usmanhf/INRIA-Aerial-Image-Labeling
Inria Aerial Image Labeling Dataset Description The Inria Aerial Image Labeling Dataset is a building semantic segmentation dataset proposed in "Can semantic labeling methods generalize to any city? the inria aerial image labeling benchmark," Maggiori et al.. It consists of 360 high-resolution (0.3m) RGB images, each with a size of 5000x5000 pixels. These images are extracted from various internat
Engineering Snapshot
Use cases & tasks 4
- Best suited for
-
- perception AI researchers
- remote sensing engineers
- Primary tasks
-
- training building segmentation models
- benchmarking cross-city segmentation generalization
Stack & ecosystem
- Resource type
- Dataset
- Ecosystem
- perception_ai · remote-sensing · earth-observation · geospatial · satellite-imagery · scene-segmentation
License & compliance
- License
-
unknown(Inferred)
Lifecycle & freshness Show
- Maintenance
- Active
- Latest version
- Not recorded
- Last activity
- 2026-07-25
- Last checked
- 2026-08-13
- Verification
- Official confirmed
What It Solves
Provide a benchmark for building semantic segmentation in high-resolution aerial RGB imagery and test cross-city generalization of labeling methods.
Primary use cases
- training building segmentation models
- benchmarking cross-city segmentation generalization
Secondary use cases
- urban mapping
- geospatial scene parsing
When to Use
Consider when
- require 0.3m resolution 5000x5000 tiles
- focus on building class labels
Verify before adopting
- license is unknown/inferred; confirm before use
- exact capture locations not fully detailed in supplied excerpt
Start Here
Adoption Checklist
- Needs verification license is unknown/inferred; confirm before use
- Needs verification exact capture locations not fully detailed in supplied excerpt
Each check stays "needs verification" until an official source confirms it; unconfirmed items are never marked verified.
Known Limitations & Unknowns
Known limitations
- license unknown
- only building labeling per summary
Not publicly verified
- exact license
- full city list
- annotation format
Alternatives & Related Tools
Alternatives
- uavid — Alternative to
Related tools
- mmsegmentation — compatible with
How is it used?
Start from the recorded entry points below, then validate against the technical checklist.
- Official site https://huggingface.co/datasets/usmanhf/INRIA-Aerial-Image-Labeling
- Documentation https://huggingface.co/datasets/usmanhf/INRIA-Aerial-Image-Labeling
Technical checklist
- OK License identified Recorded: unknown
- OK Maintenance signal Active
- OK Verification status Official confirmed
- OK Source evidence attached 1 source record(s)
- NEEDS REVIEW Latest version recorded Not recorded
Official Links
Metadata & Governance
| License | unknown — Inferred |
|---|---|
| Commercial model | Unknown |
| Maintenance status | Active |
| Verification status | Official confirmed — Confirmed via the official repository API responses in SourceRefs below. |
| Latest version | Not recorded |
| Latest release | Not recorded |
| Last activity | 2026-07-25 |
| Last checked | 2026-08-13 |
| First seen | Not recorded |
Dataset facts
| Task | image-segmentation |
|---|---|
| Modality | image, geospatial |
| License (dataset card) | unknown |
| Size category | n<1K |
| Downloads | 975 |
| arXiv | 1608.05167 |
Facts above come from the official dataset card only; unconfirmed fields stay unknown.
Related Resources & Dependencies
- uavid — alternative to (verified)
- mmsegmentation — compatible with (verified)
Recent Activity
New resource: usmanhf/INRIA-Aerial-Image-Labeling
New repository resource added by the sprint promote pipeline.
Related Knowledge
Collections
- Aerial Mapping and Survey Stack — An open-source stack for aerial mapping work from imagery and datasets through photogrammetry processing.
- Aerial Perception Models and Datasets — Source-backed aerial dataset and model repositories for detection and tracking research and prototyping.
- Edge AI Perception Starter — A starting stack for prototyping aerial perception models before edge deployment work.
- Visual Perception Models and Data — Indexed model and dataset repositories for aerial visual perception research and prototyping.