The API documentation for cv2.waitKey() notes the following:

This function is the only method in HighGUI that can fetch and handle events, so it needs to be called periodically for normal event processing unless HighGUI is used within an environment that takes care of event processing.

So perhaps calling the function in an endless loop would make the window responsive? I haven't tested this, but maybe you would like to try the following:

import cv2


cvim2disp = cv2.imread('data/home.jpg')
cv2.imshow('img', cvim2disp)
while(True):
k = cv2.waitKey(33)
if k == -1:  # if no key was pressed, -1 is returned
continue
else:
break
cv2.destroyWindow('img')

I am not sure if you can open a window from Jupyter Notebook. cv2.imshow expects a waitKey which doesn't work in Jupyter.

Here is what I have done (using OpenCV 3.3):

from IPython.display import display, HTML
import cv2
import base64


def imshow(name, imageArray):
_, png = cv2.imencode('.png', imageArray)
encoded = base64.b64encode(png)
return HTML(data='''<img alt="{0}" src="data:image/png;base64, {1}"/>'''.format(name, encoded.decode('ascii')))


img = cv2.imread('./media/baboon.jpg',cv2.IMREAD_COLOR)
imshow('baboon', img)

If you don't need to use cv2, just:

from IPython.display import Image
Image('./media/baboon.jpg')

I was having a similar problem, and could not come to a good solution with cv2.imshow() in the Jupyter Notebook. I followed this stackoverflow answer, just using matplotlib to display the image.

import matplotlib.pyplot as plt
# load image using cv2....and do processing.
plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
# as opencv loads in BGR format by default, we want to show it in RGB.
plt.show()

This will help you understand what is happening:

import cv2
cvim2disp = cv2.imread('data/home.jpg')
cv2.imshow('HelloWorld', cvim2disp)
cv2.waitKey(0)
cv2.destroyWindow('HelloWorld')

waitKey(0) method is waiting for an input infinitely. When you see a frame of the corresponding image, do not try to close the image using close in top right corner.

Instead press some key. waitkey method will take that as an input and it will return back a value. Further you can also check which key was pressed to close the frame.

Additionally waitKey(33) will keep the frame active for 33 ms and then close it automatically.

destroyWindow() will destroy the current frame if there. destroyAllWindows() will destroy all the frames currently present.

This will solve.

%matplotlib inline
#The line above is necesary to show Matplotlib's plots inside a Jupyter Notebook


import cv2
from matplotlib import pyplot as plt


#Import image
image = cv2.imread("input_path")


#Show the image with matplotlib
plt.imshow(image)
plt.show()

The following code works fine in Jupyter to show one image

%matplotlib inline
import cv2
from matplotlib import pyplot as plt
cap = cv2.VideoCapture(videoFName)
ret, image = cap.read()
image=cv2.resize(image,None,fx=0.25,fy=0.25,interpolation=cv2.INTER_AREA)
plt.imshow(image)
plt.show()

If you want to show the video instead of an image in a separate window, use the following code:

import cv2
cap = cv2.VideoCapture(videoFName)
while cap.isOpened():
ret, image = cap.read()
image=cv2.resize(image,None,fx=0.25,fy=0.25,interpolation=cv2.INTER_AREA)
cv2.imshow('image',image)


k = cv2.waitKey(30) & 0xff # press ESC to exit
if k == 27 or cv2.getWindowProperty('image', 0)<0:
break
cv2.destroyAllWindows()
cap.release()

Make sure the window name match, otherwise it will not work. In this case I use 'image' as window name.

The new window that opens up from Jupyter uses the same kernel as notebook. Just add this below to the code and it would work fine.

cv2.waitKey(0)
cv2.destroyAllWindows()

image = cv2.imread(file_path)
while True:
# Press 'q' for exit
exit_key = ord('q')
if cv2.waitKey(exit_key) & 255 == exit_key:
cv2.destroyAllWindows()
break
cv2.imshow('Image_title', image)

if your facing problem in google collab ,you can use this patch

from google.colab.patches import cv2_imshow
cv2_imshow(img)

%matplotlib inline
from matplotlib import pyplot as plt


img = cv2.imread(valid_img_paths[1])
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.show()

I have just developed a library that is exactly similar to cv2.imshow and it can be used in both Jupyter and colab. It can update the window. Therefore you can easily see the video inside it. It uses HTML canvas and is browser friendly :)

Installation:

pip install opencv_jupyter_ui

Usage:

This is the replacement of cv2.imshow for Jupiter. you need only to replace cv2.imshow with jcv2.imshow. It will work in Jupiter.

First:

please import the library

import opencv_jupyter_ui as jcv2

Then:

change cv2.imshow ->jcv2.imshow

More details exist on the Github Repository. Binder Demo gif

It also supports jcv2.waitKey(100) and jcv2.destroyAllWindows(). In case of the absence of Jupyter, it fallbacks to original cv2 functionality. In order to change the default keys you can use jcv2.setKeys(['a','b','esc']). Please follow the document for more information