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HighSpeedRacing.py
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HighSpeedRacing.py
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import cv2
import sys
sys.path.append("game/")
import HighSpeedRacingGame as game
from BrainDQN_Nature import BrainDQN
import numpy as np
import matplotlib.pyplot as plt
import time
imgDim = [80*1,80*1]
# preprocess raw image to 80*80 gray image
def preprocess(observation):
observation = cv2.cvtColor(cv2.resize(observation, (imgDim[0], imgDim[1])), cv2.COLOR_BGR2GRAY)
ret, observation = cv2.threshold(observation,1,255,cv2.THRESH_BINARY)
return np.reshape(observation,(imgDim[0],imgDim[1],1))
def HighSpeedRacing():
# Step 1: init BrainDQN
actions = 5
brain = BrainDQN(actions, imgDim)
# Step 2: init Flappy Bird Game
flappyBird = game.GameState()
# Step 3: play game
# Step 3.1: obtain init state
action0 = np.array([0,1,0,0,0]) # do nothing
observation0, reward0, terminal = flappyBird.frame_step(action0)
print(observation0)
# print('observation0 1:',observation0)
# observation0 = cv2.cvtColor(cv2.resize(observation0, (imgDim[0],imgDim[1])), cv2.COLOR_BGR2GRAY)
# ret, observation0 = cv2.threshold(observation0,1,255,cv2.THRESH_BINARY)
brain.setInitState(observation0,action0) #将observation0复制4份放进BrainDQN的属性self.currentState中
# isUseExpertData = False
## isUseExpertData = True
# if(isUseExpertData == True):
# filename = "./expertData/observation"
# actInd = 0
# observation0 = np.load(filename + str(actInd) + ".npy")
# plt.imshow(observation0)
# # # Step 3.2: run the game
# # while 1!= 0:
# for _ in range(1):
# actInd = 0
# for actInd in range(1,2073):
# actInd += 1
# action = np.load(filename + "action" + str(actInd) + ".npy")
# reward = np.load(filename + "reward" + str(actInd) + ".npy")
# terminal = np.load(filename + "terminal" + str(actInd) + ".npy")
# nextObservation = np.load(filename + str(actInd) + ".npy")
# plt.imshow(nextObservation)
# nextObservation = preprocess(nextObservation)
# brain.setPerception(nextObservation,action,reward,terminal)
loss=[]
plt.figure()
ind = 0
# Step 3.2: run the game
while 1!= 0:
# time.sleep(0.1)
action= brain.getAction()
loss.append(brain.loss_temp)
ind += 1
if ind%500==499:
plt.plot(loss)
plt.show()
nextObservation,reward,terminal = flappyBird.frame_step(action)
# nextObservation = preprocess(nextObservation)
brain.setPerception(nextObservation,action,reward,terminal)
def main():
HighSpeedRacing()
if __name__ == '__main__':
main()