Converting OpenAI vectorized env to stable baselines vectorized env?

I am trying to take an openai baselines environment (vectorized procgen env) and convert it to a stable baselines vectorized environment. Below is my naive attempt. I get the following error that it expects a function, but I am not sure how to resolve the issue. Any help is appreciated.

from procgen import ProcgenEnv

from baselines.common.vec_env import (
    VecExtractDictObs,
    VecMonitor,
    VecFrameStack,
    VecNormalize
)

venv = ProcgenEnv(num_envs=200, env_name="coinrun")

venv = VecExtractDictObs(venv, "rgb")

venv = VecMonitor(venv=venv, filename=None, keep_buf=200,)

venv = VecNormalize(venv=venv, ob=False)

venv = DummyVecEnv(venv)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-2-36f973b40ef0> in <module>
     16 venv = VecNormalize(venv=venv, ob=False)
     17 
---> 18 venv = DummyVecEnv(venv)

~/Documents/drl/research/venv_proc/lib/python3.6/site-packages/stable_baselines/common/vec_env/dummy_vec_env.py in __init__(self, env_fns)
     18 
     19     def __init__(self, env_fns):
---> 20         self.envs = [fn() for fn in env_fns]
     21         env = self.envs[0]
     22         VecEnv.__init__(self, len(env_fns), env.observation_space, env.action_space)

TypeError: 'VecNormalize' object is not iterable```

[araffin]

You have to create a wrapper similar to VecExtractDictObs that extracts the “rgb” item from the observation dictionary each environment individually.

this already exist: https://github.com/openai/gym/blob/master/gym/wrappers/filter_observation.py

[araffin]

Fixed in SB3: https://github.com/DLR-RM/stable-baselines3/pull/311