datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IndustryBench-MIPU
IndustryBench-MIPU: Benchmarking Multi-Image Attribute Value Extraction for Industrial Products
Multi-Image Industrial Product Understanding Benchmark — evaluating MLLMs on structured attribute extraction from real-world industrial product images.
Industrial product specifications are scattered across multiple heterogeneous images — specification tables, nameplates, technical drawings. IndustryBench-MIPU tests whether MLLMs can reliably recover them through four… See the full description on the dataset page: https://huggingface.co/datasets/alibaba-multimodal-industrial-ai/IndustryBench-MIPU.IndustrialDetectionStaticCamerasThe IndustrialDetectionStaticCameras dataset has been collected in order to validate the methodology presented in the paper entitled A few-shot learning methodology for improving safety in industrial scenarios through universal self-supervised visual features and dense optical flow. This dataset is divided into five main folders named videoY, where Y=1,2,3,4,5. Each videoY folder contains the following:
The video of the scene in .mp4 format: videoY.mp4
A folder with the images of each frame… See the full description on the dataset page: https://huggingface.co/datasets/jjldo21/IndustrialDetectionStaticCameras.vidore_v3_industrialViDoRe V3 : Industrial reports
This dataset, Industrial reports, is a corpus of technical documents on military aircrafts (fueling, mechanics...), intended for complex-document understanding tasks. It is one of the 10 corpora comprising the ViDoRe v3 Benchmark.
About ViDoRe v3
ViDoRe V3 is our latest benchmark for RAG evaluation on visually-rich documents from real-world applications. It features 10 datasets with, in total, 26,000 pages and 3099 queries, translated into 6… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_industrial.vidore_v3_industrial_mteb_format
Vidore3IndustrialRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
Retrieve associated pages according to questions.
Task category
t2i
Domains
Academic
Reference
https://huggingface.co/blog/QuentinJG/introducing-vidore-v3
Source datasets:
vidore/vidore_v3_industrial
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("Vidore3IndustrialRetrieval")… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_industrial_mteb_format.industrial_cart_2industrial-semseg-web
Industrial 3D Semantic Segmentation — Web Display Assets
Display assets for the dataset website of a synthetic industrial RGB-D dataset for 3D
semantic segmentation, generated with NVIDIA Isaac Sim. Files in this repository back
the static website and are meant to be fetched directly via resolve URLs; the full
datasets and model checkpoints live in separate repositories.
Quantitative benchmark results are not included here; they will be published together
with the thesis.… See the full description on the dataset page: https://huggingface.co/datasets/min99ian/industrial-semseg-web.X4_SWIR_Industrial_Foreign_Object_Detection_Bedding
Hyperspectral Foreign-Object Detection in Bedding — Full Dataset (VIS + SWIR)
A 6-band VIS+SWIR hyperspectral dataset for industrial foreign-object
detection on a bedding substrate (a tray of wood-shaving / sawdust animal
bedding). Captured with a Cubert Ultris X4 + SWIR rig — 6 spectral bands
at 450 / 550 / 625 nm (VIS) and 1050 / 1200 / 1450 nm (SWIR), 2400 × 4900
pixels per frame. 252 frames (193 train · 59 val), 51 frames carry
pixel-level polygon… See the full description on the dataset page: https://huggingface.co/datasets/cubert-gmbh/X4_SWIR_Industrial_Foreign_Object_Detection_Bedding.industrial-defects-detection
Industrial Defects Detection Dataset
Professional industrial defects detection dataset for AI/ML training.
Sample Dataset (60 images)
This repository contains a free sample of 60 images across 6 categories.
Full Dataset
Package
Images
Resolution
Price
Standard
2,460
512x512
15 EUR
Premium
2,460
2048x2048
Coming soon
Buy Full Dataset on Gumroad: https://betosfyro.gumroad.com/l/mumbyd
Categories
corrosion, crack, dent… See the full description on the dataset page: https://huggingface.co/datasets/xanoutas/industrial-defects-detection.IndustrialTextileDataset
Description
Introduction of new dataset for unsupervised fabric defect detection
This dataset aims to provide a color dataset with real industrial fabric defect gathered in a visiting machine with several industrial cameras.
It has been designed with the same nomenclature as MVTEC AD dataset (https://www.mvtec.com/company/research/datasets/mvtec-ad) for unsupervised anomaly detection.
Type
Total
Train(Good)
Test(Good)
Test(Defective)
Sample
type1cam1386… See the full description on the dataset page: https://huggingface.co/datasets/SimTho/IndustrialTextileDataset.industrial_cartsangyo_no_yume_industrial_dreams
From the Frontier Research Team at Takara.ai we present the "Sangyo no Yume Industrial Dreams" dataset, a collection of AI-generated industrial dreamscapes.
Sangyo no Yume Industrial Dreams
Dataset Details
"Sangyo no Yume Industrial Dreams" is a collection of images generated using SDXL Lightning with specialized prompt engineering techniques. These images balance industrial themes with dreamlike qualities, creating a unique aesthetic that sits at the intersection of… See the full description on the dataset page: https://huggingface.co/datasets/takara-ai/sangyo_no_yume_industrial_dreams.industrial-parts-and-packaging
Industrial Parts & Packaging
Try it before you download. Every item in this dataset is live in
projectsim Lab: orbit every variant at real scale, then grab the
full USD (physics, PBR maps) or a GLB preview per asset.
Jump straight to a class: Gas Cylinders · Pallet Racking.
Procedurally generated, sim-ready 3D industrial infrastructure - warehouse
pallet racking bays and LPG / propane gas cylinders - shipped as OpenUSD
(.usda) with per-zone PBR maps, plus a static… See the full description on the dataset page: https://huggingface.co/datasets/projectsim/industrial-parts-and-packaging.Industrial_testindustrial-technical-archive
🚀 Latest Updates (July, 2026)
Version: v07.2026 (Verified)
Status: Integrated with 1,000,000+ records.
New Files: product-E-26-07-2026.csv & product-V-26-07-2026.csv.
QTE Technologies: Industrial & Scientific Knowledge Base
Wikidata Entity: Q138411149
IPFS CID: bafybeibogxxuhmzfrsuhcfd4qr4tmc4okhmrcwhp3266hq47ccuyjnjxoq
Official Neural Hub: qtetech.github.io
This is the permanent technical archive for QTE Technologies, ensuring long-term accessibility of… See the full description on the dataset page: https://huggingface.co/datasets/QTE-Technologies/industrial-technical-archive.LongTS-Industrial
LongTS-Industrial Benchmark
面向视觉语言模型（VLM）长时序工业故障推理能力的评测基准。将长时间序列的多通道工业监测数据可视化为图像，要求模型通过「看图」完成从整体感知、异常定位、根因分析到运维决策的分层推理。
💻 代码（数据合成 / 基准构建 / 评测）：https://github.com/ctacyk/MERIT
📄 论文：（论文发表后补充）
数据概览
样本数：1716（4 个设备域，143 个场景，序列长度 ∈ {1000, 3000, 5000, 10000}，随机种子 ∈ {42, 123, 789}）
设备域：磨煤机 coal_mill（576）、水泵 pump（372）、变压器 transformer（372）、风电 wind_turbine（396）
生成方式：全部由 TimeBlender 物理建模合成（热惯性 + 通道耦合 + 根因传播的故障注入），并以真实工业数据统计特征标定，非真实采集数据。
任务分层（L1–L4）… See the full description on the dataset page: https://huggingface.co/datasets/ANTICH/LongTS-Industrial.IndustrialLateralLoadsThe IndustrialLateralLoads dataset is designed for object detection and instance segmentation tasks in industrial environments. It contains images of palletized loads with their corresponding annotations. The dataset is available in two formats:
Hugging Face dataset (Parquet): Ready-to-use format with images, masks, and metadata.
Raw files: Original folders accessible in the repository files.
Hugging Face dataset features:
When loaded using the datasets library, each sample… See the full description on the dataset page: https://huggingface.co/datasets/jjldo21/IndustrialLateralLoads.industrial-rebar-metric-depth
Industrial Rebar Metric Depth
Evaluation data from:
Benchmarking Metric Depth for Construction Perception: Industrial Rebar Scenes with Exact Synthetic Ground TruthSalman Hajizada, Diram Tabaa, Gianni A. Di CaroIEEE IROS 2026 Workshop on the Future of Construction (FoC)
Three synthetic rebar scenes rendered in Blender 4.5 with exact optical-axis depth and structure masks, and the physical ZED sequence of a 3D-printed lattice. These are the sequences behind Table I and Table II… See the full description on the dataset page: https://huggingface.co/datasets/sal0-h/industrial-rebar-metric-depth.synthetic-industrial-defects-teaser
Synthetic Industrial Defects — Teaser
Dataset Description
1000 synthetic images of industrial metal surfaces with 5 defect types:
scratch, dent, crack, corrosion, discoloration
Format
Images: PNG (1024x768)
Annotations: YOLO format (.txt)
Classes: 5
Usage
from datasets import load_dataset
ds = load_dataset("xanoutas/synthetic-industrial-defects-teaser")
Full Dataset
Complete dataset (5000+ images) available at:… See the full description on the dataset page: https://huggingface.co/datasets/xanoutas/synthetic-industrial-defects-teaser.Multi_View_Industrial_part_Dataset
Dataset Card for Dataset Name
This dataset contains 7 industrial parts taken from a 360-degree all-around view with one axis of rotation.
It contains a train set of all-around images and test sets with ground truth anomaly masks.
Paper: 3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection
BibTeX entry and citation info
@ARTICLE{11424398,
author={Ito, Kenta and Ueda, Shiori and Mori, Shohei and Sugano, Junichi and Adachi, Hideyuki and Saito, Hideo}… See the full description on the dataset page: https://huggingface.co/datasets/kentaito321/Multi_View_Industrial_part_Dataset.neomme-eval-vidore-v3-industrial
NeoMME Evaluation Sample — ViDoRe v3 Industrial
A 760-page, 75-query evaluation sample drawn from
vidore/vidore_v3_industrial
(revision e26c864), built for benchmarking
NeoMME-260M-Retriever
and other visual document retrieval models.
Contents
Split
Items
Notes
data/pages/
760 PNG images
Scanned USAF technical manual pages (1000x1600 RGB)
data/corpus.json
760 rows
corpus_id, doc_id, page_number_in_doc
data/queries.jsonl
75 queries
Natural language… See the full description on the dataset page: https://huggingface.co/datasets/b4ph/neomme-eval-vidore-v3-industrial.africa-synth-mental-health-industrial-air-pollution-health-all
Industrial Air Pollution & Community Health (SSA) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-mental-health-industrial-air-pollution-health-all.Industrialroboticsindustrial-defect-dataset
Synthetic Industrial Material Defect Dataset (10k)
Dataset Summary
This dataset contains 5,000 highly detailed, synthetically generated images of various industrial materials exhibiting different types of surface defects. It is designed to be used for training machine learning models in computer vision, specifically for quality control, manufacturing defect detection, and surface anomaly recognition.
All images were generated using Stable Diffusion XL (SDXL) to… See the full description on the dataset page: https://huggingface.co/datasets/himanshu1257/industrial-defect-dataset.tb4_industrial_vlaThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "turtlebot4",
"total_episodes": 92,
"total_frames": 44593,
"total_tasks": 92,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 5,
"splits": {
"train": "0:92"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": null… See the full description on the dataset page: https://huggingface.co/datasets/DavidStepc/tb4_industrial_vla.DefectLens-Industrial-Datasetvision_based_industrial_inspection_datasetsXMRec_metadata_fr_Industrial_and_Scientific
Description
Cleaned version of the Industrial and Scientific subset (metadata folder) of XMRec dataset.In particular, we have made the images available as PILs.
Possible use cases are :
text classification, using the categories column as a label
product recommendation using the related column
hybrid text/image search (cf. this Jina.ai blog post)
Original paper citation
@inproceedings{bonab2021crossmarket,
author = {Bonab, Hamed and Aliannejadi, Mohammad and… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/XMRec_metadata_fr_Industrial_and_Scientific.vidore_v3_industrial_english_instructionexperimento3-industrial-text-detection
Experimento-3 - Industrial Machinery Text Detection Dataset
Dataset Description
This dataset contains 4,237 images of industrial machinery nameplates with detailed text field annotations for OCR and information extraction tasks. The dataset focuses on extracting key information from equipment nameplates including manufacturer, model, serial numbers, and dates.
Dataset Summary
Task: Industrial text detection and OCR
Domain: Industrial machinery and equipment… See the full description on the dataset page: https://huggingface.co/datasets/kahua-ml/experimento3-industrial-text-detection.industrial-assembly-taskboard