A curated collection of helpers needed for Atari DRL environment management.
Project description
Atari Helpers
A tiny toolkit for tidying up Atari observations before they hit your RL agent. Keep installs light, configs simple, and pre-processing consistent.
- 🚀 Quick preprocessing for Atari frames (grayscale + resize)
- 🧰 Single helper focused on DRL needs; no extra baggage
- ✅ Tested on Python 3.9+ with NumPy + OpenCV
Installation
pip install atarihelpers
Usage
import gymnasium as gym
from atarihelpers import process_state
env = gym.make("ALE/Pong-v5")
state, _ = env.reset()
processed = process_state(
state,
image_size=84, # target square size
grayscale=True, # convert to single channel
resize=True, # skip if you want original resolution
)
📝 Input should be a NumPy array shaped (H, W, C) in BGR order (OpenCV style). The helper returns the processed NumPy array ready for stacking or feeding to your model.
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