---
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