Datasets:
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pretty_name: HighBuild-1M
license: other
language:
- en
task_categories:
- image-segmentation
- object-detection
tags:
- remote-sensing
- geospatial
- building-height
- aerial-imagery
- overhead-imagery
- earth-observation
- single-view-height-estimation
- building-height-estimation
- spatial-generalization
- building-segmentation
- coco
- tiff
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/webdataset/train/*.tar
- split: validation
path: data/webdataset/validation/*.tar
- split: test
path: data/webdataset/test/*.tar
---
# HighBuild-1M
HighBuild-1M is a multi-continental high-resolution benchmark dataset for single-view building height estimation from overhead imagery. Each sample contains a 1024 x 1024 RGB overhead image, a spatially aligned float32 building-height mask, and COCO-style building instance annotations.
## Dataset Statistics
| Version | 1024 x 1024 tiles | Building instances | City groups | Countries/regions | Continents |
|---|---:|---:|---:|---:|---:|
| HighBuild-1M full benchmark | 70,266 | 6,050,823 | 26 | 12 | 6 |
The full benchmark covers 6 continents, 12 countries or regions, and 26 city groups, with 70,266 paired 1024 x 1024 tiles and 6,050,823 building instances.
## Reviewer Small Sample
A small reviewer-inspection subset is available at:
https://huggingface.co/datasets/feifei140729/small-sample
The small sample follows the same triplet structure as the full dataset, including RGB images, float32 TIFF building-height masks, and COCO-style JSON annotations. It is intended for quick inspection of data quality, file organization, spatial alignment, and annotation format.
## Dataset Viewer Note
The Hugging Face Dataset Viewer may fail to render this dataset because HighBuild-1M is distributed as large WebDataset TAR shards containing JPEG images, float32 TIFF masks, and COCO-style JSON annotations rather than a single tabular dataset. This does not affect downloading, streaming, or inspecting the dataset. Please use the WebDataset loading instructions and manifest files below.
## Tasks
HighBuild-1M supports the following tasks:
1. **Single-view building height estimation**
Input: one 1024 x 1024 RGB overhead image tile.
Output: a spatially aligned float32 building-height map.
2. **Building-wise height evaluation**
Predicted height maps can be aggregated within COCO-style building polygons to compute building-level MAE/RMSE.
3. **Building segmentation and instance-level building understanding**
COCO-style building polygons and bounding boxes can be used for semantic building segmentation, instance-level building analysis, and joint height-segmentation modelling.
4. **Spatial generalization benchmarking**
The benchmark supports same-city, cross-city within-country, and cross-country evaluation protocols.
## WebDataset and Compression
For the Hugging Face hosted release, the recommended distribution format is WebDataset TAR shards.
The hosted WebDataset release uses split-aware shards under:
```text
data/webdataset/train/*.tar
data/webdataset/validation/*.tar
data/webdataset/test/*.tar |