Metadata-Version: 2.1
Name: tensorflow-caney
Version: 0.2.5
Summary: Methods for tensorflow deep learning applications
Home-page: https://github.com/nasa-nccs-hpda/tensorflow-caney
Author: jordancaraballo
Author-email: jordan.a.caraballo-vega@nasa.gov
License: MIT
Project-URL: Documentation, https://github.com/nasa-nccs-hpda/tensorflow-caney
Project-URL: Source, https://github.com/nasa-nccs-hpda/tensorflow-caney
Project-URL: Issues, https://github.com/nasa-nccs-hpda/tensorflow-caney/issues
Keywords: tensorflow-caney,deep-learning,machine-learning
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: omegaconf
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: tqdm
Requires-Dist: tensorflow
Requires-Dist: tensorflow-addons
Requires-Dist: segmentation-models
Requires-Dist: xarray
Requires-Dist: rioxarray
Requires-Dist: numba
Provides-Extra: all
Requires-Dist: pdoc (==8.0.1) ; extra == 'all'
Requires-Dist: pytest ; extra == 'all'
Requires-Dist: coverage[toml] ; extra == 'all'
Requires-Dist: black ; extra == 'all'
Provides-Extra: docs
Requires-Dist: pdoc (==8.0.1) ; extra == 'docs'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'
Requires-Dist: coverage[toml] ; extra == 'test'
Requires-Dist: black ; extra == 'test'

# tensorflow-caney

Python package for lots of TensorFlow tools.

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## Documentation

- Latest: https://nasa-nccs-hpda.github.io/tensorflow-caney

## 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.

```bash
module load singularity
singularity build --sandbox tensorflow-caney docker://nasanccs/tensorflow-caney:latest
```

## 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](CONTRIBUTING.md).

## References

- [TensorFlow Advanced Segmentation Models](https://github.com/JanMarcelKezmann/TensorFlow-Advanced-Segmentation-Models)
