AICUT

AIcut is a solution for streamers. The goal is to create an application which is creating clips from live streaming on Twitch.

You can being connecte on the solution with your twitch account, Then you can activate the AI script, and it will create a clip automatcly from a machine learning Python then You can edit it and then mount your video with your clips

We also want to have an acces without Twitch account to display trends, analytics and clips on it.

Installation

Option 1 - Docker (Recommanded for production):
launch all the containers

docker compose up
--build : Build a new image
--detach : Run containers in the background

and to shut down

docker compose down 
--rmi type: Remove images with type 'all', 'local' or '<tags>'
--volumes : Remove volumes

Option 2 - One by one (Recommanded for developpement):

• Express API -> API INSTALLATION
• Client React -> CLIENT INSTALLATION
• AI server -> AISERVER INSTALLATION

Production

The solution is currently runnning with AWS ECS & AWS ECR

• Open http://13.37.251.205:3000 to view the client in the browser.
• Open http://13.37.251.205:3000 to view the api in the browser.

Environment

3 environment :
  -- PROD
  -- TEST
  -- DEV

Documentations

You can see the official documentation in the github wiki of the repository.

You can also read the documentation here -> Aicut doc

Contributions

Feel free to contribute to the project.

Step 1: Fork the project to your github

Step 2: Create a new local branch according to the bugfix, features ... from the project forked

Step 3: Code the feature.

Step 4: Push the branch to your remote repository.

Step 5: Create a Pull Request from your branch to the base branch : [develop]

Deployment

On every Pull request or Push to the [main] branch, an build aws is launched.

Please, wait the build ended before merge the branches.

Security Issues

If you discover a security vulnerability within Aicut, please follow our disclosure procedure and set up a new issue request on the github.