Live stream Unity's ML-Agents training process from Google Colab to Twitch/YouTube server.
Project description
ML-Agents Video Streamer
Now you can Live Stream the Agent's learning behavior to Twitch/YouTube from Google Colab while training these Agents.
What’s In This Document
Installation
!pip install mlagents-video-streamer
And if you already have mlagents-video-streamer
then upgrade it by this command.
!pip install --upgrade mlagents-video-streamer
Imports and Usage
from mlagents_video_streamer import SetupVirtualDisplay
from mlagents_video_streamer import VideoStreamer
-
Now Setup the Virtual Display:
SetupVirtualDisplay()
-
Define your live stream information:
# stream_info dictionary should be in this format only stream_info = { "URL": "rtmp://live.twitch.tv/app/", # example of Twitch URL "secret": "--- secret here ---" }
-
Initialize the
VideoStreamer
class withstream_info
:videoStreamer = VideoStreamer(stream_info)
*If you don't pass
stream_info
then it will simply store the video locally in thevideos
directory. -
Start the video streamer before starting with the training process:
videoStreamer.start()
-
Now capture the training process, using subprocess library:
import subprocess from random import randrange try: train = subprocess.run([ "mlagents-learn", "config.yaml", "--run-id=train-1", "--env=3DBall_example/3DBall.x86_64", "--base-port=" + str(randrange(9000, 9999)) ], cwd="/content/", stdout=subprocess.PIPE) print("Training process has been successfully ended.") except Exception as e: print("You killed the training process in between.") finally: videoStreamer.close()
*At the end don't forget to close the video streamer by using
close()
method onvideoStreamer
object as shown in the above example.
License
Licensed under the MIT License.
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