# 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)
Raw data
{
"_id": null,
"home_page": "https://github.com/nasa-nccs-hpda/tensorflow-caney",
"name": "tensorflow-caney",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "tensorflow-caney, deep-learning, machine-learning",
"author": "jordancaraballo",
"author_email": "jordan.a.caraballo-vega@nasa.gov",
"download_url": "https://files.pythonhosted.org/packages/53/9f/6d0799d05dcf0efabf41e9996c1fa47b5951ed966498bda7d6cec53fbb1e/tensorflow_caney-0.5.1.tar.gz",
"platform": null,
"description": "# tensorflow-caney\n\nPython package for lots of TensorFlow tools.\n\n[](https://zenodo.org/badge/latestdoi/471512673)\n[\n\n\n\n[](https://github.com/psf/black)\n[](https://coveralls.io/github/nasa-nccs-hpda/tensorflow-caney?branch=main)\n\n## Documentation\n\n- Latest: https://nasa-nccs-hpda.github.io/tensorflow-caney\n\n## Objectives\n\n- Library to process remote sensing imagery using GPU and CPU parallelization.\n- Machine Learning and Deep Learning image classification and regression.\n- Agnostic array and vector-like data structures.\n- User interface environments via Notebooks for easy to use AI/ML projects.\n- Example notebooks for quick AI/ML start with your own data.\n\n## Installation\n\nThe following library is intended to be used to accelerate the development of data science products\nfor remote sensing satellite imagery, or any other applications. tensorflow-caney can be installed\nby itself, but instructions for installing the full environments are listed under the requirements\ndirectory so projects, examples, and notebooks can be run.\n\nNote: PIP installations do not include CUDA libraries for GPU support. Make sure NVIDIA libraries\nare installed locally in the system if not using conda/mamba.\n\n### Production Container\n\n```bash\nmodule load singularity\nsingularity build --sandbox /lscratch/$USER/container/tensorflow-caney docker://nasanccs/tensorflow-caney:latest\n```\n\n## Development Container\n\n```bash\nmodule load singularity\nsingularity build --sandbox /lscratch/$USER/container/tensorflow-caney docker://nasanccs/tensorflow-caney:dev\n```\n\n## Why Caney?\n\n\"Caney\" means longhouse in Ta\u00edno.\n\n## Contributors\n\n- Jordan Alexis Caraballo-Vega, jordan.a.caraballo-vega@nasa.gov\n- Caleb Spradlin, caleb.s.spradlin@nasa.gov\n\n## Contributing\n\nPlease see our [guide for contributing to tensorflow-caney](CONTRIBUTING.md).\n\n## References\n\n- [TensorFlow Advanced Segmentation Models](https://github.com/JanMarcelKezmann/TensorFlow-Advanced-Segmentation-Models)\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Methods for tensorflow deep learning applications",
"version": "0.5.1",
"project_urls": {
"Documentation": "https://github.com/nasa-nccs-hpda/tensorflow-caney",
"Homepage": "https://github.com/nasa-nccs-hpda/tensorflow-caney",
"Issues": "https://github.com/nasa-nccs-hpda/tensorflow-caney/issues",
"Source": "https://github.com/nasa-nccs-hpda/tensorflow-caney"
},
"split_keywords": [
"tensorflow-caney",
" deep-learning",
" machine-learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "4652b3ac52582a07d706b5ce6ee5bf83ee4d3a51e7e05137fee8cc99232e193c",
"md5": "e0142a5666209de6fd3ab38b1110c8e8",
"sha256": "461006dc680d7153b0a7a4a2b8e265190380bacd6487aafd8490b7a73fdd54b9"
},
"downloads": -1,
"filename": "tensorflow_caney-0.5.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "e0142a5666209de6fd3ab38b1110c8e8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 101524,
"upload_time": "2024-10-03T18:06:34",
"upload_time_iso_8601": "2024-10-03T18:06:34.233447Z",
"url": "https://files.pythonhosted.org/packages/46/52/b3ac52582a07d706b5ce6ee5bf83ee4d3a51e7e05137fee8cc99232e193c/tensorflow_caney-0.5.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "539f6d0799d05dcf0efabf41e9996c1fa47b5951ed966498bda7d6cec53fbb1e",
"md5": "bf895b80f00f3a6813800596f9455986",
"sha256": "591f99485bebce1834d57aec5a54dbd8964351f47605a8bbcd63c4dba5c417c2"
},
"downloads": -1,
"filename": "tensorflow_caney-0.5.1.tar.gz",
"has_sig": false,
"md5_digest": "bf895b80f00f3a6813800596f9455986",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 76030,
"upload_time": "2024-10-03T18:06:35",
"upload_time_iso_8601": "2024-10-03T18:06:35.905884Z",
"url": "https://files.pythonhosted.org/packages/53/9f/6d0799d05dcf0efabf41e9996c1fa47b5951ed966498bda7d6cec53fbb1e/tensorflow_caney-0.5.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-10-03 18:06:35",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "nasa-nccs-hpda",
"github_project": "tensorflow-caney",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "tensorflow-caney"
}
JSON
