billygrahamram/WeedCube
Opensource proximal hyperspectral image dataset of crops and weeds for deep learning.
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.
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7
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1
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Oct 11, 2024
Commits (30d)
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