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Copy pathatari_wrapper.py
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64 lines (59 loc) · 2 KB
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import gym
import numpy as np
from typing import Deque
import cv2
class AtariRamWrapper:
def __init__(self, env):
self.env = env
self.action_space = env.action_space
self.observation_space = env.observation_space
def reset(self):
obs = self.env.reset().astype(np.float32)
return obs#/255.
def step(self, action):
obs, reward, done, info = self.env.step(action)
obs = obs.astype(np.float32)#/255.
return obs, reward, done, info
def render(self):
return self.env.render()
def close(self):
self.env.close()
class BreakoutBlindWrapper:
def __init__(self, env):
self.env = env
self.action_space = env.action_space
self.observation_space = env.observation_space
self.queue = Deque(maxlen=4)
self.queue.append(np.zeros([84,84], np.float32))
self.queue.append(np.zeros([84,84], np.float32))
self.queue.append(np.zeros([84,84], np.float32))
self.queue.append(np.zeros([84,84], np.float32))
def reset(self):
obs = self.env.reset()
# print(obs.shape)
# obs = self.gray_scale(obs)#/255.
self.queue.append(obs)
return np.stack(self.queue, axis=0)
# def gray_scale(self, image):
# gray = 0.299 * image[:,:,0] + 0.587 * image[:,:,1] + 0.114 * image[:,:,2]
# return gray
def step(self, action):
obs, reward, done, info = self.env.step(action)
# print(obs.shape)
# cv2.imwrite("./obs.png", obs)
# cv2.imshow("as s", obs)
# cv2.waitKey()
# obs = self.gray_scale(obs)#/255.
obs = obs[36:,:]
obs = cv2.resize(obs, (84,84), None)
# cv2.imshow("obs", obs)
# cv2.waitKey()
# exit()
reward = reward*2 + 0.001
self.queue.append(obs)
obs = np.stack(self.queue, axis=0)
return obs, reward, done, info
def render(self):
return self.env.render()
def close(self):
self.env.close()