Python OpenCV load image from byte string

I think this answer provided on this stackoverflow question is a better answer for this question.

Quoting details (borrowed from @lamhoangtung from above linked answer)

import base64
import json
import cv2
import numpy as np

response = json.loads(open('./0.json', 'r').read())
string = response['img']
jpg_original = base64.b64decode(string)
jpg_as_np = np.frombuffer(jpg_original, dtype=np.uint8)
img = cv2.imdecode(jpg_as_np, flags=1)
cv2.imwrite('./0.jpg', img)

This is what I normally use to convert images stored in database to OpenCV images in Python.

import numpy as np
import cv2
from cv2 import cv

# Load image as string from file/database
fd = open('foo.jpg')
img_str = fd.read()
fd.close()

# CV2
nparr = np.fromstring(img_str, np.uint8)
img_np = cv2.imdecode(nparr, cv2.CV_LOAD_IMAGE_COLOR) # cv2.IMREAD_COLOR in OpenCV 3.1

# CV
img_ipl = cv.CreateImageHeader((img_np.shape[1], img_np.shape[0]), cv.IPL_DEPTH_8U, 3)
cv.SetData(img_ipl, img_np.tostring(), img_np.dtype.itemsize * 3 * img_np.shape[1])

# check types
print type(img_str)
print type(img_np)
print type(img_ipl)

I have added the conversion from numpy.ndarray to cv2.cv.iplimage, so the script above will print:

<type 'str'>
<type 'numpy.ndarray'>
<type 'cv2.cv.iplimage'>

EDIT: As of latest numpy 1.18.5 +, the np.fromstring raise a warning, hence np.frombuffer shall be used in that place.