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# Licensed to the Apache Software Foundation (ASF) under one
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# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import numpy as np
class Atari8080Preprocessor(object):
def __init__(self):
self.prev = None
self.obs_size = 80*80
def reset(self):
self.prev = None
def preprocess(self, img):
"""
Preprocess a 210x160x3 uint8 frame into a 6400 (80x80) (1 x input_size)
float vector.
"""
# Crop, down-sample, erase background and set foreground to 1.
# See https://gist.github.com/karpathy/a4166c7fe253700972fcbc77e4ea32c5
img = img[35:195]
img = img[::2, ::2, 0]
img[img == 144] = 0
img[img == 109] = 0
img[img != 0] = 1
curr = np.expand_dims(img.astype(np.float).ravel(), axis=0)
# Subtract the last preprocessed image.
diff = (curr - self.prev if self.prev is not None
else np.zeros((1, curr.shape[1])))
self.prev = curr
return diff
class IdentityPreprocessor(object):
def __init__(self, obs_size):
self.obs_size = obs_size
def reset(self):
pass
def preprocess(self, x):
return x