You can get a numpy array from you decoded data using:

import numpy as np
...
img = base64.b64decode(msg.payload)
npimg = np.fromstring(img, dtype=np.uint8)

Then you need imdecode to read the image from a buffer in memory. imread is meant to load an image from a file.

So:

import numpy as np
...
def on_message(client, userdata, msg): # msg.payload is incoming data
    img = base64.b64decode(msg.payload); 
    npimg = np.fromstring(img, dtype=np.uint8); 
    source = cv2.imdecode(npimg, 1)

I've been struggling with this issue for a while now and of course, once I post a question - I figure it out.

For my particular use case, I needed to convert the string into a PIL Image to use in another function before converting it to a numpy array to use in OpenCV. You may be thinking, "why convert to RGB?". I added this in because when converting from PIL Image -> Numpy array, OpenCV defaults to BGR for its images.

Anyways, here's my two helper functions which solved my own question:

import io
import cv2
import base64 
import numpy as np
from PIL import Image

# Take in base64 string and return PIL image
def stringToImage(base64_string):
    imgdata = base64.b64decode(base64_string)
    return Image.open(io.BytesIO(imgdata))

# convert PIL Image to an RGB image( technically a numpy array ) that's compatible with opencv
def toRGB(image):
    return cv2.cvtColor(np.array(image), cv2.COLOR_BGR2RGB)

This is my solution for python 3.7 without using PIL.

import base64

def readb64(uri):
   encoded_data = uri.split(',')[1]
   nparr = np.frombuffer(base64.b64decode(encoded_data), np.uint8)
   img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
   return img

I hope that this solutions works for all.

You do not need to save the buffer to a file. The following script captures an image from a webcam, encodes it as a JPG image, and then converts that data into a printable base64 encoding which can be used with your JSON:

import cv2
import base64

cap = cv2.VideoCapture(0)
retval, image = cap.read()
retval, buffer = cv2.imencode('.jpg', image)
jpg_as_text = base64.b64encode(buffer)
print(jpg_as_text)
cap.release()

Giving you something starting like:

/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGCAsICQoKCg

This could be extended to show how to convert it back to binary and then write the data to a test file to show that the conversion was successful:

import cv2
import base64

cap = cv2.VideoCapture(0)
retval, image = cap.read()
cap.release()

# Convert captured image to JPG
retval, buffer = cv2.imencode('.jpg', image)

# Convert to base64 encoding and show start of data
jpg_as_text = base64.b64encode(buffer)
print(jpg_as_text[:80])

# Convert back to binary
jpg_original = base64.b64decode(jpg_as_text)

# Write to a file to show conversion worked
with open('test.jpg', 'wb') as f_output:
    f_output.write(jpg_original)

To get the image back as an image buffer (rather than JPG format) try:

jpg_as_np = np.frombuffer(jpg_original, dtype=np.uint8)
image_buffer = cv2.imdecode(jpg_as_np, flags=1)