README.md

---
license: other
license_name: see-source-datasets
task_categories:
- image-segmentation
tags:
- pathology
- histopathology
- medical-imaging
- semantic-segmentation
- whole-slide-imaging
size_categories:
- 100K<n<1M
---

# VISTA-PATH training data (release subset)

Processed image/mask pairs used to train **VISTA-PATH**, an interactive foundation model for
histopathology image segmentation.

- 📎 Paper: <https://www.arxiv.org/abs/2601.16451>
- 💻 Code: <https://github.com/zhihuanglab/VISTA-PATH>
- 🤗 Model: <https://huggingface.co/zhihuanglab/VISTA-PATH>

This repository holds the **train split of 9 of the datasets** used in the paper, already tiled
into patches and paired with label masks. It is a subset of the full training corpus used in the paper.

## Contents

| Dataset | Image–mask pairs | Shards (images + masks) | Size |
| --- | --- | --- | --- |
| AGGC | 90,978 | 68 + 1 | 135.9 GiB |
| BRCA | 7,959 | 8 + 1 | 14.9 GiB |
| CoCaHis | 302 | 1 + 1 | 0.4 GiB |
| DRYAD | 3,343 | 3 + 1 | 5.3 GiB |
| DigestPath | 4,949 | 3 + 1 | 5.9 GiB |
| Histo-Seg | 1,869 | 1 + 1 | 2.0 GiB |
| TIGER_wsibulk | 47,669 | 35 + 1 | 69.1 GiB |
| TIGER_wsirois | 1,225 | 2 + 1 | 2.5 GiB |
| WSSS4LUAD | 540 | 1 + 1 | 1.1 GiB |

**158,834 image–mask pairs, 131 shards, 237.2 GiB in total.** Every image has exactly one mask.

## Layout

The data is stored as plain tar shards of roughly 2 GB rather than as loose files — half a million
individual PNGs run into the Hub's request limits — so the repository looks like this:

```
<dataset>/images_train_000.tar
<dataset>/images_train_001.tar
...
<dataset>/masks_train_000.tar
manifest.json
```

`manifest.json` lists every shard with its file count and byte size.

## Usage

Download one dataset, or drop `allow_patterns` to fetch everything:

```python
from huggingface_hub import snapshot_download

snapshot_download("zhihuanglab/VISTA-PATH_data", repo_type="dataset",
                  local_dir="./data", allow_patterns="WSSS4LUAD/*")
```

Each shard carries its own `<dataset>/` prefix inside the archive, so extract from the directory the
shards were downloaded into:

```bash
cd data
for f in WSSS4LUAD/*.tar; do tar -xf "$f"; done
```

That restores the original tree:

```
data/WSSS4LUAD/images/train/000-0-0.png
data/WSSS4LUAD/masks/train/000-0-0.png
```

## Format

- **Images** — RGB PNG patches extracted from the source whole-slide images or ROIs.
- **Masks** — single-channel `uint8` PNG label maps, the same height and width as the image they
  belong to and carrying the same filename. Pixel values are class indices, not colours; `0` marks
  background or unannotated pixels.

## Licensing

Each constituent dataset remains under the terms of its original provider, and those terms differ
between sources. Consult the licence of the specific source dataset before using or redistributing
the corresponding subset. The VISTA-PATH model and code are licensed separately, under the
[Penn Academic Software License](https://github.com/zhihuanglab/VISTA-PATH/blob/main/LICENSE).

## Citation

```bibtex
@misc{liang2026vistapath,
  title        = {VISTA-PATH: An interactive foundation model for pathology image segmentation and quantitative analysis in computational pathology},
  author       = {Liang, Peixian and Li, Songhao and Koga, Shunsuke and Li, Yutong and Alipour, Zahra and Tang, Yucheng and Xu, Daguang and Huang, Zhi},
  year         = {2026},
  eprint       = {2601.16451},
  archivePrefix= {arXiv},
  primaryClass = {cs.CV},
  doi          = {10.48550/arXiv.2601.16451},
}
```