MaxPooling 最大池化简单实现最大池化简单实现
#!/usr/bin/env python2
# -*-coding:utf8-*-
import numpy as np
def max_pooling(feature_map, size=2, stride=2):
"""max_pooling"""
channel = feature_map.shape[0] height = feature_map.shape[1] width = feature_map.shape[2] # 确定最后的输出形状
out_height = np.uint16((height - size) // stride + 1)
out_width = np.uint16((width - size) // stride + 1)
# print "out_shape", (out_height, out_width)
out_pooling = np.zeros((channel, out_height, out_width), dtype=np.uint8)
for map_num in range(channel):
after_height = 0
for m in np.arange(0, height, stride):
after_width = 0
for n in np.arange(0, width, stride):
try:
out_pooling[map_num, after_height, after_width] = np.max(feature_map[map_num, m:m + size, n:n + size])
# try执行不成功, 说明已经超出,终止循环
except:
break
after_width = after_width + 1
after_height = after_height + 1
return out_pooling
if __name__ == "__main__":
input = np.arange(1, 28)
input = input.reshape((3, 3, 3))
print "池化前:", input
output = max_pooling(input, 2, 1)
print "最大池化后:", output
print(output.dtype)
print "out_shape", (output.shape)
Python2:
池化前: [[[ 1 2 3] [ 4 5 6] [ 7 8 9]]
[[10 11 12] [13 14 15] [16 17 18]]
[[19 20 21] [22 23 24] [25 26 27]]]
最大池化后: [[[ 5 6] [ 8 9]]
[[14 15] [17 18]]
[[23 24] [26 27]]] uint8
"out_shape" (3, 2, 2)
作者：苑先森
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