CODEWITHSUNDEEP
pythonnumpynumpy-ndarray
max
max

Reputation: 2657

Construct a Numpy array from a hexadecimal string

I have a hexadecimal string "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49" to be specific this will contain the data of an image.

I want to convert it to a Numpy array or possibly reconstruct an OpenCV image from the said data.

The width and height will also be supplied so the dimensions of the Numpy array is known.

How can I construct a Numpy array from the above string?

Upvotes: 5

Views: 5264

Answers (6)

alercelik
alercelik

Reputation: 723

It is possible to use bytes.fromhex along with np.frombuffer

import numpy as np

hex_string = "ff01"
arr = np.frombuffer(bytes.fromhex(hex_string), dtype=np.uint8)
# array([255,   1], dtype=uint8)

in your case

import numpy as np

hex_string = "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49"
arr = np.frombuffer(bytes.fromhex(hex_string.replace("-", "")), dtype=np.uint8)

Upvotes: 0

M.T
M.T

Reputation: 5231

If memory efficiency is of concern two digits in a hexadecimal number corresponds to an unsigned 8-bit integer (ie, numbers between 0 and 255).

To return to the original string you can use format(number, '02x') (zero padded 2-length hexadecimal number string)

hex_str = "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49"
arr = np.fromiter((int(x, 16) for x in hex_str.split('-')), dtype=np.uint8)
# array([137,  80,  78,  71,  13,  10,  26,  10,   0,   0,   0,  13,  73],
      dtype=uint8)

The array would only take up 13 bytes of space, as opposed to the default array type for integers (np.int64) which would take up 104 bytes.

Once could return it to its original string form in the following way:

hex_str = '-'.join((format(x, '02x') for x in arr)).upper()

Upvotes: 0

RMPR
RMPR

Reputation: 3531

You can use list comprehension and the built-in int module to convert from hexadecimal to decimal the splitted string:

import numpy as np

hex_string = '89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49'
np.array([int(x, base=16) for x in hex_string.split('-')])

Upvotes: 1

taras
taras

Reputation: 6915

You can split the string by dash and convert individual base-16 numbers into int.

>>> import numpy as np
>>> hext_str = "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49"
>>> np.array([int(x, 16) for x in hex_str.split("-")])
array([137,  80,  78,  71,  13,  10,  26,  10,   0,   0,   0,  13,  73])

Provided that (n, m) are dimensions of your image you can use on the result the .reshape((n, m)) method of np.array.

Upvotes: 0

Mohamed Shabeer kp
Mohamed Shabeer kp

Reputation: 882

import numpy as np
arr = np.array([int(x, 16) for x in "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49".split("-")])
print(arr)

Upvotes: 0

yatu
yatu

Reputation: 88275

We could use np.fromiter, and cast the individual strings to hexadecimal, using the base argument in int, and then to integer type using the dtype argument in np.fromiter:

s = "89-50-4E-47-0D-0A-1A-0A-00-00-00-0D-49"

np.fromiter((int(x, 16) for x in s.split('-')), dtype=np.int32)
# array([137,  80,  78,  71,  13,  10,  26,  10,   0,   0,   0,  13,  73])

Upvotes: 3

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