How to convert Python numpy array to base64 output

Question

I basically need to do this but in Python instead of Javascript. I receive a base64 encoded string from a socketio connection, convert it to uint8 and work on it, then need to convert it to base64 string so I can send it back.

So, up to this point I've got this (I'm getting the data dictionary from the socketio server):

import pickle
import base64
from io import BytesIO
from PIL import Image
base64_image_string = data["image"]
image = Image.open(BytesIO(base64.b64decode(base64_image_string)))
img = np.array(image)

How do I reverse this process to get from img back to base64_image_string?

UPDATE:
I have solved this in the following manner (continuing from the code snippet above):

pil_img = Image.fromarray(img)
buff = BytesIO()
pil_img.save(buff, format="JPEG")
new_image_string = base64.b64encode(buff.getvalue()).decode("utf-8")

Somewhat confusingly, new_image_string is not identical to base64_image_string but the image rendered from new_image_string looks the same so I'm satisfied!

• MeadowMuffins: It seems that save to JPEG is a loss function. The then decoded image string is no longer equivalent to the original image.
• Hristo Vrigazov: @MeadowMuffins Just use another format that is lossless, for example PNG

Answer 1

I believe since numpy.arrays support the buffer protocol, you just need the following:

processed_string = base64.b64encode(img)

So, for example:

>>> encoded = b"aGVsbG8sIHdvcmxk"
>>> img = np.frombuffer(base64.b64decode(encoded), np.uint8)
>>> img
array([104, 101, 108, 108, 111, 44, 32, 119, 111, 114, 108, 100], dtype=uint8)
>>> img.tobytes()
b'hello, world'
>>> base64.b64encode(img)
b'aGVsbG8sIHdvcmxk'
>>>

• jtlz2: This is amazing! BUT, when I deserialize, my 3-D numpy array comes out as 1-D only - must I reshape using values for the original shape carried with the array, or is there a way that circumvents reshape? Thx!
• jtlz2: It's quite ugly but I ended up doing: payload = ('nparr',img.shape,base64.b64encode(img.copy(order='C'))) and deserializing correspondingly. Is there a way around this? Huge thanks!
• juanpa.arrivillaga: @jtlz2 no, but have you considered another serialization method like numpy.save?
• jtlz2: Thanks, I tried that route (see stackoverflow.com/a/43925741/1021819) - but in the end I thought it safer to use base64 over the wire than a byte string. Do you have a view on which is preferable?
• juanpa.arrivillaga: @jtlz2 sorry, but I dont really follow. Base64 produces a byte string. And it is safer in what sense? numpy.save is much much more portable across platforms, taking care of things like byte-order along with shape out if the box. If I was choosing with no arbitrary restrictions, I would undoubtedly use numpy.save over base64 encoding. It's probably faster, and definitely less memory intensive

Answer 2

I have the same problem. After some search and try, my final solution is almost the same as yours.

The only difference is that the base64 encoded string is png format data, so I need to change it from RGBA to RGB channels before converted to np.array:

image = image.convert ("RGB")
img = np.array(image)

In the reverse process, you treate the data as JPEG format, maybe this is the reason why new_image_string is not identical to base64_image_string ?

Answer 3

from http://www.programcreek.com/2013/09/convert-image-to-string-in-python/ :

import base64
with open("t.png", "rb") as imageFile:
 str = base64.b64encode(imageFile.read())
 print str

is binary read

https://docs.python.org/2/library/base64.html

• juanpa.arrivillaga: Wait, why would you have to convert the numpy array to utf-8?
• ralf htp: the base64 alphabet is "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=" Base64 ist ein Verfahren zur Kodierung von 8-Bit-Binärdaten (z. B. ausführbare Programme, ZIP-Dateien oder Bilder) this translates as Base 64 is a standard to encode 8-bit binary data (i.e. executables, ZIP files or images)
• juanpa.arrivillaga: ... yes, so what?
• juanpa.arrivillaga: it's an array of byes (uint8). See the example I posted. In any event, I'm not sure why you think converting to utf8 would help...
• ralf htp: ok nice i did not know that numpy arrays are structured on bytes because normally i use them with composed datatypes like float, integer,...