# GeoVistaBench

**GeoVistaBench is the first benchmark to evaluate agentic models’ general geolocalization ability.**

GeoVistaBench is a collection of real-world photos with rich metadata for evaluating geolocation models. Each sample corresponds to one picture identified by its `uid` and includes both the original high-resolution imagery and a lightweight preview for rapid inspection.

## Dataset Structure

- `id`: unique identifier.
- `raw_image_path`: relative path (within this repo) to the source picture under `raw_image/<uid>/`.
- `preview`: compressed JPEG preview (<=1M pixels) under `preview_image/<uid>/`. This is used by HF Dataset Viewer.
- `metadata`: downstream users can parse it to obtain lat/lng, city names, multi-level location tags, and related information.
- `data_type`: string describing the imagery type.

All samples are stored in a Hugging Face-compatible parquet file.

## Working with GeoBench

1. Clone/download this folder (or pull it via `huggingface_hub`).
2. Load the parquet file using Python:
   ```python
   from datasets import load_dataset

   ds = load_dataset('path/to/this/folder', split='test')
   sample = ds[0]
   ``
   `sample["raw_image_path"]` points to the higher-quality file for inference.

## Related Resources

- GeoVista Technical Report
https://huggingface.co/papers/2511.15705

- GeoVista-Bench (previewable variant):
A companion dataset with resized JPEG previews intended to make image preview easier in the Hugging Face dataset viewer:
https://huggingface.co/datasets/LibraTree/GeoVistaBench
(Same underlying benchmark; different packaging / image formats.)

## Citation
```
@misc{wang2025geovistawebaugmentedagenticvisual,
      title        = {GeoVista: Web-Augmented Agentic Visual Reasoning for Geolocalization},
      author       = {Yikun Wang and Zuyan Liu and Ziyi Wang and Pengfei Liu and Han Hu and Yongming Rao},
      year         = {2025},
      eprint       = {2511.15705},
      archivePrefix= {arXiv},
      primaryClass = {cs.CV},
      url          = {https://arxiv.org/abs/2511.15705},
}
```