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README.md

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+---
+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"**