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Datasets:
bbrangeo
/
Cowpea-Architecture-XML

Tasks:
Image-to-Text
Modalities:
Image
Text
Formats:
webdataset
Size:
100K - 1M
Tags:
biology
plant-phenotyping
synthetic-data
cowpea
plant-architecture
webdataset
Libraries:
Datasets
WebDataset
License:
Dataset card Data Studio Files
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bbrangeo heesup commited on
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Duplicate from heesup/Cowpea-Architecture-XML

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Co-authored-by: Heesup Yun <heesup@users.noreply.huggingface.co>

Files changed (42) hide show
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.avro filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ license: mit
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+ task_categories:
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+ - image-to-text
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+ tags:
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+ - biology
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+ - plant-phenotyping
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+ - synthetic-data
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+ - cowpea
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+ - plant-architecture
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+ - webdataset
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+ ---
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+
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+ # Cowpea-Architecture-XML-WDS
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+
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+ 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.
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+
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+ ## Dataset Structure
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+ The dataset is sharded into `.tar` files, each containing up to 10,000 samples.
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+ Each sample consists of:
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+ - `.jpeg`: The plant image
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+ - `.xml`: The organ-level architecture representation
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+ - `.json`: (Optional) Metadata
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+
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+ ## Usage with WebDataset
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+ You can load this dataset directly in PyTorch using the `webdataset` library:
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+
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+ ```python
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+ import webdataset as wds
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+ from torch.utils.data import DataLoader
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+
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+ url = "https://huggingface.co/datasets/heesup/Cowpea-Architecture-XML-WDS/resolve/main/shard-{000000..000200}.tar"
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+ dataset = (
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+ wds.WebDataset(url)
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+ .decode("rgb")
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+ .to_tuple("jpeg", "xml")
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+ )
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+
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+ dataloader = DataLoader(dataset, batch_size=16)
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+ for images, xmls in dataloader:
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+ # training loop
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+ pass
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+ ```
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+
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+ ## Citation
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+ If you use this dataset, please cite:
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+ **"A Vision Language Model for Generating XML-based Organ-level Plant Architecture Representations of Cowpea from Simulated Images"**
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