Python - byte image to NumPy array using OpenCV

I searched all over the internet finally I solved:

NumPy array (cv2 image) - Convert

NumPy to bytes

and

bytes to NumPy

:.

#data = cv2 image array
def encodeImage(data):
    #resize inserted image
    data= cv2.resize(data, (480,270))
    # run a color convert:
    data= cv2.cvtColor(data, cv2.COLOR_BGR2RGB)
    return bytes(data) #encode Numpay to Bytes string



def decodeImage(data):
    #Gives us 1d array
    decoded = np.fromstring(data, dtype=np.uint8)
    #We have to convert it into (270, 480,3) in order to see as an image
    decoded = decoded.reshape((270, 480,3))
    return decoded;

# Load an color image
image= cv2.imread('messi5.jpg',1)

img_code = encodeImage(image) #Output: b'\xff\xd8\xff\xe0\x00\x10...';
img = decodeImage(img_code) #Output: normal array
cv2.imshow('image_deirvlon',img);
print(decoded.shape)

You can get full code from here

I created a 2x2 JPEG image to test this. The image has white, red, green and purple pixels. I used cv2.imdecode and numpy.frombuffer

import cv2
import numpy as np

f = open('image.jpg', 'rb')
image_bytes = f.read()  # b'\xff\xd8\xff\xe0\x00\x10...'

decoded = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), -1)

print('OpenCV:\n', decoded)

# your Pillow code
import io
from PIL import Image
image = np.array(Image.open(io.BytesIO(image_bytes))) 
print('PIL:\n', image)

This seems to work, although the channel order is BGR and not RGB as in PIL.Image. There are probably some flags you might use to tune this. Test results:

OpenCV:
 [[[255 254 255]
  [  0   0 254]]

 [[  1 255   0]
  [254   0 255]]]
PIL:
 [[[255 254 255]
  [254   0   0]]

 [[  0 255   1]
  [255   0 254]]]