# pyxit
This code implements the core algorithms for Random subwindows extraction and Extra-Trees classifiers. It is used by Cytomine DataMining applications: classification_validation, classification_model_builder, classification_prediction, segmentation_model_builder and segmentation_prediction. But it can be run without Cytomine on local data (using dir_ls and dir_ts arguments).
It is based on the following paper:
1) For image/object classification: “Towards Generic Image Classification using Tree-based Learning: an Extensive Empirical Study”. Raphael Maree, Pierre Geurts, Louis Wehenkel. Pattern Recognition Letters, DOI: 10.1016/j.patrec.2016.01.006, 2016.
2) For image semantic segmentation: Fast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees Dumont et al., 2009 http://orbi.ulg.ac.be/handle/2268/12205
# Install Simply: ` pip install pyxit `
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Release files for pyxit 1.1.2
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Source distribution (sdist)
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| pyxit-1.1.2.tar.gz | 7.3 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyxit-1.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.1 kB
Release files / pyxit-1.1.2.tar.gz
| Download URL | pyxit-1.1.2.tar.gz |
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Release files / pyxit-1.1.2-py3-none-any.whl
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| Size | 10.8 kB |
| Tags | Python 3 |
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