TRAIIN VIDEO — UAV & Autonomous Systems Datasets

Every Environment. Every Sensor. Every Frame.

Purpose-built video training data for UAV, drone, and autonomous systems teams. RGB, stereo, thermal, and fisheye video with onboard GPS, accelerometer, and gyroscope logs captured at source on every submission — across 8 real-world environment types worldwide. What academic datasets like VisDrone and EuRoC MAV can't: on-demand, custom-briefed, rights-cleared data with richer sensor metadata for your exact brief.

GPS + IMU on every clipGlobal coverage8 environment typesAPI & batch deliveryVerifiable provenance

8 real-world environment types

No simulator covers every condition your UAV will hit in the field. Our contributors capture across every major environment type, at global scale.

🏙️

Urban & dense city

🌾

Agricultural & open field

🌲

Forest & dense vegetation

🏭

Industrial & infrastructure

🏔️

Mountainous & uneven terrain

🏖️

Coastal & waterfront

🆘

Disaster & search & rescue zones

🛣️

Road, highway & transit

What you get with every dataset

Fully packaged datasets for perception model training, SLAM development, and autonomous navigation — with the documentation enterprise and defence teams require.

Verifiable Provenance

Verifiable Provenance

A tamper-evident record on every asset: who captured it, when, where, on what device, at what GPS coordinate. Audit-ready for legal review, defence procurement, and EU AI Act documentation.

Direct Pipeline Ingestion

Direct Pipeline Ingestion

API or batch delivery structured for perception and navigation training. Drops into PyTorch, TensorFlow, and ROS-based pipelines with minimal integration.

Autonomous Systems Annotations

Autonomous Systems Annotations

Human QA on every asset, with schemas for bounding-box detection, multi-class tracking, semantic segmentation, and optical flow — the annotations that feed UAV perception pipelines.

AI + Human QA Pipeline

AI + Human QA Pipeline

AI pre-screening flags resolution, motion blur, and missing sensor data. Trained human reviewers then validate quality, environmental diversity, and annotation accuracy on every batch.

Defence data

Defence-grade UAV video. Cinematic-quality training data.

For defence, aerospace, and national-security AI teams: sensor-rich UAV and aerial video captured in real operational environments, at a fidelity built for the most demanding models — with the provenance and rights documentation mission-critical programs require.

Operationally realistic capture

Real environments, real conditions, real sensor noise — the field reality defence and autonomous programs deploy into, not a test range or simulator approximation.

Cinematic-grade fidelity

High-resolution, high-dynamic-range, professionally framed footage that meets the fidelity bar of state-of-the-art perception and generative world models — not low-bitrate scraped clips.

Audit-ready provenance

Every clip carries a tamper-evident chain of custody (who, when, where, on what device) built for defence procurement, EU AI Act Article 10, and program audits.

Controlled, rights-cleared sourcing

Consent captured at source, licensing documented per asset, export-aware handling — so sensitive programs train on data with a clean, defensible origin.

Sensor metadata captured at source

The same signals your UAV relies on — GPS, gyroscope, accelerometer — captured natively on contributor devices with every submission. No reconstruction. No estimation.

Core Metadata

Captured at source with every video asset — no post-processing required.

GPS coordinates, geotag & altitude/headingGPS coordinates, geotag & altitude/heading
Date, time & timezoneDate, time & timezone
Resolution & frame rateResolution & frame rate
Frame rate (FPS)Frame rate (FPS)
Scene descriptions & tagsScene descriptions & tags
Rights & provenance infoRights & provenance info

Enriched Sensor Data

Optional annotation layers that deepen your training signal — including the IMU data autonomous systems depend on.

Device make, model & specsDevice make, model & specs
Gyroscope, accelerometer & 6-DOF pose dataGyroscope, accelerometer & 6-DOF pose data
Object, obstacle & scene tagsObject, obstacle & scene tags
Usage permissions & license tierUsage permissions & license tier
Environmental audio flagsEnvironmental audio flags

From brief to production-ready dataset

Define your capture requirements. We activate the right contributors. You receive sensor-annotated, rights-cleared data ready for your pipeline.

01

Submit Your Capture Brief

Define target environments, regions, sensor requirements, annotation schema, and volume. We scope and confirm within 24 hours.

02

Contributor Matching

We activate verified contributors in the right geographies, matched to your environmental and demographic requirements via our AI Reputation Score.

03

Native Capture with Sensor Data

Contributors record RGB, stereo, and thermal video on their own devices with GPS and IMU logs — accelerometer, gyroscope, and altitude captured at source, no post-processing.

04

Dataset Delivery

Receive your dataset via API or batch download with structured metadata, rights documentation, sensor logs, and a QA report — on a delivery SLA confirmed in your scope proposal.

ScreenedValidatedTrustedPriority briefs

Your data quality starts with contributor quality

UAV perception models are only as good as their training data. Pioggia's AI Reputation Score puts only proven contributors on your most demanding briefs — with a full track record that's on-chain, auditable, and immutable.

Every contributor is scored on accuracy, consistency, metadata completeness, and content quality, with higher-reputation contributors prioritized for complex multi-environment and high-precision sensor briefs. Academic datasets like VisDrone and UAVid were captured once, for one research purpose — Pioggia's on-demand model means fresh data for your brief every time, not a static snapshot from someone else's agenda.

AI-powered technical screening (resolution, blur, sensor data completeness)
Human validation for environmental diversity and context accuracy
Behaviour-based reputation ranking, tamper-evident
GPS and IMU log verification against device hardware
Rights and consent verification at the file level

Stop closing the sim-to-real gap manually.

Every UAV team eventually finds that simulation-trained models need real-world fine-tuning. Start with real data and the gap closes in training, not in the field.

Screened contributors are already active worldwide. Submit a brief and we activate the right ones for your geographic, environmental, and sensor requirements, typically within hours.