---
license: mit
task_categories:
- image-to-text
tags:
- biology
- plant-phenotyping
- synthetic-data
- cowpea
- plant-architecture
- webdataset
---

# Cowpea-Architecture-XML-WDS

This dataset contains simulated images of Cowpea plants paired with organ-level architecture representations in XML format, packaged in **WebDataset (.tar)** format for efficient high-performance training.

## Dataset Structure
The dataset is sharded into `.tar` files, each containing up to 10,000 samples.
Each sample consists of:
- `.jpeg`: The plant image
- `.xml`: The organ-level architecture representation
- `.json`: (Optional) Metadata

## Usage with WebDataset
You can load this dataset directly in PyTorch using the `webdataset` library:

```python
import webdataset as wds
from torch.utils.data import DataLoader

url = "https://huggingface.co/datasets/heesup/Cowpea-Architecture-XML-WDS/resolve/main/shard-{000000..000200}.tar"
dataset = (
    wds.WebDataset(url)
    .decode("rgb")
    .to_tuple("jpeg", "xml")
)

dataloader = DataLoader(dataset, batch_size=16)
for images, xmls in dataloader:
    # training loop
    pass
```

## Citation
If you use this dataset, please cite:
**"A Vision Language Model for Generating XML-based Organ-level Plant Architecture Representations of Cowpea from Simulated Images"**