https://github.com/nasa-nccs-hpda/tensorflow-caney
Python framework for lots of geospatial TensorFlow tools
https://github.com/nasa-nccs-hpda/tensorflow-caney
deep-learning machine-learning python remote-sensing tensorflow
Last synced: about 1 year ago
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Python framework for lots of geospatial TensorFlow tools
- Host: GitHub
- URL: https://github.com/nasa-nccs-hpda/tensorflow-caney
- Owner: nasa-nccs-hpda
- License: apache-2.0
- Created: 2022-03-18T20:47:22.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-03-25T12:38:29.000Z (over 1 year ago)
- Last Synced: 2025-03-25T12:39:20.144Z (over 1 year ago)
- Topics: deep-learning, machine-learning, python, remote-sensing, tensorflow
- Language: Python
- Homepage: https://nasa-nccs-hpda.github.io/tensorflow-caney
- Size: 6.08 MB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
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README
# tensorflow-caney
Python package for lots of TensorFlow tools.
[](https://zenodo.org/badge/latestdoi/471512673)
[
[](https://github.com/psf/black)
[](https://coveralls.io/github/nasa-nccs-hpda/tensorflow-caney?branch=main)
## 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.
### Production Container
```bash
module load singularity
singularity build --sandbox /lscratch/$USER/container/tensorflow-caney docker://nasanccs/tensorflow-caney:latest
```
## Development Container
```bash
module load singularity
singularity build --sandbox /lscratch/$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](CONTRIBUTING.md).
## References
- [TensorFlow Advanced Segmentation Models](https://github.com/JanMarcelKezmann/TensorFlow-Advanced-Segmentation-Models)