我有一个可以这样处理的数组:

ba = bytearray(fh.read())[32:]
size = int(math.sqrt(len(ba)))

我可以判断像素是黑色还是白色
iswhite = (ba[i]&1)==1

如何快速将1D字节数组转换为行长size的2D numpy数组,并将白色像素转换为(ba[i]&1)==1的2D numpy数组,将黑色像素转换为其他的2D numpy数组?我创建的数组如下:
im_m = np.zeros((size,size,3),dtype="uint8)

最佳答案

import numpy as np

# fh containts the file handle

# go to position 32 where the image data starts
fh.seek(32)

# read the binary data into unsigned 8-bit array
ba = np.fromfile(fh, dtype='uint8')

# calculate the side length of the square array and reshape ba accordingly
side = int(np.sqrt(len(ba)))
ba = ba.reshape((side,side))

# toss everything else apart from the last bit of each pixel
ba &= 1

# make a 3-deep array with 255,255,255 or 0,0,0
img = np.dstack([255*ba]*3)
# or
img = ba[:,:,None] * np.array([255,255,255], dtype='uint8')

有几种方法可以完成最后一步。如果您需要相同的数据类型(uint8),请小心。

关于python - 将1D字节数组转换为2D numpy数组的最快方法,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/24518034/

10-09 21:11