billygrahamram/WeedCube

Opensource proximal hyperspectral image dataset of crops and weeds for deep learning.

29
/ 100
Experimental

This dataset provides high-resolution hyperspectral images of common crops like canola and soybean, alongside various weeds. It allows agricultural researchers and precision agriculture specialists to train and validate AI models for tasks like identifying weeds from crops using detailed spectral and spatial information. You get raw image data and accompanying scripts to visualize pseudo-RGB images and extract specific plant regions.

No commits in the last 6 months.

Use this if you are a plant scientist, agricultural engineer, or crop researcher developing machine learning models to differentiate crops from weeds using hyperspectral imaging.

Not ideal if you need a dataset for field-scale imagery or already have a large, diverse dataset for different plant species or growing conditions.

weed-detection precision-agriculture crop-monitoring plant-phenotyping hyperspectral-imaging
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 9 / 25

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Stars

7

Forks

1

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Oct 11, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/billygrahamram/WeedCube"

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