Various scripts to support DeepLabCut. Feel free to contribute your own analysis methods, and perhaps some short notebook of how to use it. Thanks!
These two scripts illustrate how to train, test and analyze videos for multiple projects automatically (scale_raining_and_evaluation.py) and how to analyze videos that are organized in subfolders automatically (scale_analysis_oversubfolders.py). Feel free to adjust them for your needs!
https://github.com/AlexEMG/DLCutils/blob/master/scale_analysis_oversubfolders.py https://github.com/AlexEMG/DLCutils/blob/master/scale_raining_and_evaluation.py
Contributed by Alexander Mathis
This code allows you to import the labeled data from DLC 1 to DLC 2 projects. Note, it is not streamlined and should be used with care.
https://github.com/AlexEMG/DLCutils/blob/master/convertDLC1TO2.py
Contributed by Alexander Mathis
#UPDATE: as of Deeplabcut 2.0.4 onwards you no longer need to use this code! You can simply create the training set on the cloud and it will automatically convert your project for you.
- This solves a path problem when creating a project and annotating data on Windows (see DeepLabCut/DeepLabCut#172). This functionality will be included in a later version of DLC 2 (DONE!) https://github.com/AlexEMG/DLCutils/blob/master/convertWin2Unix.py
Usage: change in lines 70 and 71 of https://github.com/AlexEMG/DLCutils/blob/master/convertWin2Unix.py
basepath='/content/drive/My Drive/DeepLabCut/examples/'
projectname='Reaching-Mackenzie-2018-08-30'
then run this script on colaboratory after uploading your labeled data to the drive. Thereby it will be converted to unix format, then create a training set (with deeplabcut) and proceed as usual...
Contributed by Alexander Mathis
https://github.com/AlexEMG/DLCutils/blob/master/time_in_each_roi.py
Contributed by Federico Claudi
- (adpated from https://github.com/gordonberman/MotionMapper)
https://github.com/AlexEMG/DLCutils/tree/master/DLC_2_MotionMapper
Contributed by Mackenzie Mathis
paper: https://www.biorxiv.org/content/early/2018/11/28/482349
code: https://github.com/bf777/DeepCutRealTime
maintainer: Brandon Forys
code: https://github.com/lambdaloop/anipose
maintainer: Pierre Karashchuk
- From Tom Vaissie - [email protected]
- Please see the README.txt file https://github.com/AlexEMG/DLCutils/tree/master/pupilTracking for details; this code makes the video in case study 7 https://www.mousemotorlab.org/deeplabcut/.
Please direct inquires to the contributors/code-maintainers of that code. Note that the software(s) are provided "as is", without warranty of any kind, express or implied.