An animal behaviour processing and analysis package
Project description
behavysis_pipeline
Installation
Dev installation
conda env create -f conda_env.yaml
conda activate behavysis_pipeline_env
pip install poetry
poetry install
User installation
conda env create -f conda_env.yaml
References
Mathis, A., Mamidanna, P., Cury, K. M., Abe, T., Murthy, V. N., Mathis, M. W., & Bethge, M. (2018, August 20). DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience. Springer Science and Business Media LLC. http://doi.org/10.1038/s41593-018-0209-y
Nath, T., Mathis, A., Chen, A. C., Patel, A., Bethge, M., & Mathis, M. W. (2019, June 21). Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Nature Protocols. Springer Science and Business Media LLC. http://doi.org/10.1038/s41596-019-0176-0
Lauer, J., Zhou, M., Ye, S., Menegas, W., Schneider, S., Nath, T., … Mathis, A. (2022, April). Multi-animal pose estimation, identification and tracking with DeepLabCut. Nature Methods. Springer Science and Business Media LLC. http://doi.org/10.1038/s41592-022-01443-0
Nilsson, S., Goodwin, N., Choong, J. J., Hwang, S., Wright, H., Norville, Z., Tong, X., Lin, D., Bentzley, B., Eshel, N., McLaughlin, R., & Golden, S. Simple Behavioral Analysis (SimBA): an open source toolkit for computer classification of complex social behaviors in experimental animals [Computer software]. https://github.com/sgoldenlab/simba
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for behavysis_pipeline-0.1.20.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4a5d777a93268ba8aee7018d06165ac9fa83af1d1eec7d5db81ffd2df1c365ae |
|
MD5 | b90cf8c77b8952c7d7ca5344412b4a16 |
|
BLAKE2b-256 | ddff74ef8c3dec5049b8f57d76be7134d3d1f90f9c96c447f353927371bb276e |
Hashes for behavysis_pipeline-0.1.20-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d28f679f8cbd895275ebd79f031d69ce5acaac04988777f2b991e4a270375dea |
|
MD5 | fd2969b6cd4ccc44354d7fd11e6c5d6e |
|
BLAKE2b-256 | 0492e8c807168bb50985679923f4f683929dbc96604df291e2d6fdc8c69104c3 |