataset
Overview
The Watermark-or-Not-20K dataset consists of 20,000 images annotated with binary labels indicating the presence or absence of a watermark. It is designed to support training and evaluation of models focused on watermark detection, which is useful for content filtering, copyright protection, and image moderation tasks.
Dataset Structure
Split: train
Number of samples: 20,000
Label Type: Categorical (2 classes)
Image… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Watermark-or-Not-20K.khurushkul-pond-water-lily-sample
Pink Water Lily & Water Hyacinth — Khurushkul Pond, Bangladesh
100 GPS-tagged freshwater wetland images from a single pond survey in Khurushkul, Cox's Bazar, Bangladesh. By Golam Rob — www.golamrob.com
✅ Free to use, including commercially — just credit "Golam Rob (golamrob.com)". Licensed CC BY 4.0. Use it, train on it, remix it, share it. All I ask is attribution.
📸 These 100 images are a small taste of a 200,000+ image personal library of coastal, tidal, and freshwater… See the full description on the dataset page: https://huggingface.co/datasets/golamrob/khurushkul-pond-water-lily-sample.amfitrite-open-waters-hab-sentinel2
Dataset Card for Amfitrite-Open-Waters-HAB-Sentinel2
This dataset contains multispectral Sentinel-2 satellite imagery tiles focused on open water and coastal marine environments, classified by the potential presence of Harmful Algal Blooms (HABs).
It is designed to train Machine or Deep Learning models (like CNNs) for large-scale environmental monitoring and ocean anomaly detection.
Dataset Details
Dataset Description
Amfitrite-Open-Waters-HAB-Sentinel2 is a… See the full description on the dataset page: https://huggingface.co/datasets/kostaspic/amfitrite-open-waters-hab-sentinel2.WaterHyacinth_variety_classification
WaterHyacinth Variety Classification
A dataset for variety classification of Water Hyacinth species. The dataset contains raw and augmented versions.The raw dataset contains 1,790 images.Images per class:
Common Duckweeds (Lemna minor): 390
Common Water Hyacinth (Eichornia crassipes): 470
Heartleaf False Pickerelweed (Monochoria korsakowii): 450
Water Lettuce (Pistia stratiotes): 480
The augmented dataset contains 4,050 images.Images per class:
Common Duckweeds (Lemna minor):… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/WaterHyacinth_variety_classification.places-water-binary
Places — Water or No Water
34 original photographs labelled by whether a body of water is visible, resized to
224x224. Homework 1.
Property
Value
Splits
train (391), validation (5), test (6)
Resolution
224x224 RGB
Target
label — 1 water, 0 no_water
Balance (all originals)
17 water / 17 no_water
Purpose
Binary image classification: is there a body of water in this scene?
Composition
Column
Type
Description
image
image… See the full description on the dataset page: https://huggingface.co/datasets/ssg1/places-water-binary.watermelon_disease_classification
Watermelon Disease Classification
A dataset for disease classification of Watermelon. The dataset contains raw and augmented versions.The raw dataset contains 1,155 images.Images per class:
Anthracnose: 155
Downy_Mildew: 380
Healthy: 205
Mosaic_Virus: 415
The augmented dataset contains 5,775 images.Images per class:
Anthracnose: 775
Downy_Mildew: 1,900
Healthy: 1,025
Mosaic_Virus: 2,075
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/watermelon_disease_classification.scenery_watermarksDataset for watermark classification (no_watermark/watermark)~22k images, 512x512, manually annotatedadditional info - https://github.com/qwertyforce/scenery_watermarks
waterbirds
Dataset Card for Waterbirds
The Waterbirds dataset is constructed by cropping out birds from photos in the Caltech-UCSD Birds-200-2011 (CUB) dataset (Wah et al., 2011) and transferring them onto backgrounds from the Places dataset (Zhou et al., 2017).
The original instructions and data from which this dataset and its card have been created can be found here.
Dataset Details
Dataset Description
The official train-test split of the CUB dataset is used, randomly… See the full description on the dataset page: https://huggingface.co/datasets/salman53/waterbirds.water_glassbottle_aesthetics_rated
Dataset Card for Dataset Name
This dataset holds 121 images of glass bottles for drinking water. The aesthetics were rated by five participants from Germany across different demographics.