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Disaster!

As you can see, the image isn't quite loaded correctly. The original:

The code:

import cv2
import imutils
a=imutils.url_to_image("https://www.google.com/images/branding/googlelogo/2x/googlelogo_color_272x92dp.png", readFlag=-1)
cv2.imshow("goog", a)
cv2.waitKey()

The implementation of url_to_image in imutils:

def url_to_image(url, readFlag=cv2.IMREAD_COLOR):
 # download the image, convert it to a NumPy array, and then read
 # it into OpenCV format
 resp = urlopen(url)
 image = np.asarray(bytearray(resp.read()), dtype="uint8")
 image = cv2.imdecode(image, readFlag)

 # return the image
 return image

I also tried readFlag=cv2.IMREAD_UNCHANGED, but that didn't do the trick either.

please send help

alright gang we did it

so I tried another version of displaying:

plt.figure("Correct")
plt.imshow(imutils.opencv2matplotlib(a))
plt.show()

No luck it would appear. But then, looking into the opencv2matplotlib source, we find:

def opencv2matplotlib(image):
 # OpenCV represents images in BGR order; however, Matplotlib
 # expects the image in RGB order, so simply convert from BGR
 # to RGB and return
 return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

Aha, but we have 4 channel color (alpha), so by common sense we need cv2.COLOR_BGRA2RGBA not cv2.COLOR_BGR2RGB!!

Testing this theory:

plt.figure("Correct")
plt.imshow(cv2.cvtColor(a, cv2.COLOR_BGRA2RGBA))
plt.show()

We get...

Whoop dee doop!

# import the necessary packages
import numpy as np
import urllib
import cv2

def url_to_image(url):
 # download the image, convert it to a NumPy array, and then read
 # it into OpenCV format
 resp = urllib.request.urlopen(url)
 image = np.asarray(bytearray(resp.read()), dtype="uint8")
 image = cv2.imdecode(image, cv2.IMREAD_COLOR)

 # return the image
 return image


# initialize the list of image URLs to download
url="http://i.dailymail.co.uk/i/pix/2015/09/01/18/2BE1E88B00000578-3218613-image-m-5_1441127035222.jpg"

print ("downloading %s" % (url))
image = url_to_image(url)
cv2.imshow("Image", image)
cv2.waitKey(0)

And the output is: