I have an image in bytes:
print(image_bytes)
b\'\\xff\\xd8\\xff\\xfe\\x00\\x10Lavc57.64.101\\x00\\xff\\xdb\\x00C\\x00\\x08\\x04\\x04\\x04\\x04
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]]]