Homecage Video Analysis

Using DeepLabCut to precisely track user-defined features of mice as they perform a whisker-based task in a Chen Lab home cage system.

Quick walkthrough of processing pipeline

How to Use

You can either clone this repository to your SCC home directory or you can directly use it from the ChenLab Z drive path /net/claustrum/mnt/data/Projects/Homecage/HomecageVideoAnalysisCopy

Step 1: Setting up your SCC account

Video analysis of the training module view is run using the Shared Computing Cluster(SCC). To make sure you have an accessible SCC account, log on to the SCC dashboard using your BU Kerberos email and password. If you were able to log in with no issues, you can move on to the next step. Otherwise, contact Jerry Chen, to add your BU account to the SCC lab project.

Step 2: Creating an Anaconda environment (ONLY NEED TO DO ONCE)

If this is your first time setting up an Anaconda environment on the SCC, read the SCC-provided instructions on setting up a .condarc file. https://www.bu.edu/tech/support/research/software-and-programming/common-languages/python/anaconda/

Once all is done, we can now set up the conda environment used to run this code.

The conda YML file env which contains all the necessary dependencies for this project is in the conda-environments folder. To create an environment with this file, run the following command:

conda env create -f conda-environments/env.yml

To be sure the environment was successfully set up, run the command conda env list. You should hopefully see VideoAnalysisENV in the list of environments.

Once the VideoAnalysisENV environment is set up, you don't need to do this again.

Step 3: Running analysis

To run the analysis, change the directory to the scc folder. The main shell script to analyze is run_training_module_job_array.sh. This script takes in two input arguments:

1. Full path to the directory that contains the video files ex. /net/claustrum/test/folder
2. The number ID of the rigs you would like to run analysis on. If you plan to run an analysis on all videos in the directory instead of individual rigs, input all as the argument.

Example 1 (Running video analysis on rigs 6 and 8 with files located in /Projects/Homecage/Videos):

qsub run_training_module_job_array.sh /Projects/Homecage/Videos 6 8

Example 2 (Running video analysis on all videos with files located in /Projects/Homecage/Videos):

qsub run_training_module_job_array.sh /Projects/Homecage/Videos all

Dependencies Used:

https://github.com/DeepLabCut/DeepLabCut

https://github.com/matterport/Mask_RCNN

https://github.com/sirfz/tesserocr

https://pjreddie.com/darknet/yolo/