https://github.com/getnamo/ml-remote-server

Server component of https://github.com/getnamo/machine-learning-remote-ue4
https://github.com/getnamo/ml-remote-server

python pytorch tensorflow unreal

Last synced: 9 days ago
JSON representation

Server component of https://github.com/getnamo/machine-learning-remote-ue4

• Host: GitHub
• URL: https://github.com/getnamo/ml-remote-server
• Owner: getnamo
• License: mit
• Created: 2019-11-17T11:26:38.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2024-04-18T15:48:37.000Z (7 months ago)
• Last Synced: 2024-05-01T19:48:42.739Z (6 months ago)
• Topics: python, pytorch, tensorflow, unreal
• Language: Python
• Size: 58.6 KB
• Stars: 21
• Watchers: 5
• Forks: 14
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome_unreal_engine_4_-_5 - ml-remote-server
• awesome_unreal_engine_4_-_5 - ml-remote-server

README

        
# ml-remote-server

Server complement of https://github.com/getnamo/MachineLearningRemote-Unreal.

Startup the server, point your ```MachineLearningRemote``` component to your server address with the script file name set in ```DefaultScript``` property and it will load on begin play.

## Quick Setup

1. Install [python 3](https://www.python.org/downloads/) on target machine recommended version for e.g. tensorflow: 3.7.

*Option 1)Using Windows Local Server*

2. Update requirements.txt with any dependencies you need, e.g. tensorflow==2.2

3. Double click on ```InstallRequirements``` (you may need to run this command in admin)

![](https://i.imgur.com/zUInHbV.png)

4. *(Optional)* If you're not using the autolaunch option on MachineLearnineRemote: Double click ```StartupServer.bat``` 

*Option 2) Using Remote Server*

2. Pick a folder, navigate to it

3. ```git clone https://github.com/getnamo/ml-remote-server.git```

4. Update requirements.txt with any dependencies you need, e.g. ```tensorflow==2.2```

5. run ```pip install -r requirements.txt```. 

6. In terminal type ```python server.py``` to start the server

Server is now ready to use. 

*Optional Client Steps*

1. Connect your unreal instance via https://github.com/getnamo/MachineLearningRemote-Unreal

2. Listen to log events via your browser by going to ```:8080``` or [```localhost:8080```](http://localhost:8080) in your browser. There are some debug commands like ```/r ``` to swap script and ```/i``` to send dummy inputs; see https://github.com/getnamo/ml-remote-server/blob/master/server.py#L117 for all supported commands.

## How to use

### Startup event flow

*Begin Play -> (if connect on beginplay) connect to backend -> (if start script on connection) Default Script start*

Listen to the ```OnScriptStarted``` event to know it's safe to send inputs/start training.

### API

See https://github.com/getnamo/MachineLearningRemote-Unreal as all interaction beyond debugging is handled by client.

Keep in mind that you can end play, do some code changes, and begin playing again without rebooting your server; the default script will be reloaded. You can also use the debug browser with ```/r <script name>``` or call ```StartScript``` from ```MachineLearningRemote``` component to live reload a script even during play.