The front-end dashboard that provides the ability to annotate videos of livestock for the use in research.
The goal of this project is to create a tool that is easy to use, has a small learning curve and can scale easily to provide the ability to annotate videos efficiently and at scale. The intuition of this project is gained from analyzing similar projects and analyzing the weaknesses and points of frustration and improving them. Another goal is to have an annotation workflow that is extremely fast and efficient, as there are terabytes of video that needs to be processed at large.
Please refer to USAGE.md for a detailed guide on how to use the tool.
These instructions will get you a copy of the project up and running on your local machine for viewing.
You will need to have npm, firefox/chrome and git installed on your system for this to work.
First, you will need to clone the repository to your desired location
git clone https://github.com/AIFARMS/pig-annotation-tool
Secondly, you will need to install the node_modules which can be done by:
npm install
Lastly, run start to get the project running on your local machine. The website will be on http://localhost:4000/ This is for the front-end portion of the dashboard. Currently, there is no backend portion to this website.
npm start
If the goal is to simply access the website, then go to the build folder to index.html to access the website.
Currently docker is setup to run the the node project. This will be further expanded onto in the future to include Clowder integration, backend servers, etc
These commands are written for a UNIX based machine running Docker. Support for windows is uncertain
Easy command list:
- To build and run docker container
sudo docker build --tag avat:latest . && sudo docker run -it --rm -v ${PWD}:/avat -v /AVAT/node_modules -e CHOKIDAR_USEPOLLING=true --name avat -p 3001:3000 avat && sudo docker start avat && sudo docker ps -a | grep avat - To stop and remove container
sudo docker stop avat && sudo docker rm avat - To remove pre-existing container and build new container
sudo docker stop avat && sudo docker rm avat && sudo docker build --tag avat:latest . && sudo docker run -it --rm -v ${PWD}:/avat -v /AVAT/node_modules -e CHOKIDAR_USEPOLLING=true --name avat -p 3001:3000 avat && sudo docker start avat && sudo docker ps -a | grep avat
There is also support for running this off of a flask server. This will be further expanded on into the future to include any external models and such.
These commands are written for a UNIX based machine running Docker. Support for windows is uncertain
Setup a virtual environment and install the proper dependencies from backend/requirements.txt. Then change current directory to backend and type in flask run. The website should be up on http://127.0.0.1:5000
- React - Main Front-End Framework
- React Bootstrap - UI Library
- react-player - Video Player
- fabric.js - Canvas renderer
- Pradeep Senthil pradeepsen99 - AVAT
- Ana Lucic alucic2 - Data Conversion Scripts
- Zimu Li neuroZ68 - Usage Documentation