tensorflow-caney
Python package for lots of TensorFlow tools.
Documentation
Objectives
- Library to process remote sensing imagery using GPU and CPU parallelization.
- Machine Learning and Deep Learning image classification and regression.
- Agnostic array and vector-like data structures.
- User interface environments via Notebooks for easy to use AI/ML projects.
- Example notebooks for quick AI/ML start with your own data.
Installation
The following library is intended to be used to accelerate the development of data science products for remote sensing satellite imagery, or any other applications. tensorflow-caney can be installed by itself, but instructions for installing the full environments are listed under the requirements directory so projects, examples, and notebooks can be run.
Note: PIP installations do not include CUDA libraries for GPU support. Make sure NVIDIA libraries are installed locally in the system if not using conda/mamba.
Production Container
module load singularity
singularity build --sandbox /lscratch/$USER/container/tensorflow-caney docker://nasanccs/tensorflow-caney:latest
Development Container
module load singularity
singularity build --sandbox /lscratch/$USER/container/tensorflow-caney docker://nasanccs/tensorflow-caney:dev
Why Caney?
"Caney" means longhouse in Taíno.
Contributors
- Jordan Alexis Caraballo-Vega, jordan.a.caraballo-vega@nasa.gov
- Caleb Spradlin, caleb.s.spradlin@nasa.gov
Contributing
Please see our guide for contributing to tensorflow-caney.
References
1 maintainer
Metadata
1 maintainer
Release files for tensorflow-caney 0.5.1
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| tensorflow_caney-0.5.1-py3-none-any.whl | Python 3 | none | any | Details for tensorflow_caney-0.5.1-py3-none-any.whl |
Total release size: 177.6 kB
Release files / tensorflow_caney-0.5.1.tar.gz
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