yharby/split-rs-data
Divide remote sensing images and their labels into data sets of specified size.
This tool helps remote sensing specialists and GIS analysts prepare their geospatial image and vector data for machine learning tasks. It takes large satellite images (GeoTIFFs) and their corresponding geographic features (shapefiles), then processes and divides them into smaller, uniformly sized image tiles and their rasterized labels. The output is a structured dataset ready for training machine learning models.
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Use this if you need to transform large remote sensing imagery and vector-based annotations into standardized, tiled datasets suitable for deep learning model training.
Not ideal if you're not working with remote sensing data or if your primary goal is general image processing rather than preparing data for machine learning.
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12
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4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 12, 2021
Commits (30d)
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