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.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.WaterBench
WaterBench: Evaluating Geospatial Foundation Models for Coastal and Marine Tasks
Overview
WaterBench is a benchmark and evaluation protocol for assessing GFMs on high-resolution (10m) radar and optical satellite imagery (Sentinel-1, Sentinel-2) across two downstream task families: image-level regression and classification (e.g., water quality, bathymetry, oil-slick detection) and pixel-level segmentation (e.g., mangroves, seagrass). We also include 300m Sentinel-3… See the full description on the dataset page: https://huggingface.co/datasets/ayushprd/WaterBench.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.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.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.aquaveritas-water-stress
AquaVeritas Water Stress Dataset
Classification labels for 1,656 Sentinel-2 satellite observations across 20 global freshwater and saline sites, used to fine-tune LFM2.5-VL-450M for on-board satellite freshwater monitoring.
Built for the Liquid AI x DPhi Space Hackathon: AI in Space (Hack #05).
Dataset Summary
Each observation covers one of 20 monitored water bodies and includes structured classification labels for two zones:
Core zone (15km x 15km centred on the… See the full description on the dataset page: https://huggingface.co/datasets/Arty1001/aquaveritas-water-stress.Water-Heater-Shape-Classification-Dataset
Water Heater Shape Classification Dataset
The retail e-commerce industry is rapidly evolving, facing challenges in accurately categorizing diverse product shapes to enhance customer experience. Existing solutions often struggle with inconsistent labeling and insufficient datasets, leading to poor classification performance. This dataset aims to tackle the specific need for robust image classification of water heater shapes, addressing the gap in reliable training data for machine… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Water-Heater-Shape-Classification-Dataset.