How to render OpenAI gym in google Colab? [closed]

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Korakot’s answer is not correct.

You can indeed render OpenAi Gym in colaboratory, albiet kind of slowly using none other than matplotlib.

Heres how:

Install xvfb & other dependencies (Thanks to Peter for his comment)

!apt-get install x11-utils > /dev/null 2>&1 
!pip install pyglet > /dev/null 2>&1 
!apt-get install -y xvfb python-opengl > /dev/null 2>&1

As well as pyvirtual display:

!pip install gym pyvirtualdisplay > /dev/null 2>&1

then import all your libraries, including matplotlib & ipythondisplay:

import gym
import numpy as np
import matplotlib.pyplot as plt
from IPython import display as ipythondisplay

then you want to import Display from pyvirtual display & initialise your screen size, in this example 400×300… :

from pyvirtualdisplay import Display
display = Display(visible=0, size=(400, 300))
display.start()

last but not least, using gym’s “rgb_array” render functionally, render to a “Screen” variable, then plot the screen variable using Matplotlib! (rendered indirectly using Ipython display)

env = gym.make("CartPole-v0")
env.reset()
prev_screen = env.render(mode="rgb_array")
plt.imshow(prev_screen)

for i in range(50):
  action = env.action_space.sample()
  obs, reward, done, info = env.step(action)
  screen = env.render(mode="rgb_array")

  plt.imshow(screen)
  ipythondisplay.clear_output(wait=True)
  ipythondisplay.display(plt.gcf())

  if done:
    break

ipythondisplay.clear_output(wait=True)
env.close()

Link to my working Colaboratory notebook demoing cartpole:

https://colab.research.google.com/drive/16gZuQlwxmxR5ZWYLZvBeq3bTdFfb1r_6

Note: not all Gym Environments support “rgb_array” render mode, but most of the basic ones do.

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