Simba-UW-tf-dev


NameSimba-UW-tf-dev JSON
Version 1.88.7 PyPI version JSON
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home_pagehttps://github.com/sgoldenlab/simba
SummaryToolkit for computer classification of behaviors in experimental animals
upload_time2024-03-28 16:53:45
maintainerNone
docs_urlNone
authorSimon Nilsson, Jia Jie Choong, Sophia Hwang
requires_pythonNone
licenseGNU Lesser General Public License v3 (LGPLv3)
keywords
VCS
bugtrack_url
requirements Pillow pyyaml shapely shapely dtreeviz eli5 graphviz imblearn imgaug imutils matplotlib numpy opencv-python opencv-python pandas pandas scikit-image scipy seaborn scikit-learn scikit-learn joblib joblib tabulate tabulate tqdm xgboost yellowbrick dash dash_color_picker dash_core_components dash_colorscales dash_html_components h5py numba numba numexpr plotly statsmodels statsmodels cefpython3 pyarrow shap tables xlrd trafaret geos ffmpeg-python
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # SimBA (Simple Behavioral Analysis)
![SimBA Splash](https://raw.githubusercontent.com/sgoldenlab/simba/master/docs/tutorials_rst/img/index/landing_page_1.png)

SimBA (Simple Behavioral Analysis) is a platform for analyzing behaviors of experimental animals within video recordings.

### More Information
See below for raison d'être, detailed API, tutorials, data, documentation, support, and walkthroughs:

- GitHub: [https://github.com/sgoldenlab/simba](https://github.com/sgoldenlab/simba)
- Documentation readthedocs: [https://simba-uw-tf-dev.readthedocs.io/en/latest/](https://simba-uw-tf-dev.readthedocs.io/en/latest/)
- API: [https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html](https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html)
- Gitter Chat: [https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im](https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im)
- biorxiv preprint: [https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2](https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2)
- OSF: [https://osf.io/tmu6y/](https://osf.io/tmu6y/)

### Installation
To install SimBA, use the following command:

```bash
pip install simba-uw-tf-dev
```


### Citation
If you use the code, please cite:

```bash
@article{Nilsson2020.04.19.049452,
  author = {Nilsson, Simon RO and Goodwin, Nastacia L. and Choong, Jia Jie and Hwang, Sophia and Wright, Hayden R and Norville, Zane C and Tong, Xiaoyu and Lin, Dayu and Bentzley, Brandon S. and Eshel, Neir and McLaughlin, Ryan J and Golden, Sam A.},
  title = {Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals},
  elocation-id = {2020.04.19.049452},
  year = {2020},
  doi = {10.1101/2020.04.19.049452},
  publisher = {Cold Spring Harbor Laboratory},
  URL = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452},
  eprint = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452.full.pdf},
  journal = {bioRxiv}
}
```

### Licence
SimBA is licensed under GNU Lesser General Public License v3.0.

### Contributors
Contributers on Github https://github.com/sgoldenlab/simba#contributors




            

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    "description": "# SimBA (Simple Behavioral Analysis)\n![SimBA Splash](https://raw.githubusercontent.com/sgoldenlab/simba/master/docs/tutorials_rst/img/index/landing_page_1.png)\n\nSimBA (Simple Behavioral Analysis) is a platform for analyzing behaviors of experimental animals within video recordings.\n\n### More Information\nSee below for raison d'\u00eatre, detailed API, tutorials, data, documentation, support, and walkthroughs:\n\n- GitHub: [https://github.com/sgoldenlab/simba](https://github.com/sgoldenlab/simba)\n- Documentation readthedocs: [https://simba-uw-tf-dev.readthedocs.io/en/latest/](https://simba-uw-tf-dev.readthedocs.io/en/latest/)\n- API: [https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html](https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html)\n- Gitter Chat: [https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im](https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im)\n- biorxiv preprint: [https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2](https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2)\n- OSF: [https://osf.io/tmu6y/](https://osf.io/tmu6y/)\n\n### Installation\nTo install SimBA, use the following command:\n\n```bash\npip install simba-uw-tf-dev\n```\n\n\n### Citation\nIf you use the code, please cite:\n\n```bash\n@article{Nilsson2020.04.19.049452,\n  author = {Nilsson, Simon RO and Goodwin, Nastacia L. and Choong, Jia Jie and Hwang, Sophia and Wright, Hayden R and Norville, Zane C and Tong, Xiaoyu and Lin, Dayu and Bentzley, Brandon S. and Eshel, Neir and McLaughlin, Ryan J and Golden, Sam A.},\n  title = {Simple Behavioral Analysis (SimBA) \u2013 an open source toolkit for computer classification of complex social behaviors in experimental animals},\n  elocation-id = {2020.04.19.049452},\n  year = {2020},\n  doi = {10.1101/2020.04.19.049452},\n  publisher = {Cold Spring Harbor Laboratory},\n  URL = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452},\n  eprint = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452.full.pdf},\n  journal = {bioRxiv}\n}\n```\n\n### Licence\nSimBA is licensed under GNU Lesser General Public License v3.0.\n\n### Contributors\nContributers on Github https://github.com/sgoldenlab/simba#contributors\n\n\n\n",
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