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.
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
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.
3 environment :
-- PROD
-- TEST
-- DEV
You can see the official documentation in the github wiki of the repository.
You can also read the documentation here -> Aicut doc
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]
On every Pull request or Push to the [main] branch, an build aws is launched.
Please, wait the build ended before merge the branches.
If you discover a security vulnerability within Aicut, please follow our disclosure procedure and set up a new issue request on the github.