DLC_Helper

Designed to making setting up a markerless pose estimation of user-defined features with deep learning for all animals, including humans

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

Run in a windows 10 environment using Anaconda 4.7.5 and python 3.7.3

• DeepLabCut

  • Repo found here

• Python 3

  • Download

• Anaconda

  • Download

Installing

Setting up the Anaconda environment-

1. Follow these instructions

Running the Script

Important: At anytime the script can be paused by clicking into the window, hit enter to resume

1. Open anaconda prompt

2. Type activate name_of_environment

3. Change direcotries using ``cd Downloads```

4. Run the script by typing python DLC_Helper.py

5. In the script:

   • Enter the project title ex. TestProject
   • Enter the experimenter's name ex. Chase or Chase Dudas
   • wait
   • Type in the name of the video ex. Vole 1159 side video 1
   • Eneter the full path leading to the selected video ex. C:\Users\Behavior Scoring\Downloads\Vole 1159 side video 1.mpg
   • Enter the working directory ex. C:\Users\Behavior Scoring\Desktop\DeepLabCutProjects
   • Done! Now sit back and let the magic happen

Deployment

Additional notes about how to deploy this on a live system

Python 3.7.3
conda 4.7.5

Built With

• Anaconda - Platform
• Visual Studio - IDE
• Python - Code Language
• deeplabcut - Pose Estimator w/ Machine Learning

Versioning

We use species for versioning. For the versions available, see the tags on this repository.

Authors

• Chase Dudas - Script - Personal GitHub
• alex - Script - Git

License

This project is not licensed

Acknowledgments